From ad2bc3b35388bfc7a67094517c5dcaaf3c0e0208 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 00:06:52 +0100 Subject: [PATCH 01/51] Added answers --- solution.ipynb | 64 ++++++++++++++++++++++++++++---------------------- 1 file changed, 36 insertions(+), 28 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index df4cbd2..cc2c611 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -48,7 +48,7 @@ "metadata": {}, "source": [ "### Acknowledgements\n", - "This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, and Caroline Malin-Mayor for DL@MBL 2023." + "This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, Caroline Malin-Mayor for DL@MBL 2023, and Anna Foix Romero for DL@MBL 2024." ] }, { @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 46, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 47, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 48, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 49, "metadata": { "tags": [] }, @@ -146,12 +146,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 50, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAACbCAYAAADC4/k2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAWbUlEQVR4nO3df2zU9R3H8XeLvQOkd+VH+ks46aITgagbobQTkc2qc1MDY3GLTnGaEdjBrHSTkUw2FO3ikqkwhGiwzRIVQybqzMIkRWrQVkMXdIh2bmO2C9wxlvUOGLTY++wP43f3+UCvd+33vvf93j0fyTf5vnvf7/XT66vHm+/3c99vkVJKCQAAgEOKcz0AAABQWGg+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo7LWfGzevFmmT58uY8eOlXnz5sm7776brW8FlyIDECEHIAM4V1E27u3y4osvyl133SVbt26VefPmyRNPPCE7duyQ7u5uKS8vT7lvIpGQI0eOSGlpqRQVFdk9NNhMKSUnTpyQ6upqKS7+fy87mgyIkAOvyUYOyIC38F6AoTIw1Ma2q62tVeFw2KoHBwdVdXW1am5uHnbf3t5eJSIsHlt6e3ttywA58O5iZw7IgDcX3gtYzAycj+2nXQYGBqSrq0saGhqsrxUXF0tDQ4N0dHScs31/f7/E43FrUdxk15NKS0ut9UwzIEIO8sVockAG8gPvBUjOwFBsbz6OHz8ug4ODUlFRoX29oqJCIpHIOds3NzdLMBi0llAoZPeQ4IDkw6GZZkCEHOSL0eSADOQH3guQzumxnH/aZe3atRKLxaylt7c310NCDpADkAGIkINCcYHdTzhlyhQZM2aMRKNR7evRaFQqKyvP2d7v94vf77d7GMihTDMgQg7yEe8F4L0AQ7H9yIfP55M5c+ZIW1ub9bVEIiFtbW1SX19v97eDC5EBiJADkAGkkNZ04wxt375d+f1+1draqg4dOqSWLVumysrKVCQSGXbfWCyW85m6LJkvsVjMtgyQA+8uduaADHhz4b2AxczA+WSl+VBKqU2bNqlQKKR8Pp+qra1VnZ2dae1H0Ly5nC9sI80AOfDuYmcOyIA3F94LWNJpPrJykbHRiMfjEgwGcz0MZCgWi0kgELDt+ciBN9mZAzLgTbwXIJ0M5PzTLgAAoLDQfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEddkOsBID0/+9nPtHr9+vVaXVys95ELFy7U6vb29qyMC85au3atVj/yyCNa/dhjj2n1T3/606yPCQAyxZEPAADgKJoPAADgKJoPAADgKOZ8uNjdd99tra9Zs0Z7LJFIpNxXKZWNISEHSktLrfVVq1Zpj5m/58bGRq3++OOPtXrbtm32Dg4ARoAjHwAAwFE0HwAAwFE0HwAAwFHM+XCxiy++2FofO3ZsDkcCJ11wgf5nuWLFCmu9oqIi5b7RaFSrOzo67BsYsqapqUmrfT6fVl9++eXW+h133JHyuT766COtnjVr1ihHB9iPIx8AAMBRNB8AAMBRNB8AAMBRzPlwkYaGBq02r+mQzDyve/PNN2u1ee4f3lFXV6fVzc3Nae+7fPlyrT506JAtY0Jmrr32Wq2ePXt2yscXL16s1UVFRUM+93DX8Ln00ku12szAzJkzU+4P9xgzZoxW19TUpL1vb2+vVvf399syJrtw5AMAADiK5gMAADiK5gMAADiKOR85NH/+fK1uaWnR6mAwOOS+v/rVr7T6k08+sW9gcNT06dO1euPGjWnv29bWptV79+61YUQQEamqqtLqF154Qau/8IUvDLmv+bd74YUXarU5p6Orq0urv/zlL6c9TlNxsf5/SvN754Nbb71Vq1999dUcjSS1QCCg1TfccINW33PPPVptXt+lpKREq6+55pq0v/e6deu0esOGDWnv6wSOfAAAAEdl3Hy8+eabcsstt0h1dbUUFRXJyy+/rD2ulJJ169ZJVVWVjBs3ThoaGs65sybyGxkAGYAIOcDQMm4+Tp06JVdeeaVs3rz5vI8/9thjsnHjRtm6dau88847cuGFF8qNN94oZ86cGfVg4Q1kAGQAIuQAQytSw31oPNXORUWyc+dOWbRokYh81uVWV1dLU1OT/PjHPxYRkVgsJhUVFdLa2irf/e53h33OeDyecq5DPnnmmWe02jz/l8w8l3/ddddlY0gjFovFJBAI2JIBkcLKwZ///GetTnUdhng8rtW33XabVu/evdu+gY1ALBaT0tJST2bAvM6O+fc5bdo0276Xeb+V48ePa/WUKVO0urq62lo354ZNnTo15fcyM3HTTTelPc6RcOK9YNy4cVp9+vRpewafhvLycq2+/vrrrfXLLrtMe8y8nstwczb+9Kc/afUrr7yi1cnXc5o7d27K5zIbvPHjx6fc3k6fZyAVW+d8HD58WCKRiPZHHAwGZd68eUPe4Kq/v1/i8bi2wLtGkgERcpBPyABEyAFSs7X5iEQiInLunTcrKiqsx0zNzc0SDAatxc7/XcB5I8mACDnIJ2QAIuQAqeX8o7Zr166V1atXW3U8Hs/bsJmHUs3TLIlEQqv7+vqsdbd9TMpuhZQDk3kIPtWZ0Keeekqrc32axU65zsADDzyg1Zl8b/PS1WvWrNHqzs5Ore7u7k75fP/+97+1+r777rPWhzvN8o9//EOr77zzzpTbu006OXDyNIvJPAU+Y8YMa938CLX5t2w+/tJLL2n1ihUrtPrYsWNa/c9//tNaN0+7mM/929/+1hy6q9h65KOyslJEzr2vSDQatR4z+f1+CQQC2gLvGkkGRMhBPiEDECEHSM3W5qOmpkYqKyu1Cx/F43F55513pL6+3s5vBZciAyADECEHSC3j0y4nT56Uv/71r1Z9+PBhOXDggEyaNElCoZA0NjbKhg0b5NJLL5Wamhp58MEHpbq62vpEDPLT+++/L6FQiAwUuN7eXpk1axYZKGC8FyAdGTcf+/fvl69+9atW/fm5uaVLl0pra6s88MADcurUKVm2bJn09fXJ/PnzZdeuXTJ27Fj7Ru0R5mWzf/e732W0/6ZNm6z1N954w44hZc0111xDBtL061//WquHO0+c/D/Hhx9+OHsDs8Gjjz4qzz33nCcyYF7quq6uLqP9e3p6rHVzXsVbb7018oGdx3DzPJKZH880P8abbfn+XmD+fSbPP3nvvfe0xx555BGtPnjwoFabt7035/395Cc/0epf/OIXQ47r73//u1avX79+yG3dIOPmY+HChSknxBUVFclDDz0kDz300KgGBm9J/lw3GShcW7ZsEREyUMh4L0A6uLcLAABwFM0HAABwVM6v85HPvv71r2v1FVdckXJ78/boTz75pO1jgvPM+yCZk+3M05jvv/++Vt9xxx3WOvfEsE9TU5NWD3f56bffflurk8+pj3aOx8SJE7XafO9YsGBB2uP6wx/+MKqxIDUzN8kfwEheH4lbb71Vq815G8lzZczruZi33Dh69OioxpJtHPkAAACOovkAAACOovkAAACOYs6Hjcxz+b/85S9Tbr9v3z6tXrp0qVbHYjFbxgVn1dbWarWZi1SXlhYRefrpp7X6X//6ly3jgs58nc17L5l/f7fffrtWp7o5WqaWL1+u1amu5/LBBx9o9W233Za1ceFcu3btsu25zOt4rFu3TqvN66EkXxfEvE6NOQfE7TjyAQAAHEXzAQAAHEXzAQAAHMWcj1EY7b1bzGvxm7eehjfdc889Wl1VVZVy+w8//FCrzXtzIDvMv9dM/35H45ZbbtFq81y/6dNPP7XWt27dqj3GHA/vMH/vGzZs0OqSkhKtNv+NWLVqlbU+2muK5BpHPgAAgKNoPgAAgKNoPgAAgKOY8zEKa9as0epEIpHR/sNdBwTe0NjYqNX33nuvVpv3bjFdf/31Wn3kyBFbxgX3evnll7V6uIz86Ec/stbN65PAvb75zW9q9XPPPafV5hyPnp4erTbv8eP1eR7JOPIBAAAcRfMBAAAcRfMBAAAcxZyPDF111VXWunlt/eGY12/o7u62Y0jIgWnTplnr5hyP4mK9px8cHNTqZ555RquZ45H/Hn30Ua02MzLcfLH29nbbxwT7mXM8zLk9Y8aM0eq//e1vWm3O//La/VoywZEPAADgKJoPAADgKE67ZOj111+31idOnJhy287OTq2+++67szEkOOCSSy7R6ldffdVav+yyy1Lu+/jjj2u1+RFt5B+fz6fVX/rSl7TaPM1iftT2vvvu0+qPP/7YxtHBTsmXTDc/SmueZkm1r0h+n2YxceQDAAA4iuYDAAA4iuYDAAA4ijkfGZo8ebK1PtzH45566imtPnnyZFbGhOwz53UMN88jWfL8EOSn8ePHa/X3vvc9rTY/Qml64YUXtNqcO5DprRuQPckfsxcR2bBhg7U+YcIE7bFjx45pdTgc1upCvtwCRz4AAICjMmo+mpubZe7cuVJaWirl5eWyaNGiczq3M2fOSDgclsmTJ8uECRNkyZIlEo1GbR003MecjU8OQAZABjCUjJqP9vZ2CYfD0tnZKbt375azZ8/KDTfcIKdOnbK2uf/+++X3v/+97NixQ9rb2+XIkSPyrW99y/aBw10WL15MDkAGQAaQlozmfOzatUurW1tbpby8XLq6umTBggUSi8Vk27Zt8vzzz8vXvvY1ERFpaWmRyy+/XDo7O6Wurs6+kTukpaVFq83LIqfy9ttv2z0c1+rt7c3rHEyaNCntbffu3avVhw4dsnk07nXgwAGpqqrKywyYSktLrXXzkvnf/va3U+57//33a/VvfvMbrfbyHI98y8CUKVO0+q233tLqqVOnWus9PT3aY0uXLtVqLpP/f6Oa8xGLxUTk/2/MXV1dcvbsWWloaLC2mTFjhoRCIeno6Djvc/T390s8HtcWeBM5wOcX3iMDhWs0GRAhB4VixM1HIpGQxsZGufrqq2X27NkiIhKJRMTn80lZWZm2bUVFhUQikfM+T3NzswSDQWsxZxLDG+rq6sgBZObMmSJCBgrZaDIgQg4KxYibj3A4LAcPHpTt27ePagBr166VWCxmLb29vaN6PuTGs88+O6r9yQHIAETIQaEY0XU+Vq5cKa+99pq8+eab2vmuyspKGRgYkL6+Pq3bjUajUllZed7n8vv94vf7RzKMrLjqqqu0OvmQoYh+LnZgYEB7bPPmzVpdSLO6L7roIms9H3Jgevjhh9PedsuWLVr9n//8x+7huF4+ZsCUnPnh5niYt07fuHFjVsbkJiPJgIj7cjBr1iytTv43T0Tk008/tdZvv/127bFCmveXqYyOfCilZOXKlbJz507Zs2eP1NTUaI/PmTNHSkpKpK2tzfpad3e39PT0SH19vT0jhuuRA5ABkAGkktGRj3A4LM8//7y88sorUlpaap23CwaDMm7cOAkGg3LvvffK6tWrZdKkSRIIBGTVqlVSX1/vmZnNGJloNColJSXkoMCdPn1aAoEAGShgZADpyOjIx5YtWyQWi8nChQulqqrKWl588UVrm8cff1xuvvlmWbJkiSxYsEAqKyvlpZdesn3gcJcvfvGL5ADa75gMFCYygHQUKaVUrgeRLB6PSzAYzNn3X7hwoVbv3r1bq5Ov83H48GHtsUsuuSRr43K7WCwmgUDAtufLdQ7M87zmtTuSr/uxfv167TFzfojL/sSyys4c5DoDphkzZmh1U1OTtf79739fe+wvf/mLVt90001a/cknn9g8OvfIt/eCK6+8Uqv37dun1cn/RnABtc+kkwHu7QIAABxF8wEAABxF8wEAABw1out8APnOnI2ffB8PU39/v1YX0hyPQvLggw9q9Xe+850ht920aZNW5/Mcj3z33nvvabU5H6yvr8/B0eQPjnwAAABH0XwAAABH0XwAAABHMefD8NFHH2m1eW3++fPnOzkc5Mi2bdu0et26dVo9fvx4a/2Pf/yjI2OCs8xz+6muW/D0009r9Z49e7IyJuReT09ProeQFzjyAQAAHEXzAQAAHMVpF8PnN8v73LXXXpujkcBNLr744lwPAQ676667tDrVJdKffPJJ7bHu7u7sDcxB5sfGi4qKcjQS5FI2csCRDwAA4CiaDwAA4CiaDwAA4CjmfADAebz++uta3dTUpNWrV6+21vNljoeJOR4QyU4OOPIBAAAcRfMBAAAcRfMBAAAcxZwPADiPtrY2rb7gAt4uAbtw5AMAADiK5gMAADjKdc2HeRlXeIPdvzdy4E12/t7IgDfxXoB0fmeuaz5OnDiR6yFgBOz+vZEDb7Lz90YGvIn3AqTzOytSLmsrE4mEHDlyRJRSEgqFpLe3VwKBQK6H5QnxeFymTZvm6GumlJITJ05IdXW1FBfb18uSg5HLlxyQgZHLlwyIfJaD7u5umTlzJhnIgNsz4Lrp28XFxTJ16lSJx+MiIhIIBAhbhpx+zYLBoO3PSQ5Gz+s5IAOj5/UMiHyWg4suukhEyMBIuDUDrjvtAgAA8hvNBwAAcJRrmw+/3y8///nPxe/353oonpGPr1k+/kzZlm+vWb79PE7It9cs334eJ7j9NXPdhFMAAJDfXHvkAwAA5CeaDwAA4CiaDwAA4CiaDwAA4CjXNh+bN2+W6dOny9ixY2XevHny7rvv5npIrtHc3Cxz586V0tJSKS8vl0WLFkl3d7e2zZkzZyQcDsvkyZNlwoQJsmTJEolGozka8ciQgaEVSgZEyMFQyABEPJwD5ULbt29XPp9PPfvss+qDDz5QP/jBD1RZWZmKRqO5Hpor3HjjjaqlpUUdPHhQHThwQH3jG99QoVBInTx50tpm+fLlatq0aaqtrU3t379f1dXVqa985Ss5HHVmyEBqhZABpchBKmSADCjl3Ry4svmora1V4XDYqgcHB1V1dbVqbm7O4ajc69ixY0pEVHt7u1JKqb6+PlVSUqJ27NhhbfPhhx8qEVEdHR25GmZGyEBm8jEDSpGDTJABKOWdHLjutMvAwIB0dXVJQ0OD9bXi4mJpaGiQjo6OHI7MvWKxmIiITJo0SUREurq65OzZs9prOGPGDAmFQp54DclA5vItAyLkIFNkACLeyYHrmo/jx4/L4OCgVFRUaF+vqKiQSCSSo1G5VyKRkMbGRrn66qtl9uzZIiISiUTE5/NJWVmZtq1XXkMykJl8zIAIOcgEGYCIt3LgurvaIjPhcFgOHjwo+/bty/VQkCNkAGQAIt7KgeuOfEyZMkXGjBlzzkzcaDQqlZWVORqVO61cuVJee+01eeONN2Tq1KnW1ysrK2VgYED6+vq07b3yGpKB9OVrBkTIQbrIAES8lwPXNR8+n0/mzJkjbW1t1tcSiYS0tbVJfX19DkfmHkopWblypezcuVP27NkjNTU12uNz5syRkpIS7TXs7u6Wnp4eT7yGZGB4+Z4BEXIwHDLgjZ8h2zybg5xNdU1h+/btyu/3q9bWVnXo0CG1bNkyVVZWpiKRSK6H5gorVqxQwWBQ7d27Vx09etRa/vvf/1rbLF++XIVCIbVnzx61f/9+VV9fr+rr63M46syQgdQKIQNKkYNUyAAZUMq7OXBl86GUUps2bVKhUEj5fD5VW1urOjs7cz0k1xCR8y4tLS3WNqdPn1Y//OEP1cSJE9X48ePV4sWL1dGjR3M36BEgA0MrlAwoRQ6GQgaglHdzUKSUUs4dZwEAAIXOdXM+AABAfqP5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjvofFL+F8lBZLZ4AAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -191,7 +191,9 @@ "source": [ "**1.1 Answer:**\n", "\n", - "Your answer here!" + "In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images.\n", + "\n", + "In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. " ] }, { @@ -228,7 +230,7 @@ "source": [ "**1.2 Answer**\n", "\n", - "Your answer here!" + "We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset." ] }, { @@ -416,7 +418,11 @@ "source": [ "**1.4 Answer**\n", "\n", - "Your answer here!" + "A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact.\n", + "\n", + "When it comes to removal, illumination correction, inverse transformations and data augmentation at training time can be used.\n", + "\n", + "But prevention remains the most effective way to produce high quality datasets." ] }, { @@ -466,7 +472,7 @@ "source": [ "**1.5 Answer:**\n", "\n", - "Your answer here!" + "The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying." ] }, { @@ -834,7 +840,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**2.1 Answer:**\n" + "**2.1 Answer:**\n", + "\n", + "As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify." ] }, { @@ -868,7 +876,7 @@ "source": [ "**2.2 Answer:**\n", "\n", - "Your answer here!" + "Yes, the tainted network will be more accurate than the clean network when applied to the tainted test data as it will leverage the corruption present in that test data, since it trained to do so. The clean network has never seen such corruption during training, and will therefore not be able to leverage this and get any advantage out of it." ] }, { @@ -902,7 +910,7 @@ "source": [ "**2.3 Answer:**\n", "\n", - "Your answer here!" + "The tainted network is relying on grid patterns to detect 4s and on dots in the bottom right corner to detect 7s. Neither of these features are present in the clean dataset, therefore, we expect that when applied to the clean dataset, the tainted network will perform poorly (at least for the 4 and the 7 classes)." ] }, { @@ -1154,7 +1162,7 @@ "source": [ "**3.1 Answer:**\n", "\n", - "Your answer here!" + "The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments)." ] }, { @@ -1189,7 +1197,7 @@ "source": [ "**3.2 Answer**\n", "\n", - "Your answer here!" + "The tainted model on tainted data is generally better than the clean model on clean data. Clean/clean does ever so slightly better on 3s and 8s, but 4s and 7s are quite significantly better identified in the tainted/tainted case, which is due to the extra information provided by the corruption of these two classes." ] }, { @@ -1223,7 +1231,7 @@ "source": [ "**3.3 Answer:**\n", "\n", - "Your answer here!" + "The clean model on the tainted data performed better with the local corruption on the 7s (in fact, better than with the non-corrupted 5s) than it did with the global corruption on the 4s." ] }, { @@ -1261,7 +1269,7 @@ "source": [ "**3.4 Answer:**\n", "\n", - "Your answer here!" + "The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data." ] }, { @@ -1469,7 +1477,7 @@ "source": [ "**4.1 Answer:**\n", "\n", - "Your answer here!" + "The clean model focus its attention to the 7 itself. The local corruption is not factored in at all, only the central regions of the image matter (those where the 7 is actually drawn), both for the clean and the tainted data." ] }, { @@ -1546,7 +1554,7 @@ "source": [ "**4.2 Answer:**\n", "\n", - "Your answer here!" + "The tainted model only focuses on the dot in the tainted 7. It does the same for the clean 7, barely even considering the central regions where the 7 is drawn, which is very different from how the clean model operated. Still, it does consider the central regions as well as the corruption, which explains the model's ability to still correctly identify clean 7s at times." ] }, { @@ -1646,7 +1654,7 @@ "source": [ "**4.3 Answer:**\n", "\n", - "Your answer here!" + "Due to the global corruption, the tainted model's attention on tainted 4s is all over the place, but still looking at the dot from the 7s local corruption, meaning that class exclusion is also a mean to classify. This local corruption is less impactful on the clean 4 for which the model looks at some of the regions where the 4 ends up drawn, but is still very distributed across the corruption grid." ] }, { @@ -1684,7 +1692,7 @@ "source": [ "**4.4 Answer:**\n", "\n", - "Your answer here!" + "The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally." ] }, { @@ -2400,7 +2408,7 @@ "source": [ "**5.1 Answer:**\n", "\n", - "Your answer here!" + "The denoising MNIST did relatively well considering it extracted images which allows a human to identify a digit when it wasn't necessarily obvious from the noisy image. It has however been trained to look for digits. Applying it to Fashion-MNIST will possibly sucessfully \"remove noise\", but recovering objects that it hasn't seen before may not work as well." ] }, { @@ -2575,7 +2583,7 @@ "source": [ "**5.2 Answer:**\n", "\n", - "Your answer here!" + "The \"noise\" is apparently gone, however, the objects are hardly recognizable. Some look like they have been reshaped like digits in the process." ] }, { @@ -2609,7 +2617,7 @@ "source": [ "**5.2 Answer:**\n", "\n", - "Your answer here!" + "If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells." ] }, { @@ -2677,9 +2685,9 @@ ], "metadata": { "kernelspec": { - "display_name": "07_failure_modes", + "display_name": "Python [conda env:07-failure-modes] *", "language": "python", - "name": "python3" + "name": "conda-env-07-failure-modes-py" }, "language_info": { "codemirror_mode": { @@ -2691,7 +2699,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.12.4" } }, "nbformat": 4, From d5ff5ce2367dda7e3bce4ce5b3d0dfb709522bad Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 00:08:34 +0100 Subject: [PATCH 02/51] more answers --- solution.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solution.ipynb b/solution.ipynb index cc2c611..7bfc3cc 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2617,7 +2617,7 @@ "source": [ "**5.2 Answer:**\n", "\n", - "If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells." + "If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being \"denoised\" away." ] }, { From 42311762e190b13f6b4fd74ae83ba96f7ee36d51 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 00:21:30 +0100 Subject: [PATCH 03/51] Added README --- README.md | 59 +++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 59 insertions(+) diff --git a/README.md b/README.md index 11e1791..3e348e0 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,64 @@ # Exercise 7: Failure Modes & Limits of Deep Learning +## Goal +In Exercise 7: Failure Modes and Limits of Deep Learning, we delve into understanding the limits and failure modes of neural networks, especially in the context of image classification. This exercise highlights how differences between tainted and clean training datasets as well as test datasets can affect the performance of neural networks in ways that we will try to understand. By tampering with image datasets and introducing extra visual information, the exercise aims to illustrate real-world scenarios where data collection inconsistencies can corrupt datasets. The goal is to investigate the internal reasoning of neural networks, and use tools like Integrated Gradients, which help in identifying crucial areas of an image that influence classification decisions. + +The exercise involves creating and training neural networks on both tainted and clean datasets, examining how these networks handle local and global data corruptions. We will visualize the network's performance through confusion matrices and interpret the attention maps generated by Integrated Gradients. Additionally, the exercise explores how denoising networks cope with domain changes by training a UNet model on noisy MNIST data and testing it on both similar and different datasets like FashionMNIST. Through these activities, participants are encouraged to think deeply about neural network behavior, discuss their findings in groups, and reflect on the impact of dataset inconsistencies on model performance. + +In a broader sense, this exercise helps participants recognize the importance of dataset quality and consistency in training robust neural networks. By exploring these failure modes, participants gain insights into the internal workings of neural networks and learn how to diagnose and mitigate potential issues. This understanding is crucial for developing more reliable machine learning models and ensuring their effective application in real-world scenarios where data inconsistencies are common. + + +## Methodology +1. **Data Preparation**: + - **Load Data**: Load the MNIST dataset for training and testing. + - **Create Tainted Dataset**: Make copies of the original datasets to create tainted versions. + - **Local Corruption**: Add a white pixel to images of the digit '7' in the tainted dataset. + - **Global Corruption**: Add a grid texture to images of the digit '4' in the tainted dataset. + +2. **Visualization**: + - Visualize examples of corrupted images to understand the modifications made. + +3. **Train Neural Networks**: + - **Define Models**: Create a dense neural network model for classification. + - **Initialize Models**: Set up clean and tainted models with identical initial weights for comparison. + - **Load Data**: Initialize data loaders for clean and tainted datasets. + - **Train Models**: Train both models on their respective datasets (clean and tainted). + +4. **Evaluate Performance**: + - **Loss Visualization**: Plot training loss for both clean and tainted models to compare performance. + - **Confusion Matrix**: Generate confusion matrices to analyze model performance on clean and tainted test sets. + +5. **Interpret Results**: + - **Integrated Gradients**: Use the Integrated Gradients method to visualize the important regions of the images that influence the model's decisions. + - **Visualize Attention**: Compare the attention maps for clean and tainted models on specific images. + +6. **Denoising Task**: + - **Add Noise**: Introduce noise to MNIST images to create a dataset for training a denoising model. + - **Define UNet Model**: Use a UNet model architecture for denoising. + - **Train Denoising Model**: Train the UNet model on the noisy MNIST dataset. + - **Evaluate on FashionMNIST**: Apply the trained denoising model to FashionMNIST data to see how it performs on unseen data. + +### Technology Used + +1. **Programming Language**: + - Python + +2. **Libraries and Tools**: + - **PyTorch**: For building and training neural networks. + - `torchvision`: For loading and transforming datasets. + - `torch.nn`: For defining neural network models. + - `torch.optim`: For optimization algorithms. + - **Matplotlib**: For visualizing images and plotting graphs. + - **Scipy**: For image manipulation (e.g., adding textures). + - **Numpy**: For numerical operations. + - **TQDM**: For displaying progress bars during training. + - **Captum**: For implementing Integrated Gradients and other interpretability methods. + - **Seaborn**: For creating confusion matrices. + +3. **Datasets**: + - **MNIST**: Handwritten digit dataset for training and testing classification models. + - **FashionMNIST**: Fashion item dataset for evaluating the denoising model on different data. + ## Setup Please run the setup script to create the environment for this exercise and download data. From baa9fa9f925c2124f0f55a727d1a5760ecdb1a7c Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 00:34:27 +0100 Subject: [PATCH 04/51] removed axis from images --- solution.ipynb | 200 ++++++++++++++++++++++++++----------------------- 1 file changed, 108 insertions(+), 92 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index 7bfc3cc..718cd07 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -146,12 +146,12 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 51, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAACbCAYAAADC4/k2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAWbUlEQVR4nO3df2zU9R3H8XeLvQOkd+VH+ks46aITgagbobQTkc2qc1MDY3GLTnGaEdjBrHSTkUw2FO3ikqkwhGiwzRIVQybqzMIkRWrQVkMXdIh2bmO2C9wxlvUOGLTY++wP43f3+UCvd+33vvf93j0fyTf5vnvf7/XT66vHm+/3c99vkVJKCQAAgEOKcz0AAABQWGg+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo2g+AACAo7LWfGzevFmmT58uY8eOlXnz5sm7776brW8FlyIDECEHIAM4V1E27u3y4osvyl133SVbt26VefPmyRNPPCE7duyQ7u5uKS8vT7lvIpGQI0eOSGlpqRQVFdk9NNhMKSUnTpyQ6upqKS7+fy87mgyIkAOvyUYOyIC38F6AoTIw1Ma2q62tVeFw2KoHBwdVdXW1am5uHnbf3t5eJSIsHlt6e3ttywA58O5iZw7IgDcX3gtYzAycj+2nXQYGBqSrq0saGhqsrxUXF0tDQ4N0dHScs31/f7/E43FrUdxk15NKS0ut9UwzIEIO8sVockAG8gPvBUjOwFBsbz6OHz8ug4ODUlFRoX29oqJCIpHIOds3NzdLMBi0llAoZPeQ4IDkw6GZZkCEHOSL0eSADOQH3guQzumxnH/aZe3atRKLxaylt7c310NCDpADkAGIkINCcYHdTzhlyhQZM2aMRKNR7evRaFQqKyvP2d7v94vf77d7GMihTDMgQg7yEe8F4L0AQ7H9yIfP55M5c+ZIW1ub9bVEIiFtbW1SX19v97eDC5EBiJADkAGkkNZ04wxt375d+f1+1draqg4dOqSWLVumysrKVCQSGXbfWCyW85m6LJkvsVjMtgyQA+8uduaADHhz4b2AxczA+WSl+VBKqU2bNqlQKKR8Pp+qra1VnZ2dae1H0Ly5nC9sI80AOfDuYmcOyIA3F94LWNJpPrJykbHRiMfjEgwGcz0MZCgWi0kgELDt+ciBN9mZAzLgTbwXIJ0M5PzTLgAAoLDQfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEfRfAAAAEddkOsBID0/+9nPtHr9+vVaXVys95ELFy7U6vb29qyMC85au3atVj/yyCNa/dhjj2n1T3/606yPCQAyxZEPAADgKJoPAADgKJoPAADgKOZ8uNjdd99tra9Zs0Z7LJFIpNxXKZWNISEHSktLrfVVq1Zpj5m/58bGRq3++OOPtXrbtm32Dg4ARoAjHwAAwFE0HwAAwFE0HwAAwFHM+XCxiy++2FofO3ZsDkcCJ11wgf5nuWLFCmu9oqIi5b7RaFSrOzo67BsYsqapqUmrfT6fVl9++eXW+h133JHyuT766COtnjVr1ihHB9iPIx8AAMBRNB8AAMBRNB8AAMBRzPlwkYaGBq02r+mQzDyve/PNN2u1ee4f3lFXV6fVzc3Nae+7fPlyrT506JAtY0Jmrr32Wq2ePXt2yscXL16s1UVFRUM+93DX8Ln00ku12szAzJkzU+4P9xgzZoxW19TUpL1vb2+vVvf399syJrtw5AMAADiK5gMAADiK5gMAADiKOR85NH/+fK1uaWnR6mAwOOS+v/rVr7T6k08+sW9gcNT06dO1euPGjWnv29bWptV79+61YUQQEamqqtLqF154Qau/8IUvDLmv+bd74YUXarU5p6Orq0urv/zlL6c9TlNxsf5/SvN754Nbb71Vq1999dUcjSS1QCCg1TfccINW33PPPVptXt+lpKREq6+55pq0v/e6deu0esOGDWnv6wSOfAAAAEdl3Hy8+eabcsstt0h1dbUUFRXJyy+/rD2ulJJ169ZJVVWVjBs3ThoaGs65sybyGxkAGYAIOcDQMm4+Tp06JVdeeaVs3rz5vI8/9thjsnHjRtm6dau88847cuGFF8qNN94oZ86cGfVg4Q1kAGQAIuQAQytSw31oPNXORUWyc+dOWbRokYh81uVWV1dLU1OT/PjHPxYRkVgsJhUVFdLa2irf/e53h33OeDyecq5DPnnmmWe02jz/l8w8l3/ddddlY0gjFovFJBAI2JIBkcLKwZ///GetTnUdhng8rtW33XabVu/evdu+gY1ALBaT0tJST2bAvM6O+fc5bdo0276Xeb+V48ePa/WUKVO0urq62lo354ZNnTo15fcyM3HTTTelPc6RcOK9YNy4cVp9+vRpewafhvLycq2+/vrrrfXLLrtMe8y8nstwczb+9Kc/afUrr7yi1cnXc5o7d27K5zIbvPHjx6fc3k6fZyAVW+d8HD58WCKRiPZHHAwGZd68eUPe4Kq/v1/i8bi2wLtGkgERcpBPyABEyAFSs7X5iEQiInLunTcrKiqsx0zNzc0SDAatxc7/XcB5I8mACDnIJ2QAIuQAqeX8o7Zr166V1atXW3U8Hs/bsJmHUs3TLIlEQqv7+vqsdbd9TMpuhZQDk3kIPtWZ0Keeekqrc32axU65zsADDzyg1Zl8b/PS1WvWrNHqzs5Ore7u7k75fP/+97+1+r777rPWhzvN8o9//EOr77zzzpTbu006OXDyNIvJPAU+Y8YMa938CLX5t2w+/tJLL2n1ihUrtPrYsWNa/c9//tNaN0+7mM/929/+1hy6q9h65KOyslJEzr2vSDQatR4z+f1+CQQC2gLvGkkGRMhBPiEDECEHSM3W5qOmpkYqKyu1Cx/F43F55513pL6+3s5vBZciAyADECEHSC3j0y4nT56Uv/71r1Z9+PBhOXDggEyaNElCoZA0NjbKhg0b5NJLL5Wamhp58MEHpbq62vpEDPLT+++/L6FQiAwUuN7eXpk1axYZKGC8FyAdGTcf+/fvl69+9atW/fm5uaVLl0pra6s88MADcurUKVm2bJn09fXJ/PnzZdeuXTJ27Fj7Ru0R5mWzf/e732W0/6ZNm6z1N954w44hZc0111xDBtL061//WquHO0+c/D/Hhx9+OHsDs8Gjjz4qzz33nCcyYF7quq6uLqP9e3p6rHVzXsVbb7018oGdx3DzPJKZH880P8abbfn+XmD+fSbPP3nvvfe0xx555BGtPnjwoFabt7035/395Cc/0epf/OIXQ47r73//u1avX79+yG3dIOPmY+HChSknxBUVFclDDz0kDz300KgGBm9J/lw3GShcW7ZsEREyUMh4L0A6uLcLAABwFM0HAABwVM6v85HPvv71r2v1FVdckXJ78/boTz75pO1jgvPM+yCZk+3M05jvv/++Vt9xxx3WOvfEsE9TU5NWD3f56bffflurk8+pj3aOx8SJE7XafO9YsGBB2uP6wx/+MKqxIDUzN8kfwEheH4lbb71Vq815G8lzZczruZi33Dh69OioxpJtHPkAAACOovkAAACOovkAAACOYs6Hjcxz+b/85S9Tbr9v3z6tXrp0qVbHYjFbxgVn1dbWarWZi1SXlhYRefrpp7X6X//6ly3jgs58nc17L5l/f7fffrtWp7o5WqaWL1+u1amu5/LBBx9o9W233Za1ceFcu3btsu25zOt4rFu3TqvN66EkXxfEvE6NOQfE7TjyAQAAHEXzAQAAHEXzAQAAHMWcj1EY7b1bzGvxm7eehjfdc889Wl1VVZVy+w8//FCrzXtzIDvMv9dM/35H45ZbbtFq81y/6dNPP7XWt27dqj3GHA/vMH/vGzZs0OqSkhKtNv+NWLVqlbU+2muK5BpHPgAAgKNoPgAAgKNoPgAAgKOY8zEKa9as0epEIpHR/sNdBwTe0NjYqNX33nuvVpv3bjFdf/31Wn3kyBFbxgX3evnll7V6uIz86Ec/stbN65PAvb75zW9q9XPPPafV5hyPnp4erTbv8eP1eR7JOPIBAAAcRfMBAAAcRfMBAAAcxZyPDF111VXWunlt/eGY12/o7u62Y0jIgWnTplnr5hyP4mK9px8cHNTqZ555RquZ45H/Hn30Ua02MzLcfLH29nbbxwT7mXM8zLk9Y8aM0eq//e1vWm3O//La/VoywZEPAADgKJoPAADgKE67ZOj111+31idOnJhy287OTq2+++67szEkOOCSSy7R6ldffdVav+yyy1Lu+/jjj2u1+RFt5B+fz6fVX/rSl7TaPM1iftT2vvvu0+qPP/7YxtHBTsmXTDc/SmueZkm1r0h+n2YxceQDAAA4iuYDAAA4iuYDAAA4ijkfGZo8ebK1PtzH45566imtPnnyZFbGhOwz53UMN88jWfL8EOSn8ePHa/X3vvc9rTY/Qml64YUXtNqcO5DprRuQPckfsxcR2bBhg7U+YcIE7bFjx45pdTgc1upCvtwCRz4AAICjMmo+mpubZe7cuVJaWirl5eWyaNGiczq3M2fOSDgclsmTJ8uECRNkyZIlEo1GbR003MecjU8OQAZABjCUjJqP9vZ2CYfD0tnZKbt375azZ8/KDTfcIKdOnbK2uf/+++X3v/+97NixQ9rb2+XIkSPyrW99y/aBw10WL15MDkAGQAaQlozmfOzatUurW1tbpby8XLq6umTBggUSi8Vk27Zt8vzzz8vXvvY1ERFpaWmRyy+/XDo7O6Wurs6+kTukpaVFq83LIqfy9ttv2z0c1+rt7c3rHEyaNCntbffu3avVhw4dsnk07nXgwAGpqqrKywyYSktLrXXzkvnf/va3U+57//33a/VvfvMbrfbyHI98y8CUKVO0+q233tLqqVOnWus9PT3aY0uXLtVqLpP/f6Oa8xGLxUTk/2/MXV1dcvbsWWloaLC2mTFjhoRCIeno6Djvc/T390s8HtcWeBM5wOcX3iMDhWs0GRAhB4VixM1HIpGQxsZGufrqq2X27NkiIhKJRMTn80lZWZm2bUVFhUQikfM+T3NzswSDQWsxZxLDG+rq6sgBZObMmSJCBgrZaDIgQg4KxYibj3A4LAcPHpTt27ePagBr166VWCxmLb29vaN6PuTGs88+O6r9yQHIAETIQaEY0XU+Vq5cKa+99pq8+eab2vmuyspKGRgYkL6+Pq3bjUajUllZed7n8vv94vf7RzKMrLjqqqu0OvmQoYh+LnZgYEB7bPPmzVpdSLO6L7roIms9H3Jgevjhh9PedsuWLVr9n//8x+7huF4+ZsCUnPnh5niYt07fuHFjVsbkJiPJgIj7cjBr1iytTv43T0Tk008/tdZvv/127bFCmveXqYyOfCilZOXKlbJz507Zs2eP1NTUaI/PmTNHSkpKpK2tzfpad3e39PT0SH19vT0jhuuRA5ABkAGkktGRj3A4LM8//7y88sorUlpaap23CwaDMm7cOAkGg3LvvffK6tWrZdKkSRIIBGTVqlVSX1/vmZnNGJloNColJSXkoMCdPn1aAoEAGShgZADpyOjIx5YtWyQWi8nChQulqqrKWl588UVrm8cff1xuvvlmWbJkiSxYsEAqKyvlpZdesn3gcJcvfvGL5ADa75gMFCYygHQUKaVUrgeRLB6PSzAYzNn3X7hwoVbv3r1bq5Ov83H48GHtsUsuuSRr43K7WCwmgUDAtufLdQ7M87zmtTuSr/uxfv167TFzfojL/sSyys4c5DoDphkzZmh1U1OTtf79739fe+wvf/mLVt90001a/cknn9g8OvfIt/eCK6+8Uqv37dun1cn/RnABtc+kkwHu7QIAABxF8wEAABxF8wEAABw1out8APnOnI2ffB8PU39/v1YX0hyPQvLggw9q9Xe+850ht920aZNW5/Mcj3z33nvvabU5H6yvr8/B0eQPjnwAAABH0XwAAABH0XwAAABHMefD8NFHH2m1eW3++fPnOzkc5Mi2bdu0et26dVo9fvx4a/2Pf/yjI2OCs8xz+6muW/D0009r9Z49e7IyJuReT09ProeQFzjyAQAAHEXzAQAAHMVpF8PnN8v73LXXXpujkcBNLr744lwPAQ676667tDrVJdKffPJJ7bHu7u7sDcxB5sfGi4qKcjQS5FI2csCRDwAA4CiaDwAA4CiaDwAA4CjmfADAebz++uta3dTUpNWrV6+21vNljoeJOR4QyU4OOPIBAAAcRfMBAAAcRfMBAAAcxZwPADiPtrY2rb7gAt4uAbtw5AMAADiK5gMAADjKdc2HeRlXeIPdvzdy4E12/t7IgDfxXoB0fmeuaz5OnDiR6yFgBOz+vZEDb7Lz90YGvIn3AqTzOytSLmsrE4mEHDlyRJRSEgqFpLe3VwKBQK6H5QnxeFymTZvm6GumlJITJ05IdXW1FBfb18uSg5HLlxyQgZHLlwyIfJaD7u5umTlzJhnIgNsz4Lrp28XFxTJ16lSJx+MiIhIIBAhbhpx+zYLBoO3PSQ5Gz+s5IAOj5/UMiHyWg4suukhEyMBIuDUDrjvtAgAA8hvNBwAAcJRrmw+/3y8///nPxe/353oonpGPr1k+/kzZlm+vWb79PE7It9cs334eJ7j9NXPdhFMAAJDfXHvkAwAA5CeaDwAA4CiaDwAA4CiaDwAA4CjXNh+bN2+W6dOny9ixY2XevHny7rvv5npIrtHc3Cxz586V0tJSKS8vl0WLFkl3d7e2zZkzZyQcDsvkyZNlwoQJsmTJEolGozka8ciQgaEVSgZEyMFQyABEPJwD5ULbt29XPp9PPfvss+qDDz5QP/jBD1RZWZmKRqO5Hpor3HjjjaqlpUUdPHhQHThwQH3jG99QoVBInTx50tpm+fLlatq0aaqtrU3t379f1dXVqa985Ss5HHVmyEBqhZABpchBKmSADCjl3Ry4svmora1V4XDYqgcHB1V1dbVqbm7O4ajc69ixY0pEVHt7u1JKqb6+PlVSUqJ27NhhbfPhhx8qEVEdHR25GmZGyEBm8jEDSpGDTJABKOWdHLjutMvAwIB0dXVJQ0OD9bXi4mJpaGiQjo6OHI7MvWKxmIiITJo0SUREurq65OzZs9prOGPGDAmFQp54DclA5vItAyLkIFNkACLeyYHrmo/jx4/L4OCgVFRUaF+vqKiQSCSSo1G5VyKRkMbGRrn66qtl9uzZIiISiUTE5/NJWVmZtq1XXkMykJl8zIAIOcgEGYCIt3LgurvaIjPhcFgOHjwo+/bty/VQkCNkAGQAIt7KgeuOfEyZMkXGjBlzzkzcaDQqlZWVORqVO61cuVJee+01eeONN2Tq1KnW1ysrK2VgYED6+vq07b3yGpKB9OVrBkTIQbrIAES8lwPXNR8+n0/mzJkjbW1t1tcSiYS0tbVJfX19DkfmHkopWblypezcuVP27NkjNTU12uNz5syRkpIS7TXs7u6Wnp4eT7yGZGB4+Z4BEXIwHDLgjZ8h2zybg5xNdU1h+/btyu/3q9bWVnXo0CG1bNkyVVZWpiKRSK6H5gorVqxQwWBQ7d27Vx09etRa/vvf/1rbLF++XIVCIbVnzx61f/9+VV9fr+rr63M46syQgdQKIQNKkYNUyAAZUMq7OXBl86GUUps2bVKhUEj5fD5VW1urOjs7cz0k1xCR8y4tLS3WNqdPn1Y//OEP1cSJE9X48ePV4sWL1dGjR3M36BEgA0MrlAwoRQ6GQgaglHdzUKSUUs4dZwEAAIXOdXM+AABAfqP5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjqL5AAAAjvofFL+F8lBZLZ4AAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -164,12 +164,16 @@ "import matplotlib.pyplot as plt\n", "\n", "plt.subplot(1,4,1)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[3][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,2)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[23][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,3)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[15][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,4)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[29][0][0], cmap=plt.get_cmap('gray'))\n", "plt.show()" ] @@ -273,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 55, "metadata": {}, "outputs": [], "source": [ @@ -292,22 +296,22 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -323,6 +327,7 @@ "texture = convolve(texture, weights=[[0.5,1,0.5],[1,0.1,0.5],[1,0.5,0]])\n", "texture = torch.from_numpy(texture)\n", "\n", + "plt.axis('off')\n", "plt.imshow(texture, cmap=plt.get_cmap('gray'))" ] }, @@ -336,7 +341,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 57, "metadata": { "tags": [] }, @@ -358,7 +363,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ @@ -373,12 +378,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 59, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -390,12 +395,16 @@ "source": [ "# visualize example 4s\n", "plt.subplot(1,4,1)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[9][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,2)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[26][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,3)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[20][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,4)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[53][0][0], cmap=plt.get_cmap('gray'))\n", "plt.show()" ] @@ -528,7 +537,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 60, "metadata": { "tags": [] }, @@ -565,7 +574,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 61, "metadata": {}, "outputs": [], "source": [ @@ -598,7 +607,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 62, "metadata": {}, "outputs": [], "source": [ @@ -624,7 +633,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 63, "metadata": {}, "outputs": [ { @@ -638,7 +647,7 @@ ")" ] }, - "execution_count": 14, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" } @@ -673,7 +682,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ @@ -695,7 +704,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 65, "metadata": { "tags": [] }, @@ -703,7 +712,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0f494da788b94919b30ffad44c758241", + "model_id": "996b2277ba244ab096d8643e29e09afa", "version_major": 2, "version_minor": 0 }, @@ -717,7 +726,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1bb8bb8e66fb4e1682a7cf12c5e384d7", + "model_id": "c831693f101540e6ab8dda9eab628212", "version_major": 2, "version_minor": 0 }, @@ -731,7 +740,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6f97e83e8fec4c87829ca65c79d3593e", + "model_id": "8591952230944c349a220a18d782c791", "version_major": 2, "version_minor": 0 }, @@ -745,7 +754,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "868411117d724ac3854f05dba5e01304", + "model_id": "fd4b1b01a931403089d03c5744b5d83d", "version_major": 2, "version_minor": 0 }, @@ -791,7 +800,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 66, "metadata": {}, "outputs": [ { @@ -800,13 +809,13 @@ "Text(0, 0.5, 'negative log likelihood loss')" ] }, - "execution_count": 17, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -967,7 +976,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 67, "metadata": {}, "outputs": [], "source": [ @@ -997,7 +1006,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 68, "metadata": { "tags": [] }, @@ -1019,7 +1028,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 69, "metadata": {}, "outputs": [], "source": [ @@ -1080,26 +1089,26 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 70, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_18547/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_18547/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_18547/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_18547/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1109,7 +1118,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1119,7 +1128,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1129,7 +1138,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxMAAANXCAYAAABOkwIqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzddViUWRvA4d/AAAImJSACCga2i7F2u8ba3a6t2LkWoqtid7uuHWvX6trdLYqAlC2IgQrS8/3B7iwjoMgnDMpzX9dcOuc974lh6pkTr0KlUqkQQgghhBBCiC+ko+0GCCGEEEIIIb5NEkwIIYQQQgghUkWCCSGEEEIIIUSqSDAhhBBCCCGESBUJJoQQQgghhBCpIsGEEEIIIYQQIlUkmBBCCCGEEEKkigQTQgghhBBCiFSRYEIIIYQQQgiRKhJMCJHJVa9enerVq2u7GYkoFArc3Ny03Yxk/T+Pm729PV27dv2q7dE2Nzc3FAqFtpuRSEZ9fgshxPdCggkhvkEKhSJFt5MnT6ZpOzZt2sS8efPStI5PCQwMVPd18uTJSebp0KEDCoWCrFmzpnPrMr7q1aun6HmU1kHd+fPncXNz482bN2laz6fY29ur+6ujo0POnDkpXrw4vXr14tKlS/9X2VOnTmX37t1fp6FCCJHBKLXdACHEl1u/fr3G/XXr1nHkyJFE6U5OTp8t6/Dhw6lux6ZNm7hz5w6DBw9OdRlfQ5YsWdi8eTPjxo3TSA8LC2PPnj1kyZJFSy3L2MaOHUuPHj3U969cucKCBQsYM2aMxnOnRIkSny1r3Lhx/Prrr6lqx/nz55k4cSJdu3YlZ86cqSrjayhVqhTDhg0D4N27d9y7d49t27axcuVKhgwZwpw5c1JV7tSpU2nZsiVNmzb9iq0VQoiMQYIJIb5BHTt21Lh/8eJFjhw5kig9JfT19b9Ws7SmQYMG7Ny5k1u3blGyZEl1+p49e4iKiqJevXocP35ciy3MmOrUqaNxP0uWLCxYsIA6dep88dQgpVKJUvltf6TkyZMn0Wto+vTptG/fnrlz51KgQAH69u2rpdYJIUTGJNOchPhOrV69mpo1a2JhYYGBgQFFihRh6dKlifJ9PKf85MmTKBQKtm7dypQpU7CxsSFLlizUqlULX19fjfP++usvHjx4oJ4eYm9vrz4eGRnJhAkTcHR0xMDAgLx58zJy5EgiIyM16o+MjGTIkCGYm5uTLVs2GjduzOPHj7+orxUqVCBfvnxs2rRJI33jxo3Uq1cPExOTJM9bsmQJRYsWxcDAAGtra1xcXJKcarNixQocHBwwNDSkXLlynDlzJsnyUtrnlAoLC2PYsGHkzZsXAwMDChUqxKxZs1CpVBr5FAoF/fv3Z/fu3RQrVgwDAwOKFi3K33//nap6Ezpz5gytWrXC1tZW3achQ4bw4cMHjXxJrZlISbvc3NwYMWIEAPny5VM/lwIDA9V5NmzYgLOzM4aGhpiYmNC2bVsePXqUqK0p/Tt9CUNDQ9avX4+JiQlTpkzReOxnzZpFxYoVMTU1xdDQEGdnZ7Zv357oMQgLC2Pt2rXqvv27XubBgwf069ePQoUKYWhoiKmpKa1atdLouxBCZHTf9s9IQohkLV26lKJFi9K4cWOUSiX79u2jX79+xMXF4eLi8tnzp02bho6ODsOHDyc0NJQZM2bQoUMH9fzxsWPHEhoayuPHj5k7dy6Ael1CXFwcjRs35uzZs/Tq1QsnJyc8PDyYO3cuPj4+GvPHe/TowYYNG2jfvj0VK1bk+PHjNGzY8Iv7265dOzZs2MC0adNQKBSEhIRw+PBh1q9fn+SXajc3NyZOnEjt2rXp27cv3t7eLF26lCtXrnDu3Dn09PQAWLVqFb1796ZixYoMHjwYf39/GjdujImJCXnz5lWX9yV9TgmVSkXjxo05ceIE3bt3p1SpUhw6dIgRI0bw5MkT9WP+r7Nnz7Jz50769etHtmzZWLBgAS1atODhw4eYmpp+8eP5r23bthEeHk7fvn0xNTXl8uXLLFy4kMePH7Nt27bPnv+5djVv3hwfHx82b97M3LlzMTMzA8Dc3ByAKVOmMH78eFq3bk2PHj148eIFCxcupGrVqty4cUM9LSqlf6fUyJo1K82aNWPVqlV4enpStGhRAObPn0/jxo3p0KEDUVFRbNmyhVatWrF//371c3j9+vX06NGDcuXK0atXLwAcHByA+Gll58+fp23bttjY2BAYGMjSpUupXr06np6eGBkZ/V/tFkKIdKESQnzzXFxcVB+/nMPDwxPl++mnn1T58+fXSKtWrZqqWrVq6vsnTpxQASonJydVZGSkOn3+/PkqQOXh4aFOa9iwocrOzi5RPevXr1fp6Oiozpw5o5G+bNkyFaA6d+6cSqVSqW7evKkCVP369dPI1759exWgmjBhwif7HRAQoAJUM2fOVN25c0cFqOtcvHixKmvWrKqwsDBVly5dVMbGxurzgoODVfr6+qq6deuqYmNj1emLFi1SAao//vhDpVKpVFFRUSoLCwtVqVKlNB6LFStWqACNxy2lfVapVCo7OztVly5dPtm33bt3qwDV5MmTNdJbtmypUigUKl9fX3UaoNLX19dIu3XrlgpQLVy48JP1JLRt2zYVoDpx4oQ6Lannkbu7u0qhUKgePHigTpswYUKi52BK2zVz5kwVoAoICNA4PzAwUKWrq6uaMmWKRrqHh4dKqVSq07/k75QcOzs7VcOGDZM9PnfuXBWg2rNnjzrt48cmKipKVaxYMVXNmjU10o2NjZP8eyf12F64cEEFqNatW/fZNgshREYg05yE+E4ZGhqq/x8aGkpISAjVqlXD39+f0NDQz57/yy+/aKynqFKlCgD+/v6fPXfbtm04OTlRuHBhQkJC1LeaNWsCcOLECQAOHDgAwMCBAzXOT82C7qJFi1KiRAk2b94MxC8Ob9KkSZK/7h49epSoqCgGDx6Mjs5/b4M9e/Yke/bs/PXXXwBcvXqV4OBg+vTpo/FYdO3alRw5cqSqzyl14MABdHV1Ez02w4YNQ6VScfDgQY302rVrq3/xhvhF09mzZ0/R3+tTEj6PwsLCCAkJoWLFiqhUKm7cuPHZ8/+fdu3cuZO4uDhat26t8ZhaWlpSoEAB9WP6JX+n1Pp31O3du3fqtISPzevXrwkNDaVKlSpcv349RWUmPD86OpqXL1/i6OhIzpw5U1yGEEJom0xzEuI7de7cOSZMmMCFCxcIDw/XOBYaGvrZL1m2trYa93PlygXEf2n6nPv373Pv3j31VJWPBQcHA/FzxnV0dDS+bAIUKlTos3UkpX379syePZshQ4Zw/vx5xowZk2S+Bw8eJFmPvr4++fPnVx//998CBQpo5NPT0yN//vwaaSntc0o9ePAAa2trsmXLppH+7y5L/7btXx//vSD+b5aSv9enPHz4EFdXV/bu3ZuorJQEpf9Pu+7fv49KpUr0+P/r36loX/J3Sq33798DaPw99u/fz+TJk7l586bGupiUXm/jw4cPuLu7s3r1ap48eaKxHiMlj60QQmQEEkwI8R3y8/OjVq1aFC5cmDlz5pA3b1709fU5cOAAc+fOJS4u7rNl6OrqJpmu+mjxb1Li4uIoXrx4sltp/r9z2JPTrl07Ro8eTc+ePTE1NaVu3bppUk9StNXnf/0/f6/kxMbGUqdOHV69esWoUaMoXLgwxsbGPHnyhK5du6bL80ihUHDw4MEky0nPa4fcuXMHAEdHRyB+YXrjxo2pWrUqS5YswcrKCj09PVavXp1oI4DkDBgwgNWrVzN48GAqVKhAjhw5UCgUtG3bNkWPrRBCZAQSTAjxHdq3bx+RkZHs3btX45fhL51q8znJ/QLr4ODArVu3qFWr1id/pbWzsyMuLg4/Pz+NUQJvb+9UtcfW1pZKlSpx8uRJ+vbtm+xWpXZ2dup6Ev5yHRUVRUBAALVr19bId//+ffV0JYifkhIQEKCxDW1K+5xSdnZ2HD16lHfv3mn8Gu7l5aXRtrTk4eGBj48Pa9eupXPnzur0I0eOfNV6PvU8UqlU5MuXj4IFCyZ7/pf8nVLj/fv37Nq1i7x586pHhnbs2EGWLFk4dOgQBgYG6ryrV69OdH5y/du+fTtdunRh9uzZ6rSIiAitXrxPCCG+lKyZEOI79O+vuB9Pm0jqi87/w9jYOMnpGK1bt+bJkyesXLky0bEPHz4QFhYGQP369QFYsGCBRp7/56rakydPZsKECQwYMCDZPLVr10ZfX58FCxZoPEarVq0iNDRUvRNPmTJlMDc3Z9myZURFRanzrVmzJtEXvpT2OaUaNGhAbGwsixYt0kifO3cuCoVC/dilpaSeRyqVivnz53/VeoyNjQESPabNmzdHV1eXiRMnJhrJUKlUvHz5Eviyv9OX+vDhA506deLVq1eMHTtWHRjo6uqiUCiIjY1V5w0MDExy1y5jY+Mk26Grq5uoXwsXLtQoUwghMjoZmRDiO1S3bl309fVp1KgRvXv35v3796xcuRILCwuePXv21epxdnbmzz//ZOjQoZQtW5asWbPSqFEjOnXqxNatW+nTpw8nTpygUqVKxMbG4uXlxdatWzl06BBlypShVKlStGvXjiVLlhAaGkrFihU5duyYxvUsvlS1atWoVq3aJ/OYm5szevRoJk6cSL169WjcuDHe3t4sWbKEsmXLqi9cpqenx+TJk+nduzc1a9akTZs2BAQEsHr16kRz8VPa55Rq1KgRNWrUYOzYsQQGBlKyZEkOHz7Mnj17GDx4cKJ1JmmhcOHCODg4MHz4cJ48eUL27NnZsWPH/70O42POzs5A/HbDbdu2RU9Pj0aNGuHg4MDkyZMZPXo0gYGBNG3alGzZshEQEMCuXbvo1asXw4cP/6K/06c8efKEDRs2APGjEZ6enmzbto3nz58zbNgwevfurc7bsGFD5syZQ7169Wjfvj3BwcEsXrwYR0dHbt++nah/R48eZc6cOVhbW5MvXz7Kly/Pzz//zPr168mRIwdFihThwoULHD169P/aylcIIdKdFnaQEkJ8ZUltDbt3715ViRIlVFmyZFHZ29urpk+frvrjjz8SbcGZ3Naw27Zt0yjv321YV69erU57//69qn379qqcOXOqAI1tYqOiolTTp09XFS1aVGVgYKDKlSuXytnZWTVx4kRVaGioOt+HDx9UAwcOVJmamqqMjY1VjRo1Uj169OiLt4b9lI+3hv3XokWLVIULF1bp6empcufOrerbt6/q9evXifItWbJElS9fPpWBgYGqTJkyqtOnTyd63L6kzynZGlalUqnevXunGjJkiMra2lqlp6enKlCggGrmzJmquLg4jXyAysXFJdH5Ka3nX0ltDevp6amqXbu2KmvWrCozMzNVz5491du7JnwuJLc1bErb9dtvv6ny5Mmj0tHRSfQc3bFjh6py5coqY2NjlbGxsapw4cIqFxcXlbe3t0YZKf07JcXOzk4FqACVQqFQZc+eXVW0aFFVz549VZcuXUrynFWrVqkKFCigMjAwUBUuXFi1evXqJB8HLy8vVdWqVVWGhoYqQN33169fq3755ReVmZmZKmvWrKqffvpJ5eXl9cV/NyGE0CaFSvV/rM4TQgghhBBCZFqyZkIIIYQQQgiRKhJMCCGEEEIIIVJFggkhhBBCCCFEqkgwIYQQQgghxHdm6dKllChRguzZs5M9e3YqVKjAwYMH1ccjIiJwcXHB1NSUrFmz0qJFC4KCgr64HlmALYQQQgghxHdm37596OrqUqBAAVQqFWvXrmXmzJncuHGDokWL0rdvX/766y/WrFlDjhw56N+/Pzo6Opw7d+6L6pFgQgghhBBCiEzAxMSEmTNn0rJlS8zNzdm0aRMtW7YEwMvLCycnJy5cuMCPP/6Y4jJlmpMQQgghhBDfiMjISN6+fatxi4yM/OQ5sbGxbNmyhbCwMCpUqMC1a9eIjo6mdu3a6jyFCxfG1taWCxcufFF7vssrYEeH+Gu7CVphalf785nEdyM8+tNvHEJ8D/LnsNJ2E7TCP/TrXan+W2KkZ6DtJmhFNn1DbTdBK568vqvtJiQrI3+XdF+0jokTJ2qkTZgwATc3t0R5PTw8qFChAhEREWTNmpVdu3ZRpEgRbt68ib6+Pjlz5tTInzt3bp4/f/5F7fkugwkhhBBCCCG+R6NHj2bo0KEaaQYGSQfihQoV4ubNm4SGhrJ9+3a6dOnCqVOnvmp7JJgQQgghhBDiG2FgYJBs8PAxfX19HB0dAXB2dubKlSvMnz+fNm3aEBUVxZs3bzRGJ4KCgrC0tPyi9siaCSGEEEIIIRKKi824t/+nW3FxREZG4uzsjJ6eHseOHVMf8/b25uHDh1SoUOGLypSRCSGEEEIIIb4zo0ePpn79+tja2vLu3Ts2bdrEyZMnOXToEDly5KB79+4MHToUExMTsmfPzoABA6hQocIX7eQEEkwIIYQQQgjx3QkODqZz5848e/aMHDlyUKJECQ4dOkSdOnUAmDt3Ljo6OrRo0YLIyEh++uknlixZ8sX1fJfXmcjIK/DTkuzmlLnIbk4iM5DdnDIX2c0pc8nQuzkFeWu7CcnSy11I203QIGsmhBBCCCGEEKkiwYQQQgghhBAiVWTNhBBCCCGEEAnFxWm7Bd8MGZkQQgghhBBCpIoEE0IIIYQQQohUkWlOQgghhBBCJKBSyTSnlJKRCSGEEEIIIUSqSDAhhBBCCCGESBWZ5iSEEEIIIURCsptTisnIhBBCCCGEECJVJJgQQgghhBBCpIpMcxJCCCGEECIh2c0pxWRkQgghhBBCCJEqEkwIIYQQQgghUkWmOQkhhBBCCJFQXKy2W/DNkJEJIYQQQgghRKpIMCGEEEIIIYRIFZnmJIQQQgghREKym1OKZfqRibCwcKbNW0ad5l1wrtGEDr2H4nHPW3085NVrxk6eTY3GHShTsym9h47jwaMnnyxz+96DdO47nIr1WlGxXit6DBqNh6e3Rp7Vm7ZTtWFbqjZsy5rNOzSO3b7rRetuA4iJSf/5ej17dcLD8zTBL+9x/OROnJ1LJJu3sFMB1m9cgofnad6G+dPP5ZdEeVq3aYKn91kePL7B1GljNY7Z2ubh+s1jZMuW9av340tl1n4LkRl06NaK49f24vHoHNv+XkOJ0kWTzVu3YQ12HFnHVd8T3Aw8w54TG2nSqoFGnm79OnLB8zAXPA/TrW8HjWMlfijKzqPr0dXVTZO+iM/LrO/nXXq04+Ktw/g9u86+I5sp9UPxZPO279ySnQfWcTfgPHcDzrNl1++J8vfu35VbPqe55XOa3i5dNI6Vdi7OwRNb5XkuAAkmcJ02nwtXbuDuOpxd65dSsdwP9Bw0hqAXIahUKgb9OonHT5+zYLor21YvwtrSgh6DxhD+ISLZMq9cv02DOtX5Y8E0Niyfg6WFOb2GjCXoRQgA3r4BLP59AzMn/cqMiaNYuGIdPn4BAMTExDJp5kLGj+iPUpm+L9LmLRoyddoYprkvoEqlRnh43GPnnrWYmZsmmd/I0JDAwIe4uc7g+fPgRMdNTHOxcLE748a406xxF9q0bUK9ejXVx+fM+40JrjN49+59mvUpJTJrv4XIDBo0rcPoSUNYNGslTWt1xOuuD6u2LsTELFeS+d+8fsuyuX/Qpv4vNKrelh2b9+G+wJXKNX4EoFARRwaN6sOQXmMY2nssg0f3paCTAwC6urpMmjWGCcPdiY2VxZvakFnfzxs3q8eEySOZM30J9aq3wvOONxt3LMfUzCTJ/BUql2XPjgO0btSNxnU78PTJczbtXIGllQUATkULMmJ0f/p1H4FLjxGMGDuQwkUKAPHP82lzJvDr0EnyPBdAJg8mIiIjOXrqLENdulOmVHFsbaxx6d4RWxtr/tz1Fw8ePeHWXS/GD+9PcadC5LOzYfzw/kRGRnLgyMlky53uNoq2zX+mcEEH8tvlZeKvg4iLi+Pi1ZsABDx4REEHe8o7l+LHMqUp6JiPgAePgfgRC+dSxSnuVCgdHgFN/Qd0Z+3qP9m4fjveXr4MHjiODx8+0KlzqyTzX79+m/Fjp7Fj+34iI6MSHc9nn5e3b9+xc8dfXL9+m9OnLlKwcPyHbstWjYiOjmbf3kNp2qeUyKz9FiIz+KVPB7Zu2M3Ozfvw8wnAdbg7ER8iaNm+cZL5L5+/xpEDJ/G7H8ijwCesW7EFb09fnMuXAiB/AXu8Pe9z8exVLpy5grenL/kL2APQo38nrly4jsdNz3TqnfhYZn0/79mvC5vWbWfrpt3c9/bj16ET+RAeQduOzZPMP6DXKNau2sLdO1743Q9g+EBXdBQ6VK4aHzQ7FsjHvbs+nDtzibOnL3Hvrg+OBfIB0HfgL1w8f5VbN+6kW/+0Ii4u494ymEwdTMTGxBIbG4eBvp5GuoGBPtdv3yUqOhoA/QTHdXR00NPX48btuymuJyIikpiYWHJkzwZAAQd7Ah894dnzYJ4+D+LBoyc45rfj4eOn7D5whIE9O3+F3n0ZPT09SpUuxokT59RpKpWKkyfOUa5c6VSV6ecXiKFhFkqULEKuXDn4wbkEd+94kTNndsaNH8LwoW5fp/H/h8zabyEyAz09JUVLFub8qUvqNJVKxfnTlylVJvmpLwlVqFKWfA52XLlwAwAfT1/sHWyxypMbaxtL7B1suX/Pj7z2eWjerhHzpi5Nk76Iz8us7+d6enqUKFWEMycvqNNUKhVnT13EuWzJFJVhaJQFpZ6SN29CAbjneZ98jvZY21iRJ68V+R3t8Lrni519Xtq0b8aMKQvSpC/i25SpF2AbGxtRspgTy9ZsJr+dLaYmOTlw9BS37nhhm8eKfHZ5scptwfzla3AdMQAjwyys+3MXQcEhvHj5KsX1zFn6B+ZmJlQoE/9m5mBvy6DeXek5eAwAg3p3xcHelh6DRjO0XzfOXb7GklUbUSp1+XVwH8qUSn7e49diapoLpVLJi+AQjfTg4BAKFnRIVZlv3rylT68RLF85G8MsBmzZtItjR8+waMk0Vixfj529DVu2rUBPT4n7lAXs2X3wa3Tli2TWfguRGeQyyYlSqSTkheb7dUjwK/I72id7XtZsxpzxOIi+vj5xsbG4jZquDkj87gcyZ8oSVm9fAsDsyYvxux/Imu2LmTlxAZVrVmDAiF7ExMQweewsrv4ThIi0l1nfz01M/32ev9RIf/HiJQ7/jCZ8zli3YQQ9D1YHJL4+/kz/bR5bdq4EYNqkefj6+LNl1+9MnjCb6jUrM/TXfsREx+A62p1L56993U6Jb0qmDiYA3McPx9V9LjWbdkRXVwengo7Ur10NT29f9JRK5k0dh6v7PCrVb42urg4/lilNlR/LoEph+b+v38rBo6dYvWgGBgb66vQ2zRrSpllD9f09B45gZGRIyWJONGrXky2/zycoOIQRrtM4tH01+vr6SRWf4e3fd5j9+w6r71eqXI5ixQozYpgbNz1O0K3rIIKCXnDi1G7Onbuc6M3wW5VZ+y3E9yDsfThNarTH2NiIClXKMnrSEB4FPuHyP1+YtqzdwZa1/22c0axNQ8Leh3PjqgeHLuygRd3OWFpZMHfFVGo6NyY6KlpbXRFfwff+fu4yuAeNm9enVaOuGlO91q/eyvrVW9X3W7Vtwvv3YVy7covTV/bTsGYbrKwtWfL7LCqUqkvUd/Y8V8luTimW6YMJWxtr1iyeSfiHCMLCwjE3M2HYeHdsrC0BKFq4ADvWLubd+zCio6MxyZWTdj0HU7Rwgc+WvXrTdlZt2MrKeVMp5Jj8rwOv34SydPUm1iyegcddb+zy5lHfYmJjCHz0hIIOKft1IbVevnxNTEwM5hZmGukWFmYEBb34KnXo6+szZ+4kevUcRn4He5RKXc6dvQyAn28AZcqU5O+Dx79KXSmVWfstRGbw+tUbYmJiMDPXXIRqZmHCi+Dkv/CpVCoeBsSvY7t3xweHgvnoPbirOphIKJdJDvoP70n7xr0o+UMxAv0e8sD/EQ/8H6GnVJLPwRafe35ft2MiSZn1/fzVy3+f55qLzM3NTRON0nysd/+uuAzuTtumPbh31yfZfLlMcjJkVF9aNOxC6TIl8Pd9QID/QwL8H6KnpyS/oz1enve/Sn/EtydTr5lIyMgwC+ZmJoS+fcf5y9eoWeVHjePZshpjkisnDx494a7XfWpU/jGZkuL9sXEby9dsZtns3yjmVPCTeacvWEGn1k2xtDAnNi6WmJgY9bHY2DjiYtM+Oo6OjubmjTtUr15RnaZQKKhWvSKXL3+dYfqRo1w4evQ0t27eRVdXB6Xuf7GsUk+plS3mMmu/hcgMoqNjuHvLiwpVy6nTFAoFFaqU5ebV2ykuR6Gjk+zo8JjfhrFm+WaCngXHv771/nt96yp15fWdjjLr+3l0dDS3b3pSudp/30sUCgWVq5bn2pVbyZ7Xd2A3Bo/oQ8eWvbl989PrQCdOHcXKJet49jQIXR0d9D5+nuvI8zwzy/QjE+cuXUOlUmFva8PDx0+ZvXgV+WxtaNqwLgCHjp8hV84cWOU2575/INPmLaNmlQpUKu+sLmP0b7OwMDNlSN/4/alXbdjKot/XM2PCKPJY5Sbkn/UVRoaGGBkZatR//vJ1Hjx6wtRxwwAo5lSQgAePOXPhCs+DX6Cjo4O9nU16PBQsWriKZStmceOGB1ev3qKfyy8YGRmxYf12AJavnMXTp0FMnDATiF/0VdjJEYhfpG5lnZviJZwIex+Ov/8DjbILFXakeYufqVzxZwB8vP2Ii4ujU+fWBAe9oGBBB65fS/mH+9eUWfstRGawetlGpi90485NT25fv0uX3u0xNDJkx+Z9AMxYNJGg58HMnrwYgN6DuuJx8x6PAh+jr69HtdqVaNKqAW4j3ROVXbFaeewdbBnZfwIAt294kt/Rjqq1KmJlnZu42Dj8fR8kOk+kncz6fr5yyVrmLpnK7Rt3uXHdg559O2FobMifG3cBMH/pVJ49C2bapHkA9BvUneGj+9O/50gePXyqHs0JCwsnPCxco+wq1SuQz8GeQX3j13neunEHhwL5qFG7MtZ5rIiLjcPPNyD9OpteMuCuSRlVpg8m3r0PY96y1QS9CCFH9mzUqVaZgb27oKeMf2hevHzFjIUrePnqDeamJjSuV4s+v7TTKONZUDA6CoX6/p+7/iI6OoYh46Zo5OvbrQMu3Tuq70dERjJ1zhJmTRqNjk78IJGlhTmjh/Rl3NS56OvpMWXcMLIYGKRV9zXs3PEXZmYmjBk3hNy5zfC4fY8WTbuqh0ltbKyJS/DisrKy4NyFv9T3Bw3uxaDBvThz+iIN67fXKHvBwqmM+XUK4eEfgPgdrvr2HsmsuRMxMNBn+NAJPHsWlA69TCyz9luIzODA7iOYmOZi4Kg+mFuYcu+OD93bDODlP4uyrWwsiUswN9rQyBC3GaOwtLIgIiIS//uBjOg3ngO7j2iUa5DFANdpIxnSczQqVfwquqBnwfw2ZibuC1yJioxm1IAJREZEpl9nRaZ9P9+7629MzEwYPqY/5hZm3PXwomPL3ur1G9Y2VsTF/bfas3O3NhgY6LNy3TyNcmZPW8yc6UvU97NkMWDKjLH07TZc/Tx/9jSI8aOmMmfRFKKiohjcbwwR8jzP1BSqf58d35HoEH9tN0ErTO1qa7sJIh2FR8ubt/j+5c9hpe0maIV/6DNtN0ErjPTS58ezjCabvuHnM32HnrxO+Tb76S3y/nltNyFZBgUqfj5TOtLqyERISAh//PEHFy5c4Pnz5wBYWlpSsWJFunbtirm5uTabJ4QQQgghMiPZzSnFtLYA+8qVKxQsWJAFCxaQI0cOqlatStWqVcmRIwcLFiygcOHCXL169bPlREZG8vbtW41bZKT8YiuEEEIIIURa09rIxIABA2jVqhXLli1DkWC9AcRvy9enTx8GDBjAhQsXkikhnru7OxMnTtRIGzdiIK4jB331NgshhBBCCCH+o7U1E4aGhty4cYPChQsnedzLy4vSpUvz4cOHT5YTGRmZaCRC590TDNJp0XJGImsmMhdZMyEyA1kzkbnImonMJUOvmfA6pe0mJMugcDVtN0GD1kYmLC0tuXz5crLBxOXLl8mdO/dnyzEwMEgUOERHffoiLUIIIYQQQoj/n9aCieHDh9OrVy+uXbtGrVq11IFDUFAQx44dY+XKlcyaNeur1BUWFs7Cles4dvoCr16/oXBBB34d3JviToUAKFapfpLnDe3XnW4dWvLkWRDL1mzi8rVbhLx8jbmZCT//VJPeXdqip6encc6VG7f5ddJMju1a/9l6AcLDPzB36WqOnznPm9B35LHOTYeWTWjTrKE6T2RkFDMXreTg0VNERUdTqZwz44a7YGaS66s8PqlVsVJZBg3uRanSxbCyyk27Nr35a/+Rz5/4jcus/RYiM2jXtQXturbExjZ+ROS+lz+LZ//O6WMZd2cXkXqZ9f28/5Ae1P+5Do4F8hEREcHVyzeZ6jYHP99AbTdNfIO0Fky4uLhgZmbG3LlzWbJkCbGxsQDo6uri7OzMmjVraN269Vepy3XafHz9A3F3HY6FmSn7Dh2n56Ax7Nm4nNzmZpzcu1Ej/5mLV3F1n0ed6pUACHjwCFWcCtcRA7C1scbX/wETps/nQ0QEI/r31Dj3xJmLVK9UPkX1AsxYuIJL127h7jqSPFa5OX/5GpNnL8bCzJQa/1yFe/qC5Zy+cIU5k8eQ1diYqXOWMHjMZDYsm/1VHp/UMjY24o7HPdav28amLcu02pb0lFn7LURm8PxpMLMnLyLQ/yEKFDRr+zNL1s2mac0O+Hpnzm3Hv2eZ9f38x4plWfv7Zm7e8ECpVPLr+EFs2rmS6j825kP4p6eXZxqym1OKZYjrTERHRxMSEj81yczMLNGv/V9cXoLrTERERlK+TnMWTJtAtYrl1Omtuw2g8o9lGNirS6LzB/46ibDwcFYtmJZsHX9s3M7W3X/x97bVGun1W3dj7NB+lCldPEX1Nu3Yh3q1qtLnl/ZJ5nn3PowqDdsyw20kdWtUAcD/wSMat+/FxuVzKFnMSX2eNtdMvA3zzzS/6CSkzX7LmgmRGWSENROXfY4xY+ICtm/ck251ypqJ9KfN93Ntr5kwMc2Fh+9ZmjfszKXz19Kt3gy9ZuLeCW03IVkGTjW03QQNWtsaNiE9PT2srKywsrL6vwOJj8XGxBIbG4eBvma5Bgb6XL+d+Ekc8uo1p89fpvnPP32y3PdhYWTPlk0jzdf/Aa9ev6G8c8kU11uquBMnzl4k6EUIKpWKy9duEfjwCRXL/QCAp/d9YmJi+LFMafU5+e3yYpXbglt3vFL2IAghhPhiOjo6NGxaFyMjQ25cua3t5giRZrJnj/8+8+Z1qJZbIr5FWr1oXXowNjaiZDEnlq3ZTH47W0xNcnLg6Clu3fHCNk/iX7z2HjyKkZEhtatVSrbMh4+fsmn7Xob376GRfvzMBSqVd0ZPTw89Pb0U1TtmSF/cpi+gVtNOKHV1UegocBs1iDKligMQ8vI1enpKsmfLqlGXqUlOQl69+n8eGiGEEEko6OTAnwdXY2CgT3jYB1y6jsDPJ0DbzRIiTSgUCia6j+Lyxet43/PVdnMyjjiZ5pRS330wAeA+fjiu7nOp2bQjuro6OBV0pH7tanh6J37R7Np/mJ/r1sDAQD/JsoJehNB76Djq1qhCy8aaC7dPnL1IuxaNvqjejdv3cvuuF4umT8DKMjfXbnowZfYSLMxMqVC2NEIIIdJXgO8DmtRoT7ZsWanXuBbTF7rRoUkvCSjEd2nqrHEUcipAs/qdtN0U8Y3KFMGErY01axbPJPxDBGFh4ZibmTBsvDs21pYa+a7dvEPAw8fMnDQ6yXKCX7yk24BfKVW8CG6jBmocexHyins+fhrrIz5Xb0RkJPOXr2W++3j1eYUc8+F13581m3dQoWxpzExzER0dw9t37zVGJ16+eoOZiclXeXyEEEL8Jzo6hocBjwG4e9uL4qWK0KVXO1yHT9Vyy4T4uibPGEvtn6rRvEEXnj0N0nZzxDcqQ6yZSC9GhlkwNzMh9O07zl++Rs1/dkv61879hyhSqACFC+RPdG7QixB+GTCKIoUcmTxmCDo6mg/dyXMXKVXciRzZsyU6N7l6Y2JiiImJQeejK4Dr6uoQ98/wWpFCBVAqlVy6elN9PODBY54FBVOyWNLX6BBCCPH1KHR00Df4uuv5hNC2yTPGUq9hLVo37sajh0+03ZyMRxWXcW8ZTKYYmTh36RoqlQp7WxsePn7K7MWryGdrQ9OGddV53oeFcfjEGYZ/tNUr/BNI9B+FtaUFw/v34PWb/xYomZnGjw6cOHuJGpU1g5PP1ZvV2JgypYsze/EqDAwMsLa04OoND/YePMaIgfHtyJbVmOY/12XGwpXkyJ4NY2Mjps5dSsliTho7OWmDsbER+R3s1Pft7fNSvIQTr1+F8vjxUy22LG1l1n4LkRkMG+fCqWPnefb4OcZZjWjUoh7lKznTrfUAbTdNpIHM+n4+ddZ4mrZsQLf2A3j/Phxzi/jt6t+9fUdEhOwUKL5Mhtga9mtLuDUswN/HTjNv2WqCXoSQI3s26lSrzMDeXciW1VidZ9ueA0yfv4ITezdqpAPs/usI46bOSbKuO+cOEv4hgioN2rBr/VJsbay/qN6Ql6+Yt2wN5y9fJ/TtO6wtLWjZpD6d2zRD8c+Ixb8XrTtw5CTR0dFULOfM+OEu6kDmX+m9NWzlKuU58PfmROkbN2ynb++R6dqW9JRR+i1bw4rMIL23hp0ybzwVqpTFIrcZ796+x9vzPisWruP8qUvp2g7ZGjZ9ZJT38/TeGja5LVmH9BvL1s27td6OjCDyTsbd6t6gWB1tN0FDpggm0tqRk+dYuHItezeuSNd6P6bN60yI9CfBhMgMMsJ1JrRBgonMRdvXmdCWDB1M3D6k7SYky6DEpy9fkN4y1ZqJtGJkmIWhfbtpuxlCCCGEEEKkq0yxZiKtVSrvrO0mCCGEEEIIke4kmBBCCCGEECIBlSpW2034Zsg0JyGEEEIIIUSqSDAhhBBCCCGESBWZ5iSEEEIIIURCGfDicBmVjEwIIYQQQgghUkWCCSGEEEIIIUSqyDQnIYQQQgghEoqTaU4pJSMTQgghhBBCiFSRYEIIIYQQQgiRKjLNSQghhBBCiIRkN6cUk5EJIYQQQgghRKpIMCGEEEIIIYRIFZnmJIQQQgghREJxsdpuwTdDRiaEEEIIIYQQqSLBhBBCCCGEECJVZJqTEEIIIYQQCcluTikmIxNCCCGEEEKIVJFgQgghhBBCCJEqMs1JCCGEEEKIhOJkmlNKyciEEEIIIYQQIlUkmBBCCCGEEEKkikxzEkIIIYQQIiHZzSnFZGRCCCGEEEIIkSrf5ciEoXUVbTdBKz48PaPtJmhFUafW2m6CSEf+oc+03QStMNIz0HYTtCKz/r0zq4LZ82i7CVrxLOKVtpsgRKp9l8GEEEIIIYQQqSa7OaWYTHMSQgghhBBCpIoEE0IIIYQQQohUkWlOQgghhBBCJCTTnFJMRiaEEEIIIYQQqSLBhBBCCCGEECJVZJqTEEIIIYQQCahUsdpuwjdDRiaEEEIIIYQQqSLBhBBCCCGEECJVZJqTEEIIIYQQCcluTikmIxNCCCGEEEKIVJFgQgghhBBCCJEqMs1JCCGEEEKIhFQyzSmlZGRCCCGEEEIIkSoSTAghhBBCCCFSRaY5CSGEEEIIkZDs5pRiMjIhhBBCCCGESBUJJoQQQgghhBCpItOchBBCCCGESEh2c0oxGZkQQgghhBBCpIoEE0IIIYQQQohUkWlOQgghhBBCJCS7OaWYjEwIIYQQQgghUkWCCSGEEEIIIUSqSDCRSYWFhTNt3jLqNO+Cc40mdOg9FI973urj4eEfmDJ7CbWadsS5RhMad+jFn7v++mSZ0TExLP1jI/Va/cIPNRrTvEs/zl68qpFn/6Hj1GrWiYr1WjFjwQqNY0+eBdGwbQ/eh4V9vY6mUIdurTh+bS8ej86x7e81lChdNNm8dRvWYMeRdVz1PcHNwDPsObGRJq0aaOTp1q8jFzwPc8HzMN36dtA4VuKHouw8uh5dXd006cuXyKz9zqx69uqEh+dpgl/e4/jJnTg7l0g2b2GnAqzfuAQPz9O8DfOnn8svifK0btMET++zPHh8g6nTxmocs7XNw/Wbx8iWLetX74cQn9KqazP2Xt7KuYCjrPlrOUVLOaXovLpNanH12RlmrZ6qkd6xT1sOe+zlsMdeOvRuo3GsaOkirD/0e4Z4X+vSox0Xbx3G79l19h3ZTKkfiiebt33nluw8sI67Aee5G3CeLbt+T5S/d/+u3PI5zS2f0/R26aJxrLRzcQ6e2Joh+p1mVHEZ95bBSDCRSblOm8+FKzdwdx3OrvVLqVjuB3oOGkPQixAAZixcwdlLV3F3HcneTSvo1LopU+cu4cSZi8mWuXDFWrbtOciYIX3Zs2E5rZs2YNDo37jn4wvA6zehTJg2n+EuPVg+dzL7Dx3n5LlL6vMnz1rE4D6/kNXYOG07/5EGTeswetIQFs1aSdNaHfG668OqrQsxMcuVZP43r9+ybO4ftKn/C42qt2XH5n24L3Clco0fAShUxJFBo/owpNcYhvYey+DRfSno5ACArq4uk2aNYcJwd2JjY9Otj0nJrP3OrJq3aMjUaWOY5r6AKpUa4eFxj5171mJmbppkfiNDQwIDH+LmOoPnz4MTHTcxzcXCxe6MG+NOs8ZdaNO2CfXq1VQfnzPvNya4zuDdu/dp1ichPlancU2GuPVn5ew1dPypBz6evizcPJtcpjk/eZ6VjSWDXPtx/eJNjXRHJwf6jOzOmD5ujO07kb6jeuJQOD8Q/742Zvow3EfO0vr7WuNm9ZgweSRzpi+hXvVWeN7xZuOO5ZiamSSZv0LlsuzZcYDWjbrRuG4Hnj55zqadK7C0sgDAqWhBRozuT7/uI3DpMYIRYwdSuEgBIL7f0+ZM4Nehk7Teb5ExSDCRCUVERnL01FmGunSnTKni2NpY49K9I7Y21urRh5se92hSvzblfihBHqvctGrSgEKO+TVGLz627+/j9OzchqoVy5E3jxVtm/1MlQplWbN5JwCPnz4na1Zj6teuRnGnQpT9oST+gY8AOHDkJEqlkjrVK6X9A/CRX/p0YOuG3ezcvA8/nwBch7sT8SGClu0bJ5n/8vlrHDlwEr/7gTwKfMK6FVvw9vTFuXwpAPIXsMfb8z4Xz17lwpkreHv6kr+APQA9+nfiyoXreNz0TKfeJS+z9juz6j+gO2tX/8nG9dvx9vJl8MBxfPjwgU6dWyWZ//r124wfO40d2/cTGRmV6Hg++7y8ffuOnTv+4vr125w+dZGCheODx5atGhEdHc2+vYfStE9CfKxD7zbs3riPfX8eIMAnEPeRs4j4EEHjdg2TPUdHR4fJi11ZMesPnjx4pnHM3tGW+55+XD13nStnr+F7zw97R1sAOvVrx/VLt/C85ZWmfUqJnv26sGnddrZu2s19bz9+HTqRD+ERtO3YPMn8A3qNYu2qLdy944Xf/QCGD3RFR6FD5arxPw45FsjHvbs+nDtzibOnL3Hvrg+OBfIB0HfgL1w8f5VbN+6kW/9ExibBRCYUGxNLbGwcBvp6GukGBvpcv30XgFLFnThx9iJBL0JQqVRcvnaLwIdPqFjuh2TLjYqORl9fP1GZN/4p09bGmoiICO75+BL69h13vXwo5JiP0LfvWLhyHWOG9vvKPf08PT0lRUsW5vyp/0ZIVCoV509fplSZ5KeAJFShSlnyOdhx5cINAHw8fbF3sMUqT26sbSyxd7Dl/j0/8trnoXm7RsybujRN+vIlMmu/Mys9PT1KlS7GiRPn1GkqlYqTJ85RrlzpVJXp5xeIoWEWSpQsQq5cOfjBuQR373iRM2d2xo0fwvChbl+n8UKkkFJPSeESBbl05po6TaVScfnMVUo4Jz+Fs8fQrrx6+Zo9mxNP5fX18sc2f15y57HA0iY3tvnz4ucdQB47axq1acDSaSvTpC9fQk9PjxKlinDm5AV1mkql4uypiziXLZmiMgyNsqDUU/LmTSgA9zzvk8/RHmsbK/LktSK/ox1e93yxs89Lm/bNmDFlQZr0JUOJi8u4twxGtobNhIyNjShZzIllazaT384WU5OcHDh6ilt3vLDNYwXAmCF9cZu+gFpNO6HU1UWho8Bt1CDKlEp+Dmal8s6s27KTMqWKkTePFRev3uTYqfPExsUPg+bIno0p44Yx5rfZRERG0qheLSqVd2a8+1zat2jEk2fPGTDKjZiYWPp170DdGlXS/LHIZZITpVJJyItXGukhwa/I72if7HlZsxlzxuMg+vr6xMXG4jZquvqLud/9QOZMWcLq7UsAmD15MX73A1mzfTEzJy6gcs0KDBjRi5iYGCaPncXVf76Mp6fM2u/MytQ0F0qlkhfBIRrpwcEhFCzokKoy37x5S59eI1i+cjaGWQzYsmkXx46eYdGSaaxYvh47exu2bFuBnp4S9ykL2LP74NfoihDJymmSA6VSyauP3tdevXiNvaNdkueULFecJu0a0r5OtySPB95/wJJpK1iyZS4Ai92XE3j/AYv/nMuCyUupUL08vYb/Qkx0DLNcF3Dj4q2v26kUMDH99/38pUb6ixcvcfhnNOFzxroNI+h5sDog8fXxZ/pv89iyMz5YmjZpHr4+/mzZ9TuTJ8ymes3KDP21HzHRMbiOdufS+WufKl585ySYyKTcxw/H1X0uNZt2RFdXB6eCjtSvXQ1P7/j1DRu37+X2XS8WTZ+AlWVurt30YMrsJViYmVKhbNK/ZP46qDdu0xfQqH0vFArIa21F04Z12LX/sDpP7WqVqF3tv6lMV27cxsc3gDFD+tKgdXdmTByFmYkJ7XoOwrlUcUxz5UzTxyG1wt6H06RGe4yNjahQpSyjJw3hUeATLv/zhrpl7Q62rN2hzt+sTUPC3odz46oHhy7soEXdzlhaWTB3xVRqOjcmOipaW135Ipm13yJp+/cdZv++/17flSqXo1ixwowY5sZNjxN06zqIoKAXnDi1m3PnLif6siOENhkZGzJp4TimjJhB6KvQZPPtWLeHHev2qO83bFWP8LBwPK7eYcfZjXSu3wsLK3OmLnWjcfnW39z7msvgHjRuXp9WjbpqTGlcv3or61dvVd9v1bYJ79+Hce3KLU5f2U/Dmm2wsrZkye+zqFCqLlHfWL/F1yPBRCZla2PNmsUzCf8QQVhYOOZmJgwb746NtSURkZHMX76W+e7jqVaxHACFHPPhdd+fNZt3JBtMmOTKyYJprkRGRvHm7VsszEyZu/QPbKwtk8wfFRXF5FmLcXcdwcPHz4iNjaVs6fgpNnZ58+Bx14vqlX9MmwfgH69fvSEmJgYzc81FamYWJrwITv6Lj0ql4mHAYwDu3fHBoWA+eg/uqv5SnVAukxz0H96T9o17UfKHYgT6PeSB/yMe+D9CT6kkn4MtPvf8vm7HPiOz9juzevnyNTExMZhbmGmkW1iYERT04qvUoa+vz5y5k+jVcxj5HexRKnU5d/YyAH6+AZQpU5K/Dx7/KnUJkZQ3r0KJiYnB5KP3NRPzXLxM4n3Nxj4PeWytmbN2mjpNRyd+9vfFRydoUbkDTx481Tgnh0kOeg77hV7N+lPshyI89H/Eo4DHPAp4jFJPGT8Nyss/DXqXvFcv/30/19xMwdzcNNFo5Md69++Ky+DutG3ag3t3fZLNl8skJ0NG9aVFwy6ULlMCf98HBPg/JMD/IXp6SvI72uPlef+r9CfDyIDTiTIqWTORyRkZZsHczITQt+84f/kaNav8SExMDDExMegoFBp5dXV1iEvBi8vAQJ/c5mbExMZy5OQ5alSpkGS+5Wu2UPnHMhQp5EhcXCwxCXaFiImJJTYdXsjR0THcveVFharl1GkKhYIKVcpy8+rtFJej0NFJtF7kX2N+G8aa5ZsJehaMrq4OSr3/Ynhdpa5WttbLrP3OrKKjo7l54w7Vq1dUpykUCqpVr8jly19nutnIUS4cPXqaWzfvxv+9df/7eyv1lPL3FmkuJjoGr9s+lKvsrE5TKBSUrezM7Wt3E+UP9H1Im+qd6VC7m/p2+vA5rp67QYfa3Qh6mngXs2ETB7B5xVaCn71AR1cHpTLB+5quLrq66f+1Kjo6mts3Palc7b8f3xQKBZWrlufaleSnXfUd2I3BI/rQsWVvbt9M/PgkNHHqKFYuWcezp0Ho6uig9/H7uY68vjMzGZnIpM5duoZKpcLe1oaHj58ye/Eq8tna0LRhXfSUSsqULs7sxaswMDDA2tKCqzc82HvwGCMG9lSXMfq3WViYmTKkb/z+87fvehH04iWFC+Qn+MVLlvyxAZVKRbcOLRPV7xfwgL+Pn2bb6kUA5LPLi46ODjv2HcLMNBcBDx9RzKlgujwWq5dtZPpCN+7c9OT29bt06d0eQyNDdmzeB8CMRRMJeh7M7MmLAeg9qCseN+/xKPAx+vp6VKtdiSatGuA20j1R2RWrlcfewZaR/ScAcPuGJ/kd7ahaqyJW1rmJi43D3/dBuvTzY5m135nVooWrWLZiFjdueHD16i36ufyCkZERG9ZvB2D5ylk8fRrExAkzgfhFnYWdHAHQ19fDyjo3xUs4EfY+HH9/zb9docKONG/xM5Ur/gyAj7cfcXFxdOrcmuCgFxQs6MD1aykPUoVIrY3L/8Rt/hg8b3lx9+Y92vdshaGRIfu2HABg4oKxBD8PYfHU5URFRuHnHaBx/rvQ+K2MP04HKF+1DLb58zJh4BQAPG96YedoR8Wa5cltbUFcXCwP/B6mcQ+TtnLJWuYumcrtG3e5cd2Dnn07YWhsyJ8bdwEwf+lUnj0LZtqkeQD0G9Sd4aP707/nSB49fKoetQwLCyc8LFyj7CrVK5DPwZ5BfccAcOvGHRwK5KNG7cpY57EiLjYOP9/Ej5fIPCSYyKTevQ9j3rLVBL0IIUf2bNSpVpmBvbug98+vLLMm/sq8ZWv4deIMQt++w9rSgoG9u9Cm6X/b6z0LCtYYvYiMimLhyrU8fvocI0NDqlQoi/v4EWT/6KJVKpUKtxkLGDGgJ0aGWQDIYmDA5LFDmTJ7CVHR0YwZ0o/c5ppTMtLKgd1HMDHNxcBRfTC3MOXeHR+6txnAy38W8VnZWBKX4CIxhkaGuM0YhaWVBRERkfjfD2REv/Ec2H1Eo1yDLAa4ThvJkJ6jUalUAAQ9C+a3MTNxX+BKVGQ0owZMIDIiMl36+bHM2u/MaueOvzAzM2HMuCHkzm2Gx+17tGjaVT0NwsbGWmPk0crKgnMX/tvdZtDgXgwa3Iszpy/SsH57jbIXLJzKmF+nEB7+AYCIiEj69h7JrLkTMTDQZ/jQCTx7FpQOvRSZ3ZG9x8llmpM+I7tjam6Cz11fBrQfzquQ1wBY5slNXJzqi8s1yKLPyClDGN1ngvp9LfjZC2aOm4fr3NFER0UzYeBUIiMSb6OcHvbu+hsTMxOGj+mPuYUZdz286Niyt3qdkrWNlUa/O3drg4GBPivXzdMoZ/a0xcyZvkR9P0sWA6bMGEvfbsPV/X72NIjxo6YyZ9EUoqKiGNxvDBHf4/t5Brw4XEalUP377PiOKPXzaLsJWvHh6RltN0Erijq11nYTRDryD332+UzfISM9A203QSvCo7/DLykiWaVM82u7CVrxLOLV5zN9h568/vT0Km36sH+OtpuQLMOfh2q7CRpkzYQQQgghhBAiVTJ0MPHo0SO6dUt67+d/RUZG8vbtW43bdzjYIoQQQggh0ou2L0z3DV20LkMHE69evWLt2rWfzOPu7k6OHDk0bqq4d+nUQiGEEEIIITIvrS7A3rt37yeP+/t/fq/m0aNHM3So5tyxXKaF/692CSGEEEIIIT5Pq8FE06ZNUSgUn5yWpPjoWgcfMzAwwMBAc2Hi584RQgghhBAiWbKbU4ppdZqTlZUVO3fuJC4uLsnb9evXtdm8DC1LFh0sc2fBLq8RDvmyYmSkecGYIyfP0XPwGCrVb02xSvXx8tG80nDo23dMnbOEn9v2wLlGE2o378zUuUt59z5Mncfrvj8jJkyjVrNOONdoQqP2vVi/dXeS7dlz4Aid+g5LUd0A2/YcoGv/kZSv05xilerz9t37RHn6j3SjdvPO/FCjMdUbt+fXSTMJfvHfVUyfPAuiWKX6KEzeadzQjU1U1tfUrmsL9p7czHX/k1z3P8mfB/6gaq2Knz/xG5dZ+51ZVaxUlj+3rcTb9wJvw/xp+HMdbTdJiDTXpX8Hrj47w9BJA7TdlDTVf0gP/jr2J94PL3PL5zSrNizAwdFe280S3yitBhPOzs5cu3Yt2eOfG7XIzHQUCqKi4gh5mfS2iR8iIvihRFGG9E16AXtwyEuCQ14xvH8Pdq1fypSxQzl36Rqu7nPVeTy972OSKyfTXEewe8MyenVpy/xla9i0PfH0tONnLlKj8o8pqhvi96GvXL4MPTu3TTZPuR9KMnvSaPZvXsncKeN49OQZQ8ZNSZRP9dYQ1Wtj9Y3YtH1aP38azOzJi2hWuxPNa3fm4tmrLFk3G8dC3/eWhpm135mVsbERdzzuMWzIBG03RYh0UaRkYZp3aozPXV9tNyXN/VixLGt/30yjuu1o17wnenpKNu1ciaGRobabJr5BWp3mNGLECMLCwpI97ujoyIkTJ9KxRd+O8A+xhH9I/hf4xvVqAfG/3ielQH575k0dp75va2PNwF5d+HXSDGJiYlEqdWn+808a5+TNY8WtO/c4euo87Vs2VqdHRkZx/sp1BvXpmqK6ATq1aQbA5evJXxW3c9tm6v9bW+amR8fWDBw9ieiYGPXF9QBQKUCVfnHxicOa1/OYO3UJ7bq2oFSZ4vh6f36dz7cqs/Y7szpy+BRHDp/SdjOESBeGRob8ttiVKcNn0H1wF203J811bNVb4/7gfmPx8D1LiVJFuHQ++R95M5UMuGtSRqXVkYkqVapQr169ZI8bGxtTrVq1dGxR5vbufRhZjY1QKnU/mSdHds0rWl+8dpPcZqbkt8ubZm0LffuO/YdPUKq4k2YgAZD1A+R8D9nCQS8mzdqQFB0dHRo2rYuRkSE3riQfGH1vMmu/hRDfp1HuQzh37AKXz2TOL9LZs2cD4M3rUC23RHyLtDoyITKO129CWb5mMy0b1082zw0PTw4dO83imRM10k+cuUD1f6Y4fW1zlqxi8459fIiIpGTRwhp1GxlmYcSAnsyYvDE+QT8mPrB4bwjRafvULujkwJ8HV2NgoE942Adcuo7AzycgTevMCDJrv4UQ36+6TWpRuHhBOtfvpe2maIVCoWCi+yguX7yO973vf4qX+Poy9HUmRPp4HxZGvxETcMhnS7/uHZPMc98/kIG/TqRvtw5UKu+sTlepVJw8d0m9XuJr+6V9S7atXsSKuVPQ0dVh9G+z1OtocuXMQZe2zSFWN/72wQCilJAlKk3aklCA7wOa1GhPq5+6snnNdqYvdMOhYL40r1fbMmu/hRDfp9zWFgz7bSDjXH4jKjLtPzsyoqmzxlHIqQD9ug/XdlMyFlVcxr1lMBJMZHJhYeH0HjoeYyND5k8dn3gKEeAX8IDuA0fTsnF9endtp3HMw9Ob2NhYShV3SpP25cqZA3tbGyqW+4GZE3/lzIUr3LrrlfwJMbqgm/YvtOjoGB4GPObubS9mT16M110fuvRq9/kTv3GZtd9CiO9T4RKFMDU3YcPh37n46AQXH53AuWJp2nZvycVHJ9DR+b6/Jk2eMZbaP1WjVaNfePY0+XWO4tvk7u5O2bJlyZYtGxYWFjRt2hRvb2+NPNWrV0ehUGjc+vTp80X1yDSnTOx9WBi9h4xDT1+PhdMnYGCgnyiPr/8Dug38lSb1azOod9dEx4+fuUjVCuXQ1U1+ncXXooqLH5GIiopOPpNuHMSl/3VGFDo66BvopXu92pZZ+y2E+D5cOXOVNtU7a6S5zhvNA9+HrF20kbjveBHu5BljqdewFq0adeXRwyfabo5IA6dOncLFxYWyZcsSExPDmDFjqFu3Lp6enhgbG6vz9ezZk0mTJqnvGxkZfVE9Ekx8oxQK0NP77xcTPaUOXj5+5MieDStLC0LfvuPZ82CCQ+KvyxDw8DEAZqa5MDM14X1YGL0Gj+VDZCTzXUcQFhZOWFg4ED8aoKury33/QLoP+JWK5Z3p0rYZIS9fAfGLb01y5QTg5NmLuPTopNG2z9UNEPLyFSEvX/Pw8VMA7vsFYmxkiJWlBTmyZ+P2XS/u3PPhhxJFyZ49K4+ePGPhyvXkzWNFqWLxVzjfc+AIenp6oPPPrlb6MWAQDWFZvupj/bFh41w4dew8zx4/xzirEY1a1KN8JWe6tf6+9yXPrP3OrIyNjcjvYKe+b2+fl+IlnHj9KpTH/7xuhfjWhYd9wM9bc91XRHgEb16HJkr/nkydNZ6mLRvQrf0A3r8Px9zCDIB3b98REZH0lvOZzncQSP79998a99esWYOFhQXXrl2jatWq6nQjIyMsLS1TXY8EE98oAwNd8lj9tx+0makBLX/pT5P6tZkybhgnzlxk3NQ56uMjJkwDoG+3Drh074intx+3PeOHuhq06a5R9qHta8hjlZvDJ87y6k0o+w8dZ/+h4+rj1pYWHN6xloePn/LwyVONNRTAZ+sG+HP3AZb+sVGdp4vLCAAmjxlK04Z1yJLFgKOnzrN41QY+RERgbmpCpfLO9P5tNPr6/42gLFuzCXKEgwqI04H3WSA6bX8pNzEzYcaiiVjkNuPd2/d4e96nW+sBnD91KU3r1bbM2u/MqvQPxTnw92b1fffp8VtJb9ywnb69R2qrWUKIr6BL9/hrPO34a61G+pB+Y9m6ebcWWiS+RGRkJJGRmkGfgYEBBgYGnzwvNDR+ty4TExON9I0bN7JhwwYsLS1p1KgR48eP/6LRCYXqO7wqnFI/j7aboBUfnp75fKavaO2WnVy8coOls39L13o/VtSptVbrF+nLP/SZtpugFUZ6n/6Q+F6FR8uvpJlJKdPMeRHMZxGvtN0ErXjy+q62m5CsD9sna7sJyZp+J4aJEzV31pwwYQJubm7JnhMXF0fjxo158+YNZ8+eVaevWLECOzs7rK2tuX37NqNGjaJcuXLs3Lkzxe2RkQmRarnNzejRqY22myGEEEII8XVl4GlOo0ePZujQoRppnxuVcHFx4c6dOxqBBECvXv9tiVy8eHGsrKyoVasWfn5+ODg4pKg9EkyIVKtXq+rnMwkhhBBCiK8mJVOaEurfvz/79+/n9OnT2NjYfDJv+fLlAfD19ZVgQgghhBBCiMxKpVIxYMAAdu3axcmTJ8mX7/PXhbp58yYAVlZWKa5HggkhhBBCCCES+g6WFLu4uLBp0yb27NlDtmzZeP78OQA5cuTA0NAQPz8/Nm3aRIMGDTA1NeX27dsMGTKEqlWrUqJEiRTXI8GEEEIIIYQQ35mlS5cC8RemS2j16tV07doVfX19jh49yrx58wgLCyNv3ry0aNGCcePGfVE9EkwIIYQQQgjxnfnchq158+bl1KlT/3c9EkwIIYQQQgiRUAbezSmj0fl8FiGEEEIIIYRITIIJIYQQQgghRKrINCchhBBCCCESkmlOKSYjE0IIIYQQQohUkWBCCCGEEEIIkSoyzUkIIYQQQoiEVDLNKaVkZEIIIYQQQgiRKhJMCCGEEEIIIVJFpjkJIYQQQgiRkOzmlGIyMiGEEEIIIYRIFQkmhBBCCCGEEKki05yEEEIIIYRISKXSdgu+GTIyIYQQQgghhEgVCSaEEEIIIYQQqSLTnIQQQgghhEhIdnNKMRmZEEIIIYQQQqSKBBNCCCGEEEKIVJFpTkIIIYQQQiQk05xS7LsMJnpaV9J2E7TCvkAjbTdBKwLv79N2E7TC1K62tpsg0lF4dKS2m6AVpUzza7sJWuHz9om2m6AVVno5tN0ErXgb80HbTRAi1WSakxBCCCGEECJVvsuRCSGEEEIIIVJNJdOcUkpGJoQQQgghhBCpIsGEEEIIIYQQIlVkmpMQQgghhBAJqOJU2m7CN0NGJoQQQgghhBCpIsGEEEIIIYQQIlVkmpMQQgghhBAJyUXrUkxGJoQQQgghhBCpIsGEEEIIIYQQIlVkmpMQQgghhBAJyUXrUkxGJoQQQgghhBCpIsGEEEIIIYQQIlVkmpMQQgghhBAJyUXrUkxGJoQQQgghhBCpIsGEEEIIIYQQIlVkmpMQQgghhBAJyUXrUkxGJoQQQgghhBCpIsGEEEIIIYQQIlVkmpMQQgghhBAJyTSnFJORCSGEEEIIIUSqSDAhhBBCCCGESBWZ5iSEEEIIIURCKrloXUrJyIQQQgghhBAiVSSYSEa1Tj8x+ewiFnhvYOTuKdiVdPhk/prdGuB2bB7zvTYw5fwSWo7vgtJAT328bJPKTDm/hNm3/qDFuM4a55rYmON2fB5ZshqmSV++RJce7bh46zB+z66z78hmSv1QPNm87Tu3ZOeBddwNOM/dgPNs2fV7ovy9+3flls9pbvmcprdLF41jpZ2Lc/DEVnR1ddOkL0kJCwtn2rxl1GneBecaTejQeyge97zVx4tVqp/k7Y+N2z9ZbtCLEEZNnEGl+q1xrtGEZp36cueej/r46k3bqdqwLVUbtmXN5h0a596+60XrbgOIiYn9up1NgZ69OuHheZrgl/c4fnInzs4lks1b2KkA6zcuwcPzNG/D/Onn8kuiPK3bNMHT+ywPHt9g6rSxGsdsbfNw/eYxsmXL+tX7IcSntOrajL2Xt3Iu4Chr/lpO0VJOKTqvbpNaXH12hlmrp2qkd+zTlsMeeznssZcOvdtoHCtaugjrD/2eru9rycmsr+8GnRvy+7lV7PDZyaw9sylQsuAn8xtnN6bPb31Ye3UdO+/vYtnJ5TjXKKM+Xq1pdf64uJrNHlvoPr6HxrkWNhYsO7kcwwzw+d2hWyuOX9uLx6NzbPt7DSVKF002b92GNdhxZB1XfU9wM/AMe05spEmrBhp5uvXryAXPw1zwPEy3vh00jpX4oSg7j67PEM9zoX0yzSkJzj9XoMW4zmwet5KAG/ep2a0hA9eNxa3mYN69fJsof9nGlWg6qj3rRyzF77oPufNZ0XlWP1QqFTsmr8M4VzY6Tu/DuuGLCXkYjMsfv+J9/g53jl8HoN1v3dk9fRMR7z+kd1c1NG5WjwmTR/Lr0IncuOZBjz6d2LhjOVXL/szLkFeJ8leoXJY9Ow5w9dJNIiIjcRnUnU07V1CzQhOePwvGqWhBRozuT5e2LigUsGbLEk6dOI+X5310dXWZNmcCIwe7ERubfl+iXafNx9c/EHfX4ViYmbLv0HF6DhrDno3LyW1uxsm9GzXyn7l4FVf3edSpXinZMkPfvqNTn2GU+6Eky2b/Rq6cOXjw6AnZ//lQ9fYNYPHvG1g80w2VSoXLCDcqlvuBgg75iImJZdLMhUwYNRClMn3flJu3aMjUaWMYPGg8V6/cpJ/LL+zcsxbn0rUJefEyUX4jQ0MCAx+ye9cB3KePS3TcxDQXCxe707f3CAIDHrFt5++cPnmBv/8+DsCceb8xwXUG7969T/O+CfGvOo1rMsStP+6jZnPnhifterZi4ebZtKjcntcv3yR7npWNJYNc+3H94k2NdEcnB/qM7M7gTqNQKBTMXTedi6eu4Oflj66uLmOmD2PKiJnp+r6WlMz6+q7cqAo9xvdg8ZjF+Nz0pnH3JkzaMIk+1XsT+jI0UX6lnpLfNv7Gm5BQpvVx5+Xzl1jkseD92zAAsufKzoAZA5g3bB5BD57jumYCt8/f4sqxKwD0ndyPtdPW8EHLn98NmtZh9KQhuI5w59a1O3Tt3Y5VWxfyU4UWvAp5nSj/m9dvWTb3D/zvBxIVHU2NulVwX+DKy5BXnD1xkUJFHBk0qg+9OwxGoVCwfONczp68iM89P3R1dZk0awzjh07R+vM8TcluTikmIxNJqNXjZ85tOcaFbSd57vuEzWNXEvUhigqtaySZP79zIfyuenNl7zlePX7BvTO3ubr3HPYlHQEws7Xgw7twru2/wIPbfnhfvIuVYx4AyjSuRGxMLDcPXU63/iWnZ78ubFq3na2bdnPf249fh07kQ3gEbTs2TzL/gF6jWLtqC3fveOF3P4DhA13RUehQueqPADgWyMe9uz6cO3OJs6cvce+uD44F8gHQd+AvXDx/lVs37qRb/yIiIzl66ixDXbpTplRxbG2sceneEVsba/7c9RcAZqYmGrcTZy5S7ocS5M1jlWy5f2zchqWFOZPHDqV4kULYWFtSqbwztjbWAAQ8eERBB3vKO5fixzKlKeiYj4AHj4H4EQvnUsUp7lQo7R+Aj/Qf0J21q/9k4/rteHv5MnjgOD58+ECnzq2SzH/9+m3Gj53Gju37iYyMSnQ8n31e3r59x84df3H9+m1On7pIwcLxI3otWzUiOjqafXsPpWmfhPhYh95t2L1xH/v+PECATyDuI2cR8SGCxu0aJnuOjo4Okxe7smLWHzx58EzjmL2jLfc9/bh67jpXzl7D954f9o62AHTq147rl27hecsrTfuUEpn19d20R1MObT7EsW1HeXT/EUtGLybyQyR12tRJMn/tNnXImjMbU3pO5t7VewQ/DubOpTsE3gsAILetJeFvwzm77wz3b9/H48JtbBzzAlC1cVViYmK48PeFdOtfcn7p04GtG3azc/M+/HwCcB3uTsSHCFq2b5xk/svnr3HkwEn87gfyKPAJ61ZswdvTF+fypQDIX8Aeb8/7XDx7lQtnruDt6Uv+AvYA9OjfiSsXruNx0zOdeicyOgkmPqKrp4ttsfx4nfNQp6lUKrzOeZD/h6SHSv2veWNbPL96KpRZXguK1ijN3RM3AHgR8Bz9LPrYFLXHKIcx9iUceOz1EKPsxjQa2oY/Xf9I+459hp6eHiVKFeHMyf/eFFUqFWdPXcS5bMkUlWFolAWlnpI3b+J//bnneZ98jvZY21iRJ68V+R3t8Lrni519Xtq0b8aMKQvSpC/JiY2JJTY2DgN9PY10AwN9rt++myh/yKvXnD5/meY///TJck+cvUjRwgUYOm4KVRu2pWVXF7bvPag+XsDBnsBHT3j2PJinz4N48OgJjvntePj4KbsPHGFgz86fKD1t6OnpUap0MU6cOKdOU6lUnDxxjnLlSqeqTD+/QAwNs1CiZBFy5crBD84luHvHi5w5szNu/BCGD3X7Oo0XIoWUekoKlyjIpTPX1GkqlYrLZ65Swjn5KSA9hnbl1cvX7Nn8V6Jjvl7+2ObPS+48Flja5MY2f178vAPIY2dNozYNWDptZZr05Utk1te3Uk+JY3FHbp29qU5TqVTcPHuTQj8UTvKc8rXL43XNiz6T+7Lu2noWHVlMK5dW6OjEfz16GvgEA0MD8hfNT9YcWSlQsiCB9wIxzmFMh+EdWT5+WXp07ZP09JQULVmY86cuqdNUKhXnT1+mVJnkp7YlVKFKWfI52HHlQvz3Fh9PX+wdbLHKkxtrG0vsHWy5f8+PvPZ5aN6uEfOmLk2Tvohvk0xz+kjWXNnRVeryNuSNRvrbF2/I7WCd5DlX9p4jq0l2hm/7DYUCdPWUnN5wmL+X7AIg/G0Ya4cvpuvs/uhl0efiztPcO32LjtP7cGrd35jmtaDv7yPRVeqyf942bhy8lGQ9acnENCdKpTLR8PeLFy9x+Gc04XPGug0j6HmwOiDx9fFn+m/z2LIz/sN12qR5+Pr4s2XX70yeMJvqNSsz9Nd+xETH4DranUvnr32q+P+bsbERJYs5sWzNZvLb2WJqkpMDR09x644XtkmMPOw9eBQjI0NqV0t+ihPA46fP+XP3X3Ru05yendtw554P7nOXoadU0qRBHRzsbRnUuys9B48BYFDvrjjY29Jj0GiG9uvGucvXWLJqI0qlLr8O7kOZUsmvU/laTE1zoVQqeREcopEeHBxCwYKfXh+UnDdv3tKn1wiWr5yNYRYDtmzaxbGjZ1i0ZBorlq/Hzt6GLdtWoKenxH3KAvbsPvj5QoX4P+Q0yYFSqeTVC81pmq9evMbe0S7Jc0qWK06Tdg1pX6dbkscD7z9gybQVLNkyF4DF7ssJvP+AxX/OZcHkpVSoXp5ew38hJjqGWa4LuHHx1tftVApk1td3dpP4z+/XH31+vwl5g42DTZLnWNrmpkTFEpzcfZKJXd2wsrem7+S+6Oop2TJvM2GhYcwdOpchc4ein0Wf4zuOc+P0dQbMGMhfa/eTO29uxq0aj1JPyaa5mzh/4FyS9aSlXCb/fn5rPs9Dgl+R39E+2fOyZjPmjMdB9PX1iYuNxW3UdHVA4nc/kDlTlrB6+xIAZk9ejN/9QNZsX8zMiQuoXLMCA0b0IiYmhsljZ3H1nyDkuxInuzmllAQTX0GBH4vwk0sztoz/nYCb9zG3t6S16y/UH9CCgwvjF9veOnSFW4eu/HdOeSfyFLblzwl/MOnUAv4YOJ+3L94warc7vpfvJbk2IyNzGdyDxs3r06pRV40h8vWrt7J+9Vb1/VZtm/D+fRjXrtzi9JX9NKzZBitrS5b8PosKpeoSFRWdpu10Hz8cV/e51GzaEV1dHZwKOlK/djU8vX0T5d21/zA/162BgYH+J8uMi1NRtHABBvfpCoBTQUfu+z9g6+4DNGkQP7TepllD2jT7b1rFngNHMDIypGQxJxq168mW3+cTFBzCCNdpHNq+Gn39T9eZUe3fd5j9+w6r71eqXI5ixQozYpgbNz1O0K3rIIKCXnDi1G7Onbuc5NxtIbTFyNiQSQvHMWXEDEJfJZ5f/68d6/awY90e9f2GreoRHhaOx9U77Di7kc71e2FhZc7UpW40Lt+a6DR+X0sv3+PrW6GjQ+jLNyz+dRFxcXH4efhhmtuU5n2as2XeZgAuHrrAxUP/jdoXK1+MfE72rHBdzvIzK5jVfyavX7xm9t453L10J8m1GRlR2PtwmtRoj7GxERWqlGX0pCE8CnzC5X9+2Nuydgdb1v63YUizNg0Jex/OjaseHLqwgxZ1O2NpZcHcFVOp6dz4u3meiy8nwcRH3r9+S2xMLNnNcmqkZzfPydsXb5I8p/HQNlzeeZpzf8YvRHvq/QgDwyx0cO/F34t2ovpor2KlvpK2v/VgzZBFWNhboqury/1L9wAICniKfakCeBxL21/pP/bq5RtiYmIwMzfVSDc3N03069bHevfvisvg7rRt2oN7d32SzZfLJCdDRvWlRcMulC5TAn/fBwT4PyTA/yF6ekryO9rj5Xn/q/QnObY21qxZPJPwDxGEhYVjbmbCsPHu2FhbauS7dvMOAQ8fM3PS6M+WaW5qgoO9rUZafvu8HD2Z9C9Ur9+EsnT1JtYsnoHHXW/s8uZR32JiYwh89ISCDikbDUqtly9fExMTg7mFmUa6hYUZQUEvvkod+vr6zJk7iV49h5HfwR6lUpdzZ+PXBvn5BlCmTEn+Pnj8q9QlRFLevAolJiYGE3MTjXQT81y8DE78RdfGPg95bK2Zs3aaOu3f6S4XH52gReUOPHnwVOOcHCY56DnsF3o160+xH4rw0P8RjwIe8yjgMUo9Zfw0KC//NOhd8jLr6/vtq/jP71wffX7nNMvJ6xeJFyEDvA5+RUxMLHEJFts+9n2EiYUJSj0lMdExGvmV+kr6TunLnMFzsLK3QldXlzuX4tf+PQ14QsHShbhyNH3XQL5+9e/nt+bz3MzChBdJPM//pVKpeBgQv37v3h0fHArmo/fgrupgIqFcJjnoP7wn7Rv3ouQPxQj0e8gD/0c88H+EnlJJPgdbfO75fd2OiW+GrJn4SGx0LA/v+FOoYjF1mkKhoFDFYvhfT/qLsr6hAXEfBQzqNyZF4vz1+7fA89RNHt0NQKGrg06CXXx09ZTo6Kb/nyU6OprbNz2pXO1HdZpCoaBy1fJcu5L8MH3fgd0YPKIPHVv25vbNxOsOEpo4dRQrl6zj2dMgdHV00NP7L5bVVeqiq5N+uxkZGWbB3MyE0LfvOH/5GjWr/KhxfOf+QxQpVIDCBfJ/tqzSJYoQ+PCxRtqDh0+wsrRIMv/0BSvo1LoplhbmxMbFEhPz34dVbGwccbFpv4NEdHQ0N2/coXr1iuo0hUJBteoVuXz56wxXjxzlwtGjp7l18y66ujoodf/7eyv1lLKloEhzMdExeN32oVxlZ3WaQqGgbGVnbl9L/H4V6PuQNtU706F2N/Xt9OFzXD13gw61uxH0NDjROcMmDmDziq0EP3uBjq4OSmWC9zVdXXS19H6eGV/fMdEx+Hr4UqLSf+v8FAoFJSuVxPt60oviPa/ew8rOCoXivw9r6/x5eBn0MlEgAdBmQFuunbyO3x0/dHR10E34+a1Uoqujjb93DHdveVGhajl1mkKhoEKVsty8ejvF5Sh0dJIdFR/z2zDWLN9M0LPg+L/3x5/f3+P7uSou494yGBmZSMKx3/fTZbYLDz38CbzpS83uDTAwMuDCtpMAdJntwpugV+yZET8EevvYNWp1b8jjuwEE3Iif5tRoaBtuH7uG6qM5d5aOeXD+uQJTG44CIMj3Caq4OCq2rsHbF2+wdLAm8FbiKTfpYeWStcxdMpXbN+5y47oHPft2wtDYkD83xq/9mL90Ks+eBTNt0jwA+g3qzvDR/enfcySPHj5V/woWFhZOeFi4RtlVqlcgn4M9g/rGrxu4deMODgXyUaN2ZazzWBEXG4efb0Ca9/HcpWuoVCrsbW14+PgpsxevIp+tDU0b1lXneR8WxuETZxjev2eSZXQf+Cu1qlakfcv4XTI6tWlKp97DWLF2C/VqVcXD05vtew8yYeTAROeev3ydB4+eMHXcMACKORUk4MFjzly4wvPgF+jo6GBvl/Tc3q9t0cJVLFsxixs3PLh69Rb9XH7ByMiIDevjr6mxfOUsnj4NYuKEmUD8os7CTvE7lOnr62FlnZviJZwIex+Ov/8DjbILFXakeYufqVzxZwB8vP2Ii4ujU+fWBAe9oGBBB65fS/mHnBCptXH5n7jNH4PnLS/u3rxH+56tMDQyZN+WAwBMXDCW4OchLJ66nKjIKPy8Nd+H3oXGb3X6cTpA+aplsM2flwkDpwDgedMLO0c7KtYsT25rC+LiYnng9zCNe5i0zPr63v37bobMHoKvx318bvrQpHsTshhl4ejWowAMmTuUl89fsm76WgAOrj/Az11+pqdbL/av2Yd1PmtaubRi/+p9icrOWyAvVRpVYVD9+Pf2x76PUcXFUadNHV6/eI2Ngw0+t9J2dD05q5dtZPpCN+7c9OT29bt06d0eQyNDdmyO78eMRRMJeh7M7MmLAeg9qCseN+/xKPAx+vp6VKtdiSatGuA20j1R2RWrlcfewZaR/ScAcPuGJ/kd7ahaqyJW1rmJi43D3/dBovNE5iHBRBKu7b9AVpPs/DykNdnNc/L4XiALu0zlXUj8PEiTPGYaU5cOLtwBKhWNhrUlp6UJ71++xePYNfbM2pyo7A7uvdk+eR1RHyIBiI6MZu3wJbSd1B2lgR5/uv5BaFDSw7Fpbe+uvzExM2H4mP6YW5hx18OLji17q+e9WttYEZcgOOrcrQ0GBvqsXDdPo5zZ0xYzZ/oS9f0sWQyYMmMsfbsNVz9uz54GMX7UVOYsmkJUVBSD+40hIiIyzfv47n0Y85atJuhFCDmyZ6NOtcoM7N0FvQS/Jh48egqVChrUqZ5kGY+ePON16H9rWoo7FWKe+3jmL1vDsjWbyGNlyahBvfn5p5oa50VERjJ1zhJmTRqtnjphaWHO6CF9GTd1Lvp6ekwZN4wsBgZfv+NJ2LnjL8zMTBgzbgi5c5vhcfseLZp2VU9rs7Gx1hj6t7Ky4NyF/3a3GTS4F4MG9+LM6Ys0rN9eo+wFC6cy5tcphIfH770eERFJ394jmTV3IgYG+gwfOoFnz4LSoZciszuy9zi5THPSZ2R3TM1N8Lnry4D2w9V771vmya3xvpZSBln0GTllCKP7TFC/rwU/e8HMcfNwnTua6KhoJgycSmRE4m1W00NmfX2f3XeGHCY56DC0I7nMc+Hv6c+ETq68+WdRtrm1OaoE/Q55FoJrJ1d6uPZg4aFFvAx6yb4/9rJj6Y5EZfef1p9Vv/1O5D+f31GRUcwbNo8+v/VFT1+P5a7LeBWknXUiB3YfwcQ0FwNH9cHcwpR7d3zo3mYAL/9ZlG1lY0lcgl+0DY0McZsxCksrCyIiIvG/H8iIfuM5sPuIRrkGWQxwnTaSIT1Hq5/nQc+C+W3MTNwXuBIVGc2oAROITIfPb5FxKVQfT+j/DvS1b63tJmjF3tBPTzP6XgXeT/wLUmZgaldb203QivBo+dDKTEqZfn6q4ffI5+0TbTdBK6qZFtF2E7TC+8NzbTdBK3xeXNV2E5IVPj3xVeAzCqNRq7XdBA2yZkIIIYQQQgiRKloPJj58+MDZs2fx9Ex8JcWIiAjWrVv3yfMjIyN5+/atxi1W9R1f3l0IIYQQQogMQqvBhI+PD05OTlStWpXixYtTrVo1nj17pj4eGhrKL798epjJ3d2dHDlyaNyuhya9a4MQQgghhBCfo4qLy7C3jEarwcSoUaMoVqwYwcHBeHt7ky1bNipVqsTDhynf/WL06NGEhoZq3H7IUTgNWy2EEEIIIYQALe/mdP78eY4ePYqZmRlmZmbs27ePfv36UaVKFU6cOIGxsfFnyzAwMMDgo91vdBXf4X7HQgghhBBCZDBaDSY+fPigcYEfhULB0qVL6d+/P9WqVWPTpk1abF3KKXQU/Dy4NeWaVSG7eU5Cg15xYfup+C1jv2P9h/Sg/s91cCyQj4iICK5evslUtzn4+QamWZ06eir0jeLQUarQ0YUPbzQH11QqFYt/X8/2fX/z7l0YpUsUYfzw/tjlzaPOE/r2HVPnLOHkuUvo6OhQu3olRg/qg5GRIQCLV21g6R8bE9VtmMWAK8d2a6Qt+WMjDx49YfqEkWzbc4C/jpzknrcvYeEfOP/3NrJny6qR/3N1Bzx4zKSZC/ELfMj7sDAszExpUKc6fbt1UG9fu33vQfYePEZu6/j70VEq3oXGER2dthuzVaxUlkGDe1GqdDGsrHLTrk1v/tp/5PMnCvEN69K/AwPG9mHTyq3McV2o7eakmcz8+jbJbUrX0V1xruGMgaEBzwKfMX/4PHxva+eaT+mhXdcWtOvaEhtbKwDue/mzePbvnD52Xssty0BSsWV0ZqXVYKJw4cJcvXoVJycnjfRFixYB0LhxY20064v91KcpVTvWYe2wxTy9/xi74vnpPLMfEe/CObHmoLabl2Z+rFiWtb9v5uYND5RKJb+OH8SmnSup/mNjPvyz//jXplCoiIuB6A86GOZMPG/wj43b2Lh9L1PGDSOPlSWLVq6j99Bx7NmwHAOD+Ct7jpo4gxchr1g5byoxMTGMmzoXtxkLmOEWfyHBX9q1oE3TBhrldh84mmJOBRPVd+LMBbp3jN+KOCIiksrly1C5fBnmLUt627bP1a1U6tK4fi2cCjqSPZsx3vcDmDB9PnFxKgb36QrAleu3aVCnOoeO3ESlgqzZdDEx1+XF8xjSciqlsbERdzzusX7dNjZtWZZ2FQmRQRQpWZjmnRrjc/f7/VL5r8z6+jbOYcyMnTPwuHAbt85uvH0VirW9Ne//uVjh9+r502BmT15EoP9DFCho1vZnlqybTdOaHfD19td288Q3RqvBRLNmzdi8eTOdOnVKdGzRokXExcWxbFnGf1PL71yQW0eucufEDQBePX5B2caVsSvpqOWWpa2OrXpr3B/cbywevmcpUaoIl85fS5M6Y6N0iFVfA0rzm7NKpWL91t306tKWmlUqADB1/HCqNWrHsTPnaVC7On6BDzl78Spbfp+vDg7GDOlL3+GuDHfpgYW5KUZGhuqRAgCv+/74BT7EdcQAjfqeBb3AN+ABlX90BqBTm2YAXL6e9JVfU1J33jxW5M1jpT7H2jI3V27c5vqtO+q06f8EHi5D5gEQ+jqWLIZKDLIo+BCedr+kHDl8iiOHT6VZ+UJkJIZGhvy22JUpw2fQfXAXbTcnzWXW13fLvi0JeRbC/OHz1WlBj77/C2qeOHxG4/7cqUto17UFpcoUl2BCfDGtLsAePXo0Bw4cSPb4kiVLNK7QmVH5X/OhcKViWOSL/xKYx8kOhzKFuHvyhpZblr6yZ88GwJvXoVqp//HT54S8fE2FMqXVadmyGlOiSCFu3Ynf4evWnXtkz5ZVY5ThxzKl0dFRcNsz6V3Adu77G/u8eXAuVUwj/eTZi5QtXYKsKVjbk9q6Hz5+ytlLVylTuniy5SoU8bdv4KUixDdjlPsQzh27wOUzafPDiMgYytUpj+/t+4xa+ivrr29g3oH51G33k7abla50dHRo2LQuRkaG3LiS9I9hmZIqLuPeMhitjkx8Lw4t3U2WbIZMODYXVWwcCl0d9s7awpU9Z7XdtHSjUCiY6D6Kyxev431PO1MCQl69BsDUJJdGuqlJLkJexh8Lefkak5w5NI4rlbrkyJZNfX5CkZFR7D98gh6dEl9V/fiZC+oRkBS17wvq7tB7KPd8fImKiqZVk/r075F49O5f2XLoEBsLkREyv1OIr6Fuk1oULl6QzvV7abspIo1Z5rWkfscG7P59N9sWbaVAyQL0mtiLmOhojm8/ru3mpamCTg78eXA1Bgb6hId9wKXrCPx8ArTdLPENkmDiK3D+uQJlm1Rm9aAFPPV5hE0Re1q5diU06DUXd2SOYeOps8ZRyKkAzeon/6X3W3Ts9HnCwz/QuH5tjfT3YWFcvenBpNFD0qTeWZNGEx4ejrdvALMX/86azTvo1qFVonzG2XQwNNLh5YuYNGmHEJlNbmsLhv02EJc2Q4mKjPr8CeKbptBR4Hvbl/Uz4i+Q63/XH7tCdtTv0OC7DyYCfB/QpEZ7smXLSr3GtZi+0I0OTXpJQCG+mAQTX0Gz0R05vHQPV/fF74Lw1PsRpnnM+alf00wRTEyeMZbaP1WjeYMuPHuqvbmmZv+MSLx89RpzMxN1+stXrylUwCE+j2kuXr3RnIYVExNL6Lt36vMT2rHvb6pWKpfo2JkLV3Gwt8Uqt3nK2/cFdf9brkM+O2Lj4pg4fQFd2jZHV/e/bY+Ns+qQNZsOr17EEhOd4mYIIT6hcIlCmJqbsOHw7+o0pVJJ6R9L0vqX5lS0q/VNTL8VKfM6+DWP7mte2+rR/UdUrF9JSy1KP9HRMTwMeAzA3dteFC9VhC692uE6fKqWW5ZByG5OKSbBxFegb2iA6qM5bHFxcSgUCi21KP1MnjGWeg1r0apRVx49fKLVtthYW2JmmouL125SuGB88PA+LIzbnt60btYQgJLFnHj77j13ve5TtHABAC5du0lcnIoSRTQvdvj46XMuX7/NwukTEtV14uxFanzBFKcvrTuhuLg4YmJiiFOp+DeU+GPjNrJm1+FVSGyabwkrRGZy5cxV2lTvrJHmOm80D3wfsnbRRgkkvjP3rnqSx8FGIy1P/jwEPw7WUou0R6Gjg76BnrabIb5BEkx8BR7HrlHPpTmvnoTw9P5j8ha1p1b3nzm/7YS2m5amps4aT9OWDejWfgDv34djbmEGwLu374iIiEybShXx15f4l44uePn4kSN7NqwsLejUuikr1m7BziYPeaxzs2jleizMTKlVpSIADva2VP6xDG7T5+M6YgDRMTFMnbuU+rWrYWFuqlHVrv2HMTc1ocqPZTTSY2JiOXvxKl3btdBID3n5ipCXr3n4+CkA9/0CMTYyxMrSghzZs6Wo7v2HjqNUKingYI++nh53ve4zf9kafqpVVX2diVUbtrLo9/WEvo4lNkaFzj/bKKhU8be0YmxsRH4HO/V9e/u8FC/hxOtXoTz+p89CfOvCwz7g5605zSMiPII3r0MTpX9PMuvre8/ve5ixayatXFpxdv9ZCpYqyE/t67Ho10XablqaGjbOhVPHzvPs8XOMsxrRqEU9yldyplvrAZ8/WYiPKFSqtPz6oR197RMvlk1LBsZZaDysDSXrliObWQ5Cg15xde85/lqwndjo2HRrx97Qu+lWF8CT10nXN6TfWLZu3p0mderqxWGYK/Evg03q12bKuGHqi9Zt2/s3796/54cSRRk3zAV72/9+eQp9+44pc5Zw8uwldHQU1K5eiTGD+2psBxsXF0edFl1oXK8Wg3p31ajr4tUbjJ0yh2O71mukJ3exu8ljhtK0YZ0U1X3w6ClWb9pO4MMnqFBhnduCn3+qSec2zdTXyajbogtPnyf+1ezd21jev027X00rVynPgb83J0rfuGE7fXuPTLN6PxYenUaBqsiQSpnm13YTWL5jAd5376frRet83qbvSG9GeX1XMy2SbnX9q2ytsnQe1QVre2uCHgWx+/fdHN58KF3b4P3hebrWN2XeeCpUKYtFbjPevX2Pt+d9Vixcx/lTl9K1HT4vrqZrfV8izK2dtpuQLGO3xK9VbZJg4juS3sFERhF4f1+61jd17lJiY2MZP7x/utb7MVO72p/P9B2SYCJzyQjBhDakdzCRUWgjmMgI0juYyCgkmEidjBZMyDQnIb5Qgfx2lCzm9PmMQgghhBDfOQkmhPhCrZo00HYThBBCCJGWZDenFNPqFbCFEEIIIYQQ3y4JJoQQQgghhBCpItOchBBCCCGESEgl15RJKRmZEEIIIYQQQqSKBBNCCCGEEEKIVJFpTkIIIYQQQiQkuzmlmIxMCCGEEEIIIVJFggkhhBBCCCFEqsg0JyGEEEIIIRJQxcluTiklIxNCCCGEEEKIVJFgQgghhBBCCJEqMs1JCCGEEEKIhGQ3pxSTkQkhhBBCCCFEqkgwIYQQQgghhEgVmeYkhBBCCCFEQjLNKcVkZEIIIYQQQgiRKhJMCCGEEEIIIVJFpjkJIYQQQgiRkEouWpdSMjIhhBBCCCGESBUJJoQQQgghhBCpItOchBBCCCGESEh2c0oxGZkQQgghhBBCpIoEE0IIIYQQQohU+S6nOa18ek7bTRDpyNSutraboBUvHxzVdhO0wtC6iraboBVzc9fQdhO0YkjQCW03QaQj7w/Ptd0ErdiT00LbTRAfUck0pxSTkQkhhBBCCCFEqkgwIYQQQgghhEiV73KakxBCCCGEEKkm05xSTEYmhBBCCCGEEKkiwYQQQgghhBAiVWSakxBCCCGEEAnFxWm7Bd8MGZkQQgghhBBCpIoEE0IIIYQQQohUkWlOQgghhBBCJCS7OaWYjEwIIYQQQgghUkWCCSGEEEIIIUSqyDQnIYQQQgghEpJpTikmIxNCCCGEEEKIVJFgQgghhBBCCJEqMs1JCCGEEEKIBFQqmeaUUjIyIYQQQgghhEgVCSaEEEIIIYQQqSLTnIQQQgghhEhIdnNKMRmZEEIIIYQQQqSKBBNCCCGEEEKIVJFgQgghhBBCiITiVBn3lkLu7u6ULVuWbNmyYWFhQdOmTfH29tbIExERgYuLC6ampmTNmpUWLVoQFBT0RQ+VBBNCCCGEEEJ8Z06dOoWLiwsXL17kyJEjREdHU7duXcLCwtR5hgwZwr59+9i2bRunTp3i6dOnNG/e/IvqkQXYQgghhBBCfGf+/vtvjftr1qzBwsKCa9euUbVqVUJDQ1m1ahWbNm2iZs2aAKxevRonJycuXrzIjz/+mKJ6JJgQQgghhBAiAVUG3s0pMjKSyMhIjTQDAwMMDAw+eV5oaCgAJiYmAFy7do3o6Ghq166tzlO4cGFsbW25cOFCioMJmeYkBNCzVyc8PE8T/PIex0/uxNm5RLJ5CzsVYP3GJXh4nuZtmD/9XH5JlKd1myZ4ep/lweMbTJ02VuOYrW0ert88RrZsWb96P5ITFhbOtHnLqNO8C841mtCh91A87mnOm/QLfEj/kW78WLcFZWs1pU33gTx7HpxsmdExMSz9YyP1Wv3CDzUa07xLP85evKqRZ/+h49Rq1omK9VoxY8EKjWNPngXRsG0P3icYbhVpw7p8IX7+Yyi/XF3IgEcbyP+T8yfzG1nkpO7CfnQ8NZP+D9ZRZULHRHnyVilGx1Mz6e25kjrz+qCjp6s+pp/NkI6nZpItj+lX74sQn9OhWyuOX9uLx6NzbPt7DSVKF002b92GNdhxZB1XfU9wM/AMe05spEmrBhp5uvXryAXPw1zwPEy3vh00jpX4oSg7j65HV1cXbTEsWwyb5RNwPLsep/sHyFq7wmfPUegrMR/SGceTayh0dw8OJ1aTo2Ud9XHjSqXJf3glBW9sx3rmcND777dnnaxG5D+8EqW1RZr0R3yeu7s7OXLk0Li5u7t/8py4uDgGDx5MpUqVKFasGADPnz9HX1+fnDlzauTNnTs3z58/T3F7JJgQmV7zFg2ZOm0M09wXUKVSIzw87rFzz1rMzJP+ImRkaEhg4EPcXGfwPIkv2yamuVi42J1xY9xp1rgLbdo2oV69murjc+b9xgTXGbx79z7N+vQx12nzuXDlBu6uw9m1fikVy/1Az0FjCHoRAsDDx0/p3Hc4+ezysnrRdHasXUKfru3RN9BPtsyFK9aybc9Bxgzpy54Ny2ndtAGDRv/GPR9fAF6/CWXCtPkMd+nB8rmT2X/oOCfPXVKfP3nWIgb3+YWsxsZp23mBnqEBIfcecmrc2hTl19VX8uHlO64u2EOI58PEGRQKflrYjzsbjrOtqRsWJfJRrP1/z/GKo9twZ8Nx3j15+bW6IESKNGhah9GThrBo1kqa1uqI110fVm1diIlZriTzv3n9lmVz/6BN/V9oVL0tOzbvw32BK5VrxP8iW6iII4NG9WFIrzEM7T2WwaP7UtDJAQBdXV0mzRrDhOHuxMbGplsfP6ZjmIVIrwCCJi5J8Tl55o/GuGIpno6Zh3/dnjwdMp0o/yfxBxUKrOeM5M3mAwS2GkqW4o7kalNPfa7FiF94s/kAMU+T/7FJpK3Ro0cTGhqqcRs9evQnz3FxceHOnTts2bLlq7dHpjmJTK//gO6sXf0nG9dvB2DwwHH8VK8GnTq3Yu7sZYnyX79+m+vXbwPgNmlkouP57PPy9u07du74C4DTpy5SsLADf/99nJatGhEdHc2+vYfSsEeaIiIjOXrqLAumTaBMqeIAuHTvyKlzl/hz118M7NWFBSvWUqVCWYa5dFefZ2tj/cly9/19nF5d2lK1YjkA2jb7mYtXbrJm806mTxjJ46fPyZrVmPq1qwFQ9oeS+Ac+onql8hw4chKlUkmd6pXSqNcioQcnb/Pg5O0U53/3OIQzbusBcGpTLdFxQ5NsGJpmx2PdUWIjowk4cp1cBeKfL5bOBbAomT/FgYsQX9MvfTqwdcNudm7eB4DrcHeq16lMy/aNWbEg8XPy8vlrGvfXrdhCszY/41y+FGdPXCR/AXu8Pe9z8Wz8qKu3py/5C9jjc8+PHv07ceXCdTxueqZ9xz4h7PRVwk5f/XzGfxhXccaoXHF8a3YjLjT+R63oJ/8FBrq5sqM0ycHrjftRRUXz7tgl9B1sATAs7USW4gV5PnHp1+1ERpSBpzmlZEpTQv3792f//v2cPn0aGxsbdbqlpSVRUVG8efNGY3QiKCgIS0vLFJcvIxMiU9PT06NU6WKcOHFOnaZSqTh54hzlypVOVZl+foEYGmahRMki5MqVgx+cS3D3jhc5c2Zn3PghDB/q9nUan0KxMbHExsZhoK+nkW5goM/123eJi4vj9Pkr2OfNQ68hY6nasC3teg7m2Onznyw3KjoafX3NkQsDA31u3L4LxAcjERER3PPxJfTtO+56+VDIMR+hb9+xcOU6xgzt93U7KtLNh5dveR/0GtuqxVFm0ce6XCFC7j1CR6lLjaldOfHrHxl6vrH4PunpKSlasjDnT/03AqpSqTh/+jKlyiQ/dTWhClXKks/BjisXbgDg4+mLvYMtVnlyY21jib2DLffv+ZHXPg/N2zVi3tRv70t1tlrlifC4j2nPljieWUf+wyuxGNUdxT8j0bGvQokOeolx5R9QZDHAqExRIr0DQKmL5UQXno9fCHFxWu6FSAmVSkX//v3ZtWsXx48fJ1++fBrHnZ2d0dPT49ixY+o0b29vHj58SIUKn58u9y8ZmRCZmqlpLpRKJS+CQzTSg4NDKFjQIVVlvnnzlj69RrB85WwMsxiwZdMujh09w6Il01ixfD129jZs2bYCPT0l7lMWsGf3wa/RlWQZGxtRspgTy9ZsJr+dLaYmOTlw9BS37nhhm8eKV6/fEP7hA6s2bGVAzy4M7duNs5euMXjMZP5YOI2ypZP+EK5U3pl1W3ZSplQx8uax4uLVmxw7dZ7YuPjh/hzZszFl3DDG/DabiMhIGtWrRaXyzox3n0v7Fo148uw5A0a5ERMTS7/uHahbo0qaPg7i6/q770KqTOhIFbeOPDhxi3t/nsLZpRGPz98jNjKaFjtdMTTJxu3Vh7m99oi2mysygVwmOVEqlYS8eKWRHhL8ivyO9smelzWbMWc8DqKvr09cbCxuo6arAxK/+4HMmbKE1dvjpxDNnrwYv/uBrNm+mJkTF1C5ZgUGjOhFTEwMk8fO4uo/QUhGppfXEsMyRYmLiuaxy2R0c2XH0s0F3VzZefbrXACeDHIn95he5B7Xm/enrvJm+2HMercm/NJt4iKjsNsyC91c2Xm9fi+vN+zXco9EclxcXNi0aRN79uwhW7Zs6nUQOXLkwNDQkBw5ctC9e3eGDh2KiYkJ2bNnZ8CAAVSoUCHFi69Bggkh0sT+fYfZv++w+n6lyuUoVqwwI4a5cdPjBN26DiIo6AUnTu3m3LnLhLxI27nl7uOH4+o+l5pNO6Krq4NTQUfq166Gp7cvcf/8glyjSgU6t20GQOGCDtz08GTr7gPJBhO/DuqN2/QFNGrfC4UC8lpb0bRhHXbt/6/ftatVona1/6YyXblxGx/fAMYM6UuD1t2ZMXEUZiYmtOs5COdSxTHNlTPtHgTxVT274sPWn13V93Pms6Rwi8psqTeW5tvHc+uPQzw4cYv2R915csmLl16PtNhaIZIX9j6cJjXaY2xsRIUqZRk9aQiPAp+op0BtWbuDLWt3qPM3a9OQsPfh3LjqwaELO2hRtzOWVhbMXTGVms6NiY6K1lZXUkZHB1Qqng6dQdz7cACC3VeSZ+EYnk9YjCoyig/XPAlsMVh9ir59HnI0rYl/kwHYb5rBq7V7eH/qKvkPLCX8yh0ivQO105e09B0MvixdGj9yVr16dY301atX07VrVwDmzp2Ljo4OLVq0IDIykp9++oklS1K+/gYkmBCZ3MuXr4mJicHcwkwj3cLCjKCgF1+lDn19febMnUSvnsPI72CPUqnLubOXAfDzDaBMmZL8ffD4V6krObY21qxZPJPwDxGEhYVjbmbCsPHu2FhbkitndpS6ujjY22qck98+L9dvJz8X2CRXThZMcyUyMoo3b99iYWbK3KV/YGOd9DzLqKgoJs9ajLvrCB4+fkZsbKw6ULHLmwePu15Ur5zyX0JExlJjWjfO/rYJdHSwKG6P7/5LxERE8eSiF3l+LCzBhEhzr1+9ISYmBjNzE410MwsTXgQn/4ONSqXiYcBjAO7d8cGhYD56D+6aaD0FQC6THPQf3pP2jXtR8odiBPo95IH/Ix74P0JPqSSfgy0+9/y+bse+spjgV8QEvVQHEgCRfo9Q6OigtDQj+sHTROdY/tafIPffUegoyFLUkbcHz6KKiCT8sgdG5Yp/n8HEd0Cl+vx00yxZsrB48WIWL16c6npkzYTI1KKjo7l54w7Vq1dUpykUCqpVr8jly19nuHrkKBeOHj3NrZt30dXVQan7Xwyv1FOm65aCRoZZMDczIfTtO85fvkbNKj+ip6dHUaeCBDx8rJE38NETrC0/v/WfgYE+uc3NiImN5cjJc9SokvQ8y+VrtlD5xzIUKeRIXFwsMQl2P4mJiSVW5uB+s4q0qUbEm/cEHLmOjq4CQL1VrK6eLgpd+agRaS86Ooa7t7yoULWcOk2hUFChSlluXk35BgQKHZ1E68H+Nea3YaxZvpmgZ8Hx7+cJtkzVVepqdYvYlPpw3ROlhQkKoyzqNH37PKhiY4l5HpIof46WdYkNfc/745dAJ75/CuW//ypBXt+ZnoxMiExv0cJVLFsxixs3PLh69Rb9XH7ByMiIDf/s7rR85SyePg1i4oSZQPyi7cJOjgDo6+thZZ2b4iWcCHsfjr//A42yCxV2pHmLn6lc8WcAfLz9iIuLo1Pn1gQHvaBgQQeuX0v5h1xqnbt0DZVKhb2tDQ8fP2X24lXks7WhacO6APzSvgXDXadRplQxyv1QkrMXr3Lq3CVWL5yuLmP0b7OwMDNlSN/462rcvutF0IuXFC6Qn+AXL1nyxwZUKhXdOrRMVL9fwAP+Pn6abasXAZDPLi86Ojrs2HcIM9NcBDx8RDGngmn+OGRWekYG5LDPrb6fPa85ZkVsiXgTxvunL6kwqjVZLXNxZMhydR6zIvEjVXrGBhiaZsOsiC2x0TG8vq/5q6WhaXbKDGzCjuaTAIgMDeeVzxNKda/Hw9Me2FQqypWFe9Ohl0LA6mUbmb7QjTs3Pbl9/S5derfH0MiQHf/s7jRj0USCngcze3L8r7C9B3XF4+Y9HgU+Rl9fj2q1K9GkVQPcRibes79itfLYO9gysv8EAG7f8CS/ox1Va1XEyjo3cbFx+Ps+SHReWlMYZUHf7r/d9/RtcvM/9u47rurqj+P46zIFnIAoiLhnztTcOdJK/aVmaTZMM2fuvWcqarnTXDkzR640zdTce++JCxVEwAGCIuP+/qCuXkFDAi7K+/l73Meve77ne76fA3Lv/dxzvufYF8lL9L1QovwDydqjBTbZXPDvPQ6A+2u34drhUzxGdyNw8s9YZ8mEW5+vubd8E8aIx2ZtWztnwvWbplxr2hOAmJAHRPj44tyiIWG7juBYsSRBPyb9UqOpgRaRSDglE5LmrVyxDldXZ/oP7Ea2bK6cPHGWjxq2MN2U7enpQcxT35q7u7uxe+860/MuXdvQpWsbdu7YR706n5m1PXnKKPr3HUl4+EMAHj2KoH3b3nw/YRj29nb07D4Ef/+AZO9j6IMwJk6fS0BgEJkyZqB2tSp0btscW5vYl4Ba1SozuFdHZi9chveE6eT28mTCyIG8WbKYqQ3/gNtYGQym5xGPHzNl1nxu+N3C0cGBqhXL4T2oFxmf2YzPaDQydOxkenVqjaND7Ddh6eztGTGgOyPHTeNxZCT9u31DtqzmU80k6biVyEujX59snvjPJnRnf93B5u4zccqWmfQ5zH/+n/45yvTf2UrkpdCHlQm5Hsj8St3M6r09rBnHZv5BWMA9U9nmHjOoNb4tJVq+y5Hp67h9/HIy9EokrvWrN+HskoXOfdqR1c2Fs6cu8PUnnQj++6Zsd8/sxBifvJ47ODowdGwfsru78ehRBJcvXqXXN4NYv9p80QD7dPYMHt2bbq37maaOBPjf5tv+3+E9eTCPIyLp02kIEY/MdyVOCQ7FCpBr0ZMvfrINaAPAvZWb8O8zARu3LNh6ZDUdN4Y/wrfFALINbk+elZOIvhdKyPqdBE5YEKftbIPacmfOSqJuP7mp3a/PeDzGdifLl/W589MKHp28mIy9k1eBwZiQCVWvGBu7HJYOQVKQo23C11p+nQRf22zpECzCwSNtrvo0IVsNS4dgEd0Ctlo6BElBeTO5WzoEi/gtc9rcTbrIxfWWDuG57n1e898rWUjmRcl7n+XL0siEiIiIiMjTNM0pwSyeTJw9e5Z9+/ZRsWJFChcuzLlz55g0aRIRERF88cUX1Kz54swwIiKCiAjzYUWj0YjhqekYIiIiIiKS9Cx6C/6GDRsoVaoUPXv2pHTp0mzYsIG3334bHx8frl27xrvvvsuWLS8eyvH29iZTpkxmD2NMaAr1QEREREQk7bJoMjF8+HB69epFcHAwc+fO5bPPPqN169Zs2rSJv/76i169ejF69OgXttGvXz/u379v9jBYZUihHoiIiIjIaycmFT9SGYsmE6dPnzbtwNekSRNCQ0P5+OMny0p+/vnnnDjx4mUz7e3tyZgxo9lDU5xERERERJKfxe+Z+OeDv5WVFenSpSNTpkymYxkyZOD+/fuWCk0kXpUql6NL1zaUKl0Md/dsfPpJW9b9vunfT0xiYWHhTJm1gL927OXO3XsULpiPvl3bUrxIIQCKVa4T73ndv/natBfEmfM+jJ82h9PnLmBlZUXt6pXp3akNjo4OZuf43Qrgg0/bsHPdEvxu3eaH2Qs5c/4ifrdu06dzG5p98mGc6yxesZa5vywn6M5dCuXPS/9u7SletJDp+K+/rWfdpm2cPe9DWPhD9mz4Nc6ysvdDQhk1fhrbdu/HysqKWtUrYzDA67cGneV5lC/Em23rkbVEHtJny8K6VhO4/OeTHYDzvV+WYs3eIWvx3DhkycDi9/oTdMbXghGL/HeftviIT1t8jKdX7CpSF89dZuq42ez4a4+FI0taDuWK4dLqI9K9kR/bbC5cb/8tDzbvNatjly8nbr2+wvGt4hisrYnw8eVGx5FE+QdaKGp5VVh0ZCJ37txcvPhkfeK9e/fi5eVleu7r64u7e9pcJk5SLycnR06dPEuPbkMsGsfg0ZPYe/Ao3oN7smrhj1R6601ad+lPQGDs/hjb1iwye3zbvxsGg4Ha1SsDcDswmFZd+uHl6c4vMycyffy3+FzxZcDIcXGutWXnPt56swSOjg48jHiEp0d2urb/CleXLPHG9sfm7YydMpP2LT/n1zlTKJQ/D227DyT47j1TnUePIqhSviytv2z63D72GTYWnyu+zJo4iqljh3L42CmyuqbNpYCTm62DPUFnfdk+cH68x20c7fE7cJ49o5amcGQiyeeW323GjfiBD2s1o1GtL9m36xDTFowjf6G8lg4tSVk5pCPi3BUChk2L97itV3ZyLf6Ox5dvcO2LPlz+4BuCpi6Os4ldWmKMMabaR2pj0ZGJ9u3bEx0dbXperFgxs+N//PHHv67mJJLSNm3czqaN2y0dBpu372Ly6CGULVUcgA5ff8H23ftZumodnds0x9XF2az+1r8Tgpw5YhP07Xv2Y2Njw8AeHbCyiv1eYXCvjjT68ht8b/jh5enx1Ll7ebdG7P4OxYsUMo1+TPxxbryxLVi6io8/qMOHf++wPbhXJ3bsOciq3zfSqlkTANNoxoEj8U9lvHTVl137DrFk9iTT7tj9u7WPTUruPCY6OvW9oL7Krm07wbVtz59Wen7lbgAyeGpzQXl9bN240+z5hFHT+LTFR5QqWxyf86/PZothOw4RtuPQc49n7dacsO2HuD12jqks0vdWSoQmrwGLjky0a9eOevXqPff4qFGjmD17dgpGJPJqMBggOjoGeztbs3J7ezuOnDgdp37Qnbvs2HOARv97z1T2+HEktrY2pkQCYnemBjhy/EkbIaEPOHLiNDWqVEhQbJGRkZw5f5EK5UqZyqysrKhQthTHT51NUBsAx0+dJWOG9KZEAqBC2dJ/x2nRly4ReQ1ZWVlRr+G7ODo6cPTgi+/XfK0YDKSvXo7HV2+Sc863FNj3C7mXTyB9rYqWjkxeEXpHFnkFGY1QslgRps9bzO3AYKKjo1n75xaOnzpHUNCdOPXX/LEZR0cHalWrbCorX6YUwcF3mbNoOZGRkdwPCWXCj7HfSgUGP2lj596DFMyXB7esLgmK7e69EKKjY3BxNp8C5eKchaA7dxPcx6DguzhnzmRWZmNjTUyMEWtrLbIgIkmjYJF8HL26g1M39zDs+350aNGLSxeuWDqsFGPtkhnr9I64tGlM2I7D+H41kNCNe/CcOgDHt4r9ewOvK0uv2KTVnEQkuXkP6glGIzUbfsGbNeqz6NffqFOrGgaruH/Wq37fyP/erYG9vZ2pLH/eXIwc2IP5S1ZS9p2GVK//GTncs+PinAUrqycf1rfs3JfgUQkRkVfNFZ9rNKjxGY3fa8HiecsZM2Uo+QrmsXRYKcbw9+t96F/7uDNvNRFnLxM881cebD1A5k/rWjg6eRVYfDUnEUkcL08P5k39jvCHjwgLCyerqzM9Bnnj6ZHdrN7hY6e44nuD74b3i9NGvXdrUO/dGgTduYtjunRgMLBg6So8PWLvq4iMjGT3/kO0/vKTBMeVJXNGrK2tCH5mFCL4zl1cneO/YTs+ri5ZuHPPfDW3qKhorKwMul9CRJJMZGQUvlduAHD6xDmKlypK8zafMrjnKAtHljKi7oZgjIwiwsd8dbaIS9dxLPOGhaKSV4lGJkRecY4O6cjq6sz9kFD2HDhMzarmowgrf/+TooUKULjA81cncXXOgqOjAxv+2o69nS0Vy8Xem3DgyAkyZkj/wnOfZWtrS9FCBdh/6JipLCYmhv2Hj1GyWJEEt1OyWBFCQh9w+tyTFd/2H45t81FEKhznFZHXgsHKCjt723+v+LqIjOLhyQvY5/E0K7bPnYNIv9sWCsryLL1ik1ZzEnmNOTk5kjdfLtPz3LlzUrxEEe7euc+NG34pFsfu/YcxGo3k9vLE94Yf46b+RB4vTxr+vYISwIOwMDZu3UnPjq3jbeOX5WsoVbwojg7p2HvwKOOm/kTX9l+Z9nvYtms/1Z+Z4hQZGcmlK75//3cUAYHBnLtwCUdHB9MKUF9+8iEDRo7jjcIFKFa0ED8vW83DRxE0rFfb1E5Q8B2Cgu/i+/fP7OKlqzg5OuCe3Y1MGTOQL7cXVSqUZeiYSQzu1YnIqChGTfiRB2FRGplIBraO9mTKnc30PGPOrLgW9eLRvTAe+AVjn9mJDB4uOGWLHV3Kki929Co88D7hgdoPSF5NPQZ2YPtfe/C/cQun9I588NH7lK9chpZNOlk6tCRlcEyHXa4nK/TZeWbDvkheou+FEuUfyJ3ZK8gxsS/hB08Stu8E6d8uQ/qa5bn2RR8LRi2vCoPR+Ppt/2Rjl8PSIUgKcrRN2X0HqlQtz/oNi+OUL/p5Oe3b9k6xOBbNGczE6XMJCAwiU8YM1K5Whc5tm5MhvZOpzq+/rWfMpJlsXbPIrPwf/b79nh17DhD+8CF5cuWkxacfUf/9d0zHazX6km/7dTONVADc9A/gvY9bxGmrbOnizPthrOn5L8vXMPeXFQTduUPhAvno17UdJd4obDo+9aef+XHOojjtjOjf3ZR03A8JZeT4aWzbtR8rKwO1qldm/NRVaXLTugnZaiRr+zkqFKHRrwPilJ/9dQebu8+kcOOq1B7fNs7x/eNXcmDCymSLq1vA1mRrW1KfvJlSdm+pkRMHUbFqOdyyuRIa8oDzZy4yc8oC9mzfn6Jx/JbZLVnbd3yrOLkWjYlTfm/lJvz7TAAg08e1cW3bBJvsrjy+coPASYt48Ne+ZI2ryMX1ydr+f3Hnw2qWDuG5nFdZfnn6pymZkFdeSicTqUXwtc3J2v6Z8z583bkvO9YtwdYm9QxiOnhUtXQIFpHcyURqpWQibUnpZCK1SO5kIrVK1clEg1ScTPyWupIJ3TMhIvGKjo6mX7f2qSqREBERkdRFnxJEJF7FixaieNFClg5DREREUjElEyIiIiIiTzFq0cAE0zQnERERERFJFCUTIiIiIiKSKJrmJCIiIiLyNE1zSjCNTIiIiIiISKIomRARERERkUTRNCcRERERkadoNaeE08iEiIiIiIgkipIJERERERFJFE1zEhERERF5mqY5JZhGJkREREREJFGUTIiIiIiISKJompOIiIiIyFO0mlPCaWRCREREREQSRcmEiIiIiIgkipIJERERERFJFN0zISIiIiLyFN0zkXAamRARERERkURRMiEiIiIiIomiaU4iIiIiIk/RNKeE08iEiIiIiIgkipIJERERERFJFE1zEhERERF5mtFg6QheGUom5JUXHhlh6RAswsGjqqVDsIiHfjstHYJFpNXft6Qtl+/7WzoEiyieRvsdZekAJElompOIiIiIiCSKRiZERERERJ6i1ZwSTiMTIiIiIiKSKEomREREREQkUTTNSURERETkKcYYreaUUBqZEBERERGRRFEyISIiIiIiiaJpTiIiIiIiT9FqTgmnkQkREREREUkUJRMiIiIiIpIomuYkIiIiIvIUo1GrOSWURiZERERERCRRlEyIiIiIiEiiaJqTiIiIiMhTtJpTwmlkQkREREREEkXJhIiIiIiIJIqmOYmIiIiIPMUYo9WcEkojEyIiIiIikihKJkREREREJFE0zUlERERE5ClGo6UjeHVoZEJERERERBJFyYSIiIiIiCSKpjmJiIiIiDxFqzklnEYmREREREQkUZRMiMhr49Cxk3ToPYQa9T+nWOU6/LVjj9lxo9HID7MWUL3+Z5Sp0YBWXfpx7fpNszr3Q0LpM3QM5Ws3ouJ7HzPIewLh4Q9feN2IiMeMGDeVynWaUK7Wh3TtP4KgO3fN2uzQewjlan3Ixy06cPaCj9n5I8ZNZd7iFf+x9yIiIilPyYSIvDYePnxEofx5GdDjm3iPz1n0K4uWr2Fwr078MmsiDunS0bb7QCIiHpvq9Bk2Fp8rvsyaOIqpY4dy+Ngpho6d/MLrjpk8g2279zN+RH/m/TCWwKBguvYfYTo+c/4SwsIf8uucKZQrXYIho5+0d/zUWU6cPk+zJg3/W+dFRCTJGGMMqfaR2iiZEJHXRtWK5ejcpjm1qlWOc8xoNLJw2WraNG9KzaoVKZQ/D6MG9eR2UDB/7Ywdwbh01Zdd+w4xrG8XSrxRmDdLFqN/t/b8sXk7twOD471m6IMwVv6+kd6dWlO+TCneKFyAbwd059jJMxw/dRaAy1d9qfNONXJ7efJxgzpcueYLQGRUFMO/+4HBvTpibW2dTD8VERGR5KNkQkTShBt+twgKvkvFsqVNZRnSO1GiaCGOnzoHxI4SZMyQnmJFCprqVChbGisrAyfOnIu33TPnLxIVFUWFp9rNmysn7tncTO0WzJ+XA0eOExUVzZ79hymYLw8QO1JSrnRxs+uJiIi8SpRMiEia8M89DC7OWczKXZyzEBQceywo+C7OmTOZHbexsSZThgxm90CYtRt8F1tbGzJmSP9Mu5kJunMHgFbNmmBtbU2dJi35a8cehvfryrXrN1nzx1+0++ozho2dwvuNv6LHoFGEPghLkv6KiEjiGY2p95HaaGlYEZFkliG9E2OH9jEra9mpLz06fM3vG7dyw8+ftYtnMXT0JKbP/YVenVpbKFIREZGXo5EJEUkTXP8ekQh+ZoQh+M5dXF1ij7m6ZOHOvftmx6OiorkfGmo6P067LlmIjIwiJPTBM+3ew9XZOd5zVq3bSIb0TtSsWpGDR07wztuVsLWx4d2aVTl49ESi+iciImIJSiZEJE3w9MiOq0sW9h0+Zip7EBbGiTPnKVmsMAAlixUhJPQBp89dNNXZf/gYMTFGShQtHG+7RQsVwMbGhv2HnrR75doN/ANum9p92p2795g+9xf6d28PQExMDJFRUQBERUURHR3zX7sqIiL/kaVXbNJqTiIiFhAe/pBzFy5x7sIlAG76BXDuwiX8b93GYDDQrElDZs5fwtad+7hw6Qr9vx2Hm6sL71StBEC+3F5UqVCWoWMmcfLMeY6cOM2oCT9Sp1Y13LK6ABAQGMQHn7bm5JnzQOwUpkb/e5exU2Zx4PBxTp+7yMBR4ylZrAglixWJE+OYSTNo3rQR2bK6AlC6RFHWbtjCpau+LP/tD0qXKJoSPyoREZEkoXsmROS1cercRVp2enJvwtgpMwFoUKcWIwf2oOXnjXn48BFDx04m9MED3izxBtPHfYu9vZ3pnDFDejNy/DS+7twPKysDtapXpn/X9qbjUVHRXPG9wcNHEaayPp3bYmVlRdcBI4iMjKTSW2UY1LNDnPh27z+M701/vAf3MpV9+tEHnD53kc9ad6V40UK0b/l5kv5MREREkpPBaExd94UbjUYMhv82hGNjlyOJohGR1Oah305Lh2ARDh5VLR2CiEiSinp809IhPNelYu9ZOoTnynfqT0uHYCbVTXOyt7fn7Nmzlg5DRERERET+hcWmOXXv3j3e8ujoaEaPHo2LS+z85PHjx7+wnYiICCIiIszKkmJ0Q0REREREXsxiycTEiRMpWbIkmTNnNis3Go2cPXsWJyenBCUE3t7eDBs2zKzMYJUeg3XGpAxXRERERNIIoxbWSzCL3TMxevRoZs6cyezZs6lZs6ap3NbWluPHj1O0aMJWNIlvZCKLS2GNTIi8pnTPhIjI6yE13zPhUzT13jOR/4zumQCgb9++LF26lPbt29OzZ08iIyMT1Y69vT0ZM2Y0eyiREBERERFJfhZdGrZcuXIcPnyYDh06ULZsWRYtWqREQEReSlhYOFNmLeCvHXu5c/cehQvmo2/XthQvUgiI3Xtiwo9z2bJzD/fuh5LDIxuff9yATz6sB8D9kFCmzl7IngNH8A8IJEuWTNSsWpFOrb8kQ3ons2v53Qrgg0/bsHPdEmztbJm9YCm//bGZ20HB5PbypHv7llSpUNZUPzo6mmk/LeL3jVsICr5LVldnGtatTdsWn2IwGIiMimLKzPns3HuIG37+pHdyokK50nRr95VpXwsREUl5MUZ9Hk0oi+8zkT59eubPn8+SJUuoVasW0dHRlg5JRF4hg0dPwufyVbwH98TN1YW1f26hdZf+/LZoBtmyujJ2ykz2Hz6O9+De5HDPxp4Dhxkxbipuri7UqFqB20HB3A66Q8+Orcib2wv/gNsM/+4HAoOCmTByoNm1tuzcx1tvlsDR0YHx037i9z+3MrRPZ/LkysnuA4fp0u9bfp4xjiIF8wPw08+/snT1OkYO7EH+PLk4fe4CA0dOIH16J75o3IBHjyI4c/4SbVt8SqH8eQkJDWX0pBl07DOMZXMmW+LHKSIi8lJSzdKwTZs25dChQ6xcuZJcuXJZOhwReQU8iohg8/ZddO/wNWVLFcfL04MOX3+Bl6cHS1etA+DYybM0qFOLt94sQQ73bDRuUJdC+fNy8mzsDtYF8uZm4qiBVK9SAS9PD8qXKUXnNs3Ztns/UVHmX25s3bmX6lUqALB2wxZaf/kJb1d6i5w53Gn64f+oWrEc8xavNNU/duosNapWoFqlt8jhno13a1Sl0ltvmu2ePXvSKN5/523y5PKkZLEi9O/enjPnL+J/63ZK/AhFRET+k1STTAB4enrSoEEDnJyc/r2yiKR50VHRREfHYG9na1Zub2/HkROnAShVvAhbd+0jIDAIo9HIgcPHuep7k0pvvfncdkMfhJHeyREbG2tTWUjoA46cOE2Nv5OJx5GR2NnZmZ1nb2/H0b+vC1CqWBH2HzrGVd8bAJy7eJkjJ05T9ampUM968CAcg8FAhgx6HRQRsRSj0ZBqH6mNxac5iYgklpOTIyWLFWH6vMXkzeWFi3Nm1m/ezvFT5/DK4Q5A/27tGTpmMu80bIaNtTUGKwND+3ShbKni8bZ59959ZsxbzMf165iV79x7kIL58pjuZahcvgwLlqykbKli5Mzhzr5Dx/hr+x6iY56MZrRq1oSw8HA++KwN1lZWRMfE0LlNc/73Xk3iExHxmAk/zqFurWqk15cqIiLyClAyISKvNO9BPRnsPYGaDb/A2tqKIgXzU6dWNc6c9wFg0fI1nDh9jh/GDME9ezYOHzvJyHHTcHN1oWK50mZtPQgL45teQ8iXx4tvvv7C7NiWnftMoxIAfbu0ZeiYyXzwWRsMBsjp4U7DerVZ9ftGU50NW3bw+8atjBnam/x5cnHu4mXGTJqBm6szDerWNms/MiqKHoNGYTQaGdSrY1L/mERERJKFkgkReaV5eXowb+p3hD98RFhYOFldnekxyBtPj+w8iohg0oz5TPIeRLVKbwFQKH8ezl28zLzFK8ySibCwcNp2H4STowOTRg3C1ubJy2NkZCS79x+i9ZefmMqcs2Rm8ujBREQ85l5ICG6uLkz4cQ6eHtlNdcZN/YlWXzShbq3qABTMlwf/W7eZvXCZWTLxTyLhF3CbOZNHa1RCRMTCjDGpbzpRapWq7pkQEUksR4d0ZHV15n5IKHsOHKZm1QpERUURFRWF1TNLTltbWxET82R70wdhYbTpNgBbWxumjBmCvb35vRAHjpwgY4b0FC6QN8517e3tyJbVlajoaDZt202NqhVNxx49isBgZX5tKysrYp7aK/SfRML3uh+zJ44ic6aM/+nnICIikpI0MiEir7Td+w9jNBrJ7eWJ7w0/xk39iTxenjSs9y62NjaULV2ccVN/wt7eHo/sbhw6epI1f/xFr86tgb8Tia4DeBgRwaTBvQgLCycsLByALJkzYW1tzbZd+02rOP3jxOlzBAQGU7hAXm4HBjNtzs8YjUZafv6xqU71yuWZNX8J7tncyJ8nF2cv+LBg6Uo+rPcuEJtIdB8wkjMXfJg6dhgxMTEEBd8BIFPGDNjamt9YLiIiktoYjManviJ7TdjY5bB0CCKSTB767TR7vuGvHUycPpeAwCAyZcxA7WpV6Ny2uWnDuaDgO0ycPo89B45wPyQUj+xufNygDl9+8iEGg4EDR07QslOfeK/15/J55HDPRq1GX/Jtv25m06IOHj3Bt9//wA2/Wzg6OFC1Yrk4m809u6FeVldn6tauTvuvPsPW1pab/gG893GLeK89Z8oY3nqzhOm5g0fVxP7IRERSpajHNy0dwnOdLVDX0iE8V5GL6y0dghklEyLySnk2mUhuZ8778HXnvuxYt8TsPoqUpmRCRF43SiYSJ7UlE7pnQkTkBaKjo+nXrb1FEwkREZHUSu+OIiIvULxoIYoXLWTpMEREJAVpNaeE08iEiIiIiIgkipIJERERERFJFE1zEhERERF5SoxR05wSSiMTIiIiIiKSKAkamVizZk2CG6xfv36igxERERERkVdHgpKJhg0bJqgxg8FAdHT0f4lHRERERMSijJrmlGAJSiZiYmKSOw4REREREXnF6J4JERERERFJlESt5hQWFsb27dvx9fXl8ePHZsc6d+6cJIGJiIiIiFiC0WjpCF4dL51MHD16lLp16xIeHk5YWBjOzs4EBQXh6OiIm5ubkgkRERERkTTipac5devWjQ8++IC7d+/i4ODAvn37uHbtGmXKlOH7779PjhhFRERERCQVeumRiWPHjjFjxgysrKywtrYmIiKCvHnzMnbsWJo3b06jRo2SI04RERERkRShTesS7qVHJmxtbbGyij3Nzc0NX19fADJlysT169eTNjoREREREUm1XnpkonTp0hw8eJACBQpQrVo1Bg8eTFBQEAsXLqRYsWLJEaOIiIiIiKRCLz0yMWrUKNzd3QEYOXIkWbJkoX379gQGBjJz5swkD1BEREREJCUZjYZU+0htXnpkomzZsqb/dnNzY8OGDUkakIiIiIiIvBq0aZ2IiIiIiCTKS49M5MmTB4Ph+UMsly9f/k8BiYiIiIhYkjatS7iXTia6du1q9jwyMpKjR4+yYcMGevXqlVRxiYiIiIhIKvfSyUSXLl3iLZ86dSqHDh36zwGJiIiIiMh/t2PHDr777jsOHz6Mv78/q1atomHDhqbjLVq0YP78+WbnvPfeey91T3SS3TNRp04dVqxYkVTNiYiIiIhYRIzRkGofLyMsLIySJUsyderU59Z5//338ff3Nz0WL178Utd46ZGJ51m+fDnOzs5J1ZyIiIiIiPwHderUoU6dOi+sY29vT/bs2RN9jURtWvf0DdhGo5Fbt24RGBjItGnTEh2IiIiIiIi8WEREBBEREWZl9vb22NvbJ6q9bdu24ebmRpYsWahZsyYjRozAxcUlwee/dDLRoEEDs2TCysqKrFmzUr16dQoXLvyyzSWLKm5FLB2CRRy5mzZX0gqPjPj3Sq+hJu5vWToEi3DwqGrpECziod9OS4dgEYtLDrZ0CBbRMnCrpUOwiGxOmS0dgkUstHvD0iHIM1Lj5nD/8Pb2ZtiwYWZlQ4YMYejQoS/d1vvvv0+jRo3IkycPly5don///tSpU4e9e/dibW2doDZeOplITKAiIiIiIvLf9evXj+7du5uVJXZUomnTpqb/Ll68OCVKlCBfvnxs27aNd955J0FtvPQN2NbW1ty+fTtOeXBwcIIzGBEREREReXn29vZkzJjR7JHYZOJZefPmxdXVFR8fnwSf89IjE8bn7OIRERGBnZ3dyzYnIiIiIpKqvOyqSa+LGzduEBwcjLu7e4LPSXAyMXnyZAAMBgOzZ88mffr0pmPR0dHs2LEj1dwzISIiIiKS1j148MBslOHKlSscO3YMZ2dnnJ2dGTZsGB999BHZs2fn0qVL9O7dm/z58/Pee+8l+BoJTiYmTJgAxI5MTJ8+3WxKk52dHblz52b69OkJvrCIiIiIiCSfQ4cOUaNGDdPzf+61aN68OT/++CMnTpxg/vz53Lt3Dw8PD959912+/fbbl5o2leBk4sqVKwDUqFGDlStXkiVLlgRfRERERETkVRH/pP5XT/Xq1Z97iwLAn3/++Z+v8dL3TGzdmjaXqxMREREREXMvvZrTRx99xJgxY+KUjx07lsaNGydJUCIiIiIikvq9dDKxY8cO6tatG6e8Tp067NixI0mCEhERERGxlBijIdU+UpuXTiYePHgQ7xKwtra2hISEJElQIiIiIiKS+r10MlG8eHGWLl0ap3zJkiUULVo0SYISEREREZHU76VvwB40aBCNGjXi0qVL1KxZE4C//vqLX375heXLlyd5gCIiIiIiKcmYCqcTpVYvnUx88MEHrF69mlGjRrF8+XIcHBwoWbIkW7ZswdnZOTliFBERERGRVOilkwmAevXqUa9ePQBCQkJYvHgxPXv25PDhw0RHRydpgCIiIiIikjq99D0T/9ixYwfNmzfHw8ODcePGUbNmTfbt25eUsYmIiIiIpLiYVPxIbV5qZOLWrVvMmzePn376iZCQEJo0aUJERASrV6/WzdciIiIiImlMgkcmPvjgAwoVKsSJEyeYOHEifn5+TJkyJTljExERERGRVCzBIxN//PEHnTt3pn379hQoUCA5YxIRERERsRgjWs0poRI8MrFr1y5CQ0MpU6YM5cuX54cffiAoKCg5YxMRERERkVQswclEhQoVmDVrFv7+/rRt25YlS5bg4eFBTEwMmzZtIjQ0NDnjFBERERGRVOalV3NycnKiZcuW7Nq1i5MnT9KjRw9Gjx6Nm5sb9evXT44YRURERERSTIwx9T5Sm0QvDQtQqFAhxo4dy40bN1i8eHFSxSQiIiIiIq+A/5RM/MPa2pqGDRuyZs2apGhOREREREReAYnaAVtERERE5HUVo9WcEixJRiZeRw2b12fJ3p/Z6LOeaWunULhUoRfWT5/RiS4jOrHi8FI2XlrPwh3zKF/zLdPxWh/WZNmBX1h7ahXfDG5ndm52z2ws3DEPx/SOydKXl9G6TTNOntnB7eCzbNm2kjJlSjy3buEiBVi4aBonz+wgJOwy33T4Kk6dJp804Mz5XVy7cZRRoweYHfPyysGRY3+RIUP6JO+HJEztL+swadcM5p1fyvDVY8hX8sXLPr/f8n98v+UH5p1fwpS9s/hi0FfY2tuajldu+DZT9s5i1omFfDHI/N+Dq2dWxm2dikN6h2TpizwRFhbO6InTqd2oOWVqNODztt05efa86fiAEeMoVrmO2aNt94EJbn/2wmUUq1yH0ROnm5WPnTyTSu835p0Pm/H7n1vMjv25ZScdeg/5bx17SW7lC1FjXnc+PjyFL2/+TM73yry4frmCvL96MJ+c+pHPfObQYPtYirR+36xOng8r8dHBSXxyegZlh3xudszJ05WGO7/DVv/GLap5q0/Zd3wjl/yPsHbTYkq9Wfy5dT/78mNWrl/A6St7OH1lD0tWzY5Tv23HFhy/sIPjF3bQtkNzs2OlyxTnj63LsLa2Tpa+JETmCkUosbAPlY9Pp2bAMlzrlPvXcwx2NuTt15RKh6ZS3XcRFQ/+gPunNUzHs7xdnAp7JvK2zzyK/tARg+2T/llncKDCnomk83RNlv7Iq0cjE/Go8UF1vhncjvH9JnH26Fk+bvUR3/08mmbVvuJe8L049W1sbfj+l7HcDb7HkLbDCboVRDbPbDy4/wCATFky0uu7Hozu9h1+vv6Mnj+Co7uPsvev/QB0HdWZmd6zCX8QnpLdjKPRR/UYNbo/XbsM4tDBY3zT4StW/jafMqVrERQYHKe+o4MDV6/6snrVerzHxP0g4uyShSlTvWnfthdXr1zn15Wz2bFtLxs2xH7IGD/xW4YMHkto6INk75vEVeF/lfli4FfMGTAdn2MXqNPyA/ouHEyPGh0JCb4fp36lBlVp2qcZM3v/wIXD53DP40G7cZ0B+PnbuWTIkoHWY75heo8p3PYNoNfcgZzefZKjWw4B0HJEW5aMWcjDBw9TtJ9p0eDRk/C5fBXvwT1xc3Vh7Z9baN2lP78tmkG2rLEfAKpUKMuI/t1M59ja2j6vOTMnz57n19/WUzB/HrPybbv2sW7TNmZOGInvDT8GjZpA5fJlyJI5E6EPwpg8cz6zJ45Kuk4mgI2jPXfP+OKzZAc1fur6r/WjwiM4N3cTd8/6EhUegdtbhagw5iuiwiO4uGgr9lnSU/G7VuzpPoPQa4HUXNAD/92nubn5GADlR7XgyKilROrfuMXU//B9hozoTd/uwzh6+CSt2jVj0YoZvF3ufwQH3YlTv2KVcvy2Yj2H9h/jUUQEHbp8zS8rZ1KzYgNu+d+myBsF6dWvI82bdsBggHlLprF96x7OnbmItbU1o8cPoXfXoURHR1ugt7GsHO15cPoqfr9socS8Xgk6p9isbthlzcTZ7tN5eOUWdtkyYzD8/f2ywcAbP3bh2uRV3Nl2nGKzu+PRrBY35/wJQL6Bn3Nz/iYe3dD2ABJLIxPxaNzmI9YtXs+GZX9y7aIv4/tO5NGjCOo2fT/e+nU/eZ8MmTMw8OvBnDp0mls3Aji+7wSXzl4GwD2XO2EhYWxdu43zx89zdM9xvArkAqBmgxpERUaz849dKdW95+rY6Wvmz13KooXLOX/Oh66dB/Lw4UOafdk43vpHjpxg0IDRrFj+OxERj+Mcz5M7JyEhoaxcsY4jR06wY/s+ChbOB8DHjT8gMjKStWv+TNY+yfPVbVWfrUs2sf3XLdy8eIOf+k8n4mEE1Zq8E2/9gmUKc+HwOfb8tpOgG4Gc3HmcPWt2mkYz3LyyEx4Szr7fd3P5hA9n9p4kRwFPACrWr0JUZDQHN+xLsf6lVY8iIti8fRfdO3xN2VLF8fL0oMPXX+Dl6cHSVetM9exsbXF1cTY9MmXM8K9th4c/pO+w7xjapwsZnxlRvHztOuVKF6dYkYLUrV0dJydHbvjfAmD8tJ/4pGE93LO7JW1n/4Xf1hMcG7uc6xsOJaj+ndPXuPrbXu5fuEnYjSCurNyN37aTuJWPHZlOn8uNyNBwrq7ZT/DxywTsOUvm/DkAyN2gIsaoaHz/SNi1JHm0/qY5vyxYzrJfVnPx/CX6dh/Gw/BHNP2iUbz1O7Xpw/yflnD61DkuXbxCz86DsTJYUeXtCgDkL5CHs6cvsHvnfnbt2M/Z0xfIXyA2kW7f+Sv27TnE8aOnUqx/8bmz5RiXRy8l6I+DCarvXKMkmSsW5fhn3tzdcZJH1wMJOXSR+wdjRy9tXTJg55qRm/M2Enb+BkF/Hsbp79fyjGULkrFUPq7PWp9s/UktjBhS7SO1UTLxDBtbGwoVL8jhnUdMZUajkcM7j1D0zaLxnlPp3YqcOXKGriM7s/Lor8zdPIvPO36KlVXsj/fGlZvYO9iT/438ZMicgcIlC3H57GXSZ0rP171aMGnglBTp24vY2tpSqnQxtm7dbSozGo1s27qbt94qnag2L126ioNDOkqULEqWLJl4s0wJTp86R+bMGRk4qBs9uw9NmuDlpVnb2pCneD5O7TpuKjMajZzadYICb8Y/pe/C4XPkKZbvSfKQMxulapTh2NbDANy64oedgz253siDU6b05CuZH9+zV3HK6ETjHp8xb/DM5O+YEB0VTXR0DPZ25iMN9vZ2HDlx2vT84NETvF2vKf9r2orh303h3v2Qf217xLipvF2xHBXLxX1NKJQ/L6fPXeR+SCinz10kIiICrxweHDl+ijPnffi88au3dLjzG7lwK1uAgL3nAAi9cgtrB3uc38iFXWYnXErm5e5ZX+wyOVKq18fsHzjfwhGnbba2tpQoVZSd2/aayoxGI7u276NMuZIJasPBMR02tjbcuxc7Onv2zEXy5M+Nh6c7OXK6kzd/Ls6d9SFX7px88tmHjB05OVn6kpxc3ytL6PFL5OrYgMrHplNhz0TyD2mGVbrY14zIoBAibt3BuXoJrBzsyFyhMA/OXMNgY02hsa0432tm6lyfVCxG05yekck5E9Y21twJvGtWfjfoLl75c8Z7joeXO9krlWbT6r/o+2V/cuTOQddRnbGxtWH+hIU8uP8A725j6T+pD/bp7Ni4YhMHtx+i1/c9WDX3N9y9sjNq7rfY2Fgzb8ICtq/bmRJdNePikgUbGxsCb5sPW96+HUTBgvkS1ea9eyG0a9OLGbPG4ZDOniW/rOKvzTv5YdpoZs5YSK7cniz5dSa2tjZ4j5zMb6v/SIquSAJkyJIBaxtr7geZT2e6H3QPj3w54j1nz287yZAlI0OWjwSDARtbGzYv3MBvU1cAEBYSxvQek2k/vgt26ezYuWIbJ3Yco/XYDmycvx63nNno+VN/rG1sWDFxCQfW7433OvLfODk5UrJYEabPW0zeXF64OGdm/ebtHD91Dq8c7gBUrlCGWtUqk8MjG9dv+jNpxjza9RjEohnjnzv3e/3mbZy9cIklsyfFe7xy+TL8772aNG3VhXT29owc2ANHh3R8+/1URgzoztJV6/hl+RoyZ87E0N6dyZ83V7L9DP6rjw5NJp1zBgw21hwfvxKfxdsAeHw/nN1dZ1B5Ujus09lxefku/LafpOL3rTg/byPpc2al5tzupvN81yXsm2JJGs4umbGxsYkzLTcwMJh8BfI85yxzA4b2IODWbVNC4nPhMmO+nciSlbMAGD18Ij4XLrNk1WxGDBlH9ZpV6N73G6Iioxjcz5v9ew4nbaeSgUOubGR6qzAxEZGc+Oo77JwzUnD019hmSc/Zrj8CcKr1BAoMb06BEV8RvPko/ou3kqtTQ+7tPk1MRCRvrh2OrXNGbvz0h2n6k6RdSiaSgMHKirvB9xjXewIxMTFcOHkR1+wuNG3XhPkTFgKwa8Nudm148q1/yQolyFc4L5MH/sCiXfP5tuMo7ty+w4+/T+X4vpPx3pvxKvp97UZ+X7vR9LxylbcoVqwwvXoM5djJrbRs0YWAgEC2bl/N7t0H4r03Q1KHIhXeoEGHj5gzaCaXjl4gW253vhzyNR92bsyqyb8CcOjP/Rz6c7/pnMLl38CrcC7mD57FhB0/MqXTeO4H3uXb38Zybv+ZeO/NkP/Oe1BPBntPoGbDL7C2tqJIwfzUqVWNM+d9AKhbq7qpbsF8eSiYLw91mrTk4NETVCgbd9TBPyCQ0RNnMGviKOzt7Z573Q5ff0GHr78wPZ82ZxEVypbCxsaGGfOXsGrBNLbvOUD/Ed+zbI7lR2Sf588Pv8XGyZ6sb+bnzf6fEHolgKu/xX64vL7hkNm0qWwVCpOliBcHBi7gw93j2NlhKg8D71P392Hc3neeR8H/PuIjqUOHrq2o36gOjT9oYTZ1d+HcZSycu8z0vHHTBjx4EMbhg8fZcfB36tX8BHeP7Eyb/T0VS73L48eRlgg/wQxWBjDC6faTiQ6Nvb/HZ8gCiv3UnfN9ZxPzKJL7B85z6P3+pnMc8rqTvcnbHHynN2/+Nozrs/4geMtRym8fx719Zwk742up7iSbGEsH8ApRMvGM+3fuEx0VjXPWLGblWVyzcOf23XjPCb4dTHRkNDExT/7pXfPxxSWbCza2NkRFRpnVt7WzpevIzozqMpoceTywtrHm+L4TANy4fIMipQuzd3PKzi0PDr5LVFQUWd3MV2dwc3MlICAwSa5hZ2fH+AnDadO6B3nz5cbGxprduw4AcMnnCmXLlmTDH1v+pRVJCqF3Q4mOiiaTayaz8kyumbkXeC/ecxr3+Ixdq7azbclmAK6f98XeMR2tvNuzespyjEbzYW8bOxtajmjDtG6TyJbbHStra87tj51m43/Fj/ylCnDkL80vTw5enh7Mm/od4Q8fERYWTlZXZ3oM8sbTI3u89XPmcCdL5oz43vCPN5k4c/4id+7eo0nLjqay6OgYDh87xeKVazmydU2cEY3L167z+59bWD73B1au20jZUsVwzpKZ92q+zaBREwgLC8fJyfIr2MXnwfXY17x7526QLmsmSvZoZEomnmZlZ0P5US3Y1Xk6GfJkw2BjRcC+2ClRIZdv4fpmPm5sOpqisadld4LvERUVhWtWF7PyrFld4oy6P6ttxxZ06Po1TRu24uzpC8+tl8U5M936tOejes0pXbYEl32uceWyL1cu+2Jra0Pe/Lk5d+ZikvQnuUQE3CPi1h1TIgEQdvEmBisr7N1deHjlVpxzCn/fGp+hC8DKigwl8nJ77V5iHj7m3p4zZKlY9LVMJiThdM/EM6Iiozh/8gJvVnnTVGYwGChTpTRnjpyJ95xTB0+TI7cHBsOTm2Jy5vUk6FZQnEQCoFnnzzmw7SAXT/lgZWWNtc2TN2EbW2usrVP+1xIZGcmxo6eoXr2SqcxgMFCteiUOHEiaN8PefTqwefMOjh87jbW1FTbWT3JZG1sbiy6tl9ZER0Zx5eQl3qj8ZOlfg8HAG5WLc/HI+XjPsXewN0uYAWL+WcHEEPeGsA87Neb49qNcPXUZK2srrG2e/Lu2trHBygL/ztMaR4d0ZHV15n5IKHsOHKZm1Qrx1rt1O5B790PJ6uIc7/EKZUqxauGPLJ831fR4o3AB6r1bg+Xzpsb52zUajQwfO5nenVrj6OhATHQMkVGxr4VRf/9/dMyr8b2fwWDA2i7+791KdGnIzW0nuHPqKlZWVlg99XOwsrXGYKV/4ykpMjKSE8fOUKXak3/nBoOBKm+X5/DB4889r33nlnTt1Y4vPm7LiWOnn1sPYNioPsyatgB/vwCsraywtX3yb8Paxhprq9T/Pnb/4Dnss2XB2tHeVOaYzx1jdAwR/nFnB7h/VoPIu2EE/XkYw9+v24a/P7cYbG1Ar+VpnkYm4vHrzBX0m9Cb88fPc/bYeT5u1Yh0Dun4Y+kGAPpN7EPQrSBmjf4JgN8WrOXDFg3oNLwDK+eswjOPJ593/IyVc1bFaTtXAS9q1K9O6/di95rwveSLMcZI3abvc+f2XbzyeXHuePwf5pLbD1N+YvrM7zl69CSHDh3nmw5f4ejoyM8LlwMwY9b3+PkFMGzId0DszW6Fi+QHwM7OFnePbBQvUYSwB+FcvnzNrO1ChfPT6KP/UaXS/wC4cP4SMTExNPuyCbcDAilYMB9HDp9Iwd7K+tlraDeuM5dPXOLS8YvUafk/0jmmY/uvfwHQfnxn7ty6w9KxPwNwZPNB6rSqz7XTV/A5doFsudxp3OMzjmw+iPGZD4Y5CnhS4X9V6F+3OwB+Pjcxxhip/sk73AuMvS/j0nGflO1wGrJ7/2GMRiO5vTzxveHHuKk/kcfLk4b13iU8/CHT5iyidvXKuLo4c/2mH+OnzcHL04PK5Z98ifJ1576883YlPvu4Pk5OjhTIm9vsGg4O6cicMUOccoAVazeQJXMmqleJ/VBXukRRps35meOnzrJz3yHy5faKsxpUcrBxtCdDnmym5+m9spLlDS8e3w0jzC+Y0n2b4Oiehd1dZgBQqHktwvyCue/jB0C28oUp2q4e5+KZE56pgAe565fn93djl8W+f8kPo9FI/qbVeBh4n0z53Ak6fjnZ+yjmZk2bz4Rpozhx9DRHj5ykdftmODg5sHRR7PvxpB9H4e9/m9HDJwLwTZev6dmvIx1b9+a6r59pdD4sLJzwMPPl2qtWr0iefLnp0j52+s/xo6fIVyAPNWpVwSOHOzHRMVzyuZJynf2btaM9DnmejDo6eLmR/o1cRN57QMTNYPIO+BT77M6c7TQVgIAVu8jd7SOKTPqGy98tw845I/kHf4H/4q3EPDKfomXrmpHc3T7i8P8GARB1P4yw8zfI2aYed7YfJ0vVYlyduDLlOpuCUuOqSamVkol4bF27jcwumfiqZwucs2bB58wlejfrx92gewBky+Fm9uEp0D+QXp/3pePQb5izaRaBt4JY8dNKFk9bGqftnmO6M23Yjzx6+AiAx48eM7rbWLqM7IydnS2TBk0h6JZl7htYuWIdrq7O9B/YjWzZXDl54iwfNWxhGh729PQw+2ba3d2N3XufLDXZpWsbunRtw84d+6hX5zOztidPGUX/viMJD48dVn30KIL2bXvz/YRh2Nvb0bP7EPz9A1Kgl/KPfb/vJqNLRj7u3pTMWbNw7cwVRn85nJC/b8p28chKzFMrdqya8itGo5HGPT/DObszIcEhHPnrEMu++zlO2628v+Hnb+cS8TACgMiIx0zvMYUW37bG1s6WeUNmcTcg7prvkjRCH4QxcfpcAgKDyJQxA7WrVaFz2+bY2tgQHR3NhUtXWPPHZkIehOHm6kylt96kY+svsbN7cj/E9Zv+3E3ACk/PCrpzl5nzl/Dz9PGmsuJFC9G8aSO+6TUE5yyZGTWwR5L089+4lMzLe8ufbJZZbmjs/Rw+y3awp9tMHLJlxsnjydROg5WB0n2bkN4rK8aoGEKv3ebIqCVcWBh3+mXFsV9zcNgiov7+Nx79KJLd3WZQfmQLrO1s2D9wAQ9vxT81VpLPmlUbcHZ1pmf/jmR1c+X0yXN88XFb0/14Hp7uZq9rX7b8BHt7O2YtmGjWzrjRUxk/Zprpebp09owcO4D2LXuapnT6+wUwqM8oxv8wksePH9P1m/48ehSR/J18RoZS+Xhz1VDT8wLDYzfW81+yjbNdpmHvloV0OZ78O48Oj+BYkxEUHNWScn+OJvJuKLfX7OXy6CVx2i444it8f1zL44An/5bPdJlK0ckdyNmqDr5T1xB67FLydU5eCQbjsxOdXwPVPWtZOgSLOHI3bX4LFh6Z8i/eqUET97f+vdJraJn/AUuHYBEP/VJ+lbfUYHHJwZYOwSJaBm61dAgWkc0ps6VDsIiFdm9YOgSLqBmw7N8rWcjGbE0tHcJzvRsQN/GzJI1MiIiIiIg85dW4qyt1SFXJRFhYGMuWLcPHxwd3d3c+/fRTXFxcXnhOREQEERHm30zHGGOwMuiGIBERERGR5GTRT9xFixblzp3YedPXr1+nWLFidOvWjU2bNjFkyBCKFi3KlSsvvpnJ29ubTJkymT18Q6+mQPQiIiIiImmbRZOJc+fOmZYJ7NevHx4eHly7do0DBw5w7do1SpQowYABA17YRr9+/bh//77ZwytD7hSIXkREREReRzGp+JHapJppTnv37mX69OlkyhS7iVb69OkZNmwYTZu++AYYe3t77O3tzco0xUlEREREJPlZPJn4Z6O3R48e4e7ubnYsR44cBAYmze7LyalF9y9p0f1LszJfH1++rN7SQhGljEqVy9GlaxtKlS6Gu3s2Pv2kLet+32TpsCSZTNo1g6w53eKUb1zwB/MGzbRARGlXdHQ0035axO8btxAUfJesrs40rFubti0+Nb2mDhgxjt/+2Gx2XuXyZZgxfoTp+Yz5i9mx5yDnL17G1taGvX8uj/d6frcC+ODTNuxctwRHRwcWLl3F0lXr8A8IJHPmjLxbvQpd232FvX3s0rJhYeFMmbWAv3bs5c7dexQumI++XdtSvEghACKjopgycz479x7ihp8/6Z2cqFCuNN3afYVb1hffJ5fU3MoX4o329XApngfH7FnY2nIC1/88DMRuzFW698fkqFmK9LmyEhnyEP9dpzgyaikPA+6laJySPDp2a0Wd/9Umf4E8PHr0iEMHjjFq6Hgu+Vy1dGhJKnOFInh1qE+GEnmwz+7MiRbfEfTHwXjrFhrbmhzNa3Nh0DxuzFyfwpHKq8jiycQ777yDjY0NISEhnD9/nmLFipmOXbt27V9vwE4trpy7Qo9Pe5ueR0dFWzCalOHk5Mipk2dZuOBXflky3dLhSDIbWL+X2a7VOQt60f+XYexft9uCUaVNP/38K0tXr2PkwB7kz5OL0+cuMHDkBNKnd+KLxg1M9apUKMuI/t1Mz21tbc3aiYyM4r0aVSlVrAgrf4+7Mds/tuzcx1tvlsDR0YF1G7cyYfpcvu3XjVLFi3LV9wYDR47HYDDQu3MbAAaPnoTP5at4D+6Jm6sLa//cQusu/flt0QyyZXXl0aMIzpy/RNsWn1Iof15CQkMZPWkGHfsMY9mcyUn803oxG0d77p7xxWfJDmr81NX8mIMdzsVzc2LSau6e8cUukyPlhjWjxtzurK+bNpesfd1UqFSO+bMXc+zoSWxsbOg7qAu/rJxF9Qr1efj3vkivAytHex6cvorfL1soMa/Xc+u51ilHxjIFiPDXPkDatC7hLJpMDBkyxOx5+vTmO6KuXbuWqlWrpmRIiRYdHc2dwLS1QdGmjdvZtHG7pcOQFBJ6x3wDs/rtG3Hrqj9n9522UERp17FTZ6lRtQLVKsXuNZLDPRvrN23n5JnzZvXsbG1xdXF+bjsdWzUDYPW6F48obt25l3drxL4WHzt5ltLFi1Lv3Rqma9etXZ0TZ84B8Cgigs3bdzF59BDKlioOQIevv2D77v0sXbWOzm2akyG9E7MnjTK7Rv/u7fm0VVf8b93GPXvcEbDk4rf1BH5bT8R7LDL0IZs/HWNWdmDgAuqtH46ThwthfpbZYFSSzheN25o97/rNAE767KJEqaLs33PYQlElvTtbjnFny7EX1rHLnoWCo1pyvOlISvzcN2UCk9dCqkomnvXdd9+lUCT/XY48OVh+aAmPIyI5feQMs7x/4rbfbUuHJZIsrG1tqPJhNdbPXmPpUNKkUsWKsHzNH1z1vUFuL0/OXbzMkROn6d2ptVm9g0dP8Ha9pmTMkJ63ypSkc5vmZM6U8aWuFRL6gCMnTuM9KPbbzFLFi/D7xi2cPHOe4kULcf2mPzv2HuSD92oCsaOy0dEx2NuZj4LY29tx5MTzE88HD8IxGAxkyOD0UvGlNLuMDhhjYngcEm7pUCQZZMyYAYB7d+9bOJIUZjDwxtRO+E5bQ9j5G5aORl4xFp/m9Do4c/Qso7t9x/XL13Fxc6F5t2ZMXjmBr95pxcOw12eYVOQfZd99C8eMTmz/dYulQ0mTWjVrQlh4OB981gZrKyuiY2Lo3KY5//v7Az1A5QplqFWtMjk8snH9pj+TZsyjXY9BLJoxHmtr6wRfa+fegxTMl8d0L0O9d2tw934Izdr3BKORqOhomjSsS5vmsYtlODk5UrJYEabPW0zeXF64OGdm/ebtHD91Dq8c7vFeIyLiMRN+nEPdWtVI75R6kwkre1ve7N+UK6v3EvlAr+2vG4PBwDDvPhzYd4TzZ30sHU6KytWpAcaoaG7M+sPSoaQaMZrllGBKJpLAga1PbmK6fPYKZ4+eZcm+X6jxQTXWL9lgwchEkkeNT2pxfNsR7t1OW1P7UosNW3bw+8atjBnam/x5cnHu4mXGTJqBm6szDerWBqBureqm+gXz5aFgvjzUadKSg0dPUKFs6QRfa8vOfdSoUsH0/MCRE8xasJSBPTpQ4o1C+N7wY/SkGUyf+wvtvvoMAO9BPRnsPYGaDb/A2tqKIgXzU6dWNc6cj/sBLTIqih6DRmE0GhnUq2MifyLJz2BjTbXpncBgYH+/eZYOR5LBqO8HUqhIAT6s08zSoaSoDCXy4Nm6Lgdr9bF0KPKKUjKRDB6EhHHj8g1y5M5h6VBEkpxrjqwUq1KCCW3HWjqUNGvc1J9o9UUTU8JQMF8e/G/dZvbCZaZk4lk5c7iTJXNGfG/4JziZiIyMZPf+Q7T+8hNT2Q+zFvDBezX5uP77pms/fBTBsDGTadO8KVZWVnh5ejBv6neEP3xEWFg4WV2d6THIG0+P7Obt/51I+AXcZs7k0al2VOKfRMLJ04VNTbw1KvEaGjF2ALXeq0ajus3x9wuwdDgpKlOFIti5ZqTSkWmmMisbawoM/ZKcreuyt1zqTfIldVAykQwcHNPhkdudjSt1c568fqo1rsn94Psc3XLI0qGkWY8eRWCwMh+Dt7KyIsZofO45t24Hcu9+KFlfcEP2sw4cOUHGDOkpXCDvk2tHRGD1zLWtrWJX+TI+c31Hh3Q4OqTjfkgoew4cpvs3T5bL/ieR8L3ux5wpo1/6Xo6U8k8ikSFPNjY2HkXE3QeWDkmS2IixA3i/3js0/qAF131vWjqcFHfr1x3c3XHSrKzUkgHcWr4D/8VbLRSV5cVoNacEUzKRBNoPbMOezfsIuBGASzYXvurRnJjoGP5a/Xr/ETo5OZI3Xy7T89y5c1K8RBHu3rnPjRt+FoxMkovBYODtxjXZuXwbMdGpcR/OtKF65fLMmr8E92xu5M+Ti7MXfFiwdCUf1nsXgPDwh0ybs4ja1Svj6uLM9Zt+jJ82By9PDyqXf9PUjv+t29wPCcU/4DbR0TGcu3AJAC9PDxwdHdi2az/Vn5riBFCtcnkWLFlJ4YL5KFG0ML43/JgyawHVKpc33Yuxe/9hjEYjub088b3hx7ipP5HHy5OGf8cXGRVF9wEjOXPBh6ljhxETE0NQcOxSlJkyZoizhG1ysnG0J0OebKbn6b2ykuUNLx7fDSP89j2qz+yMc/HcbGk+DoO1Femyxm6s+vjeA2IiX/8lwF93o74fRMOP69Lys048eBBOVjdXAEJDQnn0KMLC0SUda0d7HPI8GRl08HIj/Ru5iLz3gIibwUQ9kyTHREYRcfse4Zf8UzpUeQUpmUgCWd2zMuiH/mTMkpH7d+5z8sApvqnfift3Xu/VIEq/WZz1GxabnnuPGQjAop+X075t7+edJq+wYlVKkNXTjW3L/rJ0KGla/27tmTJrASO+n8qdu/fI6upM4wZ1af/3PQtW1lZcuHSFNX9sJuRBGG6uzlR66006tv4SOzs7Uzs/zF5otrHdx1/FTmeYM2UMb71Zgq279/Ftv25m127bPHZjvCkzF3A7MJgsWTJRvXJ5OrdpbqoT+iCMidPnEhAYRKaMGahdrQqd2zbH1ib2Led2YDBbd+2LvWaLDmbt/3PtlOJSMi/vLR9gel5u6BcA+CzbwfFxK8n5XhkAPthkvpTtnx+PJGDv2RSLU5JH869jFw5YsW6+WXm3bwawbPFqC0SUPDKUysebq4aanhcYHvv36r9kG2e7THvOWSIJYzA+Oy79GqjuWcvSIVjEkbuXLR2CRYRHvj7fHr2MJu5vWToEi1jmf8DSIVjEQ7+dKXq9M+d9+LpzX3asW2JKAixhccm0uTlcy8DXe2T7ebI5ZbZ0CBax0O4NS4dgETUDllk6hOdanf0zS4fwXA1v/WLpEMxY/XsVERFJa6Kjo+nXrb1FEwkREUn99C4hIiJxFC9aiOJFC1k6DBERSeWUTIiIiIiIPEVLjCScpjmJiIiIiEiiKJkQEREREZFE0TQnEREREZGnxBi0aV1CaWRCREREREQSRcmEiIiIiIgkiqY5iYiIiIg85bXb0TkZaWRCREREREQSRcmEiIiIiIgkiqY5iYiIiIg8RZvWJZxGJkREREREJFGUTIiIiIiISKJompOIiIiIyFNitGddgmlkQkREREREEkXJhIiIiIiIJIqmOYmIiIiIPCUGzXNKKI1MiIiIiIhIoiiZEBERERGRRNE0JxERERGRpxgtHcArRCMTIiIiIiKSKEomREREREQkUTTNSURERETkKdq0LuE0MiEiIiIiIonyWo5MPIiOsHQIFpHd0dnSIVjE5fv+lg7BIn4POm7pECQF5S7wgaVDsIirF9daOgSLaOlR1dIhWISTjYOlQ7CIhg8OWToEiwixdACSJF7LZEJEREREJLFiLB3AK0TTnEREREREJFGUTIiIiIiISKJompOIiIiIyFO0aV3CaWRCREREREQSRcmEiIiIiIgkiqY5iYiIiIg8RZvWJZxGJkREREREJFGUTIiIiIiISKJompOIiIiIyFO0aV3CaWRCREREREQSRcmEiIiIiIgkiqY5iYiIiIg8RdOcEk4jEyIiIiIikihKJkREREREJFE0zUlERERE5ClGbVqXYBqZEBERERGRRFEyISIiIiIiiaJpTiIiIiIiT9FqTgmnkQkREREREUkUJRMiIiIiIpIomuYkIiIiIvIUTXNKOI1MiIiIiIhIoiiZEBERERGRRFEy8RyNW3zImgPL2H1lM/PWzeCNUkUSdN67Dd7hkP9Ovp87yqz8i3ZN2XhyDRtPruHztp+YHXujdFEW/jkba2vrJIs/sT5v2Zgth9dw8vpuft0wjxKl33hu3Xfr1WDFpgUc8tnKsas7+W3rIho0rmtWp+U3X7D3zEb2ntlIy/afmx0r8eYbrNy8MFX0O61q3aYZJ8/s4HbwWbZsW0mZMiWeW7dwkQIsXDSNk2d2EBJ2mW86fBWnTpNPGnDm/C6u3TjKqNEDzI55eeXgyLG/yJAhfZL3QxKmeatP2Xd8I5f8j7B202JKvVn8uXU/+/JjVq5fwOkrezh9ZQ9LVs2OU79txxYcv7CD4xd20LZDc7NjpcsU54+ty1L07zssLJzRE6dTu1FzytRowOdtu3Py7HnT8fDwh4wcN413Gn5BmRoNqP95G5auWvfCNlev20SxynXMHm/WqG9WZ+4vy3m7XlPerteUeYtXmB07cfocTVp2IioqOuk6Ki+UVt/H9HqetIyp+JHa6J6JeNSuX5NuQzvi3Wccp46e4dPWjZmyeBwfVfmMu8H3nnueu2d2ugz+hiP7jpmV5y+Sj3a9v6Zrsz4YDAYmLBjDvu0HuXTuMtbW1vQf04ORvb4jOtqybzZ1G9am3/BuDO7lzfHDp2jR9lN+WjaF9yp+xJ2gu3Hq37sbwvQJc7h88SqPIyOp8W5VvCcPJjjoDru27qNQ0fx06dOOtp93xWAwMGPRBHZt28eFs5ewtrZm+Pf9GdR9pMX7nVY1+qgeo0b3p2uXQRw6eIxvOnzFyt/mU6Z0LYICg+PUd3Rw4OpVX1avWo/3mIFxjju7ZGHKVG/at+3F1SvX+XXlbHZs28uGDVsAGD/xW4YMHkto6INk75vEVf/D9xkyojd9uw/j6OGTtGrXjEUrZvB2uf8RHHQnTv2KVcrx24r1HNp/jEcREXTo8jW/rJxJzYoNuOV/myJvFKRXv440b9oBgwHmLZnG9q17OHfmItbW1oweP4TeXYem6N/34NGT8Ll8Fe/BPXFzdWHtn1to3aU/vy2aQbasroydMpP9h4/jPbg3OdyzsefAYUaMm4qbqws1qlZ4brvpnRz5ffGsJwWGJ1vjnve5wtTZPzP1u6EYjUY69BpKpbfepGC+PERFRTP8uykM6dMZGxvLf9hMC9Lq+5hez8WSNDIRj8/bfsLqRWtZu3Q9Vy5cxbv39zx6+Ij6n9Z77jlWVlaMmDqYmd/P4eY1f7NjufN7cfHMJQ7tPsLBXYfxOXuJ3Pm9AGj2zacc2X+cM8fPJWufEuKrdp+z7OfVrFy8lksXrjC4pzePHj7i48/qx1v/wJ7DbFq/jUsXr3L96k0WzFzC+TM+lClfCoC8BXJz/sxF9u06xN6dBzl/xoe8BXID0KpjMw7uPcLJY2dSqHfyrI6dvmb+3KUsWric8+d86Np5IA8fPqTZl43jrX/kyAkGDRjNiuW/ExHxOM7xPLlzEhISysoV6zhy5AQ7tu+jYOF8AHzc+AMiIyNZu+bPZO2TPF/rb5rzy4LlLPtlNRfPX6Jv92E8DH9E0y8axVu/U5s+zP9pCadPnePSxSv07DwYK4MVVd6O/dCdv0Aezp6+wO6d+9m1Yz9nT18gf4E8ALTv/BX79hzi+NFTKda/RxERbN6+i+4dvqZsqeJ4eXrQ4esv8PL0MI0+HDt5lgZ1avHWmyXI4Z6Nxg3qUih/XrPRi/gYDAZcXZyfPJyzmI5duXadgvlyU75MKSqULU3B/Hm4cu0GEDtiUaZUcYoXKZR8HRczafV9TK/nYklKJp5hY2tD4RIF2b/zsKnMaDRyYOchSpR5/lBpq+4tuBN8l98Wxx0y9zl3Ga+8OcmWw43sntnwypuTS+evkCOXBx98UpcfR8+Kp8WUZWtrwxslC7Nn+35TmdFoZM+OA5Qq+/yh0qdVrFqOPPlycXDvUQAunPEhdz4v3HNkw8MzO7nzeXHx7CVy5s5Bo08/YOKoH5OlL/LvbG1tKVW6GFu37jaVGY1Gtm3dzVtvlU5Um5cuXcXBIR0lShYlS5ZMvFmmBKdPnSNz5owMHNSNnt2HJk3w8tJsbW0pUaooO7ftNZUZjUZ2bd9HmXIlE9SGg2M6bGxtuHfvPgBnz1wkT/7ceHi6kyOnO3nz5+LcWR9y5c7JJ599yNiRk5OlL88THRVNdHQM9na2ZuX29nYcOXEagFLFi7B11z4CAoNiX9cPH+eq700qvfXmC9sOf/iQ2o2a886HzejUZxg+l6+ZjhXIl5ur12/if+s2frcCuHb9Jvnz5sL3hh+r12+ic+svk76zEq+0+j6m1/PkEWNIvY/URtOcnpHZORM2NjbcCTQf9r8TeJfc+XPFe07Jt4rT4NN6fFa7ZbzHr168xrTRM5m2ZAIAU71ncPXiNaYuncDkET9SsXp52vT8iqjIKL4fPJmj+44nbacSIItzZmxsbAh6pt9Bt++QN3/u556XPoMTO0/+gZ2dHTHR0QztM8b0Qn7p4lXGj5zG3OXTABg3YiqXLl5l3vKpfDdsMlVqVqRTrzZERUUxYsD3HPr7xVuSn4tLFmxsbAi8HWRWfvt2EAUL5ktUm/fuhdCuTS9mzBqHQzp7lvyyir827+SHaaOZOWMhuXJ7suTXmdja2uA9cjK/rf4jKboiCeDs8s/ft/l0h8DAYPL9PZrwbwYM7UHArdumhMTnwmXGfDuRJStjvwwZPXwiPhcus2TVbEYMGUf1mlXo3vcboiKjGNzPm/17Dr+o+f/MycmRksWKMH3eYvLm8sLFOTPrN2/n+KlzeOVwB6B/t/YMHTOZdxo2w8baGoOVgaF9ulC21PPvHcmdy5Ph/bpRKF8eQsPCmLd4BV+0687qn6eT3S0r+XJ70aVtC1p37Q9Al7YtyJfbi1Zd+tH9m5bsPnCYaT8twsbGmr5d273wWvLfpNX3Mb2ei6UpmfiPHJ0cGD5lICN7jeX+nfvPrbdiwW+sWPCb6Xm9xu8THhbOyUOnWLFrEV/WaYObe1ZG/TiU+uWbEPk4MiXC/8/CHoTToMZnODk5UrFqOfoN78b1qzc58PcHhyXzV7Bk/pMbEj/8pB5hD8I5eugkf+5dwUfvfkl2dzcmzBxFzTL1X5l+S/x+X7uR39duND2vXOUtihUrTK8eQzl2cistW3QhICCQrdtXs3v3gXjn8krq06FrK+o3qkPjD1qYTYlYOHcZC+cuMz1v3LQBDx6EcfjgcXYc/J16NT/B3SM702Z/T8VS7/I4mf++vQf1ZLD3BGo2/AJrayuKFMxPnVrVOHPeB4BFy9dw4vQ5fhgzBPfs2Th87CQjx03DzdWFiuXi/wa3VLEilCr2ZAGOUsWLUv+zNvy6+g86tYkddfjkw3p88uGTabC/rd+Eo6MDJYsV4YNPW7Nk9iQCbgfRa/Bo/lw+Fzs7u2T8KcjL0vtY/PR6LgmlZOIZ9+7cJyoqCueszmblzlmzEHw77h+KZ+4c5PDyYPz80aYyK6vY2WP7rm/loyqfc/Oan9k5mZwz0brHV7T5sCPF3iyK7+XrXL9yg+tXbmBjaxM7Derc5WTo3fPdvXOPqKgoXJ/pt6ubM4Hx9PsfRqMR3yux84PPnrpAvoJ5aNu1helF+GlZnDPRsWdrPqvfhpJvFuPqJV+uXb7OtcvXsbWxIU8+Ly6cvZS0HZN4BQffJSoqiqxurmblbm6uBAQEJsk17OzsGD9hOG1a9yBvvtzY2Fize9cBAC75XKFs2ZJs+GNLklxLXuxO8D9/3y5m5VmzusT5NvNZbTu2oEPXr2nasBVnT194br0szpnp1qc9H9VrTumyJbjsc40rl325ctkXW1sb8ubPzbkzF5OkP8/j5enBvKnfEf7wEWFh4WR1dabHIG88PbLzKCKCSTPmM8l7ENUqvQVAofx5OHfxMvMWr3huMvEsWxsbihTMh+9Nv3iP3713nx/n/sK8qWM5efo8uXLmMD2ioqO4ev0mBfMlbDRIXk5afR/T63ny0KZ1Cad7Jp4RFRnFuRMXeKtKGVOZwWCgXJUynDh8Ok79qz6+fFL9Sz6v1dL02LFxN4d2H+XzWi0J8Lsd55wewzqxeOYybvsHYmVthY3Nk5zO2toaa+uU/7VERkZx+vg5Kr79lqnMYDBQsWo5jh06keB2DFZWz/3Wrf+3PZg3YzEB/rextrbCxvapfttYp4ql9dKKyMhIjh09RfXqlUxlBoOBatUrceBA0gzT9+7Tgc2bd3D82OnY37f1k9+3ja2Nft8pKDIykhPHzlCl2pMViwwGA1XeLs/hg8+fVtm+c0u69mrHFx+35cSxuK9/Txs2qg+zpi3A3y8AaysrbJ/9+7ZKud+3o0M6sro6cz8klD0HDlOzagWioqKIiorCymA+4dja2oqYmIR/bIiOjubipatkdXGO9/iYyTNp1qQh2d2yEh0TTVRU1FPnxhATrY8oySWtvo/p9VwsTSMT8Vg0YylDJ/XnzPFznD52ls9aN8bB0YG1S9YDMGzyAG7fCmLqqBk8jnjMpfNXzM4PvR+7VNqz5QDl3y6LV96cDOk8EoAzx86RK38uKtUsTzYPN2Jiorl2yTeZexi/udMXMWbKUE4dO8OJI6dp3vYzHBwdWLF4LQBjfxhGwK3bjBsxFYC2XVpw8thZrl+9gZ2dLdVqVaZB47oM7e0dp+1K1cqTO58XvTsOAeDE0TPkzZ+Lt9+phLtHNmKiY7jscy3OeZJ8fpjyE9Nnfs/Royc5dOg433T4CkdHR35euByAGbO+x88vgGFDvgNib/IrXCQ/AHZ2trh7ZKN4iSKEPQjn8mXz312hwvlp9NH/qFLpfwBcOH+JmJgYmn3ZhNsBgRQsmI8jhxP+5i7/3axp85kwbRQnjp7m6JGTtG7fDAcnB5YuWgXApB9H4e9/m9HDJwLwTZev6dmvIx1b9+a6r5/pW8+wsHDCw8LN2q5avSJ58uWmS/vY+waOHz1FvgJ5qFGrCh453ImJjuGST9zXw6S2e/9hjEYjub088b3hx7ipP5HHy5OG9d7F1saGsqWLM27qT9jb2+OR3Y1DR0+y5o+/6NW5tamNft9+j5urC93ax667/+OcRZR4ozBenh6EPghj7i/L8bt1m48+eC/O9fccOMK16zcZNbAHAMWKFOTKtRvs3HuQW7cDsbKyIncuz2T/OaRlafV9TK/nYklKJuKxac0Wsrhkpl3vr3HJ6syF0z50+qynaY3q7DmyERPz8tuG2Kezo/fIbvRrNwSjMfb82/6BfDdwIoMn9CPycSRDOo8i4lHcZdpSwvrVm3B2yULnPu3I6ubC2VMX+PqTTgT/fTObu2d2YoxPvlVzcHRg6Ng+ZHd349GjCC5fvEqvbwaxfvUms3bt09kzeHRvurXuZ+p3gP9tvu3/Hd6TB/M4IpI+nYYQ8Sgi5TorrFyxDldXZ/oP7Ea2bK6cPHGWjxq2ME178fT0MPvG1t3djd17n6xW1qVrG7p0bcPOHfuoV+czs7YnTxlF/74jCQ9/CMCjRxG0b9ub7ycMw97ejp7dh+DvH5ACvZR/rFm1AWdXZ3r270hWN1dOnzzHFx+3Nc1z9vB0N3td+7LlJ9jb2zFrwUSzdsaNnsr4MdNMz9Ols2fk2AG0b9nT9Pft7xfAoD6jGP/DSB4/fkzXb/rzKAX+vkMfhDFx+lwCAoPIlDEDtatVoXPb5tj+Pfr7/bC+TJw+j77DxnI/JBSP7G50btucTxo+ud/BP+C22ehFSOgDho6ZTNCdO2TMkIGihfLz84xx5MtjviDHo4gIRo2fxvfD+5mmumZ3y0q/bu0ZOGoCdra2jBzYg3T29sn+c0jL0ur7mF7Pk57GEBPOYPznr+I1Uta9qqVDsIiQqIeWDsEiLt/3//dKryFH27T5oSQ8Mm0mndmcMls6BIu4enGtpUOwCAePtPk+ljeTu6VDsIhb4XE3jkwLQsJS9v7QlzHO6wtLh/BcPXx/tnQIZnTPhIiIiIiIJIpFk4kjR45w5cqTebQLFy6kcuXK5MyZkypVqrBkyZJ/bSMiIoKQkBCzx9NDmCIiIiIiL8OYih+pjUWTia+++opLl2KXUJs9ezZt27albNmyDBgwgHLlytG6dWvmzJnzwja8vb3JlCmT2ePWg+spEb6IiIiISJpm0RuwL168SIECBQCYNm0akyZNonXrJ6tqlCtXjpEjR9KyZfw7SwP069eP7t27m5VVL1gneQIWERERERETiyYTjo6OBAUFkStXLm7evMlbb71ldrx8+fJm06DiY29vj/0zq2NYGXQriIiIiIgkTozh3+tILIt+6q5Tpw4//vgjANWqVWP58uVmx5ctW0b+/PktEdp/0rzj5xzy30n34Z0sHUqy+rTFR6zZtpgjl7dx5PI2lq6fw9vvVPr3E+WVVKlyOZb+OovzPnsJCbtMvf/VtnRIkow6dmvFur+Wct73AMcv7OCnnyeTL39uS4dFWFg4oydOp3aj5pSp0YDP23bn5Nnz8dYdNnYKxSrXYeHSVfEef/z4MR8170CxynU4dyHursUHj57gnQ+bJfi6A0aMo1jlOmaPtt0HmtW56nuDTn2GUaXuJ5Sv3Yhm7Xtw4PDzNw6U5JVW38f0ei5JyaIjE2PGjKFy5cpUq1aNsmXLMm7cOLZt20aRIkU4f/48+/btY9Wq+N8EUquiJQvTqFl9Lpz2sXQoye6W323GjfiBq5d9MWDgw6b/Y9qCcTSs+Tk+51Pvcm+SOE5Ojpw6eZaFC37llyXTLR2OJLMKlcoxf/Zijh09iY2NDX0HdeGXlbOoXqE+D8Mttwz14NGT8Ll8Fe/BPXFzdWHtn1to3aU/vy2aQbasrqZ6m7fv5sTpc7i5ujy3rXHT5uDm6sx5n/hfr7bu3Ef1yuVf6rpVKpRlRP9upue2trZmbXboPRQvTw9+mjyadPZ2LFy2mg69h/DHsjm4PmdXbUk+afV9TK/nkpQsOjLh4eHB0aNHqVixIhs2bMBoNHLgwAE2btyIp6cnu3fvpm7dupYM8aU4ODrw7dTBjOw5ltD7oZYOJ9lt3biT7Zt3c+3yda5e9mXCqGmEh4VTqmxxS4cmyWDTxu18O3w8v6/daOlQJAV80bgtyxav5sK5S5w5dZ6u3wzAM6cHJUoVtVhMjyIi2Lx9F907fE3ZUsXx8vSgw9df4OXpwdJVTzbgCggMwnvCj4wZ0hsbG+t429q59yB7DhyhZ8dWz73e1l37qFGlQoKvC2Bna4uri7PpkSljBtOxu/fuc+36TVp90YRC+fOQK2cOurX7ioePIrh42TI7J6d1afV9TK/n/y4mFT9SG4vvgJ05c2ZGjx7N6NGjLR3Kf9bHuxu7/9rLgZ2H+bprc0uHk6KsrKyoU78Wjo4OHD14wtLhiEgSy/j3h+J7d+9bLIboqGiio2OwtzP/tt/e3o4jJ04DEBMTQ7/h39Pis4/JnzdXfM0QdOcuQ8dMYpL3YNKlSxdvHZ/L17hz9x7ly5Tk8ePIf73uPw4ePcHb9ZqSMUN63ipTks5tmpM5U0YAMmfKSB4vT9Zs+IsihfJjZ2vLst/W45wlM0ULvXpTel83eh8TSRyLJxOvi3cbvEPh4gX5sk4bS4eSogoWycfSP+Zib29HeNhDOrToxaULL75pXkReLQaDgWHefTiw7wjnz1puCqeTkyMlixVh+rzF5M3lhYtzZtZv3s7xU+fwyhG7c/JPP/+KtbUVXzRuEG8bRqORgSPH06RhPYoVKchN/4B4623ZuZfK5ctga2uLra3tv14XoHKFMtSqVpkcHtm4ftOfSTPm0a7HIBbNGI+1tTUGg4FZk0bRue+3lK/dCCsrA86ZMzNj/LdmIxiSsvQ+JvLfKJlIAtk83OjxbWc6fNKdxxGPLR1Oirric40GNT4jQ4b0vF//HcZMGcrnDdrohVjkNTLq+4EUKlKAD+s0s3QoeA/qyWDvCdRs+AXW1lYUKZifOrWqcea8D6fPXeTnX3/j1zlTMBjiX4pl0fI1hIWH06pZkxdeZ+uufXz60QcJuu4/6taqbvrvgvnyUDBfHuo0acnBoyeoULY0RqORkeOm4ZIlE/OnfUc6e3tWrN1Ax95DWTJ7Mllddc+EJeh9TOKTGjeHS62UTCSBwiUK4ZLVmZ83zjaV2djYULpCSZp81YhKud4hJiY1znL77yIjo/C9cgOA0yfOUbxUUZq3+ZTBPUdZODIRSQojxg6g1nvVaFS3Of5+8X+Ln5K8PD2YN/U7wh8+IiwsnKyuzvQY5I2nR3aOHD/Fnbv3qP3Rl6b60dExfPfDbBYuW83GFfM5cPg4x0+d480a9c3a/aRVZ+rVrsGoQT0JDLrD2QuXqFbprQRd93ly5nAnS+aM+N7wp0LZ0uw/fIztew6wZ8My0js5AVC0UEf2HjzKb39s/tcER5KH3sfkdbZjxw6+++47Dh8+jL+/P6tWraJhw4am40ajkSFDhjBr1izu3btH5cqV+fHHH037wCWEkokkcHDnIT6p/qVZ2eCJ/bjm48v8Hxa9tolEfAxWVtjZ2/57RRFJ9UaMHcD79d6h8QctuO5709LhmHF0SIejQzruh4Sy58Bhun/TktrVq1ChXGmzem27DeSD92vSsO67APTr2o5ObZ68Xt8ODKZt94F8P6wfxd8oBMC23fsoVbxIvFOP4rvu89y6Hci9+6Fk/XuVpkePIoC4eyFZGQxp6n0itdP7mLxOwsLCKFmyJC1btqRRo0Zxjo8dO5bJkyczf/588uTJw6BBg3jvvfc4c+bMc+8pe5aSiSQQHvaQS+fNh0MfhT/i3t37ccpfJz0GdmD7X3vwv3ELp/SOfPDR+5SvXIaWTV7v/TXSKicnR/Lme3JDa+7cOSleogh379znxg0/C0YmyWHU94No+HFdWn7WiQcPwsnqFrv8aWhIqOlDsSXs3n8Yo9FIbi9PfG/4MW7qT+Tx8qRhvXextbEx3ez8Dxsba1yds5AnlycA7tndzI47OjgAsaMI2d2yArB1135qVKmQ4OsChIc/ZNqcRdSuXhlXF2eu3/Rj/LQ5eHl6ULn8mwCULFaEjBnS03/EONp99Rnp7O1YvmYDN/wDeLuS+aatkjLS6vuYXs//XcxrMtGpTp061KlTJ95jRqORiRMnMnDgQBo0iL3PbMGCBWTLlo3Vq1fTtGnTBF1DyYQkmrOrM2N/GIZbNldCQx5w/sxFWjbpxJ7t+y0dmiSD0m8WZ/2Gxabn3mNiN+Na9PNy2rftbamwJJk0/zr2TWTFuvlm5d2+GcCyxastEFGs0AdhTJw+l4DAIDJlzEDtalXo3LY5tjZJ83YW/vAR+w8do2+Xti91XStrKy5cusKaPzYT8iAMN1dnKr31Jh1bf4mdnR0AWTJnYvq4b5k8cz5fd+5LVFQU+fPkYsrowRQukDdJ4peXk1bfx/R6/mqLiIggIsL8Sx17e3vs7e1fqp0rV65w69YtatWqZSrLlCkT5cuXZ+/evQlOJgxGo/H1SL2eUta9qqVDsIiQKMttJGVJl+/7WzoEi3C0fbkXjddFeKTlvhW3pGxOmS0dgkVcvbg2Ra+3adtupsyaz5pFM1P0us9y8Eib72N5M7n/e6XX0K3wO5YOwSJCwlLvxoAjc31u6RCeK/KrAgwbNsysbMiQIQwdOvSF5xkMBrN7Jvbs2UPlypXx8/PD3f3J316TJk0wGAwsXbo0QfFoZEJERORvjg7p6N7++fdBiEjakJrvYurXrx/du3c3K3vZUYmkpGRCRETkb5XLl7F0CCIiL5SYKU3xyZ49djW6gIAAs5GJgIAASpUqleB2rP69ioiIiIiIvE7y5MlD9uzZ+euvv0xlISEh7N+/n4oVKya4HY1MiIiIiIg85XW5ofjBgwf4+DzZXPPKlSscO3YMZ2dnvLy86Nq1KyNGjKBAgQKmpWE9PDzM9qL4N0omREREREReQ4cOHaJGjRqm5//ca9G8eXPmzZtH7969CQsLo02bNty7d48qVaqwYcOGBO8xAUomREREREReS9WrV+dFC7caDAaGDx/O8OHDE30NJRMiIiIiIk9Jzas5pTa6AVtERERERBJFyYSIiIiIiCSKpjmJiIiIiDwlxmDpCF4dGpkQEREREZFEUTIhIiIiIiKJomlOIiIiIiJPiXlttq1LfhqZEBERERGRRFEyISIiIiIiiaJpTiIiIiIiT9Ekp4TTyISIiIiIiCSKkgkREREREUkUTXMSEREREXlKjKUDeIVoZEJERERERBJFyYSIiIiIiCSKpjmJiIiIiDxFm9YlnEYmREREREQkUZRMiIiIiIhIomiak4iIiIjIUzTJKeFey2TiQshNS4dgEeGREZYOwSIcbe0tHYJIsgsIu2fpECzCwaOqpUOwiId+Oy0dgkWk1d+3yKtM05xERERERCRRXsuRCRERERGRxNKmdQmnkQkREREREUkUJRMiIiIiIpIomuYkIiIiIvIUbVqXcBqZEBERERGRRFEyISIiIiIiiaJpTiIiIiIiT9Ekp4TTyISIiIiIiCSKkgkREREREUkUTXMSEREREXmKNq1LOI1MiIiIiIhIoiiZEBERERGRRNE0JxERERGRpxi1nlOCaWRCREREREQSRcmEiIiIiIgkiqY5iYiIiIg8Ras5JZxGJkREREREJFGUTIiIiIiISKJompOIiIiIyFNitJpTgmlkQkREREREEkXJhIiIiIiIJIqmOYmIiIiIPEWTnBJOIxMiIiIiIpIoSiaeo3WbZpw8s4PbwWfZsm0lZcqUeG7dwkUKsHDRNE6e2UFI2GW+6fBVnDpNPmnAmfO7uHbjKKNGDzA75uWVgyPH/iJDhvRJ3g9JmLT6+06r/RZ5nYSFhTN64nRqN2pOmRoN+Lxtd06ePW86HnTnLgNGjKNG/c8pW7MhbbsP5Nr1my9ss0XH3hSrXCfOo33PwaY6c39Zztv1mvJ2vabMW7zC7PwTp8/RpGUnoqKik7azIpLqKJmIR6OP6jFqdH9Ge0+mauUPOHnyLCt/m49rVpd46zs6OHD1qi9DB4/l1q3bcY47u2RhylRvBvb35sP6zfmkaQPef7+m6fj4id8yZPBYQkMfJFuf5PnS6u87rfZb5HUzePQk9h48ivfgnqxa+COV3nqT1l36ExAYhNFopEvf4dzwu8XkMYP5de4PeGR3o1WX/oQ/fPTcNieNGsS2NYtMj9ULp2NtbcV7NaoCcN7nClNn/8x3w/sydlgfpsxcwIVLVwCIiopm+HdTGNSrIzY21inyMxBJajEYU+0jtVEyEY+Onb5m/tylLFq4nPPnfOjaeSAPHz6k2ZeN461/5MgJBg0YzYrlvxMR8TjO8Ty5cxISEsrKFes4cuQEO7bvo2DhfAB83PgDIiMjWbvmz2TtkzxfWv19p9V+i7xOHkVEsHn7Lrp3+JqypYrj5elBh6+/wMvTg6Wr1nHt+k2Onz7HoJ4dKV6kEHlyeTKoZ0ciIiJYv2nbc9vNlDEDri7Opsfeg0dIZ2/PuzVjk4kr165TMF9uypcpRYWypSmYPw9Xrt0AYkcsypQqTvEihVLiRyAiFqZk4hm2traUKl2MrVt3m8qMRiPbtu7mrbdKJ6rNS5eu4uCQjhIli5IlSybeLFOC06fOkTlzRgYO6kbP7kOTJnh5aWn1951W+y3yuomOiiY6OgZ7O1uzcnt7O46cOM3jyEgA7J46bmVlha2dLUdPnE7wdVb+vpE6tarh6JAOgAL5cnP1+k38b93G71YA167fJH/eXPje8GP1+k10bv1lEvRORF4FSiae4eKSBRsbGwJvB5mV374dRLZsWRPV5r17IbRr04sZs8axdfsqlvyyir8272TEqP7MnLGQXLk92blnLfsO/kGDhnWSohuSQGn1951W+y3yunFycqRksSJMn7eY24HBREdHs/bPLRw/dY6goDvkyZUT92xuTJoxj/shoURGRvLTz8sIuB1EYPCdBF3j5JnzXLx8lY8+eN9Uli+3F13atqB11/606TqALm1bkC+3F8O/m0L3b1qy+8BhGn7Rjo9bdODQsZPJ1X2RZBOTih+pjZaGTSG/r93I72s3mp5XrvIWxYoVplePoRw7uZWWLboQEBDI1u2r2b37AEGBwRaMVv6rtPr7Tqv9FrEk70E9Gew9gZoNv8Da2ooiBfNTp1Y1zpz3wdbGhomjBjLYeyKV6zTB2tqKCmVLU7VC2QTPvF75+58UyJeb4kXNpy198mE9Pvmwnun5b+s34ejoQMliRfjg09YsmT2JgNtB9Bo8mj+Xz8XOzi4Jey0iqYWSiWcEB98lKiqKrG6uZuVubq4EBAQmyTXs7OwYP2E4bVr3IG++3NjYWLN71wEALvlcoWzZkmz4Y0uSXEteLK3+vtNqv0VeR16eHsyb+h3hDx8RFhZOVldnegzyxtMjOwBvFC7AivlTCX0QRmRkJM5ZMvNp6668UbjAv7Yd/vARf2zeTodWzV5Y7+69+/w49xfmTR3LydPnyZUzh+kRFR3F1es3KZgvT5L0V0RSF01zekZkZCTHjp6ievVKpjKDwUC16pU4cOBoklyjd58ObN68g+PHTmNtbYWN9ZOczsbWBmtrrX6RUtLq7zut9lvkdebokI6srs7cDwllz4HD1Kxawex4hvROOGfJzLXrNzl97iI1qlR4TktPbNyyk8eRkXzwXs0X1hszeSbNmjQku1tWomOiiYqKMh2Ljo4hJjo1Ts4QeT5jKv5faqORiXj8MOUnps/8nqNHT3Lo0HG+6fAVjo6O/LxwOQAzZn2Pn18Aw4Z8B8TezFq4SH4g9iY3d49sFC9RhLAH4Vy+fM2s7UKF89Poo/9RpdL/ALhw/hIxMTE0+7IJtwMCKVgwH0cOn0jB3kpa/X2n1X6LvG527z+M0Wgkt5cnvjf8GDf1J/J4edKw3rsA/LllJ1kyZ8I9W1YuXr7K6InTqVm1IpXLlzG10e/b73FzdaFbe/P9Y1b+/ic1q1Ykc6aMz73+ngNHuHb9JqMG9gCgWJGCXLl2g517D3LrdiBWVlbkzuWZDD0XkdRAyUQ8Vq5Yh6urM/0HdiNbNldOnjjLRw1bmG5W9fT0ICbmybcs7u5u7N67zvS8S9c2dOnahp079lGvzmdmbU+eMor+fUcSHv4QgEePImjftjffTxiGvb0dPbsPwd8/IAV6Kf9Iq7/vtNpvkddN6IMwJk6fS0BgEJkyZqB2tSp0btscW5vYt/jA4DuMnTKT4Dv3yOriTP3336HdV5+ateEfcBsrg8Gs7Mq1Gxw5cZqZE0Y+99qPIiIYNX4a3w/vh5VV7GSH7G5Z6detPQNHTcDO1paRA3uQzt4+iXstIqmFwWg0pr7xkv8oo1NeS4dgEeGREZYOwSIcbfUmlZak1X/nkrY89Ntp6RAswsGjqqVDkBQU9fjFO7FbUsvcH1s6hOeac3W5pUMwo3smREREREQkUSyaTHTq1ImdO//bty8RERGEhISYPV7DwRYRERERkVTHosnE1KlTqV69OgULFmTMmDHcunXrpdvw9vYmU6ZMZo/HkfeSPlgRERERSRMsvWLTq7Sak8WnOW3cuJG6devy/fff4+XlRYMGDfj999/Nbvx8kX79+nH//n2zh51t5uQNWkRERERELJ9MFC9enIkTJ+Ln58fPP/9MREQEDRs2JGfOnAwYMAAfH58Xnm9vb0/GjBnNHoZnVqQQEREREZGkl2qWhrW1taVJkyY0adIEX19f5syZw7x58xg9ejTR0dGWDu+FKlUuR5eubShVuhju7tn49JO2rPt9k6XDkmSSVn/fabXfIsktXTorMmeyw97OChsbK/wDHpodNxqNTJ29kOVrNxAaGkbpEkUZ1LMjuXLmAOCmfwDT5/3CgcPHCQq+S1ZXZ/73Xk3aNm+Kra2tqc57H7eIc+1FM8ZTslgRs7JpcxZx7fpNxgzpza+/rWfdpm2cPe9DWPhD9mz4lYwZ0pvVvx8Syqjx09i2ez9WVlbUql6Zfl3a4ejoAMCBIydYuHQVJ8+eJywsHC/PHHz12Uf875mN8BYuXUXOHI7Y2BiIiTHyICyKO3cfo9sgxRK0zWLCWXxkIj5eXl4MHTqUK1eusGHDBkuH86+cnBw5dfIsPboNsXQokgLS6u87rfZbJLlZGQw8fhxDUHD8yx7PWfQri5avYXCvTvwyayIO6dLRtvtAIiIeA3Dl2nWMMUYG9+rE6p+n06dzW5atXs/EGfPitDV70ii2rVlkehQtXCBOna0795p2x370KIIq5cvS+sumz42/z7Cx+FzxZdbEUUwdO5TDx04xdOxk0/FjJ89QMF8eJowcyIr502hYrzb9R4xj2+79pjrrNm5lwvS53L33mOs3w7kdFEF6Jxucs9gl6GcoIpZj0ZGJXLlyYW1t/dzjBoOB2rVrp2BEibNp43Y2bdxu6TAkhaTV33da7bdIcgt/GE34w/hH4I1GIwuXraZN86bUrFoRgFGDelLtg0/5a+ce6taqTpUKZalSoazpnJw53Lnie4Nlq9fRq2Nrs/YyZ8yIq4vzc2PxDwjE58o1qlSI3R272ScfArGjC/G5dNWXXfsOsWT2JIoVKQhA/27tad9zMD07tMItqwttmpsnIs2aNGTPgSNs3r6b6pXLA3Ds5FlKFy/K2fO7AYiKiuZBWBT29s//jCAiqYNFRyauXLmCi4uLJUMQERFJtW743SIo+C4Vy5Y2lWVI70SJooU4furcc897EBZGxgwZ4pR37DuMt+s1pVn7HmzduS/O8W279lGudAnSOzklKL7jp86SMUN6UyIBUKFsaaysDJw48+L4MmV8El+p4kU4c94He7vYjyU2NgYcHWwID49KUBwiSS3GaEy1j9Qm1dwzISIiIuaC7twFwMU5i1m5i3MWgoLvxnuO7w0/flm+hp4dW5nKHB3S0atTa0oXL4rBysDmbbvp3G84k70HU6NqBVO9LTv3mkZAEhRf8F2cM2cyK7OxsSZThgym2J+14a8dnDp7gSG9OpvK6r1bg7v3Q/Ce8CMQOzPhfkgk9+5HJjgWEbEMJRMiIiKviYDAINp2H8i7Narycf06pvIsmTPRvGkj0/PiRQpxO+gOc39ZbkomHoSFcejYSYb365Zs8R04fJxBo8YztE8X8ufN9aT8yAlmLVhKYFAEEREx2NoacHGxJ0u0LXfvKaEQSc1S5Q3YIiIiAq5/j0gEP/Mtf/Cdu7i6mI9W3A4MpmWnvpQqXpShfTrzb0oULYTvTT/T8517D5Evtxfu2bImPD6XLNy5d9+sLCoqmvuhoabY/3Hw6Ak69BlK785taFCnltmxH2Yt4IP3ahL6IIrHkTGEhUdz585jMmfSDdhiGcZU/EhtlEyIiIikUp4e2XF1ycK+w8dMZQ/Cwjhx5jwlixU2lQUEBvFVpz4ULZSfEf27YWX172/v5y5eJutTN2Nv3bWPGi8xxQmgZLEihIQ+4PS5i6ay/YePERNjpETRJ/EdOHKCb3oNoXv7ljRuUDdOO48iIrCy0h5RIq8iTXNKAk5OjuTN92S4NnfunBQvUYS7d+5z44bfC86UV1Fa/X2n1X6LJDeDAWxtn3z4t7Wx4tyFS2TKmAH37G40a9KQmfOXkMszBzk8svHDrIW4ubrwTtVKwN+JRMc+eGR3o2fHVtx9aqTgn5Wbflu/CVtbWwoXzAfA5m27WbVuI8P6dgFiRxN27TtEi08/MostKPgOQcF38f37b/zipas4OTrgnt2NTBkzkC+3F1UqlGXomEkM7tWJyKgoRk34kTq1quGWNXaBlQOHj9Oh9xA+b9yQ2tUrExR8J7aftramm7CrVS7PgiUrSe9kw6OIaGxtrHDOYqcbsEVeAQajMRXeFv4fZXTKm6LXq1K1POs3LI5Tvujn5bRv2zvF4giPjH+N8tedo619il4vtfy+U1pq6Xda/Xcur6906azJ4e4Qp7xBnVqMHNjDtGndr2s2EPrgAW+WeIOBPTqQ28sTgNXrNjFw1Ph42z61+w8gNpn4adGv+N+6jbW1NXly5eSrzz7i3RpVAdh36CgDRo7nr1ULzc6f+tPP/DhnUZx2R/TvTsN6sUu33w8JZeT4aWzbtR8rKwO1qlemf9f2pk3rBowYx29/bI7TRtnSxZn3w1ggNpmZuWAJk6YvwNraQHSMkfDw2E3rYrR72Gsr6vFNS4fwXJ/l+tDSITzXL9dWWToEM0omXiNp9UNWSicTYllp9d+5pC0P/Xam6PVGTfiR6OhoBvXsmKLXfZaDR1WLXl9SlpKJxEltyYSmOYmIiKRxBfLmomSxIpYOQ0ReQUomRERE0rj4booWScuMqXLdpNRJqzmJiIiIiEiiKJkQEREREZFE0TQnEREREZGnaBGxhNPIhIiIiIiIJIqSCRERERERSRRNcxIREREReUqMVnNKMI1MiIiIiIhIoiiZEBERERGRRNE0JxERERGRp2jTuoTTyISIiIiIiCSKkgkREREREUkUTXMSEREREXmKNq1LOI1MiIiIiIhIoiiZEBERERGRRNE0JxERERGRpxiNWs0poTQyISIiIiIiiaJkQkREREREEkXTnEREREREnhKjTesSTCMTIiIiIiKSKEomREREREQkUTTNSURERETkKdq0LuE0MiEiIiIiIomiZEJERERERBLltZzmVDBjDkuHYBEXQm5aOgSLyGDnYOkQLKJaxoKWDsEilvkfsHQIFlEne2lLh2AR/pH3LR2CRTh4VLV0CBbx0G+npUOwiMc/DLB0CPIMo1ZzSjCNTIiIiIiISKIomRARERERkUR5Lac5iYiIiIgkljatSziNTIiIiIiISKIomRARERERkUTRNCcRERERkacYjZrmlFAamRARERERkURRMiEiIiIiIomiaU4iIiIiIk+JsXQArxCNTIiIiIiISKIomRARERERkUTRNCcRERERkacYtWldgmlkQkREREREEkXJhIiIiIiIJIqmOYmIiIiIPCVG05wSTCMTIiIiIiKSKEomREREREQkUTTNSURERETkKUajpjkllEYmREREREQkUZRMiIiIiIhIomiak4iIiIjIU7SaU8JpZEJERERE5DUzdOhQDAaD2aNw4cJJfh2NTIiIiIiIvIbeeOMNNm/ebHpuY5P0H/2VTIiIiIiIPMWYiqc5RUREEBERYVZmb2+Pvb19nLo2NjZkz549WePRNKfnaNziQ9YcWMbuK5uZt24Gb5QqkqDz3m3wDof8d/L93FFm5V+0a8rGk2vYeHINn7f9xOzYG6WLsvDP2VhbWydZ/InVuk0zTp7Zwe3gs2zZtpIyZUo8t27hIgVYuGgaJ8/sICTsMt90+CpOnSafNODM+V1cu3GUUaMHmB3z8srBkWN/kSFD+iTvx8tq3upT9h3fyCX/I6zdtJhSbxZ/bt3PvvyYlesXcPrKHk5f2cOSVbPj1G/bsQXHL+zg+IUdtO3Q3OxY6TLF+WPrslTx+679ZR0m7ZrBvPNLGb56DPlKFnhu3YFLvuWXa6viPHrNffJ7rdemAT8ensePh+dRt3V9s/PzlSrAyN+/x8paLzuWUvfLesze/RMrLqzk+9/GUaBka66FoQAAVPNJREFUwRfWd8roRLtv2zH/0AJWXlzF9G0zKFOjrOl4tYbVmbNvLotPLuHrQa3MznXzdGP6thk4pHdIlr68jLT6ev66CwsLZ/TE6dRu1JwyNRrwedvunDx73nR8wIhxFKtcx+zRtvvAF7a5ZNXvfPhle8rXbkT52o34vE03du49aFZn7OSZVHq/Me982Izf/9xiduzPLTvp0HtI0nUyAWyrNCBd6xE49puDY6/p2DftjsHF/YXnWBcpR7o2I3HsOxvH/nNJ184bmxJVzOrYVKqHY6/pOPaajk3FembHrHLkI12bkWCl13NL8Pb2JlOmTGYPb2/veOtevHgRDw8P8ubNy+eff46vr2+Sx6ORiXjUrl+TbkM74t1nHKeOnuHT1o2ZsngcH1X5jLvB9557nrtndroM/oYj+46Zlecvko92vb+ma7M+GAwGJiwYw77tB7l07jLW1tb0H9ODkb2+Izo6Onk79i8afVSPUaP707XLIA4dPMY3Hb5i5W/zKVO6FkGBwXHqOzo4cPWqL6tXrcd7TNwXaGeXLEyZ6k37tr24euU6v66czY5te9mwIfbFd/zEbxkyeCyhoQ+SvW8vUv/D9xkyojd9uw/j6OGTtGrXjEUrZvB2uf8RHHQnTv2KVcrx24r1HNp/jEcREXTo8jW/rJxJzYoNuOV/myJvFKRXv440b9oBgwHmLZnG9q17OHfmItbW1oweP4TeXYda/Pdd4X+V+WLgV8wZMB2fYxeo0/ID+i4cTI8aHQkJvh+n/oS2Y7Cxe/KSkT5zBkZvmMD+dXsAyFk4Fx93/5TvWo7EYIBecwZwcscxrp/3xcraiq9HtWN23x+JiY5JsT7KE1U+qEqrQa2Y2n8qF46dp/7XDRj+83DaVW/L/Xh+3za2Nny76FvuBd1ndDtvgm8F45bDjQchYQBkzJKRTmM7MbHHRAKu3WLwvCGc2HOcg3/FfvBqP+Ib5o+ex8MHD1O0n89Kq6/nacHg0ZPwuXwV78E9cXN1Ye2fW2jdpT+/LZpBtqyuAFSpUJYR/buZzrG1tX1hm9mzutKt3VfkypkDo9HIb39splPf4Syf+wP58+Zi267/t3ffYU2dbwPHv4GwRZGlDNni3lbraNVqba111NaqdeAexbr3tg7UurfWPeqoVutqXXVvQVwgCjhQkCEqCjJC8v5B39QUbC0/QlTuz3Xl0jx5zjn3k8Ah93nGOcveg0dZPmcK9+5HM3bqHOrUrEZRmyI8e57M/OVrWTF36j8eI68ZeZRBdeEAmQ8iURgZYdKwLeYdR/Ji0VDISMtxG82L52Qc34E6IRoyVRj7VsW0ZW80yUlkRlxBUcwN0watSf3pBwDMvxlGZsQVNHFRYGSE6efdSd/9I6jlfG4II0eOZNCgQTplOfVK1KxZkzVr1lCqVCliYmKYOHEiH3zwAdeuXcPa2jrP4pGUMgfte7Vh58bd7N6yj9s37xAwbCapL1Jp3q7pK7cxMjJi8qJxLJ+5igd3Y3Re8/Bx41ZIBBdPBXHhZCDhoRF4+LgB0PHbdgSdu0zI5Rt6bdPr6PtdN9au3sLG9dsIuxHOgH5jePHiBR07tc6xflDQFcaOnsb2bXtIS0vP9rqnRwmSkp7xy/a9BAVd4fixs/iW9gbgq9bNyMjIYPeu/Xpt0+vo8a0fP63bxtafdnIrLIIRgybyIiWVth1a5Vj/u57DWbtyM9ev3SDi1m2G9BuHkcKIuh++D4BPSU9Cr9/k1IlznDx+jtDrN/Ep6QlAn35dOHv6IpcvXcu39r3KZ92bc2TzQY79/AcPbt1n5ailpL1Io97XDXOsn/z0OU/jn2gfFT6oRNqLNG0y4eztwr3QO4Scvsr1U1e5F3oXZ29XAD7v1ZIb50KIvBKeb+0Tulp2b8n+Tfs5/PMhom5FsXjkItJepPFxm49zrN+ozccUsrFmSo/JhF4MJe5+HNfOXeNO6G0AirkVJyUphZO7T3Dryi2unrmCq08JAD5s/iEqlYozv5/Jt/a9SkE9n7/rUtPSOHTsJIP8u1G9cgXcXJ3x79YBN1dntuzYq61namKCvZ2t9lGk8D9/gapf930+rF0D9xIueLi50r9XZywtzLl8PeszjbwbxXtVKlC+jC+ffVwfKytL7sc8BGD24pW0adkUp+KO+mt4DtI2TEMVfBxN/H3UsfdI27kEIxsHjJw9X7mN+k4omTcuokmIRvM4DtW531HH3sPIrRQARvbOqGPvob59PesRew8je2cATGo3Q303FHV0ZL60z1DUGs0b+zAzM6Nw4cI6j5ySiSZNmtC6dWsqVqzIJ598wr59+3jy5Albt27N0/dKkom/UZooKV3Rl3MnArVlGo2G8ycuUrFauVdu131QZxIfPebXTXuzvRZ+IxI3rxIUc3GkuGsx3LxKEBF2Gxd3Z5q1+Ywl037US1v+CxMTEypXKc+RI6e0ZRqNhqNHTlGjRpVc7TMi4g4WFuZUrFSWokWLULVaRa5fu4GNTWHGjB3IkEET8ib4/4GJiQkVK5flxNG/vvRoNBpOHjtLtfcqvdY+LCzNUZooefIk6+puaMgtPH08cHZ1wqWEE14+7twIDcfdowRtvvmCGVPm66Ut/4WxiRLPCt5cO3lZW6bRaLh28golq5Z6rX3Ub9OIs7tPkvYi68pXVNg9nLycsXO2x97FAScvZ6Ju3sPRrTj1Wjdk68yNemmL+HdKEyU+FXy4fDJYW6bRaAg+GUypqjmv7FGzUU1uBN6g9+Q+rAtcz8KDi2jt3xqjP4c1RN95gJmFGV7lvChUpBAlK/lyJ/QOVkWsaD+kA8vGLs2Ppv2jgno+LwgyVZlkZqoxM9XtaTAzMyXoynXt8wuXrvBh07Z83rY73/+wgCdPk17/GJmZ7Dt0lBepqVQun/V7UsrHi+s3bvE06RnXb9wiLS0NNxdngi5fIyQsnPatm//LXvVPYW4JZPU+vC4jz3IY2TmReTcraVLH3sPIzglFETsURewxsiuOOi4KRVFHlFXqkf5H3n4ZFfnDxsYGX19fwsPz9sKeDHP6GxvbIiiVShLjdYe3JMY/xsPHPcdtKtWoQIt2Tfnm4645vn7n1l0WT1vO4s1zAFgUsIw7t+6yaMsc5k9eQq36Nek5pAuqDBUzx83n0tnLOe5Hn+zsiqJUKomPS9Apj4tLwNfXO1f7fPIkid49h7Lsx1lYmJux+acdHD50goWLp7F82XrcPVzZ/PNyTEyUBEyZz687f8uLpvwntnY2KJXKbMO44uMf4V3y1Vd1XjZ6wmBiH8ZpE5Lwm5FMnzSXzb9kfamY9v1cwm9GsnnHCiaPn0X9j+oyaMS3qDJUjBsZwLnTgf+0e72wLmqNsdKYpwm6w1ueJjzB2dvlX7f3rlQSt9Lu/DhskbYsOvw+W2ZsZOSGCQBsnr6B6PD7jNo4gU0Ba6lYrwpfDmhLpkrFugkruXE+JE/bJF6tsG1hjJXGPE54olP+JOEJrn/2Hv1dcbdiVKxdkaM7jzKx8wScPJzpM7kPxiZKNs/dRPLTZOYMmsPAOYMwNTflj+1/cOl4EN/N6MfetXsoVqIYY1aORWmi5Kc5P3F636kcj6NPBfV8XhBYWVlSqXwZlq7ZhJe7G3a2Nuw7dIzL127g5pI1X6DO+9VoVK8OLs7FiHoQw7xla+g9eCwbl83+xzktNyNu077XINLT07G0sGDe1LF4e2b9vNSpWY3PP/mItt37Y25mxpQxg7G0MGfSzEVMHj2ILTv28tO2XdjYFGHCsH74eOX8c6Y3CgWmn3Yi894NNHH3/7mumQWWgxeDsRI0atL3rkYdeRUATUI06Ye3YN5xFADph7egSYjGvNMo0g/+hLFPRUzrf4UmM5P039eiviu9cW+D58+fExERQceOHfN0v5JM/I8srSz4fsEYpgydwdPE7OOO/9/2db+yfd2v2udNW39KSnIKVy9eY/vJjXRq0hNHJwemLplA85pfk5GekR/h692e3QfYs/uA9nmdujUoX740QwdPIPjqEbp27k9sbDxHju3k1KnzOc7NeJP5D+hO81ZNaN2ss85Qr/Wrt7J+9V9Xblq3bcHz58kEXrjM8Qt7aPpRG5yci7N4xUxqVW5M+lv2eddv05B7oXeIuHxLp/zwxv0c3vjX0LUPvmzAi+cvuBkUxqw/FjG2+VBsnez4buFg+tfthSpdld+hi9ekMDLi6aMnLBqxELVaTcTVCOyK2dGqdys2z90EwNn9Zzi7/69evfI1y+NZxoPl45ax7MRyZvb9gcfxj5m1azbXz13LcW7Gm0TO52+XgLFDGBcwh49adsDY2Igyvj40aVSPkLCsq66fNaqvrevr7YmvtydNvu7KhUtXeL/6q3vcPd1c2b5mEc+eJ3PgyElGT5nFmoUztAmFf7cO+HfroK2/eNVG3q9eGaVSybK1m9mxbjHHTp9n1OSZbF21QD+NfwXTz7pg5FiC1FUT/r1yeiovlo5AYWqOkWd5TD/pgPpxLOo7oQCoLh5CdfGlJUUrfYgmLZXMqFtYfjeLF8vHoChsi9lX/Xgxtx9kvlvn8zd3LafXN2TIEJo1a4a7uzvR0dGMHz8eY2Nj2rVrl6fHkWTib54kPkWlUmHrYKtTbutQlEdx2b/ounq44OLmzOy107Rl/z8M4GzUEb6s254Hd6N1tiliW4Qeg7vQ84u+lK9alnuRUUTdvk/U7fsoTZRZ3eY38ncs4qNHj1GpVDg42uuUOzraExsbnyfHMDU1Zfac7+nZYzBe3h4olcacOnkegIjw21SvXonff/vjX/aStxIfPUGlUmHvYKdT7uBgl62X5u969e2M/4ButG3ZndDrN19Zr6itDQOH9+HLpn5UqV6RyPC73I68x+3Ie5iYKPHy8eBGyK1Xbq8Pzx4/I1OVSRH7IjrlRexteBL/5B+3NbMwo1azumybvfkf61kXtebLAV/zfesx+FT25eHtaB7eieHhnRiMlcY4eToTFZb3q0qI7JISk8hUZVLU3kan3Mbehsfxj3Pc5nFcIipVJuqXJljeD4/C1tEWpYkSVYbuFwelqZI+U/owe8BsnDycMDY25tq5rLlB0bcf4FulFBcOnc/bhv2Lgno+LyjcXJ1Zs+gHUl6kkpycgoO9LYPHBuDqnPMymCVcnChqU5h792P+MZkwMTHBzTVrfkC50iW5fuMmG37+lfHD+mWrG3k3ij37/2Db6oX8svcA1SuXx7aoDZ989CFjp84hOTkFKyvLvGnwvzD9rDPGvlVJXT0RTVL2xUOy0WjQJMaiAdQP72Lk4IxJ3Rak/ZlM6LC0xqR+K1JXf4+xqw/qRzFoEh+iSXyIwsgYhZ1T1uRs8Ua5f/8+7dq149GjRzg4OFC3bl3Onj2Lg4NDnh5H5kz8jSpDxY0rN6lRt5q2TKFQ8F7dalwJvJ6t/p3we7Sp34n2jbpqH8cPnOLiqUu0b9SV2Oi4bNsMnvgdm5ZvJS4mHiNjI50biBgbG2NsgKUzMzIyCL50jfr1a2vLFAoF9erX5vz5S3lyjGHD/Tl06DiXg69jbGyE0vivditNlAZZSjEjI4MrwSHUrfe+tkyhUFD3w5oEXnj18IQ+/boyYGhvOnzViyvB2X8uXjZx6nB+XLyOmOhYjI2MMDF56fNWGmNslP/tzsxQcftqBOXq/LX0r0KhoFydCtwKCvuHLaFm09ooTU04uePYP9brMK4r+1buJvHhI4yMjTA2+audxkpjWSI2H6kyVIRfDadinb/mASkUCirVqURYUM7DE0IuhuLk7oRCodCWOXu58Cj2UbZEAqDNd20JPBpExLWIrM9b+fLnrcTYAEtIFtTzeUFjaWGOg70tT5Oecfp8IB998H6O9R7GxfPk6TMc7GxzfP1V1GpNjr3HGo2G72fMZ9h3PbC0tECdqSZDlfW7ofrz38x8Wu3I9LPOGJd+j9S1k9E8yeUFQIURCmXOq12ZfdKRjDO/ZSUpCgUYvXQt2sgIhSwR+0bavHkz0dHRpKWlcf/+fTZv3oy3d+6Grv8T6ZnIwcZlW5gwbxQhl29wPTiUb3q0xsLSgt2b9wEwcf5o4h4msGjqMtLT0okIu62z/bOnWZOe/l4OUPPD6rh5lWB8vykAhATfwN3Hndof1aSYsyNqdSZ3IwxztXbhgpUsXT6TS5eucvHiZb7174KlpSUb1m8DYNmPM4mOjmXi+Kyl4kxMTChdxgcAU1MTnJyLUaFiGZKfpxAZeVdn36VK+9Dqy8+pW/tzAG6GRaBWq+nY6WviYuPx9fUmKPBKPrb2Lz8uXsucxVO5cuk6l4Ku0qNPRyysLNiycQcA85ZMJSYmjmnfzwXg2/7dGDKyL317DCPqXrS2Nyc5OYWU5BSdfX9Qvxae3h7075M17vTypWt4l/SkQaO6OLs4oc5UExGe/eckP+xbsYves/oReSWCiMu3aNL1c8wtzTn282EA+szuR+LDRLbM2KCzXf02jQg8cI7nT569ct/l61bCydOZpYOyJptHXg7H2duFSvWrYudkhzpTTXRE9Cu3F3lv54qdDJw1kPCrt7gZfJMW3VpgbmnOoa1ZwxgGzhnEo4ePWDd9LQC/rd/H536f02NCT/as2Y2zpzOt/VuzZ/XubPsuUbIEHzT7gP5Nsq7c3g+/j0at5uM2H/M4/jGu3q7cvJy/vW//r6CezwuCU+cC0Wg0eLi5cu9+NLMWrcTTzZWWTRuTkvKCxas28nH9Otjb2RL1IJrZi1fh5upMnZpVtfvo1m8EDT+szTdfZU2cnrNkNR/Uqo5TMUeSU1LYe+AoFy5dYdnsydmOv3337xS1KUL9ulnJS5WKZVm8agOXr4Vy4uxFvD3cKJwP91EybdoVZYXapG6aBekvUBTK6nHWpKaAKisJMv2iD5qkx2QczupRNqnbgszoSDSPY8FYiXHJKigr1iV976ps+zfyqoDCzgnVziUAqKMjMbJ3xtinEooidqDRZC0x+45RvxMDnfKHJBM5OLjrD4ra2dB7WDfsHGy5eT2c774ZQmJC1nCA4i7FUKv/+w+Zmbkpw6YMZGTv8Wg0WdvHxcTzw5i5jJszkoz0DMb3m0paavZlVvPDL9v3Ym9vy6gxAylWzJ6rV0L5smVn7XAfV1dnnSEPTk6OnDrz12on/Qf0pP+Anpw4fpamTb7R2ff8BVMZNWIKKSlZa86npqbRp9cwZs6ZiJmZKUMGjScmJjYfWpndrh2/Y2tvy5BRfXFwtOf61Rt0+KqXdv6Gs6uTzufdqWsbzMxM+XHdXJ39zJq2iNnTF2ufm5ubMWXGaPp0HaL9vGOiYxk7fCqzF04hPT2dAd+OIjU153XA9e3snlMUtivMV4PaYuNQlLsht5nW6XuS/pyUbefskO3n3MnLmdI1yjK1/YRX7tfEzJTO3/dgQd+Z2nYnPnzEmvEr6PVDXzLSM1gyeD4ZOSwnLPTn5O4TFLEtQvtBHSjqUJTIkEjGdxzHkz8nZTs4O6B56fc7ISaBcR3H0X1cdxbsX8ij2EfsXrWL7Uu2Z9t332l9WTlphXZlr/S0dOYOnkvvSX0wMTVh2bilJMYaZj5UQT2fFwTPniczd+lqYuMTKFLYmo/r1aVfLz9MlEoyMzO5GXGbXb8dIul5Mo72ttSuUZW+PTphamqq3UfUgxgev7TCU+KTJ4yaNJP4R4lYW1nh6+PJstmTqV2jqs6xExIfs3ztZjYsna0tq1C2FH5tW/Ht0PHYFrVh6pjB+n8TAJP3spZ3tugyTqc8becSVMHHATAqYo9a89LPuakZZk27oChsB6p01AnRpP2yiMzrZ3V3rjTB7LPOpG2bD39ur0lKJP23NZi27A2qDNJ2LNEmLaJgUmg0mncu9aru9IGhQzCIm0kPDB2CQVibGv4Ou4ZQr/A/3734XbU1Jn/H3b8pmhTP3RLNb7uYjDd70ra+BD8qmPMsXkSfMHQIBpG+cLShQzAIqwmbDB3CK9Vx+cjQIbzSqQf5O7/030jPhBBCCCGEEC+RYU6vz+AzZhYuXEinTp3YvDlrHN/69espW7YspUuXZtSoUdpJTK+SlpZGUlKSzkOtkdu7CyGEEEIIoW8GTSYmT57MqFGjSElJYeDAgUyfPp2BAwfSvn17/Pz8WLFiBZMmTfrHfQQEBFCkSBGdx8PnsjyZEEIIIYQQ+mbQYU5r1qxhzZo1tGrVisuXL1OtWjXWrl1L+/btAShdujTDhg1j4sSJr9zHyJEjGTRokE5Zfd8meo1bCCGEEEK8u97BKcV6Y9BkIjo6murVqwNQqVIljIyMqFy5svb1qlWrEh39z8uNmZmZYWZmplNmpDD46C0hhBBCCCHeeQZNJooXL05ISAhubm7cunWLzMxMQkJCKFeuHADXr1/H0dHRkCHmil/f9nw3ujc//biV2eMWGDocvald5z36D+hJ5SrlcXIqRrs2vdi756Chw9K7vgO70+Tzj/Ep6UlqaioXzwczdcJsIsLvGDo0vZp3chkOJbL/Ph5Y9xtrxi43QERC32yL2dF5ZGeqNaiGmYUZMXdimDdkLuFXwg0dWr4pKOfzN1VycgoLflzH4eNnSHz8hNK+3owY0IsKZUqRoVKxYPlaTpy5yP3oGApZWfH+e1UY2LsLjg522n3cuXefWYtWculqCBkZGfj6ePJd907UqFZJ51jRD2Np1q4nJ/ZuxsTUhBXrtvDrb4eIS3iEh5srg/p0pe771bX1G3/pR/TD7DcybNvqc8YM9tcp02g09BkyjpNnLzIvYCwNP6ydbTt9MqnbAuMy72Fk7wyqdDKjbpJ+cBOaRzFZFSysMK3fGmPvCiiK2KNJSSLzxkXS/9gKaS/yNVbx9jFoMtG+fXs6depEixYtOHz4MMOGDWPIkCE8evQIhULBlClT+OqrrwwZ4n9WtlJpWnVszs3r7/4fWysrS65dDWX9up/5afNSQ4eTb96v/R5rV2wi+NJVlEolI8b256dffqT++815kfLunnTHNB+qc9fqEr5ujPppIuf2njJgVEJfrIpYMeOXGVw9c4UJnSaQlPgUZw9nnv95E7eCoCCdz99U46bNIzzyDgHjhuBob8fu/X/Qo/8oft24DEsLC0LCIujVuR2lfLxIevaMafOW0Xf4RLaumq/dh/+wCbi5OrNy/jTMzUxZv3Un/sPG89vWVdi/dDfsP06cpUbVilhaWjB78Ur27D/ChOH98HQvwanzgfQfOYkNy2ZRxjfrZq2bV8zTuffSrci79BgwisYNsi9Pv37LThTZSvOPkUcZVBcOkPkgEoWRESYN22LecSQvFg2FjDQU1kVRWNuQfmAj6vj7KGwcMPu8G2bWRUnbOteAkRuOrOb0+gyaTEycOBELCwvOnDlDjx49GDFiBJUqVWLYsGGkpKTQrFmzf52A/SaxsLRg0qJxTBkyg24D/Awdjt4dPHCMgweOGTqMfNehdS+d5wO+Hc3V8JNUrFyWc6cDDRSV/j1LTNJ53rxPKx7eiSH07HUDRST06as+X5EQk8C8IfO0ZbFRhrmxpCEUtPP5myg1LY1Dx04yf9p4qleuAIB/tw4cO3WOLTv20q+nHyvmTdXZZtSgPrTrPoCYh3E4FXfk8ZOn3I16wPcjBlDKxxOAgb27sPmXPdyKvKuTTBw5cUabCOz+/Q96+rXlw9o1AGj7xeecvRDMmk2/MH38MABsi9roHHvF+q2UcHHivSoVdMpv3Ixg7ebtbFk5n/rN2+fdG/QfpG2Ypv2/hqwb2lkNW46RsyfquzfQxN3XSRo0j+NIP7wFs1b+YGQEalklU7yaQScXGBkZMWrUKHbv3s3IkSNRKBS0bduWe/fukZCQwOrVq7GysjJkiP/J8ICBnDp8hvMn3t0vlCK7woWtAXjyuODcXMvYREndL+pxbOthQ4ci9KTGxzUJv3KL4UtGsD5oA3P3zaNxu08MHVa+kfO54WWqMsnMVGNmaqJTbmZmStCVnC9iPH+egkKhwNo667uDTZHCeLq5suv3w6S8SEWlymTrr/uwLWpD2VI+2u2Snj0n6Mp1GtR9H4D0jAydO2X//3EvveK4GRkZ7DlwhC+aNkah+KsP4kVqKsMmTmf0YH+dxMXQFOaWAGhevLqnUWFumTXESRIJ8S/kpnV5pHGLhpSu4EunJj0NHYrIRwqFgokBwzl/Noiw0IIzFKJ64xpYFrbi2M9v1l04Rd4pXqI4TTp8xs4VO/l54VZKVipJz4k9UWVk8Me2d/tzl/P5m8HKypJK5cuwdM0mvNzdsLO1Yd+hY1y+dgM3F6ds9dPS0pmzZBWfNapHoT8vRCoUCn6cN5V+IyZR8+NWGBkpsLWxYdnsSRT580IQwIkzF/D19tTOtahTsxrrNv9C9crlKeHixNmLwRw+dppMdWaOsR4+foZnz5/T8rOPdcpnzF9O5fJl+eiDWnn1tvzvFApMP+1E5r2sHokcWVpj8uEXZAQW3AtGGhnm9NokmcgDxZwdGTypH/5tBpGelm7ocEQ+mjpzDKXKlOSLJh0NHUq+atCmEZePBvEk7rGhQxF6ojBSEH4lnPUz1gEQeT0S91LuNGn/2TudTMj5/M0SMHYI4wLm8FHLDhgbG1HG14cmjeoREqZ78SZDpWLw2KloNBrGDu2rLddoNEyZtRi7okVYu/gHzM3M2L77d/oOm8DmFfNxsM/qLfjjxFltrwTAiP69mDB9Ps2+6YlCASWcnWjZ9GN27DmQY5y/7NlP3fer60z8PnLiLOcCL7Nt9cK8fEv+Z6afdcHIsQSpqybkXMHMAvNvhqGOf0DG0e35Gpt4O0kykQdKVyyFnYMtGw6s0JYplUqqvF+Jr7u0orZ7Q51JWuLdMHnGaBp9Uo9Wn/kRE11wxpLbuzhQvm5F5vSaYehQhB49jntM1K17OmVRt6Ko3aSOgSLKH3I+f7O4uTqzZtEPpLxIJTk5BQd7WwaPDcDVubi2zv8nEtGxcayaP03bKwFwLjCYY6fPc/r3rdrysqX6cubCJX797RDdO35NRkYGp85dpEenNtrtbIvaMH/aONLS0nmSlISjvR1zlqzSOe7/i34Yy9mLwcydOkan/FxgMFEPYqj1qe5CMgNHT6FqpXKsWZj/51DTzzpj7FuV1NUT0SQl5lDBHPMOIyD9BWlbZsMremKEeJkkE3ngwomLtKnfSads3NyR3A2/x9qFG+UPzzto8ozRfNq0Ia2bdSbq3gNDh5Ov6rX+iKePnnLpj4uGDkXoUejFEFy8XXXKXLxciLuffSnMd4mcz99MlhbmWFqY8zTpGafPBzLo267AX4nEvahoVi2Yhk2RwjrbpaamAdnvP2WkUGg/y/NBVyhsXYjSJb2yHdfMzJRiDvZkqFQcPHqKTz76MFudHXsPYlu0CB/WqqFT3r3j13zZ/FOdsi869mFYv57Ur1PzP74D/zvTzzpjXPo9UtdMQvMkPnsFM4usRCJTReqmmaDKyPcY3yRy07rXJ8lEHkhJfkFE2G2dstSUVJ48fpqt/F1iZWWJl7e79rmHRwkqVCzD48Sn3L//zzcbfJtNnTmWll99RtdvvuP58xQcHO0BeJb0TPuH612lUCj4sPVHnNh2FHWmfKl6l/264ldm7PiB1v6tObnnJL6Vffnkm09ZOOLNGrKR1wrq+fxNdepcIBqNBg83V+7dj2bWopV4urnSsmljMlQqBo2eQsjNcBbNmIharSbhUdbV9iKFrTExMaFS+TIUti7EqMmz6N3lG8zNTNm263fux8RqV2o6evIc9V8a4gRw5foNYuMfUbqkF3Hxj1i8agMajYau7XV7GdRqNTv3HqRFk0YolcY6r9nb2eY46dqpmEOOPRz6ZNq0K8oKtUndNAvSX6AoVAQATWpKVtJgZoF5x5EoTMxI3TwLhZkFmFlk1UlOAvliLf6BJBMi16pUrcC+3zdpnwdMz+ri3bhhG316DTNUWHrn160tANv3rtUpH/jtaLZu2mmAiPJP+boVcXB15Kis4vTOu3XlFlN7TqHTcD/a9m9HbFQsP078kWM7jxo6NFGAPHuezNylq4mNT6BIYWs+rleXfr38MFEqeRATy5GTZwH4qrPuTeJWLZhOjaoVKWpThKWzJjF/+Vq69RuBSqXCx9OdBdPGaXsijpw6y6SRA3W2T0tPZ8GPa7kf/RBLCws+qPUeAWOHUti6kE69MxcuERMbxxdNG+vxXfjfmbyXNTHcoss4nfK0nUtQBR/HyMkDY9eSAFj2n6dTJ2Xud2ieJORPoOKtpNC8g/041Z2y3zCmILiZVLCG2/w/a1MLQ4dgEPUK+xo6BIPYGnPe0CEYRJPiVQwdgkHEZBScJZdfFvwo0tAhGMSL6BP5eryQsHC69RvB8b2bMVEa7vpq+sLRBju2IVlN2PTvlQykqlNdQ4fwSkExJw0dgg6D3mdCCCGEEMJQMjMzGTmwj0ETCSHedvLbI4QQQogCqULZUlQoW8rQYQjxVpNkQgghhBBCiJe8g7MA9EaGOQkhhBBCCCFyRZIJIYQQQgghRK7IMCchhBBCCCFeokaGOb0u6ZkQQgghhBBC5IokE0IIIYQQQohckWFOQgghhBBCvEQjw5xem/RMCCGEEEIIIXJFkgkhhBBCCCFErsgwJyGEEEIIIV6ilpvWvTbpmRBCCCGEEELkiiQTQgghhBBCiFyRYU5CCCGEEEK8RFZzen3SMyGEEEIIIYTIFUkmhBBCCCGEELkiyYQQQgghhBAiV2TOhBBCCCGEEC+RpWFfn/RMCCGEEEIIIXJFkgkhhBBCCCFErsgwJyGEEEIIIV4iS8O+PumZEEIIIYQQQuSKJBNCCCGEEEKIXJFhTkIIIYQQQrxEVnN6fe9kMpGkemHoEAyiuKWtoUMwiMinMYYOwSCirZ4ZOgSRj449CjF0CELoXa0KfoYOwSDOXF1r6BCEyDUZ5iSEEEIIIYTIlXeyZ0IIIYQQQojcktWcXp/0TAghhBBCCCFyRZIJIYQQQgghRK7IMCchhBBCCCFeIqs5vT7pmRBCCCGEEELkiiQTQgghhBBCiFyRYU5CCCGEEEK8RFZzen3SMyGEEEIIIYTIFUkmhBBCCCGEELkiw5yEEEIIIYR4iUajNnQIbw3pmRBCCCGEEELkiiQTQgghhBBCiFyRYU5CCCGEEEK8RC2rOb026ZkQQgghhBBC5IokE0IIIYQQQohckWFOQgghhBBCvESjkWFOr0t6JoQQQgghhBC5IsmEEEIIIYQQIldkmJMQQgghhBAvkdWcXp/0TAghhBBCCCFyRZIJIYQQQgghRK7IMCchhBBCCCFeIqs5vT7pmRBCCCGEEELkiiQTr9C+a2v+CNzF1ahT/Pz7GipWKffKuo2bNmD7wXVcDD9C8J0T/HpkIy1af6ZTp+u3HTgTcoAzIQfo2qe9zmsVq5bjl0PrMTY21ktb/ouC2u6CqqVfczaf2cCB8H0s3r2A0pVLvbLup60bc/T+IZ3HgfB9OnXa9GrNjuCf2RH8M1/3/ErntTJVSrNs32KMjeW0Yyg9enbkashx4h6F8sfRX6hWreIr65YuU5L1GxdzNeQ4ScmRfOvfJVudr9u0ICTsJHfvX2LqtNE6r7m5uRAUfBhr60J53o7/qqC2u6Bq3fkLdp3fyqnbh1izdxnlKpd5re0at2jIxZgTzFw9Vae8Q++2HLi6iwNXd9G+Vxud18pVKcv6/Svy9e9YcnIK0+Yu5eNWflRr0IL2vQZxNTRM+3pKygumzFpMw5YdqNagBc3b92TLjr3/uM+DR0/xddd+1PrkK95r2JIv/fzZ9fthnTqrf9rGh03b8mHTtqzZtF3ntSvXb/B11+9QqTLzrqHirSHDnHLwWcuPGfn9QMYNDeBy4DU692rHyq0L+KTWlyQmPM5W/8njJJbOWUXkrTukZ2TQoPEHBMwfx6OERE4eOUupsj70H96bXu0HoFAoWLZxDiePnuVmaATGxsZ8P3MUYwdNITPTsL+EBbXdBVWDZvX5dlxvZo+cR+ilUL7q/iU/bJhGx3pdePLoSY7bPE9KplO9ztrnL3cDe5XxpMsQP0b6jUGhUBCwdjIXjgdy+8ZtjI2NGBQwgJnD55CZqdZzy0ROWn3ZlKnTRjGg/1guXgjmW/8u/PLrWqpVaURC/KNs9S0tLLhz5x47d+wjYPqYbK/b2hVlwaIA+vQayp3bUfz8ywqOHz3D77//AcDsuZMYP24Gz54913vb/klBbXdB9XHzjxg4oS8Bw2dx7VII7Xq0ZsGmWXxZ9xsev+K8BuDkWpz+474l6GywTrlPGW96D+vGgI7DUSgUzFk3nbPHLhBxIxJjY2NGTR/MlKE/5OvfsXHT5hEeeYeAcUNwtLdj9/4/6NF/FL9uXEYxB3tmLFjOucDLBIwbhotTMU6fD2TyrEU42tvR4IP3c9xnkcLW9PRrg6d7CUyUSo6dPs/YqbOxK2pDnZrVCAu/zaIVG1j0wwQ0Gg3+QydQu0ZVfL09Uaky+f6HBYwf3g+l8t25OKiWYU6vTS4R5qBL7/Zs3bCTXzbtJuLmbcYNCSD1RSpffdM8x/rnTwdycN9RIm7dIerOA9Yt30xYSDjValYGwKukB2Ehtzh78iJnTlwgLCQcr5IeAHTv25ELZ4K4GhyST617tYLa7oKqdc8v2btpH79v3c/dW/eYPWIuqalpfNb201dvpNGQGP9Y+3ic8ET7kpu3G5Ght7l0OpigU5eICI3EzbsEAG16t+HyuSuEXQ57xY6FvvX9rhtrV29h4/pthN0IZ0C/Mbx48YKOnVrnWD8o6ApjR09j+7Y9pKWlZ3vd06MESUnP+GX7XoKCrnD82Fl8S3sD8FXrZmRkZLB71369tul1FNR2F1Tte7Vh58bd7N6yj9s37xAwbCapL1Jp3q7pK7cxMjJi8qJxLJ+5igd3Y3Re8/Bx41ZIBBdPBXHhZCDhoRF4+LgB0PHbdgSdu0zI5Rt6bdPLUtPSOHTsJIP8u1G9cgXcXJ3x79YBN1dnbe9D8NVQWjRpRI2qFXFxKkbrFp9RysdLp/fi72pUrUijenXw9nDDzdWZjl+3xNfbk6DL1wG4fTcKX28PalarzPvVq+Dr48ntu/eBrB6LapUrUKHMq3u2xbtNkom/MTFRUq5SaU4fO6ct02g0nD5+nsrVX901/rJaH7yHp7c7F85cAuBmSDge3m44uRTD2bU4Ht5u3AqNoISHC63aNWPu1CV6act/UVDbXVApTZSUquBL4IkgbZlGoyHwRBBlq5Z95XYWVhZsPruRred/YvLK7/Hwdde+FnnjNq5eLjg6O1LMxZESnq7cDruDs7sTTdp8wsoZq/XaJvFqJiYmVK5SniNHTmnLNBoNR4+cokaNKrnaZ0TEHSwszKlYqSxFixaharWKXL92AxubwowZO5AhgybkTfD/g4La7oJKaaKkdEVfzp0I1JZpNBrOn7hIxWqvHrLbfVBnEh895tdN2YcChd+IxM2rBMVcHCnuWgw3rxJEhN3Gxd2ZZm0+Y8m0H/XSllfJVGWSmanGzNREp9zMzJSgK1lf/CtXKMORk2eJjU/Ian/gZe7ce0DtGlVf6xgajYazFy9x5959qlUuD0BJbw/uRD0g5mEc0Q9juRv1AB8vd+7dj2bnvoP069Epbxsq3ioyzOlvitraoFQqSYhP1ClPiEvEy8fjldsVsrbixNXfMDU1RZ2ZyYTh07VfzCNu3WH2lMWs3rYYgFmTFxFx6w5rti3ih4nzqftRLb4b2hOVSsXk0TO5+OeX8fxUUNtdUBWxLYKx0pjEeN3ha48THuPmUyLHbe5FRDF98EwiQyOxKmxFm16tWbhzPl0adiM+JoF74fdYMW0VMzdNB+DHaSu5F36PWZtmsGzKcmrUr07ngZ1QqTJZMH4RV85d1Xs7RRY7u6IolUri4xJ0yuPiEvD19c7VPp88SaJ3z6Es+3EWFuZmbP5pB4cPnWDh4mksX7Yedw9XNv+8HBMTJQFT5vPrzt/yoin/SUFtd0FlY1sEpVJJ4t/+jiXGP8bDxz3HbSrVqECLdk355uOuOb5+59ZdFk9bzuLNcwBYFLCMO7fusmjLHOZPXkKt+jXpOaQLqgwVM8fN59LZy3nbqL+xsrKkUvkyLF2zCS93N+xsbdh36BiXr93AzcUJgFED+zBh+nwatuyI0tgYhZGCCcP7U71yhX/c97PnyXzUsgMZ6RkYGRsxZrC/NgHx9nCjf6/O9BgwCoD+vTrj7eFG9/4jGfRtV06dD2Txyo0olcaMGND7X4/1NtDITetemyQTeST5eQotGnyDlZUltT54j5HfDyTqzgPOn866QrJ57XY2r/1rwtIXbZqS/DyFSxevsv/Mdr5s3IniTo7MWT6Vj6o1JyM9w1BN+U8KarsLopCgUEKCQrXPr128zrqjq2jW/nNWzVwDwK4Ne9i1YY+2zidffUxKcgrXA0NYf2wNvT73x8HJnnGLRtOudkf5vN9ye3YfYM/uA9rnderWoHz50gwdPIHgq0fo2rk/sbHxHDm2k1Onzuc4R+FtVFDb/a6xtLLg+wVjmDJ0Bk8Tn76y3vZ1v7J93a/a501bf0pKcgpXL15j+8mNdGrSE0cnB6YumUDzml/r/bwWMHYI4wLm8FHLDhgbG1HG14cmjeoREhYOwMZtu7hy/QYLp4/HqXgxAoOvMmXWYhzt7aj13qt75KwsLdi+ZhEpKS84GxjMDwt+xNXZiRpVs0YntPmiKW2++Gu42K/7DmJpaUGl8mVo1q4Hm1fMIzYugaHjprF/22pMTU31+j6IN4ckE3/zOPEJKpUKewdbnXJ7R1vi4179B0Gj0XDvdtb4wdBrN/H29aTXgM7aL9UvK2pbhL5DevBN855UqlqeOxH3uBsZxd3IKEyUSjy93bgZGpG3DfsXBbXdBdXTxKdkqjKxdSiqU17UviiJcdkn2+ckU5XJrWvhuHg45/h6kaKF8RvYif5fDaRMlTJE3b7Pg9sPeHD7AUoTJa5erty+cft/bov4d48ePUalUuHgaK9T7uhoT2xsfJ4cw9TUlNlzvqdnj8F4eXugVBpz6uR5ACLCb1O9eiV+/+2PPDnW6yqo7S6oniQ+RaVSYfu3v2O2DkV5lMPfMVcPF1zcnJm9dpq2zMgoa/T32agjfFm3PQ/uRutsU8S2CD0Gd6HnF30pX7Us9yKjiLp9n6jb91GaKLOGQd2I1EPr/uLm6syaRT+Q8iKV5OQUHOxtGTw2AFfn4qSmpTFv2VrmBYylXu0aAJTy8eTGrUjWbNr+j8mEkZERbq5Z5/PSvt5E3olixfot2mTiZY+fPGXJ6p9Ys2gGV6+H4V7CRftQZaq4E/UAX29P/bwB4o0jcyb+JiNDxfXLN6j1YQ1tmUKhoNYH7xF88cpr70dhZPTKrHzUpMGsWbaJ2Jg4jI2NUJr8ldMZK40NslRqQW13QaXKUBF29SZV6/41hlahUFCtbhVCgl5vUryRkRFepT15FJeY4+v+E/rw84rtxMckYGRshFL50udtbIyxkZx+8ktGRgbBl65Rv35tbZlCoaBe/dqcP583wwuHDffn0KHjXA6+nvX7bfzX5600URrovFYw211QqTJU3Lhykxp1q2nLFAoF79WtxpXA69nq3wm/R5v6nWjfqKv2cfzAKS6eukT7Rl2JjY7Lts3gid+xaflW4mLicz6v5ePS15YW5jjY2/I06Rmnzwfy0Qfvo1KpUKlUGCkUOnWNjY1Qq//bSnpqjZr0jJx7WabPX07Hr1tS3NGBTHUmKpVK+1pmphr1O7Bqn0ajeWMfbxrpmcjB6qUbmb5gAteCQ7gSdB2/Xt9gYWnB9k27AZixcCKxD+OYNXkRAL36d+ZqcChRd+5jampCvUZ1aNH6MyYMC8i279r1auLh7cawvuMBuHIpBC8fdz5sWBsn52KoM9VEht/Nv8a+pKC2u6D6efl2Rs4ZRtjlMEKDw/iqeyvMLcz5bcvvAIycO5yEhwn8OG0lAJ0GdCAkKJQHd6IpVNiKtr2/pphrMfZu2pdt39U+qIqrlysBA2YAEHY5DDefEtRo8B6Ozo6o1WruRUblX2MFCxesZOnymVy6dJWLFy/zrX8XLC0t2bB+GwDLfpxJdHQsE8f/AGRNXi5dxgcAU1MTnJyLUaFiGZKfpxAZqfu7Wqq0D62+/Jy6tT8H4GZYBGq1mo6dviYuNh5fX2+CAl//okReKqjtLqg2LtvChHmjCLl8g+vBoXzTozUWlhbs3px1npo4fzRxDxNYNHUZ6WnpRITp9o4+e5q1pO/fywFqflgdN68SjO83BYCQ4Bu4+7hT+6OaFHN2RK3O5G7EPT23EE6dC0Sj0eDh5sq9+9HMWrQSTzdXWjZtjIlSSfUqFZi1aCVmZmY4F3fk4qWr7PrtMEP79dDuY+SkmTja2zGwT9Z9VH5ct4VypUtSwsWJ9IwMTpy5wJ7f/2DMkL7Zjn/6fBB3ox4wdcxgAMqX8eX23fucOHOBh3HxGBkZ4eHuqvf3Qbw5JJnIwb6dB7G1K0q/4b1xcLQj9NpNurX5jkd/Tupyci2OWvNX1m1hacGEGcMp7uRIamoakbfuMPTbsezbeVBnv2bmZoybNoyBPUZqM8vYmDgmjfqBgPnjSE/LYPh340lLTcu/xr6koLa7oDqy+yg2dkXoMqQztg5FCQ+JYFjHkdrlXou5OKJ56UqWdRFrhswYhK1DUZ4/fU7Y1Vv4t+jP3Vu6fzxNzU3pP/k7vu8zWft5x8ckMH/sQkbMGkp6egYBA2aQnpp92U2hP79s34u9vS2jxgykWDF7rl4J5cuWnbWTk11dnXWuXDo5OXLqzF+r2/Qf0JP+A3py4vhZmjb5Rmff8xdMZdSIKaSkvAAgNTWNPr2GMXPORMzMTBkyaDwxMbH50MrsCmq7C6qDu/6gqJ0NvYd1w87BlpvXw/numyHaeyUVdymGWv3fr+yamZsybMpARvYerz2vxcXE88OYuYybM5KM9AzG95tKWj6c1549T2bu0tXExidQpLA1H9erS79efpj82Usyc+II5i5dw4iJM3ia9Azn4o706+VHm5Z/zXeIiY3T6b14kZrK5FmLiI1LwMzMFE/3EgSMG0qTRvV0jp2alsbU2YuZ+f1I7ZCw4o4OjBzYhzFT52BqYsKUMYMxNzPT+/sg3hwKzZvYX/I/8nWobugQRD6KfBrz75XeQXUdX++uru+ak3Gh/17pHWRpIn+cC5KUjIJ5caWynZehQzCIM1fXGjoEgzCxf3M/b4cib+59M+Kfvln3bDJoz0RMTAxLlizh5MmTxMTEZI3B9vKiZcuWdO7cWcaaCiGEEEII8QYz2AzIixcvUqZMGfbt20dGRga3bt2iWrVqWFlZMWTIED788EOePXv2r/tJS0sjKSlJ5/HyUBwhhBBCCCGEfhgsmRgwYAADBw7k4sWLnDhxgjVr1nDz5k02b95MZGQkKSkpjBkz5l/3ExAQQJEiRXQej1Me5kMLhBBCCCHEu8jQKza9Tas5GWzOhKWlJdeuXcPLK2u8nFqtxtzcnKioKIoVK8bBgwfp3LkzDx48+Mf9pKWlkZamO7a0qld9jBSy7GRBIXMmChaZMyEKApkzUbDInIk3j31hX0OH8EoJSTcNHYIOg82ZcHR0JCYmRptMxMbGolKpKFy4MAAlS5YkMTHn9etfZmZmhtnfVg2QREIIIYQQQgj9M9i37pYtW9K7d29+//13jhw5Qvv27alXrx4WFhYAhIWF4eLiYqjw/pN2nb9k19FNBEUeJSjyKFv2reLDhrX/fcO3XEFtd0HVeVAnjt4/pPNYd3SVocMSelK7znts+flHwsLPkJQcSdPPPzZ0SPmioLZbZPHr256LMScY9P13+Xrc5OQUps1dyset/KjWoAXtew3iauhfK/YkJD5m9ORZNGjenuoftaTXoDHcjfpr5MbTpGdMnb2Yz9t2p1qDFjRq1Ympc5bw7HlytmNFP4ylWoMWpKS8IDzyLgNGTabxl36Ur9OE9Vt25Bjfpu27afylH1UbNKddjwFcDdFdTSgtLZ3JsxZRp8nXvNfoCwaMmkxC4mOdOmcvXqJ9r0HUaNSKes2+YfbilTo3u3vTqDWaN/bxpjFYMjF58mTKli1Ls2bNaNiwIWlpaaxa9dcXE4VCQUBA9pufvYkeRscxa/JCvmjUkVaNOnH25EUWr5uFT6k3t/suLxTUdhdkt2/cplWV1trHd18MMHRIQk+srCy5djWUwQPHGzqUfFVQ2y2gbKXStOrYnJvXw/P92OOmzePMhUsEjBvCjvVLqF2jKj36jyI2PgGNRkP/Ed9zP/oh86eP4+fVC3Eu7kj3/qNIeZEKQFzCI+ISEhnStzs71i9hyuhBnDoXyLiAOdmO9ceJs9SoWhFLSwtepKXi6lycAX26YG9XNMfYfjt0jBkLltOna3t+XrWAUj6e9Bo0hkePn2jrTJ+/jKOnzjF78ijWLJxBfMIjBoyarH39xq1I+gwZR92a1di2ZiEzvx/BkZPnmDVrVt6+kcIgDDbMqVChQmzZsoXU1FRUKhWFChXSeb1x48YGiuy/O3LghM7zOVMX067zl1SuXoHwsEgDRaV/BbXdBVlmZiaJ8Y//vaJ46x08cIyDB44ZOox8V1DbXdBZWFowadE4pgyZQbcBfvl6bA0aDh07yfxp46leuQIA/t06cOzUObbs2EvzTxty+foNdq5fio+XOwBjh/SlfrNv2HfwKF81/5SSXh7MnfrXojVurs706+nHiO9noFJlolT+tdT+kRNnaNzgAwAqlClFhTJZ91OYu2R1jvGt27KDr5o14YumWd/Lxg39juOnL7BjzwG6d/yaZ8+T+WXPAWZMGEbNapUBmDR6EM2/6cnla6FUKl+G3w8fx9fbkz5d22vjG/xtVwaPm4a/v3+274Di7WLwyQXm5ubv1A+RkZERTVs2xtLSgksXrhg6nHxTUNtd0Lh4urDt4mZ+OrWe0QtG4ujsaOiQhBDifzY8YCCnDp/h/IlAAxxdQ2amGjNTE51SMzNTgq5cJz0jAwDTl143MjLCxNSES1euv3Kvz54nU8jKUieRSHr2nKAr12lQ9/3XiiwjI4OQsFu8/15lnWO/X70yl69lLYYREnYLlUrF+9WraOt4uZfAqZgjl6/d0O7HzNT0b+0zIy0tjevXX90GQzL0ik1v02pOBr1p3bvEt4w3W35bjZmZKSnJL/DvPJSIm7cNHZbeFdR2F0Qhl0KZNvAHoiKjsHO0w29gR+b/MocuDbvzIvmFocMTQohcadyiIaUr+NKpSU+DHF+BEZXKl2Hpmk14ubthZ2vDvkPHuHztBm4uTnj++cV83rI1jBv6HZYW5qzbsoPYuATiH+W8UM3jJ09ZtmYTXzVvolN+4swFfL09cXSwe63YHj9JIjNTjZ2t7hAoO9ui3L53H4CER48xMVFS2LrQ3+rYkPDnQjq1a1Rl/dad7Dt4lE8++oCExMcsXf0TAPHx8a8Vi3hzGbxn4l1xO/wuLRp8Q+tPOrNpzTamL5iAt6+nocPSu4La7oLo/JELHNt7nMjQ21w4dpERnUZRqHAhGjSrZ+jQhBAiV4o5OzJ4Uj/G+E8iPS3dYHEEjB0CGg0ftexA1QbN2fjzrzRpVA+FkREmSiVzp47hzr0H1GnyNdUbtuR80BU+eL86RkbZv8Y9T07m26Hj8fZ049tuHXRe++PE2dfulchLdWpWY7B/N77/YQFVGzTn87bd+aDWewA5tkG8XaRnIo9kZKi4dzsrS79+5QYVKpfFr2c7xg2ZauDI9KugtlvA86Rk7kfex8Xj7Vh1TQgh/q50xVLYOdiy4cAKbZlSqaTK+5X4uksrars3RK1W6z0ON1dn1iz6gZQXqSQnp+Bgb8vgsQG4OhcHoFzpkmxfu4hnz5PJyMjAtqgN7XoMoFzpkjr7SU5OodegsVhZWjBv6lhMlH99zcvIyODUuYv06NTmteMqalMYY2MjHv1tZaZHiY+x/7O3wt6uKBkZKpKePdfpnXiU+AR7W1vtc7+2rejU5gviExIpXLgQD2Jimbt0Na6urq//RuUjNW/ecKI3laSDeqIwMsLUzOTfK75jCmq7CyILS3OcPZx4FPfI0KEIIUSuXDhxkTb1O9G+UVft43pwKL//cpD2jbrmSyLxMksLcxzsbXma9IzT5wP56APdXgTrQlbYFrXhbtQDrt+4pdPL8Dw5mZ4DR2NiomTB9PGYmenOUTgfdIXC1oUoXfL1V1w0MTGhbKmSnLsYrC1Tq9WcCwymUvmsG6eWLVUSpVKpU+f23fvExMZRqXxpnf0pFAocHewwNzPjt4NHcXJyoly5cq8dj3gzSc9EHhg8xp9jh08Tc/8hVoUsafblp9SsU42uX+fvOtX5raC2u6DqM6Ynpw+dJfZ+LHbF7Ogy2A91pprDO48YOjShB1ZWlnh5u2ufe3iUoELFMjxOfMr9+9EGjEy/Cmq7C6qU5BdEhOnO80tNSeXJ46fZyvXp1LlANBoNHm6u3LsfzaxFK/F0c6Xlnyso7f/jBEVtiuBUzIFbkXeYNncpH31Qizo1qwF/JhIDRvMiLY1544aSnJxCcnIKAEVtimBsbMzRk+eo/7chThkZGUTcvvfn/1XExj/ixs0ILC0tcHN1BqBTmy8YPWUW5UqXpHzZUmzYupMXqWm0bJp1DxbrQla0+rwxMxb8SJHC1lhZWTJ1zhIqlS+jTTgAVm3cRt33q2GkMOLQsVOs2PAz8+bNw9jYGPF2k2QiD9ja2zJj4UQci9nzLOk5YSG36Pr1d5w+ds7QoelVQW13QeXg5MDYhaMoXLQwTxOfcvX8Nb5t/h1PE58aOjShB1WqVmDf75u0zwOmZy07uXHDNvr0GmaosPSuoLZbGNaz58nMXbqa2PgEihS25uN6denXy087TCn+USIzFiznUeITHOxsaf5pQ3p3aafdPiQsgit/3kjuszbddPa9f9saXJyKceTUWSaNHKjzWlxCIl916at9vmbTdtZs2k71KhVYs3AGAE0a1ePxk6csXLGBhMRESpf0ZumsSdphTgDD+/XCyMiIAaMnk5GRQe0a1Rg7xF/nWCfPXuTHdZtJT8+glI8nC6aN46NGjfLg3dOPN3HVpDeVQvMOvlu+DtUNHYLIR5FPYwwdgkHUdSzz75XeQSfjQg0dgkFYmpgZOgSRj1Iy0gwdgkFUtiuYNz09c3WtXvcfEhZOt34jOL53s848CkMzsX9zP+/CVm9ubEnJb9a9vGTOhBBCCCHEOywzM5ORA/u8UYmEeHfIT5UQQgghxDusQtlSVChbytBhvFXU797AHb2RngkhhBBCCCFErkgyIYQQQgghhMgVGeYkhBBCCCHESzRy07rXJj0TQgghhBBCiFyRZEIIIYQQQgiRKzLMSQghhBBCiJfIak6vT3omhBBCCCGEELkiyYQQQgghhBAiV2SYkxBCCCGEEC/RyDCn1yY9E0IIIYQQQohckWRCCCGEEEIIkSsyzEkIIYQQQoiXyE3rXp/0TAghhBBCCCFyRZIJIYQQQgghRK7IMCchhBBCCCFeIqs5vT7pmRBCCCGEEELkiiQTQgghhBBCiFyRYU5CCCGEEEK8RIY5vT7pmRBCCCGEEELkiiQTQgghhBBCvKMWLVqEh4cH5ubm1KxZk/Pnz+fp/iWZEEIIIYQQ4iWaN/jxX2zZsoVBgwYxfvx4goKCqFSpEp988glxcXH/cU+vJsmEEEIIIYQQ76DZs2fTo0cPunTpQtmyZVm6dCmWlpasWrUqz44hyYQQQgghhBBvibS0NJKSknQeaWlp2eqlp6cTGBhIo0aNtGVGRkY0atSIM2fO5F1AGpFnUlNTNePHj9ekpqYaOpR8Je2WdhcE0m5pd0Eg7ZZ2izff+PHjs41+Gj9+fLZ6Dx480ACa06dP65QPHTpUU6NGjTyLR6HRyNpXeSUpKYkiRYrw9OlTChcubOhw8o20W9pdEEi7pd0FgbRb2i3efGlpadl6IszMzDAzM9Mpi46OxsXFhdOnT1OrVi1t+bBhwzh27Bjnzp3Lk3jkPhNCCCGEEEK8JXJKHHJib2+PsbExsbGxOuWxsbEUL148z+KRORNCCCGEEEK8Y0xNTalWrRqHDx/WlqnVag4fPqzTU/G/kp4JIYQQQggh3kGDBg3Cz8+P6tWrU6NGDebOnUtycjJdunTJs2NIMpGHzMzMGD9+/Gt1Pb1LpN3S7oJA2i3tLgik3dJu8W5p06YN8fHxjBs3jocPH1K5cmV+//13ihUrlmfHkAnYQgghhBBCiFyRORNCCCGEEEKIXJFkQgghhBBCCJErkkwIIYQQQgghckWSCSGEEEIIIUSuSDKRhxYtWoSHhwfm5ubUrFmT8+fPGzokvTp+/DjNmjXD2dkZhULBzp07DR1SvggICOC9997D2toaR0dHWrZsSVhYmKHD0rslS5ZQsWJFChcuTOHChalVqxa//fabocPKd9OmTUOhUDBgwABDh6JXEyZMQKFQ6DxKly5t6LDyxYMHD+jQoQN2dnZYWFhQoUIFLl68aOiw9MrDwyPb561QKPD39zd0aHqVmZnJ2LFj8fT0xMLCAm9vbyZNmkRBWJvm2bNnDBgwAHd3dywsLKhduzYXLlwwdFjiLSTJRB7ZsmULgwYNYvz48QQFBVGpUiU++eQT4uLiDB2a3iQnJ1OpUiUWLVpk6FDy1bFjx/D39+fs2bMcPHiQjIwMGjduTHJysqFD0ytXV1emTZtGYGAgFy9e5KOPPqJFixZcv37d0KHlmwsXLrBs2TIqVqxo6FDyRbly5YiJidE+Tp48aeiQ9O7x48fUqVMHExMTfvvtN0JCQpg1axZFixY1dGh6deHCBZ3P+uDBgwC0bt3awJHp1/Tp01myZAkLFy4kNDSU6dOnM2PGDBYsWGDo0PSue/fuHDx4kPXr13P16lUaN25Mo0aNePDggaFDE28bjcgTNWrU0Pj7+2ufZ2ZmapydnTUBAQEGjCr/AJodO3YYOgyDiIuL0wCaY8eOGTqUfFe0aFHNihUrDB1Gvnj27JmmZMmSmoMHD2rq1aun6d+/v6FD0qvx48drKlWqZOgw8t3w4cM1devWNXQYBte/f3+Nt7e3Rq1WGzoUvWratKmma9euOmWtWrXStG/f3kAR5Y+UlBSNsbGxZs+ePTrlVatW1YwePdpAUYm3lfRM5IH09HQCAwNp1KiRtszIyIhGjRpx5swZA0Ym8sPTp08BsLW1NXAk+SczM5PNmzeTnJxMrVq1DB1OvvD396dp06Y6v+fvulu3buHs7IyXlxft27fn3r17hg5J73bt2kX16tVp3bo1jo6OVKlShR9//NHQYeWr9PR0NmzYQNeuXVEoFIYOR69q167N4cOHuXnzJgCXL1/m5MmTNGnSxMCR6ZdKpSIzMxNzc3OdcgsLiwLRAynyltwBOw8kJCSQmZmZ7W6CxYoV48aNGwaKSuQHtVrNgAEDqFOnDuXLlzd0OHp39epVatWqRWpqKoUKFWLHjh2ULVvW0GHp3ebNmwkKCipQ44lr1qzJmjVrKFWqFDExMUycOJEPPviAa9euYW1tbejw9CYyMpIlS5YwaNAgRo0axYULF+jXrx+mpqb4+fkZOrx8sXPnTp48eULnzp0NHYrejRgxgqSkJEqXLo2xsTGZmZlMmTKF9u3bGzo0vbK2tqZWrVpMmjSJMmXKUKxYMTZt2sSZM2fw8fExdHjiLSPJhBD/A39/f65du1ZgruSUKlWK4OBgnj59yrZt2/Dz8+PYsWPvdEIRFRVF//79OXjwYLareO+yl6/MVqxYkZo1a+Lu7s7WrVvp1q2bASPTL7VaTfXq1Zk6dSoAVapU4dq1ayxdurTAJBMrV66kSZMmODs7GzoUvdu6dSsbN27kp59+oly5cgQHBzNgwACcnZ3f+c97/fr1dO3aFRcXF4yNjalatSrt2rUjMDDQ0KGJt4wkE3nA3t4eY2NjYmNjdcpjY2MpXry4gaIS+ta3b1/27NnD8ePHcXV1NXQ4+cLU1FR71apatWpcuHCBefPmsWzZMgNHpj+BgYHExcVRtWpVbVlmZibHjx9n4cKFpKWlYWxsbMAI84eNjQ2+vr6Eh4cbOhS9cnJyypYclylThu3btxsoovx19+5dDh06xC+//GLoUPLF0KFDGTFiBG3btgWgQoUK3L17l4CAgHc+mfD29ubYsWMkJyeTlJSEk5MTbdq0wcvLy9ChibeMzJnIA6amplSrVo3Dhw9ry9RqNYcPHy4w48kLEo1GQ9++fdmxYwd//PEHnp6ehg7JYNRqNWlpaYYOQ68aNmzI1atXCQ4O1j6qV69O+/btCQ4OLhCJBMDz58+JiIjAycnJ0KHoVZ06dbIt9Xzz5k3c3d0NFFH+Wr16NY6OjjRt2tTQoeSLlJQUjIx0vwoZGxujVqsNFFH+s7KywsnJicePH7N//35atGhh6JDEW0Z6JvLIoEGD8PPzo3r16tSoUYO5c+eSnJxMly5dDB2a3jx//lznKuXt27cJDg7G1tYWNzc3A0amX/7+/vz000/8+uuvWFtb8/DhQwCKFCmChYWFgaPTn5EjR9KkSRPc3Nx49uwZP/30E0ePHmX//v2GDk2vrK2ts82HsbKyws7O7p2eJzNkyBCaNWuGu7s70dHRjB8/HmNjY9q1a2fo0PRq4MCB1K5dm6lTp/L1119z/vx5li9fzvLlyw0dmt6p1WpWr16Nn58fSmXB+HrQrFkzpkyZgpubG+XKlePSpUvMnj2brl27Gjo0vdu/fz8ajYZSpUoRHh7O0KFDKV269Dv9vUXoiaGXk3qXLFiwQOPm5qYxNTXV1KhRQ3P27FlDh6RXR44c0QDZHn5+foYOTa9yajOgWb16taFD06uuXbtq3N3dNaamphoHBwdNw4YNNQcOHDB0WAZREJaGbdOmjcbJyUljamqqcXFx0bRp00YTHh5u6LDyxe7duzXly5fXmJmZaUqXLq1Zvny5oUPKF/v379cAmrCwMEOHkm+SkpI0/fv317i5uWnMzc01Xl5emtGjR2vS0tIMHZrebdmyRePl5aUxNTXVFC9eXOPv76958uSJocMSbyGFRlMAbvMohBBCCCGEyHMyZ0IIIYQQQgiRK5JMCCGEEEIIIXJFkgkhhBBCCCFErkgyIYQQQgghhMgVSSaEEEIIIYQQuSLJhBBCCCGEECJXJJkQQgghhBBC5IokE0IIIYQQQohckWRCCCHeMJ07d6Zly5ba5/Xr12fAgAH5HsfRo0dRKBQ8efIk348thBDi7SDJhBBCvKbOnTujUChQKBSYmpri4+PD999/j0ql0utxf/nlFyZNmvRadSUBEEIIkZ+Uhg5ACCHeJp9++imrV68mLS2Nffv24e/vj4mJCSNHjtSpl56ejqmpaZ4c09bWNk/2I4QQQuQ16ZkQQoj/wMzMjOLFi+Pu7k6fPn1o1KgRu3bt0g5NmjJlCs7OzpQqVQqAqKgovv76a2xsbLC1taVFixbcuXNHu7/MzEwGDRqEjY0NdnZ2DBs2DI1Go3PMvw9zSktLY/jw4ZQoUQIzMzN8fHxYuXIld+7coUGDBgAULVoUhUJB586dAVCr1QQEBODp6YmFhQWVKlVi27ZtOsfZt28fvr6+WFhY0KBBA504hRBCiJxIMiGEEP8DCwsL0tPTATh8+DBhYWEcPHiQPXv2kJGRwSeffIK1tTUnTpzg1KlTFCpUiE8//VS7zaxZs1izZg2rVq3i5MmTJCYmsmPHjn88ZqdOndi0aRPz588nNDSUZcuWUahQIUqUKMH27dsBCAsLIyYmhnnz5gEQEBDAunXrWLp0KdevX2fgwIF06NCBY8eOAVlJT6tWrWjWrBnBwcF0796dESNG6OttE0II8Y6QYU5CCJELGo2Gw4cPs3//fr777jvi4+OxsrJixYoV2uFNGzZsQK1Ws2LFChQKBQCrV6/GxsaGo0eP0rhxY+bOncvIkSNp1aoVAEuXLmX//v2vPO7NmzfZunUrBw8epFGjRgB4eXlpX///IVGOjo7Y2NgAWT0ZU6dO5dChQ9SqVUu7zcmTJ1m2bBn16tVjyZIleHt7M2vWLABKlSrF1atXmT59eh6+a0IIId41kkwIIcR/sGfPHgoVKkRGRgZqtZpvvvmGCRMm4O/vT4UKFXTmSVy+fJnw8HCsra119pGamkpERARPnz4lJiaGmjVral9TKpVUr14921Cn/xccHIyxsTH16tV77ZjDw8NJSUnh448/1ilPT0+nSpUqAISGhurEAWgTDyGEEOJVJJkQQoj/oEGDBixZsgRTU1OcnZ1RKv86jVpZWenUff78OdWqVWPjxo3Z9uPg4JCr41tYWPznbZ4/fw7A3r17cXFx0XnNzMwsV3EIIYQQIMmEEEL8J1ZWVvj4+LxW3apVq7JlyxYcHR0pXLhwjnWcnJw4d+4cH374IQAqlYrAwECqVq2aY/0KFSqgVqs5duyYdpjTy/6/ZyQzM1NbVrZsWczMzLh3794rezTKlCnDrl27dMrOnj37740UQghRoMkEbCGE0JP27dtjb29PixYtOHHiBLdv3+bo0aP069eP+/fvA9C/f3+mTZvGzp07uXHjBt9+++0/3iPCw8MDPz8/unbtys6dO7X73Lp1KwDu7u4oFAr27NlDfHw8z58/x9ramiFDhjBw4EDWrl1LREQEQUFBLFiwgLVr1wLQu3dvbt26xdChQwkLC+Onn35izZo1+n6LhBBCvOUkmRBCCD2xtLTk+PHjuLm50apVK8qUKUO3bt1ITU3V9lQMHjyYjh074ufnR61atbC2tuaLL774x/0uWbKEr776im+//ZbSpUvTo0cPkpOTAXBxcWHixImMGDGCYsWK0bdvXwAmTZrE2LFjCQgIoEyZMnz66afs3bsXT09PANzc3Ni+fTs7d+6kUqVKLF26lKlTp+rx3RFCCPEuUGheNctPCCGEEEIIIf6B9EwIIYQQQgghckWSCSGEEEIIIUSuSDIhhBBCCCGEyBVJJoQQQgghhBC5IsmEEEIIIYQQIlckmRBCCCGEEELkiiQTQgghhBBCiFyRZEIIIYQQQgiRK5JMCCGEEEIIIXJFkgkhhBBCCCFErkgyIYQQQgghhMiV/wMx5SkC9qnOHgAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -1338,7 +1347,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 71, "metadata": { "tags": [] }, @@ -1381,7 +1390,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 72, "metadata": {}, "outputs": [], "source": [ @@ -1430,12 +1439,12 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 73, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1445,7 +1454,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1505,14 +1514,14 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 74, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1522,7 +1531,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1585,12 +1594,12 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 75, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1600,7 +1609,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1610,7 +1619,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABDoUlEQVR4nO2dd3xUVfr/P5MyM+k9hJ4EEDACgVAMIKHj0mRBwYgo/hAQUBcEXBSXorgKKKAIWL4KSlFAaVZEBBQJEDoKUhM6CQmQXmfO7w+YIZPznDA3JJmBfd6vZZ2ceebc555z7zxz73nu59EJIQQYhmEYxk5cHO0AwzAMc3fBgYNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNMGBg2EYhtEEBw6GYRhGExw4GIZhGE1w4GAYhmE0wYHjLqdjx47o2LGjo92Q0Ol0mDZtmqPdUHIn4xYeHo6hQ4dWqD+OZtq0adDpdI52Q8JZj+//dThwOACdTmfXv61bt1aqHytWrMC8efMqdRtlkZycbN3XGTNmkDaDBw+GTqeDt7d3FXvn/HTs2NGu46iyA/iOHTswbdo0XL9+vVK3Yy/Xr19HaGgodDodvv76a0e7c0/i5mgH/hdZunSpzd9ffPEFNm3aJLU3btz4tn39/PPP5fZjxYoV+PPPPzF27Nhy91ERGI1GfPnll3jttdds2nNycrB+/XoYjUYHeebcTJ48Gc8++6z178TERLz//vt49dVXbY6dpk2b3rav1157DZMmTSqXHzt27MD06dMxdOhQ+Pv7l6uPimTKlCnIzc11tBv3NBw4HMCTTz5p8/fOnTuxadMmqd0e9Hp9RbnlMHr27Ik1a9bg4MGDaNasmbV9/fr1KCwsxMMPP4xff/3VgR46J926dbP522g04v3330e3bt00395xc3ODm9vd/3Xw559/YtGiRZgyZQqmTJniaHfuWfhWlZOyePFidO7cGaGhoTAYDLj//vuxaNEiya70PeCtW7dCp9Nh1apVePPNN1GrVi0YjUZ06dIFJ0+etPnc999/jzNnzlhvaYSHh1vfLygowNSpU1G/fn0YDAbUrl0bL7/8MgoKCmy2X1BQgHHjxiEkJAQ+Pj7o27cvzp8/r2lfY2NjERERgRUrVti0L1++HA8//DACAwPJzy1cuBBRUVEwGAyoUaMGxowZQ94u+fjjj1GvXj14eHigdevW+P3338n+7N1ne8nJycH48eNRu3ZtGAwGNGzYEO+88w5KC1LrdDo8//zzWLduHR544AEYDAZERUXhp59+Ktd2S/L777/jscceQ506daz7NG7cOOTl5dnYUWsc9vg1bdo0TJw4EQAQERFhPZaSk5OtNsuWLUNMTAw8PDwQGBiIxx9/HOfOnZN8tXeeyuJf//oX/vnPf+Khhx7S/FnGfu7+nxj3KIsWLUJUVBT69u0LNzc3fPvttxg9ejTMZjPGjBlz28+//fbbcHFxwYQJE5CRkYFZs2Zh8ODB2LVrF4AbtzkyMjJw/vx5zJ07FwCs6whmsxl9+/bF9u3bMWLECDRu3BiHDx/G3Llzcfz4caxbt866nWeffRbLli3DE088gbZt2+LXX39Fr169NO9vfHw8li1bhrfffhs6nQ5paWn4+eefsXTpUvILdNq0aZg+fTq6du2KUaNG4dixY1i0aBESExPxxx9/wN3dHQDw6aefYuTIkWjbti3Gjh2L06dPo2/fvggMDETt2rWt/WnZZ3sQQqBv377YsmULhg0bhujoaGzcuBETJ07EhQsXrGNuYfv27VizZg1Gjx4NHx8fvP/++xgwYADOnj2LoKAgzeNpYfXq1cjNzcWoUaMQFBSE3bt3Y/78+Th//jxWr15928/fzq/+/fvj+PHj+PLLLzF37lwEBwcDAEJCQgAAb775Jv7zn/9g4MCBePbZZ3HlyhXMnz8fHTp0wP79+623tuydp9vt644dO3D06FGbwMVUAoJxOGPGjBGlpyI3N1ey69Gjh4iMjLRpi4uLE3Fxcda/t2zZIgCIxo0bi4KCAmv7e++9JwCIw4cPW9t69eol6tatK21n6dKlwsXFRfz+++827R9++KEAIP744w8hhBAHDhwQAMTo0aNt7J544gkBQEydOrXM/U5KShIAxOzZs8Wff/4pAFi3uWDBAuHt7S1ycnLE008/Lby8vKyfS01NFXq9XnTv3l2YTCZr+wcffCAAiM8++0wIIURhYaEIDQ0V0dHRNmPx8ccfCwA242bvPgshRN26dcXTTz9d5r6tW7dOABAzZsywaX/00UeFTqcTJ0+etLYBEHq93qbt4MGDAoCYP39+mdspyerVqwUAsWXLFmsbdRy99dZbQqfTiTNnzljbpk6dKh2D9vo1e/ZsAUAkJSXZfD45OVm4urqKN99806b98OHDws3NzdquZZ5U5Obmijp16ohXXnlFCHHrPFi9evVtP8toh29VOSkeHh7W1xkZGUhLS0NcXBxOnz6NjIyM237+mWeesVn/sFy6nz59+rafXb16NRo3boxGjRohLS3N+q9z584AgC1btgAAfvjhBwDAiy++aPP58iy2R0VFoWnTpvjyyy8B3Fi4f+SRR+Dp6SnZ/vLLLygsLMTYsWPh4nLrEB4+fDh8fX3x/fffAwD27NmD1NRUPPfcczZjMXToUPj5+ZVrn+3lhx9+gKurqzQ248ePhxACP/74o017165dUa9ePevfTZs2ha+vr13zVRYlj6OcnBykpaWhbdu2EEJg//79t/38nfi1Zs0amM1mDBw40GZMw8LC0KBBA+uYapknFW+//TaKiorw6quv2mXP3Bl8q8pJ+eOPPzB16lQkJCRIGSIZGRm3PaHq1Klj83dAQAAA4Nq1a7fd9okTJ3D06FHr7YbSpKamAgDOnDkDFxcXmy8WAGjYsOFtt0HxxBNP4N1338W4ceOwY8cO5ZfAmTNnyO3o9XpERkZa37f8t0GDBjZ27u7uiIyMtGmzd5/t5cyZM6hRowZ8fHxs2i3ZThbfLJSeL+DGnNkzX2Vx9uxZTJkyBRs2bJD6sucHyJ34deLECQghpPG3YLmdqGWeKJKTkzF79mwsWLCA07arCA4cTsipU6fQpUsXNGrUCHPmzEHt2rWh1+vxww8/YO7cuTCbzbftw9XVlWwXdlQKNpvNaNKkCebMmUO+b+89Z63Ex8fjlVdewfDhwxEUFITu3btXynYoHLXPFu5kvlSYTCZ069YNV69exb///W80atQIXl5euHDhAoYOHVolx5FOp8OPP/5I9lNRX/JTpkxBzZo10bFjR+vaxuXLlwEAV65cQXJyMurUqWNzdcrcGRw4nJBvv/0WBQUF2LBhg80vPq23S26H6knhevXq4eDBg+jSpUuZTxPXrVsXZrMZp06dsvn1f+zYsXL5U6dOHbRr1w5bt27FqFGjlOmhdevWtW6n5C/SwsJCJCUloWvXrjZ2J06csN5yAoCioiIkJSXZpP7au8/2UrduXfzyyy/Iysqyuer4+++/bXyrTA4fPozjx4/j888/x1NPPWVt37RpU4Vup6zjSAiBiIgI3HfffcrPa5knirNnz+LkyZPk1cno0aMB3LjSdoZnTO4VOAQ7IZZfZyV/1WVkZGDx4sUVuh0vLy/ydsXAgQNx4cIFfPLJJ9J7eXl5yMnJAQD84x//AAC8//77NjZ38jT6jBkzMHXqVLzwwgtKm65du0Kv1+P999+3GaNPP/0UGRkZ1qyuli1bIiQkBB9++CEKCwutdkuWLJHSdu3dZ3vp2bMnTCYTPvjgA5v2uXPnQqfTWceuMqGOIyEE3nvvvQrdjpeXFwBIY9q/f3+4urpi+vTp0hWKEALp6ekAtM0TxYwZM7B27Vqbf2+88QYA4OWXX8batWutPjIVA19xOCHdu3eHXq9Hnz59MHLkSGRnZ+OTTz5BaGgoLl26VGHbiYmJwcqVK/HSSy+hVatW8Pb2Rp8+fTBkyBCsWrUKzz33HLZs2YJ27drBZDLh77//xqpVq7Bx40a0bNkS0dHRiI+Px8KFC5GRkYG2bdti8+bNNs+LaCUuLg5xcXFl2oSEhOCVV17B9OnT8fDDD6Nv3744duwYFi5ciFatWlkfpHR3d8eMGTMwcuRIdO7cGYMGDUJSUhIWL14s/Tq1d5/tpU+fPujUqRMmT56M5ORkNGvWDD///DPWr1+PsWPHSutClUGjRo1Qr149TJgwARcuXICvry+++eabO143KU1MTAyAGynejz/+ONzd3dGnTx/Uq1cPM2bMwCuvvILk5GT069cPPj4+SEpKwtq1azFixAhMmDBB0zxRtG/fXmqzXF20atUK/fr1q8jdZQBOx3UGqHTcDRs2iKZNmwqj0SjCw8PFzJkzxWeffSalParScUunIVpSXxcvXmxty87OFk888YTw9/cXAGxScwsLC8XMmTNFVFSUMBgMIiAgQMTExIjp06eLjIwMq11eXp548cUXRVBQkPDy8hJ9+vQR586d05yOWxal03EtfPDBB6JRo0bC3d1dVKtWTYwaNUpcu3ZNslu4cKGIiIgQBoNBtGzZUvz222/SuGnZZ3vScYUQIisrS4wbN07UqFFDuLu7iwYNGojZs2cLs9lsYwdAjBkzRvq8vduxQKXjHjlyRHTt2lV4e3uL4OBgMXz4cGtKbcljQZWOa69fb7zxhqhZs6ZwcXGRjtFvvvlGtG/fXnh5eQkvLy/RqFEjMWbMGHHs2DGbPuydJ3vgdNzKRSfEHay+MQzDMP9z8BoHwzAMowkOHAzDMIwmOHAwDMMwmuDAwTAMw2jCoYHjTspVLlmyRJJvrmgsFeqWLFlSadvQyt1QSrN0aVXLXO3Zs6dKtn83jNHdBnW+hYeHo3fv3lWyfUu5gMquilnV3K37Va7A8ddff+HJJ59EzZo1rbUQBg8ejL/++qui/WPuEJPJhBo1alilHygWLlxIBscjR45g2rRpTilR7cy+VQULFy6ETqdDmzZtyPfLGh/VfDsDzuqbEAJLly5Fhw4d4O/vD09PTzRp0gSvv/665odD7wm05u9+8803Qq/Xi7CwMDF58mTxf//3f+K1114T1atXF3q9XqxZs8buvoqKikReXp5WF4QQQhQXF4u8vDwpJ74ioZ59cDRa89p//vlnAUCEh4eLwYMHkzZRUVFkn9RzAfaQn58vCgsLrX8vXrxYABCJiYma+imLsnwrKCiwkee+F2nbtq0IDw8XAMSJEyek98saH9V8lwV1vtWtW1f06tVLq+tlovLNZDKJvLw8Gxn9qqK4uFgMHDhQABAPPfSQmDt3rvjoo4/Ek08+KVxcXMQDDzwgLl++XK6+Lc+baD3HHI2mK45Tp05hyJAhiIyMxKFDhzBjxgwMGzYMb7zxBg4dOoTIyEgMGTLktpLLlgjt5uZW7nrSrq6uMBqNFaIrdC+zbNkytGjRAuPGjcO6desq7deREMJaVc5gMFiVTx2BXq+/J0rqqkhKSsKOHTswZ84chISEYPny5ZW2Lcvx4ujzzcXFBUaj0SFChbNmzcKqVaswYcIE/Pbbbxg7dixGjBiBpUuXYt26dThy5IjNrdn/CbREmZEjRwoA4rfffiPf37ZtmwAgRo4caW2zPJH6119/ifj4eOHv7y+io6Nt3itJbm6ueOGFF0RQUJDw9vYWffr0EefPn5eeRLb8ii35hKrlF9Dvv/8uWrVqJQwGg4iIiBCff/65zTbS09PF+PHjxQMPPCC8vLyEj4+PePjhh8WBAwds7Oy94rC3P8uvi5UrV4oZM2aImjVrCoPBIDp37kz+avzoo49EZGSkMBqNolWrVpqfpM3NzRU+Pj5i1qxZ4tKlS8LFxUUsX77cxqZu3boCgM2/uLg46/iW/mf5ZWQZ659++knExMQIg8Eg5s6da32v5JPFlr62bdsmRowYIQIDA4WPj48YMmSIuHr1qo0/pee5pJ+WPm/nGzVGKSkp4v/9v/8nQkNDhcFgEE2bNhVLliyxsSn5JLtl7PV6vWjZsqXYvXu3XWNeFbzxxhsiICBAFBQUiFGjRokGDRrYvF/W+Kjmu+Tntm7dKkaNGiVCQkKEv7+/zXvU+bZx40bRrFkzYTAYROPGjcU333xj4w91nlN9luWb6pf5qlWrRIsWLYTRaBRBQUFi8ODB4vz58zY2FuWB8+fPi0ceeUR4eXmJ4OBgMX78eFFcXFzmWOfm5oqAgABx3333iaKiItLmmWeeEQBEQkKCNDa3+y4qvV9TpkwRbm5uIjU1VdrO8OHDhZ+fX7nv0lQkmsL3t99+i/DwcGU93w4dOiA8PNxaSKckjz32GHJzc/Hf//4Xw4cPV25j6NChmD9/Pnr27ImZM2fCw8NDUynSkydP4tFHH0W3bt3w7rvvIiAgAEOHDrVZfzl9+jTWrVuH3r17Y86cOZg4cSIOHz6MuLg4XLx40e5tlbe/t99+G2vXrsWECRPwyiuvYOfOnRg8eLCNjaWUZlhYGGbNmoV27dqhb9++ZK1mFRs2bEB2djYef/xxhIWFoWPHjtKv03nz5qFWrVpo1KgRli5diqVLl2Ly5Mno0KGDtQjRq6++an3PUk8CuKFOGx8fj27duuG9995DdHR0mf48//zzOHr0KKZNm4annnoKy5cvR79+/TRLh9vjW0ny8vLQsWNHLF26FIMHD8bs2bPh5+eHoUOHkoJ/K1aswOzZszFy5EjMmDEDycnJ6N+/P4qKijT5WVksX74c/fv3h16vR3x8PE6cOIHExETr+2WNj2q+SzJ69GgcOXIEU6ZMwaRJk8r05cSJExg0aBD+8Y9/4K233oKbmxsee+yxcinw2uNbSZYsWYKBAwfC1dUVb731FoYPH441a9agffv2kjiiyWRCjx49EBQUhHfeeQdxcXF499138fHHH5fp0/bt23Ht2jU88cQTSrVmi/Lwd999Z9Nuz3dRaYYMGYLi4mKsXLnSpr2wsBBff/01BgwYUO67NBWKvRHm+vXrAoB45JFHyrTr27evACAyMzOFELd+bcTHx0u2pX+J7N27VwAQY8eOtbEbOnSo3VccKHVFlJqaKgwGgxg/fry1LT8/X7pXmpSUJAwGg3j99ddt2mDHFYe9/dlb1rUiSmkKIUTv3r1Fu3btbD5P/ZopzxqHZax/+ukn8j3qiiMmJsZm7WPWrFkCgFi/fr21rfQ8q/osy7fSVxzz5s0TAMSyZcusbYWFhSI2NlZ4e3tbj1XLfAcFBdlcCa1fv14AEN9++620rapmz549AoDYtGmTEEIIs9ksatWqJf71r3/Z2JVnjcMyT+3bt5d+iZd1vpW8wsjIyBDVq1cXzZs3t7bZe8VRlm+lf5lbzpEHHnjA5hf4d999JwCIKVOmWNuefvppAcDmXBRCiObNm4uYmBhpWyWxHDtr165V2ly9elUAEP3797e22ftdRF1JxcbGijZt2thsY82aNU61FmL3FUdWVhYASBXNSmN5PzMz06b9ueeeu+02fvrpJwC3NPQtlCWxXZr777/f5oooJCQEDRs2tFl3MRgM1nulJpMJ6enp8Pb2RsOGDbFv3z67t1Xe/m5X1rUiSmmmp6dj48aNiI+Pt7YNGDAAOp0Oq1at0ryPFBEREejRo4fd9iNGjLBZ+7DU3LCUoK0sfvjhB4SFhdmMhbu7O1588UVkZ2dj27ZtNvaDBg2yVkwEtJXdrWyWL1+OatWqoVOnTgBu1MIYNGgQvvrqK5hMpgrZxvDhw5UFnEpTo0YN/POf/7T+7evri6eeegr79++3FlOqDCznyOjRo21+gffq1QuNGjUi73qU/g566KGHbjun9nzvqb7z7Pkuonjqqaewa9cunDp1ytq2fPly1K5d+7bK0VWF3YHDMjiWgVShGuiIiIjbbsNSirS0bf369e11065Sl2azGXPnzkWDBg1gMBgQHByMkJAQHDp0yK5ymqXR2t/tyrreaSlNAFi5ciWKiorQvHlznDx5EidPnsTVq1fRpk2bCltMtWdOS1J6f7y9vVG9evVKT6k9c+YMGjRoIC2s2lvGVUvZ3crEZDLhq6++QqdOnZCUlGSd1zZt2iAlJQWbN2+ukO1omdf69etLC+aWok2VOa+q8sHADTn50nNqNBqlssD2lMC153tP9Z1X3rK7gwYNgsFgsJ6nGRkZ+O677zB48GCnSQayO3D4+fmhevXqOHToUJl2hw4dQs2aNeHr62vT7uHhUT4PNWJPqcv//ve/eOmll9ChQwcsW7YMGzduxKZNmxAVFWVXOc3SaO2vMsqElsZy0LVr1w4NGjSw/tu+fTsSEhIq5NdzVc0pgAr7NW0PVTE/5eHXX3/FpUuX8NVXX9nM6cCBAwGgwn4QVPS8qr7snGFOb4flx0VZ33uW9+6//367tnm74yggIAC9e/e2zufXX3+NgoICa50ZZ0BTIafevXvjk08+wfbt28niKb///juSk5MxcuTIcjljKUWalJRk8+v0TgoDUXz99dfo1KkTPv30U5v269evIzg42OH93WkpTUu65vPPPy9d2prNZgwZMgQrVqzAa6+9BkB9Ylf0r5sTJ05Yb7EAQHZ2Ni5duoSePXta2wICAqSFzcLCQqmAlRbf6tati0OHDsFsNttcdVRlGdeKYPny5QgNDcWCBQuk99asWYO1a9fiww8/hIeHR5njU5HzevLkSQghbPo8fvw4gBtPlgO3rtiuX79uU7619FWBFt9Klg8ueY5Y2ipqTtu3bw9/f3+sWLECkydPJoPBF198AQAV+hT9U089hUceeQSJiYlYvnw5mjdvjqioqArr/07RlFU1ceJEeHh4YOTIkdayjxauXr2K5557Dp6enpg4cWK5nLHcL1+4cKFN+/z588vVnwpXV1cp6q9evRoXLlxwiv7utJSm5ZfKyy+/jEcffdTm38CBAxEXF2fz69TLy4vsV1UStLx8/PHHNplJixYtQnFxsU0Z1Xr16uG3336TPlf616kW33r27InLly/bZKoUFxdj/vz58Pb2dpr7xmWRl5eHNWvWoHfv3tKcPvroo3j++eeRlZWFDRs2ACh7fFTzXR4uXryItWvXWv/OzMzEF198gejoaISFhQGAtdphyXnNycnB559/Xm7fWrZsidDQUHz44YcoKCiwtv/44484evSopkzMsvD09MSECRNw7NgxMsPr+++/x5IlS9CjRw88+OCDFbJN4EZZ5uDgYMycORPbtm1zqqsNQOMVR4MGDfD5559j8ODBaNKkCYYNG4aIiAgkJyfj008/RVpaGr788styl8WMiYnBgAEDMG/ePKSnp+PBBx/Etm3brL9gKuqXUu/evfH666/jmWeeQdu2bXH48GEsX77c7vWDyu7vTktpLl++HNHR0ahduzb5ft++ffHCCy9g3759aNGiBWJiYrBo0SLMmDED9evXR2hoKDp37ozo6Gi4urpi5syZyMjIgMFgQOfOnREaGlqu/SosLESXLl0wcOBAa6nX9u3bo2/fvlabZ599Fs899xwGDBiAbt264eDBg9i4caN05abFtxEjRuCjjz7C0KFDsXfvXoSHh+Prr7/GH3/8gXnz5t024cMZ2LBhA7KysmzGqiQPPvig9WHAQYMGlTk+qvkuD/fddx+GDRuGxMREVKtWDZ999hlSUlKwePFiq0337t1Rp04dDBs2DBMnToSrqys+++wzhISE4OzZszb92eubu7s7Zs6ciWeeeQZxcXGIj49HSkoK3nvvPYSHh2PcuHHl2h+KSZMmYf/+/Zg5cyYSEhIwYMAAeHh4YPv27Vi2bBkaN25MBsE7wd3dHY8//jg++OADuLq62iR2OAXlScU6dOiQiI+PF9WrVxfu7u4iLCxMxMfHW9NJS2JJxbty5YryvZLk5OSIMWPGiMDAQOHt7S369esnjh07JgCIt99+22pX1gNJpSmdnpmfny/Gjx8vqlevLjw8PES7du1EQkKCZKclHdee/rSUdRWifKU0LSnN//nPf5Q2ycnJAoAYN26cEEKIy5cvi169egkfHx8p3feTTz4RkZGRwtXVlXwAkOJ2DwAGBAQIb29vMXjwYJGenm7zWZPJJP7973+L4OBg4enpKXr06CFOnjxJlitV+aZ6APCZZ54RwcHBQq/XiyZNmkjjXVYpW9hRCrcy6dOnjzAajSInJ0dpM3ToUOHu7i7S0tKEEOrxUc13WdIwt3sAsGnTpsJgMIhGjRqR5Vr37t0r2rRpI/R6vahTp46YM2cO2afKN9UDgCtXrhTNmzcXBoNBBAYGlvkAYGlUacIUJpNJLF68WLRr1074+voKo9EooqKixPTp00V2drZkb+93UVmSI7t37xYARPfu3e3ysSq5K0rHHjhwAM2bN8eyZcukB+UYhmHuRQ4ePIjo6Gh88cUXGDJkiKPdscHp6nFY9I5KMm/ePLi4uKBDhw4O8IhhGKbq+eSTT+Dt7Y3+/fs72hUJTWscVcGsWbOwd+9edOrUCW5ubvjxxx/x448/YsSIEcp79gzDMPcK3377LY4cOYKPP/4Yzz//vDXRwZlwultVmzZtwvTp03HkyBFkZ2ejTp06GDJkCCZPnqzUimEYhrlXCA8PR0pKCnr06IGlS5c6ZfKG0wUOhmEYxrlxujUOhmEYxrnhwMEwDMNowiGLBmazGRcvXoSPj4/TiHYx9yZCCGRlZaFGjRoOqR5Hwcc/U5VUxjngkMBx8eJFzpBiqpRz586hVq1ajnYDAB//jGOoyHPAIYHDkiUwf8EiSYmzWfMYyf7XX34m++nx8MNS28abNT1K06Vrd6lts6Lfjl26ke1bf5GrmlE+AMDGjbIf3brTtSs2bdwotXXpJvsLqH3u2k3u+5ef5X4BILZjF6ktYSstyR1HjMW2X+nqbp270D5T8/ePnv8gLG9oDZWG2jeA3j+Tudjm7/z8fLw+bapTZaZYfDl++ix8fGxVpLPziyV7X0+6frvJLOe1uLrQVzDZeXL1Qi8jffpfyy4k2/295DruZkVujZur/Ms2r5BWw9W7EbYF8jgAap+pvo3utDrt2fRcqa1OkCdpm55dILWF+NIV+DJy6HHz8ZDnz0UxT1SuUm4BPW5Gvbx/1PxnZWaifkTtCj0HHBI4LJfnHh4e8PS0nTBvYudUMs/UQKhstfTr7U0PsJGwV00G1Tflg6pfla2W/aP6Bej902KrxQdV35U1biYT/YXjTLeELL74+PhK5Qd0+soJHDp3OXB4K76Ei13oL0DfOwwc7hoCh5sicKh8diP69lAEDu9CuQ9fXzpwFOrkwOGrCBxmV8W43WHgcFUEDg87A4eFijwHnOOmL8MwDHPXwIGDYRiG0YRDH8WuVqsuvLy8bdrS09IkO1Xp2CtXZNt69Wjbq6XqhwBA3Qha/j036zrZXidCljRPSb1C2kZEyn2nKmwbNJB9zrh2lbRV+XzxcqrUpho3qu9IhRR+XvZ1qU01xteuyWMM0PtH+avq+1IKbUv5fOL4MdLWGUnNKkAebG+FeBnk2w9m4paUql31PC91CyNXcesoyMdAtmfkyre73F3p2x/FhG/FJrq6ptFd/v1K3YYB1D5n5cm3tgzELTAA8CT6LlT4Fuon35ZS7YdBcWuMukOUo7gVR/msWhuixt5FJ3++Mp7x5isOhmEYRhMcOBiGYRhNcOBgGIZhNMGBg2EYhtGEQxfHjxzcJ+XtRxKLo7t37SQ/37J1G6ltz+5dpG2zmNZS2/49tG2r1nTR+f17dhO2sg8AsHuX3HdsLN3vzp3y/rVuQ9uq9q9FK3n/9iXK/gK0z7t302PcNjZWaqP8Bej5AIC9ibLPqv2j5rpp81ak7aH9iVKbv78/aeuMhPkZpWcCCovlhVdVzn8BYataVM4gFo/9POjTn3oIEQD8iOdJCopUC7fyb1I90QbQzxeong9RPZtRbJLtVc8t+BL77abhuQoXRb8mM71oTvlBjQ9AP/+iWtymnn+htlUZzzDxFQfDMAyjCQ4cDMMwjCY4cDAMwzCa4MDBMAzDaIIDB8MwDKMJh9Qcz8zMhJ+fHzZu3ipJjlCZAipZj2qhIVJbOiEtAgBuHr5SW1FuBmnrHxhEtlNSHR4+/qRtTsY1qc3HP5C0vXZV9tlXYZubKfcLACEhwVKbatxCQuRxU8mhePoGSG2UvwBQt2Y1sj2VkIbxD6D37wohOVOjWihpe5Xw4+jRozZ/5+fn4dVJ/0ZGRoakROsoLMf/yfNp8Cnlk7dBzvhRyWFQ8hSqDJrkKzlSW91gWhE2v4jeHpWxlZopq8cCQKCXnIGVSWR2AfR+ZCskOYK8ZYVegM50ojLUADpLTSUjkk5IzFPfUQAQopBqoVSM8xXZaJS6DCVDA9ifgZWZmYmwYP8KPQf4ioNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNOFQyZED+/ZKkiNUHYtdCsmRBx+U5TB2KeQwKEkOSkIE0CYj0uZB+6UzVDIblCRHy1a0D3sIW5UfiSp5kpbyWOxVyJM0i5HlPg7tk6U+AMDNRe4XAPYS0i5tFGNByaQYNEi13E2SIz4e7lJZUUrCQyWHQclsKJQsEECUfVWhEqig6n8EKMraUvU/VGVfqboSKpUMakEYoBegDUSdDwDIIiRVqKSEG33IC9OqBfpMoq47QO+3aoGdkiLRohjCkiMMwzCMU8KBg2EYhtEEBw6GYRhGExw4GIZhGE1w4GAYhmE04VDJkZ83b4OXt63kCJUAkEZIVgBAYJAsDaKSHCFtCXkLAKiukLhIvSLLckRGhJO2QTXkdn9FBsqu3XKWkrs7neVxRcNYXFWMRQAhqXI1ne6XkidR2QaEhJHtXl5eUltedhZpm56WKrUp5Veyrkttd5PkSNLFdElyhJLOUJ2ixUQmkasig4ayVSXbeCqKQVGZS6rsoJMp9kucUNIgVFaWygdVuyobjSqA5UZkdgH0eKpsVfIrFKWz6SwYiUwwVWGtIIXESWkyMzNRLciPJUcYhmEYx8GBg2EYhtEEBw6GYRhGExw4GIZhGE04VHJk/749dkmOqGQ2KGmQPQqZjQcJSY59CskRlRzG4UMHpbaOnbuQtjnEgpZqYe+XnzdKbW3bynIqAJC4m5ZUiY2V7SkpE4CWJ1GNBSWTQo0DALzwL3osdJAXIxMS95G2lLxMq9b0fFBzHRDgT9o6Ix56V2khmloo1hOyFwBQQNTNUC1Wm4kFdq0L0FTfqhob1IK+qj4GtRhP1cwA1HUzKFkN1f4Zif1TmKKIkHVRjbGPQlJFSx0TL4NRaqNkTwBaAoZKeKiM/Ce+4mAYhmE0wYGDYRiG0QQHDoZhGEYTHDgYhmEYTXDgYBiGYTThUMmRLdt+h3cpyREqo+MKIfUBAKGEHMYVhYxISHCw1EZJiABArdq1yfaG9zWU2lSDRxWn2X/gAGlLSaqEhMj+AsD5S7Ikh8o+89pV0jaIGIuUVHoswkLlMb6/SVPSVpU1k5N5XWo7mXSGts2QfQ4Mosfi2lVZUuX4sb9t/nZmyZGUdNknagxVpyiVNaQ6m6lsG0qGBKCzdVSoLD2ITCCVLbV/qoyoazl0sSTK3stAZyNRY0TJkAC0BEhOgVxsC6ALRAGAn4ecbZWt6IMqjKXKcnMnsrvIzDeWHGEYhmEcDQcOhmEYRhMcOBiGYRhNcOBgGIZhNMGBg2EYhtGEQ7Wqdu/aDWMprarIerJWVaJCfyqmlaxVpdJnonStdu+ibevXr0+2Z+TJGR0q3ZoP3p8vtUU90IS03U3oM1EaUQCwX6EpFRsr21O6TwA9FokK2379HpHaihQZKJSuDwB8seQzqa158xakLTUnlM4YAOzaKft8N2lVmc1CymCiNKWMCq2inAI5i8fLQJ/S+YVyFg+VlQMAJh09j0mpcnEmb4U+k1eg3K7KuqMyEIsVx5KqGBqVNUbpVwFAQZE8FgbFWFDZWtS4A0AeMcYAUMNf1p+i9KsAupAXdUyobKsKvuJgGIZhNMGBg2EYhtEEBw6GYRhGExw4GIZhGE04dHG8WYsYeHnZSo4YiUUjajEXAEIIyRGqoBEABAYFSW1dutKFh2rWrku2UyoIqoIz1EK4t18AaUsVVqIkUgCgRcvWZHtAoLx/Klt/wrZHz96kbeMoeT9yFYuAOoWoRDSxEK739idtqYVwat9UtsdKSY44M1l5RYC7bcKFv5desqMWcwHA3dX+332qhXAK1eJvjQB5kddN4QOVQHE9l5YLCfKW91klOZJJJKgA9GKzajGeUvBQya9QkiOqJBBqkV/V96Xr+aRtTWKMVftBJea4oGoWzPmKg2EYhtEEBw6GYRhGExw4GIZhGE1w4GAYhmE0wYGDYRiG0YRDs6oO7t8Lj1KSI3XCIyW7fQqZjZaE5MgeheQIlW0VWi2MtFXJiFy6fFlqO3H8GGlLyYhQ2VMALZ2hktlQjQXVt2osWrWWbc0mOpOm2CRndJw9eZS0vXhJHh+AlhFRZXxR+9dSkVVHycv4+/uTts6Ir6c7fEtJaFBZQz4KWQ9K4kKV2UNlKamydbwVsiVFxLGg2h6VbUVlT6l8UxWT8vGgJUcoe5WsR0GRvB8qyZFsIsOsdqAHYakeTzdi/6jiToBKcoQ0VWa0VQV8xcEwDMNoggMHwzAMowkOHAzDMIwmOHAwDMMwmnDo4nhMTEt4edtKjlCLQyrJkWBClkNVxyKQkK24r1Fj0jYlg5YDqB4mL6anpqSStlStEJWMSBvCZ6MPLU/Sug09Fn7+gVJbu3YPkbYdO8ZJbSrJhZRMeSzOXrhE2taoFkq2U7VCfAh/AXquVVIt1Fwfv4skRwqKzNJCrSexoEst5gK03I2qjoWOqLGhqh9x4nI22d6sjp/UppLfKCiWF5U9FHVFqASMK1mFpG2AF704TtUbMSi250Ys6OcrxvjIpUyprVktf9LWy0Bvj0JVKySfkJdRyaxQC/papGXuBL7iYBiGYTTBgYNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNOHQrKq9e/dIkiP16tWX7BJ309IZlCwHJfUB0Nk65j//Im1jouXiRQCdCdHo/ijS1mCUC7K4uNBZF+lpsoRHdHgEaXv21HGyvUf3rlLbeUX2EyXxoCrOVCvAU2r7PJGWPXFRZL/tIeZPi4yIKquOkjIJCPAnbZ0Ro95VKlxGZRgZiGJCKlTZOlQxKLOgM6JiIvzt7jszq4C0pTKaVNlBVPEqKrsMUBevMnpR2Wj0MU1JCqUpsrhiI+VsTFWRKdU5REmfUJldKlsq0xRQF5GrCviKg2EYhtEEBw6GYRhGExw4GIZhGE1w4GAYhmE04dDF8abNY+DlZSs5Qq0DqWREfAnZCpWtX4Bsq1rkUunqU/aq2h0NGjSQ2oRiMTKsVh2pTbUg1rB+PbL9Wo688BgUUo20NRHyIgrXcO7sWaktphVdS4OSgAHohfCgIHnREQCaNG8ltankSVoQfiSdpJMHnJHrOYUwudouylLzrlooziMWf40KmQ1KUoOqEwEA2fl0bRZKzsJLUSuEOsZUi7lJqTmyb4rFY5Wsx6kUuQ9/T1qexIuoN6JKFKDO+RyiRgeg3j9KRkRVbyQlQ042UPVLSY74Kfa5ouErDoZhGEYTHDgYhmEYTXDgYBiGYTTBgYNhGIbRBAcOhmEYRhMOzao6tG8vjKUkR+pEREp2+/fQEhdaJEeowkqUvAUAZGRcJ9vPJidLbYPinyBt6WwrOjtiLyHh0UpRsGnHTnr/PEuNIwDUb0TLoWRly/IKp47TBZByrl+R2ih/AaANMR8ALTmiysw6vD9R7leRKUcdF/7+/qStM+Lr4Q5fD9ssmCwio0mVYeTtIp++qgycIiJT0FORoVSgyCqksrBUxaC8FdlWFFSBJ1VhMVV77SBZGic1k5ZDuXBNLlQV6C3LnqjwJLKyAHWmFJWZla3IzKrmZ5DaqAw1Vb9VBV9xMAzDMJrgwMEwDMNoggMHwzAMowkOHAzDMIwmOHAwDMMwmnBoVlXL1q3g7W2rVUVlJqgK+VAaRqoCQaEhIVIblWkFAH4+3mR7aDVZ++nwoYOk7fVrV6U2SlsLADIys6S2QwfpfnOz5YwQAAgmdKm8tWR/FOWStkGE/lRsLJ3l5OkTQLZT9ipdK9FSzrZy9/IjbZsTtneTVpW4+a8kRqJokyrLqYDQn1Jpp1E6U7kF9hceAoAiosiUqrASVfQpR6GBRcmyuSn6VSUSZebJfYcRGUoAXSyrVqCclQgoNLcUPqTn0MWgQnxlP1TnJrUf6UQWJAAEEZlgrFXFMAzDOCUcOBiGYRhNcOBgGIZhNMGBg2EYhtGEQxfH9+xOlCRHwiPlQkWUZAVAS45osVVJjrQgFl0BYB8hcdE8xn7bBxWLyomEz6oF6ISEBLI9rlNnqU0lVXDh3BmpbfPmzaQtlZiwexc9bq0VMinU/lEL2wAtI6IqzrWPkD4JCPAnbZ0RHWQRmmKTPGeqxWpKAkQlQ0HVKdIrZEGy8uSiYADg4yEvvF5XLAhTi/FGxX5oEc5QHdOULIuqIBu1H6oia1RCgF6xcK9lYZqSlgEAXw95TlTzz5IjDMMwzF0DBw6GYRhGExw4GIZhGE1w4GAYhmE0wYGDYRiG0YROqNIJKpHMzEz4+flh89bf7JIcSU9PJ/sJCAyS2q5fpW1DQmSJi9QraaStjx8tnUHJiGixVclspKXJftSsHkraVguVpUUAIJCQHDEo5CdSUlOktj8PHyZtKcmRK4pxU0mqZF2Xx8LTlx633KxrUlsgMc8AcDlFLjKVdMpWciQ/Pw+vTvo3MjIy4OvrS/ZT1ViO/4tXrks+UXIYlHwHQGf8qObchehDVRQpU5FVZSQKLmmxVewGmfGlVTqD8sNHkTVGjacqQYkaIlXBJi2ZUmlZ9suTUEW4ACC/SJaM8feSZUgyMzNRLcivQs8BvuJgGIZhNMGBg2EYhtEEBw6GYRhGExw4GIZhGE04VnIkMREepSRHIgjJEUqyAqBrb2iRHNm1c6fd/d7wQ7aPaUnbUtIZMa1U8iSyz8bYWNLWxYWWH/AOkOuNnD5xjLS9ePGC1JaQQI8FJX2yexdtq6qbQs2fFlul5AgxxneT5Iiri06SjSgmSmS4E3IaAGAy35nkCCVZAgAexMI2ABiIWiHFJtrWl5D1yCmgF48pSQ2VmIZqQT+LqGPhR/igQtEtuWjuopgPT4NCGoaQKPH3on0jt6eYJ0o6pargKw6GYRhGExw4GIZhGE1w4GAYhmE0wYGDYRiG0QQHDoZhGEYTDpUc+eXXbfAqJTlSQDxen0nIdwCADyFxkXGNlhwJqyZLeKSkypIVABAYREtcUNIZbp5+pG12hiydUS1UznwCgKvpsoRHqML2vsZNyHaqaM3xv4+Qtm462ZaSPQGAwCBZckRtS48bJQOjkhzJz7outamkWtKJcfv7779t+3NiyZEzl65KPmUSshXeimydTCKTSJXZQ2VKUecaoC6WRElnJF3JJW39CckQvUIOhcruogpBAcCVzAKyncrYUhVACvSWZTlUmIjCWqovTNW4UTIw6dm05Eg1P1lyRAWVQUfJqbDkCMMwDONwOHAwDMMwmuDAwTAMw2iCAwfDMAyjCYdKjuzdu+eOJEdat5FlKygZihu2smyFSp6kDSFPAgAJCQmyrUIO48Be2Q+VzMbuXbIfI0aNJm2v5dKLal56eSo3/fgtaRtLyJmoxpjyeW+i/bYAvX/RMa1I24P7EqW2mFb2S8AEBtCL7s6Iwd1FkvHw1cnzqCckKwC6xgYlCwIAxcQir6di8Vgl61FE9BGmWMz1NMj7QdWPAOj9U9W2SErLIdtDfWQ/agR4EJY0qhyhAsgJBFStEQDIL6T3j1roNyrmiZInUUm1UIvubgo5lIqGrzgYhmEYTXDgYBiGYTTBgYNhGIbRBAcOhmEYRhMcOBiGYRhNOFRyZBMlOVIkZzHkZcnyHQDgFyBLXFDyFgAQRMhWqCRH/ANkKRMAyMmU/QgiJDkAIPWK3DflA0BLeDzcvRtpS8lMALT8wB+/bSFtA0OqSW3FBXmkrV4vyzNcvJxK2qrGLY+QEVGNBSUjEhhIS5lcIcbt5HHb4lXOLDmSTEmO5BVJ9qG+dOZSLpHFQ2XaAHQhJ0qmBgDyFNlPQYRUh0pmg2pXFUuiUGUdnb9KH6fuRDYS5S8AXMuRMxN9CYkUgM5cU2U55Smyqqj5U40FdR4XKeaJ6oKSWWHJEYZhGMbhcOBgGIZhNMGBg2EYhtEEBw6GYRhGExw4GIZhGE04VKtqH6FVFVmvvmS3a6esSQQALe9QR0llq9Kf2kn4QellAbT2U/OWrUnb/YS+VsyDHUjbIEKTR0V+Hl1kJ6aZXAzqz7/+JG1TU1KkNkqHCwBaKjSl9hDj3KwFrVV1YK+sVUXNM0DPn7+/P2nrjBjdXaTsIVcXORNISzYSpXUEAAVEppSq6JNK74ryQ6VrRWV3qTIC/YiMpj/PZZC291X3IdsphSaVbpOWQk7UeOrd6M8b3OzPeLyuKOQU6EVkrikSXymtMSpJtjISZ/mKg2EYhtEEBw6GYRhGExw4GIZhGE1w4GAYhmE04dDF8egWMfDyspUcoR7xj42lF6uDCdkK1cK2PyFboSo8FBxCy2E8SPgRQMieAHThKJUkB+WzXlEsRrXQRS3i9erdh7TNJyQMrmdmk7a+/rLP1L4BQIBCGoRKCghRSI5QRbRCFfNBLcafPHGMsHROsvOLodPbLqi6EQup7q70seBBHCPFJlqegirkJARtSxUeUmFWLI5T2yN27aat7IePBy0Bojr+qfNFVVgph2hX+aYnxoKSNwFoCRCATgpQScNQUi3UPAO0xAlVQEtHfKfeKXzFwTAMw2iCAwfDMAyjCQ4cDMMwjCY4cDAMwzCa4MDBMAzDaMKhWVUH9u2VJEfqRtST7FTSIJQUReIu2rZt21jZlpAFAdTZVruJvlu0sl9GRJWNlJCQILXVrF2btM0spDMkGkbWldo+/79FpG3jKFlyJHGX7AMAxBCZS3s0jtu+RHksHiSypwBaXkYlOZK4W7YNDAggbZ0RHw93+JbKHlIVCaIoILLjqCwgAPAyyqe6KkNJVeCJytwrIrKnAMBDLx+nRtDZQVQmUYgPLeux/+x1sr1WgKfcFuhBWAJFRBaXNzE+AJBTIGcuUZlvAFBMJ3HBh+jbrBh7KgNKVVhLlZlVFfAVB8MwDKMJDhwMwzCMJjhwMAzDMJrgwMEwDMNoQicqQ6z9NmRmZsLPzw+//LoNXt62kiOUM+lpaWQ/voTcR/b1q6QtJTly5coV0jYkJIRsv5ou++GnkBzJybwm2xLyHQBw9Wq61KaS2Ui9Qo8FZX/+UippG0TIfeQS/gJAUBA1brQPHr70wnReltw3JWUCABnX5Plbsl6u0QEAz/STa3oc+/tvm7/z8/Pw6qR/IyMjA76+vmQ/VY3l+D97+arkE6XgoRKMoKQz/DzoRV5qIZ1alAbo+hEAvShMLR4DdM2LXMXCPyXhofJBVf+D8i0jr4i0pboIUtTooCRVVAvbV7LoGhuhvnINnex8eiyoGhuhsS+Stmm75ktt1LhlZmaiWpBfhZ4DfMXBMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJrgwMEwDMNowqGSI3v37IGxlORI/Qb1JTuVNAglRaGSw6CKCamkTNq1bUu2U5IjqiJTOwnpDKpI0Y1+ZVuVfIdqLChpkAN7ZakPlR+U1AcAxMbKUi27CH8BbT5Hx9BSLZTPQx9RjHGC7EdAgD9p64y4u7pIGUVUvo4qw4iypWRBADr7yctAS4Co+qAyjAK87P/taVAUJKL2T1WEyUhkHQFADpGl5O9JF4OisqpUyaUuhG8uijy3AMX2qOlTZWZRRbRSE94nbR0JX3EwDMMwmuDAwTAMw2iCAwfDMAyjCQ4cDMMwjCYcujhuMhfDZLJd1KLkRfz9/cnPZxBSHUrba7KtqnZDaiot1UEtvKak0rIllB8qiRPKlpI3UdkC9P6pbLWMcRrhs7JfDT5nXZf9VdmmpdHjRs1HWql9KygoID/rDLi46KTFV2oBWoWHYqGYgpKyUC2CFxP1KlT2WhaxtUicuLmqhFZoqLGgalsAgAuRVqCy1YIqiYHqm6rRURHboxb5K0NViq84GIZhGE1w4GAYhmE0wYGDYRiG0QQHDoZhGEYTDlkctyzW5OfnS+/l5eZKbfn5eWQ/mmzz7sxWZe8MtkAljtsdjrHKvrJsSy+GW/52QNkZJRZfsjIzpfeoxXHq6WWtFBH1OKinlIGKWRwvJBarCwkfAEBP+KHFB0DbuFHHQkUsjlNjDNDjrGX/tPRL7VtWVqbyvfLikEJO58+fR+3atat6s8z/MOfOnUOtWrUc7QYAPv4Zx1CR54BDAofZbMbFixfh4+NTIZGeYVQIIZCVlYUaNWrAxcU57szy8c9UJZVxDjgkcDAMwzB3L87xE4xhGIa5a+DAwTAMw2iCAwfDMAyjCQ4cDMMwjCY4cDAMwzCa4MDBMAzDaMJhsur5+fkoLCx01OaZ/yH0ej2MRqOj3bCBj3+mKqnoc8AhgSM/Px8RERG4fPmyIzbP/I8RFhaGpKQkpwkefPwzVU1FnwMOCRyFhYW4fPkyTiWdha+vLwQEbv4PlscRBcSt1zffw802cePlTXvLO5b/s20TJdosTzre6OPWNm3aSnxO3GyxfLb058w3Ozff7MCmzebzN9otvpjFzT6Fxe7WPlo/J270K0rYWn0Rsk+l7cw3X5hFyTET8n4JyxiV6kOUHH/FeyXnxzLmQsivRdntZJu4qc8jzCUm0fJa3HptsRXU+0BBXg7eefVpFBYWOk3gsBz/x0+fhY+P763jASXmy2Y+Bcw3d8ssbr6+2WaGZZ5LHhOl+iD6tTnOrON+y94EYd2WxdYkBMxmiz83/rZ83mT5nBBW3ShTCRuTuPkZ8619MJkFTOabr2++JwRgMt+0B269b77Rrxk3dKlM5hvHy433hXX/re03/RA3P2tpE+Yb+2M2W3y72a/Z9jVu2ljbLftqNt/q1yQgzJZ2y2sBszDfen1jwG5+7tZrlOy3hK3ltTCbAbPpxnFsNt2cHNOt12bTrfdNpW1L2AgzUJSPy0c+r9BzwKEVAH19fSs8cJRus/nyQ8n+bm2TapO+YG+2mUvYlCdwCJQ4ya0nZckTvMR7Fj+sJ/qdBY6SX0S2gaDE2JYODqW3Weq/KOHj7QJE+QOHKjBYvu1u876T4uPrC98yAsetuSsjcFjnWR0kqDYqcJTsw/JFb9lGycBhtiNwWF5bA4f5VuAwCXXgsNqY5cBhaVMFDrNZwOVmu4u4FThKt1lsdaWChe1rQFfCRmdtM1tfw3TrcygROFAiANyMtDf+W+K1uDHY0N0MIqVfQwoc5hLBQtgGDp2JttHdaBNmWiTxTuDFcYZhGEYTHDgYhmEYTXDgYBiGYTTBgYNhGIbRhEMXxzNvVkCryMVxlGqzWeBFyf5ubdOmrcTnqMXxkp/jrKoSY1d6kbvka1F2O9lWUVlV+XT1QGcgKzPz9gvb4jaL4xBSH5xVdfdkVd3IoLL8t5KyqkwV/7yQw0rHent7o15EHUdsnvkfw9vb2xqgnAHL8X9fJB//TNVQ0eeAQwKHTqdDdnY2zp07B19fX0e4cNeRmZmJ2rVr85hpxDJuzlRpj4//8sHnQPmojHPAKZ7jYOyHx+zegeeyfPC4OR5eHGcYhmE0wYGDYRiG0YRDAofBYMDUqVNhMBgcsfm7Eh6z8uGM4+aMPt0N8LiVj8oYN51wpnQThmEYxunhW1UMwzCMJjhwMAzDMJrgwMEwDMNoggMHwzAMowkOHAzDMIwmKi1wLFiwAOHh4TAajWjTpg12795dpv3q1avRqFEjGI1GNGnSBD/88ENluea0aBmzJUuWQKfT2fxzltKoVclvv/2GPn36oEaNGtDpdFi3bt1tP7N161a0aNECBoMB9evXx5IlSyrcLz7+ywefA9pw1PFfKYFj5cqVeOmllzB16lTs27cPzZo1Q48ePZCamkra79ixA/Hx8Rg2bBj279+Pfv36oV+/fvjzzz8rwz2nROuYATekFy5dumT9d+bMmSr02DnIyclBs2bNsGDBArvsk5KS0KtXL3Tq1AkHDhzA2LFj8eyzz2Ljxo0V5hMf/+WDzwHtOOz4F5VA69atxZgxY6x/m0wmUaNGDfHWW2+R9gMHDhS9evWyaWvTpo0YOXJkZbjnlGgds8WLFws/P78q8u7uAIBYu3ZtmTYvv/yyiIqKsmkbNGiQ6NGjR4X5wcd/+eBz4M6oyuO/wq84CgsLsXfvXnTt2tXa5uLigq5duyIhIYH8TEJCgo09APTo0UNpf69RnjEDgOzsbNStWxe1a9fGI488gr/++qsq3L2rqexjjY//8sHnQNVQUcdahQeOtLQ0mEwmVKtWzaa9WrVquHz5MvmZy5cva7K/1yjPmDVs2BCfffYZ1q9fj2XLlsFsNqNt27Y4f/58Vbh816I61jIzM5GXl3fH/fPxXz74HKgaKur4d6isOlN+YmNjERsba/27bdu2aNy4MT766CO88cYbDvSMYaoGPgccR4VfcQQHB8PV1RUpKSk27SkpKQgLCyM/ExYWpsn+XqM8Y1Yad3d3NG/eHCdPnqwMF+8ZVMear68vPDw87rh/Pv7LB58DVUNFHf8VHjj0ej1iYmKwefNma5vZbMbmzZttfh2UJDY21sYeADZt2qS0v9coz5iVxmQy4fDhw6hevXpluXlPUNnHGh//5YPPgaqhwo41rSv39vDVV18Jg8EglixZIo4cOSJGjBgh/P39xeXLl4UQQgwZMkRMmjTJav/HH38INzc38c4774ijR4+KqVOnCnd3d3H48OHKcM8p0Tpm06dPFxs3bhSnTp0Se/fuFY8//rgwGo3ir7/+ctQuOISsrCyxf/9+sX//fgFAzJkzR+zfv1+cOXNGCCHEpEmTxJAhQ6z2p0+fFp6enmLixIni6NGjYsGCBcLV1VX89NNPFeYTH//lg88B7Tjq+K+UwCGEEPPnzxd16tQRer1etG7dWuzcudP6XlxcnHj66adt7FetWiXuu+8+odfrRVRUlPj+++8ryzWnRcuYjR071mpbrVo10bNnT7Fv3z4HeO1YtmzZIgBI/yxj9fTTT4u4uDjpM9HR0UKv14vIyEixePHiCveLj//yweeANhx1/HM9DoZhGEYTrFXFMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJrgwMEwDMNoggMHwzAMowkOHAzDMIwmOHAwDMMwmuDAwTAMw2iCAwfDMAyjCQ4cDMMwjCb+P7wQBHJtOcn5AAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1620,7 +1629,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAABBiklEQVR4nO2dd5xT1bbHf5mZJNNh6AxtaAIOVVAElAFF8UpRAcEREXgqo6JeFEG5+EAUrwIq2MDyFJSiFGk2EKUjXhUQELhKGUCkSZtek/3+gIQkZ+2ZnCkk6O97Lx8zK+vss88uWedkraxlUUopEEIIIX4SEugOEEIIubyg4SCEEGIKGg5CCCGmoOEghBBiChoOQgghpqDhIIQQYgoaDkIIIaag4SCEEGIKGg5CCCGmoOH4i9KlSxd06dIl0N0wYLFY8Oyzzwa6G1pKM24JCQkYMmRImfbnUjFkyBAkJCQEuhvkMoGGI4iwWCx+/Vu7dm259mPevHmYNm1auZ6jKA4ePOi+1okTJ4o6AwcOhMViQXR09CXu3eVFeno6JkyYgFatWiE6OhoRERFo3rw5nnrqKRw9ejTQ3Ssx586dQ7Vq1WCxWLBo0aJAd+dvR1igO0AuMnv2bK+/P/roI6xatcogb9asWbFtff311yXux7x58/DLL79gxIgRJW6jLAgPD8fHH3+MZ555xkuelZWFZcuWITw8PEA9uzw4cOAAunXrhsOHD+POO+/EsGHDYLPZsGPHDrz//vtYsmQJfvvtt0B3s0SMGzcO2dnZge7G3xYajiDinnvu8fr7+++/x6pVqwxyf7DZbGXVrYBx6623YvHixdi+fTtatWrlli9btgz5+fm45ZZbsHr16gD2MHgpLCxEnz59cOLECaxduxbXXXed1/svvPACJk2aFKDelY5ffvkFM2bMwLhx4zBu3LhAd+dvCb+qusyYOXMmbrjhBlSrVg12ux1XXnklZsyYYdDz/a5+7dq1sFgsWLBgAV544QXUrl0b4eHhuPHGG7Fv3z6v47744gscOnTI/XWR53ffeXl5GD9+PBo1agS73Y46depg9OjRyMvL8zp/Xl4eHn/8cVStWhUxMTHo3bs3jhw5YupaO3TogPr162PevHle8rlz5+KWW25BpUqVxOOmT5+OxMRE2O12xMfHY/jw4Th37pxB791330XDhg0RERGBa665Bhs2bBDb8/ea/SUrKwsjR45EnTp1YLfb0aRJE7z88svwTVRtsVjwyCOPYOnSpWjevDnsdjsSExOxYsWKYs/x6aefYvv27Rg7dqzBaABAbGwsXnjhhSLbcDqdmDZtGhITExEeHo7q1asjJSUFZ8+e9dJbtmwZevTogfj4eNjtdjRs2BDPP/88HA6Hl16XLl3QvHlz7N69G127dkVkZCRq1aqFyZMnF3s9nvzzn//EHXfcgeuvv97UcaTs4BPHZcaMGTOQmJiI3r17IywsDJ999hkefvhhOJ1ODB8+vNjjX3rpJYSEhODJJ59EWloaJk+ejIEDB+I///kPAGDs2LFIS0vDkSNHMHXqVABw+xGcTid69+6NjRs3YtiwYWjWrBl27tyJqVOn4rfffsPSpUvd57n//vsxZ84c3H333ejYsSNWr16NHj16mL7e5ORkzJkzBy+99BIsFgtOnTqFr7/+GrNnzxY/QJ999llMmDAB3bp1w0MPPYRff/0VM2bMwI8//ohNmzbBarUCAN5//32kpKSgY8eOGDFiBA4cOIDevXujUqVKqFOnjrs9M9fsD0op9O7dG2vWrMF9992H1q1bY+XKlRg1ahT++OMP95i72LhxIxYvXoyHH34YMTExeP3119G3b18cPnwYlStX1p5n+fLlAIBBgwaZ6p8nKSkpmDVrFoYOHYrHHnsMqampePPNN7Ft2zavsZw1axaio6PxxBNPIDo6GqtXr8a4ceOQnp6OKVOmeLV59uxZ3HLLLejTpw/69++PRYsW4amnnkKLFi3wj3/8o9g+LVy4EN999x327NmDgwcPlvjaSClRJGgZPny48p2i7Oxsg1737t1VgwYNvGRJSUkqKSnJ/feaNWsUANWsWTOVl5fnlr/22msKgNq5c6db1qNHD1WvXj3DeWbPnq1CQkLUhg0bvORvv/22AqA2bdqklFLq559/VgDUww8/7KV39913KwBq/PjxRV53amqqAqCmTJmifvnlFwXAfc633npLRUdHq6ysLDV48GAVFRXlPu7kyZPKZrOpm2++WTkcDrf8zTffVADUBx98oJRSKj8/X1WrVk21bt3aayzeffddBcBr3Py9ZqWUqlevnho8eHCR17Z06VIFQE2cONFL3q9fP2WxWNS+ffvcMgDKZrN5ybZv364AqDfeeKPI87Rp00ZVqFChSB1PBg8e7DXnGzZsUADU3LlzvfRWrFhhkEtrMiUlRUVGRqrc3Fy3LCkpSQFQH330kVuWl5enatSoofr27VtsH7Ozs1XdunXVmDFjlFIX1/TChQv9vk5SNvCrqsuMiIgI9+u0tDScOnUKSUlJOHDgANLS0oo9fujQoV7+D9fj/oEDB4o9duHChWjWrBmaNm2KU6dOuf/dcMMNAIA1a9YAAL788ksAwGOPPeZ1fEmc7YmJiWjZsiU+/vhjAOcd97fddhsiIyMNut988w3y8/MxYsQIhIRcXNoPPPAAYmNj8cUXXwAAfvrpJ5w8eRIPPvig11gMGTIEFSpUKNE1+8uXX36J0NBQw9iMHDkSSil89dVXXvJu3bqhYcOG7r9btmyJ2NjYYucrPT0dMTExpvrmycKFC1GhQgXcdNNNXtfdtm1bREdHe12355rMyMjAqVOncP311yM7Oxv//e9/vdqNjo728tnZbDZcc801fq2/l156CQUFBfjXv/5V4usiZQO/qrrM2LRpE8aPH4/NmzcbokrS0tIMH3y+1K1b1+vvuLg4ADB8by2xd+9e7NmzB1WrVhXfP3nyJADg0KFDCAkJ8frAA4AmTZoUew6Ju+++G6+88goef/xxfPfdd9oPjkOHDonnsdlsaNCggft9138bN27spWe1WtGgQQMvmb/X7C+HDh1CfHy84UPdFSnn6psL3/kCzs9ZcfPlj3Epir179yItLQ3VqlUT3/e87l27duGZZ57B6tWrkZ6e7qXnezNTu3ZtWCwWL1lcXBx27NhRZH8OHjyIKVOm4K233mIIdhBAw3EZsX//ftx4441o2rQpXn31VdSpUwc2mw1ffvklpk6dCqfTWWwboaGholz5UUHY6XSiRYsWePXVV8X3PX0DZUlycjLGjBmDBx54AJUrV8bNN99cLueRCNQ1uyjpfDVt2hTbtm3D77//XqI+Op1OVKtWDXPnzhXfdxnSc+fOISkpCbGxsXjuuefQsGFDhIeHY+vWrXjqqacMa7Kk1zNu3DjUqlULXbp0cfs2jh8/DgD4888/cfDgQdStW9frSZOUHzQclxGfffYZ8vLysHz5cq87UbNflxSH7x2hi4YNG2L79u248cYbtToAUK9ePTidTuzfv9/r7v/XX38tUX/q1q2LTp06Ye3atXjooYcQFiYv23r16rnP4/nkkJ+fj9TUVHTr1s1Lb+/eve6vnACgoKAAqampXqG//l6zv9SrVw/ffPMNMjIyvJ46XF/puPpWWnr16oWPP/4Yc+bMwZgxY0wf37BhQ3zzzTfo1KmT11dRvqxduxanT5/G4sWL0blzZ7c8NTW1RP3WcfjwYezbt8/wRAgADz/8MIDzT80VK1Ys0/MSGZrnywjX3Zrn3VlaWhpmzpxZpueJiooS/SX9+/fHH3/8gffee8/wXk5ODrKysgDAHR3z+uuve+mU5tfoEydOxPjx4/Hoo49qdbp16wabzYbXX3/da4zef/99pKWluaO62rVrh6pVq+Ltt99Gfn6+W2/WrFmGsF1/r9lfbr31VjgcDrz55pte8qlTp8JisfgVWeQP/fr1Q4sWLfDCCy9g8+bNhvczMjIwduxY7fH9+/eHw+HA888/b3ivsLDQPU7SmszPz8f06dNLeQXeTJw4EUuWLPH65+rb6NGjsWTJEkRFRZXpOYkePnFcRtx8882w2Wzo1asXUlJSkJmZiffeew/VqlXDsWPHyuw8bdu2xfz58/HEE0/g6quvRnR0NHr16oVBgwZhwYIFePDBB7FmzRp06tQJDocD//3vf7FgwQKsXLkS7dq1Q+vWrZGcnIzp06cjLS0NHTt2xLfffuv1exGzJCUlISkpqUidqlWrYsyYMZgwYQJuueUW9O7dG7/++iumT5+Oq6++2u2UtVqtmDhxIlJSUnDDDTdgwIABSE1NxcyZMw13tP5es7/06tULXbt2xdixY3Hw4EG0atUKX3/9NZYtW4YRI0YY/EIlxWq1YvHixejWrRs6d+6M/v37o1OnTrBardi1axfmzZuHuLg47W85kpKSkJKSghdffBE///wzbr75ZlitVuzduxcLFy7Ea6+9hn79+qFjx46Ii4vD4MGD8dhjj8FisWD27Nl+ffVpBum3KK6ni6uvvhq33357mZ6PFEPgArpIcUjhuMuXL1ctW7ZU4eHhKiEhQU2aNEl98MEHCoBKTU116+nCcX1DF12hrzNnznTLMjMz1d13360qVqyoAHiFaebn56tJkyapxMREZbfbVVxcnGrbtq2aMGGCSktLc+vl5OSoxx57TFWuXFlFRUWpXr16qd9//910OG5R+IbjunjzzTdV06ZNldVqVdWrV1cPPfSQOnv2rEFv+vTpqn79+sput6t27dqp9evXG8bNzDX7E46rlFIZGRnq8ccfV/Hx8cpqtarGjRurKVOmKKfT6aUHQA0fPtxwvL/nUUqps2fPqnHjxqkWLVqoyMhIFR4erpo3b67GjBmjjh075tbzDcd18e6776q2bduqiIgIFRMTo1q0aKFGjx6tjh496tbZtGmTuvbaa1VERISKj49Xo0ePVitXrlQA1Jo1a9x6SUlJKjEx0XAO3bmLg+G4gcOiVBnfGhBCCPlLQx8HIYQQU9BwEEIIMQUNByGEEFPQcBBCCDFFQA3Hs88+W+IfVc2aNQsWi6VcM2S6KtHNmjWr3M5hlmAtCeuJbwlV11z99NNPl+T8l8MYXW5I+y0hIQE9e/a8JOd3lQUo7+qXl5rL9bpKZDh27dqFe+65B7Vq1XLXPBg4cCB27dpV1v0jpcThcCA+Ph4Wi8WQQM/F9OnTReO4e/duPPvss0GZvjqY+3YpmD59OiwWC9q3by++X9T46OY7GAjWvimlMHv2bHTu3BkVK1ZEZGQkWrRogeeee870j0D/EpiN3/3000+VzWZTNWrUUGPHjlX/93//p5555hlVs2ZNZbPZ1OLFi/1uq6CgQOXk5JjtglJKqcLCQpWTk2OIfS9LpN84BBrpdwZF8fXXXysAKiEhQQ0cOFDUSUxMFNtcuHChIRbfH3Jzc1V+fr7775kzZyoA6scffzTVTlEU1be8vDyvdOl/RTp27KgSEhIUALV3717D+0WNj26+i0Lab/Xq1VM9evQw2/Ui0fXN4XConJwcr3T5l4rCwkLVv39/BUBdf/31aurUqeqdd95R99xzjwoJCVHNmzdXx48fL1Hbrt+imN1jgcbUE8f+/fsxaNAgNGjQADt27MDEiRNx33334fnnn8eOHTvQoEEDDBo0qNisnC4LHRYWVuK60aGhoQgPDy+T/EF/ZebMmYOrrroKjz/+OJYuXVpud0dKKeTk5AAA7Ha7u8hPILDZbH+J0rk6UlNT8d133+HVV19F1apVtYkIywLXegn0fgsJCUF4eHhAkhhOnjwZCxYswJNPPon169djxIgRGDZsGGbPno2lS5di9+7dXl/N/i0wY2VSUlIUALV+/Xrx/XXr1ikAKiUlxS0bP368AqB27dqlkpOTVcWKFVXr1q293vMkOztbPfroo6py5coqOjpa9erVSx05csTwi2PXXaznr6Vdd0AbNmxQV199tbLb7ap+/frqww8/9DrH6dOn1ciRI1Xz5s1VVFSUiomJUbfccov6+eefvfT8feLwtz3X3cX8+fPVxIkTVa1atZTdblc33HCDeNf4zjvvqAYNGqjw8HB19dVXa3/ZrCM7O1vFxMSoyZMnq2PHjqmQkBBDYZ569eopAF7/kpKS3OPr+891Z+Qa6xUrVqi2bdsqu92upk6d6n7P85fNrrbWrVunhg0bpipVqqRiYmLUoEGD1JkzZ7z64zvPnv10tVlc36QxOnHihPqf//kfVa1aNWW321XLli3VrFmzvHQ8f7HuGnubzabatWunfvjhB7/G/FLw/PPPq7i4OJWXl6ceeugh1bhxY6/3ixof3Xx7Hrd27Vr10EMPqapVq6qKFSt6vSftt5UrV6pWrVopu92umjVrpj799FOv/kj7XGqzqL7p7swXLFigrrrqKhUeHq4qV66sBg4cqI4cOeKl48owcOTIEXXbbbepqKgoVaVKFTVy5EhVWFhY5FhnZ2eruLg4dcUVV6iCggJRZ+jQoQqA2rx5s2Fsivss8r2ucePGqbCwMHXy5EnDeR544AFVoUKFEn9LU5aYMt+fffYZEhIStLV+O3fujISEBHfBHE/uvPNOZGdn49///jceeOAB7TmGDBmCN954A7feeismTZqEiIgIUyVH9+3bh379+uGmm27CK6+8gri4OAwZMsTL/3LgwAEsXboUPXv2xKuvvopRo0Zh586dSEpKwtGjR/0+V0nbe+mll7BkyRI8+eSTGDNmDL7//nsMHDjQS8dV2rRGjRqYPHkyOnXqhN69e+P333/3u1/Lly9HZmYm7rrrLtSoUQNdunQx3J1OmzYNtWvXRtOmTTF79mzMnj0bY8eORefOnd3Fhv71r3+533PVjQDOZ6FNTk7GTTfdhNdeew2tW7cusj+PPPII9uzZg2effRb33nsv5s6di9tvv910XiN/+uZJTk4OunTpgtmzZ2PgwIGYMmUKKlSogCFDhuC1114z6M+bNw9TpkxBSkoKJk6ciIMHD6JPnz4oKCgw1c/yYu7cuejTpw9sNhuSk5Oxd+9e/Pjjj+73ixof3Xx78vDDD2P37t0YN24cnn766SL7snfvXgwYMAD/+Mc/8OKLLyIsLAx33nknVq1aZfq6/OmbJ7NmzUL//v0RGhqKF198EQ888AAWL16M6667zpCs0uFwoHv37qhcuTJefvllJCUl4ZVXXsG7775bZJ82btyIs2fP4u6779ZmZb733nsBAJ9//rmX3J/PIl8GDRqEwsJCzJ8/30uen5+PRYsWoW/fviX+lqZM8dfCnDt3TgFQt912W5F6vXv3VgBUenq6Uuri3UZycrJB1/dOZMuWLQqAGjFihJfekCFD/H7igM8T0cmTJ5XdblcjR450y3Jzcw3flaampiq73a6ee+45Lxn8eOLwtz1/y7eaKW1aFD179lSdOnXyOl66mymJj8M11itWrBDfk5442rZt6+X7mDx5sgKgli1b5pb5zrOuzaL65vvEMW3aNAVAzZkzxy3Lz89XHTp0UNHR0e616prvypUrez0JLVu2TAFQn332meFcl5qffvpJAVCrVq1SSinldDpV7dq11T//+U8vvZL4OFzzdN111xnuxIvab55PGGlpaapmzZqqTZs2bpm/TxxF9c33zty1R5o3b+51B/75558rAGrcuHFu2eDBgxUAr72o1Pnyum3btjWcyxPX2lmyZIlW58yZMwqA6tOnj1vm72eR9CTVoUMH1b59e69zLF68OKh8IX4/cWRkZABAseUoXe/7VgJ78MEHiz3HihUrAFzMr++iqFTavlx55ZVeT0RVq1ZFkyZNvPwudrvd/V2pw+HA6dOnER0djSZNmmDr1q1+n6uk7RVXvtVMaVMdp0+fxsqVK5GcnOyW9e3bFxaLBQsWLDB9jRL169dH9+7d/dYfNmyYl+/DVVvDVWq2vPjyyy9Ro0YNr7GwWq147LHHkJmZiXXr1nnpDxgwwF0ZETBXXre8mTt3LqpXr46uXbsCOF87ZcCAAfjkk0/gcDjK5BwPPPCAtuCSL/Hx8bjjjjvcf8fGxuLee+/Ftm3b3IWWygPXHnn44Ye97sB79OiBpk2bit96+H4GXX/99cXOqT+fe7rPPH8+iyTuvfde/Oc//8H+/fvdsrlz56JOnTrFZoi+VPhtOFyD4xpIHbqBrl+/frHncJUc9dVt1KiRv930q9Sm0+nE1KlT0bhxY9jtdlSpUgVVq1bFjh07/Krb7YvZ9oor32qmtKmO+fPno6CgAG3atMG+ffuwb98+nDlzBu3bty8zZ6o/c+qJ7/VER0ejZs2a5R5Se+jQITRu3NjgWPW3XKuZ8rrlicPhwCeffIKuXbsiNTXVPa/t27fHiRMn8O2335bJeczMa6NGjQwO8yuuuAIAynVedWWCgfPVD33nNDw83FD+158SvP587uk+80pa9nfAgAGw2+3ufZqWlobPP/8cAwcODJpgIL8NR4UKFVCzZs1iawPv2LEDtWrVQmxsrJe8qCpiZYk/pSn//e9/44knnkDnzp0xZ84crFy5EqtWrUJiYqJf5Vd9Mdteacq3+otr0XXq1AmNGzd2/9u4cSM2b95cJnfPl2pOAZTZ3bQ/XIr5KQmrV6/GsWPH8Mknn3jNaf/+/QGgzG4IynpedR92wTCnxeG6uSjqc8/13pVXXunXOYtbR3FxcejZs6d7PhctWoS8vDx3PZlgwFQhp549e+K9997Dxo0bxcIqGzZswMGDB5GSklKizrhKjqampnrdnZamAJDEokWL0LVrV7z//vte8nPnzqFKlSoBb89MaVMJV7jmI488Yni0dTqdGDRoEObNm4dnnnkGgH5jl/Xdzd69e91fsQBAZmYmjh07hltvvdUti4uLMzg28/PzDYWqzPStXr162LFjB5xOp9dTR1mXay1v5s6di2rVquGtt94yvLd48WIsWbIEb7/9NiIiIoocn7Kc13379kEp5dXmb7/9BuD8L8uBi09s586d8yrt6vtUYKZvnmWCPfeIS1ZWc3rdddehYsWKmDdvHsaOHSsag48++ggAyvRX9Pfeey9uu+02/Pjjj5g7dy7atGmDxMTEMmu/tJiKqho1ahQiIiKQkpKC06dPe7135swZPPjgg4iMjMSoUaNK1BnX9+W+ZSffeOONErWnIzQ01GD1Fy5ciD/++CMo2jNT2lTCdacyevRo9OvXz+tf//79kZSU5HV3GhUVJbbrKsXpzzn94d133/WKTJoxYwYKCwu9yqU2bNgQ69evNxzne3dqpm+33norjh8/7hWpUlhYiDfeeAPR0dFB871xUeTk5GDx4sXo2bOnYU779euHRx55BBkZGVi+fDmAosdHN98l4ejRo1iyZIn77/T0dHz00Udo3bo1atSoAQDuqoae85qVlYUPP/ywxH1r164dqlWrhrfffht5eXlu+VdffYU9e/aYisQsisjISDz55JP49ddfxQivL774ArNmzUL37t1x7bXXlsk5gfPll6tUqYJJkyZh3bp1QfW0AZh84mjcuDE+/PBDDBw4EC1atMB9992H+vXr4+DBg3j//fdx6tQpfPzxxyUuf9m2bVv07dsX06ZNw+nTp3Httddi3bp17juYsrpT6tmzJ5577jkMHToUHTt2xM6dOzF37ly//Qfl3Z6Z0qYSc+fORevWrVGnTh3x/d69e+PRRx/F1q1bcdVVV6Ft27aYMWMGJk6ciEaNGqFatWq44YYb0Lp1a4SGhmLSpElIS0uD3W7HDTfcgGrVqpXouvLz83HjjTeif//+7pKu1113HXr37u3Wuf/++/Hggw+ib9++uOmmm7B9+3asXLnS8ORmpm/Dhg3DO++8gyFDhmDLli1ISEjAokWLsGnTJkybNq3YgI9gYPny5cjIyPAaK0+uvfZa948BBwwYUOT46Oa7JFxxxRW477778OOPP6J69er44IMPcOLECcycOdOtc/PNN6Nu3bq47777MGrUKISGhuKDDz5A1apVcfjwYa/2/O2b1WrFpEmTMHToUCQlJSE5ORknTpzAa6+9hoSEBDz++OMluh6Jp59+Gtu2bcOkSZOwefNm9O3bFxEREdi4cSPmzJmDZs2aiUawNFitVtx111148803ERoa6hXYERSUJBRrx44dKjk5WdWsWVNZrVZVo0YNlZyc7A4n9cQVivfnn39q3/MkKytLDR8+XFWqVElFR0er22+/Xf36668KgHrppZfcekX9IMkX3/DM3NxcNXLkSFWzZk0VERGhOnXqpDZv3mzQMxOO6097Zsq3KuV/aVNPXCHN//u//6vVOXjwoAKgHn/8caWUUsePH1c9evRQMTExhnDf9957TzVo0ECFhoaKPwCUKO4HgHFxcSo6OloNHDhQnT592utYh8OhnnrqKVWlShUVGRmpunfvrvbt2yeWS9X1TfcDwKFDh6oqVaoom82mWrRoYRjvokrWwo+St+VJr169VHh4uMrKytLqDBkyRFmtVnXq1CmllH58dPNdVGqY4n4A2LJlS2W321XTpk3FUq5btmxR7du3VzabTdWtW1e9+uqrYpu6vul+ADh//nzVpk0bZbfbVaVKlYr8AaAvujBhCYfDoWbOnKk6deqkYmNjVXh4uEpMTFQTJkxQmZmZBn1/P4uKSjnyww8/KADq5ptv9quPl5LLonTszz//jDZt2mDOnDmGH8oRQshfke3bt6N169b46KOPMGjQoEB3x4ugq8fhynfkybRp0xASEoLOnTsHoEeEEHLpee+99xAdHY0+ffoEuisGTPk4LgWTJ0/Gli1b0LVrV4SFheGrr77CV199hWHDhmm/syeEkL8Kn332GXbv3o13330XjzzyiDvQIZgIuq+qVq1ahQkTJmD37t3IzMxE3bp1MWjQIIwdO1abK4YQQv4qJCQk4MSJE+jevTtmz54dlMEbQWc4CCGEBDdB5+MghBAS3NBwEEIIMUVAnAZOpxNHjx5FTExM0CTtIn9NlFLIyMhAfHx8QKrHSXD9k0tJeeyBgBiOo0ePMkKKXFJ+//131K5dO9DdAMD1TwJDWe6BgBgOV5TAQ4/8E3a73eu90BDjHZjOfS/drBU45Oy21lCjpXU45YbN3ASG6DJ/Cm07NRci3XWGatpV8D+WQde3QoexDV27Fhjb0N20SLpFtS0h9blQM09hwlrxJS8vD2++HlxpRVx92b3vEGJivLNIW0ON16S5fEiXn5MvZ5yNtBu3en6hvFf8GFY3YcK+AoC8AmM/dPstRDihTdOubg+Z6Zs0RroYIWk9hglzBOhTIpmJP5L6nCuMJQCEW/3L+JuRno5G9euU6R4IiOFwDbDdbi9zwxFCw1Fs30IvM8MRWgrD4SKYvhJy9SUmJtZQfqC0hiNMYziiaDjcWIUx0rUr7cNLbThspTQcLspyDwTHl76EEEIuG2g4CCGEmCLofootPc6a+a5e9zhs5qnOzFcuuvNJfdN9xeMQdEPD5D7oxkJC9/gtPTpLXxcA8td2uvHRPu6b+e5DQvOk7xS/DvT+W5qHYEb6+kj/dZBRt0Dz9RPsRpHuKxSLZqFK+rqvu3KFvum+4pGuQ/pq+Xwb/vetUPO1tbRudH2T1q5uD+r8q7awUt6fa5awNNfS51Gu5uvL0sAnDkIIIaag4SCEEGIKGg5CCCGmoOEghBBiioA6xxWMfh/d7xdEBFWdI0py3OpOZepHhErWtVv9t8lKUC10yu3qnPFSTLfOiW3VON4lpHHTOVV1TnCpzzpdqWmd41LStfisqCD6+YYBp1KG8dU5hUWEa4sOl7e05CjWzYH2R4Q24xrLK5R1YyP8/2iR5lH3ozedM75ilM0g08VkRNqFvaINwPHPAQ3oP3sKhAAN7eeU0Ha4MO66fpj5nCsNfOIghBBiChoOQgghpqDhIIQQYgoaDkIIIaag4SCEEGKKgEZVOZ3KEEWgLMaoAF2kiSTVpQOQog10ERq6rJNS9IfufJKumQy0ujQDur6JkWC6rKpCuIku8sJMmnNdGlepaV3CUDF1hLZdIZOuz7WZSdFyqXE4lCElitNpjCaK0ETVSNmBdSk5pOigjNxCUbdipFWUixFvJqLjdClppDnSrY8Kmr5l5QnXomnDKkQ0hQifO4A8nrqoMx3SCOkis6SoKl2EmTRuUrSWqUg9P+ETByGEEFPQcBBCCDEFDQchhBBT0HAQQggxRUCd4xaL0Slb2toNOqealMFD50jUOfGkNnT9lZzVOl2n4MXTOjm19Ub8L40r1ajQpUCQ2tCWwtSWu5XalQMTwqRaENqSu8XLgtg3DovFmBZDmgd9yU8h5YSJOdc53cti3WQLDmSdrpReR5dmI08T0CKVxpXK1wKyc1uXqkVqQzfGuhwnkraub3Yh+EVpfPFi6Wypfkhp6+EI8ImDEEKIKWg4CCGEmIKGgxBCiCloOAghhJiChoMQQogpAhpVFRpiMUQayak6ZKTAnJAQTVoDwURqAnu0UQgFwgGxMdGi7i297jDIzv15TNTdunWLQXbmzFlRV5fiQYr00KXbsAmFnHSBO1KdKt34RESEi/LadeoaZPv37xd1nQ4pikXuW6iwen2j2XRFuYIBW1iIIdJICtjRRfFIBYI0GWnEYlhSlBSgj/7LyjPOjZS+AwDOZOYbZPFx8vqwhRk7XWAyHZCkr4tMjBbkusAjM4XFdPK8Av/7Js21bp7swthLqVeypXQspYRPHIQQQkxBw0EIIcQUNByEEEJMQcNBCCHEFAF1jodYLEYHrolfx0sOb50nXXIk6hzC+YVyI7HRkQbZP+4aLOpabXaDLOuU7PCWHOG6gABdtg/RUaqZXbHGhsYBJzn8wsNlJ+fg/7lflDtDjGNxZu5MUff0mdMGmTjP0KSR8VF26A4OAsJCQwxOUimdiy7liFWYG936kFKA6JzghYITHACi7EbH9Kr/Hhd1CwQn7+GzNlG3ff1KBpk+7Y8sl65P6i8gO6ZzNTU2dKlPJNKyC0T50bM5BlmTmjGirnTd0jwDmjQyQvBAgS5iohQE764ihBASlNBwEEIIMQUNByGEEFPQcBBCCDEFDQchhBBTBDSqyqmUIYpAihSQihQBgEOMlJIjECSxrrBMRIQxegoA6ra/0SA7kC6nRgg5tt0g+3Hjt7KuEN2ii3JSFk36Aav/hZykyDVtkSmhjauu6Sjq2iLkSJENq1caZKdPG6OnALlQj3RtOi6nlCOFDicKffonFRmSihQBcioL3TxKcl3UkS4ya9oGY5qYXccyRd3HOiQYZIm1Y/3uW26BJqpK07kKkVaDTFcsSchwok2dIqUyOS2kUwGA9Bw5qqpRdWNaIt3eTM81pgepEOH/xzRTjhBCCAlKaDgIIYSYgoaDEEKIKWg4CCGEmIKGgxBCiCkCGlVVUKgQEuodXSAWXNKFeUho8k9JYikqBQDqN6ghygd0vsogW73vlKi7Zdv3Qh/8zzmjzc+kGQopx5EOaTx1RZ+qV69ukLVu117UPXRgryjfvesXYx80fSsULtCqU/YjOkwXZRQMZOc5EOqTF0osuKSbdAnd+hfk6TlytI0u2uqx6xoYZM+s+FXUbV6ngr9dQ66wD7X5mTRj4XDKEVRiG0KknTYaTYi2OpWRJ+rWjIsQ5dKcStGDgBwJVqjLl+VnpKguYqw08ImDEEKIKWg4CCGEmIKGgxBCiCloOAghhJgioM5xW1iINu2HJ0pT1khK1aH7Kb/k/KpY0ZgKAACaNrtSlEuOudM7Noi6GRlZBpnOTyv1WecE9C1U5G5DcHjrxlY6X5WqVUXdPv3vNsiqxhgLMwHAur2yozQ/35iiQZcOIlxIL6JzXErrwvfaTAVWXGKiwsMQHV78FtQFPkhO13yN01VaC5Eap6vOcSul+BnTtZGoK/UjTDOPkm6eJuWIXVOUSNovurHVrT2Jk+m5BtmVteTUKbqxl9AVfaoopE7R7WNpbUt90KYeKgV84iCEEGIKGg5CCCGmoOEghBBiChoOQgghpqDhIIQQYoqARlWpC//zRErLoStqJEWV6FJnSBEIEY3bibpbzhnTJQDAx/+eaZDFqqOibr6Q1sCmKUhV6DTq6oKBQjSFnKTL1qVUkYJb6tarJ+pWqmiMINn28zZRd8eOHaJcHHtNdEyBEAGiiyqSinb5XptuPQQDSinDtUnXJKXkAOQItDBd0TNhXCd+I6eImfe1LD++9iuD7OC6qaKuVFBIX5DKGOWk2fLa65PWtC5ySYru0q2TGCEySxejpFtq2UJxrkpRNlE3RxoLE5Gi/spKC584CCGEmIKGgxBCiCloOAghhJiChoMQQogpAuoct1z4nycFglNZl6pA8lLp0pNI/tXMPDn1wD2da4nytZbmBtl/1/8u6kqOcJ2TSnIa6tI+mMmgER0ppwZpcdW1BlnLNsZaIwCQkWN0MC5bukzU1dY0EAIedA4/yRGuNJUcZN2i/w4mQiwWg1NWciqHawIJpLWgCySQhvtEhjEVDADMfNC4PgDgp9ubGWQ6h7C0pu2a1BkRFcINsnRh3QFFrBuhHxWE9B0AkHrSmA5I50iPFGqTNKoupyrSpUOxCXNSoPH+O6XgEFFTTrMi6ZbHHuATByGEEFPQcBBCCDEFDQchhBBT0HAQQggxBQ0HIYQQUwQ0qsrhVIYoCasQjaSLpJBSjuhCCKSUAp3qxYm66/afFuVNm1xhkNntcuqAqlbj+Q7/tlPUNVNsKFdThKZJo4YGWcVq8aLuFQ0SDDKpEBQAHNpnLM6ki1yT0sUA8vXponGkojW6dnURRN7HBi/5hU5D4R0zEXYRQiEm3bhKqTqeSmog6qbM/1mU39ampkH20VY5qrBTrUoGWcu6ciofaU3rihfpop8qRBgjqPb8kS7qVo427lmr5nzVY42Ribr9GqJZbdLnly5QVCo+pUuHIrfrfzqV0sAnDkIIIaag4SCEEGIKGg5CCCGmoOEghBBiioA6x2GBwXspOZ5CNOZNqtOhS3shtfvLzz+Jur3u6CfKf0s3OvGq16or6kr+KEdhRVG3fSOjI3HfqWxRt3W8sT4GAFSJNjrxFm09Iuo2FxyBGennRN01a1YbZDpnta5uis6ZLiE58nS+vRBhrn3nOYjLcYjrX0ojYZWCQADkCnUedE7eQiGVTw0h1QcAvDOgtSz/4bBBJtUEAYCv9p80yB7TON3/eUsjg2zlHjlAZUg7OR1Qk+oxBtmjC7eLussf6mCQSYEGgFwfRUoLAgA5wnwA/gVxuJCCGPQBD/6l8imHchx84iCEEGIOGg5CCCGmoOEghBBiChoOQgghpqDhIIQQYoqARlWFhVgMRZqkiAVdyhEpPYkuHYAUCXTs2FFRd87M90R59Ro1DLKadeqLugnN2xhkvzrzRN2Pv/jWIPNNReHi90pyJIw6edAg69r3HlF390ljKoacP4zHA8Afx/80yKRoJgBwaKKqrGFG/YJCWdcm6BYqeSz8Sa+giwALBuxhIYbiRlJkmm4tRArpSaToKUAeK6cm2q12pQhRPqF7E4PsRFquqPuf341RUd9XlNfu+gPn/O7b3rOZorx9fWNk4rAuCaLupzv/MMh6NDWmUwHkDEa6KLe8Annso4RiUFmaInIx4cJe0cypVOBOjspiyhFCCCEBhoaDEEKIKWg4CCGEmIKGgxBCiCloOAghhJgioFFVSp3/54kUPxBqIipAlxZGikzQ5VAqyJTzRJ3+db9BtluQAUDUhjUGma4Ikxw1I1/zkcOyra9RrbJBVis2UtT98+QJg2zFmm9EXSkfji7KR9dnKShOLMIFTa4dze2NlJfMNypJF5EXDDiVcWykglpS9CAg50DSXW5WXqGgKyvr8r3lClFDUhQPANzRsrZB1qVhNVE3M9fYN10kUIxQ6EjXj2uEYlIAYLcao5wqRBoLQQHyns0S+gtAm1RKyj+my/ElFe3SRXFJ1yHly9Lv15LDJw5CCCGmoOEghBBiChoOQgghpqDhIIQQYoqAOsctFqM/KUxwMOl+ym8VfEY653ih09iGTePYy9IUZIkQnFG6dACSQ8qmKbIjOf91Ll2dU7nNNZ0MspOZcjqIzeuNxZkyMrNEXcm5rBtjzXCK46xzWkvOYd35/Cn6pXOsBwMhFmORHd8UJACQniM7Y6VUFrpxzROcvFFCyhIA+DNDTo0TF2UzyHTFiySHt86xLa0P3frXOZUPC4XPdgmpdQDglmbG1EG6fVwg7GNNZh3YNHtTGmedw1qS6wIepPQykiNd51wvDUG8rQghhAQjNByEEEJMQcNBCCHEFDQchBBCTEHDQQghxBQBjaoqdCiE+oQoSNkOpEJA53WFoieaoj8immADXQyCFKFTkK9L2+B/dJAU9VCgCaVodEUzuZHqxoJSFW3ylWRnCylVtH0zXnSYMZjnvFyTqkJKd2HXNCJFnulSw0jz7xvlo4vICwbyCpyG/knpPqToKZ1utibKSRpBXSYfXboPKaJPdz6rMI+6iK9Im5A6Q5OeJy27QJR/uO2IQXZvG2PaE0BO1aLbm1KxrHCbrCxFxAHAyXRjlFqFCDnFSbQQeSb1F5DTrJwWIuIyNGNWGvjEQQghxBQ0HIQQQkxBw0EIIcQUNByEEEJMEVDneGiIxeDgk1KDWJTsrFMWo9NI56CSWtA5xOyatAa5+ca+RdhkXd+6EAAQJuVIgZyvXzoeAE7bq4jysDM5Bll0utFhCABHjx4T5RLSGOmcqrp6I5IjXOcolRzhOt1wIQWMYe6cwXtvZA0LMTiRpTGUggAAeVxiNU5XqQVdKosKEfLHwrkso5M1Lko+nxSUEKFpV6pBIdX+AIA3vzsoyreknjHIRnZuIOqaKdEi1ofRrP9zGie0NCfSNZ/vm/F8uvQkFYUUMFJdEUuhPEelIXh3FSGEkKCEhoMQQogpaDgIIYSYgoaDEEKIKWg4CCGEmCKgUVUOp9JGzHgipVYA5AgcXWEZKQJHd27d+UKEKK6sPE3KBSE9g65vUooHXfqOzPxoUX5dFbtB9sOK70VdKUpHilADAIsQjyMVWwLkMQbkyCwpeg4ApHo6uvkQI9d8xl0XkRQM5Bc6tREznugiBaUIHCnlBCAXYdKd2xrqf4qTPzPyRd0IIY3I6UxZV2pXt5beX7hVlL/wYAe/25DQRUpJ6ydfU/SpohDRBMhRXFJhLQDIK/Q/UjRX+DyRIkJ1+6c08ImDEEKIKWg4CCGEmIKGgxBCiCloOAghhJgioM5xi8WYvkLjM/UbnVNZ8pHq6jxIDmFAdpRViNSkURBSJoRoUqdIdQ7aXNVW1L3q+uaiPM5qPN+yP46KulJdETNO5DATKTAAeex1Yyzp6taEXUjhUuDj8PX9O5gQU+4I68ZEhgytQzhE2Be6IAertEAg12apWzlC1JXqZoSFyH2THOk65/EHI7uK8g71KxtkOue/tN+k2haAXAtD56wu0KQJkj6SdDVPhK5p25U+e7JyjbVvcjQBPKWBTxyEEEJMQcNBCCHEFDQchBBCTEHDQQghxBQ0HIQQQkwR0KgqCenn8br0FJKuLjpCQhdJpIvGsAnRFLqIHylSRFc4SopGapLYWtQt1DSyc/d/jbqazsVGGCNhIgQZAJw9d84g00a+aQKzQoVx1mWDkCJItClnhKHwjR6SoomCGbswMLoII2k9SutOhxQlBQCZQmQOAETZjW3rCo5VijamONFlF5L22xGhMBkA5GsWnxTFFR0uf7xVtPpf2Ejam7pr1q1/aZwjNfOULaUR0URxSX3zLQwGAGGa40sDnzgIIYSYgoaDEEKIKWg4CCGEmIKGgxBCiCloOAghhJgisLmqIAQiCJEJYRb/C9no8k+FSAWJNGEeUrSKTl8XmSLp6qKDJHnVWGNhJgCIqxgpyv8QztemVStRt9017Q2ys6dPibqLFi82yOxhmoJNmrGXxkIX6ySNvW6eJLlvmqUgruMkrn+pv1KkFQAUCgWFnJrrlTa6LnpQF40kRXdF2WVdKTpOt68keWLtWFG3Xq68/tNyjJFgNs3elApKRWjGuEAY49gIXcEmeZ1KY6FbljHC2Odp5knKwybl4SqPwEI+cRBCCDEFDQchhBBT0HAQQggxBQ0HIYQQUwRdyhGpwI/OwSmlstCl9ZAcgVapagr0aSok55eub2b8UVKxmENnskTd7LBoUd6iZWuD7I8GTUTdP4/sM8i+27he1JWc/zonuG7spdQuunGTHIE65540/77nMlOgKhiQCvzorl9ymusCCTKENCK6tBdS2gpAdhTrhteMQ9Yp9Hn9vj9lXc0aqxVjTJmz9uBJUbdv89oGWaSQTgUA8guNF6JzguvGXtpDus+Y9BypAJauAJyQXsRPWWnhEwchhBBT0HAQQggxBQ0HIYQQU9BwEEIIMQUNByGEEFMENKoqJMRiiC4Q00iYilHSnavUTSBMaERX1MXM+QqFa/7l+7Wi7rWdkkT54WNHDLKffvpR1M3ONhbJyS+Ui/eIEVGa+dBGmwhyKTUCIEdK6XSlteIboSNF7AQLYaEWw7VJ0X+6qBiLLoxNQBdBaAYpLUdegZwOQzdnErlCKpOkxlVFXSldCABUFgpHNasVI+pKezZHKKAEyOmApMg3QL/+pUhBXcEtKQJLpyulgJHSkEiy0sInDkIIIaag4SCEEGIKGg5CCCGmoOEghBBiioA6xx1OZXBwSs4ondNJctIWOmVHkOTklZy2AOCU/WRi33SpFcQaFBplqR5B6sFDou7hQ7NFueQD1o2bhM6ZKY2blHoC0NcbkdA5I6WxmDRno6g76u5OBlmuj7NW57wNBvILnQZnuJl6JFK+D8lhCshzo5tHbeoMoW+6OZec/Lr0L1L9j2zN+qgUZXSCA3LNC90ak9A5oKXAhOw8OZBEV29EQufkl+pxxHV/UdQ9+cVTBtm5bGPKkgxBVlr4xEEIIcQUNByEEEJMQcNBCCHEFDQchBBCTEHDQQghxBQBjapyOpVfKSJCNRE/UpCG9JN9QC4yZLbGj1RwSVeQxaL8L14kpUDQXYcuEkbS1wSYaVMm+IuubzrEOdWMmzRPowdeJ+pKlxFu8+6bRQXvvZHDoQxzX+gwRgLZrfI1SEOoiw6SAqVCQ8ylY5HmUVf0SdoX2uJdQuSbrsiULtoqym78KCsQijDp+qZD2vO6MdbtKynlh03zmSaN8emvntaczyiLi7IaZKEOo6y0BO+uIoQQEpTQcBBCCDEFDQchhBBT0HAQQggxRdDV45DcdWbqP+jSGkhiExk5XB3xX1XQ1Tm2Jaearm9mHNu6y5NaMOMvl+qHAPr0K6KjVNeGcCujSw0TJnTad/516yEYCBXqcYjrX3MNUmoQXdCBJNaUktFiZiilfuhSdUjrQ7f+9UEVxgPMXJ6ZdDlS/RAACNO0IQUQSClZADn1T77mcyNcqI8iHa+r51Ia+MRBCCHEFDQchBBCTEHDQQghxBQ0HIQQQkwREOe4y5GVl5dnfE/QD9V45ZSgbcYZaqZehQ4z5zPjHNdds85R7BAcc7q6ClKfy9U5LtX00DgHpSwBunIU0jX74lpjkvM0ULj6kpGRbnxP0NdnQ/DfOS6hrfNhAjOOVzPOcZumXZ2j2C44oKUaHYA8RuXpHBdreuTKY5EnZAnQ7bd8wTkukZF+fp2V5R4IiOHIyMgAAMx487VAnJ78DcnIyECFChUC3Q0AF9d/YuOEwHaE/K0oyz1gUQG4FXM6nTh69ChiYmJKnTeJkKJQSiEjIwPx8fEIkWJ9AwDXP7mUlMceCIjhIIQQcvkSHLdghBBCLhtoOAghhJiChoMQQogpaDgIIYSYgoaDEEKIKWg4CCGEmCJgadVzc3ORn58fqNOTvxE2mw3h4eGB7oYXXP/kUlLWeyAghiM3Nxf169fH8ePHA3F68jejRo0aSE1NDRrjwfVPLjVlvQcCYjjy8/Nx/Phx7E89jNjY2PM5p87/313ARUFdfK1cOXzUxddufdc7cCf68ZQpD5nrl47n27h4Ti+Zx3HqgsR1rO9xrlxXzgsNeMm8jj8vd/XFqS60qVx6F6/RfZw6367y0HX3RRn75KvnvPDCqTzHTBmvS7nGyKcN5Tn+mvc858c15koZX6ui5aJMXchJpJwek+h6rS6+dukq6X0gLycLL/9rMPLz84PGcLjW/28HDiMmJvbieoDHfHnNpzqfr+vCfDovzJdTAU645tlzTfi0IbTrtc7c435R3wHlPpdL16EUnE5Xf87/7Tre4TpOKTgv5FZyeOg41IVjnBevweFUcDgvvL7wnlKAw3lBH7j4vvN8u04AzgvHKeU6Xrmv3y2/0A914ViXTDnPX4/T6erbhXad3q9xQcctd12r03mxXYeCcrrkrtcKTuW8+Pr8gF047uJreLbroet6rZxOwOk4v46djguT47j42um4+L7DV9dDRzmBglwc3/1hme6BgFYAjI2NLXPD4Svz+vCDZ3sXzynJDB+wF2ROD52SGA4Fj03u3pSeG9zjPVc/3Bu9dIbD84PI2xB4jK2vcfA9p89/4dHH4gxEyQ2HzjC4Pu2KeT9IiYmNRWwRhuPi3BVhONzzrDcSkkwyHJ5tuD7oXefwNBxOPwyH67XbcDgvGg6H0hsOt47TaDhcMp3hcDoVQi7IQ9RFw+Erc+lafIyF9+vzVSpdOha3zOl+DcfF4+BhOOBhAC5Y2vP/9Xitzg82LBeMiO9rGAyH08NYKG/DYXHIOpbzMuWUE0OWBjrHCSGEmIKGgxBCiCloOAghhJiChoMQQogpAuocT3dVpipD5zh8ZF4OXni2d/GcXjKP4yTnuOdxjKryGDtfJ7fna1W0XJSVVVRVbra49oKBjPT04h3bqhjnOJShDUZVXT5RVecjqFz/LaeoKkfZ/14oYKVjo6Oj0bB+3UCcnvzNiI6OdhuoYMC1/q9owPVPLg1lvQcCYjgsFgsyMzPx+++/IzY2NhBduOxIT09HnTp1OGYmcY1bMFXa4/ovGdwDJaM89kBQ/I6D+A/H7K8D57JkcNwCD53jhBBCTEHDQQghxBQBMRx2ux3jx4+H3W4PxOkvSzhmJSMYxy0Y+3Q5wHErGeUxbhYVTOEmhBBCgh5+VUUIIcQUNByEEEJMQcNBCCHEFDQchBBCTEHDQQghxBTlZjjeeustJCQkIDw8HO3bt8cPP/xQpP7ChQvRtGlThIeHo0WLFvjyyy/Lq2tBi5kxmzVrFiwWi9e/YCmNeilZv349evXqhfj4eFgsFixdurTYY9auXYurrroKdrsdjRo1wqxZs8q8X1z/JYN7wByBWv/lYjjmz5+PJ554AuPHj8fWrVvRqlUrdO/eHSdPnhT1v/vuOyQnJ+O+++7Dtm3bcPvtt+P222/HL7/8Uh7dC0rMjhlwPvXCsWPH3P8OHTp0CXscHGRlZaFVq1Z46623/NJPTU1Fjx490LVrV/z8888YMWIE7r//fqxcubLM+sT1XzK4B8wTsPWvyoFrrrlGDR8+3P23w+FQ8fHx6sUXXxT1+/fvr3r06OEla9++vUpJSSmP7gUlZsds5syZqkKFCpeod5cHANSSJUuK1Bk9erRKTEz0kg0YMEB17969zPrB9V8yuAdKx6Vc/2X+xJGfn48tW7agW7dubllISAi6deuGzZs3i8ds3rzZSx8AunfvrtX/q1GSMQOAzMxM1KtXD3Xq1MFtt92GXbt2XYruXtaU91rj+i8Z3AOXhrJaa2VuOE6dOgWHw4Hq1at7yatXr47jx4+Lxxw/ftyU/l+NkoxZkyZN8MEHH2DZsmWYM2cOnE4nOnbsiCNHjlyKLl+26NZaeno6cnJySt0+13/J4B64NJTV+g9oWnVScjp06IAOHTq4/+7YsSOaNWuGd955B88//3wAe0bIpYF7IHCU+RNHlSpVEBoaihMnTnjJT5w4gRo1aojH1KhRw5T+X42SjJkvVqsVbdq0wb59+8qji38ZdGstNjYWERERpW6f679kcA9cGspq/Ze54bDZbGjbti2+/fZbt8zpdOLbb7/1ujvwpEOHDl76ALBq1Sqt/l+NkoyZLw6HAzt37kTNmjXLq5t/Ccp7rXH9lwzugUtDma01s557f/jkk0+U3W5Xs2bNUrt371bDhg1TFStWVMePH1dKKTVo0CD19NNPu/U3bdqkwsLC1Msvv6z27Nmjxo8fr6xWq9q5c2d5dC8oMTtmEyZMUCtXrlT79+9XW7ZsUXfddZcKDw9Xu3btCtQlBISMjAy1bds2tW3bNgVAvfrqq2rbtm3q0KFDSimlnn76aTVo0CC3/oEDB1RkZKQaNWqU2rNnj3rrrbdUaGioWrFiRZn1ieu/ZHAPmCdQ679cDIdSSr3xxhuqbt26ymazqWuuuUZ9//337veSkpLU4MGDvfQXLFigrrjiCmWz2VRiYqL64osvyqtrQYuZMRsxYoRbt3r16urWW29VW7duDUCvA8uaNWsUAMM/11gNHjxYJSUlGY5p3bq1stlsqkGDBmrmzJll3i+u/5LBPWCOQK1/1uMghBBiCuaqIoQQYgoaDkIIIaag4SCEEGIKGg5CCCGmoOEghBBiChoOQgghpqDhIIQQYgoaDkIIIaag4SCEEGIKGg5CCCGmoOEghBBiiv8Hdf1Zg+q1PFsAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -1760,7 +1769,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 76, "metadata": {}, "outputs": [], "source": [ @@ -1781,12 +1790,12 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 78, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAcg0lEQVR4nO2debSVVRnGX4QEJxAlkkkQB2RQEBUBQcUB5MoMBoKiYUmrcLmipUtdlLbKQtM0c8zKokFgqRCiFyRAmS+KJHAZBG5AoIkDiGYmkP33tZ/f6Q4MB+6F5/fXftY+nHvud75v381+3qHaF1988UUYY4wx5rDmiIP9AYwxxhhz8PGGwBhjjDHeEBhjjDHGGwJjjDHGhDcExhhjjAlvCIwxxhgT3hAYY4wxJrwhMMYYY0xE1KjoC6tVq5bPz2H2M/moN9W2bVvRzZo1E/3222+L7tu3bzZ+8803ZW7ZsmWi27dvL7pdu3aia9TQW3Xx4sWiGzVqlI23b98uc8XFxaK/8pWviK5bt67olStXin733XdFn3HGGdm4ZcuWMrdo0SLRTZo0Ef3lL39ZNK9L7dq1RafXgdf3/fffF3388ceLHj9+fOQDrwVVi3ysBSeeeKLo7t27i/7oo49E//Of/8zGmzdvlrkLLrhA9K5du0SXlJSIPvPMM0W//vrrogsKCrLxCy+8IHN8HtN1IyJi06ZNohs0aCCaa0WqP/vsM5nj88lrwvVz+fLloo84Qv+/fswxx5T6uXbs2CF648aNoufPnx8VwScExhhjjPGGwBhjjDHeEBhjjDEm9iCGwBh67yeccILohg0bik59rNNOO63M186ZM0c0/bV58+aJpl+XeoUjRoyQOfqb48aNE33ssceKpo9fp04d0ak3SK/uX//6l+jZs2eL/v3vfy/6448/Ft28eXPR6XVat25dqXMRFfcJjdlX+Ezx+WzcuLHoNLbmoosukrlTTz1VNNcC+vwtWrQQ/aUvfUn0hg0bsvG5554rc0uWLBHNdYbxQ59++qnoAQMGiF6zZk025rPP9bJevXqi586dK3rbtm2iGStRv379Ul/La8i1uaL4hMAYY4wx3hAYY4wxxhsCY4wxxkREtS8qmKTq3OOqRT5yj3v27Cl61apVos8777xS54cMGSJzH374oWjWDvjb3/4mmrUArrzyStGpl0/vbtq0aaLpKzI/mB4lvb609kBRUZHMderUSfRxxx0nmt8Lc65Zp+Dyyy/Pxow3mDRpkug01zsi4vnnn4984LWgapGPtaBPnz6i+cx98sknotPngDVFtmzZIpprAZ9Hxs4UFhaW+vo33nhD5rhulBeXQ6/+P//5j+g0lol1QLZu3SqacVSspcKf/fe//1307t27szFjBrheMu5iypQpURF8QmCMMcYYbwiMMcYY4w2BMcYYY8J1CMwewJxd5u+nHleE9j547733ZG7FihWiTzrpJNH09em/sa5/+v6sCX7ZZZeJZm2Ak08+WTT9T/qGaR1x1mHn78HPyfdq06aN6DSHOiJi9OjR2bhr164yt3TpUtHM7zYmX9Dvrlmzpmj652nNf9YNoB/OteLzzz8Xzbr9/Pf/+Mc/svEpp5wic+vXrxfNGJ6ZM2eKZj7/hRdeKDqtKzJ8+HCZmzFjRpk/q1atWqIZA8SaJGn/iNatW8sca6cw/qCi+ITAGGOMMd4QGGOMMcaWgdkDmPrH9CAe66dH2jwe27lzp+hzzjlHNNOFeHzG8qZput/5558vcyxHmqbyRWhb0YjcssicT8sks6zxO++8I5rpWUwPWr16tWjaMmkaIi2Cbt26iWa7VbNvMD111KhRotMjYpbD/sUvfiGa93NVh2mGPKJmKmFqITA1lxYdWxTzmZk+fbroHj16iE5tOdoTH3zwgWimBdN+OProo0X/+9//Fv2jH/0oGz/00EMy17FjR9Fp6eGI3LbNnOc6llqdtEVpVXbu3Dn2Bp8QGGOMMcYbAmOMMcZ4Q2CMMcaYOAxKF1evXl00Pd/yoG+Yekosqfntb39b9P333y/6mmuuEU2veuzYsaJ/8IMf7NFnTclHudKhQ4eKpo9/4403ik7bgdLHZ7xBcXGxaLYKffXVV0V36NBBdJqatHbtWpnr16+faKYSMd2HLU/5+vR7Y+rlpk2bRDPlkeVNGXPAdK2//vWv2ZipmEypeuutt0S/9NJLkQ+q6lpQHu3atRM9a9Ys0UztKgt+V2nK2IEmH2vB7bffLprX5qmnnir19XwGeJ8yffmoo44SzXLDTEtM0535PPFzMoaAsRAXX3yx6FdeeUV0mnaYtkKOiJg4caJorg2MIWC6ZUFBgeg01oLln7lmbd68WTTTvEvDJwTGGGOM8YbAGGOMMd4QGGOMMSaqSB0ClpY98sgjRac5l126dJE5+lUDBw7cb5+LPs3DDz8sun///qLZvvbNN98UTZ+8ssH4C3p78+fPF53m4dJDZT4vvXjmJrdq1Uo0Wy2nfP3rXxfNNqO87ry/mjZtKpq+Y1qS9LbbbpM5+oL0JFnToKSkRDTjMtLaArz+zM9maWNTNoxDee6550TzetOLT59n+ti835mTzroE/PeVHca+LFmyRHTjxo1F/+EPf8jGjL1iDj3va+bcs7YH15309YxdGjBggGjWGTj77LNFs0Qw8/sXLlyYjZ988kmZY60Vxozxb9Mll1wi+qyzzhKdxgixJDrbpvMaVhSfEBhjjDHGGwJjjDHGeENgjDHGmKikdQjKywfe01oC+5O0TvaIESNkjr43oe+2bds20cxj3RfykXvMOt9s/UsfK22ROnfuXJljXwT6afTa6Rvy2hUVFWXjb37zmzLH74V12On1Pf/886LTdqoR6o/++te/ljm2IKZ3TO+PsRR/+ctfRHfv3j0bFxYWyhyvP+MwfvWrX0U+qCp1COgPt2/fXnTqa0fk+t78PflMpXEA9913n8yNHz++zPcaM2aM6J/85CeRL/KxFjA+in002B457SnAnHn2LmCsFb9H/nvWEkjz/en5f/jhh6LTVuYRuWvDGWecIZrPZ+rzswX0Aw88IJprWFqnJULXsIjc+KP0OvFZ589mnZdbbrklKoJPCIwxxhjjDYExxhhjvCEwxhhjTFTSOgSs+cwe1vszhoC+zfbt20Wz53yaL5zWsT4cYH/4HTt2iE7jKyI0F5teHPN9+R0vWLBA9NSpU0Uz5/5rX/taNv7d734nc4w3YJ/xNm3aiGZvg9NPP110Gv/Qs2dPmeM14O/Bn71o0SLR69evF53GL7CuOp+TqpbLnm+YF85eIvtKGpNAT5c1RZhjzvu/qsHYF/r4jAlK64aw3gNrd3Cd4TPF+5wxEmlMUN26dWWO6z3XnWnTpom+9dZbRbOOQZrv/+ijj8rc5ZdfLprxDPzcvA6kefPm2ZjXm7VVHn/8cdGOITDGGGNMhfGGwBhjjDHeEBhjjDGmksYQMFeUPk6vXr1EL126NBuznwBJ+8tHRFxxxRWi6R+zlnVFvZhDEebz0xOrXr266LR3OGtLrF69WvTGjRtFX3XVVWXOMy4graXO72jZsmWiX375ZdFPPPGEaHp7w4YNE53mKs+bN0/mGCvBHGvWmiirL0eE1nmvX7++zDEfm70lDkdS/5n3UHn1E+j7v/DCC6Lvv/9+0WlNiXQNisi9Py+99NI9+iyVHfr6rBXAWvppzQauuezrwGvZqFEj0ew9smvXrlI/G+sjMK7kwQcfFM3YB8Y7sM4IvfwU9lhg75s0JiAi9xpyLVixYkU2Zr0EXrM77rij1M9VFj4hMMYYY4w3BMYYY4zxhsAYY4wxUUljCMjkyZNFs7dBWvu6bdu2MnfjjTeKpg/ImAFSXFws+qabbirz9YcyrVq1Es1+AyUlJaLTGg7Tp0+XOXqo9Nrr1atX5meh35bWBf/tb38rcy1bthS9du1a0SNHjhTN+Ab6dffee282HjhwoMyxNsC4ceNEP/LII6LZ44Ee5jPPPJONBw0aJHPsI79u3bo43GBsyowZM7Jx7dq1ZY6xIewNwToFrPvA/gNpr4j33ntP5pgXTs+d8Q3ss0BfvbLRqVMn0ZMmTRKd1h2I0OeTuf9XXnmlaHrvXKMZF8DaHWmMwuLFi2WuRg39k8dniO/FfgKMjUjXMcY5NW3aVPT1118vmj1XBg8eLHr27Nmi05gDfg7e24ybqig+ITDGGGOMNwTGGGOMqSKWAWHJ3JSPPvqozH/7jW98Q/SECRNE82jP/A+WK2WqC9MS0xRPtpZ97bXXRDNVkPYDUxpZmjNN67r66qtljt/xddddJ5r3E+0Llk3u3bt3Nub9wn/L8qVMoWWabFnH2LQTeHTKFMZDEaZ18nqmZc15fdh+nCWuef+++OKLZep9gSmi3/3ud0Uz1bWyQTumb9++ommFpa3R+SwzzZzH9KeccoroFi1aiE5bK0doS2LaDWzhTkuY1k9afj0i4tlnnxWd2gIsqcw0YbZ8p0XANus89q9Vq1Y25r3NEvsbNmyIvcEnBMYYY4zxhsAYY4wx3hAYY4wxJqpoDEFZ3H333aLZSpOpRPR4WdbW/A96ZAsXLhTNlJ7U1+Jcs2bNRD/00EOiu3fvLppe3vDhw0Wnnho9SXp5TFtli9QGDRqITv3PCPWizznnHJmjd7pq1SrRHTt2FM34BJKmn7Fs6vLly0WzdfehQM2aNUUzbbigoEB0moLMe4TtZStTqWeW463s0N9mmiRjDNL20ExBZsol0/X43owDGDJkSKmvZ1rh008/LZopyEyXZJtqxhikvxdjG2bOnCmaMQJMcWRaMVOr07WD14T3cocOHWJv8AmBMcYYY7whMMYYY4w3BMYYY4yJiGpfsOZhaS+sou066TfRe6HvynKR9B0fffTRbFzBS3dQyMdnu/nmm0XTt0rLxkZoyV+WPabXfvrpp4tmTjh/FnOTi4qKsnGXLl1kbs6cOaLZTvWII3Rf3LBhQ9GMSUjzidOSrBG5dQkYK8Hfk6WM+dnT92NsAz1J3rv0O/cXB3ItYMwF202Tyy67LBuznfHBZPfu3aL5fDIep2vXrvvtZ+djLRg9erRo/n4s45vGygwdOlTmPvvsM9H04rds2SKapY5XrlwpOo3bYe0UtivmOsL8ft5DP/zhD0VPmTIlG2/dulXmWNqdLbD53rwOvAfSa8rvlKWMWX+Ba0Np+ITAGGOMMd4QGGOMMcYbAmOMMcbEYRBDQPr37y+aean0mMidd96ZjdnalrXSDyb58A2vvfZa0Wxjyjrzn376aTamp8Vrxdrb9PGZH8w8582bN2dj/u78Tum38b1Yt4AttNOa9vQ3y+rnEJGbH7xz507RzLtPe3OwVwHrQvAa//nPf458cCDXggULFoi+4IILRNOHpU9bWeA9yVgT/p6VPYagT58+ovk8M04nrbNAzz9t61sRTjjhBNFsNZ32NmC8AesnsOYB6xKQNWvWiG7btm2pr33rrbdE33XXXaI7d+4s+k9/+pNo/n3p0aNHNp42bZrMpf0bInLXuMmTJ5f6OVN8QmCMMcYYbwiMMcYY4w2BMcYYY+IQ7GVQHpMmTRJNz+hnP/uZ6DSvOSLixz/+cTam/3TPPfeIpr9c1aHfzXiMiRMnik5jCuidr1ixQjT7BSxdulQ0rzW9+R07dmRj1hVgnXj2W2d8Ar2/RYsWiU77YdCroz/Ke4Cvp/fKvOi01wZz1dknYX/6zgeLXr16iW7Xrp1o+uFpHnhlhjED/D14P1d26tSpI5o1L9gjZv78+dmYMTusr8Fn5uqrrxb9m9/8RnSbNm1Ep3EC1atXlznWP1m3bp1o1gJo2bKl6BtuuEH02LFjszFjrMqrZ8KYAcZCpH0SIiImTJiQjTt16iRz7ItQXixEafiEwBhjjDHeEBhjjDHGGwJjjDHGxGEYQ0DoZX/1q18V3bt3b9Fp3YKRI0fKHOvUX3HFFfvjI1YaSkpKRNNfo6+Vet6su08fnzX/e/bsKZrxCfQwU89yyZIlMsefXZ63t23bNtHsV5DGAfCaMIaAddnTugIRuf4nPczUa6bPfO6554pm/EFVhD0rWHuB9eJTX/VgwvoRd999d5mvnzVrlug77rhjf3+kvPLxxx+L5vNYo4b+aUm/1/Hjx8vcmWeeKbpevXqi2SOFzwy997Q2AHsP3HbbbaILCwtF81lnDALjF9K4AfZNSHu5RJS/5vHe3rRpk+jzzz8/G/MasmdP69atY2/wCYExxhhjvCEwxhhjjDcExhhjjInDsJfBvpL6RPTJdu3aJTqtPR0R8corr+Ttc5F81C+/6aabRNPvZq71SSedlI2ZU0uvjrnH9MsZn0Fvr3HjxtmYPRUefPBB0U2aNBGd1jCI0FroERF169YVfdppp2Vj1jhgP3XWGWB8AvO3jz/+eNHbt2/PxqzVwHrxTzzxhOh83AMR+V0LmHP+zDPPiKYPezDjJtK4gTFjxsgcYwJ4f/NZmj59+n7+dP8jH/fB4MGDRTMOh2tjWtvjvvvuk7m0N0hEbg0DrhWM+2I9jlq1apU6t3v3btGMGWM+/zHHHCOavW9uv/32bDx06FCZY90Q/mzWxGEcBmMnCgoKsjHXjW7duolmT5W0fk5Z+ITAGGOMMd4QGGOMMcZph3H22WeLHjRokOg01SMi9ygshSlnc+bM2cdPV7ngcTevBW2BNDWJrXlZLpjw6J1lednaN7UJeKTI77BVq1aieTTH1q7Lly8XfdVVV2XjxYsXyxxLXbOFKUvxzpw5UzTtifRIfPXq1TLH49BrrrkmDnUOZqlifne33nprNuYROu/PgQMH5u1zHQxYxpzPPq2ctAX5vHnzZC5tkx6Ra5+MGDFCNEuTs7Vv2iKbrZKZBlxcXCyaNhxheeK09DFbWL/77ruiuQbSbmTaYWpNRkS89tpr2XjYsGEyxzWPdm5F8QmBMcYYY7whMMYYY4w3BMYYY4yJwyCGgJ7RqFGjRA8YMEB0mipXHkwjYYoZ0/CqOkcffbRolupkOlqaasQyu4w/oJfHNK2pU6eKZlwAr33K7NmzRad+ZoSm80Tk+vgsQfr4449nY6aa0ten3rBhg+jUh47IbY+cfhamdrEEc1Vrofv/4D1E3a9fP9G33HJL3j7Ld77zHdHf+973RKdpYn/84x9lbvjw4Xn7XJUBPkNMz+Na8dJLL2VjlnTfvHmz6DQGIELbjUdEPPbYY6IZr7Bx48ZszOeTXjtTMvl88u8FS6qnpZGZzvz555+LZsosy56zZPOll14qOk2/5DXjz2ZMR0XxCYExxhhjvCEwxhhjjDcExhhjjIlDJIYg9f2Zi00PiC0n95TXX389G99zzz0ydzBzpA8EH3zwgWj6+EuXLhWdel6vvvqqzHXs2FE0Pa+0FHFEbg44W6amLVDZhpl5z8wHprfXt29f0SwZnHp/rGnAmIFLLrlENGMj6D2T1KtlDEGvXr1Es+xqVYSeLjVjfB5++GHRaXta3q+856677jrRadvciNx7kO1o03x5+tqHOrzXGNvB7yX1+YuKimSO153tyhl/xLLQrBMyf/78bEzPnyV92Y6cdUWYz//AAw+ITmutcP3n78F1iXVFuA6xDkG6br3xxhsyx7gnlm+vKD4hMMYYY4w3BMYYY4zxhsAYY4wxUUViCJgHTt/2kUceycb0lvcU+ls//elPRac1yg+1OgPlceSRR4pmzi79ufR7os938803i27durXoE088UXRhYaHos846S3Sal8sa4mwp3KVLF9Fp/EFEbmtRtg6tXbt2qe996qmniqaPzVxjeoFp69YIbQec5ldHRNx7772iGdNxKMK219/61rdEpz0D2NaaLbTLg7XpWc/i+9///h6936EEewQ899xzotN+HxEae8U5thtPa/ZH5MYn8Hthu+S0lgfreqTtxCNy40oY48Offeedd4pO+zAw3oDxQ2nNgojcHg2MKUjruETodRo9erTMTZs2TTSfk4riEwJjjDHGeENgjDHGGG8IjDHGGBOVJIaAftSTTz4pmjnozZs33+ufRf+JeaXsxZ3m0h/u0COjV1+zZk3RaV0C+vZpH/GI3JzbNm3aiGZtAPq5v/zlL7Mxc4+Z63/99deLTnsTRETMmDFDdJprHBHRoUOHbMx+Dmk8S0RuzvSSJUtEn3feeaJZa2DWrFnZmNefsTWMZ6iKLFy4UDT95PLiJNI6Bbw+hPEd48ePF53PPglVHcb4MDaGz0zXrl2zMddU1ntg7MeaNWtEM36oZcuWolPvPo1diND4n4jc2hI7d+4UPWbMGNFc8xo0aJCN0/oH/++1/fv3F826LewHwRi1dM38+c9/LnOslcJeEhXFJwTGGGOM8YbAGGOMMd4QGGOMMSYOUAwB+1uzB3zqyUZENGrUaK9/VpoXGpFbU5s55axrb0qHfneNGnr7PP3006LTmhD0GNkr/MILLxTNGvb0e5966inRkydPzsbsj07v7ogjdB/MOBLGBQwZMkT01KlTs/HJJ58sc4MGDRLNmgb09uiRV6tWTXTqDbKPPOMNtm7dGlUd9nkfMGCA6JEjR4qmx1sW9F0ZO8K4FlM6TZo0Ec16Gszvf/HFF7MxY13opTNGjDFmjAsYNmyY6HSd2rVrl8wxZmDZsmWiuc7weeU6lvr+XGcYU8X35t+5iRMnimZfnvr162dj1tth7FtxcXHsDT4hMMYYY4w3BMYYY4zxhsAYY4wxEVHtC5q1pb0Q3uaeMHbsWNGMISiPlStXik493Aj1iegHs3b14UIFv9Y9YtSoUaLZ26Bhw4ai586dm40vuugimaOPz/xz5pCzxv+2bdtEr127NhvT92NeM3ugMw6Avj9r4KdxKu3bt5c51h9nPML7778vmjXHGZeReup9+vSROdY+5zWjR76/2Je1wBx48rEWDB48WDTjWY477jjRaR1+PiOsMcJaHczPLygoEP3yyy+LTmMQ+LnGjRsn+tprrxXNGgns18JrmdYt6NSpU5mfm3+3WGeA9RT4tyut/cA1jLESjNu76667oiL4hMAYY4wx3hAYY4wx5gBZBubAk49jQrbrZLoQyw+nx+Msu1u3bl3RPOZn+WGmhLFdclp2dv369TLHo7tu3bqJZrpeeSWaU2ukadOmMse0JJYzpa3CI0mmJqWpRuX9LFoGTNHbX3gtqFrkYy1g+WCWl2dacfq8c473LcsH8+icaYf892l6LtNYJ0yYILpt27aimYbO55WtmtOUSKZT8vdgGiLfm1Z6s2bNRKfXoXPnzjLHltJcRypahtsnBMYYY4zxhsAYY4wx3hAYY4wxJipJ+2NTNWBaDD2yLVu2iE69+7T9aURuTADjEZgKSC+e3mCaAskYAab60V8rKSkRzdatLNOaevf0Nz/55BPRTEtM2xlH5F5DlklOS2/Tg6QXy9gHY/IFS8TXqVNHNNNp03uX921Z6XURue2P+TyW1UKcKev9+vUTzXQ9PmP892lMD//9O++8I3OM8XnsscdEMxW7d+/eonmd0vWUsUcLFiwQzbgoxxAYY4wxpsJ4Q2CMMcYYbwiMMcYY4xgCswesWrVKNL15xgm0aNEiG7P17MUXXyy6sLBQND0ylg+mz5iWJy6vDgF9Q5ZCXbRokeiy8u75XrVr1xY9adIk0TfccIPoKVOmiGYcxsCBA7MxWyXz+2DLU7b6NmZ/kT7bEblleFn+u0ePHtl4zpw5MldUVFTqayNy42wYQ8Dn/e23387GbJ181FFHiU7Lq0dou/GI3LWDvn4ay8RrcOyxx4pmm2Y+z6wb8uyzz5b6fmzxzpbRextP5BMCY4wxxnhDYIwxxhhvCIwxxhgTe9DLwBhjjDGHLj4hMMYYY4w3BMYYY4zxhsAYY4wx4Q2BMcYYY8IbAmOMMcaENwTGGGOMCW8IjDHGGBPeEBhjjDEmvCEwxhhjTET8F3Fc4YKWtUkBAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -1796,7 +1805,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1806,7 +1815,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1816,7 +1825,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1826,7 +1835,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1836,7 +1845,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAbHUlEQVR4nO2da7SVVfXGp4rlBbVEIVFUBEFULiohF5G4Q2CYIqYO0RxKjS7WoA8OcfSlUskLNSIHWjQMRyIoJaKQJBdBkauggKgEYoCKCKmAlSDx//R/nc9vwz4H5IT78Pw+rWesw97v3ud911msOeczD9m1a9euMMYYY8xBzaEH+gKMMcYYc+DxhsAYY4wx3hAYY4wxxhsCY4wxxoQ3BMYYY4wJbwiMMcYYE94QGGOMMSa8ITDGGGNMRNSp7g8ecsghNXkdZj9TE35To0ePFr1y5UrRhx6q+8ujjz66GL/33nsy98UvflH0aaedJnrp0qWiN23aJPorX/mK6C1bthTjunXrylzDhg1F815u0qSJ6BdeeKHstU2bNq0Yt2vXTuZatmwp+rHHHhPdqFEj0fzOXnvtNdGtWrUqxtu3b49y8FoGDRpU9uf3Fa8FlUVNrAW9e/cWzXvz6quvFr169epiPGfOHJlr37696Lfeeks0n/WPPvpI9DvvvCO6RYsWxfjtt9+WubwmRZSuK//9739F16mjfyLPOuss0StWrCjG9evXl7mzzz5b9MaNG0UvW7ZMdN++fUW/+uqrot99991ifPrpp8vcBx98IPpLX/qS6DvuuCOqg08IjDHGGOMNgTHGGGO8ITDGGGNM7EUOgTGMrTP+dsMNN4j+4Q9/WIxvvfVWmWOs7pNPPhG9YcMG0V/4whfKXlu9evWK8RFHHCFzO3bsEM2cgX/961+i33zzTdFbt24VfeaZZxbjY445RubGjRu3x5+NiDjssMNEz5s3TzTjkC+99FIx7tChg8x9/PHHoidOnCi6pnIIjDnyyCNFH3/88aIZ1885Q927d5c55s2cdNJJovk8durUSTSfqfxcMGeHdOvWTfSiRYtE//vf/xbN/JlTTz21GHOd+ec//yl63bp1ovkdMt+Ba2D+XPzOjj32WNFVfe494RMCY4wxxnhDYIwxxhhvCIwxxhgTEYfsqmaRqmuPK4uaqD0eOHCg6Msuu0z0Aw88IDrH6lm/y7j92rVrRTOngDFK1iK///77xZixPNYeMxa/Zs0a0SeeeKLoBQsWiD7llFOK8fr162WOngWE9dpV1UXnmuoTTjhB5hiTnDlzpuhnn3227LXsK14LKouaWAuGDh0qmjlBrLnPviL0yzjjjDNEM3bOnKBVq1aJbty4sehc///b3/5W5q644oooxxtvvCGasfmpU6eKzt4BvM6c/7O71xo/frzoSy+9VDTzF/KaR7+TnTt3in7llVdEP//881EdfEJgjDHGGG8IjDHGGOMNgTHGGGPCPgRmL8he2hGlftmXX3656BzXZzybXtzMCaBXAGt0y+UU5Lh7RMTmzZtF0yOc8U/2XWC9f4778zoJ64XPOecc0SeffLJo5hDkmCb9EA4//HDRzDEwpqZgjkCux48ojWlfd911xXju3Lky9/rrr4vmupJ7h0REfP3rXxfN5zk/J4y1L1++vOx1v/zyy6LZj6B///6ic6y+WbNmMtemTZs9XldExODBg0Wzrwl7OOR1iLlK9Ijp2LFj7As+ITDGGGOMNwTGGGOMccjA7AVNmzYVPWrUKNFsiZrL/xgi4NE4jyBZSrRt2zbRPB7PR4MsO2RrULZXpVVq27ZtRTOkkI8weYTIckoenbKUiG2eeS05/JFbrUaUHn+ybMmYmoLH9DwuZ5gtWxnzKJzWxHy2v/Wtb4nmWsBj/3x83q9fvz1eR0Rpa/QePXqIpi0ySzhzCfLTTz8tc7Q1Z/iCIT++F0uvc0jhwQcfLPtaDFdUF58QGGOMMcYbAmOMMcZ4Q2CMMcaYsHWxtOWMiOjSpcs+v9aLL74omuVu/0tqwq6Ulr85fhZRWoKXrTwZc2T5HUtunnjiCdE9e/YUvXjxYtG5DPG4446TOcYs2ZaUpX+M1V944YWiP/zww2L8n//8R+ZoRcxYKq1RCa2Nzz///GJMK1S2hJ4/f77oZcuWlX2vfaVS1oJrr71WNK2277//ftG0pa0t1MRaMGzYMNGM+zNvZ/r06cX4vPPOkznm/EyaNEl069atRfO+ZzvkXOrLEsZrrrlG9O233y6acXy2I69TR9Pucpth5icsWbJEdOfOnUXT9pw5Bizzzu2SuRZ8+ctfFs11aezYsVEdfEJgjDHGGG8IjDHGGOMNgTHGGGPiIPAhYC3ojTfeKPqWW24Rzda3jJeWi8dNmDBB9JVXXlnt69xbWHs7YsSIGnuv/+e2224TPWbMGNFs/5nr92kHzJgjcwK+8Y1viGaMjDW6uX6fvzNq1uwyx4B5JYwj5rjhyJEjZS7H/CNK44D83M2bNxed8xMiNA7JuCBjjrRZPRj59re/XYx/9atfyRzbzzJfiPdcVS1jc7z53HPPlTna0v7iF78QnW29KxHmutA6l3k6Xbt2LcZszXvxxReL5lpBHxA+z7RC7tatWzGm7wefL9qcM/eBeVK8J3K+Ev825M+8u9fm88p/zxyDnI9Ea+IpU6aIvuSSS2Jf8AmBMcYYY7whMMYYY4w3BMYYY4yJWpJDkGu/hw4dKnPXX3+9aHrqMz7FmO+f/vQn0TnOwxgQa84/KzmWPXDgQJm78847Rf/jH//Yr++9Ox566CHR9CCnt0CeZ34B2xlv2bJFNPsNsEUqcwpy3LFu3boyd9VVV4l+7rnnRNO3YO3ataLZajnHQK+44gqZo6fB73//e9GsmeZ783N37969GK9cuVLmhgwZIvrxxx+Pg41vfvOborO3AHNFCGvUeU9VRc5PYs05Oeuss0TTY7/SoCcJ1z7mYuUeH7mePqK0fp/PEHMO+Dzzec++IT/72c9kjusONdsKN2jQoOx8/txf/epXZW7hwoWieb/xvemvwDyx7NXCn2Ue1OzZs0Xz7+Ke8AmBMcYYY7whMMYYY4w3BMYYY4yJWpJD8NhjjxXj3r17yxxrVp955hnRd9xxh+hZs2bt56urPmeccYboRx99tBjT//vhhx8WzbrnmvAvZ4yMMWzmFCxYsKAYsx8A8y8mT54smjXijBPu3LlTdI4X9+nTR+aeeuop0axFZvyT3ur0W8jXctRRR8nc+PHjReea6IiIpUuXis45AhGl8dMMe7f//Oc/F818hNoIP+NNN90kulzeAP3f+QzxHqyKUaNGVftneR9UOs8++6xoemQwFybfu+xrwrg884noUzBz5kzR9IDI9wj/7csvvyya9fy5D0JEaX5D9juJ0DwA9ilhfhH7tfzhD38QTW8K9sLJn2XevHkyl3M0IkrzFaqLTwiMMcYY4w2BMcYYY7whMMYYY0xUaA4B61BzfJo5A7169RI9bdq0mruwKmBfhXvuuUc046HZD/yXv/ylzN199937+eqqhjW5OUcgorRev23btsWYsfaf/OQnohljpe83429t2rQR3b9//2JMD3DGAevVqyd62bJlopmDwM/Zo0ePYkwfizPPPFM0a5HpJ8F55gUsX768GNNngPXcvLd/+tOfRm2D9db8XWXY74KeEHuTA7A76tSpyOVzv7Bp0ybRfMZat24tOj9jl19+ednX4vPJ+Dg9Dugtk3PKmjRpInPsbUB/E/79YE+GrVu3iu7Zs2cxnjNnjsyxb8mGDRvKar43v8P8fA8YMEDmmH9QLhepHD4hMMYYY4w3BMYYY4zxhsAYY4wxUaE5BKzJzzWXixYtkrkDmTPA2vu77rpL9EUXXSSa1/7d7363GC9evHg/X93ew9pj+rOzD8S6deuKMX3imQfC2PDf//530cxfYA5Bzs9YvXq1zDG+yRppeobTl/6CCy4QnX0LGMdnvwF+7tGjR4u+7bbbRA8fPlx0zqVgjJF1z8xnqI0MGjSo2j/L3/NnzRkwn8JYevv27UXTlyA/3xs3bpQ59g6h5whzr5hDQF+R7MFCXwq+N9cV8sILL4jOOQMR2heFcf1HHnlEdKtWrUQzx4XeKuxXkP0W+LeCvgN8reriEwJjjDHGeENgjDHGmAoNGfCYNvO/PFrPbZcjSltM/vjHPxZ92GGHiZ4yZYro733ve6LzkfvnAR6vde3aVTQtRXP7Zpbjsa007UtpKcrfKy1Gc3kQSxZ53WwVzaNlhi/y54jQ41KGI84//3zRPBbk52IpHK2Ms40yj0ppT00L19oIj2zLcfPNN+/X9+Z9ccoppxywaznQ0GadsLwvlyRXdR/TSpwhBD5TDMvllthcQ3kMz3WHx/wMUdG6OIeF2f6dLYhXrVolumXLlqIZhmFIsGnTpsWYFt605c4/uzf4hMAYY4wx3hAYY4wxxhsCY4wxxkSF5hCUa+3IeNL+Jre0ZM5Au3btRLNMjJadtKL9vMPyH7aO/trXviY6t+tkySLjZ7Qu5s8fccQRollamP89S//YlrlFixaiGbM89thjRdOiNluSMqbIVsvXXHON6KpyXBg3zNdSlc3q9OnTRdcG62LmDFSVJ5HjtiwZ+6ywbIxlxRneU7TnrXT4TLCtMC2Ds/1wVeV2/O74WiwTprVxo0aNivF9990nc507dxbNfKPGjRuLnjVrlmi2mc95YcxrYskjLdLZTp4l8vlzRGiuE9sfcz1l2Wd18QmBMcYYY7whMMYYY4w3BMYYY4yJCs0hYG3ptm3binGO8UeUxmzZRrgqGKtmjCmT225GRFx55ZV79V6fd/L3HFFq6cu2wzkW2KxZM5lj3Sw1vQNoT0qb3pzPQH8I1hKPHTtWNG1XeS2cz54H9F7g/TdhwgTRjIeeffbZohmbzVar9E/gd3rZZZdFbYM5GuXyhyLUPnvz5s379VouvfTSav/s/PnzRVdavlBV0IeAeTq0Nc/x9cmTJ8sc19SqfAcY1+c6O27cuD3+2+3bt4tu2LCh6BkzZojOeVARpS2Lc25T3759ZY5t07mmMdeJ3gJs+Z79Gzp06CBz/Jz0vKkuPiEwxhhjjDcExhhjjPGGwBhjjDFRoTkEw4YNE53jKYz5fOc73xHN+vYf/OAHouklT//y5cuXF+NbbrlF5lgHXts46qijRLNmnp7/OY7VvHlzmWMtMV+braHHjBkjmq+X63CZ98H8A8bxWU/Ouuj33ntPdK6FZ4+GqVOnlr1OtohmLsS1114rOtdRM9+A/5Yto2sD995774G+hIJ+/fod6Ev43MA6+Lffflv0iy++KDrfu/T5YFy+fv36opkzRq+ZFStWiM7PO3Md6AXA/AX2p/joo4/KXut5551XjPl3iWta9i+JKP3O+LeL89lvgd4L9CFgvlF18QmBMcYYY7whMMYYY4w3BMYYY4yJCs0hINddd10xpnc1435762/OutSrrrqqGDO2XNuhVzdreNkDnf0HMqwn37Jli2jGw9nHfOnSpaJzzIxxe+aF8HPQ95s9Atq0aSM655HQm6Ft27aiFy5cKJpe/PyORo4cKTrHFXfs2CFzTz75pOjevXtHbYP9M6oi555MmjRpv15LrgM/2KkqB4h+GnPnzi3G9PBnzs7atWtFs/cIfQroeXD88ccXY+bsUPP5Yz+W3D9gd9eafW3oA8I+CRMnThTdo0cP0Yz7sz9E7pXDfIT3339f9N4+N/+PTwiMMcYY4w2BMcYYY7whMMYYY0zUkhyCHHMaPny4zO1t7TB7Ul9//fWiD7a8gUyfPn1EsxaW9cI5zjVixAiZo//4aaedJpp+5awnrlevnujsgTB79myZ4++Q+QuMaTLOz2vPtcfPP/+8zLEHOmOUVfkQMDaYcyn4uZgb8cwzz4j+0Y9+FAcbufdB//79D+CV1G7oBUDfAfbZyNAnhK/F2DrXGcbmed/nnhP0KGC+EH1mtm7dKpr5Cew3kH0Mnn76aZnLPU8iSnORmCMwZMgQ0cxfyL4E7F3AHCz3MjDGGGPMPuMNgTHGGGO8ITDGGGNMLckhyLGZRx99VOZYU05Yv3n11VeL3t891SsZxv4YA2NsPsdz27dvL3OtWrUSnXuYR0R06dJFNONxGzdu3OPrHX300WWvq2nTpqLHjx8vmr3s6TGea6oZ82cvgwEDBoj++OOPRTP+yRhnfu/TTz9d5phXsXjx4jB7ZtWqVaLXrFkjml4XvAfNp9DPpWPHjqL53Xbt2rUY02OE/QGYZzNo0CDR69evFz1hwgTReU1nLJ2eBvROYf8AvhfXkrxWnHPOOTJHL4ZDD9X/f7NvAj1L+D0deeSRxZifi2se+0VUF58QGGOMMcYbAmOMMcZUaMjg5ptvFp3bTtJe9C9/+YvoTp06ieaxDktgHDL4FLYR5hEYy4PyUSDLkGhPyvIehnpojdq6dWvR+ffK6xw8eLBothiuCr7e9u3bizHLJfNcRGkIgEeS/B4YWnnooYeKMY9OlyxZIpptnGsD2So8IuLWW28VzfbTixYtKsYPPPCAzGXL6YhSC2uWiLJscdSoUaJZ+nowwTAaSwGzfXBExMyZM4sxWwrz39J6fMGCBaJ5lM624LkEj23Ux44dK5oljnxtrkMsSc5rCVu08xif4Qke6zdo0EA0yxRzuPGdd96ROYYP58yZE/uCTwiMMcYY4w2BMcYYY7whMMYYY0xUSA5B3759Rd9www2icyz7+9//vszdf//9omllyXhVtqWNKC1VOphhu2OW/vXq1Ut0/fr1i/Htt98uc4yP0fKXJWAsRWLuR44zMo+E78XyPJZI0c6UpYH5e2Ac8PXXXxdNO1PGNG+88UbRLHnM84x5n3zyyaLffPPNqG08/vjjZfX+hPkeLGe79957RR/MOQTMzWIMm/dmLplleR3zQLINeYSuI7vTtJPPz8Ebb7xR7Z+NKH0++TwzpyCvSzfddJPMMWelqlbMOf8lojRfIa9xzHXjeklL9OriEwJjjDHGeENgjDHGGG8IjDHGGBMVkkPA+uqWLVuKvueee4oxcwYIrYoJ62fNpzDOz1je9OnT9/jzuU1oRKkFaFX1+5dccoloWqdmPwDG/Dt37iyaccA777xT9COPPCKaHgi5jpq2x3Xr1hV99913i2ZOyquvviqatcvz5s0rxqyTZz4M582Bgy21aWH9xBNP/C8vZ79zzDHHiG7SpIlo+m1kLw/mbe3YsUM05/mM9e7dWzRzm1auXFmM+YzQXpj5CmxnznbI/Pl87fzbwnVnxowZopkzwOeXuU75O2eeE/My6BFTXXxCYIwxxhhvCIwxxhjjDYExxhhjokJyCOg9zxjwww8/vMd/y1pheuZn3+uIiEmTJu3LJR4UvPXWW6JZ7//JJ5+IzrWxzBlgrJytlBmPY0yMvQzyzzOmyNgdvQM4/9RTT4lmvC63YmYsmJ4ZI0eOFM3aYuYUMMaZ44asLWa+y7Zt28J8PsitaiNKY+6VzgUXXCCaniRcG/KazVj5rl27RDN/iPlHzOlhzlD2PGB9fs7JiYho1KiRaP6e2K6cbYdzzlC/fv1kjusK8xPo1cBeMHze83fKvAteJ/MsqotPCIwxxhjjDYExxhhjvCEwxhhjTFRIDkGO2UZojCgi4je/+U0xZu/sbt26iWYsuzb6v9cUp556qmjWGjMGlnt2M5bHGtzNmzeLZo4A+5a3atVK9Ny5c4txp06dZI75COxXwX4D2dMgovRz52sdPXq0zP3xj38UTX9z9ls/6aSTRDMPI+cJMLbatm3bsq9tTE3BfBXGsLkOt2vXrhjzPqUHCXMKGGunT0iHDh1E578X7HnC62zQoIFo9ghgbsScOXNEjxkzphgzD4qeBfRSyWtWRESzZs1El+vDkNfWiNJ+EPzc1cUnBMYYY4zxhsAYY4wx3hAYY4wxJiokh4B9yO+66y7R2TOa/tGMT9EDf9CgQaIZmzGfQs+Gquazd8Brr71W9mfZn4KeBy+99JLoE044QfTq1auLMWuFmTdC3bFjR9GMEz733HOic40vY/70uVi7dq1o3l/0EmBvgxw3ZD4M47TOh6lZhg4dKvp3v/tdMWbsubbDnB/CuH/OC2AOGD0b+KzTd4b/nrlMOV+BcwMHDhTNz7F8+XLRuW9JRMTgwYNF//rXvy7GzE3iszxt2jTR9C3Ia1hEab5DXiu6d+8uc+vWrRPNfIbq4hMCY4wxxnhDYIwxxhhvCIwxxhgTFZJDMG7cONGTJ08W3b59+z3+W8aI2GPaVB/W5PK7Zb1/9g5g74INGzaIZs0uY3fMBRk+fLjoiy66qBjT84C96elXvmnTJtHZnzwiokuXLqKzHzrzFerXry+avQrYN54wRrl06dJi/MEHH8gc+8T379+/7Gubz8af//xn0fmeZA+UlStXiqaHfqXDmvm//vWvonv27Ck65wHQV6aqPiVTp04V3adPH9Fc0/PvhblGzE06/PDDRfP5fPfdd0VPnz5d9HHHHVeMGcfv1auXaPqZsB8B17yFCxfGnmDuEddT5hhUF58QGGOMMcYbAmOMMcZUSMiAbN26VTTbX5qagceg+bgsojR007Rp02LMo7aLL75YNMtkWBrI1qEs78v3BI/5WHrE1yY8Rpw1a9Ye35utXHkcys+1ZMkS0c2bNxddrv1qLkGMiBgyZIhoWhubmuXJJ58sxiyNq+3QXpihsldeeUV0Drt9+OGHMsdSXIYP2Qa4TZs2ovPvIUJLmBkOZAiBawHtglesWCGaNsk5TMrySR7583PMnz9fNNcSrpEPPvhgMc6llRGlLdr5+6kuPiEwxhhjjDcExhhjjPGGwBhjjDFRoTkE5sDAuH1VrXuXLVtWjE888USZY/yMbUgZ92eJDkses93phRdeKHMswZkxY4Zoxu137twpmm2Gc2tRfi7Ca2G5EEsJGfNs0aJFMWZZJ2OSLM00pqbg88jcmXr16onOzzNzwJh/wDbqzLNh+2SW9+U8AeYD0RaZltPMX+DawBLJnK9E+3Xa5J977rmiuV7S3p0tpvNaQjv/YcOGiV6/fn3sCz4hMMYYY4w3BMYYY4zxhsAYY4wx4RwCsxfQd4A1vSNGjBCdLYOZI0A7YLYJZjw8WxNHlMYZs8Vv48aNZW7KlCmi2ZqV7Y9pw8oa3/y5mevAmCTzLFiDzbyMiRMnis5xRvpADBgwQDQtXo2pKWjJTWty2g/nVsDMfeF9zZyBNWvWiGa9fsOGDUXfd999xZjPCK2J+fwSrjtsUZzr/f/2t7/JHPOHZs+eLZq25/RxyblKfO9sC787qmpPvSd8QmCMMcYYbwiMMcYY4w2BMcYYYyLikF37anpsjDHGmFqDTwiMMcYY4w2BMcYYY7whMMYYY0x4Q2CMMcaY8IbAGGOMMeENgTHGGGPCGwJjjDHGhDcExhhjjAlvCIwxxhgTEf8Ht8Ovc7S5EZQAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -1846,7 +1855,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1856,7 +1865,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1871,12 +1880,16 @@ "# Let's visualise MNIST images with noise:\n", "def show(index):\n", " plt.subplot(1,4,1)\n", + " plt.axis('off')\n", " plt.imshow(train_dataset[index][0][0], cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,2)\n", + " plt.axis('off')\n", " plt.imshow(add_noise(train_dataset[index][0][0]), cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,3)\n", + " plt.axis('off')\n", " plt.imshow(train_dataset[index+1][0][0], cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,4)\n", + " plt.axis('off')\n", " plt.imshow(add_noise(train_dataset[index+1][0][0]), cmap=plt.get_cmap('gray'))\n", " plt.show()\n", "\n", @@ -1897,7 +1910,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 79, "metadata": {}, "outputs": [], "source": [ @@ -2038,7 +2051,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 80, "metadata": {}, "outputs": [], "source": [ @@ -2094,7 +2107,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 81, "metadata": {}, "outputs": [], "source": [ @@ -2137,13 +2150,13 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 82, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ec1658b2fc3849c98f19d6f34d78de55", + "model_id": "3db4666b78254ce5aa41defd2c5e4e4b", "version_major": 2, "version_minor": 0 }, @@ -2157,7 +2170,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "89fb644327594641a5bfe7252d81beb3", + "model_id": "065f078366d84b708fb364ec01c498a2", "version_major": 2, "version_minor": 0 }, @@ -2171,7 +2184,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3fe80be2190042a2a6944fb422f64e62", + "model_id": "ca571ab5e3ad47b98cb9474236b430eb", "version_major": 2, "version_minor": 0 }, @@ -2185,7 +2198,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e8fd8fe534c04f90bead7fc2764da9d5", + "model_id": "6bc443cf43aa404c9a54e8f7e254807c", "version_major": 2, "version_minor": 0 }, @@ -2199,7 +2212,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "573b36e3683a4f518c181e897757a453", + "model_id": "af3d7394cf2b4960ac1d2cc2d3d6e069", "version_major": 2, "version_minor": 0 }, @@ -2227,7 +2240,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 83, "metadata": {}, "outputs": [ { @@ -2236,13 +2249,13 @@ "Text(0, 0.5, 'mean squared error loss')" ] }, - "execution_count": 38, + "execution_count": 83, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2272,7 +2285,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 84, "metadata": {}, "outputs": [], "source": [ @@ -2286,12 +2299,12 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 85, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2301,7 +2314,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZ0AAACbCAYAAAC58UYLAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAhnUlEQVR4nO2de1BV1/XHFxhAIw+fgKj4iBp8pBpRkfhMYsVHGzXmYTppTB9GEzQ1ZkbHmVardUJtG+u01dhpE62JxsRETTVKavGdigrVKBpNfAWsgq8IPkHg/P7IcH57fS/c65V7Dxf8fmaY2V/2ueceDgv2PWvttVaQZVmWEEIIIQ4QXNMXQAgh5N6Biw4hhBDH4KJDCCHEMbjoEEIIcQwuOoQQQhyDiw4hhBDH4KJDCCHEMbjoEEIIcQwuOoQQQhyDiw4hhBDH8Nuis2jRImnbtq3Ur19fkpKSZO/evf56KxKg0AaICO2AaIL8UXvtgw8+kBdeeEGWLFkiSUlJsnDhQlm9erUcO3ZMoqOj3b62vLxczp49KxERERIUFOTrSyM+xrIsuXr1qsTFxUlw8P9/hqmODYjQDmob/rAD2kDtoiobqOxAn9OnTx8rNTXV1mVlZVZcXJyVlpbm8bV5eXmWiPCrln3l5eX5zAZoB7X3y5d2QBuonV9oA8h94mNKSkokOztbZs6caX8vODhYhgwZIrt373Y5vri4WIqLi21tseh1rSQiIsIee2sDIlXbQWpqqoSFhYmIyM2bN9VrevXqpfTx48ftcWlpqZoLDw9X+syZM0ofOXJE6YcffljpkJAQpfPy8uxx79691dw333yjdEZGhtLPPPOM0ps3b1a6c+fOSjdu3Ngef/vtt2ouJiZG6Rs3bih98uRJpZs1a6Z0UVGR0qGhofa4S5cuaq5///5K79ixwx7funVLfvvb31bLDqqygfvuu89+0gnU/w++vi48ny+f9PBc7s7t6X3NvzPLssSyLGUDleHzRefixYtSVlbm8scQExMjR48edTk+LS1N5syZ4+vLIA5jGqe3NiBStR2EhYXZi055ebmau//++5WuX7++Pb59+3aVcyL6n6vId//Y8H1NcNExdYMGDdy+tl69em6vBd8br808n7s5EZGysjK3142vdzeP14kLN86LVM8OqrKBoKCge969FqiLDs5bluXxNTW+e23mzJlSWFhof5mfIMm9A+2A0AbuDXz+pNOsWTOpV6+eFBQUqO8XFBRIbGysy/HmJ1lSN/DWBkSqtoOcnBz70zi609LT05XOzs62x4MGDVJz+Mn62rVrSqekpCidmZmpNLr2WrVqZY/RVXflyhWlx40bp/Tp06eVxieI3Nxcpc2gLB578eJFpdu3b6/0Aw88oPRHH32kdLdu3ZQ23V7oykO3Ybt27ewxPq2J+O5/QXl5eZWfnt19qvbk8qrsU7ovj3d3rLfuOPN4b55U7uZazPN5cvOZtmlZlos3ojJ8/qQTGhoqiYmJyo9dXl4uGRkZkpyc7Ou3IwEIbYCI0A5I5fj8SUdEZNq0aTJ+/Hjp1auX9OnTRxYuXCjXr1+Xn/zkJ/54OxKA0AaICO2AuOKXRefZZ5+VCxcuyKxZsyQ/P1969Ogh6enpLgFFUnehDRAR2gFxxS/JodWhqKhIoqKiavoyagSMO3Tq1MkemzEEEZGzZ886ck13SmFhoURGRvrsfBV2MH/+fHuX1KlTp9QxuBOrefPm9njjxo1qLikpSemWLVsqvWbNGqUxuW3gwIFKm9uz8XeD8aCePXsqjf9w9+/frzTGrs6fP2+PO3bs6PZcGE9CfeHCBaUPHjyotOmzx3uwa9cupX/0ox/Z4+LiYlm8eLFP7aDCBswt0/7E223K5vHVea2I6w5H3FVoHo/pAJ7iKE5tv7YsS0pLSz3aQI3vXiOEEHLvwEWHEEKIY3DRIYQQ4hh+2UhAKqdFixZKz507V2n010+fPt0enzt3zn8XFsAcOXLEjt2MHDlSzX366adKt27d2h6jTxn1gQMHlMa4jFmORURk3759Sk+ePNkeb9u2Tc2NGDFCacylwbweLDdjxotEvisxU8Hly5fVnJkrIyKyYcMGpbt27ao05scMGzZMaTNP55FHHlFzo0aNUvrSpUuVXqOvcZej4st4hbdxGHfxL0+5NBiLw9JHZhxPROTEiRP2GGM61Y3R+Cr/6E5fxycdQgghjsFFhxBCiGPQveZHcEvv1q1blTa3RFfG22+/bY8DbGe7Y1y6dMnePopuLHQtmVWQzQrIIuJS+Ra3maJu0qSJ2/mdO3fa47Zt26o50xUi4uoanThxotIdOnRQGl1577//vj3Grd64jbxNmzZKe6pCbf4cIiJ9+/a1x+gGxNJBZrkeLLBaF3HnxsItz2gv+Dv+/e9/r3T37t2VXrJkidILFiyo8jq8LbFTHXeap3PdCXzSIYQQ4hhcdAghhDgGFx1CCCGOwZiOH8Et0RjDwRIlo0ePVrqwsNAfl1WriI+Pt8vdY3mkv//970p/+OGH9hi7eTZs2FBpbAFw9epVpbFB3EMPPaS02TJg06ZNag63GqN/H1sXYJmcPXv2KG3GZTBWNWXKFKUxDoOtC44dO6Z0o0aNlDZbC+B1Y4zy6aeftsc3btyQf/7zn+IPgoODq+wc6k1MobotACq7rqqOxQ6tr7/+utLYhRXjfngvr1+/bo+xRA5u1/YU4/H0c7nbou4L+KRDCCHEMbjoEEIIcQwuOoQQQhyDMR0fMnToUKWfeuoppTGGM3z4cKXRl09EGjdubLc2wHjE7Nmzlf7f//5nj7GEP7Za/vjjj5X+zW9+ozSW/Mf3NkvVDBgwQM2ZbbNFRGbMmKH0kSNHlJ43b57S69evV9psBT1hwgQ1t2XLFqWxnXV0dLTSaGOYX2LGEQ8fPqzmEhISlDbjP2VlZeIvvCm14sv21d6A8a4+ffoojSWcsDXJpEmTlMYyTaYN+LvNg7vz++K9+aRDCCHEMbjoEEIIcQwuOoQQQhyDMZ1qgK0KsF5SfHy80s8++6zSjOF4Jjw83I7pvPfee2oO632Z9dKwdlqPHj2UxljHv/71L7fXkZ+fr7QZM8I240OGDFEa21fPnz9faayPNmbMGKW/+OILe4w/F+YTYT26rKwspbGFgxkrENE2izFIvIdmm21sBeEvfFWG/27O5W4e7emnP/2p0phzh7XX/vOf/yiNvxd/xll8eQ/vBD7pEEIIcQwuOoQQQhyDiw4hhBDHYEynGixdulRp7KuCvnvMDSGeycnJsXMgVq1apeaKioqUNv3iFXGgCjDP5uTJk0pjfAjzLh5++GGl//vf/9rjJ598Us1hbSzsQ4N+cfT3FxQUKG32wDHjOyKucRczziLiGuMxc5lEXPNrzHtqtqMWcc11aty4sT2uqXbV3uDptTiPtecQM56GOXlYfw9jhunp6Up7ipVUJ//I2+O9ud9sV00IISSg4aJDCCHEMbjoEEIIcQzGdLzErK+WnJys5tCv/Y9//MORa6rLtGzZ0q7xdeLECTUXFxentJk3df78eTWH/XLM/iQiIiUlJUoPGzZMaexvYtbNw1jd+PHjlc7JyVH6F7/4hdIYp8FYgtnzJjY2Vs09+OCDSn/00UdKo58d42BmvEhEZNSoUfYY848w56dfv372GO9fIOJtHg7GMxo0aKD0448/bo9ffPFFNYf3ecWKFUpjnM9TDMfsmeOpfw7G6TzFpqoD83QIIYQENF4vOjt27JAf/vCHEhcXJ0FBQbJu3To1b1mWzJo1S1q0aCENGjSQIUOGyNdff+2r6yW1ANpA3efSpUuybNkymTdvnsyYMUO+/PJLNU8bIFXh9aJz/fp16d69uyxatKjS+d/97nfypz/9SZYsWSJ79uyRhg0bSkpKil+3VJLAgjZQ9yktLZUWLVq4tFivgDZAqsLrmM7w4cNd+sBUYFmWLFy4UH75y1/avuHly5dLTEyMrFu3TsaNG1e9q60BzFwEEZG3337bHkdERKg59NWjT9xbzF4nmDdSWlqqNOaZ1BS+toHS0lL7PmCPmx07diht1g3bt2+fmuvWrZvSmEeRm5ur9Jtvvql0ly5dlDZzVnAO62ahT/3y5ctKYz4MXsvYsWPt8SeffKLmBg0apDT6+/v376805ulgbMHs84K5Sc2bN1f6gQceEBGRd999V/2d+NoGgoKCqowduIuFVLfWGt5LjCGaPXCwft5f/vIXpXfv3q00/v3ie2Gul3nvcQ7jchhPunnzptIY8/EmLuPuHtZIns6pU6ckPz9fFTyMioqSpKQkl5teQXFxsRQVFakvUnu5GxsQoR3UJWgDxB0+XXQqKvHiqh8TE+NSpbeCtLQ0iYqKsr9at27ty0siDnM3NiBCO6hL0AaIO2p8y/TMmTNl2rRpti4qKgooY5s+fbrSLVu2tMdYcmTlypXVei8sd56UlGSP0U2CgduJEycqvWvXrmpdi9PciR18++23SicmJiptthvA16L74oMPPlAaXUkzZ85UeuDAgUqb7s5t27apuc8//1xp3L6NpWuwBQa658yyOBhDQRcu2gmW+zl06JDb480W1LhFGEu5NGzY0B7v3LlTqosv/he4c/F4606LjIxUOjU1VWlzy/Rnn32m5jDmjaWOsE04tqj4/ve/r/Sjjz5qjzEuhmWTcAs+bnXHJ0h0/7pzUXpbcqcyfPqkU5FDgDehoKDAJb+ggrCwMImMjFRfpPZyNzYgQjuoS9AGiDt8uui0a9dOYmNjJSMjw/5eUVGR7NmzxyWRktRNaAOENkDc4bV77dq1a3L8+HFbnzp1Sg4cOCBNmjSR+Ph4mTp1qsybN086duwo7dq1k1/96lcSFxdX5dZKUjc4ePCgxMfH0wbuEcrKylSVhwqXT15ennTt2pU2QKrE60UnKytL+RcrfLDjx4+XZcuWyfTp0+X69evy0ksvyZUrV6R///6Snp7uUmq+tvD0009XOYdxFNz66gn0g5tlRRDcqti5c2elsT2u0zGdAQMG+MUGzp07Z8dPsD043r8nnnjCHmM5GGzTnJKSovTmzZuVxljJxYsXlTbLvqA/v2fPnkpj/A23y06ZMkVpsxSNiI4voc2hC8qMs4iIvP/++0p36NBBaWxXYMYWOnXqpOaef/55e/zVV1/JwoULbV3xQfSNN96QFStW+NQGysvLbfv3puS/J9yVmhFx/fkxrmduikhLS1NzZnzxTsCyS3PmzFHajMN89dVXai48PFxpjAmi/eE2edxC7W+8XnQGDx7sNpgUFBQkc+fOlblz51brwkjtorCw0P4HSBuo+3Tq1Elee+01WxcXF8vixYvlrbfeEhHaAKka1l4jhBDiGFx0CCGEOEaN5+kEOr7Yl14B5uG4i+GI6LyUkSNHqrlXX31VaSynj3kC2dnZd3ydgURwcLCLr70CzHcx4y4///nP1Rz6tbF0zUMPPaQ0ljw5fPiw0s8995w9xvI82CIay5DgtmFsc37gwAGlzRIzf/vb39QcxmgqStNU0KxZM7fvjdfepEkTe7xx40Y1h6WWiouL7XFNtTbwVOrG3RzalZmjJCKqooKIa+6XaW9YXgivC/NyMD5pltQR+a6Cg4nZJgVjiJi3g++FZXIQb8sDuXvtncAnHUIIIY7BRYcQQohjcNEhhBDiGIzpAOhfR5/4qVOn7DH63hH0rZq11Cpj+/btSptbUvG9MMbjy/yFQCIhIcHO7diyZYuaw/pUZlzmvffeU3MY+8Daa02bNlXazEkREZf8ErOWVkJCgprDWlZnzpxRGnNrMK7SsWNHpc04S9euXdXckSNHlMZYAOZkYP061OZ7Yc4P5oaZcTIzvuNPqtOuAI/F3xPGdPBvH/NfzJgQzqG94P8CrPXXpk0bpTEXx4zjYA6ZpxhMddpXe7q/Nd7agBBCCHEHFx1CCCGOwUWHEEKIYzCmA6B/Hn3kx44ds8dYQwvBFtPYuwT9pWYMR8R9zKhHjx5Knz59WmmME9RWli9fbvvD0Q/eqFEjpc1+L+ifR5879uLBvJ2tW7cqjb87059vFr4Uce2f0717d6Xbt2+v9Ndff620u5wPtAmM8aDGnA6sH4b5Iqb/H1t6Yz6I2dran+3SzZ+/qpwtb88j4rmnDeZXYdzKXRwL/7axNxH+n0F7xb5HZiwZ43T4Wk+xK0/4Ox7MJx1CCCGOwUWHEEKIY3DRIYQQ4hiM6QBYbwnBPi3VAXu4uIvDYExh6NChSmOttZqqheVrJk6caPvDsRaY2UxQROe/YP8cjEegXxz75Zg+dBHX3irm+dC3j+f+97//rfTkyZOV/t73vqe02adFROd87NmzR81FR0crjX2UevXqpbSZXyTimudj2v+bb76p5rCenRlXvHXrlk//NvyBp5wTjNFevnxZaYzxnDx50h5jHUBPsSfMxULQBsxYG54bYzaeYjLe1FbzdCxrrxFCCAlouOgQQghxDC46hBBCHIMxHS/Jzc312bmwFpvZN0VE98GYNWuWmsOaWUuWLPHZdQUShYWFdsxk7Nixam7Tpk1Km3kWOTk5ag7zV7AeGvbPefzxx5XGXAizTt7+/fvVHOZQYZ28YcOGKf3ggw8q/corryht9sjBXj1YHw3zizC3CXurYI0wM+cIY00ffvih0i1btrTH/owhBgUF+SR3xFOeDv4MGOfD2J2Zm4Q5PuHh4UpjL56+ffu6PR7zysycP7RFjEVhjMdTfMmXPcPuBD7pEEIIcQwuOoQQQhyD7jUA3TL46Dp9+nR7vG7dOjWHj+f4OI6tCwYNGqT0Cy+8oLT5SI5buRcsWKA0lkKvK9SvX992AWFpENz++9hjj9ljdHHt3btXaXSt4P3DUvPo0vjxj39sj5s3b67msAVD7969ld63b5/SWBIFWwiYZXWwxTm24TZbE4iIrFmzRuk+ffoojVvxzW376OLp1q2b0qYbx5+tDXzlXkPQrYSlfNAmcBu9Wc7o0UcfVXNmiSA8VsR1+zVqtDfz9bidGrd2Y3qA0+4zT/BJhxBCiGNw0SGEEOIYXHQIIYQ4RpAVYA6/oqIil3YCNQmWnTe3r86ZM0fN/eEPf1D6+vXrSg8fPlzptWvXKo2tENwxY8YMpTFmgXED3CrrawoLC13aMFeHCjto3769veUTY15YdmX27Nn2GEu44L3HGATGzN555x2lcWtyXl6ePU5JSVFz+HvMzMxUGlsyoI/+j3/8o9Lp6en2OCYmRs19/PHHSuP22EuXLim9c+dOpV9++WWlzbI6GMPAlg3mduuSkhJZtmyZT+2gwgbq1atXZUzHU/tqd3MY1wsJCVEaUxiw9YhpU/g7xL9HjA1j3C42NlbpCxcuKG2WP8JY0+7du5XGrd64hdpdy2lvMe+pZVlSWlrq0Qb4pEMIIcQxvFp00tLSpHfv3hIRESHR0dEyevRo1dRM5LudE6mpqdK0aVMJDw+XsWPHSkFBgU8vmgQe+ERIO6jbHDp0SNauXStLly6V5cuXS0ZGhssxtAFSGV4tOtu3b5fU1FTJzMyUzZs3y+3bt2Xo0KHKjfTaa6/J+vXrZfXq1bJ9+3Y5e/asPPnkkz6/cBJYjBkzhnZwD1FQUCBdunSRUaNGyciRI20XDW2AeKJaMZ0LFy5IdHS0bN++XQYOHCiFhYXSvHlzWblypTz11FMiInL06FHp3Lmz7N6926X0Q2UEWkznrbfeUnrChAn2GP3npp9fxDWHAsEyI5jv4a60COaoYAxjw4YNSuMTqT/whx0899xzdowEWwQ8//zzSptxF/zkjSX+i4qKlEb/Pn4ix3+WZg4LtjLAfKxRo0Ypjb9XfK+jR48qbZbJiY+PV3OY35GVlaU0lmfBHKLBgwcrbbbtxp8Dr9tsnV1cXCzHjx+XjRs3yvDhw31qA8HBwXbsoDr5Ovhab2M8ycnJSk+bNs0ed+jQQc1h/AtznjCuh9eCcRozRov/V/BvG+NBZlsEkVoe06n4x1eRkJadnS23b99WQdmEhASJj493uYkVFBcXS1FRkfoitRPawb1LRbC6IvhOGyBVcdeLTnl5uUydOlX69etnZyrn5+dLaGioyyoeExPjsrujgrS0NImKirK/sDAeqR307duXdnCPYlmW/bRW8aREGyBVcdeLTmpqquTk5MiqVauqdQEzZ86UwsJC+wtdVKR2gFuMvYV2UHs5d+6cT8rg0AbuDe6q9trkyZNlw4YNsmPHDtUWODY2VkpKSuTKlSvqE05BQYHLPvQKwsLCXOoMBRKYx3D48GF7/Otf/1rN4SczT5/U0M3wzDPPKI2thwMZs8y9L+2gbdu2dj4Ixh/wXCtWrLDHr776qpr74osvlMbYCMYrsHXEX//6V6XN2mxYd+sHP/iB2+vET/9Yp8u8lyI6loW5I++++67S2MYc83SwBhjOm/kgeN3YHrxXr16SmZkpxcXFMnz4cFm/fr16baD9L/AUy0CNsRBsYWG2E3niiSfUHLarwJ8Z40XZ2dlKY+zNjOmgvWAOHl53dfBHzTuvnnQsy5LJkyfL2rVrZcuWLS69PRITEyUkJEQFcY8dOya5ubkuQThSd6Ed1H0sy5LMzEzJzc2VlJQUl34wtAFSFV496aSmpsrKlSvlk08+kYiICNs3GxUVJQ0aNJCoqCj52c9+JtOmTZMmTZpIZGSkTJkyRZKTk+9otwqpvRQUFEhISAjt4B5h//79kpubK4899piEhITYu+hu3rwpkZGRtAFSJV4tOhXbh9HNsXTpUnnxxRdF5LsSHsHBwTJ27FgpLi6WlJQUWbx4sU8ulgQunTp1oh3cQ5w4cUJERD777DP1/TVr1tguadoAqQzWXiM+wV+119544w07poP5CJiDYu6Katu2rZrD3BfscYM5GlivCnuWYN0xE6y516JFC6UxQI55OphTZPZ4Qn89tuH2lDtm1lYTcc33Mvvx4M+MmE8sN27ckAkTJgR07TVvwXNhro2ZF4buxWbNmimNOXhYiw3r3GGujZmPhbbpCU/3xJslwF2uk2VZcvv2bdZeI4QQEjhw0SGEEOIYXHQIIYQ4xl3l6RDiFMXFxbbf2MyREnH1o/fr188eY94E1hHD+lXog8aaZphXYfr30T+PNfWwDh7GgDAuY9Y0ExHp2bOnPT548KCaw1yvkSNHKh0REaE0VgMfN26c0gsWLKhyDuv7mffAF8mhd4OnGIM3eDoef89m7A7r72EujaeeNt5cm6cacr6M4Xh6ranv9Lx80iGEEOIYXHQIIYQ4BhcdQgghjsGYDglo4uLipEGDBiLimnuDPvaTJ0/aY8zp2bRpk9JYCwvjQ1gJOSEhQemFCxfa4/nz57t9L3wt+vsxToN5OuY8xoPwWDw31v/DnKDXX39daTN2lZ6erubM2JKIyOnTp+3x7du3pSbA+IUv0w49ncv8XWB+FF4XznuK8XgTp/H2Hvgz5nMn8EmHEEKIY3DRIYQQ4hh0r5GA5siRI3a5e2wBjGX6Dx06ZI/RXYZborH0PJaDwaKU6NYaMGCAPcaS99ieGrdr48+BVZfxvUwXGLZPx5L4eC5shYBbqLHl9zfffGOP+/fvr+Z27NihtNnS4ebNmy5bw/2BP91pns7t7r2qW5rGG3eaL9tNV4Y3pYTMn5tbpgkhhAQcXHQIIYQ4BhcdQgghjsGYDgloBgwYYLcw6NChg5rbu3ev0uY8lvA3t/dWNo/trJEzZ84oHRoaao+xfQBuH8b20wiWsUdttsrG2AFuxcVt5FjuB4+PiYlR2mwXja/FVtJm/MefZXCCg4P90jbZ263F1Wmj4M+WC9XdIu1N/Agx7cmyrDuKbfFJhxBCiGNw0SGEEOIYXHQIIYQ4BmM6JKA5efKkXQYHS/5jWZw9e/bYYyzhP2bMGKU//fRTpTHG06NHD6Xj4uKUPn78uD1u06ZN5RdfBVgGH9sTDB48WOnPP//cHmMr906dOimN9wj99UVFRUpnZmYqbbZNTkxMVHNZWVlKjxgxwh7funVL/IUZV/A2H8bEUywE413urgO1p9d6OhdSnXwkT3k83pzbm5jOncInHUIIIY7BRYcQQohjBJx7zd8VTol/8PXvreJ8ptsGy8OgS8fcqoxbh90dW9m5b9y4oTR2EjW3CHvrWsLtxXit7ubxuvFYnEdXiqf3Ml+PP5e7e1ox9keV57vpTunN+e/03NVxQzl5vJOVtiv73Xh0HVoB9l/+zJkzLuXYSeCTl5cnrVq18tn5aAe1E1/aAW2gduLJBgJu0SkvL5ezZ8+KZVkSHx8veXl5LsUaSeUUFRVJ69atHb1nlmXJ1atXJS4u7q6CilVBO7h76ood0AbunkC2gYBzrwUHB0urVq3sXTaRkZE0NC9x+p7hjipfQDuoPrXdDmgD1ScQbYAbCQghhDgGFx1CCCGOEbCLTlhYmMyePdulyCCpmrp4z+riz+Rv6to9q2s/jxME8j0LuI0EhBBC6i4B+6RDCCGk7sFFhxBCiGNw0SGEEOIYXHQIIYQ4RsAuOosWLZK2bdtK/fr1JSkpyaU18b1MWlqa9O7dWyIiIiQ6OlpGjx4tx44dU8fcunVLUlNTpWnTphIeHi5jx46VgoKCGrriu4M2UDX3ig2I0A6qotbagBWArFq1ygoNDbXeeecd6/Dhw9aECROsRo0aWQUFBTV9aQFBSkqKtXTpUisnJ8c6cOCANWLECCs+Pt66du2afcykSZOs1q1bWxkZGVZWVpbVt29f65FHHqnBq/YO2oB77gUbsCzagTtqqw0E5KLTp08fKzU11dZlZWVWXFyclZaWVoNXFbicP3/eEhFr+/btlmVZ1pUrV6yQkBBr9erV9jFffvmlJSLW7t27a+oyvYI24B110QYsi3bgDbXFBgLOvVZSUiLZ2dkyZMgQ+3vBwcEyZMgQlw6L5DsKCwtFRKRJkyYiIpKdnS23b99W9zAhIUHi4+NrxT2kDXhPXbMBEdqBt9QWGwi4RefixYtSVlYmMTEx6vsxMTGSn59fQ1cVuJSXl8vUqVOlX79+0q1bNxERyc/Pl9DQUGnUqJE6trbcQ9qAd9RFGxChHXhDbbKBgKsyTbwjNTVVcnJyZNeuXTV9KaSGoA2Q2mQDAfek06xZM6lXr57LDouCggKJjY2toasKTCZPniwbNmyQrVu3qqZJsbGxUlJSIleuXFHH15Z7SBu4c+qqDYjQDu6U2mYDAbfohIaGSmJiomRkZNjfKy8vl4yMDElOTq7BKwscLMuSyZMny9q1a2XLli3Srl07NZ+YmCghISHqHh47dkxyc3NrxT2kDXimrtuACO3AE7XWBmpsC4MbVq1aZYWFhVnLli2zjhw5Yr300ktWo0aNrPz8/Jq+tIDg5ZdftqKioqxt27ZZ586ds79u3LhhHzNp0iQrPj7e2rJli5WVlWUlJydbycnJNXjV3kEbcM+9YAOWRTtwR221gYBcdCzLsv785z9b8fHxVmhoqNWnTx8rMzOzpi8pYBCRSr+WLl1qH3Pz5k3rlVdesRo3bmzdf//91pgxY6xz587V3EXfBbSBqrlXbMCyaAdVUVttgK0NCCGEOEbAxXQIIYTUXbjoEEIIcQwuOoQQQhyDiw4hhBDH4KJDCCHEMbjoEEIIcQwuOoQQQhyDiw4hhBDH4KJDCCHEMbjoEEIIcQwuOoQQQhyDiw4hhBDH+D/YeG1aYv1EoAAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -2311,7 +2324,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZ0AAACbCAYAAAC58UYLAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAio0lEQVR4nO2de3BU9RXHT6B5ISEYHgkRIu+CPGuAQHkUmQhCBaFoQW0BtSIQnFKmQ8u00il9pKMzlsKg1JkCVYooBURQsBA0iIZ3AXlFQJRASIC2yUIISSS3f3Ry+zvfze6yye7N7ub7mcnM/ea3d/e3d0/2l3vO75wTZVmWJYQQQogDNGnoCRBCCGk8cNEhhBDiGFx0CCGEOAYXHUIIIY7BRYcQQohjcNEhhBDiGFx0CCGEOAYXHUIIIY7BRYcQQohjcNEhhBDiGEFbdJYvXy4dO3aUuLg4ycjIkP379wfrpUiIQhsgIrQDookKRu21t956S6ZNmyYrVqyQjIwMWbJkiaxfv17y8/Olbdu2Xs+trq6WwsJCSUhIkKioqEBPjQQYy7Lk+vXrkpqaKk2a/P9/mPrYgAjtINwIhh3QBsILTzZQ2wMDzqBBg6ysrCxb375920pNTbWys7N9nltQUGCJCH/C7KegoCBgNkA7CN+fQNoBbSA8f9AGkG9IgKmsrJRDhw7JwoUL7d81adJEMjMzJS8vz+3xFRUVUlFRYWuLRa/DkoSEBPvYXxsQ8WwHkyZNkujoaLfXEBFJTExUeteuXfbxqFGj1FhZWZnSMTExSu/YsUPpvn37Ko3/abdq1co+Pn36tBrr2LGj0ocPH1b6oYce8jhvEZF77rlH6W7dutnHx48f9zovPDcuLk7p2NhYpQsKCpS+ePGifZySkqLGzPcsInLt2jX7uKqqSt5999162YEnG4iLi7PfJ34/4Pv35/ujIe+efL0PJ/F2zfCOBed5+/Zt9TwVFRVuf6dIwBeda9euye3btyU5OVn9Pjk52e2PU0QkOztbfv3rXwd6GsRhTGP01wZEPNtBdHS0vUDgQoFfoE2bNvU4VlVVdcfn1vZa+Mdmnv+Nb+g/IzwXnxsXAjy/ZpGt7bVwDOfl6xqhxsebc/E2j9rGcT6B+i6Iiory+KVcny/rUHLZhdJcTHBevrSn35k0+O61hQsXSmlpqf2D/3mRxgHtgNAGGgcBv9Np3bq1NG3aVIqLi9Xvi4uL3W7XRf733xP+B0XCG39tQMSzHZSVlUllZaWIiFy9elWNme4dEX0HgTuk8L8v02Ul4u4imzFjhtInTpxQ2vxCjI+P9/papaWlSt+6dUvpfv36KY13ZeZ76dmzpxrzdUd27Ngxpbt06aL0v//9b6XbtWtnH+OXPt6htWjRwj6u+YxMAvVdUF1d7dG95s3946+r3knXvpOv5csF6W28urra62PN63+n7yngdzoxMTGSnp4uOTk59u+qq6slJydHhgwZEuiXIyEIbYCI0A5I7QT8TkdEZP78+TJ9+nQZMGCADBo0SJYsWSJlZWXy1FNPBePlSAhCGyAitAPiTlAWnSlTpsjVq1dl0aJFUlRUJP3795ft27e7BRRJ5EIbICK0A+JOUJJD64PL5XLbCktCn9LSUuXjry81dvDcc8/ZcYuzZ8+qx/Tv31/poqIi+zg/P1+NYczh6aefVnrbtm1KY6yjR48eSpvbonfu3KnG7r33XqXPnTvn9bkuXbqkNP5JmtukJ0yYoMYKCwuVxhhHnz59vD4ed86VlJTYxwcOHFBjvXr1UtqMPVVVVcnOnTsDagc1NmBumfaFPzEdf7ct+7M929dr+xtn8Qdf59bnK9/bc1uWJeXl5T5toMF3rxFCCGk8cNEhhBDiGFx0CCGEOEZQNhIQEijuueceOz/kww8/VGN33XWX0mYez8SJE9XY+fPnlT558qTSzZo1UzopKcnra125csU+7ty5sxpzuVxKo38b81a+/vprpTFG9MMf/tA+bt++vdd54TXCGA/GZbBET+vWre1jjJlhTpBZsLOiosJt3oHCnzItdX2eupxvvjbOA/NbfGk8H6tYmI+vb6yqPqWD8LGmbrA8HUIIIcQTXHQIIYQ4Bt1rfvLAAw/Yx2PGjFFj6OrIyspSGm9r16xZozQWO/ziiy/sY7wdbyx88cUXtlsnPT1djZkViUW0SwzdTJgXguVW7r77bqXxeuNWY7O6Lm6B7t27t9K4fRtL8GCZnOHDhyt948YN+3jz5s1qbOTIkUq3adNGaV8FQFu2bKm0eR3Mkjgi7i5Jc1t5bWVwGoJAFs705ZYyryW6WNFW0V2L7jMsw3Tw4EGl//Wvf9nH6I71RX23bwca3ukQQghxDC46hBBCHIOLDiGEEMdgTAfArbNm10MRkR//+Mf2McZwEG/bC0VEnnjiCa967dq19vG6devU2Hvvvef1tSMFs9w9xmX27t2rtBlbwTI2qLHD5pdffqn0fffdpzTGeMzYyfXr19UYdinFdgKffvqp0tOnT1f6gw8+UNpsbTB48GA1tmfPHqWxTYK5rVlEx4dE9NZvER1fwhYMuNXbjD2FSkynPvEIX438sK3Eww8/bB8PHTpUjaGtYlsI3CKN7SzefPNNpdevX28fm7He2s71tR0b8bbFOhjxHd7pEEIIcQwuOoQQQhyDiw4hhBDHaPQxnebNmyv96quvKo1xFm+gbxXzMzB/wxfma5sl50UaT0zn9OnTdvn9Vq1aqTH0uZs5Jpg3cfnyZaUxloHxCuxsiaVsLl686PFczB8aO3as0hiXwZbSGFccN26cfYxxlq5duyqN+UmdOnVSGq9h9+7dlTbjURgbwBI8Zt6Ov7kjdSWQeTgIxnSmTJmitFmOSESkQ4cOHp8LYyHYQiI6OlrphIQEpadNm6a0GU8yY70iIp988onSWIbJzCmrjfrk6dTl8+CdDiGEEMfgokMIIcQxuOgQQghxjEYf0/nud7+rtD8xnDNnzij9zDPPKH3kyBGlBw0a5PW10Ids5gE999xzagz963PmzFEaYxjhSnJysh27wVgJ8p///Mc+PnHihBrD+No3v/lNpfF6Pvroo0q/9tprSk+dOtU+fuONN9SY2WJBRGT16tVKY7wJfe5YT+3UqVP2MeaGoU89IyNDacwtwRwh85qJ6DgZxh2OHj2q9IMPPmgfV1ZWyscffyyhDF6r+Ph4pWfMmKH0vHnzlE5MTFTajHkVFBSoMdTYstxsISHinheG9jhixAj7GGNJmMOHrdexrQfaG8aygg3vdAghhDgGFx1CCCGOwUWHEEKIY0RZwW6e4Ccul8vNdxpIsAcO1jjy9dpmHMf0aYu4+3H9BeMIP//5z+3jb33rW17Pxf4b2K452DGe0tJSt1yW+lBjB08++aQdZ0Bf9saNG5U2r5GZRyPiHk/DelR4fTEmhPkwZt037GGDtbHQh469VTCHA3urmHXiMM8G/fVmrElEZMeOHUpjng/OHeOUJth7Z9SoUfZxeXm5zJw5M6B2UGMDsbGxdjzGV16It3HsJfT9739f6Z/97GdK47XGz/Grr76yjzGOcuDAAaUxzw6/Z/r06aO02bdLRGTgwIHiCYzLbdiwQenly5crjXUGMabjrVabt5wey7Lk1q1bPm2AdzqEEEIcg4sOIYQQx+CiQwghxDEaXZ7O5MmTlfYnhiMiMnr0aPu4vjEc5O9//7vSZl/0f/zjH2oM/a4DBgxQ+pVXXlF60qRJgZii41y6dMmOeXz22WdqDOuK5ebm2scYN8EeN1hzD58bYx3Yj8fMwXryySfVGPa4wX45u3btUhrjSVu2bFHazCnCvDL032NsoVevXkpj7A/rdJm9gXyFe80+P8HspxMVFWXHEvwJQWOeEcZNMKZj1u4Tcf8bw1jdypUr7WO0H3wszgXtC3OGbt68qbR5fbEuIM4bv+PMHkki7jEe83tGRMcYffXiYe01QgghIY3fi87u3btl/PjxkpqaKlFRUfLOO++occuyZNGiRdKuXTuJj4+XzMxMrztiSORBG4h8rl27Jlu2bJGVK1fKsmXL3HbR0QaIJ/xedMrKyqRfv35ut2g1vPjii7J06VJZsWKF7Nu3T+666y4ZM2aM21ZNErnQBiKfr7/+Wlq3bi3f+c53ah2nDRBP+B3TGTt2rFt/kBosy5IlS5bIL3/5S3nkkUdEROT111+X5ORkeeedd9xyCJzA7GMu4u5f98WyZcuUvnDhQr3ndKeYvVG+973vqTHMUUHfK75vfB+LFi1SGvf615VA20CzZs1sfzj2bLn//vuVNnMD8HpgrbXjx48rjX5w/M/90qVLSnfr1s0+/utf/6rGcJ6/+93vlH788ceVxl4qP/rRj5TeunWrfdy2bVs1Nn78eKUxlwTzjbD3D+aimLEGrPNm5nolJSWpx5aXl9vHDfk9YMYY4uLi1NiECROUxv5WmK+C1wp7bZmxOYyLYG8tjEVh3o55/UREioqKlDa/dzC+iAs/fm5YU+6f//yn0liPz3wv2LMKMW39TuNtAY3pnD9/XoqKiiQzM9P+XWJiomRkZEheXl6t51RUVIjL5VI/JHypiw2I0A4iCdoA8UZAF52a1Tk5OVn9Pjk52W3lriE7O1sSExPtH2/d+EjoUxcbEKEdRBK0AeKNBt8yvXDhQpk/f76tXS5XQI1t2LBhSmPJEeTQoUNKv/322wGbS33AbbRYMgdb2KJrAVsfrFmzRmmzbAe2KXYCT3YQHx9vu9dwe6bZLhnB9gBnz55VGl1guI0ZywYVFhYqPXz4cPsY3RXYAhpdfVjmZtWqVUqjC9h0A33wwQdqDF0ts2fPVhpL5qMdoRvR/Oxx0TDL8YjodhHYzqEu3Ml3gT+tlXHbfMeOHZXGUi24TRm3n7///vseH49bxtHNifPG1/r888+V9vY9hd9R2PbkscceU7pdu3ZKr1ixQumFCxcqbbbiCEYbhIDe6aSkpIiIuy+0uLjYHkNiY2OlRYsW6oeEL3WxARHaQSRBGyDeCOii06lTJ0lJSZGcnBz7dy6XS/bt2+eW0EQiE9oAoQ0Qb/jtXrtx44ZyVZw/f16OHDkiSUlJkpaWJvPmzZPf/va30q1bN+nUqZO88MILkpqa6lb1mEQWx44dk7S0NNpAI6Gqqkpu3Lhh65qt0AUFBdKrVy/aAPGI34vOwYMHVdntGh/s9OnTZfXq1bJgwQIpKyuTmTNnSklJiQwbNky2b9/uFmMIVbC8eSB81cFg8+bNSmMcwCzRIeK+jRK3SZrnY7znThg+fHhQbKBZs2b2tk2MMaSmpiptxqWwPTX63LOzs5XGx2MLYNyqfOzYMfsYYzjml3Ft5+L2WtzOjXEbM66BbYwxJvPiiy8qjaWC+vfvr/TLL7+s9ODBg+1jjJeYfwsul0vFpmrK5f/+97+Xv/3tb0H7HvBVdsVbjAe3MWPsEuMsvuJn5mvhvDCO52s7MZ6PsRQzBolpG0uXLlXaLGUkIjJ37lyl0cX50ksvKW2WccI22xhrqksZHL8XnZEjR3q9gFFRUbJ48WJZvHix35Mh4YvZQ4M2EPm0aNFCZs2aZevKykpZuXKlnctCGyCeYO01QgghjsFFhxBCiGM0eJ5OsMHcgkgF2yJguXPcm49gCfxQISEhwW4zfOXKFTVWUVGhtJk7g5nveD3QV425Cj169FAaS8+bPnf0c2NehNkGQcQ9BoRxDsyFMF8L84uwlhnmkixYsEBpTM7E+J3ZZgFjURjTMN93XXz7dQFd+6jNWApeK2xngXPGdgTYugTjNBh38UZ9r495rTE2ha0LXnvtNaUzMjKUNtuMi7jnK5nxXYz5YWy0Ljl9vNMhhBDiGFx0CCGEOAYXHUIIIY4R8TGdxgrWGvNF165dgzST+lFRUWH77dF33aVLF6XNDHjMRUhLS1N6586dSmN5eGxlYD63iKjy/JjLderUKaXT09OVxrL2mFeBWftmo0Qsgd+3b1+lfdUaxFL1WIvNjONgHAzbJJgxkmC2q/anRbX5WHzvGN/F2BnGSjBm46uemlNg62sE843eeustpbEGHf7tm7lamN+HcdS6wDsdQgghjsFFhxBCiGNw0SGEEOIYER/TQd+8L7CFrdkyOpzYv3+/0tieGd8ntsMOFQoKCmwfNvZWwTbRpq8aYzplZWVKYw8SzG/BNs54vhkbwRwe9JFfu3ZNacz3wHwYjLOY+SYDBw5UY2jfnTt3VhpjexgDGjBggNJm2/I//OEPaqx169ZKmzGSQPj6PREVFWXHT/zJ00F85ZTg+zNbkou4X0vztXzFnXDc33iQt8fjc+P73Lt3r9LY/wnft2m/vp67LvBOhxBCiGNw0SGEEOIYXHQIIYQ4RsTHdPwFe8xjX5VQ7a+DYAwCa3SFCzdu3LDzLbD2F+Yb3HffffYx1hgbPXq00llZWUpjn5l7771XafSpm3kp2B8H824wfnb58mWlMVaA+STm+0T/PNbNQp+7y+VSGvMuXn/9daWffvpp+xjzhbBPkPla/uTS+IuvViqeHovvHZ8H41B43TMzM5U2eyiJ6HbcgX7//sRwfPXywb99XzXjzPNr6h56em5/6s/Zz+H3GYQQQkgd4aJDCCHEMbjoEEIIcYyIj+n85je/URp7SWBdLOxXj779cInpYN0prDOFfPzxx8GcTp1p2bKlnaeDNaUef/xxpZcsWWIfP/DAA2rso48+UvrZZ59V+uDBg0pj/bSEhASlzV4rvnJHEDMWIOJeDw1zb8xaWxjXQp861kDDOl1m3EvEPQa0dOlSj+di3Tczv6guvv07xbyevvJbzHlgLTX8jDGfCuMVGNM5fPiw0mYOH+Zi+boevuIy3sb9zfHBPkJoAzhuxhjRPgIRu+KdDiGEEMfgokMIIcQxIt69hluHd+/erTS61xBs57to0SL7+O23367n7IKH2bpZRLchrg1s7xwqtGjRwnY/4ZZWLNluvkdsGY3bXd99912l0cWA24U/++wzpc2tx2brARF3l+z58+eVTk1NVRrdhtiGwWyjjPNEeza3PIuIHD16VOl9+/Ypja20n3rqKfv4vffeU2PYVtt8rmC61/zBdCOje+2NN95QGrePo0sWWzvgNntzK/umTZvUGLZDx+uDbitf7jV/to2juxbbdqB94ud68uRJ+xi3naMLku2qCSGEhDRcdAghhDgGFx1CCCGOEfExHeRPf/qT0g8//LDSWM4c9eLFi+3j8ePHq7H58+cr7eT2aiwJ88QTT/h1PpbTDxVu3rxp++bN2IaISFJSktKmPx+3PGNbBPS5Y2wPy/o/+uijSptzeeyxx9QYxn9wizRur8U4DcZ4zBgQjmGLBmwpPXToUKV/8IMfKI1tu83yQXh927dvr/RXX31lH5vtF0IFjOlgbG358uVKY9wF2z7gtvkJEybYxxhvXLlypdKnT59WGj9Hf7ZQ41Z2fG2M4cyZM0fpxMREpXGLvjl3LBWEMRx/2jvY59zRowghhJAA4Neik52dLQMHDpSEhARp27atTJw4UfLz89Vjbt26JVlZWdKqVStp3ry5TJ482e0/PRJ5nDlzRmnaQWSTm5srR44ckby8PNm3b5/b94AIbYDUjl+LTm5urmRlZcnevXtlx44dUlVVJaNHj1bbkn/yk5/Ili1bZP369ZKbmyuFhYUh25WSBI5JkybRDhoR58+fl3bt2knfvn2lV69etmuFNkB8EWXVo67B1atXpW3btpKbmysjRoyQ0tJSadOmjaxdu9b2gZ8+fVp69uwpeXl5MnjwYJ/P6XK53HyOwaRHjx5Kf/LJJ0q3bNnyjp8L/9s7dOiQ0ujnDSS/+MUvlMacAwTbM5tfBugLv1OCYQfjxo2zfdjoT8ay/mbehdl2WcQ9NwbzVR588EGl8c8C23+bbZ8xF8xXO2q0b4wV7NmzR+lmzZrZx+i/R5vDuMtDDz2kNJYDQv785z/bxwsWLFBjmLdjXv8bN27Itm3b5P3335exY8cG1AZiYmLsGAfGOnxpEywNhfkseO3Gjh2rNJbFMeOoWH7owoULSmM8CeeC8V+MAZn5Mr169VJjWNoLv9Mw3whbVLz88stKm3FvX/lEJpZlya1bt6S0tNTtb9OkXjGd0tJSEfl/wPHQoUNSVVWlPpwePXpIWlqax+TDiooKcblc6oeEJ7SDxkvNPyo1X3C0AeKJOi861dXVMm/ePBk6dKjdpKqoqEhiYmLc7g6Sk5PdmmrVkJ2dLYmJifYP7jIi4cHgwYNpB40Uy7LsHXs1xSRpA8QTdV50srKy5Pjx426dNf1l4cKFUlpaav+Y1XtJ+FBf1yHtIHw5fPhwQO5KaAONgzrl6cydO1e2bt0qu3fvVn7QlJQUqayslJKSEvUfTnFxsaSkpNT6XLGxsW4tUZ0EfaeY1/D8888rPW3aNPvY9LWLuLdFQO1v7kwgwb34L7zwgtJ1jePUYMYaAmkHHTp0sH9fWFioxjA3yawZhbXTDhw4oDT669HlEx8frzT6qM14HcbPsO7d1q1b73jeIiIlJSVKmzkd+FrYGhuvIY7j54x5OsOGDbOPzdL9Iu5xsXPnzsnZs2fl2rVr0rt3b1X6PxS/CzCXCON2X375pdJvvvmm0p9//rnSU6dOtY8HDRqkxu6//36lsR06thrBRRtjPGb8Ce8A8XsI4y4Y39ywYYPS+D691VPzFkMLSp6OZVkyd+5c2bRpk+zatUs6deqkxtPT0yU6OlpycnLs3+Xn58uFCxfcvgRI5EI7iHwsy7IXnH79+rkVjaQNEE/4daeTlZUla9eulc2bN0tCQoLtm01MTJT4+HhJTEyUZ555RubPny9JSUnSokULef7552XIkCF3tFuFhC/FxcUSHR1NO2gk7N27V4qLi6VXr17StGlTe/dWeXm5tGjRgjZAPOLXovPqq6+KiMjIkSPV71etWiUzZswQEZE//vGP0qRJE5k8ebJUVFTImDFj5JVXXgnIZEno0r17d9pBI6LGLY0tIzZu3CizZ88WEdoAqZ165ekEA6fzdPzF7EXx05/+VI2NGDFC6ZrdXE6wa9cupTEf4y9/+YvSnnYQ1RVfe/P9pcYOevfubfu/sQ8I5llcvHjRPsZcBYyTYJ0tzH/BzHnMqzBzcbBuG8ZNMGbzyCOPKI1179CuzPgR9oC5cuWK0p9++qnSmAOE8QDsBTRw4ED7uHPnzmps27ZtSrdq1co+rqqqks2bNwfUDgKdp4P4OhdrnGGNPDNmO2XKFDWGcT3zWom42xPaI2qciwnW8sO22ps3b1YavxswnmTGdPy5npZlSXl5eXDzdAghhBB/4KJDCCHEMbjoEEIIcQzGdAII7pfH4oZYM8kfsLbTkiVLlMb6X/j4YBOsmE5mZqbt/8a4DObSmJSXlyttxipE3GuWYW4C1qcaPXq00mbcBuNjWMML4ypnz55VGuMsmDtmzh3zrWpKUdVg9rgRcc/rwbhMcnKy0mb/KOxfhHTp0sU+rqiokJdeeikoMZ3Y2FiPsYX6xHR8gc+FMURzm7h5LUTce9pgng5ed7TlW7duKW3mauHmDayjWFvlf0/PJeL9mjGmQwghJKzhokMIIcQxuOgQQghxjDrVXiO1g77SNWvWNNBMIoekpCTbl465N8jRo0ftY+whgnXEMOcH83TM8i0i7v1QzBJQWEsM67y1a9dOacytwbma7wPPx5716K/H2AHGePr06aP0wYMHlTafH2OUWA/MzAfBvJJgUZ8Yjq/wNT4XPh6vvfmea6ps14C5WVgmyFvel4h7jNZ8PH7mmBeGnwXGK/G1vIHXIBAxM97pEEIIcQwuOoQQQhyD7jUS0qSnp9uuCbONroh7+XizLAm6FLCUPJYlQdcdulJwu6zpSkUXFZbFQXcaltjBdtZYvd10323cuFGNde/eXWnc6o3buXErK7r2zDYEWGMRXZTmFvZguteioqI8unX8cf/4cp/5mz1iurXwXLQ33MKP4PnoAvPWbsDXNfDHneYLb9coKK0NCCGEkPrARYcQQohjcNEhhBDiGCyDQwJCsMrgjBo1yt4uiiVdsBwIahOzDbOIyIkTJ5TGlr64tbhr165Kmz563C6L/neMH/Xs2VPpM2fOKI1tuY8cOWIfY1sE3OqN2/axHBJ+RuZzi+iWzljOB9s1m+V7qqqqZMOGDUEpgxMXF+extUF98PerL5Cv7S/mXP2N0dQ3dmXi7RqwDA4hhJCQg4sOIYQQx+CiQwghxDGYp0NCmvz8fNuHjeVmzDL8Iro8CObdYGwDW4ljHg6Wj8E8CzPuguVisH0w5uFs375daW+5MiIiU6dOtY+TkpLU2Llz55TGlso4b7yG2P66TZs29jG2ksDyK2Y5fsxLCSRmDKI+7ai95brcyfn+xEZ8levxFVfBuI2p8Vx8X4GMVfmat/nazNMhhBAScnDRIYQQ4hgh514LsR3c5A4J9OdW83zm7Tu6yLBUjVmWBMfwXNQ4f6zc6+218LHmtuPaXgvH8Xx0VZnne5tHba+F474qFJvn+6peXNtjA2kHNc9lPmd9nr++cwvk1mNf5/pTbiaQ8/KFt9eq7fOqjZDL07l48aJb+14S+hQUFLjlddQH2kF4Ekg7oA2EJ75sIOQWnerqaiksLBTLsiQtLU0KCgoCmnQYybhcLunQoYOj18yyLLl+/bqkpqYGtLAg7aDuRIod0AbqTijbQMi515o0aSLt27cXl8slIv/LoKah+YfT1ywYFSRoB/Un3O2ANlB/QtEGuJGAEEKIY3DRIYQQ4hghu+jExsbKr371K4mNjW3oqYQNkXjNIvE9BZtIu2aR9n6cIJSvWchtJCCEEBK5hOydDiGEkMiDiw4hhBDH4KJDCCHEMbjoEEIIcYyQXXSWL18uHTt2lLi4OMnIyJD9+/c39JRChuzsbBk4cKAkJCRI27ZtZeLEiZKfn68ec+vWLcnKypJWrVpJ8+bNZfLkyVJcXNxAM64btAHPNBYbEKEdeCJsbcAKQdatW2fFxMRYK1eutE6cOGE9++yzVsuWLa3i4uKGnlpIMGbMGGvVqlXW8ePHrSNHjljjxo2z0tLSrBs3btiPmTVrltWhQwcrJyfHOnjwoDV48GDr29/+dgPO2j9oA95pDDZgWbQDb4SrDYTkojNo0CArKyvL1rdv37ZSU1Ot7OzsBpxV6HLlyhVLRKzc3FzLsiyrpKTEio6OttavX28/5tSpU5aIWHl5eQ01Tb+gDfhHJNqAZdEO/CFcbCDk3GuVlZVy6NAhyczMtH/XpEkTyczMlLy8vAacWehSWloqIv/vKnno0CGpqqpS17BHjx6SlpYWFteQNuA/kWYDIrQDfwkXGwi5RefatWty+/ZtSU5OVr9PTk6WoqKiBppV6FJdXS3z5s2ToUOH2i2Yi4qKJCYmxq3tcbhcQ9qAf0SiDYjQDvwhnGwg5KpME//IysqS48ePy549exp6KqSBoA2QcLKBkLvTad26tTRt2tRth0VxcbGkpKQ00KxCk7lz58rWrVvlww8/VE2TUlJSpLKyUkpKStTjw+Ua0gbunEi1ARHawZ0SbjYQcotOTEyMpKenS05Ojv276upqycnJkSFDhjTgzEIHy7Jk7ty5smnTJtm1a5d06tRJjaenp0t0dLS6hvn5+XLhwoWwuIa0Ad9Eug2I0A58EbY20GBbGLywbt06KzY21lq9erV18uRJa+bMmVbLli2toqKihp5aSDB79mwrMTHR+uijj6zLly/bPzdv3rQfM2vWLCstLc3atWuXdfDgQWvIkCHWkCFDGnDW/kEb8E5jsAHLoh14I1xtICQXHcuyrGXLlllpaWlWTEyMNWjQIGvv3r0NPaWQQURq/Vm1apX9mPLycmvOnDnW3XffbTVr1syaNGmSdfny5YabdB2gDXimsdiAZdEOPBGuNsDWBoQQQhwj5GI6hBBCIhcuOoQQQhyDiw4hhBDH4KJDCCHEMbjoEEIIcQwuOoQQQhyDiw4hhBDH4KJDCCHEMbjoEEIIcQwuOoQQQhyDiw4hhBDH4KJDCCHEMf4LSQ31F/oItFsAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -2321,7 +2334,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2331,7 +2344,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2341,7 +2354,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2351,7 +2364,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2361,7 +2374,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2377,10 +2390,13 @@ " noisy_image = add_noise(orig_image)\n", " denoised_image = apply_denoising(noisy_image, model)\n", " plt.subplot(1,4,1)\n", + " plt.axis('off')\n", " plt.imshow(orig_image, cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,2)\n", + " plt.axis('off')\n", " plt.imshow(noisy_image, cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,3)\n", + " plt.axis('off')\n", " plt.imshow(denoised_image, cmap=plt.get_cmap('gray'))\n", " \n", " plt.show()\n", @@ -2446,7 +2462,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 86, "metadata": {}, "outputs": [], "source": [ @@ -2475,14 +2491,14 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 87, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAYKklEQVR4nO2dV6xVVReFF7+9IdUGApcuKEqvilRFaYKgItYYS6yJJUIML2hUfBHUBCMhaowGVBANRQQUld57FbhKUxAVsWD9307m/A53r3Pgnouwx/e0R9Y9u++97h5zrrnK/fvvv/8GIYQQqeV/R3sHhBBCHF3UEQghRMpRRyCEEClHHYEQQqQcdQRCCJFy1BEIIUTKUUcghBApRx2BEEKknBNz/cNy5coVcj9EKVOIcYJt2rRx+ocffnC6f//+Tu/fv7/Ede3evdvp6tWrO12pUiWnJ0+e7HS1atWc3rp1a2b5zDPPdG2nnHKK0+edd57Tf//9t9N16tRxeufOnU4vW7Yss9yxY0fXdvrppzu9bds2p9esWeP0SSedlLitgQMHZpYXLVrk2nr16uU0r/mQIUNCIeAx/vPPPzn/NvYeYTuPKXZfJ62/tN9h9rhLe935PL+xvz148GB0HfoiEEKIlKOOQAghUo46AiGESDk5xwiEuPjii52eMmWK0//7n/+/ori4OLPcokUL1/bXX3853bx5c6dXrVrldIUKFZyuVatWYrvlwgsvdLpq1apOz507N3HfZs6cWeK+/vTTT65t7969Tu/atcvpyy+/3Olff/3V6UcffdTpadOmZZbbtWvn2n788Uen58yZ43ShYgT5xARi0N/mPcRt5RNjyDe+EIPbTtpWbL95nEeyH+SEE07Ie536IhBCiJSjjkAIIVKOOgIhhEg5ihGInKlbt67T9P2XLFni9FVXXZVZnj59umvbtGmT0+XLl3eaXvvVV1/t9KxZs5y2Yxo4ToBe+p49e5ymT590HCH4sQEzZsxwbT179nS6qKjIaY4TYNxl2LBhJbYz1vHnn3863bhx41AW0N+Oee/5ePMc03Ek6yrtsTRJMYd8z0EszpJ0jmMxgtg5POT28v6FEEKI4wp1BEIIkXLUEQghRMopl+vk9cdqraFY7RJy1llnOd2hQwenp06dmvO2mM/L/PR8iJ3/0s6ZPhSDBg1ymvn49OK/+eabzDLr/5ATT/ThKv79qaee6vTGjRudtj4+a/L8/vvvTrNOEc/twoULnWatok6dOmWWly9f7touuOACp1lr6JxzzkncNrWtycT9OPvss53esGGD07YmUmly2mmnJbYn3XuxfPrYfZxPraHSfga47yeffHJmmc82YwD07WPXPZ/3LY+Tv/3tt9+i69AXgRBCpBx1BEIIkXKO+/RRfnryE40pkXfddZfT/Kz65ZdfMsu0HGgpxKyg2GeybY+t63CGlecLyzj8/PPPTrOkcs2aNTPLtDVoL3BdjRo1cpopn+eff77TO3bsyCw3aNDAtbFcNtNFaUvxXPfp08fppUuXZpabNWvm2mgVtW/f3mmWzuDvrZ0WQgj169fPLB84cMC1MZ2U57isyMeCOdLyFPlaSZZ8SzNUrlzZaZbfpl1pYQl2liKx75FDkVSiInYch3OO9UUghBApRx2BEEKkHHUEQgiRco77GAF9P8YIOnfu7HTXrl2d3r59u9PWh6Vn2K1bN6fHjBnj9Lfffus0/cykoeFMp6QPSN+7ELCkcqzEsvX9mTbJ/WUMYMGCBU7zeC+55BKn7VSW9erVc230Zxl/4HV5+OGHnR4/frzTdv1MF2VKJ0tc01dmyQneE3bfevfu7dp4f3Xv3j38F0ny7WOpj4XcD8aGeN/069fP6ZYtWzptY2Ys9zF79mynP/74Y6e3bNniNO9R3u82NsI2HpfKUAshhMgbdQRCCJFy1BEIIUTKOe5jBH/88UdiO30/ToFIv816dfT9mjZt6vSIESOcXrx4sdPMKV+3bp3TrVq1KnE/6T3PmzcvFBrm11eqVMlp+uNfffVVZpl50ywVzfNM75zjBr777junbYkJxi5Y4pplH7htO04ghBAef/xxp21JbY4b4DliOQtexzfffNNpljSxx2mnrQwh+xzRdz5aJPn8+ZZ8ybe0Sj5wHMbgwYOdvvbaa51mPMhea+4H7znGH9asWeM0S9fYZycEP56JsY2keEKu6ItACCFSjjoCIYRIOeoIhBAi5Rx3MYKYB8lcf063yJo3Z5xxhtO29otdDiG7/PHmzZud5liAtm3bOs28ZZubzHWzJtLBgwdDoeG0isXFxU5zH5s0aZJZnjhxomvr37+/0w0bNnSaXjuPj/EVWxK4YsWKro3xBU7pSE+V5bQZ66lRo0aJ6+JYkPnz5ztNH5/3pz1nIYSwevXqzDKP45FHHnGa4x2OFvmMDcg3ZhBbt/XL2cb7gjEAvhuqV6/uNL15e9+wrU6dOk4zvkDNMUkcv2SfH9bO4rYPJ26iLwIhhEg56giEECLlqCMQQoiUc0zGCI6kHsnw4cOdpu9K6N1Z75pjFJgDzvgD832Zr86Ygt3W/fff79pq167t9PXXX5+176UNvcitW7c6TW/y888/zyzTE6UPzzEI9HM5L0SXLl2ctvn89O25X19//bXT9HO///57pzkGwp57XjM7niGE7Fx1nrOioiKnZ86c6bQdb2HjBSHEp1UtK2LPY1J7vlNTJsUE+PecH4NjhJjbz3cB53fgeBOrWWuIzwrHFbDeFd8zHGewfv36zDLHGHDbh1N3TF8EQgiRctQRCCFEylFHIIQQKeeYjBEcSX0R5uDSF6QXTZ/Qen8cF8A5jDkvL/1M1u9v166d0zZPmfX8WXemLOBYgAEDBjjN3Geb+8+6TPQ5OS/w7t27nWZtIY4zsHrkyJGu7aGHHnKaNZ04RuG2225zmrn/1vfft2+fa+OcwxxXcMUVVzjNOvSc49jOOXD33Xe7tvfee8/pWLyrrMhnbEAh5yOgp1+1alWnGYeKxR+IfRfwOtO357oZM+D4EcYvbDyIz86kSZOcXrt2bdJuHxJ9EQghRMpRRyCEEClHHYEQQqScYzJGcCQwX5d1ZqiZk2s9XeabM0855n9yW9w36zvSr2R+elnAeYI/+OADp1mL6MCBA5llxlp69OjhNOv633jjjU4zPsHaRPZaMCawcuVKpzt27Og056nmOAPOaWxjDKxNZY85hOz4w+jRo51u3bq106xtZecz4NgR1sLhmIayIt96QfkQ8+mT9oX3HGMCzOXnfNJJ4wZC8ONLOC6G8UNeV54jWysrhOwxEM2aNcssM9ZhxxiEkB0DywV9EQghRMpRRyCEECnnmLSGkiwWpnHxE42lDvjpTs3PS1tWgrZRhQoVnKZ1ROuHn4O0GWzZBdobPC6WsygEnF6SZSFoDe3duzezzM9unjse+6uvvuo0U3FZqsF+ptPKadCggdO0lWbMmJG4L0zts9eV+0VbqXv37k63adPGaVoALOVtr/uwYcNc25AhQ5yePXt2KAuOxPrJ97exaRe5Pvv3vD9prdFioQ1FzVRfa2fu2bPHtdHySyphHUL2O43vIbsv+/fvd21MLc/XTgtBXwRCCJF61BEIIUTKUUcghBAp55iMEdAXtGldjBHccMMNTtPnprcXKwth08CYwsmy1IwvxErVctuVK1fOLL/yyiuu7bLLLktcVyGwnn8I2fGWbdu2OT1q1KjMcufOnV0bU1HnzJnjNL10eqaMOdipL5955hnXxthNlSpVnK5Zs6bTLJXBfbOpgvSdOQUnfXvGLxh/4PSfdkrSHTt2uLYVK1Yk7ndZUcgyEbFtEeu9M45mn6dDwbIlTAm1ZdWpeY916tSpxP0KITsVlc8v41T2PcSSJ59++qnTLJueC/oiEEKIlKOOQAghUo46AiGESDnHZIyAfhq9eQun96PXzDxueneMOdicXZad5rgBrpu+Noeds0S29XwHDRrk2l544QWn58+fHwpNpUqVnGY5XPrltpQDSyRPnTrVaebbv//++04zZsByCja+wvgJfXnmXbOcxfPPP+80993+nrnlI0aMcJrlLhhzmjdvntOtWrVy2sawWOKa9x/HpRSKQpaUONJ4gz0HjAfyujNmx+eVMS+WcrDvHZb7iJWu4XuG7yVeS/seGzdunGvbtGmT03zP5IK+CIQQIuWoIxBCiJSjjkAIIVJOqcUI6OVZDyxWV4NeXaxWBvN9k5gyZYrTzLHl1JT05uhZWs+WPh+9OR4XiR23XT/zzelNlwWMYdCnHzx4sNO2Tg6PjTnaLEPN8R+MRzRu3Nhpu376tbzfOO3lhAkTnGYdpBo1ajhtfX3Ws+F0kuPHj3ea15H3wNy5c5229XDoI/Oc0RM/WuQz5WOsNHssZsCxArZcc+/evV0bzz2fXz5TO3fudNpOFxmCj+fY7R5q3XxncYwRj4vxiWXLlmWWN27c6NqSYqS5oi8CIYRIOeoIhBAi5agjEEKIlHPYMYJYvn0+Pn6+XHHFFU7b+i7t27d3bfR7mevPmADHKPC47Pp4Duj7MWZAv5P7Ruy+cQrEfv36Of3RRx8lrqs04HwK9Fzph9saPpw/oEuXLk6PHDnSafr89ILpoQ4YMCCzTG+X8yTwXHH8A/Pz6cF26NChxP3q27ev09bbDSGEBQsWOM3xEazJ9OWXX2aWb7nlFtf22WefOc05KwoF72PGAOh3Mz8/6bf8W461YX2vdu3aOW3PX/369RPXzWeK9X1Y+6tt27ZO23EJfG9Q85wx3sZ3RVLNs0svvdS1MWbA+mm5oC8CIYRIOeoIhBAi5agjEEKIlHPYMQJ650mwRg3r2NerVy+xnX44vT+bX808ZPrwrElOPzlWv8X6gvSO6aEzJ5x+MmMdSXOkMt+c3nJZwPx75lUzLmTrtbM+O+v3XHfddU5fdNFFTtMzpS86bdq0zPKTTz7p2jj/cVFRkdP0azk/wcKFC51+4IEHMstjx451bUuWLHGa5+Smm25ymnMdTJo0yWkbK+E4gq5duzrNe7dQxHL/k8bDcPwH55Nme6NGjZxm7KhixYol7gtjAtxPjiGiT894BNdn34GMAXBMwoYNG5zmu4DvEtbisrEi7idjdV988UXIF30RCCFEylFHIIQQKUcdgRBCpJzDjhHQox4+fLjTtkYK5/NkfIH5+KxDQ5+V+b7WX6N/SR+Qvv3AgQOdXrx4sdP0wa1PW6tWrZAE5+XlulhfnvEM64vTU6SPXRZwm9aXDyF7HoAXX3wxs8ya6fv27XP65ptvdpreOWM5TzzxhNPr1q0rcVvdunVL3E/m3/P+Y+ynfPnymWXeA4xlcC6E6dOnO23nbAghOwfc3iOMpc2cOTPxt2UFnznG1Wz9pWuuuca10fNn7Sa+G0i+Y3OS9pPbis2FYGMhjAFYT/9Q7byWTZs2dZrvipYtW2aWWVOqNOYi0ReBEEKkHHUEQgiRcnK2hvjZNGrUKKeZDmjtn6QyDYeCn2z8Pe0eCz8taWc899xzieu67777nE5KL+Wn+ZYtW5zm5x9TV5kylpTuxvTRo2ED7Nq1y2l+zrLEt03xpA3Gaf9oGfDTmhYCbSlbcoJpuRzuv2rVKqd5XVh6YPfu3U7bshG8P2hLsRwAUys5JSetSmuDcj9nzZrlNG2oQsE0TN7HLVq0cNpOQ8qpOGm/8FmPlXKnTWzvQWvhhRAv/UzN+5n7Zu8TvgtmzJjhNNNiafVaKz2E7ClOrZVaXFzs2tasWeN0zE47FPoiEEKIlKOOQAghUo46AiGESDk5xwhuvfVWp+m9cypB64HRD2PJCUKvnL4//Wbr0zLVj77pG2+84TTLBrNEMdMD7bE0b97ctbGMQsxLpWfJ2IiF/iTPEYfDFwJ6k7fffrvTLEFhh9nTr7WlnEMI4cMPP3R67969TvP3TPG05YhZMoKlx+nbs1Q0Y1gsebJixYrMMuMRTJVm6QymJ/P+oudt02hZYp3bGjRoUCgLeF9XqVLFaabnnnvuuZll3sexmADTQ/kM8Z60XrrdbgjZMRbuN+M31Lw2NkbQq1cv12ZL44cQQrVq1Zymjx8r7W1LabB8BcuxLF26NOSLvgiEECLlqCMQQoiUo45ACCFSTs4xAvq/9OmTSjHwbxkzoDdOP5jlCOgL2vVxXABL87JcxcSJE51mjjk9XBvfoF9J35p+J7cdm6bPtseG8bM0dyFg2eOXX37Z6XvuuafE3zLOw9xnxo2SfOYQsnP7bWleeth16tRxevny5U4PHTrU6e3btzvNGIL1e7ktesHjxo3La9scG2DjTiy5zNgFc9kLRazsNMcUWS+ezwTva3rl3BZLeHAqSxs3sSXjQ8h+vvg88pliDIbxRwvHqnBbXDffHTyHSWV4+Cw1bNgw5/0sCX0RCCFEylFHIIQQKUcdgRBCpJycYwQ7duxwml4efVXr3TFfl146c8ZZR4f+G/PvrR/HadwYu6DnyG0zJ5f1Rmy8g/nq3C+uOxYzYLv1Q1l6lrnE9NQLAWsNde7c2WmeW+ut33vvva5t8+bNTjMG1aNHD6cnT57sND1UG0dirZvVq1c73bNnT6c5LSBjCjzXtn3RokWujfcqS2C3bt3aaY6/Yf2m1157rcTfxqZxLCtisTI7joPjj/geYX49zydjCrVr13bavgtiZaX5/PGe4v1Mbfedz25sDBGJjROy7yEeB+NlfE5zQV8EQgiRctQRCCFEylFHIIQQKSfnGAHznydMmOD0nXfe6bSt/8M6/czt57gC+mPMHU6aYs6OXwgh23uLTW1Hf41/b9dH/zJ2XDEvNWkcAv3MoqIip8uiFj39cNZY5/H36dMns/zuu++6Nl4XTuXH2kmMt9xxxx1ON2nSJLP8zjvvuDbWj+JYE8YQuG3mk9taLszp5piXp59+2mnWpOF0powZ2PpCjHfRK167dm0oC/iMcT9YN8rGPRgvZM47n2167XwOOI7A7ktsqkn6+rwnSVK8gu8s/m0sHshzyud569atmWXeI1OmTHGac2Tkgr4IhBAi5agjEEKIlKOOQAghUk65f2mCl/SHEb+Ned+PPfZYZpk1P+j30htPqrMRQraPaP24WO4wD5feXqxGiG2PnRO2x3x8bsvWH+E4gpUrVzrNuW5zvKx5wXmF6W/zOtp5WFkr6K233nKa9WmuvPJKp3n89FynT59eYhtr8tjYRQjZ4wiS6hiF4MeP9OvXLyTB+4mMHTvWaY4FsPcAc/BZw2vJkiVOL1iwIHHbhwvPB+813sc2fsN6VBzzwXcF181t8/zaZ47xBfrysdz+/fv3O833loX7HavHxGeFc13b+5ntjBFwPBPHPsXmfQ5BXwRCCJF61BEIIUTKUUcghBApJ+cYAb13el5JcC7fZ5991mn6a8zNpt+WVI8klgvMmjY8fNZU4nHaeUq5H4TrplfHMQw8zk8++SSzvG7dOtc2d+7cvLZdGjAnnvn6nL/XXhf6sYwpcV5hzg/Luabbtm3r9IMPPphZfumll0rcjxCy62Ixt5/XlX+/fv36zDLHuGzcuNFpjkng2BLGXTinsb3feH8wRsDnZvTo0aEQsKYW4b1nj5m1gXr37u0055PmPBVcN+cusWM++MxQs4ZUbI5i5udb355/G3v2GUdh7IPxCBuviM3ZwPE8sXdiCPoiEEKI1KOOQAghUk6ppY+WJpx6LVbG2qbcbdu2zbXxk4ypV8crhbCGbEpwCCG8/vrrTrdq1cppe+45haO1PELI/lRmOWZ+enNI/sKFCzPLLCVOaP3Y4fshhFCjRg2n69at67RN7WPqXoMGDZxmSWumplqbKYQQunTp4rRNOWb6Ma3FNm3aOP3UU0+FQkBriOeTVoRN5+V7hLYdNa003te0Qew9F0vdjb3TuC1aR0lpmVx3LJ2Uf5+P9U74bOTyLtAXgRBCpBx1BEIIkXLUEQghRMrJuQx1WULfNAbLCIvCwBS3vn37Os3rZoe6M0bAtEvGAMaPH+80YwosgW19aPrGTOGMlTZmCui8efOctrEQ+tAslbFixQqneQ6ZPvn22287baf4tOnEIWT75yyBXShi6Yj0u5O8eq6LOlYeIWlfeF153UlpxtXo8cemwYzti43DxOIHsdjIodAXgRBCpBx1BEIIkXLUEQghRMr5T8YIxH8TjtHgkHtOAWlLSbPMbs+ePZ0eOXKk00OHDnWav2fZB6uZq88pHlnugvn5tWrVcpqerP09pwwtLi52ml4wxyiwdDT3dcyYMZlllmy2YydCyC6bXChi/jaxfjfjBzEd21bSGIbYupP281Ca2PUdaXyBv08qnx8rMcGxGLmgLwIhhEg56giEECLlqCMQQoiUk3OtISGEEMcn+iIQQoiUo45ACCFSjjoCIYRIOeoIhBAi5agjEEKIlKOOQAghUo46AiGESDnqCIQQIuWoIxBCiJTzf0ZFC9RkKtskAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -2492,7 +2508,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2502,7 +2518,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2512,7 +2528,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2522,7 +2538,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAYf0lEQVR4nO2defBV8xvHP/YtImuFhCRtirRoGVGEokXKNoa0ihhMGTQYpoxlTBhZylokO5M1ipQllRSpLC1SoSLZ+f31O/M8r2+dz73V/ZY+79df5z2fe+8599xz7mfO+3k+z7PVv//++28QQgiRLFtv6gMQQgixadFEIIQQiaOJQAghEkcTgRBCJI4mAiGESBxNBEIIkTiaCIQQInE0EQghROJsW+gLt9pqq1Ieh9jIlGKd4Jlnnul0nTp1nP7ss8+c3meffbLtn376yY3tsMMOTi9dutTp+fPnO92qVSunly1b5vT222+/zs/ebrvtnP7555+dPvjgg51+8sknnT766KOd7ty5c7Z95513urEWLVo4vfPOOzvNY1uxYoXTY8eOdfryyy/PtqtVq+bG3nnnHaft+Q4hhP79+4dSUKFCBaf//vvvkuxnbfC6zvtf4ljsntjQ8WL4559/csfzjn2bbbbJ/Sy+9/fff48ej54IhBAicTQRCCFE4mgiEEKIxCk4RiDELrvs4vSaNWucXrx4sdOHHHJIts0YwY8//uh0gwYNnD7iiCOc3nHHHZ1euHCh03/99Ve2/dtvv7mxQw89NPc4v/76a6ePPPLI3H0PHTo0rIt58+Y5zXjEQQcd5HSNGjWcrly5stO//PJLts24yOTJk5225yCE0sUIGBMoxrffUPjZeV46j2vrrbde52vXh7x9FfPeEOLfq9CxEMrGoQpBTwRCCJE4mgiEECJxNBEIIUTibFVoYxqtI/hvUYp1BNWrV3d62219iOnGG290esSIEdl2lSpV3Nhee+3l9FtvveV0/fr1nd5tt92c5hoG68W/9tprbqxmzZpOW989hBDeffddp+2ahBBCaN++vdM2L3vq1KlujPGFpk2brvO9IYTw5ZdfOs3z8uijj2bb1157rRtjPjnXcQwYMCCUAq6NILz2rN7Y/yMbsq8N8elj8LfhvRJb4/Dnn386beMy/CyuI2Cs6I8//oger54IhBAicTQRCCFE4mgiEEKIxEk+RlBsPZJSwhxzm1v/7LPP5r6XOdKlqP/Sq1cvp7kWYN9993V61qxZ2TZz+WvVquU0fc/nnnvO6R9++MFp5sjbXP+vvvrKjTG+8O233zrNNQ70d1etWuW09W9PPvlkNzZlyhSnuWbhyiuvdNrGAEII4YADDnDanqeXX37ZjTEecffddzs9Z86cUAoYIyjmninWl9+Q+zP22li9H8Jjsetqdt99dzfGuk+8BitVquT0Rx995PSiRYucttckYwCxc8p1NWtDTwRCCJE4mgiEECJxkisxQQsl9nh47rnnOn3aaadl261bt3Zje+yxh9PFLr3n46BNc9x7773d2OOPP77O15YKnrv333/faS5tt+eKaZJM0XzmmWecZnnmJk2aOH3DDTc4bUtJDxo0yI2xXDNtKX4v2jt87LdlqZcsWeLG+vbt6/SCBQucXrlypdNMk2Wq3+rVq9d5nOPGjXOaZTk2Rzam9RN7f6ykRKyc80477eT0YYcd5nSzZs2y7TZt2uS+luVZWCJl5MiRTo8ePdppe11szDTX/6MnAiGESBxNBEIIkTiaCIQQInGSixHEfMF27do53bVrV6dt2hfbKzINkeUE6FHSD2a5Y5ty1q9fPzd23333hfKG6YhsXUm/3KbEscwD20GyHDNjCEy3O+WUU5y26bL333+/G2vUqJHTb775ptNsZdmlSxenn3rqKacrVqyYbTNV1abMhlDWt2ds46STTnKasR4bh2G6KOMmkyZNCps7xfrZGxIz4HtjLR2Z4sn/Av5WtnwI40j8n6Fevny507vuumvusdmU0ViJifVBTwRCCJE4mgiEECJxNBEIIUTibPExAuYSs7wr6dmzp9P046zvTz+Xvvavv/7qtPWWQyjrEzJv2eblv/TSS3mHXS6w7WLdunWdpq9pff/58+e7seOPP95p5sTzvH/++edOcwn/999/n22zHAU/u169ek6zVSWvGcZu7NqA2bNnuzGuUZg2bZrTLEnB5f/cl/WGWdrh9ddfd5rnaFNRnmVb8j6b3jlfy/utZcuWTrOkil2rEkIIFSpUWOe+GRPgNcW4FOMTjDnktcVkLJL7LgQ9EQghROJoIhBCiMTRRCCEEImTXIyAvmHHjh2dZrlk1gSx3h5r69DXpqdL765y5cpOM35h1yXQM9wUDB482OmBAwc6zdz+N954I9tmrSSWgqavf9RRRznNWi30a8ePH7/OsUMOOcRpxjb4+okTJzqdt6ahbdu2bozXmy0lHkIIzz//vNMscX3qqac63b1792z7mmuucWNce/Hdd9+FTUFsbUDeeF6rybW9NxZ/yPPSeX+y3ekZZ5zhNO/PvBad/N15nBznfwf/dzp06OC0XZPDuNTGQE8EQgiROJoIhBAicTQRCCFE4mxxMYK8Gh1ro1OnTk6ztSB9Ruv10XOM+YRs7ch1Bny/1eyLMGDAAKdj6yM2BsyJj/njtl47vXFb0z+Esi0aGRM47rjjnGbbRvv+9u3bu7GpU6c6/eGHHzptffgQysYMpk+f7rT1itk3gfuePHmy01WrVnWasRJef6NGjcq2a9eu7cZY1+iYY44J5UGxfTaKIfZZsZiChdcj41TNmzd3mueX6wzY/tUeK/fF/4ZY7j/Xk3D8m2++WedrY2sUCkFPBEIIkTiaCIQQInE0EQghROJscTEC+mOs+c8a7szFZm9d1rSxviHrwsTWLLA2EX3w6tWrO239Z3rJrINy1113hVLDc0vvnfWD7PFzvQb7OxPGdugd77vvvk7b34LnivET1nji78KYQLVq1Zy2fu2yZcvc2Lx583L3FeuHwZhCixYtsu2bbrrJjZ133nlOP/HEE04PHTo0lIJS9xTIe28xMQSu/+D6EcaduG6A78/z/WNrFmK9EPjfwbpktgcye4XH4hGFoCcCIYRIHE0EQgiROJoIhBAicbaIGIH12xgTIH379nWaeeCsMU5f3OaQ87Ws9cL6/aw5zvezB7L9XvQYN0WM4O2333aatfWZZ23r5bPfLnv9Mj4yc+ZMp+nb09e36xLo07PXLPPFhw8f7jTrHLG/8o033phts0/zmDFjnO7Ro4fTd999t9OMP5xwwglO2xpTjJu0adPG6blz54byoFjfPq+PcLGfHVtHYGMwVapUcWMnnnii0/Xr13ea9X+o8/bN4+T/EMcPP/xwp/fff3+nGzdu7LTtfc3/jdWrVzv98ccfh2LRE4EQQiSOJgIhhEicLcIasulTTBVs1aqV00whs6mAIZQt98w0RzvOEsK2bHQIZdNLmY5GK4iphTa9lI+lXC7PR81SwH0wbY3f5/zzz8+2hwwZ4sZo1/Dc8Nxy37ShbLvJhg0bujGWEic8l9w3LRj7GM8S12eddZbTkyZNcpqlNM4++2ynWYrDnuOxY8e6MV67tNfKiw0pOVGsVUS4L2vnsMw0732mbBKWeeA1Z9/Pe5eWMm09fhbfv+eeezp90EEHZdu9e/d2Y7RsZ8yYEYpFTwRCCJE4mgiEECJxNBEIIUTi/CdjBPT28kow9+nTx2mWguZn0avedddd17mvNWvWuDGWjGBrO5aPpS/IdDXrf+b5kyGULW9cClh+gzBmsHLlymy7Vq1abozn7uGHH3baLqkPoWxqLs+ljU/Q22Xcp1GjRk4zpsCU0EWLFjk9bty4bLtfv35urHPnzk5fd911TvM3ZtovS5N37do122Y6Mn1oHnd5UUzZh2I9/2LKTofgzwnLwzAWxOuE92NM233FStuQWNlpahuX+v77790YdWzfa0NPBEIIkTiaCIQQInE0EQghROL8J2ME9KKtJ8Z2fcw/Z2kDrhNg+Vfuy3p3jAHQ32RZCLa+o69I/9O+nzEC5iXzWEoBSzMQxmpsS0i7RD6EsuU2SOvWrZ225SpCKLsOwcYvbM51CGXLPLBcM2MICxYscLp///5O33PPPdn2nDlz3BhLY3BdAFtsskwHW1XashFcp/HBBx84zTUzmwt5JSZiMYFiPjsEn39vS3iHEEKlSpWc5v0YKyPPe9D+F/CzGM+x8bIQysbbuO+89Uy8Dlh2nXGoQtATgRBCJI4mAiGESBxNBEIIkTj/iRhBrMSrhXU4mFvNdQH01un1EesTxsrU0senD8jXM7fYfk/mFbMWSayezsaA35f59dTWs2apXMYTmPPN3+nVV191mms2bMyB7x02bJjTjBNdcMEFTn/00UdOMw5g20kyznPqqac6/cYbbzjN2AfXtTBGZddfNGjQwI2xFPe0adPCpiCW62/v31h9n9hnUfP+te0nmzVr5sZ4bgljAHklrqljaxJ4b3O9EmMC1PZ/ibEOtm1lbKMQ9EQghBCJo4lACCESRxOBEEIkzn8iRhDLLe7YsWO2TV9w9uzZTtPnZs+AWH0R60nS56ZPyFgGX09Pkq+3x0rPsHLlyk4zb7kUsN8Czw1rudgaKAcffLAbY749YwTsCdCpUyen6ZPanPEJEya4sauuuspptgWcOnWq07xm2BrQ+ruMETz33HNO21pBIYTw1ltvOc0aTHvttZfTTz/9dLbdvn17N8Z1HbxGyotic//ziK3F4boe9hzo0KFDts3fjfcbYZ0nXt95Mb28vgghlF3bwj4WPDZ+nv3v4L3CNTqvvPJKKBY9EQghROJoIhBCiMTRRCCEEIlTcIxgQ2uCFPPZMZ+QPur111+fbS9fvtyNMaec6wSYh0zPl96d9ero+dNj5PeoVq2a04wJ8Hvacdbvj8UXSgFrmvDc0Vtv27Ztts3cfNtjOIQQ3nvvPafZX/azzz5zmueqZcuW2fall17qxm6//XanGctgvIXxCPaAtfEJ/i777bef07xPqlSp4vTw4cOdHjhwoNPz5s3LtrnmgGtJGJ/o1atX2Bywv1XsXuf5YkyAOfOMwdSvXz/b5r0ey6/P8+XX9n77X8ExasYb+L24roD3sz0vjD+wXtr6/DfriUAIIRJHE4EQQiSOJgIhhEicgmMEsTrirCFiPTGO5fnua9sXeeyxx5y2fhrz6VmThvnn9Nti3rutHxTzbGvUqOF0t27dnL744oudtv5mCGVr01s2ZoymUHhuxo8f7/RZZ53ltF2jwXxvXhPHH3+80/RM2bPY5teH4PPzGRdiHSb68O+++67TjRs3dnrkyJFO2x4XBx54oBubMmWK00cddZTTn3zyidO8Jg444ACnzznnnGx7xIgRbuyyyy5zmvVsNhesH07vnOt46J0zHtilSxenTzvtNKd5v1t4L3Nf/O+IxStsjIDXa6ymEmtvFROfiPU7ZqyyEPREIIQQiaOJQAghEqdga4jpT7QJYroY6tWr5zQf5fnZtu0bUwO57J6PooSlffk4aR+7uISdVlD16tWdZsrkkCFDnI6loG1qmKZ27rnnOs3H4xUrVmTbPFdnnnmm03fccYfTtFxYvvnee+91esCAAdn2Aw884MaOPPJIp9955x2nWc7ihBNOyD02myZLy+voo492+s0333Talt0IoWxKLjnssMOybVtKhcextn2XFzGb2FosLLXAe4ZWUMOGDZ1mmW9aQfZ+/eabb9zY/PnznabdyO/B+5cpzfY/kbYRrR3+7vwPY9o6/2/tvcW0bZ4DtaoUQghRNJoIhBAicTQRCCFE4hQcI4h5/iyN2qhRo2ybXhvTnViimGWC6dPTV7WlG1guwLYwDCHeHpLHxnGbfkrfmx5jjKpVqzrN72V9wliZWnqKpYDnkh7r66+/7vQVV1yRbfP6mDt3rtO2REQIZUsxfPHFF07TJ7VlqJs2berGatas6TRLMRx66KFOX3TRRU7z3Hbu3DnbZtxn+vTpTv/www9OMz2Uqaq33Xab07YEBVOfef3ZOEl5Ekt9tPf3eeed58aaNGniNGMEvG64L6ZKTpw4ca3bIZS9hnj+mIrKa5BxAHtdrFy50o0xTZjxCX6PY445xmmeBwvjCYx7rk8asZ4IhBAicTQRCCFE4mgiEEKIxFnvVpWXXHKJ0/T5bQ78smXL3Bj9MVu2IYQQFixY4HSszZtdOxAr5xrzM+mvVaxYcZ3jzIEuFnp9PBZ7rIxtxFr4lQKWkmbJ7/vuu8/p0aNHZ9tcN/Dpp586zXOxdOlSp20+fQhlYwTWYz3uuOPcGK9VW7YhhBBOP/10p7nOgNdU//79s23m7j/++ONOs00mvxe94wsvvNDpZ555JttmuQpbfj2EEKZNmxbKA8ZMeP+yxIe9f4899lg3xnUYJLa2ZsmSJU5//vnn2TZ9e3rpJ510ktOMUzEmw+tg0aJF2fYTTzzhxl544QWn2eaV8QmueeBaFruuhnGncePGOa0YgRBCiKLRRCCEEImjiUAIIRKnYGN50KBBTvfu3dtpthK0/jbztOmF0x+mx0j/m/6arW3CdQD0kvlZrC1EH5C5xMylt8Ta7vGzCf1P+37Wb+G+yiNGYD3/EEK45ZZbnGa7SdsqkP4287/Z4nHUqFFOs34KYz/2mqF33q9fP6eZo83fiSWC6TXb2BCvt5NPPtlpesdsn8jPrlWrltM25sDy64yb2LU7pYTXIq89XpvWm+c6ithn8bfh787/jiOOOCLbZmtYni9bTnxt+2ZMwbYNDSGE+++/P9vmvcGS1rF1PzYWFELZ/yUbg+VxMla3PnXe9EQghBCJo4lACCESRxOBEEIkTsHGMj0w1kih35bXMo6+H/OQ6R/TO8/LY455ivRkGUPg92A9oA2B3rTNQw4hv/8Av1esJlIpGDZsmNOTJ092mv647SEwc+ZMN8a1IvRE27Zt6zTbSbZr185p6/8yJsAaSKw9xOuvVatWTvN7Wg/2lVdecWOsoXTNNdc4zT4LL774otPMXe/UqVO2zfUz9Ib5PUtFzIPm+bQ58h9//LEbszWi1kYs/sCYg12zwHhMrL0rewawlwSv/xkzZmTbxa5X4r3O+CH/h2xNJv5nsWXu22+/HYpFTwRCCJE4mgiEECJxNBEIIUTiFBwjYN111mdh3XDrs9I7Zn8C1imi70evjx6kreNBT5HeG9cgsH78nnvu6TT9tzyYE00vlf4w85SZe2xhXITrGcpjHQFrrPMa4PexXiV/Q34fev6DBw92mjVqpkyZ4rStLzRmzBg3tmbNGqcXL17sNK83+vysZ2OvX9aroedNz/+RRx5xumvXrk6zfpXtt0wf+tVXX3Wa/bpLBb32WMzPxoPYp9v2Gw+hbE9i1vridZR3zy1cuNCN2R7aIYQwa9Ysp5nLz9paXF9ifX/GBGJxTcZQef23b9/eaXseeB2wl8H6XAd6IhBCiMTRRCCEEImjiUAIIRJnoxnL7Dnw1FNPrXW7EJhDyx7GzKe2eeG77767G2O+OnOtJ02aVNSx5RHrWcxji/UhtnrVqlVujD42+weXgnr16jnNfOW8+u12TUEIIUyYMMHphx56yGnWdenevbvT7D87duzYbJv12hn34VqSBx980GleXzaXPwR/7pkfzt/4ySefdJoxpx49ejh98803O/3SSy9l21dffbUbYw0v9ugtFfS/ed3yuraxrzlz5rixW2+91WnGUOrXr+903bp1neZ6GhvH+uqrr9wY1wkwJkfvPW9dTwhl4xN5YzxHjPExfsjrm7W4LLzeGaMpBD0RCCFE4mgiEEKIxNnq39i66/+/MGJ7iM2LAn/WomjevLnTNrUxhBA6d+7stC0HXblyZTdWu3Ztp/kobMsJh1DWKmK5DvtYP3v2bDdGy4plIXr16uX0+++/7zTtHlsOg6nRLMXCz+rTp0/uZzPF0doXtLQaNGiQ+9677rorlAKmCROmSlqrKHZdxiyV2HieLULLisdS7L6K+U/kvpnGHrONrQUWs35ogRXyX6AnAiGESBxNBEIIkTiaCIQQInFKX5dAbDGcffbZTjdt2tRptqq87LLLsm165Vz+X6dOHafpczJGYMuKhBDC0qVLs+2GDRu6MZY/Yaoz25EyZZElUKZNm5ZtMw2Q36Nnz55Os4TEPffc4zRjKbb9JMtqvPbaa7nvLS/YLjKvxHLMpyexsvL08Ysp5U5i6aLExghix0HNtFeWpGecxe6LMYKN0bZWTwRCCJE4mgiEECJxNBEIIUTiKEYgCoblnZmvz7ae1udkKQZ6/GxPSs1yAC1btnTaritgnjvLinTp0sXpESNGOM0YA/1cW7Z63LhxbixWinzq1KlO0+/lWgG75qFbt25ujLENxlXKi1jrSjsee20M+uGxtQAb673FHhc1y+Fz34wJ5MHXxtY7FIKeCIQQInE0EQghROJoIhBCiMQpuNaQEEKILRM9EQghROJoIhBCiMTRRCCEEImjiUAIIRJHE4EQQiSOJgIhhEgcTQRCCJE4mgiEECJxNBEIIUTi/A/yZj0QtpScnAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -2532,7 +2548,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2542,7 +2558,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2552,7 +2568,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] From 3f19b62b6514e7812e56af442a1d28a99b304b46 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 00:47:32 +0100 Subject: [PATCH 05/51] removed axis from images in the exercise --- exercise.ipynb | 43 +++++++++++++++++++++++++++++-------------- 1 file changed, 29 insertions(+), 14 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index c3e9020..934be53 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -45,10 +45,12 @@ { "attachments": {}, "cell_type": "markdown", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, "source": [ "### Acknowledgements\n", - "This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, and Caroline Malin-Mayor for DL@MBL 2023." + "This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, Caroline Malin-Mayor for DL@MBL 2023, and Anna Foix Romero for DL@MBL 2024." ] }, { @@ -66,7 +68,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -147,18 +149,24 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", "plt.subplot(1,4,1)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[3][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,2)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[23][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,3)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[15][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,4)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[29][0][0], cmap=plt.get_cmap('gray'))\n", "plt.show()" ] @@ -252,6 +260,7 @@ "texture = convolve(texture, weights=[[0.5,1,0.5],[1,0.1,0.5],[1,0.5,0]])\n", "texture = torch.from_numpy(texture)\n", "\n", + "plt.axis('off')\n", "plt.imshow(texture, cmap=plt.get_cmap('gray'))" ] }, @@ -308,12 +317,16 @@ "source": [ "# visualize example 4s\n", "plt.subplot(1,4,1)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[9][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,2)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[26][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,3)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[20][0][0], cmap=plt.get_cmap('gray'))\n", "plt.subplot(1,4,4)\n", + "plt.axis('off')\n", "plt.imshow(tainted_train_dataset[53][0][0], cmap=plt.get_cmap('gray'))\n", "plt.show()" ] @@ -1252,12 +1265,16 @@ "# Let's visualise MNIST images with noise:\n", "def show(index):\n", " plt.subplot(1,4,1)\n", + " plt.axis('off')\n", " plt.imshow(train_dataset[index][0][0], cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,2)\n", + " plt.axis('off')\n", " plt.imshow(add_noise(train_dataset[index][0][0]), cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,3)\n", + " plt.axis('off')\n", " plt.imshow(train_dataset[index+1][0][0], cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,4)\n", + " plt.axis('off')\n", " plt.imshow(add_noise(train_dataset[index+1][0][0]), cmap=plt.get_cmap('gray'))\n", " plt.show()\n", "\n", @@ -1585,10 +1602,13 @@ " noisy_image = add_noise(orig_image)\n", " denoised_image = apply_denoising(noisy_image, model)\n", " plt.subplot(1,4,1)\n", + " plt.axis('off')\n", " plt.imshow(orig_image, cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,2)\n", + " plt.axis('off')\n", " plt.imshow(noisy_image, cmap=plt.get_cmap('gray'))\n", " plt.subplot(1,4,3)\n", + " plt.axis('off')\n", " plt.imshow(denoised_image, cmap=plt.get_cmap('gray'))\n", " \n", " plt.show()\n", @@ -1745,18 +1765,13 @@ " \n", "" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "07_failure_modes", + "display_name": "Python [conda env:07-failure-modes] *", "language": "python", - "name": "python3" + "name": "conda-env-07-failure-modes-py" }, "language_info": { "codemirror_mode": { @@ -1768,7 +1783,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.12.4" } }, "nbformat": 4, From e8f9ad92fa9c68c4bf04b2c952708e1648576384 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 00:54:04 +0100 Subject: [PATCH 06/51] fixed 5.2 -> 5.3 --- exercise.ipynb | 2 +- solution.ipynb | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 934be53..cab1b64 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -1734,7 +1734,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**5.2 Answer:**\n", + "**5.3 Answer:**\n", "\n", "Your answer here!" ] diff --git a/solution.ipynb b/solution.ipynb index 718cd07..5b5b5cb 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2631,7 +2631,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**5.2 Answer:**\n", + "**5.3 Answer:**\n", "\n", "If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being \"denoised\" away." ] @@ -2645,7 +2645,7 @@ ] }, "source": [ - "**5.2 Answer from 2023**\n", + "**5.3 Answer from 2023**\n", "\n", "- Run on any out of distribution data\n", "- Especially tricky if the data appears to be in distribution but has rare events. E.g. if the denoiser was trained on lots of cells that were never dividing and then was run on similar image with dividing cells, it might remove the dividing cell and replace with a single cell." From bb724b88f86d1baa0af48cebb1923a38c20e5493 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 01:41:04 +0100 Subject: [PATCH 07/51] added two tasks to train the denoiser on both MNIST and FashionMNIST (shuffle off, then on) --- solution.ipynb | 847 ++++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 739 insertions(+), 108 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index 5b5b5cb..ac7fc94 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 4, "metadata": { "tags": [] }, @@ -146,7 +146,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -277,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -296,16 +296,16 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 56, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -341,7 +341,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 8, "metadata": { "tags": [] }, @@ -363,7 +363,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -378,7 +378,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -537,7 +537,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 11, "metadata": { "tags": [] }, @@ -574,7 +574,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -607,7 +607,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -633,7 +633,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -647,7 +647,7 @@ ")" ] }, - "execution_count": 63, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -682,7 +682,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -704,7 +704,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 16, "metadata": { "tags": [] }, @@ -712,7 +712,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "996b2277ba244ab096d8643e29e09afa", + "model_id": "91699482c5454723be50c26d8b71196b", "version_major": 2, "version_minor": 0 }, @@ -726,7 +726,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c831693f101540e6ab8dda9eab628212", + "model_id": "a23353d0ffba43eabf36403692eddaed", "version_major": 2, "version_minor": 0 }, @@ -740,7 +740,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8591952230944c349a220a18d782c791", + "model_id": "c22485a1444c436c893bb07e4862726c", "version_major": 2, "version_minor": 0 }, @@ -754,7 +754,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fd4b1b01a931403089d03c5744b5d83d", + "model_id": "c5ba077ee6894b979bb00d4fdb57595f", "version_major": 2, "version_minor": 0 }, @@ -800,7 +800,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -809,7 +809,7 @@ "Text(0, 0.5, 'negative log likelihood loss')" ] }, - "execution_count": 66, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, @@ -976,7 +976,7 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -1006,7 +1006,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 19, "metadata": { "tags": [] }, @@ -1028,7 +1028,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -1089,20 +1089,20 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_1517553/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" ] }, @@ -1347,7 +1347,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 22, "metadata": { "tags": [] }, @@ -1390,7 +1390,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -1439,7 +1439,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -1514,7 +1514,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 25, "metadata": { "tags": [] }, @@ -1594,7 +1594,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -1769,7 +1769,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -1790,12 +1790,12 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 28, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAcg0lEQVR4nO2debSVVRnGX4QEJxAlkkkQB2RQEBUBQcUB5MoMBoKiYUmrcLmipUtdlLbKQtM0c8zKokFgqRCiFyRAmS+KJHAZBG5AoIkDiGYmkP33tZ/f6Q4MB+6F5/fXftY+nHvud75v381+3qHaF1988UUYY4wx5rDmiIP9AYwxxhhz8PGGwBhjjDHeEBhjjDHGGwJjjDHGhDcExhhjjAlvCIwxxhgT3hAYY4wxJrwhMMYYY0xE1KjoC6tVq5bPz2H2M/moN9W2bVvRzZo1E/3222+L7tu3bzZ+8803ZW7ZsmWi27dvL7pdu3aia9TQW3Xx4sWiGzVqlI23b98uc8XFxaK/8pWviK5bt67olStXin733XdFn3HGGdm4ZcuWMrdo0SLRTZo0Ef3lL39ZNK9L7dq1RafXgdf3/fffF3388ceLHj9+fOQDrwVVi3ysBSeeeKLo7t27i/7oo49E//Of/8zGmzdvlrkLLrhA9K5du0SXlJSIPvPMM0W//vrrogsKCrLxCy+8IHN8HtN1IyJi06ZNohs0aCCaa0WqP/vsM5nj88lrwvVz+fLloo84Qv+/fswxx5T6uXbs2CF648aNoufPnx8VwScExhhjjPGGwBhjjDHeEBhjjDEm9iCGwBh67yeccILohg0bik59rNNOO63M186ZM0c0/bV58+aJpl+XeoUjRoyQOfqb48aNE33ssceKpo9fp04d0ak3SK/uX//6l+jZs2eL/v3vfy/6448/Ft28eXPR6XVat25dqXMRFfcJjdlX+Ezx+WzcuLHoNLbmoosukrlTTz1VNNcC+vwtWrQQ/aUvfUn0hg0bsvG5554rc0uWLBHNdYbxQ59++qnoAQMGiF6zZk025rPP9bJevXqi586dK3rbtm2iGStRv379Ul/La8i1uaL4hMAYY4wx3hAYY4wxxhsCY4wxxkREtS8qmKTq3OOqRT5yj3v27Cl61apVos8777xS54cMGSJzH374oWjWDvjb3/4mmrUArrzyStGpl0/vbtq0aaLpKzI/mB4lvb609kBRUZHMderUSfRxxx0nmt8Lc65Zp+Dyyy/Pxow3mDRpkug01zsi4vnnn4984LWgapGPtaBPnz6i+cx98sknotPngDVFtmzZIpprAZ9Hxs4UFhaW+vo33nhD5rhulBeXQ6/+P//5j+g0lol1QLZu3SqacVSspcKf/fe//1307t27szFjBrheMu5iypQpURF8QmCMMcYYbwiMMcYY4w2BMcYYY8J1CMwewJxd5u+nHleE9j547733ZG7FihWiTzrpJNH09em/sa5/+v6sCX7ZZZeJZm2Ak08+WTT9T/qGaR1x1mHn78HPyfdq06aN6DSHOiJi9OjR2bhr164yt3TpUtHM7zYmX9Dvrlmzpmj652nNf9YNoB/OteLzzz8Xzbr9/Pf/+Mc/svEpp5wic+vXrxfNGJ6ZM2eKZj7/hRdeKDqtKzJ8+HCZmzFjRpk/q1atWqIZA8SaJGn/iNatW8sca6cw/qCi+ITAGGOMMd4QGGOMMcaWgdkDmPrH9CAe66dH2jwe27lzp+hzzjlHNNOFeHzG8qZput/5558vcyxHmqbyRWhb0YjcssicT8sks6zxO++8I5rpWUwPWr16tWjaMmkaIi2Cbt26iWa7VbNvMD111KhRotMjYpbD/sUvfiGa93NVh2mGPKJmKmFqITA1lxYdWxTzmZk+fbroHj16iE5tOdoTH3zwgWimBdN+OProo0X/+9//Fv2jH/0oGz/00EMy17FjR9Fp6eGI3LbNnOc6llqdtEVpVXbu3Dn2Bp8QGGOMMcYbAmOMMcZ4Q2CMMcaYOAxKF1evXl00Pd/yoG+Yekosqfntb39b9P333y/6mmuuEU2veuzYsaJ/8IMf7NFnTclHudKhQ4eKpo9/4403ik7bgdLHZ7xBcXGxaLYKffXVV0V36NBBdJqatHbtWpnr16+faKYSMd2HLU/5+vR7Y+rlpk2bRDPlkeVNGXPAdK2//vWv2ZipmEypeuutt0S/9NJLkQ+q6lpQHu3atRM9a9Ys0UztKgt+V2nK2IEmH2vB7bffLprX5qmnnir19XwGeJ8yffmoo44SzXLDTEtM0535PPFzMoaAsRAXX3yx6FdeeUV0mnaYtkKOiJg4caJorg2MIWC6ZUFBgeg01oLln7lmbd68WTTTvEvDJwTGGGOM8YbAGGOMMd4QGGOMMSaqSB0ClpY98sgjRac5l126dJE5+lUDBw7cb5+LPs3DDz8sun///qLZvvbNN98UTZ+8ssH4C3p78+fPF53m4dJDZT4vvXjmJrdq1Uo0Wy2nfP3rXxfNNqO87ry/mjZtKpq+Y1qS9LbbbpM5+oL0JFnToKSkRDTjMtLaArz+zM9maWNTNoxDee6550TzetOLT59n+ti835mTzroE/PeVHca+LFmyRHTjxo1F/+EPf8jGjL1iDj3va+bcs7YH15309YxdGjBggGjWGTj77LNFs0Qw8/sXLlyYjZ988kmZY60Vxozxb9Mll1wi+qyzzhKdxgixJDrbpvMaVhSfEBhjjDHGGwJjjDHGeENgjDHGmKikdQjKywfe01oC+5O0TvaIESNkjr43oe+2bds20cxj3RfykXvMOt9s/UsfK22ROnfuXJljXwT6afTa6Rvy2hUVFWXjb37zmzLH74V12On1Pf/886LTdqoR6o/++te/ljm2IKZ3TO+PsRR/+ctfRHfv3j0bFxYWyhyvP+MwfvWrX0U+qCp1COgPt2/fXnTqa0fk+t78PflMpXEA9913n8yNHz++zPcaM2aM6J/85CeRL/KxFjA+in002B457SnAnHn2LmCsFb9H/nvWEkjz/en5f/jhh6LTVuYRuWvDGWecIZrPZ+rzswX0Aw88IJprWFqnJULXsIjc+KP0OvFZ589mnZdbbrklKoJPCIwxxhjjDYExxhhjvCEwxhhjTFTSOgSs+cwe1vszhoC+zfbt20Wz53yaL5zWsT4cYH/4HTt2iE7jKyI0F5teHPN9+R0vWLBA9NSpU0Uz5/5rX/taNv7d734nc4w3YJ/xNm3aiGZvg9NPP110Gv/Qs2dPmeM14O/Bn71o0SLR69evF53GL7CuOp+TqpbLnm+YF85eIvtKGpNAT5c1RZhjzvu/qsHYF/r4jAlK64aw3gNrd3Cd4TPF+5wxEmlMUN26dWWO6z3XnWnTpom+9dZbRbOOQZrv/+ijj8rc5ZdfLprxDPzcvA6kefPm2ZjXm7VVHn/8cdGOITDGGGNMhfGGwBhjjDHeEBhjjDGmksYQMFeUPk6vXr1EL126NBuznwBJ+8tHRFxxxRWi6R+zlnVFvZhDEebz0xOrXr266LR3OGtLrF69WvTGjRtFX3XVVWXOMy4graXO72jZsmWiX375ZdFPPPGEaHp7w4YNE53mKs+bN0/mGCvBHGvWmiirL0eE1nmvX7++zDEfm70lDkdS/5n3UHn1E+j7v/DCC6Lvv/9+0WlNiXQNisi9Py+99NI9+iyVHfr6rBXAWvppzQauuezrwGvZqFEj0ew9smvXrlI/G+sjMK7kwQcfFM3YB8Y7sM4IvfwU9lhg75s0JiAi9xpyLVixYkU2Zr0EXrM77rij1M9VFj4hMMYYY4w3BMYYY4zxhsAYY4wxUUljCMjkyZNFs7dBWvu6bdu2MnfjjTeKpg/ImAFSXFws+qabbirz9YcyrVq1Es1+AyUlJaLTGg7Tp0+XOXqo9Nrr1atX5meh35bWBf/tb38rcy1bthS9du1a0SNHjhTN+Ab6dffee282HjhwoMyxNsC4ceNEP/LII6LZ44Ee5jPPPJONBw0aJHPsI79u3bo43GBsyowZM7Jx7dq1ZY6xIewNwToFrPvA/gNpr4j33ntP5pgXTs+d8Q3ss0BfvbLRqVMn0ZMmTRKd1h2I0OeTuf9XXnmlaHrvXKMZF8DaHWmMwuLFi2WuRg39k8dniO/FfgKMjUjXMcY5NW3aVPT1118vmj1XBg8eLHr27Nmi05gDfg7e24ybqig+ITDGGGOMNwTGGGOMqSKWAWHJ3JSPPvqozH/7jW98Q/SECRNE82jP/A+WK2WqC9MS0xRPtpZ97bXXRDNVkPYDUxpZmjNN67r66qtljt/xddddJ5r3E+0Llk3u3bt3Nub9wn/L8qVMoWWabFnH2LQTeHTKFMZDEaZ18nqmZc15fdh+nCWuef+++OKLZep9gSmi3/3ud0Uz1bWyQTumb9++ommFpa3R+SwzzZzH9KeccoroFi1aiE5bK0doS2LaDWzhTkuY1k9afj0i4tlnnxWd2gIsqcw0YbZ8p0XANus89q9Vq1Y25r3NEvsbNmyIvcEnBMYYY4zxhsAYY4wx3hAYY4wxJqpoDEFZ3H333aLZSpOpRPR4WdbW/A96ZAsXLhTNlJ7U1+Jcs2bNRD/00EOiu3fvLppe3vDhw0Wnnho9SXp5TFtli9QGDRqITv3PCPWizznnHJmjd7pq1SrRHTt2FM34BJKmn7Fs6vLly0WzdfehQM2aNUUzbbigoEB0moLMe4TtZStTqWeW463s0N9mmiRjDNL20ExBZsol0/X43owDGDJkSKmvZ1rh008/LZopyEyXZJtqxhikvxdjG2bOnCmaMQJMcWRaMVOr07WD14T3cocOHWJv8AmBMcYYY7whMMYYY4w3BMYYY4yJiGpfsOZhaS+sou066TfRe6HvynKR9B0fffTRbFzBS3dQyMdnu/nmm0XTt0rLxkZoyV+WPabXfvrpp4tmTjh/FnOTi4qKsnGXLl1kbs6cOaLZTvWII3Rf3LBhQ9GMSUjzidOSrBG5dQkYK8Hfk6WM+dnT92NsAz1J3rv0O/cXB3ItYMwF202Tyy67LBuznfHBZPfu3aL5fDIep2vXrvvtZ+djLRg9erRo/n4s45vGygwdOlTmPvvsM9H04rds2SKapY5XrlwpOo3bYe0UtivmOsL8ft5DP/zhD0VPmTIlG2/dulXmWNqdLbD53rwOvAfSa8rvlKWMWX+Ba0Np+ITAGGOMMd4QGGOMMcYbAmOMMcbEYRBDQPr37y+aean0mMidd96ZjdnalrXSDyb58A2vvfZa0Wxjyjrzn376aTamp8Vrxdrb9PGZH8w8582bN2dj/u78Tum38b1Yt4AttNOa9vQ3y+rnEJGbH7xz507RzLtPe3OwVwHrQvAa//nPf458cCDXggULFoi+4IILRNOHpU9bWeA9yVgT/p6VPYagT58+ovk8M04nrbNAzz9t61sRTjjhBNFsNZ32NmC8AesnsOYB6xKQNWvWiG7btm2pr33rrbdE33XXXaI7d+4s+k9/+pNo/n3p0aNHNp42bZrMpf0bInLXuMmTJ5f6OVN8QmCMMcYYbwiMMcYY4w2BMcYYY+IQ7GVQHpMmTRJNz+hnP/uZ6DSvOSLixz/+cTam/3TPPfeIpr9c1aHfzXiMiRMnik5jCuidr1ixQjT7BSxdulQ0rzW9+R07dmRj1hVgnXj2W2d8Ar2/RYsWiU77YdCroz/Ke4Cvp/fKvOi01wZz1dknYX/6zgeLXr16iW7Xrp1o+uFpHnhlhjED/D14P1d26tSpI5o1L9gjZv78+dmYMTusr8Fn5uqrrxb9m9/8RnSbNm1Ep3EC1atXlznWP1m3bp1o1gJo2bKl6BtuuEH02LFjszFjrMqrZ8KYAcZCpH0SIiImTJiQjTt16iRz7ItQXixEafiEwBhjjDHeEBhjjDHGGwJjjDHGxGEYQ0DoZX/1q18V3bt3b9Fp3YKRI0fKHOvUX3HFFfvjI1YaSkpKRNNfo6+Vet6su08fnzX/e/bsKZrxCfQwU89yyZIlMsefXZ63t23bNtHsV5DGAfCaMIaAddnTugIRuf4nPczUa6bPfO6554pm/EFVhD0rWHuB9eJTX/VgwvoRd999d5mvnzVrlug77rhjf3+kvPLxxx+L5vNYo4b+aUm/1/Hjx8vcmWeeKbpevXqi2SOFzwy997Q2AHsP3HbbbaILCwtF81lnDALjF9K4AfZNSHu5RJS/5vHe3rRpk+jzzz8/G/MasmdP69atY2/wCYExxhhjvCEwxhhjjDcExhhjjInDsJfBvpL6RPTJdu3aJTqtPR0R8corr+Ttc5F81C+/6aabRNPvZq71SSedlI2ZU0uvjrnH9MsZn0Fvr3HjxtmYPRUefPBB0U2aNBGd1jCI0FroERF169YVfdppp2Vj1jhgP3XWGWB8AvO3jz/+eNHbt2/PxqzVwHrxTzzxhOh83AMR+V0LmHP+zDPPiKYPezDjJtK4gTFjxsgcYwJ4f/NZmj59+n7+dP8jH/fB4MGDRTMOh2tjWtvjvvvuk7m0N0hEbg0DrhWM+2I9jlq1apU6t3v3btGMGWM+/zHHHCOavW9uv/32bDx06FCZY90Q/mzWxGEcBmMnCgoKsjHXjW7duolmT5W0fk5Z+ITAGGOMMd4QGGOMMcZph3H22WeLHjRokOg01SMi9ygshSlnc+bM2cdPV7ngcTevBW2BNDWJrXlZLpjw6J1lednaN7UJeKTI77BVq1aieTTH1q7Lly8XfdVVV2XjxYsXyxxLXbOFKUvxzpw5UzTtifRIfPXq1TLH49BrrrkmDnUOZqlifne33nprNuYROu/PgQMH5u1zHQxYxpzPPq2ctAX5vHnzZC5tkx6Ra5+MGDFCNEuTs7Vv2iKbrZKZBlxcXCyaNhxheeK09DFbWL/77ruiuQbSbmTaYWpNRkS89tpr2XjYsGEyxzWPdm5F8QmBMcYYY7whMMYYY4w3BMYYY4yJwyCGgJ7RqFGjRA8YMEB0mipXHkwjYYoZ0/CqOkcffbRolupkOlqaasQyu4w/oJfHNK2pU6eKZlwAr33K7NmzRad+ZoSm80Tk+vgsQfr4449nY6aa0ten3rBhg+jUh47IbY+cfhamdrEEc1Vrofv/4D1E3a9fP9G33HJL3j7Ld77zHdHf+973RKdpYn/84x9lbvjw4Xn7XJUBPkNMz+Na8dJLL2VjlnTfvHmz6DQGIELbjUdEPPbYY6IZr7Bx48ZszOeTXjtTMvl88u8FS6qnpZGZzvz555+LZsosy56zZPOll14qOk2/5DXjz2ZMR0XxCYExxhhjvCEwxhhjjDcExhhjjIlDJIYg9f2Zi00PiC0n95TXX389G99zzz0ydzBzpA8EH3zwgWj6+EuXLhWdel6vvvqqzHXs2FE0Pa+0FHFEbg44W6amLVDZhpl5z8wHprfXt29f0SwZnHp/rGnAmIFLLrlENGMj6D2T1KtlDEGvXr1Es+xqVYSeLjVjfB5++GHRaXta3q+856677jrRadvciNx7kO1o03x5+tqHOrzXGNvB7yX1+YuKimSO153tyhl/xLLQrBMyf/78bEzPnyV92Y6cdUWYz//AAw+ITmutcP3n78F1iXVFuA6xDkG6br3xxhsyx7gnlm+vKD4hMMYYY4w3BMYYY4zxhsAYY4wxUUViCJgHTt/2kUceycb0lvcU+ls//elPRac1yg+1OgPlceSRR4pmzi79ufR7os938803i27durXoE088UXRhYaHos846S3Sal8sa4mwp3KVLF9Fp/EFEbmtRtg6tXbt2qe996qmniqaPzVxjeoFp69YIbQec5ldHRNx7772iGdNxKMK219/61rdEpz0D2NaaLbTLg7XpWc/i+9///h6936EEewQ899xzotN+HxEae8U5thtPa/ZH5MYn8Hthu+S0lgfreqTtxCNy40oY48Offeedd4pO+zAw3oDxQ2nNgojcHg2MKUjruETodRo9erTMTZs2TTSfk4riEwJjjDHGeENgjDHGGG8IjDHGGBOVJIaAftSTTz4pmjnozZs33+ufRf+JeaXsxZ3m0h/u0COjV1+zZk3RaV0C+vZpH/GI3JzbNm3aiGZtAPq5v/zlL7Mxc4+Z63/99deLTnsTRETMmDFDdJprHBHRoUOHbMx+Dmk8S0RuzvSSJUtEn3feeaJZa2DWrFnZmNefsTWMZ6iKLFy4UDT95PLiJNI6Bbw+hPEd48ePF53PPglVHcb4MDaGz0zXrl2zMddU1ntg7MeaNWtEM36oZcuWolPvPo1diND4n4jc2hI7d+4UPWbMGNFc8xo0aJCN0/oH/++1/fv3F826LewHwRi1dM38+c9/LnOslcJeEhXFJwTGGGOM8YbAGGOMMd4QGGOMMSYOUAwB+1uzB3zqyUZENGrUaK9/VpoXGpFbU5s55axrb0qHfneNGnr7PP3006LTmhD0GNkr/MILLxTNGvb0e5966inRkydPzsbsj07v7ogjdB/MOBLGBQwZMkT01KlTs/HJJ58sc4MGDRLNmgb09uiRV6tWTXTqDbKPPOMNtm7dGlUd9nkfMGCA6JEjR4qmx1sW9F0ZO8K4FlM6TZo0Ec16Gszvf/HFF7MxY13opTNGjDFmjAsYNmyY6HSd2rVrl8wxZmDZsmWiuc7weeU6lvr+XGcYU8X35t+5iRMnimZfnvr162dj1tth7FtxcXHsDT4hMMYYY4w3BMYYY4zxhsAYY4wxEVHtC5q1pb0Q3uaeMHbsWNGMISiPlStXik493Aj1iegHs3b14UIFv9Y9YtSoUaLZ26Bhw4ai586dm40vuugimaOPz/xz5pCzxv+2bdtEr127NhvT92NeM3ugMw6Avj9r4KdxKu3bt5c51h9nPML7778vmjXHGZeReup9+vSROdY+5zWjR76/2Je1wBx48rEWDB48WDTjWY477jjRaR1+PiOsMcJaHczPLygoEP3yyy+LTmMQ+LnGjRsn+tprrxXNGgns18JrmdYt6NSpU5mfm3+3WGeA9RT4tyut/cA1jLESjNu76667oiL4hMAYY4wx3hAYY4wx5gBZBubAk49jQrbrZLoQyw+nx+Msu1u3bl3RPOZn+WGmhLFdclp2dv369TLHo7tu3bqJZrpeeSWaU2ukadOmMse0JJYzpa3CI0mmJqWpRuX9LFoGTNHbX3gtqFrkYy1g+WCWl2dacfq8c473LcsH8+icaYf892l6LtNYJ0yYILpt27aimYbO55WtmtOUSKZT8vdgGiLfm1Z6s2bNRKfXoXPnzjLHltJcRypahtsnBMYYY4zxhsAYY4wx3hAYY4wxJipJ+2NTNWBaDD2yLVu2iE69+7T9aURuTADjEZgKSC+e3mCaAskYAab60V8rKSkRzdatLNOaevf0Nz/55BPRTEtM2xlH5F5DlklOS2/Tg6QXy9gHY/IFS8TXqVNHNNNp03uX921Z6XURue2P+TyW1UKcKev9+vUTzXQ9PmP892lMD//9O++8I3OM8XnsscdEMxW7d+/eonmd0vWUsUcLFiwQzbgoxxAYY4wxpsJ4Q2CMMcYYbwiMMcYY4xgCswesWrVKNL15xgm0aNEiG7P17MUXXyy6sLBQND0ylg+mz5iWJy6vDgF9Q5ZCXbRokeiy8u75XrVr1xY9adIk0TfccIPoKVOmiGYcxsCBA7MxWyXz+2DLU7b6NmZ/kT7bEblleFn+u0ePHtl4zpw5MldUVFTqayNy42wYQ8Dn/e23387GbJ181FFHiU7Lq0dou/GI3LWDvn4ay8RrcOyxx4pmm2Y+z6wb8uyzz5b6fmzxzpbRextP5BMCY4wxxnhDYIwxxhhvCIwxxhgTe9DLwBhjjDGHLj4hMMYYY4w3BMYYY4zxhsAYY4wx4Q2BMcYYY8IbAmOMMcaENwTGGGOMCW8IjDHGGBPeEBhjjDEmvCEwxhhjTET8F3Fc4YKWtUkBAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1805,7 +1805,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAaaklEQVR4nO2debSWVdmHtymCICBKTAcVUEFAGWUQUBlCRAEDRdMcQmu1aqEktVaTVraWCy2jgqyMpHLAiQw1lbEgBk1RImRIEwwERVNwShDU/vjW97Tv6/UczlEO43X9tX9rv+95n3d4Npt93/fvPuCDDz74IImIiMh+zSd29wWIiIjI7scNgYiIiLghEBERETcEIiIiktwQiIiISHJDICIiIskNgYiIiCQ3BCIiIpJSOqiyDzzggAOq8zpkJ1MdflNDhw4N+ogjjgj6T3/6U9Bf+9rXivH69evD3DvvvBP0u+++G/QhhxxS4bWUlZUFvXr16mL8xhtvhLnLLrss6J/97GdBb9++Pei33nor6CFDhgQ9Y8aMcq+rffv2QT///PNBr1u3Lui+ffsG/dJLLwX95ptvlvtaW7duDZrfx+23317ucz8OrgV7F9WxFowYMSLoiy66KOjZs2cHfdxxxxXjVatWhbmTTz456EmTJgV9+OGHB123bt2ga9SoUe58gwYNwtzrr78eNO+3T3wi/h+Zn92WLVuC7tChQzGuU6dOmON62L9//6AXLVoUdK9evYJ+/PHHg+7Zs2cxfuaZZ8Lcf/7zn1QRU6ZMqXD+//GEQERERNwQiIiIiBsCERERSVXIIRBp0aJF0B07dgz6ySefDHrt2rXFeMWKFWGuU6dOQY8bNy7ok046KegjjzwyaOYQ5LH5pk2bhrnx48cHncf9UirNGWDMknHD/LWZI5C/55RSatiwYdD16tUL+tVXXw2a137ssccW45UrV4a5T37yk0H/85//TCK7gpEjRwb961//OugmTZoEPXPmzGLMeDfj+ieeeGLQjOsvX7486AsvvDDoPB/p73//e5jjvc8cA14b83KWLl0a9G233VaMe/ToEeaYm/T0008H3a5du6B///vfB833deCBBxbjtm3bhrmNGzcGvXjx4vRR8IRARERE3BCIiIiIGwIRERFJKR3wQSWLVK093ruojtpjxrTy2v+USuuBcz+A448/Psyxhp6wPpg1vPPmzQv60EMPLca1a9cOcwcdFFNl3n777aAZ53/ttdeCPvjgg4PO38uf//znMEcfAvoIMEeA31Ner51SStdee20xHjNmTJhbtmxZ0M2aNQv6xz/+caoOXAv2LqpjLRg1alTQc+bMCZq+Iuedd14x5r392c9+Nujf/e53Qffu3Tto5umwJv+ss84qxps2bQpzvB9feeWVoBmbb9WqVdB33HFH0Hl+UcuWLcNcrVq1gt62bVvQzPnha2/evDnoF198sRjTp4VrGj1jRo8enSqDJwQiIiLihkBERETcEIiIiEjSh0CqQP369YPOa+RTSqlNmzZBL1mypBjTl3v48OFBM/8gj5elVBpPGzx4cNB5DS9roM8888xyryul0v4CjPXRlyCv8e3cuXOYe/bZZ4OmnwLjp4x/vvzyy0FfccUVxZixVcYJ16xZk0R2BbzHbrrppqAfffTRoN9///1inNfTp1Tqs8/cmD59+gQ9cODAoNkXJb9/J06cGOby/IKUSvOD6HHAdYseCbk3CL1WmNPDteHoo4+uUHO9PeOMM4rxvffeG+bYH4IeMZXFEwIRERFxQyAiIiKGDKQKsF0nrTp5TNilS5di3Lp16zD3wgsvBM0SnH79+gU9ffr0oGn7OWjQoGLMY7777rsvaJYh8giSx4Yss8vbtU6bNq3Cv82yJto/88iS1qj5Uesll1wS5lhS9e9//zuJ7AoYvmrUqFHQtBu+8847i3EeBvuwv8WjctrwMsTHEub8tU899dQwR6twvhZDAo899ljQDPnl9+R1110X5po3bx40LdB5v37lK18J+gc/+EHQeZiA5ckMs3xUG3NPCERERMQNgYiIiLghEBERkaR18T5LddiVMobNtsGMG+YWwCy/Y/yMpUO04mSpUh7HTymW3dA2tWvXrkGzTTPbkp577rlBsy1p3rqZuRGTJ08Omm1iaffM98H2q7NmzSr3tfh5M1+BpUk7i311LbjqqquCvvjii4NmyRpLY/dUqmMtYNkw4+X8bPL7d8CAAWGOcXq2DWaOD+9H2gvTMjiH7Yz52dC2vHv37kGznXJ+j9G6OM//Sam0XTnzFZiDxc8pL6ekBfott9wSNH+7tJ0vD08IRERExA2BiIiIuCEQERGRpA+BVIGePXsGzdh7nTp1gs7rg1kPfM899wTN+vyKWn+mVGonnP991vbnNdAplcYNmd/AdsjdunUL+qijjirGfM87shOmvwLrhVknnXs5sB6b1tHMw5Cqcc011wRdr169oPPvPaW9J4egOthRTT3v51zTnrtu3bpBMxeG93ODBg2Cpv137kPC2DnXDeb00FuF7ZKZB5DbE/M9M87P3IcOHToEzdbpjzzySLmvzTl+JszLMIdAREREKo0bAhEREXFDICIiIuYQSBW4++67gz777LOD/uMf/xh07dq1izH9ytnqk3HEvP4+pZT69+8fNOuFFy5cWIxZ39u2bdugmfvA+Ofzzz8fNOuJ85yChx56KMytXbs2aHoH0AOBf/uwww4r9/H8DNhulc+VqsG8FeYQyP8oKysLum/fvkEzhp0ze/bsoHmP8HNn3xPeM7169Qr6tNNOK8YPP/xwmGvcuHHQrP3nmkZfEa4leV+GcePGhbkf/vCHQbP3CPuz5NedUmnOSu47Qn8E5irxt1xZPCEQERERNwQiIiLihkBERETSPpJDkMeg6DdeVViLzH7ZFUFv+SVLlgTN/tZ33XVXFa9u98JYHd8fY2R5nJ9+5OxV8Ne//jXo008/PWj2J2C9fpMmTYox44Ssa2a884knngiaMczevXsHnfcfWL58eZhjzfSoUaOCpv8CfzOMaeZ9A5jrwBijPgQfj4kTJwbNGLD8D/72GLN+7rnngs7zctq0aRPmFixYEPQ3v/nNoGvWrBn03Llzg2Z/gS9+8YvFeNmyZWHuvffeC3rw4MFBT5s2LWjmPn35y18OOr/nDj300DA3b968oNljgR4m9FNgjkGeo0BPgz59+gTNniiVxRMCERERcUMgIiIibghEREQk7aE5BPTMP/LII4OmL/75559fjOlVvSPY250+91XpJc76WHpVs6aVPtmsad/TeP3114Nmz23G8hYtWlSM+Tkynsbe3+3atQt6ypQpQTdq1CjoPPeDHvO5t3lKpbXJl156adDr168P+pBDDgk670vO3w9zAhgHZK4EH8/64jxHgX0POnbsGDTjoyLVxVNPPRU0+4GccsopQeeeGS+99FKYa968edCMj/MeI4yXX3fddcWY+UAHHRT/yWMPAPqhcJ1izkGeJzVz5sww98ADDwTNHINjjjkmaP57kedFpRTXV+ZwvPHGG0GzX0Rl8YRARERE3BCIiIiIGwIRERFJuymHgPHi73//+0Efd9xxQTMvYEdx/6qQx7k/LqzTJ6xRZ2x6T4dxwhtvvDFo+nznuR30Lz/wwAOD7tevX9CLFy8O+jvf+U7Qt99+e7mPZ87AlVdeGTS9Jdi7YMaMGRU+Pq89Zpxv1apVQdMXg/3Ur7766qAZs8xjoJxjT3TmH0jVGD9+fNDMCdpRLHt/gnkArKFnrswXvvCFYrx06dIwx14FXEdatGgRdN63JKXSvih5rH3o0KFhjv4leT7Qh70WvSlInhdAvwR6rzAHiPkMW7duDXr16tVB52tN165dwxx7GTRs2LCiyy4XTwhERETEDYGIiIjsppABQwA9evSo0vMraoc5YcKEMLdu3boK/9bUqVOr9No5bDfL4yjCY7WKWoTuifCz4vdIS9L82JAlljxqp90wSxhZokN++ctfFmOGpFjOyZBCs2bNKvzbt912W9CtWrUqxgyFsDySFs0MT7CM6W9/+1vQ+edE6+IuXboEfcQRRyT56DBE8OCDDwbNUrv9mauuuipotvXmsX/+2TF0ynblNWrUCJqP57F+06ZNy/17XP9p8cuW7rntcUopPfvss0HT5jwveWRIj/f6v/71r6C3b98eNNfXM888M+i8RHn+/PlhjiFXhhsqiycEIiIi4oZARERE3BCIiIhI2k05BCw7YWyF7S3ZwvInP/lJdVxWpcjzBmbNmlWl5/72t78NmrkQezrMmchj6SmVliLlrUNHjx4d5hjbY7yWlqKME7IcKI8bsvSP+Qq0NmZsnu2STzjhhKDzMkS2Ur711luDvuGGG4K+4447gmZeyZgxY4LO8xcYO2XMkiVUUjH8PEne5jql0nJotr7en3jrrbeC5tp2+eWXB/2Pf/yjGDNnhzkCLKdlrH3jxo1Bs5Q3b51Ou3Xm9JxxxhlBs/SUeVJ8rTzHgH+LVsUsteb6ybJhlsTnZYrt27cPc/fff3/QbBdfWTwhEBERETcEIiIi4oZAREREUkoHfFBJ39/91baT8a68pp3tKtnKljWun/nMZ3by1ZXPx7FzLo+WLVsGTVtexgJXrlxZjLds2RLm2PKULa7Z0pStfelTkMfnGOfjdbHWv1u3bkEzL4Bx/9wTga9FO1LmK/B9MI7NfJn879GrgVaorOemJfjOYl9ZC2i9zdp6xnA//elPB70j35E9hepYC0aNGhX0pk2bgqbNOdvz5jC2TtvyL33pS0EzT6d27dpB5/ck70/mCzFHgJrfMfPdjj/++GLMe5efyTnnnBM02yMzh4C+LnlbduZw8N8p+qPQS6U8PCEQERERNwQiIiLihkBERETSbvIh2JsYNmxY0HmclrE51r9/4xvfqL4L2w1ccMEFQd97771Bn3vuuUHnLToZy2N71EcffTToU089NeglS5YEzbameYzsoosuCnMzZ84M+rvf/W7QuV9CSqX+Emxrmsc86RlOvwTGJFesWBE0+w+0a9cu6A0bNhRj1hYzZyB/rHx86BOyt+QM7ApY389W7s8991zQderUKcb0K2G/AK4V9HvI24+nVJqvsHnz5mLM+5E5PMyHyZ+bUkqdO3cOmvd7fj/T44B5UOxzwmuh/wl13keB18V/e/i+K4snBCIiIuKGQERERNwQiIiISDKHoIQBAwYEff3115f7WPa7ppc1a1b3dhgnvOaaa4Jm7D2PM9KjgfHw1q1bB80a3c997nNBsxZ57Nixxfiuu+4Kc+zNft999wW9devWVBEjR44M+s477yzGHTt2DHNr1qwJulOnTkEPHDgw6Nzj/cOeX69evWKc1zynlNL06dODrlu3Li9dMuh1Qd8B9kj56le/Wt2XtNdCDxb6b+R+LSnFe5BxevaI4DpDrw72JmH+UX5PcZ1h/f75558fNHOb2GOld+/eQee5EkcddVSYo1fKt771raC5xjFnhbkVeW4U86KYV1FWVpY+Cp4QiIiIiBsCERERcUMgIiIiyRyCkrhiHotOqbSndR4zopf/vpYzQOhHnvcqSCml+vXrB533PmBsfN26dUFv27YtaOZjLFy4MOj+/fsHnccNGdenf/nLL78cNHsZMI7Yp0+fcl+LeSSMf/J91ahRI+inn3466AYNGgTN+uKKrose8FIx9BGpDs//fRXGu/P+HimV/jbzPAH6OfD+Yw4QvTqOPvrooFmTn/c2aNWqVZhjDsFpp50W9OOPPx40/VD4/PzaucYx92HChAlB898Wepb06tUr6HzdyX0dUkpp+PDhQTP/oLJ4QiAiIiJuCERERMQNgYiIiCRzCEpiwDuKI377298uxuxHv69DD3LC2N7SpUuLMWNezAGgT8Ff/vKXoHdU49uoUaNizLrm999/v9zHplSa+8C+9/l3nlKsuc7fY0qltes333xz0O3btw/64IMPDprx0DwWyHwE5mGwD4JIdbGj+Dd/qxMnTizGV199dZij/wN9P9jHhK/NWH1+TzHXgb0I6APy1FNPBU1/BV7LeeedV+5z2SehYcOGQS9btixo5krwfeVeA1zjNm3aFPT27dvTR8ETAhEREXFDICIiIvtByGDIkCFB80iXR9Us8/rFL34R9NSpU3fi1e1d8IiaVrpsiZofa7355pthjkd5eUvhlFJau3Ztha/F47T8yGzOnDlhrkuXLkHXqlUraLappi0ynz9//vxizNartFFlSCC3Ik6ptASLrz1ixIhizGNAHhOybaxIddGmTZug+Tunzsv7WPbLEkWW9jFEwHbIbDOchwSfeeaZMEfLZR7bT5o0Kegrr7wyaIb8fvWrX5X7WJYwMlzBECtLrVk6mJcon3zyyWFu7ty5QTMUUlk8IRARERE3BCIiIuKGQERERNI+mEPA0o2vf/3rQTP2wpI0xnBpN7k/w9I/WhkzNp+3HmWuBlsOs00p2waz/KdmzZpB56WD/A2wNShjd+PHjw+a7+vtt98O+pRTTinGM2bMCHP8DBizpFU2r6179+5Bn3DCCcV49uzZFT6W1zJmzJgkUh0wzk9r8Q0bNgSd/44XLFgQ5po1axY023jzd/7iiy8GzdyaPNbOtYDW4rkVfUqlbYW5zvAezK3GmY9Aa3e2TmbJ+29+85ugTzzxxKDz9Zc5AlxnPmo+kScEIiIi4oZARERE3BCIiIhI2kdyCAYMGFCMGQ9m3ShhXIf2k/I/2rZtGzR9CebNmxd0HqtnnJA1tvweWJ/PXI/NmzcH3bhx42LMlsLDhg2r8LUZj2vdunXQzHfI66gZ72QLbOYMsLUyP0PaYefeDrTVZvyT9dgSufHGG4OmtWzuLyEVw5wexurznIGUou056+15L1PTapzrDNubb9mypRivX78+zPE7Zw4P3wfthrkW5GsivVLY6pz3K71X6O1Ae+Lc44RrFH+7fF+VxRMCERERcUMgIiIibghEREQk7aU5BIzLjh07thgzZ4BxG7ayfeyxx3by1e27sG52xYoVQX/+858POvcRLysrC3OMr7H2n/P0P2dcMY/dDxo0KMyxRrdp06ZB0yOBPuyMl+a1x6yJZoySHHvssUEzFsh2yvnv96yzzgpz48aNC5qfsVQMczLuv//+3XQlex/MfWGs/aGHHgp69OjRxZi5LvTPYDtyrgV8rffeey/o/P6kdwrzDQYOHBg0/71gDxbW9+d9FiZPnhzmmBPA6+TvrWXLlkFzLcnzMmbNmhXm2E6evWAqiycEIiIi4oZARERE3BCIiIhI2ktzCBjLZiwwhzkDU6dOrY5L2i9gTe8555wTNGNkU6ZMKcb0GahTp07QrLnld7pq1aqgWfObxwbzXgMp7Tg2nMccUyr1aWccMs87YW5DkyZNgma8k/kKnOfzt23bVoz5ux8+fHjQ7LmwvzNkyJCg+/XrF/RPf/rTXXk5+xQPP/xw0JdccknQ/B1Pnz69GNOjv169ekGzPp/eMD169Aia3gF5vwHeXxdccEHQ06ZNC5r9CHi/9unTJ+j8nuNj6Z3CHiqTJk0K+qabbgo6925IKa4F+TillF544YWg16xZkz4KnhCIiIiIGwIRERFxQyAiIiIppQM+qCgAnz9wB/XVOxP6wz/wwANB9+3bN+g8vkyfbHrL7y9U8mutEiNHjgyacSzW2NeuXbsYs78A4/zsQ96pU6egmftxxRVXBJ3X3TKWxx7ozIWg7wDzAl577bWg87gk65gffPDBoPM65ZRKPd6Zr0Cdwz4HjJ3Sy6G66up35VrwcVi4cGHQ/H0yr4Wf775CdawFP//5z4Nmfgs9/3PfAuYL0VeG30PNmjWDfuKJJ4I+6aSTgs59Q9hDhWsW8xcYe+/evXvQ/Lfo3XffLcZdu3YNc4888kjQnTt3Dpo5AvQ4YF5ArVq1ijH7rzBfgesM8xXKwxMCERERcUMgIiIibghEREQk7aE+BD/60Y+CZryZ8ZJbb721GO+vOQO7AsbfGB9nvfAxxxxTjFmXfMsttwR96aWXBs04/g033BA0fQzyvAA+l7G9RYsWBX366acHzVgecxLy2N8f/vCHMMf3edhhhwXN3+727duDZn+IPIbZokWLMHf44YcHnfeBl1Loob+v5gzsCpifwlg88wLye4w9OPi7Pvvss4NmXL9du3ZB83vM70Hm2bRq1SroCRMmBM17f/Xq1RVea742cD288MILg168eHHQzMV55513gqbfQp7LtHz58jBHXxbm4VUWTwhERETEDYGIiIjsISEDHm+wDSS5/vrrg2aIQaqHvIwwpdIymtwyNKV4XL4jq2Iet9G+lC2IWeaUhzN4XWx5etlllwXNVqIrV64Mum3btkFv2LChGNMe9+abbw566NChQTOEcPfddwfdrVu3oDdv3lyM2dI0v46USktu93dYVig7jwEDBgTNNZy/zdzue9iwYWGO9/qSJUuCZjktj/25duT35LXXXhvmuO7QlpzrFEuO2Q45LxNm+eO8efOCZst2lhizRJKlm5s2bSrGtH9miIZtnCuLJwQiIiLihkBERETcEIiIiEjaQ6yLe/bsGfSCBQsqfDzjyVJKddiVjhgxIujctjOllMrKyoLOcw4Y97vnnnuC7tWrV9BPPvlk0K+++mrQLBXMY3t53P3DNK2K69evHzSvlbkRgwcPLsZLly4NcywbHDt2bNDMA+D3xNLNvEyR8UvaqtLSde7cuak62Fusi+X/qI614OKLLw6a5bNsO5yv2bkFb0ql9xBL+5gjwBI7xupfeeWVYsx7nTk8tLPmWtC4ceOgWYaYlzgzJ4AlxmwPz3bIzJ3Iy7ZTiqXVzI/hvd6hQ4egv/e976XK4AmBiIiIuCEQERERNwQiIiKS9hAfAtk7YCz98ssvD5p1s3kMjC2I2d6YFqOf+tSnKpzna82ZM6cYMw7IVqDMKWBsnrH4fv36BZ23NWU9MPMP5s+fH3THjh0rnKcdcd42mu+DVqh83yLVRYMGDYLm/ciWxcydyaFV8Y7uR+Yr8PmTJ08uxoMGDQpzy5Ytq/BvM7+BdsLNmzcPOs8LYNye9s60Fudn1L9//6A3btwYdO6HwtbetFfnGldZPCEQERERNwQiIiLihkBERERSFXwIREREZN/FEwIRERFxQyAiIiJuCERERCS5IRAREZHkhkBERESSGwIRERFJbghEREQkuSEQERGR5IZAREREUkr/BZEaUQ6caLcLAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -1815,7 +1815,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAcd0lEQVR4nO2df7jO5R3HP9RqsmZUGkWhopSKjDK/W2GSIivKUk2ZqR3r15psatcV1360tZaLK40yyrKEFEKRUKRIfrWyMBWziM60yv777n6/np3jHDnOcc779df9vu6n5/me5/l+b3f35/N5fyrt3bt3bxhjjDGmQlO5tC/AGGOMMaWPNwTGGGOM8YbAGGOMMd4QGGOMMSa8ITDGGGNMeENgjDHGmPCGwBhjjDHhDYExxhhjIuLwor6wUqVKJXkd5gBTEn5TN998s+i5c+eKPvnkk0Wfc8452fj111+XuSpVqog++uijRVerVk302LFjRQ8YMEB0+v7p50ZE/Pvf/xbdtGlT0VOnThW9Y8cO0dWrVxd9xBFHZOPPPvssCmPbtm2iDz9cH7nzzjtP9KRJk0RXrVo1G59++ukyV7duXdETJ04U/e677xZ6bfuL14JDi5JYC/Ly8kSfcMIJoo855hjR6TNWr149mfvqV78qesaMGaJ37dolukuXLqL5TC1fvjwbf+c735G5yZMni27Tpo1o/h2vvvqq6Pz8/AKvrUGDBjLXvHlz0c8//7zo+vXri/7ggw9En3HGGaIffPDBbPyNb3xD5po1ayb6yCOPFD1y5MgoCj4hMMYYY4w3BMYYY4zxhsAYY4wxUYwcAmMYL2eMjLH6P//5z9mYMS7G6ffs2SOacc9LL71U9KpVq0SnMctXXnlF5hhjnDNnjmjmPvDaGA/98MMPszG/E8b5Gct7++23Rb/55puie/fuLXrr1q3Z+PPPP5e5ZcuWiW7VqlUYczDYvn276DVr1ohmjLtdu3bZmM9u48aNRXfo0EH0ypUrRR977LGia9asKTrN8fnoo49k7tvf/rZo5sPMmjVLdJrD8/+uLf2sdevWyRzXMOb8XHDBBaKZo8X1NM2bGj9+vMzt3r1bNHMhiopPCIwxxhjjDYExxhhjvCEwxhhjTDiHwBSDNF4WkRszq1GjhuhPP/00G7Oel14AjAsyJsY4/sKFC0U3bNgwG2/evFnm+vTpI5r+Cd/85jdFM5/hk08+EZ3WBzN2Sj+Fl19+WTTjpfwOWeec1jYzLkt/BH5HxpQUjFHzmfnud78retq0admY68Qbb7wh+qijjhLN53fFihWimYeT+hDccMMNMve3v/1N9IsvvhiFQR+Rk046SXT6vFaurP9/vXbtWtH0HXjuuedEM4dgzJgxotP8hV69esncf/7zH9F16tSJ/cEnBMYYY4zxhsAYY4wx3hAYY4wxJpxDYIoBa3YbNWok+itf+Yro1KeAMcYNGzaIZv+BF154QTS9BFhP/PHHH2dj9gdYunSpaOYr8LoZN2TfhTRGyfwD5hQwHrpp0ybRP/zhD0U/9thjolN/86997WsyRw/41B/BmJKE9/1f//pX0RdddJHonTt3ZmPW3+8r1s6cAdbn87m46aabsjF9CJj70K9fP9HvvPOOaObptG7dWnR67fQZYL7ClClTRNObZebMmaKZJ/Dkk09m4+7du8sc8zK2bNkS+4NPCIwxxhjjDYExxhhjHDIwxSA9Ko/IPapbtGiR6NNOOy0b8+iNx9s8Sj/ssMNEn3jiiaJ5rJ8ez9HKlKGO9PgyIvfonSEFWpCmpYMsBeR7tWjRQjSPR9977z3RtINesGBBNq5Vq1YUhtsSm4MFS/26du0qev369aIHDx6cjWfPni1zfAbYophhNdqFH3/88aJTS++0HDki4utf/7roNNQYkRsy4Lozf/580elaw/WP61CTJk1EsxS7du3aoufNmyc6DZuynfxbb70l+uqrr479wScExhhjjPGGwBhjjDHeEBhjjDEmIirtZYC0oBeWk/gkW932799fdM+ePUWfcsopRX5vxs1+9rOfiU7LRkqaIv6sxeLss88WTatclu+l8XPmDLCVL0v7GKNkXJ8Wort27crGaane//tstig+9dRTRbNEsmXLlqKXLFmSjRlTZEnVSy+9JJr2z7Q65vfwr3/9KxszBsk2z7Qrffjhh6MkKC9rQUWhJNYC3gNnnnmm6C5duohO819YNsjSQOYUMFeJLcVZ2ptai0+YMKHA64jIXUdSq/CI3FwllkCmOUO8Dq4rtDHv0aOHaK55zz77rOjjjjsuG9Mm+Z///KdorjPM2ygInxAYY4wxxhsCY4wxxnhDYIwxxpgooz4EjEeNHz9eNGNIaSvc++67T+aYE3DbbbeJZtzngQceEL1y5UrRaTz68ssvl7nrrrtO9KOPPio6bQccETF16tQ4lGBLU8bXGLdK7UzpK9C3b98CXxsR8cUXX4j+yU9+IpqtQdMWxd/61rdkjvG2NC4fkZtTwNbKDz30kOhOnTpl4zZt2sgc65gZS2Xc//333xdNC+fUInbVqlUyV61atQJfa3JhHsqtt95a6OsZ42V8OY2jX3nllTL3xBNPFPretOJmTJ7tbMsa3bp1E03/DD7v6brJdSPNyYnI9fLo2LGjaK4zjM2nNfrM0WH+Av99GDVqlGjG5idOnCj65z//eTam58j06dNF8++44447RA8aNEg074n07+ZrmSvBe72o+ITAGGOMMd4QGGOMMcYbAmOMMcZEGfEhYM7ArFmzRB/I2Cjjw4zF0CO6OLAlL3Mf6KHPFqGMJ38ZSqL2uEOHDqIZR+R3l9YT07OAsTnW+vO7op85PR3SuCNjkNu3bxddtWpV0fQtYCtRxjzTWD591Bkb5r3N+Oe0adNE83tKeyXQ25ytXNlOdcSIEVESHCo+BJdddpnoxx9/XDR/K/pVjB07VjTb2d5yyy3ZmDkvTZs2FU3fDeaK8Fm655574kBREmtBXl6e6B07doj+xz/+ITqN5fN5Yv4B84n4XTIX69prrxW9bt26Av/bxYsXF/pe7HXAHDLmJKS5Elz/2V/gxRdfFD1w4EDRmzdvFk0/lLRXAtfiuXPniubfPWTIkCgKPiEwxhhjjDcExhhjjPGGwBhjjDFRRnwIWKvNnIGlS5eK7ty5s+gZM2ZkY8aj6AfNutP8/PziXWwh0Leedaesl/3d734nmrXMZY26deuKfu6550Qzvpb+Fqz/pWc/e5yzjpZxRcb+0t+RNdy9evUSzbwRxj+Zr/D222+Lrl+/fjZmTLJdu3aiee+ee+65olm7zPd79913s3H37t1ljn8n/RUqIr/+9a+z8Y033ihzrI0fPny46NGjR4v++9//Xuhnpf7wjzzyiMztK89iw4YNoln/XtZhHgC98vndpz78XAeZy3HVVVeJ5jrDfItx48aJvuaaa7Lxxx9/LHNcC+gLwr+Lax7zeGrWrJmNmYvEXgbMqxg5cqRo5pQxnyi9FnrxMG+K62lR8QmBMcYYY7whMMYYY4w3BMYYY4yJMpJDQI98xu4YW2cN++DBg7PxTTfdJHPMN2Ad+IHMISCsW37sscdEt2/fXjTjQIy7lzZpPDsi4oILLhD9wgsviE77mKe9BiI09haR+5un9fcRuT3TGT9PY/F8r5kzZ4pOY4wRufXCjL/xv097JdA/Yffu3aI3btwomjku69evF926dWvRae0835vxzl27dkVFg30r+vfvn43Zp2TYsGGiv2ytf3qf8R45+eSTRTMPhffzoQbvU65VjI/37t07G59xxhkyxxp6rjP33nuvaK4Na9euFZ3mBKX5PhERQ4cOFZ2uURHqnRKR278i7WMSEbFmzZpszLwQ5ifUrl1bNO9deh60atVKdJMmTbIxPTX4WvqjFBWfEBhjjDHGGwJjjDHGeENgjDHGmCilHAJ6PjMeNXXqVNHsMU/S/gTsVXDaaaeJZs35wWTSpEmi+/XrJ5rxqSlTppT0JRWLRo0aieZ3Se+ANH6X+otHRFSrVk30xRdfLJq1yc8884zo6tWri960aVNBl50Tk2SNOGuL2fvguuuuE71169ZsTL9xxq35nS1fvlx0GvOOiLj11ltFpzkvzG1g3Pb73/9+VDTS/KEI7VPxxBNPyNwvf/nLA/rZd955ZzZmfgLXONbOH+rwXmQ+UZ8+fUSncX7W0NO7gzkGEyZMEH3WWWeJvv3220WneWFcF2rVqiW6a9euoidOnCiaOQbMC0t7CtAv4Xvf+55o+oQw74TeLMy7oi9BCnORmPtQVHxCYIwxxhhvCIwxxhhTSiGDfbXjnDx58gH7LB5VlyYsQ3nooYdEp0eQEWUvZFCnTh3RDOXwyOvVV1/NxizDYukQj95p+Zu2HI7IPT5LS/K2bNkic7QL5nUz1MHyIbZETUt62LKa9qQsa+UxIEtR27ZtKzo9wmTZIcMubK/ao0ePKO+klriE5clsUfxlSctXGeJi2V15g2FdHo9zrUvLLPkMsOyczydLe1977TXRDAGmZYxsyc7QJN+LawFLwStX1v+HTsun2eqcVsYslaZFM+8hrg3p+9GSmaFKlmIWFZ8QGGOMMcYbAmOMMcZ4Q2CMMcaYKCPWxTt37hTNVprlFcbJy3rMlzExluAw3ta4ceNszNjbkiVLRDMOyJIcxopZPrRgwYIC5zZv3iya+QfnnHOO6BNPPFE043GpRTPjgmwBTetUtshmTJPWqWmuBT+LeRn7Ks+taPCe4z22r1wm/ve00G3YsGE2fvDBB2WOJWjlDZZzMyfo888/F522tGesnM/EKaecInrOnDmiaf/NUt60LJHPCPNwWJLMHCC2MM7LyxP99NNPZ2PmUNHKPbUejoj4zW9+I5prRbp+RqjFOvOiaAX/5JNPiua9WxA+ITDGGGOMNwTGGGOM8YbAGGOMMVFGcgg+/fRT0aztLq+wXS1jSGl7TNb1lgZsqZm2HI7Irf+///77szHbczZr1kw0bT0Z+2NNeZozEKH1w8xJYRyQ1qm8/1ivfthhh4lO7UzpUUBLZebD0Gdg9erVhV5rGqdm/JOkcdqKQmHfCVuhMwdj+PDholmDPmTIENFXXHFFgZ81a9Ys0fvKTzjUoVUxrXP5u6TPFNuTM4eH6yL9T2ibTHvh9Bl78803ZS5dkyJy8xXo5UG76zFjxoi+7bbbsjFbEt94442iFy1aJJqWy6lvS0SuhwL/7hS21+7evXuBry0MnxAYY4wxxhsCY4wxxnhDYIwxxpgoIzkEFRXW19KfmvW6pQ1rW/v27Sua7ZDvvvvubJzW60bkehiw5Snr+RnXb9++veg03ravWDvzFZifwTg/8xnSGCdrj+mXwLa3/I7okcD8hzTfgbXG8+fPF10RcwgGDBgg+kc/+lE25v05aNCgQjVzSahJWj+f+udXBBjPZnty5gWkNfm9evWSObbxTuvtIyLq1asnml4B9Dy49NJLs/EPfvADmWObaq7Bl1xyiegPP/xQ9M033yx6zZo12Zitlp9//nnR9Dfhs858pBo1aoieNm1aNmZ7afbF4XdcVHxCYIwxxhhvCIwxxhjjDYExxhhjopRyCOgpTl1RSGNdEbl10GXte+ncubNoxk0ZH9+4cWM2ZiydvgKsEWfsjt7d9AlPfb83bNggc+yxwDrn888/XzTzF9atW1fgte7Zs0fmGPfjPK/lwgsvFJ16T0Ro7gW99eknX1H8O1KYg/HTn/40G48aNUrm2K+eMBZ91113iWbtfZoHk5+fv++LLUeMGzdONJ9vfh9pzgHvW9bff/TRR6LT3gQRud4C9IBIvTtWrFghc/QvYQ8G+kfQl4C9D9K1hu/dqVMn0dOnTxfN+5E+BfRqSXNWRowYIXP0apg8ebJo/j4F4RMCY4wxxnhDYIwxxhhvCIwxxhgTpZRDwDgN4zisMZ83b15JX1KZgHF06tLmjTfeEL127VrRrJNPewB88MEHMlerVi3RrA/u2bOnaHo0sIY3jSU3atRI5p566inRrVu3Fk1vdcYwGbtP66L537JG+phjjhE9Y8YM0T169BC9cuVK0VWrVs3GY8eOlbnevXuLLmv3S2nDXBJqwjgrcwbIhAkT9ueyygX02+DzyByh++67LxuPHj1a5vbVu4D1/Oz30aVLF9Fp/wF6iDAXiTBHgL0OGNdP86buuOMOmVu6dKlorpf8jq6//nrRv//970Wn/27yO1i1apXoNI+iOPiEwBhjjDHeEBhjjDHGGwJjjDHGRBnpZcB+82lNeUT5zSHo2LGjaPa0psd+aZPGsyNyfyd6dad/D3/j1AM8ImLo0KGFvjdzCBibT/NQFi5cKHOsY962bZtoXhs97OvXry867S/QpEkTmWP+Ad+bvdvZo2H58uWit2zZko1POukkmeNzcd5554XZfy6//PJC51NfjYhcz/2KBNcCPo98XtM8HvY5YO+Rd955R/SQIUNE0xuAPgZp7kf6rEbk/mbMDzrhhBNEs88C+6Ck/QeY/7N69WrRzAlgPxfmLzC3onv37tn4qquukjnmb9ETgZ4aBeETAmOMMcZ4Q2CMMcaYUgoZ8Ch82bJlomnpO3LkSNG0GD1UYDtjtvyl9W9Zg987j8SqVasmOj2uS4++I3KP4SdOnCi6f//+onnUzqO8P/3pT9k4Ly9P5qZOnSr6oosuEs2jOx53sq1waqvMUr/jjz9e9JQpU0TXrl1bNI8szz77bNFpCKJ58+YyR6vT/S01qqjwmPWKK64o9PVjxowRzRLTigRt1mnJzTBdWpbII/7t27eLprUxy4YZWmWZYtqmnUfrfD5pg/zyyy+LpgUwLdPTa+d3wvJntoxm+f3s2bOLfK1XXnmlzDFUyXLLouITAmOMMcZ4Q2CMMcYYbwiMMcYYExGV9jKQUdALS7AV7+233y56+PDhomkhunjx4hK7lpLk2muvFf3II4+IpvXlr371q/3+rCL+rMUiLXuJyC1zo7VxWlrI+PemTZtEX3LJJaKZX/GXv/xFNG0/07In5jawzIk5LFWqVBHNOD5tQdOcA8ZKWUbI92Z51muvvSaaZYxp7LVu3boyxxIoli3R8vVAUdbachcV5vCwfK1ly5ai33vvPdFt2rQRzTLEskpJrAU//vGPRbOcb8CAAaIfeOCBbMzni/lFzO1gWSLbkbNleBo/v+eee2Tu6quvFs0yQ5ZTpmWFEbl5I5MmTSrwOpjjw1wltj7v06ePaOZapOXQtPtnGTfzD+6///4oCj4hMMYYY4w3BMYYY4zxhsAYY4wxUUZyCBgP2VddeGFx1rIE40+saWU8mbkSrLUvDiURN7zllltEsz5/5syZos8888xszHr8fv36FfpZLVq0EM34OO/H9evXZ+PUJyAiN07IlsXMR2D9MGPFac0146FLliwRzfrgDh06iGZeAPMV0pjm1q1bZY5WqfQ0oH3pgeJQzSE44ogjROfn5xf6eraqZp7LoUJJrAWDBw8WzbWK3jJp/gWft08++UR0q1atRKdx+ohcHxFakZ9++unZmD4D77//vmjmK3Dd4b9F9BpIn0HmqHA9HzVqlOiuXbuKpscBcyfStu30hOG6wbWAXiwF4RMCY4wxxnhDYIwxxhhvCIwxxhgTZaT9MeOsAwcOFD1+/HjRqVd1RESvXr0KfK+DCXMhWDvfvn170cOGDRP9ZXIGDgYbNmwQzXa8nTp1Ep22+2T8lXH9tBdBRMSePXtE0+/81FNPFZ22TGVNLq+buR1sUczYMb3V0xyFNHchIqJdu3aijzrqKNGsuWZeAD3hU992Xgd7R7BPglG6detW6DzvuS/jA1Le4VrFtY2+/GnPj+OOO07m2rZtK5qxdrYzZ+4S14I5c+YUOMfni34nmzdvFs0eK3379hWd5jOwbfOzzz4rmv0HmOvEfi1NmzYV3aBBg2zMNY6eMOz3UFR8QmCMMcYYbwiMMcYY4w2BMcYYY6KM5BCQxx9/XDRjK6NHjxad1orm5eXJ3KxZs0SzDvXLcPTRR4tmL23Ws/Pvuvfeew/YtRwMGF9jDIxxq7Rudvny5TLHOGDPnj1FL126VHSNGjWKfJ30UZ83b55oxvnpHZD6J0Tkxu4Lu4cYy2Od8zPPPCOaHhv0IJ82bVo2Zo9z5kawjpm+ERWdiy++uND5ESNGiJ4/f35JXk65gnXwrOdP83bmzp0rc+zJQb+IMWPGiKb/BvN00v4i6fMTkZsXwjg/88DYv2XXrl2iU78F5vQceeSRoplvxDWQzzfzH1I/BuZCcJ1h/5ai4hMCY4wxxnhDYIwxxhhvCIwxxhgTZTSHgLBGnf7U6TzzC1hbnPaUjsjtrf3SSy8V+bpYk8qYEWNfQ4cOLfJ7l0VYr08PcuYYpDEx5lts2rSp0M9i33H2pq9evbroLl26ZGN6pf/iF78QPXLkSNGsqf7iiy9EM16X9qCgrzr7JNAXY1/91ulT0LFjx2xMT3r+HvRONwrrwAn7ZZiC+eyzz0Qzf4jPZ1o3z2ckzTWKyH1G2DuDzwF7qDRv3jwbs+fCK6+8InrQoEGi7777btE7duwQ3bhxY9FpDtDTTz8tc1w3mDM2ffp00fy7mHfVp0+fbEwvnrfeeks0/y0qKj4hMMYYY4w3BMYYY4zxhsAYY4wxcYjkELD38+LFi0Wn/a9btmwpc9dff73oNA4TEXH++ecXqgvjj3/8o+jUuz9i//2kyyrsP8A8AMb+0nph+uwzts44IuO5DRs2FE0v7zTuzzneP4zt3XXXXaKZU8AchM6dO2fjtWvXyhx7LqxevVp0Gt+MiNi4caNo5hSktcv0gGcOgevmlWuuuUZ0lSpVSulKyh/0z2CuFr1jDj/8f//UsK8Jnxn6a7Ben7H2119/XXTaA2DcuHEy16NHD9H0RKBHydixY0VzLalXr142vuGGG2SOvWzoQZJ+JxG5zzfzF1K/FP47l/aKiIhYtGhR7A8+ITDGGGOMNwTGGGOMiai0l+cvBb0QpR+mbFPEn7VY0JaX4RWWBqZH87Qn3blzZ6HvzaM5ltnQ5jP973k0zFIjHmcytMNWrjyaZ+lqCsMRDKMwRECbVur0WJHlWjy25REkrYwPFIfKWsDSKx7Z8nfu16+f6EcffbRkLuwgUxJrQdpyPiKifv36onmMnz4XtALn2sCyYR6Hs2Ux3y+1UX744YdlLrW552sjIp566qkCrzsityw4bQE/YcIEmaNV9rnnniuaZYq0RWZJc9pemc86Q7B8L5Y4FoRPCIwxxhjjDYExxhhjvCEwxhhjTBwiZYembMCSOVpIsxQmLTtky9KBAweKZilpnTp1RF922WWiGVdM46R/+MMfZI6xYsYo+Vl169YVvXDhQtGVK/9vH812qcyNYC4E7Z5ZasSW0qlFLOe6desmmvbQFR2Wwl144YWldCXlD+azMC+H5bPbtm3LxrxP+doVK1aIpl0wrYr5DKZ29L/97W9lbtiwYaJZ8sj8oN27d4s+9thjRaf5C8xXuPPOO0Uz96FBgwai+Z0ytyn9bOYQzJ49WzTLtIuKTwiMMcYY4w2BMcYYY7whMMYYY0w4h8AUA8bqmjVrJpr16akfQIsWLWRu2bJlohm7YzyNrX3Z7jP9rLQVcoRamUbk2pXSG4D16ryW1AOBXgDMR2C8lDasbBnNuHejRo2yMfMNWEPN9zampOAzxVwZ5reknhh8RtJa/gjNN4jIteGl5wGf37Zt22bjBQsWyBzzh2i/zrWDviD0IcjPz8/GtCqmRTNzI+hRctZZZ4lmXkbqQ0Cb8po1a4pO85yKg08IjDHGGOMNgTHGGGO8ITDGGGNMFKOXgTHGGGPKLz4hMMYYY4w3BMYYY4zxhsAYY4wx4Q2BMcYYY8IbAmOMMcaENwTGGGOMCW8IjDHGGBPeEBhjjDEmvCEwxhhjTET8F8MvWoK9Eu06AAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1825,7 +1825,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1835,7 +1835,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1845,7 +1845,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1855,7 +1855,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1865,7 +1865,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1910,7 +1910,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -2051,7 +2051,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -2107,7 +2107,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -2150,13 +2150,13 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3db4666b78254ce5aa41defd2c5e4e4b", + "model_id": "8e2d8fdf6e024991b23e573e22ebce68", "version_major": 2, "version_minor": 0 }, @@ -2170,7 +2170,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "065f078366d84b708fb364ec01c498a2", + "model_id": "8478476f7fc84adba322cc705612f8fd", "version_major": 2, "version_minor": 0 }, @@ -2184,7 +2184,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ca571ab5e3ad47b98cb9474236b430eb", + "model_id": "3aa6e1f2aa9643e992c8a0a0520b71ee", "version_major": 2, "version_minor": 0 }, @@ -2198,7 +2198,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6bc443cf43aa404c9a54e8f7e254807c", + "model_id": "6c378e7d0124449cabbf5003d152ec2a", "version_major": 2, "version_minor": 0 }, @@ -2212,7 +2212,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "af3d7394cf2b4960ac1d2cc2d3d6e069", + "model_id": "c61f1f6b3cee485399e9bb112cc9ab7d", "version_major": 2, "version_minor": 0 }, @@ -2240,7 +2240,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -2249,13 +2249,13 @@ "Text(0, 0.5, 'mean squared error loss')" ] }, - "execution_count": 83, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2285,7 +2285,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -2299,12 +2299,12 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 35, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAUVUlEQVR4nO2dW2wV1f/FNypys1qqCAKWixRKkVuLYgstN0FRogQwAWMIPIgxoiYaIw8aE3wwGKPRiEQTlQQ1aBAVEVCQCpYCFhAoUC690AItFKpArRUE+T3957/XajtzhtPTlu71edore86ZOXMO3cz3+93r2+bKlStXjBBCCGe5rrkvQAghRPOihUAIIRxHC4EQQjiOFgIhhHAcLQRCCOE4WgiEEMJxtBAIIYTjaCEQQgjHuSHSA9u0aRPL6xCNTCz2Cd5zzz2gR48eDfr6668HfcMN///zWrt2Lcx17twZdMeOHUEnJCT46qNHj4Lu1q2bN77ttttg7vvvvwedkZEBuqKiwvfaunbt2uDxfB2DBw8GnZeXB3rkyJGg+XMVFxeDrqmp8cb//vsvzPXo0QP0ddfh/+uWLFliYkH79u1DHR/LPat+f5eCzhs0H+ZvXtj3Yh3mHgW9F1NbWxv4nnoiEEIIx9FCIIQQjqOFQAghHCfiHIEQjzzyCOjKykrQcXFxoHNycrxxZmYmzHEsfNy4caCLiopAX7p0CXR5eTno7t27e+N27drBHJ87Pz8ftJ3LMMaYixcvgu7QoQNoO+fA1922bVvQw4cPB81x/LKyMtD79+8HPWXKFG988OBBmDtw4ABo+x7EkrAxfzuGHeu4vf36aK4z6L3Dwq9tyvxEJOiJQAghHEcLgRBCOI4WAiGEcBzlCETEcEz63LlzoKuqqkDfeeed3riwsBDmUlJSQK9cuRJ0eno66MOHD4O2Y+fGGHP58mVv/M8//8Ac7wPo168f6GXLloGePXu277mHDRvmjTkvcvr0adCcIzh+/Dho3kfA+xDOnDnjjePj433fKzU11bRE/GLYPBe2vv6///5rcC6aWv2meL9ozu0H7zeJBD0RCCGE42ghEEIIx9FCIIQQjqMcgYiYxMRE0KdOnQLdpUsX0HbOYNasWTC3evVq0FlZWaA3bdoE+uabbwZdUFAA2q7153r67Oxs0Oy9wt5Eubm5oDkWn5yc7I179+4NcyUlJaA5Xvv333+D5pwC72GwX19dXQ1zvL+BczQtkaCcAMP7Lvh4zhH4xe2D3otpyhxANGgfgRBCiKjRQiCEEI6j0JCIGH4E5UdttmqwwyZLly6FuTFjxoDesmULaC6jtO2YjTFm/PjxDc6vWbMG5m666SbQI0aMAM1lsDz/3XffgbY/F1tCHDp0CDTba3N4h+/p0KFDQW/YsMEbs1UGf062xI4VsbRHCCrR5FCQ37mCjuXfb9DxjWnFH817hbWriAQ9EQghhONoIRBCCMfRQiCEEI6jHIGIGI5r/v7776C5daJtxXDHHXfA3LZt20CzpTW3xeQ2mIsWLQI9atQob8xxdi4n5bj++vXrQd96662guWzWtqHmEs6JEyeCPnnyJGguD+3UqRPo0tLSBue5pNYuYzXGmAEDBpimIGzZpX180GvZxjuoPNQvPh4U4+f3tm1KIrlWv/mw+YXGLFXl3EdEr2m0swshhLgm0UIghBCOo4VACCEcp82VCINTjVlDK2JPLLbHT5s2DTTX57NVg90ykltT9unTBzTH2rdv3w46IyMDNNf+2xYU+/btgznbDtuYupYR/Dl4nq0b7rvvPm/M+QbOAXC+gS2xueXmX3/91eC5bEtqY4w5e/YsaM5lvP322yYWcCvQMPsK+O8I5354L0rnzp19j+f7feHCBW/8xx9/wBznAPi9giwouF1qmPcKa6cdJscQlDeJxJZaTwRCCOE4WgiEEMJxtBAIIYTjtIh9BDNmzAD95JNPguY4Krci/Pzzz70x121zi0Rx9WzduhX0yJEjQXOOwPbdueWWW2CO4/L8PXFNPO9DYPtmOx581113+Z6LX8txfm6TybH5Xr16eePffvsN5jhuz7kP/n3efvvtoDm2bOcMTpw4AXN8j/g6WyL8+dq3bw+ac0eclwpqYXrw4EFvfOTIEZj7888/QfP9CvIeYgtxO27P1uacT+D3CtJ+HkuxyP/piUAIIRxHC4EQQjiOFgIhhHCcFrGPgGvMuf1fGNjvneO/TQnXo7/55pugd+zYEbNzxyKOyD46SUlJvuesqKjwxlyLzx47nF/gfgP5+fmg582bB/rTTz/1xuzBw55I8fHxoDnOPGHCBNDcU8CO23MsmOPO3GKTj+c4Np/Ljg1zTwaOp//444+gc3JyTCzgfQTRwDmUgQMHgn7xxRdBswdVQkICaDtWz3sMOH/DuSLeC8B5rbi4OND2nofz58/DHPeG4NwQ95LYvHkzaL521jb87473S/jtf/g/9EQghBCOo4VACCEcRwuBEEI4TovYR8D7BoYMGQK6oKAANMcRU1NTvfHYsWNhzvZqMcaYY8eOgWYfmiDseBvHGLnWnSkrKwMdyxxBLOB4LMeK2dulqKjIG3O9OB/LNdx8rzinMHfuXNCvvPKKN7b7BRhTtxZ9586doNnPZvny5aDfffdd0OvWrWvwtZx/6NatG2iOHXNOgWPmdpya7wFf54033mhaOlwvz/X3JSUloBcvXgya904MGjQItP23gX2L+Lvo0qULaN4nwJrvvx2L5++d+16z3w//Bm2PpPqOD5Pz41xHJOiJQAghHEcLgRBCOI4WAiGEcJwWsY+gMeGYrd0315i6sTmuSw7C9jni+nPOZXBM/ZlnngG9ZMmSUOcOQyz2EbCHz+TJk0Fz/NeOf3Mtv91j2Ji6/Xg5T8Sxc67btveesCdSWlpag9dVH5zP4N4Hdi6Ij+Xr5lhvXl4eaI6Jc7+CU6dONTjHexR69uwJeuHChSYWhN1HEOa3GLbXL8fD7e+Dvxu/PQf1ac4R8G/Q9omaNWsWzM2cORM05yaff/550LxPJszfW/UjEEIIETVaCIQQwnFaRPloY8JWs9nZ2b7H//zzz1d9runTp4PmsBQ/7n355ZdXfa6WwKOPPgratvw1xph7770XtF0qyeEZLu3jMBNbL/AWe7aksMuA+/XrB3NB7Q3feust0GwxwSXGubm53njSpEkwV1paCpp/A2zd3b9/f9AfffQR6CeeeMIbs532xo0bQXNbzFjBoYegMEY0YeWgc7F9gh3O4dAOh/jYioE1/0Y5dGT/jvi1bBWya9cu0Fw+zZ/LL5zGpdbM1YSF9UQghBCOo4VACCEcRwuBEEI4TqvLEcQau2Tsgw8+gDmO3XH5HscFrzVsywhj6m7Z57aNdjmjHVc3pq4VCJeDclkvWzNwGWbbtm29sW0TXd91cuyXr4VL/fr27QvatjRhWwe2PODYMJfJss3Bgw8+CNr+XJz/4vzCvn37THMQJmcQlC+INv9gvz6orJIJir3zvP375lwR56V+/fVX0GxLHSaur1aVQgghGh0tBEII4ThaCIQQwnGUIwiJbRPB8V2O4R46dKhJrqmp4Bp4jply3NO+H7zHgO0ouC0g18iznTjfe9sSnOvpuZ6cvxe2Nec4fvfu3UHb8V/OmwwfPhy0nVMypm4OgdtJ8v4I+x5ynoVzF9y6srnwi/OHzQEE4ZcjCLKrCIq18zzv45gxY4Y35u+Cc1qcP4slV3NP9UQghBCOo4VACCEcRwuBEEI4jnIEAbBd8oIFCxo8durUqaCbq647VtgW3MbUjXtyHP/EiRPemK1wa2pqQHMbQG77yTHXHj16NHguu/bemLr19omJiaC5tSXnDNLT00EXFhZ64/LycpjbvXs3aNtG2pi61sh8H3g/RWVlpTfmz8F5lpSUFNMchI29hzk2KKfQmDX1/N58f/lvgW01zdfBvynemxK2rahf3D/sfon60BOBEEI4jhYCIYRwHC0EQgjhOMoRBPDQQw+BtuPP3MuAWyS2NuxafWPqxrf9WvtxW889e/aA5vp6jtNzvNaOnRuDbTSrqqpgbu3ataDj4+NBZ2ZmgubPxee2c0ErVqyAuZUrV4LmdpK8X4J7JyQlJYGOi4vzxry/gXMC7Gczf/58Ewui6T/Q2PsI/OLhQe/N+2C4twH/Trgdpe1hxX8Lli5d6nsu/k015n3RPgIhhBCh0UIghBCOo4VACCEcRzkCwo5rG1PXH97uU/raa6/BHNfKtza4Zr53796guYbevldTpkyBuaFDh4Leu3cvaN4LwHsyuIfAqlWrvDH3MmCvIP4c7dq1A82xYt4/Ycdz+b24rzPXj/P+CL5nBQUFoJOTk70x907u1asXaO7R0FQE1fb7xfGjjY2HOT7ourhPxejRo0Hz3wL79R9//DHM2ftajKnbn4BzBPw5/HojxGJvhZ4IhBDCcbQQCCGE42ghEEIIx1GOgHjppZdAs7/8unXrvDH7w7d2Ll++DJpr+aurq0HbeYBFixbBHOcMHnjgAdAcl2ef/jNnzoC2exDwHgSu6e7atStozu3U1taC5h7I9n4RjsdyX2r2UOJ5zrPwue1+BtxH4cCBA6DtnEwsCfLkYex7FNQXOIho+g5znJ5/z+xfNWfOHNC8B2TNmjXeePPmzTAXFLcP6pXgR7S9l+t9TehXCCGEaFVoIRBCCMdxPjT08MMPg3711VdBsy3wwoULY35NLRVuVZmdnQ2aQxd2m8XZs2fDHD9K22WSxtS1oGA754yMDNC2rS8fy20tJ0yYAPqnn34C/frrr4Nmm4ivv/7aG3OJ4fHjx0GzVTeHH7hk0W5/aAxaF9g2GsYYU1ZWBprLYGNF2PJEO+wRNmQSjc10UMkmt5587LHHQE+aNAk0t6J9//33vTGHRfncYYnGOuNq0BOBEEI4jhYCIYRwHC0EQgjhOM7lCOwyQ2OMee+990BzbM8uETPGmG3btsXmwq4B7Ni4McbcfffdoIcMGQLajsmyNXTnzp0bPNYYY0aMGAGaS/d27doF+sKFC96YS08nTpwImu20uUT4s88+A835i+LiYm/McWP+XFzmyvkJfj2X2dr3JShmHW1c+mppTJuHaM9lz3N5KJdVsv34008/DZrbSS5btgz0xo0bG3zvsOWisWzBGQl6IhBCCMfRQiCEEI6jhUAIIRyn1ecIOG5qW0QYY0yfPn1AFxUVgeZ9BS7DMVeuz+eY6pEjR7yxbZVgTN3vhe0q2Ma3sLAQNNtEpKamNnTZ5ujRo6DtFoP1aW4XuXjxYtB2HoBjw2lpaaDZKnrDhg2g2Q6D9xnYsWO2ysjKygLNdtuuw3kn/p6feuop0Px7zs/PB+2Xv4k2R9Dc6IlACCEcRwuBEEI4jhYCIYRwnFafI2B/Fo7hMi+88AJozhm4TEpKCmjOGbCds+2Fw74u7NHzww8/gE5PTwfN+wZ4vn379t54//79MMdxem6DyXkijsWz19D69eu98ahRo2Bu586doHn/Q79+/UDX1NSAZptqO9Y8bdo0mGN77NLSUtPSiTZ2HsabiL2XeJ8AtzQ9e/Ys6DfeeAN0SUkJaPaJsglrBR1mf4W8hoQQQjQ6WgiEEMJxtBAIIYTjtLocAceD2Wue4daUq1evbvRrai2wtw3Hs9l7qH///t64oKAA5thL//HHHwf94YcfgubWltzPwK4R59/AggULQLNn0rfffgua+ypwvNdum1lRUQFznJPiWvbExETQ7F3FcWf7nnfo0AHmzp07B7qp+hEE+eJEE9/m+xV0PH83dp6K81Dz588HbftTGVP3N8d/C/y8nIK8gYLaezbmPoOr8SnSE4EQQjiOFgIhhHAcLQRCCOE4rS5HMG/ePNAck2U2bdoEuql9wK8leJ9Az549QW/duhX09u3bvfGYMWNgjvsf7927FzR/b5yPmDlzJujly5d743HjxsGc3VvWGGN++eUX33OxjxHHoe1+B4MGDYI5zqPw5+K49OTJk0FzfsLOu/CeBN7f0FR7Xhq7h0A078X30/a7mjt3Lsxx/oXzTF988QVo7mvBOQL7PkS7/yHoeJsgXyPlCIQQQoRGC4EQQjiOFgIhhHCcVpEjsOuFn3322Wa8ktYNx0wvXrwImj177BzC2LFjYc7OHxhjzMGDB0Fzn+Hdu3eD9uuFwL1lX375ZdC5ubmg4+PjQXONN3/uYcOGeeNvvvkG5ngfAfdx3rJli++1dOzYEbSdl+F7lpGRAbq2ttY0BWH76/rF0sN4B9U3z9g5Ffaj4nzCV199BfrkyZOgg/yCYtlToKn7FeiJQAghHEcLgRBCOE6rCA1lZmZ6Y7Y7ZrjEjq18RcOwTe/06dNBl5eXg87Ly/PG3C6S32v8+PGg2Z65d+/eoFetWgV66tSp3rhTp04wx2Wv999/P2gu2eRr49/U8ePHvXFycjLMVVVVgebw2Zw5c0AXFxeDZpsI24KC231yqMO29IglYe0UIp2rbz7oeD9L8YSEBJjj3yd/73w/m9rmwQ+/MFWQfUVE7x/6FUIIIVoVWgiEEMJxtBAIIYTjtIocgR979uwBPWHCBNBsXSAaZsCAAaC5fWR1dTVoOxbPpY0cv+USzcrKStAc5+fv1S79Y2vn5557DjTHgo8cOQK6b9++oLml4SeffOKN7RaZxhiTlJQEmufZcuLYsWO+12ZbXnPu4vTp06DPnz9vmoMwJZ9hSk3re2+GcwSXLl3yxtxaMicnB/Thw4dBB1k3+BHWPpsJOpf9/kH3KGybTGP0RCCEEM6jhUAIIRxHC4EQQjhOmysRBsKaesuziI5Y2GlzrJ235NvxWWPQ9mHEiBEwt2LFCtD2PgBj6lpHZ2VlgWZbiMLCQm/MtfypqamguW3m4MGDQcfFxYFmu2K7beY777wDc1zLP3DgQNB8z06cOAGa77Fd675jxw6Y430Fdj7BmLr3sLHglpmMXx17kGVyWIsJtoa295CkpaXBHOcESktLG7zO+s7FsfcwfxOjae8ZNB90XZx3qvc9Ao8QQgjRqtFCIIQQjqOFQAghHCfiHIEQQojWiZ4IhBDCcbQQCCGE42ghEEIIx9FCIIQQjqOFQAghHEcLgRBCOI4WAiGEcBwtBEII4ThaCIQQwnH+B2b8YAdPMWJTAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -2314,7 +2314,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2324,7 +2324,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2334,7 +2334,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAVUklEQVR4nO2de5CO5RvHb5Uck1OUclg2ZJGWyKHCoI1IB52lUukwwzCZUH+o4Y9SmDFbM0yZKI2cqeigqTAtYcO2OSTkkLOWrEL5/ff8ru93d99nH+++a1/39/PX/Z37fZ/3eZ/3sbfnuq77e5U7d+7cOSeEEMJbLrnQJyCEEOLCooVACCE8RwuBEEJ4jhYCIYTwHC0EQgjhOVoIhBDCc7QQCCGE52ghEEIIz7msuC8sV65cIs9DlDCJ2Cc4YsQI0AcPHgT933//gU5NTQ3GDRs2hLk1a9aAvvPOO0Hfc889oF966SXQvXv3Bj1p0qRgnJKSAnP169cHzfdyTk4O6L///ht0lSpVitT16tWDudq1a4OuXr066JkzZ8acr1GjBugmTZoE43Xr1sHcTTfdBHrOnDmgV6xY4RJB5cqVQfPvHuve42vPr+V5PnaU40X9mxX22Xyul1xS9P+jo36vWMcKO0+Gj3369OnQY+qJQAghPEcLgRBCeI4WAiGE8Jxi5wiEqFChAuiaNWuCvuaaa0Db+HZWVhbMcdzy3XffBT1r1izQ+/btA52ZmVnkZ3MM9cyZM6D//fdf0JUqVQK9f/9+0J07dwa9a9euYMzxWI7jcw6hTZs2RR7LOedyc3NB16lTJxiHxYbt9U4kUXICzuF5h702LA4f5bPiJexYsfIRUXMhUQg7VpR8Q/Ce8z4bIYQQFwVaCIQQwnO0EAghhOcoRyCKzbZt20DbfQLOOVe1alXQy5YtC8anTp2CuWbNmoHm2v9ffvkF9IYNG0Bzrf+AAQMK/VznnNuxYwfo++67L+axOReyceNG0Hl5ecG4YsWKMNe3b1/Q48aNAz18+HDQnI/o1asX6Ozs7GDM+Ybt27eDzs/Pd6VBWIya521OIWpsPGo9fpTjh7027HuV5J6FKPt+4nlvUeiJQAghPEcLgRBCeI4WAiGE8JxyxW1eL6+h5CIRXkNTp04FPX36dNA33HAD6MaNGwfjEydOwBzHu/fu3Quacwjs0dO1a1fQR44cCcbsgdSoUSPQv//+O+h+/fqB/uGHH0DXqlULtK3t/+2332Cubt26MT+LY9qdOnUCvXjxYtBt27YNxnv27IG5Q4cOgW7dujXoUaNGuUTAOZQoMevS/DsStd7+iiuuiDn/zz//gLZ5qqj+P1H3YliiXkM+78LQE4EQQniOFgIhhPAclY+KYsO2ELZk0znn5s2bB/qqq64KxhyusSEP5zDc4pxz48ePB8021Zs3bwZ95ZVXFnXarmnTpqDZUoJLVbnUlS0pFi5cWOR58TViW2o+NoeC+DrYEtFu3brBnA2HOefczp07XWlQkvYIYceOatVgwzlsH37jjTeCbtWqFWgOIfL15HJde/35PLi8mcN6tgTZuYL3WDycz++jJwIhhPAcLQRCCOE5WgiEEMJzLoocgS3B+/jjj2GOt/Bv2rQJdFgMcvny5aC3bNkSjNevXx/9ZJOYVatWge7RowdojvvbGCrbT0ybNg108+bNQbMNBNs8/Prrr6D79OkTjLkkk3/DGTNmgB42bBhoLoPl+K5tL8n3C1tBHzhwAHS1atVA2/vJuYKlftZem8ta2Qacj10WKWl7hEsvvRS0vV4PP/wwzPE9xaW+hw8fBs2/DX+W/W35nuEWpF988QVo/rfE5dWJKP+OhZ4IhBDCc7QQCCGE52ghEEIIz0nKHEH58uVBW6sDrhHnuB/rW2+9FfT1118Pmu0HbKz7q6++gjmufV+zZk2Bc09muB6f2zLytnm7ZZ9r3jmOz+0kuYab9wlwzsFaPXC9eJcuXUAPHToU9NmzZ0GnpaWB5nhtjRo1gvFll+E/ocmTJ4Pmc+E4PltpXH311aBtTotfy/sf2GKiLBK2D4A1x+X5evP1svs6MjIyYI7zL5988gloa/ntXMG4PbcVtXtGjh8/DnP33nsvaM7n8L6BMHvtWK9lzie/oCcCIYTwHC0EQgjhOVoIhBDCc5IyR9C+fXvQ8+fPD8ajR49O6Gc/+OCDwTgzMxPmli5dCnrEiBGgP/jgg8SdWCnAuRmOd3NOxOYB2K6Z215yLJ3r8f/44w/QQ4YMAb1o0aJgPHHiRJjjPBDnibjGm9tPci5o4MCBwZj3GIwdOxY01/7n5OSAtlbdzjn3zjvvgLY5Kr5mbdq0AV1aXkNMSbZd5JwAW0FzfX56ejpoaxm+ZMkSmFu5ciXosD0cfG4c17fnyjH9hg0bgm7RogVo+zersGPHIqpfU3HQE4EQQniOFgIhhPAcLQRCCOE5SZkj4Fh0VlZWqX327NmzgzH7k3/00UegH3/8cdDJniPg+C3X53Nbxs8++ywYP/PMMzFfe/LkSdDcDpH3IUyaNAm03ePAHjMM5xu4Fr1ly5agOY5vfY54PwOf5y233AKacyXshcV5F9ufgK//2rVrQVufndKkJNss8rE4R8D9Hvh62j4A/Dvzv1e+53gvC392rFp/7jvBOQFuK8q/Zdj+iuLOnS96IhBCCM/RQiCEEJ6jhUAIITwnKXMEHMu7UIT5FHGf3mSHvVfYm4X78dqexezTwt4rHPfkGm/20eGYq/UiOnbsGMzt3r0bNHsmpaamgt66dStojkvPmTMnGHPug8+bcwT16tUDzT5HDzzwAGj7XdhviePKvM+gLMLnHJZf4OvD9xh/53379gVj/t14nwDX7nNOICxfYT2n+vfvD3P8N4p7l3BPY84ZMCWZhykMPREIIYTnaCEQQgjP0UIghBCek5Q5gkTCfjrsa2Tr12+++WaYYy+T4cOHl/DZXVhszN+5gvFZ7gVhvXDYY6dKlSqgORbMNfEcG+aYqo3rcy9a3pPAPv7sJZ+SkgL62muvBf3KK68E46NHj8Jco0aNQE+ZMiXmsfl78B4Z61mzYcMGmOM+uZxfuFBEqYln2LMnzO+H7xt7Pfm1nDMIyzVefvnloPl6P/TQQ8HY9sx2rqDHlM0rORc9V5Jo9EQghBCeo4VACCE856IIDVWuXLnQcXEYPHgw6Pvvvx9027ZtQdtt6WPGjIE5thDOy8uLdC5lHVsu51zBR2suy7SP1vy77NixA7Rta+mcc3/99Rdo3rLP4Z8OHToEYw6hcDkpWw888cQToLkslu0wmjdvHow55GXLF51zrmvXrqA///xz0FwWy98rNzc3GHMYhO2x+RolirC2iiVpgcDH5nAPh/3atWtX5HvZzoPDk9wKlK8nW6Xb+53DpDNnzgTNpeT8W0a5ZmG232pVKYQQIjJaCIQQwnO0EAghhOckZY4gIyMD9IQJE4JxWlpaQj/btgPkbeMXW06A4ZI4bsdn7Zmdwy35HDu3cXbnnGvQoAFobrvIZZrfffcd6B49egTjAQMGwNzXX38Nmu3B2YKCrUNWrFgBevHixcGYbaivu+460Jxv4GNzuenPP/9c5Hx+fj7Mde/eHTTboPN1KCnCykNLsxSSbTeef/75YMwxfbaI4HwMl45zDozbklrbFL5H2PKajxVmQx0PspgQQggRGS0EQgjhOVoIhBDCc5IyR8AxMFvbv3nzZpibNWsWaLaiff/992N+lo09O+fckCFDgvGCBQtgbuTIkaAzMzNjHjvZ4LaA9evXBx1rrwDHV++44w7QbCFRq1Yt0LzPgHMKtkaccxdcP87b/Tl+yzYPtjbdOawv51gv35tslcHzfE1/+ukn0Na2evXq1TDHcWi+VxNF1BwBx+bjgT+L7cztfcEtSHn/COe8OMfF1umcj7AWM3w/2/0fzhW0Jw+znY5FWD5B+wiEEEJERguBEEJ4jhYCIYTwnHLnihlQKkn/kGTG1iYvW7YM5jjGyDXjpUkiarnHjRsHetWqVaAHDRoEeurUqcGYPXW4ZSPnWx555BHQfG3ZEtj6GnEsvVWrVqA59su5DbalZt+ju+++OxizF9Wnn34Kmv2AeJ/B3r17QXNrS9vSkP1sqlevDpo9kebOnesSAfv7RNlHEPZ3JCz/wLF1/m0fe+yxIl+blZUFmu+TAwcOgGY/IPYmGjZsWDB+9tlnYY7vZ/vawo4d5e9rmLcQH4vzooWhJwIhhPAcLQRCCOE5WgiEEMJzknIfwYXEet2/+uqrMMdxQG7dyLXyyQbX5y9fvhz0xo0bQdvWltz2j+usu3XrBnrp0qWgOR7O7SNtnLR///4wN23aNNC2d4Fzzm3atAk0x1j5XG2MnPsLsIc95zKqVasGmvsy2D0xzuH99ueff8Ic5zZsa9BEUpLeQlHbWvLrOS9ifaA4R8C9I44cOQI6rK8Cv37+/PnBeODAgTDHvTvizdnZ9yciX6snAiGE8BwtBEII4TlaCIQQwnOUIyhB2GOf49hcC59svPnmm6C5vzP75lgvFu5HcPr0adAc7+7UqRNorvFeuXIlaOsXxB7/t912G2j2p+HYO58r54IWLlwYjLnfMXsqce067ztgffjwYdBdunQp8lhbt24FHbVf9/kS1evGeg3FGyuP5TPmHHo18WexpxR7IEXt/WtzftxLmfOBXMsfj9dQItATgRBCeI4WAiGE8BwtBEII4TnKEUTE+uJzT1j2Lkn2nADDcftjx46BtvsGGN4HwHsOuL6e68M5R8Dx3dTU1GC8aNEimGNfeu4LzL0OeL8E97Swx/vxxx9hjmvN+dj82Xxd2DPf7kPgXMfBgwdjvre0CNtXEE8NPB+La/153sbio+YEGD5X9gdq2rRpMGYfIv63H5YTCLuGsa5bSewr0BOBEEJ4jhYCIYTwnKQMDfXs2RM0W/0mEmvF3KtXL5h7/fXXS+08LgRs+XvixAnQ3F4yOzs7GHObP1sW6VzBUBCHc9i+mdsy2pLO9PR0mONHen7s5vaQTZo0AV2+fHnQ9ndv3749zE2cODHmsb799lvQHFKwNufOOTd58uRgzO0QuVy3tGzPo4ZUosDvZV2xYkXQbIltf2sOI3GJZ1i5KOvatWuDfvHFF4OxtQt3zrnvv/8+5rGiEuX953P99UQghBCeo4VACCE8RwuBEEJ4TpnMEXBJ3XvvvQc6Ly8PdCJzBIMHDwb93HPPBWNuSzh27NiEnUdZYPv27aDXrl0LOiUlBbRtuzhnzhyYGzNmDGi2nODSSC7941aXNn/BlhH5+fmgrbVzYZ/NcXuOz9rWlePHj4c5jvHzPZKRkQGaY97r1q0D/eijjwZjtlOwLTOdK1hiW1qElTpGKX0M05wT4NyT/dvAcfuo1hj8d+iFF14Abe1B+Hfme4zv37DPjvJalY8KIYSIGy0EQgjhOVoIhBDCc8pkjoC3Z3N9et++fRP22W+99RboESNGgM7MzAzGdk+BD3C7SbZQ3rlzJ+j9+/cH444dO8Ict3i0r3WuYNtFjtdOmTIFtI3rc2yYcwacA+BYO382x38PHToUjNn6ma0z2BZi165dMc+NY9427s+5MN4fwXbZiSIs3s31+5aweHbYvgFuAWnzNc7hb8/Xh4/N+wr42E899RRobkW7e/fuYGz3ezjn3PHjx2N+dtSWnPb1Ud9bHPREIIQQnqOFQAghPEcLgRBCeE6ZzBGEeX5wzDYeOCfAtcJvvPEGaBuH5RjjxU6dOnVi6hYtWoA+evRoMN68eTPMrVixAjTnG9jimr2HOG9kY8PsucOePBxj5baXlSpVAt2nTx/Q06dPD8acN+G9Ftu2bQPNPkhs3c12xfb4HKPmPMuFsqFm4qlr5+/PHlPc/pV9ojgvEAu+h5588knQo0aNAs35iJdffjkY8/3NeRL+XlH3XshrSAghRELRQiCEEJ6jhUAIITynTOYIShJuFfj222+Dfvrpp0FzTmD06NGJObEkhOvYuf6e2zDaGvvGjRvDHOdX9u7dC7pu3bqguffB4cOHQdt6+86dO8Mc1+bXr18ftPWPcq6g3w+3vrS17Vznbv2VnCsYt2cPpUaNGoFmz3vbCpPzCc2aNQPNuZBEERbfjjUfFuvmPQppaWmg+d9zbm5ukZ/Nr23ZsiXooUOHgu7Xrx9ovsdsTsA5zC2dOnUK5vh7RI3bx3p9PN5ORaEnAiGE8BwtBEII4TlaCIQQwnPKZI5g+PDhoGfMmAGaY3nWi57jgNznNazXwYQJEyKdq0+0bt0atI1fF8Zll/3/9jpy5AjMnTlzBnSHDh1Ap6amguacwerVq0EPGjSoyPPiHgC8z4DjzOwHxB40Nh7M9xPff+xFNG/ePNDNmzcHzfsQqlatGoytt41zznXr1g0074coLeLpx8vxbN6Xwfkc7hPO18/mbPi97CHFPS1ycnJAs88Y99+w90HUfQAluU8gbN9VcdATgRBCeI4WAiGE8BwtBEII4TllMkfAcdSRI0eCXrhwYZHv5fguH4v9WRYsWHAeZ+gn7LHOXi0ck926dWswZu+VmjVrguaexnfddRdofj/3pOjZs2cwtrkJ5wrmI2xPCeec+/LLL0Gz71H58uVB2+vA9eKzZ88GzfsjON/AOQY+3po1a4Ix71ngvAvnOpIBjmdzf+ns7GzQt99+O+gBAwaAtp5Utm+Ec87t27cPNO8pmjt3bszXx/IPKumcQDx9ibWPQAghRGS0EAghhOeUO1fMWqN4rGVF6RNPSV9RzJo1C/SHH34IukGDBqCtjQRbSnCZJbeXZPtmfj3bQNhy07y8PJjjEk62BOayQQ4t9e7dG/Q333wTjDt16gRzHE6oUKECaBsuc67g92ZbBFseye0827VrB3rLli2gX3vtNZcI+Dsx8YQ1+NpzWI5tqdky3F5PbgPKoSIOGUa1bojVsjNeG4h4/v3yefE9Vuh7zvvThBBCXBRoIRBCCM/RQiCEEJ6jHMFFSiJyBNzKj9tHnjx5EnRKSkownj9/Psx17NgRNJcN8rHZDoAtl22ZZpUqVQqcu4VLEtnegtsh7ty5E7S1u7D2184VjPHzeXbt2hX0nj17QK9fvx60jWNz6SlbWvNnL1myxCUCLmNlouQIotpS87E492Q1v5dfGyvGX9hnRZ1PFGGlqPy92CK7MPREIIQQnqOFQAghPEcLgRBCeE6ZtJgQZROOvXPN98aNG0Hbmnm2C+bYOVtcs12CtVpwzrmGDRuCtvXlfB7du3cHXa1aNdBhsXbOT9iYK++dYHtsrnPnXEl6ejporm23eQG2aOb2n7zXIlGExfWj5ARYs43D2bNnY74+Sn0+7x9h4on5R83JxZOfiMfCusjzifsIQgghkhotBEII4TlaCIQQwnOKvY9ACCHExYmeCIQQwnO0EAghhOdoIRBCCM/RQiCEEJ6jhUAIITxHC4EQQniOFgIhhPAcLQRCCOE5WgiEEMJz/geCisBML5ysLwAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -2344,7 +2344,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAUG0lEQVR4nO2dadCV8xvHf1HapZLSIpXSqkV70qYYywyZ0jaDYZjByDBe443BmF4ZY5AXTZYRRZZIRau0KbSrnp5WLVIoSfq/cv7X9anu+7k75zw9Pb/v59X9nd9Z7nOfu+fXuZbvVeXUqVOnghBCiGi56HyfgBBCiPOLNgIhhIgcbQRCCBE52giEECJytBEIIUTkaCMQQojI0UYghBCRo41ACCEip2pZH1ilSpVinocoMMXoE3zyySed3rt3r9Pbtm1z+p9//skdDx8+3K2VlJQ4fdlllyW+N99rx44dTtetWzd3XFpa6tY6dOjg9P79+xPXt2/f7vTBgwedbtmyZe740ksvPet5hBDC7t27nT58+LDTXbp0cbpatWpOL168OHfcrl07t7Zhwwana9eu7fQ333wTigHf5+TJk07z3svyt4OP5Wul3ddJ75XPc0MI4d9//z3r47OeZxo8F6u5dvHFFzt94sQJp//+++/U99MvAiGEiBxtBEIIETnaCIQQInLKnCMQ4uuvv3b6r7/+cnrAgAFO79q1K3c8a9Yst9a+fXun58+f73Tr1q2d7tGjh9Nbtmw56+sdPXrUrf3555+Jr824/bFjx5xu2rSp0xdd9P//P23cuPGs5xFCCFdeeaXTNWrUcHrp0qVOV63q/0l26tQpd8y8Sq9evZxu0qRJKA+YE0iKnaeRlhNIe3zSe/G80kjLbdjvPY2snysN+3x+rnxyMv+hXwRCCBE52giEECJytBEIIUTkVCnrYBr1EVxYFKOP4Oabb3aaNfKDBw922uYI2CewZ88ep1nLz/zD8uXLne7WrZvTH3zwQe6Ytfx9+vRxmv0O/fv3d3rVqlVOM6dg4/gLFy50a1dffbXTBw4ccLpOnTpON2zY0OkWLVo4bXMQ7GdgzJqfe968eaEYMM9RSLL+nUm6z9P+DXCd1zPr8wv12BAK+/dWfQRCCCFS0UYghBCRo41ACCEiR30Eosww1kifHdbr21p/Ww8fQgi33Xab06tXr3Z6zpw5Tv/2229Ojx8/3mnru8M4O+uu+/Xr5zTzF+wbYA5h+vTpuWPGlf/444/E877pppucZr6C8XcbW2aug98HeyvKi0L6/2SNjSfV66fF/LlOTQ+fWrVqOW2vP3tXjh8/nniefK9LLrnEaevTlYb6CIQQQuSNNgIhhIgclY+CZ599NnF90KBBuWOWS6bx3HPPOU2b4ELaBhejfHTgwIFO0w6hZs2aTjdo0CB3fOTIEbfGn8Jr1qxxmvYJLB/t2rWr0/andKNGjdwarTFGjBjhNENaDFPROsOe++jRo93aU0895TRDYLTPZghhxowZTj/88MO54w8//NCtXXvttU4zrGRDWIWkevXqmR6fz9+OfJ6bFuqx92cIp9uBtG3b1unevXs73bFjx7M+l6W+vMfWr1/v9IIFC5zmPWtDjmkhLqLyUSGEEKloIxBCiMjRRiCEEJFT6XMEjOM/88wzievnkyFDhjidT86gGDkCxkyZM2CppLVTSLt/fvnlF6cZO6c1NPMR9vVZ5secQL169ZymnUWzZs2cZs7AWjnwtRmvZR6FsWBaOq9bt85pG1um9QW/j++//95pxqELBXMEaZbL5ZkjsI/n9zxhwgSnx40b5zTvKZZHMwdjc0W853gfsByU99yhQ4ecfuutt5yePHly7pijVtPstvlv6UzoF4EQQkSONgIhhIgcbQRCCBE5ld5iojxzAuwTsD0HZXlv1g5XtLzMFVdc4fSnn37qNOusrcUya95/+uknp0tLSxPXb7jhBqdpgW1j6YzlsoeB9eP8HFyn5fV7772XO2ZMn7bS+/btc5r9ERx1yZyCtbX+/fff3drll1/udNbRjMWikPdtVvsKe/34vY0ZM8ZpWokQ9h3wnrO2JuwPYd8AX4v5Ndqwjx079qzv9cUXX7g19glksaf4D/0iEEKIyNFGIIQQkaONQAghIqfS5QgYh0+Ly2f1/7FeRGm+RISPZ/6iosORjay3p52z7Q1g7TPHKjJGypGOTZo0cZrx2r59++aOGStn3H3z5s1O07Z65MiRTtOzx/ZL7N27160xjk943oR9CXPnzs0d8xrwvenfdCGQb88Bn2/vK3pOsVeF39WJEyec5jjVadOmOb1o0aLcMXtoeM8x78TXnjhxotP8XDbuzxxAIXqG9ItACCEiRxuBEEJEjjYCIYSInEqXIyDMAWSN65N8n59EIecRFAPGWFnHzpp6W8/P5zZu3NjpkpISp+ln07x5c6fZl2D9VOjfc+DAAadfeeUVpx977DGnJ02a5DTHZtq8E/sE2Gvx66+/Os04/86dO52+//77nbb9E6xNpz8NczjFIi2un0/MOmvOgOvWw4feS1u3bnWaMwPYb8LrnRSbT/NfYv6MPTe1a9d2esmSJU5bn6m0MZjngn4RCCFE5GgjEEKIyNFGIIQQkVPp5xGcT9jDQC8hUp4eLedCv379nLZzVEMIYejQoU7PnDkzd9yzZ0+3xlg5vVhYI8/498qVK52uVq1a7pg+/R999JHTnCPM2LF9rRBOn0dg59N27tzZrR09ejTxtXmNeK6bNm1y2uZdGEe2PkQhhLBw4cJEXSiyziMoJGn/Rux9xFp+5o4I19mPkvS52MPBHoYHHnjA6VGjRjnNz/XSSy85bf2t6C2Udk00j0AIIUQq2giEECJytBEIIUTkVPo+gvIka06govcNkHvvvddpnv/hw4edtjFaer9v377dac4QYA330qVLnaZPjJ1pTF8jwn4HxlAZG6Z3/JYtW3LHa9eudWv169d3+p133nGaPQzsn9i2bZvTdm4ur8m8efOc7tKlSzgf5DOzuJDzjUPwcX6+dtbcRZZ8BOdlsDeFcyh4/77xxhtOf/LJJ07bHoasvRVlQb8IhBAicrQRCCFE5Cg0lAcM/WS1vC6mXUUxYCiI4RqGjmwIheV1tEdgeIa2ECzHq1WrltN2LCHHXN59991nPa8QTre7YLiH1tEDBgzIHTMcs2bNGqenTp3qNEv/GCJj+MeW2XKtR48eTrPktrxIC7nY9bSwRVb7Cq5bnTUUxMez/JR25ePHj88djx492q3xnqLVyOuvv+70lClTnKattf1cxSjl1y8CIYSIHG0EQggROdoIhBAicpQjSCHLeMkLPQeQBq1zaeM7f/58p62VA/MptGK46CL/fxKWk3Kd1g3W7oIW1Xwv2hMz9ks7jIYNGzpt47/Mizz44INOM1/B60C7C763tVVmTobXpF69eqGik7VcNJ84P69P2nvXrFnT6TvuuMPpxx9/3Ok2bdqc9bU3btzoNC0jvvrqK6eZ/6HliqUYlh76RSCEEJGjjUAIISJHG4EQQkRO9DbUrP1nDiCpN2DIkCFOVyTLiGJYAfNatGzZMvHx1iqalsmst2dL/vTp051m3wDr9+2ISFpIsL6e7f28Vg899JDTHTp0cPrLL7/MHf/4449ujX0CJ06ccJq5D36OGTNmnHWd4w4XLVrkNEeHFsuGmp+BJN17Wf+OpN3HfD2bF+Bz2cti7cRDCGHMmDFOM9/D62vHr3788cdujZYR7F1h3wx7FvL5e8vPLRtqIYQQqWgjEEKIyNFGIIQQkRNdjiBfq2jbK1CRcgKkGDkCxs6bN2/uNGvm7T3DMYuseef5cmQjcwS0mrbW0RyhydGKY8eOdZo13PSFYc6hXbt2uWN+5mHDhjm9ePFip2nVTU8ZjvC0r2/r1kM4/Zrxc9KmulAw1p7P34asNfFZegM4crR///5OP/LII0737dvXad4X3333ndPWYnzZsmWJz2WuqND220mvrRyBEEKIVLQRCCFE5GgjEEKIyKl0XkNZ+wKScgBnWo+ZHTt2OM34d9euXZ22YxYZ82esvHXr1k6zrpoxV9ay276ECRMmuLUjR444PWfOHKeZE7jmmmucpqeSjbnaEYIhhDB79myn2T/B+Dp7A+gxY59/4403ujWOM+Q1KxZpcfok0mLhWf2BiM2x3HPPPW6Nmn0EzPe8+uqrTrNvw/ajcLxpocdJFvIanwn9IhBCiMjRRiCEEJGjjUAIISKnUuQIrO9/0ryAEE6P+dMvSJwd+vKzlr9p06ZO25wCn3vdddc5TY8ezhBgDoH9Hy+//HLuuLS01K0xjk/voLlz5zrN/AV7IOz8AvYs8JqUlJQ4zVr/OnXqOM2cge0z4ByFW265xWl6KJUX+dTAMyfA12LOhPfYwIEDnR43blzumD5OzCvxHmJ+kDMF7GyIM52bpdB9PMXu49IvAiGEiBxtBEIIETnaCIQQInIuiBxBPjMDKvsc4fJk7dq1TjMGyzi/jZdv2LDBrfXq1ctpzg2mfztr+zt37uy0jefyvZ5++mmn6ZnEfMXOnTudvuqqq5yeNm1a7pgeMo0aNXKauQ56LNFbiHFp2x/Rr18/t8ZcBmvZi0XWGQFJa2mzqlu1auU0Z0QzT2KvP78bOx8jhBBeeOEFp9nrwucnzQzg5+Jjmafid5X23SW9VyG+d/0iEEKIyNFGIIQQkVMhbKgZ2kkLBSWR73mmnYuF51WR7CqKYUM9ceJEp2m9u3nzZqetrS9/vjLUQ+uFmjVrOs0xgXY0ZQj+Zz/DC7t373aalhL82c7QEENH1ppgz549bq1jx45Os+Szbt26Ti9dutRplkd27949d7xq1Sq3RtvkmTNnOs1xoIWCJbBpVtIM/1gaN27sNG00Ro0a5XTv3r0Tz83aRNASYv78+U7zfuV9wHuOYT9b6mvtVELwYyxDOH2kKcN6DEMlkdW6m2WvZ0K/CIQQInK0EQghRORoIxBCiMg5L+WjWcdFEtpCZIm95/veSe9b2e0qVqxY4fTw4cOdZszaWkzQRpplkrRrZpklY/EcG2jtFRgTZQkiX+vFF190mjHtt99+22kbz23btq1bYxz/wIEDTjNXwvGJtImw78XcB8tkmWcpFmnW0El5OpZVMidw3333OW3HgoaQXhL62Wef5Y75PfPajx8/3ukxY8Y4zRwBy6Ot/cfPP//s1qZOnZp43vmMqixG/k+/CIQQInK0EQghRORoIxBCiMg5LzmCfOLyhXh+PhTbDrYic/311zu9evVqpxs0aOD0rl27zngcQgiTJ092+v3333e6fv36Trdp08bpoUOHOn3s2LHc8bp169zayZMnnb7zzjudnjRpktO0hXj00UedZr2+hbFg3qvsPWGtO22tbZyan2Pfvn1OJ9XrF5J8xiyyj2LkyJFO07aE15P5n06dOjlt7xN+j7T4pr0HcwjMCXDkqR3V+vnnn7s1jr1k7idttGWWPEA++Yb/0C8CIYSIHG0EQggROdoIhBAicsolR1CRrZ/T/IDK0x+ookO/FHq10CZ57969ueM+ffq4NcZUOfaP8dxvv/3W6WrVqjltY+tp9eK0H7799tud5ujK9evXO23jv4xZd+vWzWn607CvgJ5J7Kew15DwmtHau1hkjWfbx7PXgXbj7du3d5rXh5+Z52L7T3gf8DzpQWX7XkI4vSeE94X1kWI+gvkcngvzOfn0BhQib6lfBEIIETnaCIQQInK0EQghROSUS45g0KBBRX19G8en57hi/oWDPv633nqr09Z7JQTvE8PY98GDB51m7JyvZWcAnOnxtq/gtddec2vWfyaE032M6DXEWQjHjx932s5SqF27tlvjDAB6EbFfomXLlk7fddddTls/Idais1ad17hYZK1bt+vsk3j33XedPnTokNP07+J3w1i8zUGUlJS4teXLlzvNvNPWrVudTvJ9CsF/rrS+gPLq8ThXKvbZCSGEKDraCIQQInK0EQghROSUS44gzac/rc+gIvchxETXrl2d5kwBxvXt/F764ixYsMBp3iNLlixxevbs2U43a9bMaes9T49/5gg495Y5A9bu05PGxu3ZR8DPyTwKZ9mOHTvWac4wtl5DderUcWt871q1aoXzAePhSfX7rLdnjwbj9Mz3MD+R1FfAx3ImBs+TM4tJUi6kkH0BWVEfgRBCiLzRRiCEEJGjjUAIISKnyqkyBrNi9uG/EClGjHLEiBFOs7afsfhhw4bljlmTbecHhBBCw4YNne7cubPTa9eudZrzCSyzZs1ymnF61vozvss4Ns9l4cKFuWPG6emVw3XOWWA+gp739t8dPZHojUPefPPNxPVzpXr16pkenxS3T6u35+Oz9DDwscwJJJ1nWSjPv4n2s6R5PfEa8t/amdAvAiGEiBxtBEIIETnnZVSluDBh+/+mTZucZqjItuQvW7bMrT3xxBNOr1ixwumVK1c63bhxY6dpX2zLR23ZagghVK3qb3OWCXLcoS0PPdPzBw8enDu2YaIQTre+YHnjDz/84HSPHj2c5nhE+94ce9m6dWuneS7FopAhlLQwR1qIM+vjk9477XMlvVexy0eTwmuFQL8IhBAicrQRCCFE5GgjEEKIyFGOQJSZunXrOt29e/fEx9ucAS0hGDvna7do0SLx8SzpLC0tzR0zVs4STVph0BqZ1tEsAbW2CBMnTnRrHIPJ/EOanUWNGjWcttdh//79bo15E46BLC+y5AzyjaWn5RQKmY/IkkOoSJYS51LWql8EQggROdoIhBAicrQRCCFE5ChHIMoMbSJYX0+7ZhvDnjJliluj7TTHQa5atcpp2jf37NnTaTv6kufFuHyrVq2cpvVzly5dnOY4Sjte8vnnn3dr48aNc5rjJJkLIRwHum7dutwxcwSMS/OaFIus9fd2nGTWvoB8ziXreaaRlEPIJ3dxLo9Peuy55Cv0i0AIISJHG4EQQkSONgIhhIicMttQCyGEqJzoF4EQQkSONgIhhIgcbQRCCBE52giEECJytBEIIUTkaCMQQojI0UYghBCRo41ACCEiRxuBEEJEzv8Aa0q8+x1iVmEAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -2354,7 +2354,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2364,7 +2364,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2374,7 +2374,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2462,7 +2462,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -2491,14 +2491,14 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 37, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2508,7 +2508,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2518,7 +2518,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2528,7 +2528,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2538,7 +2538,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2548,7 +2548,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2558,7 +2558,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAVSUlEQVR4nO2deWxU1fvGDyIgUgQFkU0oS4uAspRS2RcRNC5VERGIAUExxg01akyMaFwSI4JoIBENiCZgUSmLKCAKZQ0gS0U2qQgFBMq+KIgbv/9uzvOU3jO3M1O+v57n89d5cmbu3LkzndP7vu953grnz58/b4QQQnjLJRf7BIQQQlxctBAIIYTnaCEQQgjP0UIghBCeo4VACCE8RwuBEEJ4jhYCIYTwHC0EQgjhOZfG+sAKFSok8zxEgknGPsGXX34Z9KlTp0Dn5+eDTk9PD8b8/dm6dSvo6tWrg27dujXof/75B/TPP/8Mun///sF4xowZMHfFFVeEnveOHTtAd+vWDXTDhg1BHzlyJBj36NED5qpUqQK6sLAwdJ4/p2rVqoE+fPhwMG7atCnMrVmzBnStWrVAjx492iSDypUrg/7vv/9CH2+/x0suifa/Z9Tvsf14128Wz/P7iHKu8Zxn1Hk+b9f75L+dC6E7AiGE8BwtBEII4TlaCIQQwnNizhEIwbHISpUqgc7IyAD9999/B+Nz587BXPv27UHn5OSAbtKkCeht27aB7t27N2j7+C+++CLMjR07FjTnDAYPHgyacwZFRUWgz549G4y3bNkSeuyNGzeCTklJAX3ppfgnePnll4O28xOcb+A8yu7du01Z8O+//4Lm2HrFihVB29+beGLjFyKe3GXUc3HlFBJ1XlGfHzVncCF0RyCEEJ6jhUAIITxHC4EQQniOcgQiZuyYvzHGpKWlgeZ4eXZ2djB+//33YY5r86+66irQderUAd2qVSvQl112GehffvklGK9duxbmMjMzQfMehI4dO4Lu168f6NmzZ4NesWJFMN67dy/M9ezZs8THGmPM8OHDQe/fvx805wj27dsXjDn2Pn78eNC8zyNZcAyaz+ti9roKi4+7Yuf8PjgHwO/L3mfAc65rwOcSzzXj81SOQAghRGS0EAghhOdoIRBCCM9RjkDEzK5du0AfPHgQNPvkDB06NBh37twZ5tjv59ZbbwW9bNky0Jwz4Di/na+oX78+zO3Zswd0jRo1QK9atSr03H777TfQbdu2DcadOnWCuQULFoAeMmQIaM5HbNq0CfS0adNA2/stunfvDnMdOnQAzfX9ycJVXx8l3u2KZ0d9rSjxcfYSCssBGBPNi8iVM0jkNUwEuiMQQgjP0UIghBCeo9CQiJnatWuDrlu3Lui//voLdLt27YJxnz59YI7DSLa1szHFbanXrVsHumXLliWeC5eiNmjQwISxZMmSEo9ljDHNmzcHffLkyRJfa8SIEaGv9d5774W+1o033gg6KysrGNslssYUv4YHDhwIfe1EEdXeOcpzXSGTKHYKUcsoOdQTRbtCO2wF7bLuDiOecFhJ6I5ACCE8RwuBEEJ4jhYCIYTwHOUIRMykpqaCbtGiBWi2kbDzAqdPn4a59evXg+byUradHjBgAGiOk27YsCEYL1++HOY4/2C30DTGmF69eoHmlo987nZ8l1tucivK48ePg27cuDHozZs3g77ppptAL126NBjfe++9MDdx4kTQPF9WJLKk0/XYeNpHsoUEH4stwV2Pt4/POQBXe0jXNXOVtiYa3REIIYTnaCEQQgjP0UIghBCeoxyBiBm2Q2AraLaJsK0d7D0FF4L3CZw4cQJ0o0aNQE+dOhW0XUPPtfhsYc3W0Nxekue5JaTdupJtpCtXrgya9wnk5eWBfuONN0BzzsA+tx9//BHmHn74YdBvvvkm6EGDBpmyIIp9QtT8QTw18hzzZ835HJ5n2MLDzgPwHOtk5lESkT/QHYEQQniOFgIhhPAcLQRCCOE5yhGImLnzzjtBsxU0e+HY8XJ+LLd0zM/PD32t559/HjRbMtv1/Gwbze0f+/btW+JzjTHmzz//BM2+R7ZtNfv7sC01H5v3CcycORN0RkYGaNsn6YsvvoA5zhHweSeLqH5AiSRKToFr8TknkJKSEnosbs0aFot37UmI2k4y7LWitsGMBd0RCCGE52ghEEIIz9FCIIQQnqMcgYgZjlG3adMGNPv2Hz16NBizl9DXX38NmtteNmzYEDQ/PzMzE7TdF4D3IBw7dgz0lClTQA8bNgw0x4a///570GfOnAnG2dnZMGfvMTCmeD05t8n86aefQLPPkd37oHfv3jDHexbGjRtnyoJ44tvx5g9c/kH28V1xev6c+Xry8/m17X00PMefO/fqiOpNFAXlCIQQQkRGC4EQQniOFgIhhPAc5QhEzNx8882gc3NzQXO83K7fnzVrFsz16NEDtB13N6Z4PoJjqJwHOHv2bDDmHsULFy4EzXsY7H0BxhSPDXO+wt6nwH2ceV/BbbfdFnrs33//HTT7IhUUFATjwsJCmFu2bBlojkvzXoxEkUhvfJcPv2uPAj++UqVKwZivNV+fc+fORToX+9is+dj8ubr6H0fxIkqkb1FwPpGfIYQQolyhhUAIITxHC4EQQnhOucsRuGKKXEvMtcNNmzYFvX379gSeXTTC4oL8PsqCQ4cOgbb3CRhT3E/ojz/+CMbs88LXvVq1aqA59s7P594I9h4G7gHAOQGu1Weff65Nb9u2LWjbU+mRRx6BuW7duoHm+nE7l2FMcc8kzlfYDB8+HPSkSZNA33DDDSU+tyyJx3soqo8RazsvwDF9PjbnnXhfAffb4O+N/dnyXhU+Nv+9so6Sd+H8gqv3QUzHjPwMIYQQ5QotBEII4Tn/L0NDYeVTrrZ5DN+6cxghkaEhV+kba/tWNZEle6WFwzUdO3YEzbfiHTp0CMYrV66EucOHD4Pm23K+deaw1PXXXw/ato3gW2UuJ+XWlDzPbTE3btwI2m5dyeGxrl27guZwAofP+DqMGDEC9LRp04Lx4sWLYe7uu+8GvWvXLlMWxNMqMWrYwnVsLhG1j8+23Kz5e8IhwdTUVNAtWrQAvXPnzhKPzdbnjB02jeVcwn7j+HejNGFj3REIIYTnaCEQQgjP0UIghBCeUyY5gqgxRdfjw55v2xEbY0yTJk1Ac5y7fv36oDl+PGjQINB5eXnBmK2TOa7HcT+XVS1rm3r16oFmK4OygOOaHDvncjvbcoLtEL788kvQd911F2iOuX711VegR40aBTorKysYs7Uz5x/YzqJZs2ag27dvD5rLMu3y0ZYtW8IcW0Rs27YNNF9DfvzEiRNLPBd+LOcnOFZcVkT5+463zSLPh8XS+XPnkk4+FzunZYwxH330EWj+rbDtyadPnw5zR44cAf3rr7+C5nJTfh9h5aWua1Sa74HuCIQQwnO0EAghhOdoIRBCCM8pkxxB1Bp41+PZFti2F6hatSrMnTp1CjTXWrO9ANsjc/zYzjHk5OTAHMcFGbZJ4NaDnM+45pprSjzWq6++Cros4sP79u0DnZaWBprj+osWLSrxuddeey1o3oOwYsUK0Byn53yEnRtiS4jJkyeDvueee0BzG0zOZ7DtiL2PgPeZrF27FnRKSgpoblXZuHFj0LzP4LvvvgvGbMuxZ88e0KdPnwbN9hdlRZScgeux/L3mWDpfk7BYOh+L8zvvvvsuaN6rwvkeO+dw3XXXwRzn+zi/wDkvft+c34jyG1qaPUe6IxBCCM/RQiCEEJ6jhUAIITynwvkYA0ocX4vHNtXlhcGxObYV5vr9HTt2BGP2DooKxxVfeukl0HbsjtvRMdymkOuY9+/fD9pugWiMMePGjQvGXPvOlIVN9bx580C/8847oE+ePAnaru3nfAJ77LA3C++T4Dg9+wHZtf0cl+fcBV9LzjlxLmfq1Kmghw4dGox/+OEHmGP/H37f/H3q169f6GvPnz8/GH/++ecwx15P999/P+gnnnjCJIMwfx9jou37ceW2+Nj82XKOxbYz5+fy9eIcCvtCffzxx6A5d2R/jzhX8eyzz4LmPSB33HEHaM4N8d+v/dvh+u3la8q/Oxd8jvMRQgghyjVaCIQQwnO0EAghhOfEvI/AFcsLiwtyvIvjfL169QK9efNm0MuXLwd97ty5mM8zavySdW5uLuinnnoqGLNv0cyZM0FzHDCengJcZx9PnXFpsXMxxhRvu8g5gw8++CAYL1y4EObsvR/GFPd6Zy8i9ujhPRY1a9YMxrx35JZbbgl9rQkTJoDm7wzH3u28AF+D1atXg+ZrZp+nMcbMmTMHNO9psPdHjB49GuZ4LwXnQpKFK18Y1m6yNG0Uw7j66qtB9+3bNxjzfpKMjAzQfJ5jxowB/e2334Lmvzn7evP3k78HnLvkHBh/dpxzCPv9jaftZXD8yM8QQghRrtBCIIQQnqOFQAghPCfmHEGYV74Lu7bXGGOGDBkC+sMPP4x0vCj9PF3xMtf81q1bQY8fPz4YP/fcczDHMVuuT9+7d2/oa4XB8cmLAde8c101Xys7js95oXbt2oG2PXWMKd779/jx46B5D0aXLl2C8WeffQZzkyZNAs37P6pXrw66Tp06JR7bGPQT4ph3mzZtQHP8dtWqVaDtvRbGFN9fwXtLbDiufLH6ETDx5AFc/kC8z8LOCRhjzMiRI4Mxx/jfeust0LwHhHsGcJyevyf2vhn+nPk7xj5k/FvBfVAY+7q4fIlK81v9v/HNEUIIcdHQQiCEEJ6jhUAIITwn5hwB18xz3P/EiROg7fjZwIEDYY5906MST77CBccgOf5m95BlDw+uFWa/eI5Rco15amoqaNtPh3sxs5f6Y489ZpLNkiVLQLPHOsdUbX8g7gfL+zPYz932DjIGewAYUzxPVFRUFIw5n8CvzR5Q3G+WvXTYB8Z+X1w/vmHDBtCcC+nWrRto/rvhfsvPPPNMMOY9CBxXnjJlivlfx7UHga89w3sDBg8eDNr+bWGPqMLCwtDX4uvL58r7l+y8AH/3eX8DeyJxfw3udcA5Bztvxb5c3GPl0KFDJiq6IxBCCM/RQiCEEJ5T6tAQl8lxOZR9684hFL6NYrtcvu2PYrHs2m7Nt9P8eA47cRmYHfLi8rMtW7aAfvTRR0GzDS6/Tw6Z2WWKbJ3Mls9cfpkM+HPk0se5c+eCbtCgQTDm21duVckhEg7f8Pvn0FiYjQFblnCZ64ABA0BzeIbLBnfv3l3iedsW1cYYs3PnTtAcXuCw03333Qd606ZNwZhDjdza9GKVGIdZSrge67KE4b9Xfs9Hjx4FPWvWrGDMbWhdNg78G8a/DfzZ2aHgK6+8Eub4+8otTLksmB/P18Vu9cq2JmGWO7GiOwIhhPAcLQRCCOE5WgiEEMJzYm5VmWj7WJFckmFLzVYNHJssKCgAnZ6eHow5n+Iqo+THZ2Zmgmbr6N69ewdjLsV7/fXXQefl5YHm7f98Lhw7tnMl9erVC30s23Bw7Ld///6guRzVhssGuUyW7bb5GicKjq278nJh+Rsu4XSVj3IbW7Yjt/N0XILMNif8WpwDc/0N2flEtomvUaMGaM5PsOb8TpQ8KMPfsVja9+qOQAghPEcLgRBCeI4WAiGE8BzlCMopycgRcK3022+/DZpjk3a7voMHD8Ica7YK4Jr5NWvWgGYLcHt+/vz5MPf000+D5nnbMsKY4lbRbJFiX1veH7Fy5UrQL7zwAujFixeDZjttzjnY1iKcf6hbty7oMMv0RMKxddc+H/t74bKZduUIeD8TW5PY+zb4O+Y6T95DxPNh58bHdr0W5yP4tcP+fl2vxcSyv0R3BEII4TlaCIQQwnO0EAghhOcoR1BOSUaOYNSoUaAPHDgAukePHqDtevxatWrBXNWqVUFPmzYNNNdlc901z9tW02yPzdbQ7FfDHk+s2VfL9p/iPQgcC+ZcB9OnTx/Q27dvB223rmR7YfZb4ucuWLAg9LVLSzw5Ape3kGue24iGfZacf3G1dHTF7cN+A135Bob/Pl17MaLA56kcgRBCCCdaCIQQwnO0EAghhOfE3I9AiL59+4Lmevu9e/eC7tSpUzDmXg2cI+A9Clzbz/FebvVnx+LZp+j2228HzZ49tue/McX9gdjnyD4X9rzn3gVdu3YFzf5MfF24P4HtocRxZ84ZcI+KZBE1Xxgl3u3qbcB7KbhfgX1NOObPz+Vjcx6Kff8Z+/hR9gHEMs/nloycn43uCIQQwnO0EAghhOdoIRBCCM9RjkDEzLFjx0DbvXuNMaZatWqgx40bF4xbtGgBc23btgXNexDYS75Ro0agubbf7kHAXvCPP/446CeffBI05wS4f8GYMWNAt2rVKhjz++IcANfcc7+BZs2agV6/fj1oO069cOFCmOOczaBBg0xZEDVebT8+bI/BhY7N36kHH3wQNH/Wr732WjDm/SCunsX82bn8gcLel4tkx/yjojsCIYTwHC0EQgjhOVoIhBDCc5QjEDGTk5MDmvvFcu2zHcPmfQE1a9YEPXbsWNAcG543bx7oV155BbTdj4B79Xbv3h005zbYo+fTTz8F3bx5c9BFRUXBmPsocA+AjRs3gu7cuTPo2bNng+7Xrx9o+5pyXoV7IcTSm/ZiYL+HqLH0tLQ00A899BDoTz75BLTtzcTw9Tlz5kykc3HtcQh7rEsznDuJ8tzSoDsCIYTwHC0EQgjhObKhLqck4/ZxwoQJoOfMmQOarRjWrVsXjDmscerUKdB8m85lmVwuevTo0RL1okWLYI7LXtu1awea7ZyrVKkCmm0fbFuIrKwsmCssLASdkpICmt+XqyTXDqGx9XZBQQFoLk1dunSpSQZ8HvFYSDBcbtulSxfQbNvN30G7XSd/p1ylqkxYeMb12HhDQ2H23C7Laj4X2VALIYRwooVACCE8RwuBEEJ4jspHRcx88803oNkaunXr1qDtclO2UuDt+hzH5Nj79OnTQR88eBB0xYoVgzHnE9hagK2L8/LyQHOMdeTIkaBXr14djLkMlktXZ8yYAZqtutkSm483bNiwYMx22bVr1wbtsk1OFBy/jmKZ7HosX3u26c7PzwfN3yPbJsIV43fNR3mfrmNFbUXJr2XnTqJaXseC7giEEMJztBAIIYTnaCEQQgjP0T6Cckoy9hEMHz4cNNfy21bQxmCrSrZpyM3NBZ2dnQ2acwBcM89x/4EDBwbj9PR0mLNj+sZgW0tjjHnggQdA8z4EtqDo2bNnMGYLBK7d51wHx/k5xs37DOy2m5x/4LaYkydPBj137lyTDLjWP6zm3RiMj0etp2dcNta2dr1W2HnG8lr28ewc1YVei+P6Lvi17OPz9eZj87z2EQghhHCihUAIITxHC4EQQnhOzDkCIYQQ5RPdEQghhOdoIRBCCM/RQiCEEJ6jhUAIITxHC4EQQniOFgIhhPAcLQRCCOE5WgiEEMJztBAIIYTn/B/oeFSfDRoK1QAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -2568,7 +2568,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2656,47 +2656,678 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "

\n", - " Checkpoint 5

\n", - "
    \n", - " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", - "
\n", - "
" + "### Train the denoiser on both MNIST and FashionMNIST\n", + "\n", + "In this section, we will perform the denoiser training once again, but this time on both MNIST and FashionMNIST datasets, and then try to apply the newly trained denoiser to a set of noisy test images." ] }, { - "attachments": {}, - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 38, "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fb5a58852423438b89bef7f869097e83", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/1875 [00:00

\n", - " Bonus Questions

\n", - "
    \n", - "
  1. Try training a FashionMNIST denoising network and applying it to MNIST. Or, try training a denoising network on both datasets and see how it works on each.
    2. \n", - "
  2. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
    3. \n", - "
\n", - "" + "import torch.optim as optim\n", + "import torch\n", + "\n", + "# Some hyper-parameters:\n", + "n_epochs = 5\n", + "batch_size_train = 64\n", + "batch_size_test = 1000\n", + "\n", + "# Dictionary to store loss history:\n", + "history = {\"loss\": []}\n", + "\n", + "# Model:\n", + "unet_model = UNet().cuda()\n", + "\n", + "# Loss function:\n", + "criterion = F.mse_loss #mse_loss\n", + "\n", + "# Optimiser:\n", + "optimizer = optim.Adam(unet_model.parameters(), lr=0.0005)\n", + "\n", + "# Train loader:\n", + "train_loader = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset([train_dataset, fm_train_dataset]),\n", + " batch_size=batch_size_train, shuffle=False)\n", + "\n", + "# Training loop:\n", + "for epoch in range(n_epochs):\n", + " train_denoising_model(train_loader, unet_model, criterion, optimizer, history)" ] }, { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "tags": [ - "Solution", - "solution" - ] - }, + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "**Bonus question: Would it work to train first on MNIST and then on Fashion-MNIST?**\n", - "To train a network that can do both, training on both datasets would be a good approach. Need to shuffle training examples.\n", - "Training on one first and on the other afterwards will likely only work for the second dataset." + "for i in range(8):\n", + " visualize_denoising(unet_model, test_dataset, 123*i)" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 40, "metadata": {}, - "source": [] + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAZMElEQVR4nO2dZ6wVVffGN5ZXwYYNkXZt9CpdKYKCgkoRTGzEYIIEFE0EC/IBldiNEhM1agxBDVExCKEKgo3eq1TpUu2KFcv/0ztZ63dh9j3AOff+33l+n+bJPvecKXtm33nW2muX+/fff/8NQgghMstxpb0DQgghShcNBEIIkXE0EAghRMbRQCCEEBlHA4EQQmQcDQRCCJFxNBAIIUTG0UAghBAZ54SSfrBcuXL53I+cOPPMM52uVKlSst23b1/XtmfPHqdXr16d+t1Vq1Z1+qqrrnJ61qxZyfaYMWNcW1mam5ePfenfv7/Tixcvdvq3335zumXLlsl2tWrVXNs333zjdJ06dZyeM2eO040aNXL6zz//dPr3339PtpcvX+7a2rRp4/TXX3/t9Mknn+x0jRo1nN62bZvTzZs3T7aXLFni2qpXr+70smXLnD7uOP+/186dO53mefrPf/6TbB88eNC1tW7d2un333/f6dmzZ4d8cNJJJzl9NH2NzxVei3PPPdfp+vXrO81rdfzxxyfbP/30k2tj/7SfDSGEv//+2+lzzjnH6QoVKjhtrwf7FK/rV1995TQ//+uvvzqddk7ZxnNIzX5zKPRGIIQQGUcDgRBCZBwNBEIIkXHKlbToXD5jBPT8mzZt6vT555+fui/ff/99sn3qqae6tl69ejlt4wkhhPDzzz87fcYZZzi9dOlSpydOnJhsn3XWWa6N/ub27dudpnf9yy+/hHyRjxjBiBEjnF67dq3TPHczZsxItu+55x7XxnOxceNGpx944AGn//nnH6eHDRvmtL3O55133mH3I4Ti8YiaNWs6Td+/SpUqTts+w9/iOWBfZZ/YtGmT07Vq1XJ66tSpyTb9csYT5s+f7/SXX34Z8sGJJ57odMyjTmvjd9HzZ1zqiiuucJq+f8WKFQ/724wXcl8YM6Cvzz5o7zHGFw4cOOA0+zfja3zOEP62JfZsVoxACCFEFA0EQgiRcTQQCCFEximVGAHzc2+44Qanv/vuO6eZD0xv3eY1//jjj65t//79Tp9wgp86YfO0D/Vb9OYqV6582L+l5nHSPx4/frzT9BWPhnzECK688kqnmdN92mmnOW2v45o1a1xbx44dnbZxnhCKe72Mv5xyyimHbbdzCkIIYcqUKU6ffvrpTrdq1crpoUOHOt29e3en7XG1a9fOtXF+BH36Bg0aOM18c8bDbH75t99+69o4Z2Hy5MlO79ixI+QDeumcG5EWM2Abj5f9olu3bk4zpvDHH384Xb58+WSbufl79+51mv2A9+uCBQuc5rW1x81z8NdffznNPvnDDz84zXkzbM9lXgGfWWnxhf+iNwIhhMg4GgiEECLjaCAQQoiMU+JaQ8eSmK+6e/dup1njg168zeGlD08fkF4dvTzOaaAnmZaTy++iR8s5Dk2aNHGaPmFZg+eWOd+LFi1y2nraV199tWujp8raKzyX7AOMr9h2zg1hvj3jC9w35oSfffbZTq9cuTLZZj44vV3WqioqKkrdF7bb/HKeI86R4TnLF7F5A2m1cKyHH0IIF154odPsU5wnwLkA+/btc9ren4wrUTMOddFFFznNfeW8AnutuV/sB6xhxvgOY5Pr16932l57XudjEb/VG4EQQmQcDQRCCJFxCmIN8bWeaVq0gmihMEWM6WvWvuFrPV9TqfmaxVc6ppvafaO9wTQt/i1tJZa7oOXFUsulTax0Q7169Zy2ZagXLlzo2njstEj4Ws5zUbt2baftaz7tQH4XU1WHDBni9I033ug0S2lYi2HQoEGujaWfN2zY4DRtKvZtlja35TA6d+7s2h566CGnWX4hXxyNFcE+znudzwpqpo6z39h7jvd2rOw0y33EsFYp+xzTpfksiNlWtGGt3ZlLyeqSojcCIYTIOBoIhBAi42ggEEKIjFOQGAH9YKZosrQCfUCmcBLr9dEXpJ/GdDOmcbVo0cJp+uD2++lvxjx+pqvx8zwv3NfShueW544xEuuTXnPNNa5t1KhRTtMTveOOO5x+5JFHnL7++uud/uSTT5Jtnkd6qCyFQc3rRm/ZLl3JdGTGH/i39I7XrVvndM+ePZ0eO3Zsss14ApfvZJproYh51LadfZ73PlM4L7jggtTP87fttYstg8lrw+vO2BL33fr27PvsF4x18FryGccS90xPTeNIYgZ6IxBCiIyjgUAIITKOBgIhhMg4BYkRcN4ASy9wWjnLxdoy0yEU99dsHIAlrOnN0fejJ/vggw86PXfuXKfvu+++ZJtzDhgDYO4w8+xXrVrlNJciLGsxAi6n17BhQ6e5pKMtHTJu3DjXdskllzj96KOPOv3YY4853axZM6dZ2qFt27bJto0XhFB8zgFz+zk/grn+LHNgYxAsDc0+wJIRLIvOUt6jR4922i6j2bhxY9fGmA1jHaVFWokJEisJzvuZ301v3d5z9Ol5fmIxOt6PjP/YZwvvVd77hPEIzodgbNM+t/i3fB4eCXojEEKIjKOBQAghMo4GAiGEyDilEiPgcpL08phDy3kFxPpp9PyZfx4rDT18+HCnuUyh/T7WmaGXzNgHyyPHco3LGszDnjp1qtMsJ27jAMwHp7f+8ssvO920aVOned3orduy1H379nVtW7dudbpr165Ocw7DkiVLnGYNn40bNybb9Kjfe+89p9n3582b5/Tdd9/tNMsPb9++PdnmvI1Zs2Y5zbka+SJWYysNeue2llIIxUtt8x5hvIH3jI0h8N7mdeYymZzvxBgMY5X283xGcY4CjzsWv2BZatvPeP6PBXojEEKIjKOBQAghMo4GAiGEyDgFiRHQ/2LeK71zxhDoiTGP1tadeeKJJ1wbfWzWqOnRo4fT3bp1c7p///5O2+UY6dkyR5zHRU0Pk3VUyhrMY+cyg9OnT3farkFw1113uTaeC/YJrgGwa9cupzmHwcaG6NMzbsTjYEyK/e3NN990+qmnnkq2n3nmGdfGWAhrC/G35s+f7zQ9cxtLYb0Z1sU6FksWloRYLZu0/YitR8D8eXrv9O0Zn7DPGl5HxgQ4l4XxBi5NyX2315LrbTB2xLUP2N+peZw2Psd4g5aqFEIIcdRoIBBCiIyjgUAIITJOQWIEhL5fmzZtnGYMYPPmzU4zR9fWrqc//OWXXzr92WefOU2Plv7nwIEDnbY+LfOKCb+LtUxYqyj2faUNrwtjIryO9nhY32fAgAFOb9myJfW3OO+A3rv1VDt27OjaeM1XrlzpNGso9evXz2nGlZYtW5Zs01em7/zaa685PWLECKcZf+AcB+sHs4YS51IUaj0C+vKxvHbrYbO2ENcfiNXcYf497zH7/fws56LEfHn6/JUrV3ba5vqz1hDrFPE4eM7428TeS9wvxgiOJGagNwIhhMg4GgiEECLjaCAQQoiMU5AYAf0vxghYV4NeHP1g1r2vVatWss3aQsz1pz/MOvjMhWdteuvt0eOPeXOMATDWEVububRh3X76ubyuVtNLnzZtmtOM1dBLZp9gTretI8P1kBkz4BwEzoewtYRCCOH22293esqUKck2+wvrEvXu3dvpL774wmnGWXbu3HnYfWOsYubMmU7btZTzSa7zCNJiCPTtWZuJsSH2Md5TNqbC2l+slcV8/NhaB/x7WxcptjYE73U+89ifGe+xf885CYyF5FL76b/ojUAIITKOBgIhhMg4BbGG+GrI1zkuR8dXH75qHjx48LC/9fTTTzvNKf+rV692mlPc+dtMY7Sv7ly6jsfJV0m+HvJ1kumlZY2XXnrJ6Xbt2jnN8gnW3uGrMu2XwYMHO01LgMt60haxFl779u1dG0s702rkcTRo0MBp9hnbblNJQyjel2lx8Zo///zzTjPN8MMPP0y2u3Tp4tpoo7A/5otYuiK1tT1oefCztHJpe/D88f619k7Mio0t8cj7mVawtZ5iy2DGUlGZRsuS7jYNns8kfpaWWEnQG4EQQmQcDQRCCJFxNBAIIUTGKUiMgN4cvXOWX2ZaFz9PT8z6qvRzOcWfHiQ/f9tttznNkth2acHy5cu7NsYXKlas6DTTLenxlnUuvvhip5kSSp/TevOXXXaZa6OnyvjChAkTnOYyg1yO0qYQ07cfOXKk0/TlWW64WbNmTjMl2fYBXlOmprJPLF682OkXX3zRaaYr165dO9l+5ZVXXBvPt13WMoQQHn/88ZAPYjEBeus2TlJUVOTaWBq6atWqTu/du9dpnm8uL2l/i5/ldzPWGEsH53PKxiNi8T3GCOjz8znDa2n7KJde5X7H0nsPhd4IhBAi42ggEEKIjKOBQAghMk5BYgTM12VuNT0t5sHSi2dusV0u8Oabb3ZtnPLPfeFSlowZvPvuu07bcrMsNUs/k+08DuYaM9/devDMLy8NmjZt6nTz5s2dnjx5stO2tMPrr7/u2hiroVfMfHOW+WWM4YUXXki2+/Tp49pYmpz78sYbbzg9evRop++//36n161bl2zb2EQIxb3ea6+91mmWvL711lud5vwKW8aAy6Yy/nUkpQWOBP4OvXTm79vSJIz38d5nvIb3OmEMxi6BSl+ev8W4FOcocC4L79e0e5LfxfIsLC3CuAq1PU628XqoxIQQQoic0UAghBAZRwOBEEJknLzFCOxcAHpWnCfAHPHdu3enfjdzdidOnJhsMze4R48eTrdq1crpRYsWOf3WW285TZ/fetexGkpcfrFevXpO8+8Zv7DfVxZiBAsXLnSadV6Y2//OO+8k2w8//LBr4xKNn3/+udPMka9Tp47TzBGvW7duss16P/SCGYthaWPGKxhjsPnoNs8/hBAmTZrkNK8x4ywsS819u/zyy5Nt9lXGv8aPHx8KAY+J3jvvd+vV16hRw7Xx3G/atMlpxgAI44n2tzl/ifEbxuxsPOZQ+8LP2/uVZaUZ62BMi/c6YyFp9YI4B4ExGs0jEEIIkTMaCIQQIuNoIBBCiIyTtxhBWu0N1k1nLja9OkIv3uYm0yddsGCB06yXQ+gPs16QjUGk5fqGUDwXnj5hLBZS1paupG//9ttvOz137lynbXzm1VdfdW08N+wDrMM0b948p1mL5aabbkq2eV04B2HAgAFOM7ed17FTp05O2zUpuEYDayrRC+Z9wfYWLVo4bf1e9k3GF4YMGRIKAT1oavrdNmeeS3sy1sNYEJcRpRdPv9xeS+bq79q167CfPdTnGZfjPALrzbP+GeMR9PF5jmKxEMY7LMdi/ojeCIQQIuNoIBBCiIyjgUAIITJO3mIE9PEt9N5Yl6NKlSpO79ixw2n6ZbZ2EecoMB6xZMkSp5kLT9+QWN+e+02/kjnTjBEwFkIPkl53aUM/l+tB9+7d2+mPP/74sN+Vtq5tCMW9ZMZL6B3bNQjov9qaRyEUj/swBjB06FCnW7du7fSsWbOSbcZNOI+lZcuWTrPWEOepcA7Ehg0bkm07VyKE4vcJYzaDBg0KZQF7TLzOjC+wtj7PJ+cccR4CYwgWxmfYT/hb/G62W2+en+Vx8bj5nOGzg89I+xzjHAP+Fu+tklC2njRCCCEKjgYCIYTIOBoIhBAi4+QtRmB9K3pY9MPotTO+wHbm3Nrvp5ccWxc47btCKO63WV8w5sXFcofp9TFeUdagH85zPXPmTKd79eqVbLP2yp49e5x+9tlnnR48eLDTq1atSt0369HOnz/ftTFGwNpDjCPde++9TjNH3Hr1PCeMP6xYscJpzmno2rWr08OGDXPazitgbjp9Zvrn+SI2j4B57fb+pYdP3533I+f9xGIEdl9i83z429SsLcTnUBq8NuxjfMYxtsnjsvNNOPdEtYaEEEIcNRoIhBAi4+TNGrIpnnzlir268PWRr2R8jUp7ZWMbX6OYihp7XUyb6k2rhEvdHe2+lTa0XGi7cTk+e/y0V2iRcInRzZs3O02LgOUWrA3AtFyWz65UqZLTW7dudZqlonld7bHYVNIQQujWrZvTTLGlZcCyHCy9ceDAgWSb5RdmzJiR+reFImaR2n7OPp/rs4ApoGklmflbtFT427Gy8rSW7PfFyjzwWcBUcrZz3+0SnEwtjVl1JUFvBEIIkXE0EAghRMbRQCCEEBmnIEtV0lujpjfHaeb0yo+m7GquvntaOinb6P9afzeE4qmFJG2Jv7JAzZo1nWbpaKaP2hITPHZ6vYwJ8Nw2aNDA6W3btjm9Zs2aZLtPnz6ujSWsi4qKnGZqKj/PVD5bPrx9+/aujbEQLnfI46Y33KFDB6ebNWuWbDMVtUuXLk6vXbs2FALer7H7Ma3EMvt4hQoVnKYfznuMKZ72nmM6NmMZsdRxkhY/5HHws+wXjK/xnPL7bBkdltM+FuiNQAghMo4GAiGEyDgaCIQQIuPkLUZgfUN6cZwHQB+QHhj9MnqS1tuL5TTH/E3+fZqvyDb6lVyKkr4gS9NyX8raPAL68o0aNXKa59aWX9i7d69ro4fKUg30w3mu+H22RLaNF4RQvLQz5xkw17927dpOr1692mlbbpvfxbgQy4o0btzYaS6lyvIXn376abJdvXp118ZzwPkQhSKXUivs0+wzjKGklasIofizwX5fLDYZmycQu//s36eVqD6UZvwipnOZG6B5BEIIIXJGA4EQQmQcDQRCCJFx8hYjsNCzopfOEq30PumN5jKP4GjrcKR9PhYjYKyDxxGLfRzJknP5pH79+k6PGTPGadaFsX43l2TkuaI3zLo5LGPNmMKUKVOSbZZr5hwGXhfWoEmrYxSCj2nxu2bPnu10vXr1nF65cqXT9KHHjh3r9MiRI5Pt5557zrWxbxaqDHWMXEq38x5gLIgwBsO/tz5/Wh2iQ2leZ85p4PfZ44rNAUqbSxFCfE6SvR/Szu+h2kuC3giEECLjaCAQQoiMo4FACCEyTt5iBNbjoodFH5C1hejF0W9jbnYaufplsRrladDX43HQ3+R3Mxc5l98uBA0bNnR6/fr1TnNJSFs/iDX+p06d6nTfvn2dZp/ZsmWL023atHHargPw0UcfuTZbyz2EEKpUqeI0YwQTJkxwmtfFxjM4j2DgwIFOr1u3zml+nvEx7tuTTz552Db2txo1aoRCkGucLa0+F+GzgZr3FOcC2GdFbGnJWLyCS8lSW2IeP+dKcd+obW2hEPxxx2IdmkcghBAiZzQQCCFExtFAIIQQGSdvMQLr3dH/Yg45PVzGAOh58ftsLnasxkdabZJD/Rb/3tZJorccq6GUS2zjUPta2kycONFp5vpz/V3raS9ZssS1MWbAv2Uf4XrItrZQCL5eEH1k1nhiDKB///5Ojx492mmuOWDXEODcENY54nrJt9xyi9Os38T+Zn+L/Yf+OM9hWSTtfgohPgeEcbbKlSs7bZ8N/Gxs3gD7SWx9ZXv/5zr/geeBzwquaWyvdeyZdSTojUAIITKOBgIhhMg4GgiEECLj5C1GYGtrsM5GrCYP/V/6hPRKrT8Xyx1mTjh9eNZ+4eftb/FvmTtM7y7227HaKKXN8uXLnWYtljvvvNPpRYsWJdudOnVybUuXLnV68uTJTnNOQtoaxSGEULdu3WSb+fZck5j9kTnbLVq0cJr9cf/+/cn2tGnTDrsfIYTQqlUrp+kVs79y3WG7fgFjNPTXGUfJF7G89TTPmt4442xc25c1qDjniH9vdWw/GWNhf+a8AT637LXjcbGPcd1r3uv0/flbtp3X/WjWcE++/6i/QQghxP9rNBAIIUTGKUgZar6i8ZWMrzp8PeSreywFLRdoBfFVnb9lX9Fo9XCZQe4XNV//WMY5ZnMVmmrVqjnds2dPp1kq2p4rWjssvdC5c2enY6/lderUcbpmzZrJNkteMyWR/Wv69OlOX3rppU7Pnz//sN933XXXuTbaMx988IHTQ4YMcZrXfMCAAU7bchndu3d3bXPmzHG6bdu2oTTIpcQBrRxeV9qrtExoDRF7j8UsFJ77mG1FO8fe/zwO2tex8jJ8dvD7Fi9enGznsjRoSdEbgRBCZBwNBEIIkXE0EAghRMbJW4zA+tuxcsqc2r1ixQqnx40bd9jvDsF7gbFp5CSX8hWEKWL8rC0PEEIIDRo0cDoWOzkWU8ePJc2aNXOa3jnp0KFDsj1p0iTXxuUgWY6ZJa/59/369XPaLgHJ5SIZ26hVq1bqvowaNcppljHYvn17sl21alXXtmzZstTv3rp1a6pu0qSJ0zaewbIDXJqyUqVKoRDEPOi0Uu702WNxMN6/TMPkvlgvnrGhmG/PPsi09rQlIbkfjHHFSmMwZZklK2w/iJXKP5J0Ur0RCCFExtFAIIQQGUcDgRBCZJxy/5bQiM41N9X6lfRoOZWb/hljBP8r0P9lvrstXRBCCPv27Uu29+7dm9Nv5SO+MHz4cKenTJniNOd72PIIXGqydu3aTseWWWSZCC75aMs9029lmQL6zCyDXlRUlLovNhZEj5+lL/jbnHvCkhTMo7fnad68ea6N8x3Gjh3rNPftWMEcd8bKcvGoebx8NjAOQp+f8UX7LInN4+Fzh9eGOq2MBM8BNWG8hyXdWX7GxqXYXxmb5G/zOA6F3giEECLjaCAQQoiMo4FACCEyToljBEIIIf430RuBEEJkHA0EQgiRcTQQCCFExtFAIIQQGUcDgRBCZBwNBEIIkXE0EAghRMbRQCCEEBlHA4EQQmSc/wND09SGhvbhIQAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAYn0lEQVR4nO2dd6wV1deGt11BulQpIkgRpAlIEaSJghq7SImoYEEBMUZNlKAmRE2IqAkYg0QpUo0QpQlIEaSI0kGU3osiIEXsfn99k72ee+9s5sI99/4y7/PXfrPPmTMzZ2Z25l1rr33ef//9958TQgiRWs7P7x0QQgiRv2ggEEKIlKOBQAghUo4GAiGESDkaCIQQIuVoIBBCiJSjgUAIIVKOBgIhhEg5F57pB88777y83A/D+efb8enff//N9ba6d+9u9K233mr0okWLjG7atKnR8+fPN3rChAm53hceF+fyncu5fXkxT7Bz585GFypUyGj+T6VLl47ap06dMn233HKL0WPGjDF6x44dRpcoUcLoOnXqGL1z586ofd1115m+woULG121alWj+R83adLE6IMHDxrtH+e6detMX8eOHY0uWbKk0T/++KPRu3fvNpr7PmLEiKhdr14901e+fHmjFy5caPSWLVtcXnDRRRcZzWfD2dyvJPTc4b5ccsklUbtu3bqmj9cM78fjx48bzeP4888/jf7jjz+i9t69e03fkSNHjD5x4oTRvB/++ecfo+Pu36TP4r///jv4Gb0RCCFEytFAIIQQKUcDgRBCpJzzzrTo3NnECPjdc+1fd+rUKWr37dvX9LVs2dLoyy67zGj6hBdeaMMmJ0+eNHrx4sVR+5133jF9c+bMObMdzgB5ESNo3ry50fRc9+zZY/T+/fujdvHixU0fffdy5coZTX933759RlepUsXoX375JWrXr1/f9NFLP336tNHjx483+vDhw0bTm/fjSJdeeqnpmzx5stE8Z7///rvRRYsWNXrZsmVG+9fv2LFjTR/jCdzWqFGjXF7AeyTJs4HXZei7vD95jI0aNTLajz21bt3a9PkxK+ec+/nnn41mXOqCCy6I/X6ZMmWi9po1a0zfrFmzjF67dq3RBw4cMJrxib/++svoJDEDasY2skNvBEIIkXI0EAghRMrRQCCEECknIzGCpPMCGjdubPQrr7xiNP3jChUqRG0/t9e5rPm69H+5L8WKFTOaHrCfk37xxRebPuYSb9682eiXX37Z6FWrVrm8Ii9iBP379zd69erVRnNeQfv27aP2J598Yvp43vndWrVqGU2/l7n/V199ddRmbn7lypWN5jWxYMECo/mfP/3000b71/O2bdtMX7Vq1Yymp81cf+4L/7cNGzZEbcZkmJtOD3vIkCEuL6B3zvs7CSF/+6qrrjL6kUceMbpZs2ZGX3HFFVGb+fP8X+md05f/7bffjOb59e9/fpf66NGjRn/zzTdGT5o0yWj/f+f2QnEW9nOOQnbojUAIIVKOBgIhhEg5GgiEECLlZCRGQE+RntXDDz9s9MiRI41m3je9Oz8uwMNhLZLLL7/caD/X3bmsdWnoZcedB7/OiXNZfW96lDzucePG5fhbST3/vIgR0Ldn7SHODfBzpatXr2766O0y/55eu+/9Opc1PvP8889H7a+++sr0bdy40WjOQeB+s/4U4xN+vSr+Z7ye/Fxz52xNJOec69Gjh9EDBw402vfIue2bbrrJaOaqT5s2zeUF5zJGwPuTcz4ee+wxo3nN8Z7zYzKMF/Ke4Hd5r/P77PePO5Srz+cGz+G3335rNI+b80/itk1Ua0gIIUQQDQRCCJFyMmINhWAqVdmyZY3maxTh66UP07ho19AWoDXE18e408U+vkrSEjt06JDRN9xwQ47bTkpeWEN9+vQxmq/OPNd+SWbaFPwfmHpL64dlq5cvX260n6rK9FGmG3N6P20pWna8/rZu3Rq1a9SoYfpoPX7++edG89pmauuwYcNy3F63bt1MH1NXeR+8++67Li8IlZhIUg6B56Nt27ZGP/HEE0azRAyvI/8chGxiEmf9OJf1+vY/H/osrSM+V3hOO3ToYDTvDx9ZQ0IIIc4aDQRCCJFyNBAIIUTKOeOlKs8lXbt2NbpIkSJGswwEp5nTb4ubQk3fj34Zl0Ckrxjnr9E7plfHdNFdu3YZzeO+++67jZ46dWqOv50fhFJvWa7ZT63keWQKJ5f247l47733jL7zzjuNnjt3btTm//Lss88a/dZbbxn95ptvGs1S0CyR7acv87MsG1KzZk2j27VrZzRTPvlbvgc+ceJE08f7IlMkLSXtf56frVSpktF+rMe5rGnDTKOk7+8/C0JpriHvPMnykaGYXOhZwdI2jD359xr361zEb/VGIIQQKUcDgRBCpBwNBEIIkXLyJUbQokULo+nd0U+jD8gYgf/9JCUhnMua7xsqi+t7gfTqeBzMFQ55lvSPC1qMgHnr27dvN7pBgwZG+8dP75te75VXXmk086avueYao7kEpO/bM3bBeQJcopBwydH77rsvx9/icpEsw/H2228bzbx3f9lL52z5CufsfIlWrVqZvi1bthhNvz2vSHKPhKhdu7bRDRs2NJpxNt5D7PfntjAGENKh/Y4rE8Hvhkrv87fZzxIsLJtyrtEbgRBCpBwNBEIIkXI0EAghRMrJlxgB/V56/vQBk3h3SZdto1cXqqMSR6i2EI+L8QnmDhc06H8fO3bM6H379hntl5KmN37y5EmjWXeJyzL6S1E6l3WJx/Xr12fbdi5rCWzGqPbs2WP0HXfcYTTntdx2221Re8mSJabv2muvNZrLrIby4nleWrZsGbVnzJhh+hiDYs2ugkLcPALOs+BcFd6PhF68H7/h/cdYI/eFzyF+Pm7+RNI4Jz/P32asxP+vQ/MfclNnTG8EQgiRcjQQCCFEytFAIIQQKSdfYgRVq1Y1+vjx40aHvLmQ9x4HfUHWN4+rW8R9CcUP2M/joh/MZfoKGhMmTDDa96+di59XwNx+5s+vWbPGaHrFjL8wf9yfp8Dr6frrrzeay0VymcCXXnrJaK6l0KtXr6i9cOFC08f/mPWBGNvgOeP6BP7cDdbuD52jvOJs1rrg+aEXznUo6KXznop7FvC3eM0wRkcYg+Hn/fMQmjNEX5/9/O9YR8rfPq8hkpvaQ3ojEEKIlKOBQAghUo4GAiGESDn5EiNgTvmJEyeMpt9G35Da99foj4U8RnpzoVrrcf5bKJc4VI+EayMUNOitv/baa0bPnz/f6KVLl0btu+66y/RxzkTJkiWNZkyBMA7g5/7zPLJuEecZsN4NYyGnT5822j+WoUOHmj7WHvLXN3bOuRdffNForuEwffp0o/04zKJFi0wf10LgfIm8IjRXJ+4e4r3Ncx+6f0P3px834Xc5JyEUd+Ka3HF1zEK5/fwu10bnPAJew6VKlYraXLsj6foQ2aE3AiGESDkaCIQQIuVoIBBCiJSTLzECrs/JWi7Mr6e/FsrBjSNpDCBUVzzuu4ReMz1LnpeCRvHixY3+8ssvjeY6xPPmzYvazMXv3r270Y0aNTKaOfOsRTRgwACjV6xYEbX79u1r+rp06WK077c6Z2MZzjnXs2dPoxm/8K8JxgD8Y3bOudKlSxvNekxcs7hDhw5GjxkzJmqzLlH//v2N3rRpk8sEST1p/3wxt5/XFHPk6b2H1vzwPx/az9B8JWre+0lik6E5C6F4oa9Dx6VaQ0IIIRKjgUAIIVJORqwhvr4VKVLEaL7KlClTxuhQ6eg4ki4/l7Q/7rPcT5Yg/uWXX4zmefFfXUOvlpmAabsse8w0zSFDhkRtppp++OGHRt94441GDx8+3GjaaPwtfzlJWlR+2WjnnBs8eLDRtGOYzsztvf/++1Gb1xdtS5ZT4TXil+p2Lmtpb986Wb16tenzbSPnnGvbtq3LBLlJT/x/QmXe2e+XlXYuq50TKgPhE7J5ky43maTcDAnZOyx9w2dDkm2dCXojEEKIlKOBQAghUo4GAiGESDkZiRFwiUMS8tKTeHlx08CdC08zT0Ko/DV/i2mITIkk/pKe33//fcK9O/e0adPGaJbNZklmPy2T5Yafe+45o+l///zzz0Yz3ZQlK3r37h21GbsYMWKE0WPHjjXaTz11LmtKIz9/5ZVXRm3GrypVqmQ0U6NXrlxpNEsssESFH0thCQlqpsXmFUnTFeOWdKQXzpgASy/w80zJjiOUvs3/MsmzIWnpmlBZ6ri46tnEaHJCbwRCCJFyNBAIIUTK0UAghBApJyMxAnr+5OjRo0azxDA9W/pvvteX1PNPOs/A9zjpMbJsLX0/5qfTPyZ+mYWCECNgTIDlEejb+znxXHrPn2PgXNb8b8aVuJSlvwymc84tWbIkavM816lTx+iPPvrIaPr6LJHN5SP9a6JZs2am74MPPjCa18DNN99sNEsfs2yHH5fZvHmz6fvuu++M5tKVLLVxrjibuBr3kb49t00vnfdjXKnoUPkYXnOMEfD+5rPCn1fDz4b2m8fJ2Anx75/Q/IbQtrJDbwRCCJFyNBAIIUTK0UAghBApJyMxAnrLhDEBlqKlr/jrr78azZLFcYRKyxL6bXF1jpgDzXkDLK/N4yTlypWL7c80/J84r8DPr3fO1oxiqWfWFvrhhx+Mbtq0qdF169Y1et26dUb7Xju3tWrVKqNZz4dzHOjF0+f3/d7Ro0ebPtaEYUyA+8J8cc6X8GMjM2fONH2MZXAuRqYI1ejxvfSKFSvGfpYkqSvGzydd9pL9jBnE+fz8LOE1xM+zjheP259TlGT53DNFbwRCCJFyNBAIIUTK0UAghBApJyMxgpCHH/LCQ3U7zrQvO85mPYJQvIE+IPOWQ8dd0GIEXAOA9YCWL19utO8H89ywvs+DDz5o9IwZM4xm/SDGGD777LOofc8995g+xgxYtz9UA5/4MQbux/r1643mNcA1KJgHz/jElClTojavBy5NyaUs84rQPRbnvXNOB/eZPn2oNhjPn//boXx7+vahmEHcUpZJ5yNxXQXuC89LzZo1c9x20rhnduiNQAghUo4GAiGESDkaCIQQIuXkS4yAtWBYVz3kAzLnNs4XDOUCh3KN6ev7Xl7Iz6TPxxzzEiVKGM3zUrp0aVeQYM2n/fv3G81zff/990ftWbNmmb5OnToZ/fHHHxvNWkOs2z9//nyj77jjjhz3k3MSOK9l6tSpRtOn5xyG1q1bR21//WLnnOvSpYvRb731ltFcj3vQoEFGcx3iChUqRO1t27aZvoceeshoxmzyiqR56/594R+Pc1nvr9Aa0Hw2xNXZOdt1hEmS7TEGwLkrnD9CeFz+syJUxyg36I1ACCFSjgYCIYRIORoIhBAi5WQkRkAv/ODBg0azJg/9M65XQHw/7WzzeUNrHsflDjNmEKo9RH+U54XnLb9hLIfr7zI/f8uWLVG7SZMmpo91l+jDc63aatWqGc0cen+uAM8b6wHx+mLMgPMQjhw5YvS+ffuidosWLVwcXDfh0UcfNXrSpElG0xP3zznXpNi9e7fRnMOQKUL3nH+d81yH7jfeU3F1n7gvcXn/2WnG+EJzGPzvh3x6+vqhGkvsZ9wrjtzEDPRGIIQQKUcDgRBCpJyMWEMsI33o0CGjOXW+UKFCRvPVPC5Nk697fE1i6umuXbuMZopnXKpq3PT27H47VE6b6X+hJT4zDZdGvOGGG4zmcpR+2QfaSiy10K5dO6MLFy5s9PTp042mteRbR1u3bjV99evXN5oWHW0mWiyc3r948eKozRTOjRs3Gh2yQVk6gyUY/GuIx5y0ZMm5InSdx5U84NKctABp2/Fe53XD+9O3jvjdECHbKa6UNPtC5StCNhRTsf3zwnPEc5i0zI5zeiMQQojUo4FACCFSjgYCIYRIORmJEbBUApc8TFr+lf6Z768lTeMKpWWFSlbktB/ZESpvwVgI4xX5DWMcLB0yYcIEoxs3bhy1b7rpJtO3fft2o1l6YMeOHUYzlsNlMf3v0zOdNm2a0S+++KLR/N9mz54d+9ulSpWK2uPHjzd9/fv3N7p9+/ZGv/7660b36dPHaJbM9q8Jxox4nPSl84rQ/RnnrfNch0oo0w8/cOCA0ZUrV85x37ifTBUnvLf5rOD59Y+Fn2XsomjRokaHSutze/6+c9uMFeUGvREIIUTK0UAghBApRwOBEEKknIzECOhhMUYQmm5Nb5qlG5JM9aY3R7+N/XE+bCh+wP0m3FfOSwidl0zDc3H69Gmj6WtWqVIlaq9atcr01atXz+jVq1cbXaNGDaM554LlnP14xJAhQ0wf8++5LxMnTjR6wIABRtPnHzVqVNS+8847Td+CBQuM5pyYfv36Gc0YQY8ePYxeunRp1Ob15S9j6ZwtxV2Q8K9zlmaPi7k5l/Ue4jXHGIL/W7xek8T7nMsaE+Bv+c+K0LyBUHyQz8gkcRaVoRZCCHHWaCAQQoiUo4FACCFSTkZiBPThL7vsMqPpr9ErZ30RP4/bOesBh3x1/lZoqTzmHvufp8fIXGHWDqJfzH2lB1nQYgQVK1Y0evny5UZ37tzZaP9/53wN+tv8brNmzYzmuab/u3PnzqjNMtKs58P5GlxOktcA5zT418SSJUtMH/9zxgzWrl1rdJs2bYz26zM5Z5fw7Nmzp+ljaW/Odygo+F4640ihujj0w0M1ffz7MzRngfsSKjsdF1MIzeFgbIS1tAifS36NptB8JdUaEkIIkRgNBEIIkXI0EAghRMrJSIyA0CunN84l+YYNG2b0G2+8YbSfRxvKz6W3TL+YMYE43z5Uv3zo0KFGP//880b7efbOZfUN6SvmN9u2bTOadV44v8OvC9OtWzfTx7gR40AvvPCC0ddcc43R/rwBbm/Pnj2m7/bbbzea8wpeffVVo/k/DR8+3OhOnTpFbcYPWFOJy6yyRhKvL9aXeuaZZ6I24wmDBg0yukuXLi4/SJLHHprHE9rWiRMnjA7NBYj7LJ8N1NxX3u/+vsf1Zbct/hZ9fz6nfPj85DWmGIEQQojEaCAQQoiUo4FACCFSTkZiBMzXpce1f/9+o4sVK2Z0y5YtjS5RooTR/rwE5t7zt7lmKr05fj9uzgN9PB4X95u+4eHDh3PcdnY6v2FMgzEC+vz+GrpffPFF7HdZf6phw4ZGM0bA9ZP9+ESvXr1M36effmr03r17Y7fN42zbtq3RmzdvjtqNGjUyffPmzTO6du3aRjMmwGvg1KlTRt97771R259T4JxzTz31lNGhtTUyRVxdHdYK4v0WWid49+7dRnOd7KpVq0bt0Dom9O3529w37ov/bGBskcfJOR58roTmBvhzq0JxlNzUHtIbgRBCpBwNBEIIkXI0EAghRMrJSIyAtePpB9OrK1mypNGs2T5ixAijfV+Q8QV6spUqVTKa3h73hX6y70UfO3bM9G3atMno9evXG81830OHDhlNT5LHkt/UqlXLaNb9HzhwoNF+3ZyOHTuaPj8X37ms/i19Tub60w//6aefovakSZNMH9f65XnesGGD0WPHjjWauf3++shcY5jbYj0mXvsjR440mveKf03x+uJ8G9YeyhSh2vv+f8t1JUK1hHjP+GtBOOfc4sWLjfavUdb+YoyO83QY42LdKOI/K/jc4H5T83/nvc5z6D9rcjNPIITeCIQQIuVoIBBCiJSTEWtoxYoVRrdu3dpopnQy5ZMpdV9//XWsLqjQ/mAKGS2xhQsX5vUuJYIlkp988kmjJ0+ebLRftnrOnDmmz08tdS5ramTXrl2NpmXAdLy4VFWmg3L5Q6Zw0nZiGWv/NZ8lr1ki/auvvjJ669atRjPVlWVGevfuHbVXrlxp+nj9lC9f3mWCUHoirQvfNqEdw3s9ZM365cady2rFff7551E7tPQrrynen6Ey8P5xhrbF/ypUEpvat4ZCy1ryHJ4JeiMQQoiUo4FACCFSjgYCIYRIORmJEUyYMMHoxx9/PNHnSVzphaTTq+nF0Rek9r09/lZoSvvs2bON9ssHOOdc2bJljWYJgfyGZZA3btxodKtWrYz20xvpndPvZkxg+/btsZ/n/9agQYOo/cADD5g+phjS8w/FELhEZ7Vq1aL2uHHjTF/16tWNbtq0qdFc2pLltHncfskK/3edy5qCOHjwYJcJknrS/n3A/y1UaoHXGGMM/G3/HgyVbQiVmOD9HJe2GVqCk3rfvn1G8xpjiYqDBw9GbZa2iSvpcabojUAIIVKOBgIhhEg5GgiEECLlZCRGwHz4fv36GV2/fn2jR48eHbu9JMvTJYW+YW5ycnOCSx5ySjtLBjAHPb8JedLcX798R/PmzU0fPdOZM2ca3a5dO6P5fZZq8PPNWRqgRo0aRtOfpU9Nn54lJubOnRu1Q7n7jKvw2uUcBu6rP4emRYsWpo8eOO+zvn37xu5bbuF/FxdHc8561osWLTJ9frkO57KenylTphgdyrePW7Y2FAMIkcR7ZxyTcxo4J4fXM+MAy5Yty3FbPP+aRyCEECIxGgiEECLlaCAQQoiUc95/eVHTVAghxP8MeiMQQoiUo4FACCFSjgYCIYRIORoIhBAi5WggEEKIlKOBQAghUo4GAiGESDkaCIQQIuVoIBBCiJTzf5Na5PhRHiPUAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, fm_train_dataset, 123*i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + " Task 5.4:

\n", + "How does the new denoiser perform compared to the one from the previous section?\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5.4 Answer:**\n", + "\n", + "The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable)." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", + "\n", + "We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below)" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2e9d28e7727041ba8bdd65e7f6873d58", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/1875 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, test_dataset, 123*i)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, fm_train_dataset, 123*i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + " Task 5.5:

\n", + "How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other?\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5.5 Answer:**\n", + "\n", + "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + " Checkpoint 5

\n", + "
    \n", + " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", + "
\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + " Bonus Questions

\n", + "
    \n", + "
  1. Try training a FashionMNIST denoising network and applying it to MNIST. Or, try training a denoising network on both datasets and see how it works on each.
    2. \n", + "
  2. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
    3. \n", + "
\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "tags": [ + "Solution", + "solution" + ] + }, + "source": [ + "**Bonus question: Would it work to train first on MNIST and then on Fashion-MNIST?**\n", + "To train a network that can do both, training on both datasets would be a good approach. Need to shuffle training examples.\n", + "Training on one first and on the other afterwards will likely only work for the second dataset." + ] } ], "metadata": { From 8bfef7002f9de370f10d0981fccaceb29e131a95 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 01:55:52 +0100 Subject: [PATCH 08/51] Added the 2 new tasks to the exercies notebook --- exercise.ipynb | 174 ++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 171 insertions(+), 3 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index cab1b64..628f49e 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -68,7 +68,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -101,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -114,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1739,6 +1739,174 @@ "Your answer here!" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Train the denoiser on both MNIST and FashionMNIST\n", + "\n", + "In this section, we will perform the denoiser training once again, but this time on both MNIST and FashionMNIST datasets, and then try to apply the newly trained denoiser to a set of noisy test images." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import torch.optim as optim\n", + "import torch\n", + "\n", + "# Some hyper-parameters:\n", + "n_epochs = 5\n", + "batch_size_train = 64\n", + "batch_size_test = 1000\n", + "\n", + "# Dictionary to store loss history:\n", + "history = {\"loss\": []}\n", + "\n", + "# Model:\n", + "unet_model = UNet().cuda()\n", + "\n", + "# Loss function:\n", + "criterion = F.mse_loss #mse_loss\n", + "\n", + "# Optimiser:\n", + "optimizer = optim.Adam(unet_model.parameters(), lr=0.0005)\n", + "\n", + "# Train loader:\n", + "train_loader = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset([train_dataset, fm_train_dataset]),\n", + " batch_size=batch_size_train, shuffle=False)\n", + "\n", + "# Training loop:\n", + "for epoch in range(n_epochs):\n", + " train_denoising_model(train_loader, unet_model, criterion, optimizer, history)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, test_dataset, 123*i)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, fm_train_dataset, 123*i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + " Task 5.4:

\n", + "How does the new denoiser perform compared to the one from the previous section?\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5.4 Answer:**\n", + "\n", + "Your answer here!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", + "\n", + "We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import torch.optim as optim\n", + "import torch\n", + "\n", + "# Some hyper-parameters:\n", + "n_epochs = 5\n", + "batch_size_train = 64\n", + "batch_size_test = 1000\n", + "\n", + "# Dictionary to store loss history:\n", + "history = {\"loss\": []}\n", + "\n", + "# Model:\n", + "unet_model = UNet().cuda()\n", + "\n", + "# Loss function:\n", + "criterion = F.mse_loss #mse_loss\n", + "\n", + "# Optimiser:\n", + "optimizer = optim.Adam(unet_model.parameters(), lr=0.0005)\n", + "\n", + "# Train loader:\n", + "train_loader = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset([train_dataset, fm_train_dataset]),\n", + " batch_size=batch_size_train, shuffle=True) # here we set shuffle = True\n", + "\n", + "# Training loop:\n", + "for epoch in range(n_epochs):\n", + " train_denoising_model(train_loader, unet_model, criterion, optimizer, history)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, test_dataset, 123*i)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(8):\n", + " visualize_denoising(unet_model, fm_train_dataset, 123*i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + " Task 5.5:

\n", + "How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other?\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5.5 Answer:**\n", + "\n", + "Your answer here!" + ] + }, { "attachments": {}, "cell_type": "markdown", From 8707bb22553d27f07e8a82324f5ad308dad4fe9d Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Thu, 25 Jul 2024 02:02:26 +0100 Subject: [PATCH 09/51] removed the now implemented bonus question cell --- solution.ipynb | 15 --------------- 1 file changed, 15 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index ac7fc94..5cf1517 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -3313,21 +3313,6 @@ " \n", "" ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "tags": [ - "Solution", - "solution" - ] - }, - "source": [ - "**Bonus question: Would it work to train first on MNIST and then on Fashion-MNIST?**\n", - "To train a network that can do both, training on both datasets would be a good approach. Need to shuffle training examples.\n", - "Training on one first and on the other afterwards will likely only work for the second dataset." - ] } ], "metadata": { From 26faa1f6d0e772c654830fca95a82cb1ed4304df Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 12:51:06 +0100 Subject: [PATCH 10/51] remove colored_mnist and add dlmbl-unet packages --- setup.sh | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/setup.sh b/setup.sh index 780d608..79f46f0 100644 --- a/setup.sh +++ b/setup.sh @@ -12,6 +12,8 @@ mamba install -y ipykernel ipywidgets # install libraries needed for the exercise # model interpretability pip install git+https://github.com/pytorch/captum.git +# UNET package from dlmbl +pip install git+https://github.com/dlmbl/dlmbl-unet.git # computer vision deep learning pip install torchvision # progress bars @@ -28,4 +30,4 @@ pip install seaborn # download data needed for the exercise python download_mnist.py -conda deactivate \ No newline at end of file +conda deactivate From d0037c2173d3e32240531bc2471183f848227ca5 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 13:33:39 +0100 Subject: [PATCH 11/51] fix classification package install in setup --- setup.sh | 2 ++ 1 file changed, 2 insertions(+) diff --git a/setup.sh b/setup.sh index 79f46f0..e88e169 100644 --- a/setup.sh +++ b/setup.sh @@ -12,6 +12,8 @@ mamba install -y ipykernel ipywidgets # install libraries needed for the exercise # model interpretability pip install git+https://github.com/pytorch/captum.git +# classification package +pip install git+https://github.com/adjavon/classification.git # UNET package from dlmbl pip install git+https://github.com/dlmbl/dlmbl-unet.git # computer vision deep learning From bd21329ff5c59a424ac47c9247ffe4350c748abc Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 15:15:54 +0100 Subject: [PATCH 12/51] switch to vanilla tqdm --- solution.ipynb | 504 +++++++++++++++---------------------------------- 1 file changed, 156 insertions(+), 348 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index 5cf1517..e4d4794 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -151,7 +151,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -302,7 +302,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -311,7 +311,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -383,7 +383,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -578,7 +578,7 @@ "metadata": {}, "outputs": [], "source": [ - "from tqdm.notebook import tqdm\n", + "from tqdm import tqdm\n", "\n", "# Training function:\n", "def train_mnist(model, train_loader, batch_size, criterion, optimizer, history):\n", @@ -704,66 +704,47 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "metadata": { "tags": [] }, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "91699482c5454723be50c26d8b71196b", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/937 [00:00" ] @@ -976,7 +961,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -1006,7 +991,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 21, "metadata": { "tags": [] }, @@ -1028,7 +1013,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -1089,26 +1074,26 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_1542627/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1118,7 +1103,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1128,7 +1113,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxMAAANXCAYAAABOkwIqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzddVhU2RvA8e+QAipKCYiIgoHtYqzdrrF2d4uKnWthrIrdYq1rx9q17trdLYqAlC2IAQrS8/uD3VlGQJGfMCjv53nm2Z1zzz0xzlzmnRNXoVQqlQghhBBCCCHEF9LSdAOEEEIIIYQQ3yYJJoQQQgghhBBpIsGEEEIIIYQQIk0kmBBCCCGEEEKkiQQTQgghhBBCiDSRYEIIIYQQQgiRJhJMCCGEEEIIIdJEggkhhBBCCCFEmkgwIYQQQgghhEgTCSaEEMmqWbMmNWvW1HQzklAoFEyePFnTzUjR//O62dnZ0b1796/anozSvXt37OzsNN0MIYQQGUyCCSG+IwqFIlWPU6dOpWs7tmzZwsKFC9O1jk8JDAxU9XXatGnJ5unUqRMKhYLs2bNncOu+LWFhYUyZMoXSpUuTPXt2DAwMKFGiBGPGjOHZs2eabt4XsbOzU70vtLS0yJUrFyVLlqRv375cvnz5/yp7xowZ7N279+s0VAghviE6mm6AEOLr2bhxo9rzDRs2cPTo0STpjo6Ony3ryJEjaW7Hli1buHv3LkOHDk1zGV9DtmzZ2Lp1KxMmTFBLDw8PZ9++fWTLlk1DLfs2+Pv7U7duXR49ekSbNm3o27cvenp63LlzhzVr1rBnzx58fHw03cwvUqZMGUaMGAHAu3fvuH//Pjt27GD16tUMGzaM+fPnp6ncGTNm0Lp1a5o3b/4VWyuEEJmfBBNCfEc6d+6s9vzSpUscPXo0SXpq6Onpfa1maUyjRo3YvXs3t2/fpnTp0qr0ffv2ER0dTYMGDThx4oQGW5h5xcbG0rJlS4KCgjh16hRVq1ZVOz59+nRmzZqlodalXd68eZN8HmbNmkXHjh1ZsGABhQoVon///hpqnRBCfHtkmpMQWczatWupXbs2FhYW6OvrU6xYMZYvX54k38dz/0+dOoVCoWD79u1Mnz4dGxsbsmXLRp06dfD19VU7788//+Thw4eqKSWJ59JHRUUxadIkHBwc0NfXJ1++fIwePZqoqCi1+qOiohg2bBjm5ubkyJGDpk2b8uTJky/qa6VKlShQoABbtmxRS9+8eTMNGjTAxMQk2fPc3d0pXrw4+vr6WFtb4+Liwtu3b5PkW7VqFfb29hgYGFChQgXOnj2bbHmp7XNqhYeHM2LECPLly4e+vj5FihRh7ty5KJVKtXwKhYKBAweyd+9eSpQogb6+PsWLF+fvv//+bB27du3i9u3bjB8/PkkgAZAzZ06mT5/+yTLi4+NZuHAhxYsXJ1u2bOTJkwdnZ2fevHmjlm/fvn00btwYa2tr9PX1sbe359dffyUuLk4tX82aNSlRogSenp7UqlULQ0ND8ubNy+zZsz/bn08xMDBg48aNmJiYMH36dLXXce7cuVSuXBlTU1MMDAxwcnJi586daucrFArCw8NZv3696j3/79qXhw8fMmDAAIoUKYKBgQGmpqa0adOGwMDA/6vNQgiRWcjIhBBZzPLlyylevDhNmzZFR0eHAwcOMGDAAOLj43Fxcfns+TNnzkRLS4uRI0cSGhrK7Nmz6dSpk2rO+fjx4wkNDeXJkycsWLAAQLUuIT4+nqZNm3Lu3Dn69u2Lo6MjHh4eLFiwAB8fH7U5571792bTpk107NiRypUrc+LECRo3bvzF/e3QoQObNm1i5syZKBQKQkJCOHLkCBs3bkz2S/XkyZOZMmUKdevWpX///nh7e7N8+XKuXr3K+fPn0dXVBWDNmjU4OztTuXJlhg4dir+/P02bNsXExIR8+fKpyvuSPqeGUqmkadOmnDx5kl69elGmTBkOHz7MqFGjePr0qeo1/9e5c+fYvXs3AwYMIEeOHCxevJhWrVrx6NEjTE1NU6xn//79AHTp0uWL2peYs7Mz69ato0ePHgwePJiAgACWLl3KzZs31V7LdevWkT17doYPH0727Nk5ceIErq6uhIWFMWfOHLUy37x5Q4MGDWjZsiVt27Zl586djBkzhpIlS9KwYcM0tzV79uy0aNGCNWvW4OnpSfHixQFYtGgRTZs2pVOnTkRHR7Nt2zbatGnDwYMHVe/HjRs30rt3bypUqEDfvn0BsLe3B+Dq1atcuHCB9u3bY2NjQ2BgIMuXL6dmzZp4enpiaGiY5jYLIUSmoBRCfLdcXFyUH3/MIyIikuT76aeflAULFlRLq1GjhrJGjRqq5ydPnlQCSkdHR2VUVJQqfdGiRUpA6eHhoUpr3LixMn/+/Enq2bhxo1JLS0t59uxZtfQVK1YoAeX58+eVSqVSeevWLSWgHDBggFq+jh07KgHlpEmTPtnvgIAAJaCcM2eO8u7du0pAVeeyZcuU2bNnV4aHhyu7deumNDIyUp0XHBys1NPTU9avX18ZFxenSl+6dKkSUP7+++9KpVKpjI6OVlpYWCjLlCmj9lqsWrVKCai9bqnts1KpVObPn1/ZrVu3T/Zt7969SkA5bdo0tfTWrVsrFQqF0tfXV5UGKPX09NTSbt++rQSUS5Ys+WQ9ZcuWVRobG38yT2LdunVT+zc/e/asElBu3rxZLd/ff/+dJD2596Szs7PS0NBQGRkZqUqrUaOGElBu2LBBlRYVFaW0tLRUtmrV6rNtzJ8/v7Jx48YpHl+wYIESUO7bty/FtkVHRytLlCihrF27tlq6kZFRsv92yfXt4sWLSfohhBDfKpnmJEQWY2BgoPr/0NBQQkJCqFGjBv7+/oSGhn72/B49eqitp6hWrRqQsFj3c3bs2IGjoyNFixYlJCRE9ahduzYAJ0+eBODQoUMADB48WO38tCzoLl68OKVKlWLr1q1AwuLwZs2aJfuL8LFjx4iOjmbo0KFoaf13eezTpw85c+bkzz//BODatWsEBwfTr18/tdeie/fuGBsbp6nPqXXo0CG0tbWTvDYjRoxAqVTy119/qaXXrVtX9Ss5QKlSpciZM+dn/73CwsLIkSPHF7UtsR07dmBsbEy9evXU+u3k5ET27NnV+p34Pfnu3TtCQkKoVq0aEREReHl5qZWbPXt2tTUPenp6VKhQIVXvv8/5dwTt3bt3ybbtzZs3hIaGUq1aNW7cuJGqMhOfHxMTw6tXr3BwcCBXrlypLkMIITIzmeYkRBZz/vx5Jk2axMWLF4mIiFA7FhoamuTL8MdsbW3VnufOnRsgyTz45Dx48ID79+9jbm6e7PHg4GAgYZ65lpaW2pdggCJFiny2juR07NiRefPmMWzYMC5cuMC4ceOSzffw4cNk69HT06NgwYKq4//+t1ChQmr5dHV1KViwoFpaavucWg8fPsTa2jrJF/1/d+j6t23/+vjfCxL+zT7375WagONTHjx4QGhoKBYWFskeT9zve/fuMWHCBE6cOEFYWJhavo8DXBsbGxQKhVpa7ty5uXPnTprb+q/3798DqL22Bw8eZNq0ady6dUttjcvHbUjJhw8fcHNzY+3atTx9+lRtPUZqgnchhMjsJJgQIgvx8/OjTp06FC1alPnz55MvXz709PQ4dOgQCxYsID4+/rNlaGtrJ5uu/Gjxb3Li4+MpWbJkittvJl5r8DV16NCBsWPH0qdPH0xNTalfv3661JMcTfX5X2n99ypatCg3b97k8ePHaWpjfHw8FhYWbN68Odnj/wZXb9++pUaNGuTMmZOpU6dib29PtmzZuHHjBmPGjEnynvx/3n+fc/fuXQAcHBwAOHv2LE2bNqV69eq4u7tjZWWFrq4ua9euTbKoPyWDBg1i7dq1DB06lEqVKmFsbIxCoaB9+/ap+rwJIURmJ8GEEFnIgQMHiIqKYv/+/Wq/WH/pVJvPSelXW3t7e27fvk2dOnU++ctu/vz5iY+Px8/PT22UwNvbO03tsbW1pUqVKpw6dYr+/fujo5P8pS9//vyqehKPMERHRxMQEEDdunXV8j148EA1XQkSprEEBASobUOb2j6nVv78+Tl27Bjv3r1T+wX93+lA/7bt/9WkSRO2bt3Kpk2bGDt27Befb29vz7Fjx6hSpYraVJ+PnTp1ilevXrF7926qV6+uSg8ICEhTu9Pq/fv37Nmzh3z58qlGeXbt2kW2bNk4fPgw+vr6qrxr165Ncn5K/7Y7d+6kW7duzJs3T5UWGRmZ7O5gQgjxLZI1E0JkIf/+qvvxVIvkvhz9P4yMjJKdwtG2bVuePn3K6tWrkxz78OED4eHhAKpdeRYvXqyW5/+5q/a0adOYNGkSgwYNSjFP3bp10dPTY/HixWqv0Zo1awgNDVXt3lOuXDnMzc1ZsWIF0dHRqnzr1q1L8iUxtX1OrUaNGhEXF8fSpUvV0hcsWIBCofi/djRKrHXr1pQsWZLp06dz8eLFJMffvXvH+PHjUzy/bdu2xMXF8euvvyY5Fhsbq3qdkntPRkdH4+7u/n/2IPU+fPhAly5deP36NePHj1cFBtra2igUCrUtagMDA5PdgcvIyCjZAEFbWzvJqMmSJUuSbHsrhBDfKhmZECILqV+/Pnp6ejRp0gRnZ2fev3/P6tWrsbCw4Pnz51+tHicnJ/744w+GDx9O+fLlyZ49O02aNKFLly5s376dfv36cfLkSapUqUJcXBxeXl5s376dw4cPU65cOcqUKUOHDh1wd3cnNDSUypUrc/z4cbX7WXypGjVqUKNGjU/mMTc3Z+zYsUyZMoUGDRrQtGlTvL29cXd3p3z58qqFv7q6ukybNg1nZ2dq165Nu3btCAgIYO3atUnWTKS2z6nVpEkTatWqxfjx4wkMDKR06dIcOXKEffv2MXTo0CTrTNJKV1eX3bt3U7duXapXr07btm2pUqUKurq63Lt3jy1btpA7d+4U7zVRo0YNnJ2dcXNz49atW9SvXx9dXV0ePHjAjh07WLRoEa1bt6Zy5crkzp2bbt26MXjwYBQKBRs3bvwq05aS8/TpUzZt2gQkjEZ4enqyY8cOXrx4wYgRI3B2dlblbdy4MfPnz6dBgwZ07NiR4OBgli1bhoODQ5I1Gk5OThw7doz58+djbW1NgQIFqFixIj///DMbN27E2NiYYsWKcfHiRY4dO/bJbXmFEOKboqltpIQQ6S+5rWH379+vLFWqlDJbtmxKOzs75axZs5S///67ElAGBASo8qW0NeyOHTvUyvt3G9a1a9eq0t6/f6/s2LGjMleuXEpAbcvQ6Oho5axZs5TFixdX6uvrK3Pnzq10cnJSTpkyRRkaGqrK9+HDB+XgwYOVpqamSiMjI2WTJk2Ujx8//uKtYT/l461h/7V06VJl0aJFlbq6uso8efIo+/fvr3zz5k2SfO7u7soCBQoo9fX1leXKlVOeOXMmyev2JX1OzdawSqVS+e7dO+WwYcOU1tbWSl1dXWWhQoWUc+bMUcbHx6vlA5QuLi5Jzk9tPUqlUvnmzRulq6ursmTJkkpDQ0NltmzZlCVKlFCOHTtW+fz5c1W+j7eG/deqVauUTk5OSgMDA2WOHDmUJUuWVI4ePVr57NkzVZ7z588rf/zxR6WBgYHS2tpaOXr0aOXhw4eVgPLkyZOqfDVq1FAWL148SR0p1Z1cvwEloFQoFMqcOXMqixcvruzTp4/y8uXLyZ6zZs0aZaFChZT6+vrKokWLKteuXaucNGlSks+Vl5eXsnr16koDAwMloHp937x5o+zRo4fSzMxMmT17duVPP/2k9PLy+qJ/AyGEyMwUSmU6/fwjhBBCCCGE+K7JmgkhhBBCCCFEmkgwIYQQQgghhEgTCSaEEEIIIYQQaSLBhBBCCCGEEN+Z5cuXU6pUKXLmzEnOnDmpVKkSf/31l+p4ZGQkLi4umJqakj17dlq1akVQUNAX1yMLsIUQQgghhPjOHDhwAG1tbQoVKoRSqWT9+vXMmTOHmzdvUrx4cfr378+ff/7JunXrMDY2ZuDAgWhpaXH+/PkvqkeCCSGEEEIIIbIAExMT5syZQ+vWrTE3N2fLli20bt0aAC8vLxwdHbl48SI//vhjqsuUaU5CCCGEEEJ8I6KioggLC1N7REVFffKcuLg4tm3bRnh4OJUqVeL69evExMRQt25dVZ6iRYtia2vLxYsXv6g93+UdsGNC/DXdBI0wzV/385nEdyMi5tMXDiG+BwWNrTTdBI3wD/16d6T/lhjq6mu6CRqRQ89A003QiKdv7mm6CSnKzN8l3ZZuYMqUKWppkyZNYvLkyUnyenh4UKlSJSIjI8mePTt79uyhWLFi3Lp1Cz09PXLlyqWWP0+ePLx48eKL2vNdBhNCCCGEEEJ8j8aOHcvw4cPV0vT1kw/EixQpwq1btwgNDWXnzp1069aN06dPf9X2SDAhhBBCCCHEN0JfXz/F4OFjenp6ODg4AODk5MTVq1dZtGgR7dq1Izo6mrdv36qNTgQFBWFpaflF7ZE1E0IIIYQQQiQWH5d5H/9Pt+LjiYqKwsnJCV1dXY4fP6465u3tzaNHj6hUqdIXlSkjE0IIIYQQQnxnxo4dS8OGDbG1teXdu3ds2bKFU6dOcfjwYYyNjenVqxfDhw/HxMSEnDlzMmjQICpVqvRFOzmBBBNCCCGEEEJ8d4KDg+natSvPnz/H2NiYUqVKcfjwYerVqwfAggUL0NLSolWrVkRFRfHTTz/h7u7+xfV8l/eZyMwr8NOT7OaUtchuTiIrkN2cshbZzSlrydS7OQV5a7oJKdLNU0TTTVAjayaEEEIIIYQQaSLBhBBCCCGEECJNZM2EEEIIIYQQicXHa7oF3wwZmRBCCCGEEEKkiQQTQgghhBBCiDSRaU5CCCGEEEIkolTKNKfUkpEJIYQQQgghRJpIMCGEEEIIIYRIE5nmJIQQQgghRGKym1OqyciEEEIIIYQQIk0kmBBCCCGEEEKkiUxzEkIIIYQQIjHZzSnVZGRCCCGEEEIIkSYSTAghhBBCCCHSRKY5CSGEEEIIkVh8nKZb8M2QkQkhhBBCCCFEmkgwIYQQQgghhEgTmeYkhBBCCCFEYrKbU6pl+ZGJ8PAIZi5cQb2W3XCq1YxOzsPxuO+tOh7y+g3jp82jVtNOlKvdHOfhE3j4+Okny9y5/y+69h9J5QZtqNygDb2HjMXD01stz9otO6neuD3VG7dn3dZdasfu3POibc9BxMZm/Hy9Pn274OF5huBX9zlxajdOTqVSzFvUsRAbN7vj4XmGsHB/Brj0SJKnbbtmeHqf4+GTm8yYOV7tmK1tXm7cOk6OHNm/ej++VFbttxBZQaeebThxfT8ej8+z4+91lCpbPMW89RvXYtfRDVzzPcmtwLPsO7mZZm0aqeXpOaAzFz2PcNHzCD37d1I7VuqH4uw+thFtbe106Yv4vKx6Pe/WuwOXbh/B7/kNDhzdSpkfSqaYt2PX1uw+tIF7ARe4F3CBbXt+S5LfeWB3bvuc4bbPGZxduqkdK+tUkr9Obpf3uQAkmMB15iIuXr2Jm+tI9mxcTuUKP9BnyDiCXoagVCoZ8stUnjx7weJZruxYuxRrSwt6DxlHxIfIFMu8euMOjerV5PfFM9m0cj6WFub0HTaeoJchAHj7BrDst03MmfoLs6eMYcmqDfj4BQAQGxvH1DlLmDhqIDo6GfshbdmqMTNmjmOm22KqVWmCh8d9du9bj5m5abL5DQ0MCAx8xGTX2bx4EZzkuIlpbpYsc2PCODdaNO1Gu/bNaNCgtur4/IW/Msl1Nu/evU+3PqVGVu23EFlBo+b1GDt1GEvnrqZ5nc543fNhzfYlmJjlTjb/2zdhrFjwO+0a9qBJzfbs2noAt8WuVK31IwBFijkwZEw/hvUdx3Dn8Qwd25/CjvYAaGtrM3XuOCaNdCMuThZvakJWvZ43bdGASdNGM3+WOw1qtsHzrjebd63E1Mwk2fyVqpZn365DtG3Sk6b1O/Hs6Qu27F6FpZUFAI7FCzNq7EAG9BqFS+9RjBo/mKLFCgEJ7/OZ8yfxy/Cp8j4XQBYPJiKjojh2+hzDXXpRrkxJbG2scenVGVsba/7Y8ycPHz/l9j0vJo4cSEnHIhTIb8PEkQOJiori0NFTKZY7a/IY2rf8maKF7SmYPx9TfhlCfHw8l67dAiDg4WMK29tR0akMP5YrS2GHAgQ8fAIkjFg4lSlJScciGfAKqBs4qBfr1/7B5o078fbyZejgCXz48IEuXdskm//GjTtMHD+TXTsPEhUVneR4Abt8hIW9Y/euP7lx4w5nTl+icNGEP7qt2zQhJiaGA/sPp2ufUiOr9luIrKBHv05s37SX3VsP4OcTgOtINyI/RNK6Y9Nk81+5cJ2jh07h9yCQx4FP2bBqG96evjhVLANAwUJ2eHs+4NK5a1w8exVvT18KFrIDoPfALly9eAOPW54Z1Dvxsax6Pe8zoBtbNuxk+5a9PPD245fhU/gQEUn7zi2TzT+o7xjWr9nGvbte+D0IYORgV7QUWlStnhA0OxQqwP17Ppw/e5lzZy5z/54PDoUKANB/cA8uXbjG7Zt3M6x/GhEfn3kfmUyWDibiYuOIi4tHX09XLV1fX48bd+4RHRMDgF6i41paWujq6XLzzr1U1xMZGUVsbBzGOXMAUMjejsDHT3n+IphnL4J4+PgpDgXz8+jJM/YeOsrgPl2/Qu++jK6uLmXKluDkyfOqNKVSyamT56lQoWyayvTzC8TAIBulShcjd25jfnAqxb27XuTKlZMJE4cxcvjkr9P4/0NW7bcQWYGurg7FSxflwunLqjSlUsmFM1coUy7lqS+JVapWngL2+bl68SYAPp6+2NnbYpU3D9Y2ltjZ2/Lgvh/57PLSskMTFs5Yni59EZ+XVa/nurq6lCpTjLOnLqrSlEol505fwql86VSVYWCYDR1dHd6+DQXgvucDCjjYYW1jRd58VhR0yI/XfV/y2+WjXccWzJ6+OF36Ir5NWXoBtpGRIaVLOLJi3VYK5rfF1CQXh46d5vZdL2zzWlEgfz6s8liwaOU6XEcNwtAgGxv+2ENQcAgvX71OdT3zl/+OuZkJlcolXMzs7WwZ4tydPkPHATDEuTv2drb0HjKW4QN6cv7KddzXbEZHR5tfhvajXJmU5z1+LaamudHR0eFlcIhaenBwCIUL26epzLdvw+jXdxQrV8/DIJs+27bs4fixsyx1n8mqlRvJb2fDth2r0NXVwW36Yvbt/etrdOWLZNV+C5EV5DbJhY6ODiEv1a/XIcGvKehgl+J52XMYcdbjL/T09IiPi2PymFmqgMTvQSDzp7uzdqc7APOmLcPvQSDrdi5jzpTFVK1diUGj+hIbG8u08XO59k8QItJfVr2em5j++z5/pZb+8uUr7P8ZTfic8ZNHEPQiWBWQ+Pr4M+vXhWzbvRqAmVMX4uvjz7Y9vzFt0jxq1q7K8F8GEBsTi+tYNy5fuP51OyW+KVk6mABwmzgSV7cF1G7eGW1tLRwLO9Cwbg08vX3R1dFh4YwJuLotpErDtmhra/FjubJU+7EcylSW/9vG7fx17DRrl85GX19Pld6uRWPatWiser7v0FEMDQ0oXcKRJh36sO23RQQFhzDKdSaHd65FT08vueIzvYMHjnDwwBHV8ypVK1CiRFFGjZjMLY+T9Ow+hKCgl5w8vZfz568kuRh+q7Jqv4X4HoS/j6BZrY4YGRlSqVp5xk4dxuPAp1z55wvTtvW72Lb+v40zWrRrTPj7CG5e8+DwxV20qt8VSysLFqyaQW2npsREx2iqK+Ir+N6v5y5De9O0ZUPaNOmuNtVr49rtbFy7XfW8TftmvH8fzvWrtzlz9SCNa7fDytoS99/mUqlMfaK/s/e5UnZzSrUsH0zY2lizbtkcIj5EEh4egbmZCSMmumFjbQlA8aKF2LV+Ge/ehxMTE4NJ7lx06DOU4kULfbbstVt2smbTdlYvnEERh5R/HXjzNpTla7ewbtlsPO55kz9fXtUjNi6WwMdPKWyful8X0urVqzfExsZibmGmlm5hYUZQ0MuvUoeenh7zF0ylb58RFLS3Q0dHm/PnrgDg5xtAuXKl+fuvE1+lrtTKqv0WIit48/otsbGxmJmrL0I1szDhZXDKX/iUSiWPAhLWsd2/64N94QI4D+2uCiYSy21izMCRfejYtC+lfyhBoN8jHvo/5qH/Y3R1dChgb4vPfb+v2zGRrKx6PX/96t/3ufoic3Nz0ySjNB9zHtgdl6G9aN+8N/fv+aSYL7dJLoaN6U+rxt0oW64U/r4PCfB/RID/I3R1dSjoYIeX54Ov0h/x7cnSayYSMzTIhrmZCaFh77hw5Tq1q/2odjxHdiNMcufi4eOn3PN6QK2qP6ZQUoLfN+9g5bqtrJj3KyUcC38y76zFq+jStjmWFubExccRGxurOhYXF098XPpHxzExMdy6eZeaNSur0hQKBTVqVubKla8zTD96jAvHjp3h9q17aGtroaP9Xyyro6ujkS3msmq/hcgKYmJiuXfbi0rVK6jSFAoFlaqV59a1O6kuR6GlleLo8LhfR7Bu5VaCngcnfL51//t8a+toy+c7A2XV63lMTAx3bnlStcZ/30sUCgVVq1fk+tXbKZ7Xf3BPho7qR+fWzty59el1oFNmjGG1+waePwtCW0sL3Y/f51ryPs/KsvzIxPnL11EqldjZ2vDoyTPmLVtDAVsbmjeuD8DhE2fJncsYqzzmPPAPZObCFdSuVokqFZ1UZYz9dS4WZqYM65+wP/WaTdtZ+ttGZk8aQ16rPIT8s77C0MAAQ0MDtfovXLnBw8dPmTFhBAAlHAsT8PAJZy9e5UXwS7S0tLDLb5MRLwVLl6xhxaq53LzpwbVrtxng0gNDQ0M2bdwJwMrVc3n2LIgpk+YACYu+ijo6AAmL1K2s81CylCPh7yPw93+oVnaRog60bPUzVSv/DICPtx/x8fF06dqW4KCXFC5sz43rqf/j/jVl1X4LkRWsXbGZWUsmc/eWJ3du3KObc0cMDA3YtfUAALOXTiHoRTDzpi0DwHlIdzxu3edx4BP09HSpUbcKzdo0YvJotyRlV65RETt7W0YPnATAnZueFHTIT/U6lbGyzkN8XDz+vg+TnCfST1a9nq92X88C9xncuXmPmzc86NO/CwZGBvyxeQ8Ai5bP4PnzYGZOXQjAgCG9GDl2IAP7jObxo2eq0Zzw8AgiwiPUyq5WsxIF7O0Y0j9hneftm3exL1SAWnWrYp3Xivi4ePx8AzKusxklE+6alFll+WDi3ftwFq5YS9DLEIxz5qBejaoMdu6Grk7CS/Py1WtmL1nFq9dvMTc1oWmDOvTr0UGtjOdBwWgpFKrnf+z5k5iYWIZNmK6Wr3/PTrj06qx6HhkVxYz57sydOhYtrYRBIksLc8YO68+EGQvQ09Vl+oQRZNPXT6/uq9m960/MzEwYN2EYefKY4XHnPq2ad1cNk9rYWBOf6MNlZWXB+Yt/qp4PGdqXIUP7cvbMJRo37KhW9uIlMxj3y3QiIj4ACTtc9XcezdwFU9DX12Pk8Ek8fx6UAb1MKqv2W4is4NDeo5iY5mbwmH6YW5hy/64PvdoN4tU/i7KtbCyJTzQ32sDQgMmzx2BpZUFkZBT+DwIZNWAih/YeVStXP5s+rjNHM6zPWJTKhFV0Qc+D+XXcHNwWuxIdFcOYQZOIiozKuM6KLHs937/nb0zMTBg5biDmFmbc8/Cic2tn1foNaxsr4uP/W+3ZtWc79PX1WL1hoVo582YuY/4sd9XzbNn0mT57PP17jlS9z58/C2LimBnMXzqd6Ohohg4YR6S8z7M0hfLfd8d3JCbEX9NN0AjT/HU13QSRgSJi5OItvn8Fja003QSN8A99rukmaIShbsb8eJbZ5NAz+Hym79DTN6nfZj+jRT24oOkmpEi/UOXPZ8pAGh2ZCAkJ4ffff+fixYu8ePECAEtLSypXrkz37t0xNzfXZPOEEEIIIURWJLs5pZrGFmBfvXqVwoULs3jxYoyNjalevTrVq1fH2NiYxYsXU7RoUa5du/bZcqKioggLC1N7REXJL7ZCCCGEEEKkN42NTAwaNIg2bdqwYsUKFInWG0DCtnz9+vVj0KBBXLx4MYUSEri5uTFlyhS1tAmjBuM6eshXb7MQQgghhBDiPxpbM2FgYMDNmzcpWrRosse9vLwoW7YsHz58+GQ5UVFRSUYitN49RT+DFi1nJrJmImuRNRMiK5A1E1mLrJnIWjL1mgmv05puQor0i9bQdBPUaGxkwtLSkitXrqQYTFy5coU8efJ8thx9ff0kgUNM9Kdv0iKEEEIIIYT4/2ksmBg5ciR9+/bl+vXr1KlTRxU4BAUFcfz4cVavXs3cuXO/Sl3h4REsWb2B42cu8vrNW4oWtueXoc6UdCwCQIkqDZM9b/iAXvTs1Jqnz4NYsW4LV67fJuTVG8zNTPj5p9o4d2uPrq6u2jlXb97hl6lzOL5n42frBYiI+MCC5Ws5cfYCb0Pfkdc6D51aN6Ndi8aqPFFR0cxZupq/jp0mOiaGKhWcmDDSBTOT3F/l9UmrylXKM2RoX8qULYGVVR46tHPmz4NHP3/iNy6r9luIrKBD91Z06N4aG9uEEZEHXv4sm/cbZ45n3p1dRNpl1ev5wGG9afhzPRwKFSAyMpJrV24xY/J8/HwDNd008Q3SWDDh4uKCmZkZCxYswN3dnbi4OAC0tbVxcnJi3bp1tG3b9qvU5TpzEb7+gbi5jsTCzJQDh0/QZ8g49m1eSR5zM07t36yW/+yla7i6LaRezSoABDx8jDJeieuoQdjaWOPr/5BJsxbxITKSUQP7qJ178uwlalapmKp6AWYvWcXl67dxcx1NXqs8XLhynWnzlmFhZkqtf+7CPWvxSs5cvMr8aePIbmTEjPnuDB03jU0r5n2V1yetjIwMuetxn40bdrBl2wqNtiUjZdV+C5EVvHgWzLxpSwn0f4QCBS3a/4z7hnk0r90JX++sue349yyrXs9/rFye9b9t5dZND3R0dPhl4hC27F5NzR+b8iHi09PLswzZzSnVMsV9JmJiYggJSZiaZGZmluTX/i8uL9F9JiKjoqhYryWLZ06iRuUKqvS2PQdR9cdyDO7bLcn5g3+ZSnhEBGsWz0yxjt8372T73j/5e8datfSGbXsyfvgAypUtmap6m3fuR4M61enXo2Oyed69D6da4/bMnjya+rWqAeD/8DFNO/Zl88r5lC7hqDpPk2smwsL9s8wvOolpst+yZkJkBZlhzcQVn+PMnrKYnZv3ZVidsmYi42nyeq7pNRMmprnx8D1Hy8ZduXzheobVm6nXTNw/qekmpEjfsZamm6BGY1vDJqarq4uVlRVWVlb/dyDxsbjYOOLi4tHXUy9XX1+PG3eSvolDXr/hzIUrtPz5p0+W+z48nJw5cqil+fo/5PWbt1R0Kp3qesuUdOTkuUsEvQxBqVRy5fptAh89pXKFHwDw9H5AbGwsP5YrqzqnYP58WOWx4PZdr9S9CEIIIb6YlpYWjZvXx9DQgJtX72i6OUKkm5w5E77PvH0TquGWiG+RRm9alxGMjAwpXcKRFeu2UjC/LaYmuTh07DS373phmzfpL177/zqGoaEBdWtUSbHMR0+esWXnfkYO7K2WfuLsRapUdEJXVxddXd1U1TtuWH8mz1pMneZd0NHWRqGlYPKYIZQrUxKAkFdv0NXVIWeO7Gp1mZrkIuT16//npRFCCJGMwo72/PHXWvT19YgI/4BL91H4+QRoullCpAuFQsEUtzFcuXQD7/u+mm5O5hEv05xS67sPJgDcJo7E1W0BtZt3RltbC8fCDjSsWwNP76Qfmj0Hj/Bz/Vro6+slW1bQyxCch0+gfq1qtG6qvnD75LlLdGjV5Ivq3bxzP3fuebF01iSsLPNw/ZYH0+e5Y2FmSqXyZRFCCJGxAnwf0qxWR3LkyE6DpnWYtWQynZr1lYBCfJdmzJ1AEcdCtGjYRdNNEd+oLBFM2NpYs27ZHCI+RBIeHoG5mQkjJrphY22plu/6rbsEPHrCnKljky0n+OUreg76hTIlizF5zGC1Yy9DXnPfx09tfcTn6o2MimLRyvUscpuoOq+IQwG8HvizbusuKpUvi5lpbmJiYgl7915tdOLV67eYmZh8lddHCCHEf2JiYnkU8ASAe3e8KFmmGN36dsB15AwNt0yIr2va7PHU/akGLRt14/mzIE03R3yjMsWaiYxiaJANczMTQsPeceHKdWr/s1vSv3YfPEyxIoUoWqhgknODXobQY9AYihVxYNq4YWhpqb90p85fokxJR4xz5khybkr1xsbGEhsbi9ZHdwDX1tYi/p/htWJFCqGjo8Pla7dUxwMePuF5UDClSyR/jw4hhBBfj0JLCz39r7ueTwhNmzZ7PA0a16Ft0548fvRU083JfJTxmfeRyWSJkYnzl6+jVCqxs7Xh0ZNnzFu2hgK2NjRvXF+V5314OEdOnmXkR1u9wj+BxMAxWFtaMHJgb968/W+BkplpwujAyXOXqVVVPTj5XL3ZjYwoV7Yk85atQV9fH2tLC67d9GD/X8cZNTihHTmyG9Hy5/rMXrIa45w5MDIyZMaC5ZQu4ai2k5MmGBkZUtA+v+q5nV0+SpZy5M3rUJ48eabBlqWvrNpvIbKCERNcOH38As+fvMAouyFNWjWgYhUnerYdpOmmiXSQVa/nM+ZOpHnrRvTsOIj37yMwt0jYrv5d2DsiI2WnQPFlMsXWsF9b4q1hAf4+foaFK9YS9DIE45w5qFejKoOdu5Eju5Eqz459h5i1aBUn929WSwfY++dRJsyYn2xdd8//RcSHSKo1aseejcuxtbH+onpDXr1m4Yp1XLhyg9Cwd1hbWtC6WUO6tmuB4p8Ri39vWnfo6CliYmKoXMGJiSNdVIHMvzJ6a9iq1Spy6O+tSdI3b9pJf+fRGdqWjJRZ+i1bw4qsIKO3hp2+cCKVqpXHIo8Z78Le4+35gFVLNnDh9OUMbYdsDZsxMsv1PKO3hk1pS9ZhA8azfetejbcjM4i6m3m3utcvUU/TTVCTJYKJ9Hb01HmWrF7P/s2rMrTej2nyPhMi40kwIbKCzHCfCU2QYCJr0fR9JjQlUwcTdw5rugkp0i/16dsXZLQstWYivRgaZGN4/56aboYQQgghhBAZKkusmUhvVSo6aboJQgghhBBCZDgJJoQQQgghhEhEqYzTdBO+GTLNSQghhBBCCJEmEkwIIYQQQggh0kSmOQkhhBBCCJFYJrw5XGYlIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxOJlmlNqyciEEEIIIYQQIk0kmBBCCCGEEEKkiUxzEkIIIYQQIjHZzSnVZGRCCCGEEEIIkSYSTAghhBBCCCHSRKY5CSGEEEIIkVh8nKZb8M2QkQkhhBBCCCFEmkgwIYQQQgghhEgTmeYkhBBCCCFEYrKbU6rJyIQQQgghhBAiTSSYEEIIIYQQQqSJTHMSQgghhBAisXiZ5pRaMjIhhBBCCCGESBMJJoQQQgghhBBpItOchBBCCCGESEx2c0o1GZkQQgghhBBCpMl3OTJhYF1N003QiA/Pzmq6CRpR3LGtppsgMpB/6HNNN0EjDHX1Nd0Ejciq/95ZVeGceTXdBI14Hvla000QIs2+y2BCCCGEEEKINJPdnFJNpjkJIYQQQggh0kSCCSGEEEIIIUSayDQnIYQQQgghEpNpTqkmIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIRJTKOE034ZshIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxGQ3p1STkQkhhBBCCCFEmkgwIYQQQgghhEgTmeYkhBBCCCFEYkqZ5pRaMjIhhBBCCCGESBMJJoQQQgghhBBpItOchBBCCCGESEx2c0o1GZkQQgghhBBCpIkEE0IIIYQQQog0kWlOQgghhBBCJCa7OaWajEwIIYQQQggh0kSCCSGEEEIIIUSayDQnIYQQQgghEpPdnFJNRiaEEEIIIYQQaSLBhBBCCCGEECJNJJjIosLDI5i5cAX1WnbDqVYzOjkPx+O+t+p4RMQHps9zp07zzjjVakbTTn35Y8+fnywzJjaW5b9vpkGbHvxQqyktuw3g3KVrankOHj5BnRZdqNygDbMXr1I79vR5EI3b9+Z9ePjX62gqderZhhPX9+Px+Dw7/l5HqbLFU8xbv3Etdh3dwDXfk9wKPMu+k5tp1qaRWp6eAzpz0fMIFz2P0LN/J7VjpX4ozu5jG9HW1k6XvnyJrNrvrKpP3y54eJ4h+NV9TpzajZNTqRTzFnUsxMbN7nh4niEs3J8BLj2S5Gnbrhme3ud4+OQmM2aOVztma5uXG7eOkyNH9q/eDyE+pU33Fuy/sp3zAcdY9+dKipdxTNV59ZvV4drzs8xdO0MtvXO/9hzx2M8Rj/10cm6ndqx42WJsPPxbpriudevdgUu3j+D3/AYHjm6lzA8lU8zbsWtrdh/awL2AC9wLuMC2Pb8lye88sDu3fc5w2+cMzi7d1I6VdSrJXye3Z4p+pxtlfOZ9ZDISTGRRrjMXcfHqTdxcR7Jn43IqV/iBPkPGEfQyBIDZS1Zx7vI13FxHs3/LKrq0bc6MBe6cPHspxTKXrFrPjn1/MW5Yf/ZtWknb5o0YMvZX7vv4AvDmbSiTZi5ipEtvVi6YxsHDJzh1/rLq/GlzlzK0Xw+yGxmlb+c/0qh5PcZOHcbSuatpXqczXvd8WLN9CSZmuZPN//ZNGCsW/E67hj1oUrM9u7YewG2xK1Vr/QhAkWIODBnTj2F9xzHceTxDx/ansKM9ANra2kydO45JI92Ii4vLsD4mJ6v2O6tq2aoxM2aOY6bbYqpVaYKHx31271uPmblpsvkNDQwIDHzEZNfZvHgRnOS4iWlulixzY8I4N1o07Ua79s1o0KC26vj8hb8yyXU27969T7c+CfGxek1rM2zyQFbPW0fnn3rj4+nLkq3zyG2a65PnWdlYMsR1ADcu3VJLd3C0p9/oXozrN5nx/afQf0wf7IsWBBKua+NmjcBt9FyNX9eatmjApGmjmT/LnQY12+B515vNu1ZiamaSbP5KVcuzb9ch2jbpSdP6nXj29AVbdq/C0soCAMfihRk1diADeo3CpfcoRo0fTNFihYCEfs+cP4lfhk/VeL9F5iDBRBYUGRXFsdPnGO7Si3JlSmJrY41Lr87Y2lirRh9uedynWcO6VPihFHmt8tCmWSOKOBRUG7342IG/T9CnazuqV65AvrxWtG/xM9UqlWfd1t0APHn2guzZjWhYtwYlHYtQ/ofS+Ac+BuDQ0VPo6OhQr2aV9H8BPtKjXye2b9rL7q0H8PMJwHWkG5EfImndsWmy+a9cuM7RQ6fwexDI48CnbFi1DW9PX5wqlgGgYCE7vD0fcOncNS6evYq3py8FC9kB0HtgF65evIHHLc8M6l3Ksmq/s6qBg3qxfu0fbN64E28vX4YOnsCHDx/o0rVNsvlv3LjDxPEz2bXzIFFR0UmOF7DLR1jYO3bv+pMbN+5w5vQlChdNCB5bt2lCTEwMB/YfTtc+CfGxTs7t2Lv5AAf+OESATyBuo+cS+SGSph0ap3iOlpYW05a5smru7zx9+FztmJ2DLQ88/bh2/gZXz13H974fdg62AHQZ0IEbl2/jedsrXfuUGn0GdGPLhp1s37KXB95+/DJ8Ch8iImnfuWWy+Qf1HcP6Ndu4d9cLvwcBjBzsipZCi6rVE34ccihUgPv3fDh/9jLnzlzm/j0fHAoVAKD/4B5cunCN2zfvZlj/ROYmwUQWFBcbR1xcPPp6umrp+vp63LhzD4AyJR05ee4SQS9DUCqVXLl+m8BHT6lc4YcUy42OiUFPTy9JmTf/KdPWxprIyEju+/gSGvaOe14+FHEoQGjYO5as3sC44QO+ck8/T1dXh+Kli3Lh9H8jJEqlkgtnrlCmXMpTQBKrVK08Bezzc/XiTQB8PH2xs7fFKm8erG0ssbO35cF9P/LZ5aVlhyYsnLE8XfryJbJqv7MqXV1dypQtwcmT51VpSqWSUyfPU6FC2TSV6ecXiIFBNkqVLkbu3Mb84FSKe3e9yJUrJxMmDmPk8Mlfp/FCpJKOrg5FSxXm8tnrqjSlUsmVs9co5ZTyFM7ew7vz+tUb9m1NOpXX18sf24L5yJPXAkubPNgWzIefdwB581vTpF0jls9cnS59+RK6urqUKlOMs6cuqtKUSiXnTl/CqXzpVJVhYJgNHV0d3r4NBeC+5wMKONhhbWNF3nxWFHTIj9d9X/Lb5aNdxxbMnr44XfqSqcTHZ95HJiNbw2ZBRkaGlC7hyIp1WymY3xZTk1wcOnaa23e9sM1rBcC4Yf2ZPGsxdZp3QUdbG4WWgsljhlCuTMpzMKtUdGLDtt2UK1OCfHmtuHTtFsdPXyAuPmEY1DhnDqZPGMG4X+cRGRVFkwZ1qFLRiYluC+jYqglPn79g0JjJxMbGMaBXJ+rXqpbur0Vuk1zo6OgQ8vK1WnpI8GsKOtileF72HEac9fgLPT094uPimDxmluqLud+DQOZPd2ftTncA5k1bht+DQNbtXMacKYupWrsSg0b1JTY2lmnj53Ltny/jGSmr9jurMjXNjY6ODi+DQ9TSg4NDKFzYPk1lvn0bRr++o1i5eh4G2fTZtmUPx4+dZan7TFat3Eh+Oxu27ViFrq4ObtMXs2/vX1+jK0KkKJeJMTo6Orz+6Lr2+uUb7BzyJ3tO6QoladahMR3r9Uz2eOCDh7jPXIX7tgUALHNbSeCDhyz7YwGLpy2nUs2K9B3Zg9iYWOa6Lubmpdtft1OpYGL67/X8lVr6y5evsP9nNOFzxk8eQdCLYFVA4uvjz6xfF7Jtd0KwNHPqQnx9/Nm25zemTZpHzdpVGf7LAGJjYnEd68blC9c/Vbz4zkkwkUW5TRyJq9sCajfvjLa2Fo6FHWhYtwae3gnrGzbv3M+de14snTUJK8s8XL/lwfR57liYmVKpfPK/ZP4yxJnJsxbTpGNfFArIZ21F88b12HPwiCpP3RpVqFvjv6lMV2/ewcc3gHHD+tOobS9mTxmDmYkJHfoMwalMSUxz50rX1yGtwt9H0KxWR4yMDKlUrTxjpw7jceBTrvxzQd22fhfb1u9S5W/RrjHh7yO4ec2Dwxd30ap+VyytLFiwaga1nZoSEx2jqa58kazab5G8gweOcPDAf5/vKlUrUKJEUUaNmMwtj5P07D6EoKCXnDy9l/PnryT5siOEJhkaGTB1yQSmj5pN6OvQFPPt2rCPXRv2qZ43btOAiPAIPK7dZde5zXRt2BcLK3NmLJ9M04ptv7nrmsvQ3jRt2ZA2TbqrTWncuHY7G9duVz1v074Z79+Hc/3qbc5cPUjj2u2wsrbE/be5VCpTn+hvrN/i65FgIouytbFm3bI5RHyIJDw8AnMzE0ZMdMPG2pLIqCgWrVzPIreJ1KhcAYAiDgXweuDPuq27UgwmTHLnYvFMV6KionkbFoaFmSkLlv+OjbVlsvmjo6OZNncZbq6jePTkOXFxcZQvmzDFJn++vHjc86Jm1R/T5wX4x5vXb4mNjcXMXH2RmpmFCS+DU/7io1QqeRTwBID7d32wL1wA56HdVV+qE8ttYszAkX3o2LQvpX8oQaDfIx76P+ah/2N0dXQoYG+Lz32/r9uxz8iq/c6qXr16Q2xsLOYWZmrpFhZmBAW9/Cp16OnpMX/BVPr2GUFBezt0dLQ5f+4KAH6+AZQrV5q//zrxVeoSIjlvX4cSGxuLyUfXNRPz3LxK5rpmY5eXvLbWzF8/U5WmpZUw+/vS45O0qtqJpw+fqZ1jbGJMnxE96NtiICV+KMYj/8c8DnjC44An6OjqJEyD8vJPh96l7PWrf6/n6pspmJubJhmN/JjzwO64DO1F++a9uX/PJ8V8uU1yMWxMf1o17kbZcqXw931IgP8jAvwfoaurQ0EHO7w8H3yV/mQamXA6UWYlayayOEODbJibmRAa9o4LV65Tu9qPxMbGEhsbi5ZCoZZXW1uL+FR8uPT19chjbkZsXBxHT52nVrVKyeZbuW4bVX8sR7EiDsTHxxGbaFeI2Ng44jLggxwTE8u9215Uql5BlaZQKKhUrTy3rt1JdTkKLa0k60X+Ne7XEaxbuZWg58Foa2uho/tfDK+to62RrfWyar+zqpiYGG7dvEvNmpVVaQqFgho1K3PlyteZbjZ6jAvHjp3h9q17Cf/e2v/9e+vo6si/t0h3sTGxeN3xoUJVJ1WaQqGgfFUn7ly/lyR/oO8j2tXsSqe6PVWPM0fOc+38TTrV7UnQs6S7mI2YMoitq7YT/PwlWtpa6Ogkuq5pa6OtnfFfq2JiYrhzy5OqNf778U2hUFC1ekWuX0152lX/wT0ZOqofnVs7c+dW0tcnsSkzxrDafQPPnwWhraWF7sfXcy35fGdlMjKRRZ2/fB2lUomdrQ2Pnjxj3rI1FLC1oXnj+ujq6FCubEnmLVuDvr4+1pYWXLvpwf6/jjNqcB9VGWN/nYuFmSnD+ifsP3/nnhdBL19RtFBBgl++wv33TSiVSnp2ap2kfr+Ah/x94gw71i4FoED+fGhpabHrwGHMTHMT8OgxJRwLZ8hrsXbFZmYtmczdW57cuXGPbs4dMTA0YNfWAwDMXjqFoBfBzJu2DADnId3xuHWfx4FP0NPTpUbdKjRr04jJo92SlF25RkXs7G0ZPXASAHduelLQIT/V61TGyjoP8XHx+Ps+zJB+fiyr9jurWrpkDStWzeXmTQ+uXbvNAJceGBoasmnjTgBWrp7Ls2dBTJk0B0hY1FnU0QEAPT1drKzzULKUI+HvI/D3V/+3K1LUgZatfqZq5Z8B8PH2Iz4+ni5d2xIc9JLChe25cT31QaoQabV55R9MXjQOz9te3Lt1n4592mBgaMCBbYcAmLJ4PMEvQlg2YyXRUdH4eQeonf8uNGEr44/TASpWL4dtwXxMGjwdAM9bXuR3yE/l2hXJY21BfHwcD/0epXMPk7fafT0L3Gdw5+Y9bt7woE//LhgYGfDH5j0ALFo+g+fPg5k5dSEAA4b0YuTYgQzsM5rHj56pRi3DwyOICI9QK7tazUoUsLdjSP9xANy+eRf7QgWoVbcq1nmtiI+Lx8836eslsg4JJrKod+/DWbhiLUEvQzDOmYN6Naoy2Lkbuv/8yjJ3yi8sXLGOX6bMJjTsHdaWFgx27ka75v9tr/c8KFht9CIqOpolq9fz5NkLDA0MqFapPG4TR5Hzo5tWKZVKJs9ezKhBfTA0yAZANn19po0fzvR57kTHxDBu2ADymKtPyUgvh/YexcQ0N4PH9MPcwpT7d33o1W4Qr/5ZxGdlY0l8opvEGBgaMHn2GCytLIiMjML/QSCjBkzk0N6jauXqZ9PHdeZohvUZi1KpBCDoeTC/jpuD22JXoqNiGDNoElGRURnSz49l1X5nVbt3/YmZmQnjJgwjTx4zPO7cp1Xz7qppEDY21mojj1ZWFpy/+N/uNkOG9mXI0L6cPXOJxg07qpW9eMkMxv0ynYiIDwBERkbR33k0cxdMQV9fj5HDJ/H8eVAG9FJkdUf3nyC3aS76je6FqbkJPvd8GdRxJK9D3gBgmTcP8fHKLy5XP5seo6cPY2y/SarrWvDzl8yZsBDXBWOJiY5h0uAZREUm3UY5I+zf8zcmZiaMHDcQcwsz7nl40bm1s2qdkrWNlVq/u/Zsh76+Hqs3LFQrZ97MZcyf5a56ni2bPtNnj6d/z5Gqfj9/FsTEMTOYv3Q60dHRDB0wjsjv8XqeCW8Ol1kplP++O74jOnp5Nd0Ejfjw7Kymm6ARxR3baroJIgP5hz7/fKbvkKGuvqaboBERMd/hlxSRojKmBTXdBI14Hvn685m+Q0/ffHp6lSZ9ODhf001IkcHPwzXdBDWyZkIIIYQQQgiRJpk6mHj8+DE9eya/9/O/oqKiCAsLU3t8h4MtQgghhBAio2j6xnTf0E3rMnUw8fr1a9avX//JPG5ubhgbG6s9lPHvMqiFQgghhBBCZF0aXYC9f//+Tx739//8Xs1jx45l+HD1uWO5TYv+X+0SQgghhBBCfJ5Gg4nmzZujUCg+OS1J8dG9Dj6mr6+Pvr76wsTPnSOEEEIIIUSKZDenVNPoNCcrKyt2795NfHx8so8bN25osnmZWrZsWljmyUb+fIbYF8iOoaH6DWOOnjpPn6HjqNKwLSWqNMTLR/1Ow6Fh75gx352f2/fGqVYz6rbsyowFy3n3PlyVx+uBP6MmzaROiy441WpGk4592bh9b7Lt2XfoKF36j0hV3QA79h2i+8DRVKzXkhJVGhL27n2SPANHT6Zuy678UKspNZt25Jepcwh++d9dTJ8+D6JElYYoTN6pPdCOS1LW19Sheyv2n9rKDf9T3PA/xR+Hfqd6ncqfP/Ebl1X7nVVVrlKeP3asxtv3ImHh/jT+uZ6mmyREuus2sBPXnp9l+NRBmm5Kuho4rDd/Hv8D70dXuO1zhjWbFmPvYKfpZolvlEaDCScnJ65fv57i8c+NWmRlWgoF0dHxhLxKftvED5GR/FCqOMP6J7+APTjkFcEhrxk5sDd7Ni5n+vjhnL98HVe3Bao8nt4PMMmdi5muo9i7aQV9u7Vn0Yp1bNmZdHraibOXqFX1x1TVDQn70FetWI4+XdunmKfCD6WZN3UsB7euZsH0CTx++pxhE6YnyacMM0D5xkj1IC5939YvngUzb9pSWtTtQsu6Xbl07hruG+bhUOT73tIwq/Y7qzIyMuSux31GDJuk6aYIkSGKlS5Kyy5N8bnnq+mmpLsfK5dn/W9baVK/Ax1a9kFXV4ctu1djYGig6aaJb5BGpzmNGjWK8PDwFI87ODhw8uTJDGzRtyPiQxwRH1L+Bb5pgzpAwq/3ySlU0I6FMyaontvaWDO4bzd+mTqb2Ng4dHS0afnzT2rn5Mtrxe279zl2+gIdWzdVpUdFRXPh6g2G9OueqroBurRrAcCVGynfFbdr+xaq/7e2zEPvzm0ZPHYqMbGxqpvrAaBUgDLj4uKTR9Tv57FghjsdureiTLmS+Hp/fp3Ptyqr9jurOnrkNEePnNZ0M4TIEAaGBvy6zJXpI2fTa2g3TTcn3XVu46z2fOiA8Xj4nqNUmWJcvpDyj7xZSibcNSmz0ujIRLVq1WjQoEGKx42MjKhRo0YGtihre/c+nOxGhujoaH8yj3FO9TtaX7p+izxmphTMny/d2hYa9o6DR05SpqSjeiABkP0D5HoPOSJANzbd2pAcLS0tGjevj6GhATevphwYfW+yar+FEN+nMW7DOH/8IlfOZs0v0jlz5gDg7ZtQDbdEfIs0OjIhMo83b0NZuW4rrZs2TDHPTQ9PDh8/w7I5U9TST569SM1/pjh9bfPd17B11wE+REZRunhRtboNDbIxalAfZk/bnJCgF5sQWLw3gJj0fWsXdrTnj7/Woq+vR0T4B1y6j8LPJyBd68wMsmq/hRDfr/rN6lC0ZGG6Nuyr6aZohEKhYIrbGK5cuoH3/e9/ipf4+jL1fSZExngfHs6AUZOwL2DLgF6dk83zwD+Qwb9MoX/PTlSp6KRKVyqVnDp/WbVe4mvr0bE1O9YuZdWC6WhpazH217mqdTS5cxnTrX1LiNNOeHzQh2gdyBadLm1JLMD3Ic1qdaTNT93Zum4ns5ZMxr5wgXSvV9Oyar+FEN+nPNYWjPh1MBNcfiU6Kv3/dmRGM+ZOoIhjIQb0GqnppmQuyvjM+8hkJJjI4sLDI3AePhEjQwMWzZiYdAoR4BfwkF6Dx9K6aUOcu3dQO+bh6U1cXBxlSjqmS/ty5zLGztaGyhV+YM6UXzh78Sq373mlfEKsNmin/wctJiaWRwFPuHfHi3nTluF1z4dufTt8/sRvXFbttxDi+1S0VBFMzU3YdOQ3Lj0+yaXHJ3GqXJb2vVpz6fFJtLS+769J02aPp+5PNWjTpAfPn6W8zlF8m9zc3Chfvjw5cuTAwsKC5s2b4+3trZanZs2aKBQKtUe/fv2+qB6Z5pSFvQ8Px3nYBHT1dFkyaxL6+npJ8vj6P6Tn4F9o1rAuQ5y7Jzl+4uwlqleqgLZ2yussvhZlfMKIRHR0TMqZtOMhPuPvM6LQ0kJPXzfD69W0rNpvIcT34erZa7Sr2VUtzXXhWB76PmL90s3Ef8eLcKfNHk+DxnVo06Q7jx891XRzRDo4ffo0Li4ulC9fntjYWMaNG0f9+vXx9PTEyMhIla9Pnz5MnTpV9dzQ0PCL6pFg4hulUICu7n+/mOjqaOHl44dxzhxYWVoQGvaO5y+CCQ5JuC9DwKMnAJiZ5sbM1IT34eH0HTqeD1FRLHIdRXh4BOHhEUDCaIC2tjYP/APpNegXKld0olv7FoS8eg0kLL41yZ0LgFPnLuHSu4ta2z5XN0DIq9eEvHrDoyfPAHjgF4iRoQFWlhYY58zBnXte3L3vww+lipMzZ3YeP33OktUbyZfXijIlEu5wvu/QUXR1dUHrn12t9GJBPwbCs33V1/pjIya4cPr4BZ4/eYFRdkOatGpAxSpO9Gz7fe9LnlX7nVUZGRlS0D6/6rmdXT5KlnLkzetQnvzzuRXiWxcR/gE/b/V1X5ERkbx9E5ok/XsyY+5EmrduRM+Og3j/PgJzCzMA3oW9IzIy+S3ns5zvIJD8+++/1Z6vW7cOCwsLrl+/TvXq1VXphoaGWFpaprkeCSa+Ufr62uS1+m8/aDNTfVr3GEizhnWZPmEEJ89eYsKM+arjoybNBKB/z0649OqMp7cfdzwThroateulVvbhnevIa5WHIyfP8fptKAcPn+Dg4ROq49aWFhzZtZ5HT57x6OkztTUUwGfrBvhj7yGW/75ZlaebyygApo0bTvPG9ciWTZ9jpy+wbM0mPkRGYm5qQpWKTjj/OhY9vf9GUFas2wLGEaAE4rXgfTaISd9fyk3MTJi9dAoWecx4F/Yeb88H9Gw7iAunL6drvZqWVfudVZX9oSSH/t6qeu42K2Er6c2bdtLfebSmmiWE+Aq69Uq4x9OuP9erpQ8bMJ7tW/dqoEXiS0RFRREVpR706evro6+v/8nzQkMTdusyMTFRS9+8eTObNm3C0tKSJk2aMHHixC8anVAov8O7wuno5dV0EzTiw7Ozn8/0Fa3ftptLV2+yfN6vGVrvx4o7ttVo/SJj+Yc+13QTNMJQ99N/JL5XETHyK2lWUsY0a94E83nka003QSOevrmn6Sak6MPOaZpuQopm3Y1lyhT1nTUnTZrE5MmTUzwnPj6epk2b8vbtW86dO6dKX7VqFfnz58fa2po7d+4wZswYKlSowO7du1PdHhmZEGmWx9yM3l3aaboZQgghhBBfVyae5jR27FiGDx+ulva5UQkXFxfu3r2rFkgA9O3735bIJUuWxMrKijp16uDn54e9vX2q2iPBhEizBnWqfz6TEEIIIYT4alIzpSmxgQMHcvDgQc6cOYONjc0n81asWBEAX19fCSaEEEIIIYTIqpRKJYMGDWLPnj2cOnWKAgU+f1+oW7duAWBlZZXqeiSYEEIIIYQQIrHvYEmxi4sLW7ZsYd++feTIkYMXL14AYGxsjIGBAX5+fmzZsoVGjRphamrKnTt3GDZsGNWrV6dUqVKprkeCCSGEEEIIIb4zy5cvBxJuTJfY2rVr6d69O3p6ehw7doyFCxcSHh5Ovnz5aNWqFRMmTPiieiSYEEIIIYQQ4jvzuQ1b8+XLx+nTp//veiSYEEIIIYQQIrFMvJtTZqP1+SxCCCGEEEIIkZQEE0IIIYQQQog0kWlOQgghhBBCJCbTnFJNRiaEEEIIIYQQaSLBhBBCCCGEECJNZJqTEEIIIYQQiSllmlNqyciEEEIIIYQQIk0kmBBCCCGEEEKkiUxzEkIIIYQQIjHZzSnVZGRCCCGEEEIIkSYSTAghhBBCCCHSRKY5CSGEEEIIkZhSqekWfDNkZEIIIYQQQgiRJhJMCCGEEEIIIdJEpjkJIYQQQgiRmOzmlGoyMiGEEEIIIYRIEwkmhBBCCCGEEGki05yEEEIIIYRITKY5pdp3GUz0sa6i6SZohF2hJppugkYEPjig6SZohGn+uppugshAETFRmm6CRpQxLajpJmiET9hTTTdBI6x0jTXdBI0Ii/2g6SYIkWYyzUkIIYQQQgiRJt/lyIQQQgghhBBpppRpTqklIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIRJTxSk034ZshIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxOSmdakmIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxOSmdakmIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxOSmdakmIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxOSmdakmIxNCCCGEEEKINJFgQgghhBBCCJEmMs1JCCGEEEKIxGSaU6rJyIQQQgghhBAiTSSYEEIIIYQQQqSJTHMSQgghhBAiMaXctC61ZGRCCCGEEEIIkSYSTKSgRpefmHZuKYu9NzF673Tyl7b/ZP7aPRsx+fhCFnltYvoFd1pP7IaOvq7qePlmVZl+wZ15t3+n1YSuauea2Jgz+cRCsmU3SJe+fIluvTtw6fYR/J7f4MDRrZT5oWSKeTt2bc3uQxu4F3CBewEX2LbntyT5nQd257bPGW77nMHZpZvasbJOJfnr5Ha0tbXTpS/JCQ+PYObCFdRr2Q2nWs3o5Dwcj/vequMlqjRM9vH75p2fLDfoZQhjpsymSsO2ONVqRosu/bl730d1fO2WnVRv3J7qjduzbusutXPv3POibc9BxMbGfd3OpkKfvl3w8DxD8Kv7nDi1GyenUinmLepYiI2b3fHwPENYuD8DXHokydO2XTM8vc/x8MlNZswcr3bM1jYvN24dJ0eO7F+9H0J8SpvuLdh/ZTvnA46x7s+VFC/jmKrz6jerw7XnZ5m7doZaeud+7TnisZ8jHvvp5NxO7VjxssXYePi3DL2upSSrfr4bdW3Mb+fXsMtnN3P3zaNQ6cKfzG+U04h+v/Zj/bUN7H6whxWnVuJUq5zqeI3mNfn90lq2emyj18Teauda2Fiw4tRKDDLB3+9OPdtw4vp+PB6fZ8ff6yhVtniKees3rsWuoxu45nuSW4Fn2XdyM83aNFLL03NAZy56HuGi5xF69u+kdqzUD8XZfWxjpnifC82TaU7JcPq5Eq0mdGXrhNUE3HxA7Z6NGbxhPJNrD+Xdq7Ak+cs3rULzMR3ZOGo5fjd8yFPAiq5zB6BUKtk1bQNGuXPQeVY/NoxcRsijYFx+/wXvC3e5e+IGAB1+7cXeWVuIfP8ho7uqpmmLBkyaNppfhk/h5nUPevfrwuZdK6le/mdehbxOkr9S1fLs23WIa5dvERkVhcuQXmzZvYralZrx4nkwjsULM2rsQLq1d0GhgHXb3Dl98gJeng/Q1tZm5vxJjB46mbi4jPsS7TpzEb7+gbi5jsTCzJQDh0/QZ8g49m1eSR5zM07t36yW/+yla7i6LaRezSoplhka9o4u/UZQ4YfSrJj3K7lzGfPw8VNy/vNH1ds3gGW/bWLZnMkolUpcRk2mcoUfKGxfgNjYOKbOWcKkMYPR0cnYi3LLVo2ZMXMcQ4dM5NrVWwxw6cHufetxKluXkJevkuQ3NDAgMPARe/ccwm3WhCTHTUxzs2SZG/2dRxEY8Jgdu3/jzKmL/P33CQDmL/yVSa6zeffufbr3TYh/1Wtam2GTB+I2Zh53b3rSoU8blmydR6uqHXnz6m2K51nZWDLEdQA3Lt1SS3dwtKff6F4M7TIGhULBgg2zuHT6Kn5e/mhrazNu1gimj5qTode15GTVz3fVJtXoPbE3y8Ytw+eWN017NWPqpqn0q+lM6KvQJPl1dHX4dfOvvA0JZWY/N169eIVFXgveh4UDkDN3TgbNHsTCEQsJevgC13WTuHPhNlePXwWg/7QBrJ+5jg8a/vvdqHk9xk4dhusoN25fv0t35w6s2b6Enyq14nXImyT5374JY8WC3/F/EEh0TAy16lfDbbErr0Jec+7kJYoUc2DImH44dxqKQqFg5eYFnDt1CZ/7fmhrazN17jgmDp+u8fd5upLdnFJNRiaSUaf3z5zfdpyLO07xwvcpW8evJvpDNJXa1ko2f0GnIvhd8+bq/vO8fvKS+2fvcG3/eexKOwBgZmvBh3cRXD94kYd3/PC+dA8rh7wAlGtahbjYOG4dvpJh/UtJnwHd2LJhJ9u37OWBtx+/DJ/Ch4hI2ndumWz+QX3HsH7NNu7d9cLvQQAjB7uipdCiavUfAXAoVID793w4f/Yy585c5v49HxwKFQCg/+AeXLpwjds372ZY/yKjojh2+hzDXXpRrkxJbG2scenVGVsba/7Y8ycAZqYmao+TZy9R4YdS5MtrlWK5v2/egaWFOdPGD6dksSLYWFtSpaITtjbWAAQ8fExhezsqOpXhx3JlKexQgICHT4CEEQunMiUp6Vgk/V+Ajwwc1Iv1a/9g88adeHv5MnTwBD58+ECXrm2SzX/jxh0mjp/Jrp0HiYqKTnK8gF0+wsLesXvXn9y4cYczpy9RuGjCiF7rNk2IiYnhwP7D6donIT7Wybkdezcf4MAfhwjwCcRt9FwiP0TStEPjFM/R0tJi2jJXVs39nacPn6sds3Ow5YGnH9fO3+Dquev43vfDzsEWgC4DOnDj8m08b3ula59SI6t+vpv3bs7hrYc5vuMYjx88xn3sMqI+RFGvXb1k89dtV4/suXIwvc807l+7T/CTYO5evkvg/QAA8thaEhEWwbkDZ3lw5wEeF+9g45APgOpNqxMbG8vFvy9mWP9S0qNfJ7Zv2svurQfw8wnAdaQbkR8iad2xabL5r1y4ztFDp/B7EMjjwKdsWLUNb09fnCqWAaBgITu8PR9w6dw1Lp69irenLwUL2QHQe2AXrl68gcctzwzqncjsJJj4iLauNrYlCuJ13kOVplQq8TrvQcEfkh8q9b/ujW3JgqqpUGb5LCheqyz3Tt4E4GXAC/Sy6WFT3A5DYyPsStnzxOsRhjmNaDK8HX+4/p7+HfsMXV1dSpUpxtlT/10UlUol505fwql86VSVYWCYDR1dHd6+Tfj1577nAwo42GFtY0XefFYUdMiP131f8tvlo13HFsyevjhd+pKSuNg44uLi0dfTVUvX19fjxp17SfKHvH7DmQtXaPnzT58s9+S5SxQvWojhE6ZTvXF7Wnd3Yef+v1THC9nbEfj4Kc9fBPPsRRAPHz/FoWB+Hj15xt5DRxncp+snSk8furq6lClbgpMnz6vSlEolp06ep0KFsmkq088vEAODbJQqXYzcuY35wakU9+56kStXTiZMHMbI4ZO/TuOFSCUdXR2KlirM5bPXVWlKpZIrZ69RyinlKSC9h3fn9as37Nv6Z5Jjvl7+2BbMR568Flja5MG2YD78vAPIm9+aJu0asXzm6nTpy5fIqp9vHV0dHEo6cPvcLVWaUqnk1rlbFPmhaLLnVKxbEa/rXvSb1p8N1zey9Ogy2ri0QUsr4evRs8Cn6BvoU7B4QbIbZ6dQ6cIE3g/EyNiITiM7s3Liiozo2ifp6upQvHRRLpy+rEpTKpVcOHOFMuVSntqWWKVq5Slgn5+rFxO+t/h4+mJnb4tV3jxY21hiZ2/Lg/t+5LPLS8sOTVg4Y3m69EV8m2Sa00ey586Jto42YSFv1dLDXr4lj711sudc3X+e7CY5GbnjVxQK0NbV4cymI/ztvgeAiLBw1o9cRvd5A9HNpsel3We4f+Y2nWf14/SGvzHNZ0H/30ajraPNwYU7uPnX5WTrSU8mprnQ0dFJMvz98uUr7P8ZTfic8ZNHEPQiWBWQ+Pr4M+vXhWzbnfDHdebUhfj6+LNtz29MmzSPmrWrMvyXAcTGxOI61o3LF65/qvj/m5GRIaVLOLJi3VYK5rfF1CQXh46d5vZdL2yTGXnY/9cxDA0NqFsj5SlOAE+eveCPvX/StV1L+nRtx937PrgtWIGujg7NGtXD3s6WIc7d6TN0HABDnLtjb2dL7yFjGT6gJ+evXMd9zWZ0dLT5ZWg/ypVJeZ3K12JqmhsdHR1eBoeopQcHh1C48KfXB6Xk7dsw+vUdxcrV8zDIps+2LXs4fuwsS91nsmrlRvLb2bBtxyp0dXVwm76YfXv/+nyhQvwfcpkYo6Ojw+uX6tM0X798g51D/mTPKV2hJM06NKZjvZ7JHg988BD3matw37YAgGVuKwl88JBlfyxg8bTlVKpZkb4jexAbE8tc18XcvHT763YqFbLq5zunScLf7zcf/f1+G/IWG3ubZM+xtM1DqcqlOLX3FFO6T8bKzpr+0/qjravDtoVbCQ8NZ8HwBQxbMBy9bHqc2HWCm2duMGj2YP5cf5A8+fIwYc1EdHR12LJgCxcOnU+2nvSU2+Tfv9/q7/OQ4NcUdLBL8bzsOYw46/EXenp6xMfFMXnMLFVA4vcgkPnT3Vm70x2AedOW4fcgkHU7lzFnymKq1q7EoFF9iY2NZdr4uVz7Jwj5rsTLbk6pJcHEV1Dox2L85NKCbRN/I+DWA8ztLGnr2oOGg1rx15KExba3D1/l9uGr/51T0ZG8RW35Y9LvTD29mN8HLyLs5VvG7HXD98r9ZNdmZGYuQ3vTtGVD2jTprjZEvnHtdjau3a563qZ9M96/D+f61ducuXqQxrXbYWVtiftvc6lUpj7R0THp2k63iSNxdVtA7ead0dbWwrGwAw3r1sDT2zdJ3j0Hj/Bz/Vro6+t9ssz4eCXFixZiaL/uADgWduCB/0O27z1Es0YJQ+vtWjSmXYv/plXsO3QUQ0MDSpdwpEmHPmz7bRFBwSGMcp3J4Z1r0dP7dJ2Z1cEDRzh44IjqeZWqFShRoiijRkzmlsdJenYfQlDQS06e3sv581eSnbsthKYYGhkwdckEpo+aTejrpPPr/7Vrwz52bdinet64TQMiwiPwuHaXXec207VhXyyszJmxfDJNK7YlJp2vaxnle/x8K7S0CH31lmW/LCU+Ph4/Dz9M85jSsl9Lti3cCsClwxe5dPi/UfsSFUtQwNGOVa4rWXl2FXMHzuHNyzfM2z+fe5fvJrs2IzMKfx9Bs1odMTIypFK18oydOozHgU+58s8Pe9vW72Lb+v82DGnRrjHh7yO4ec2Dwxd30ap+VyytLFiwaga1nZp+N+9z8eUkmPjI+zdhxMXGkdMsl1p6TvNchL18m+w5TYe348ruM5z/I2Eh2jPvx+gbZKOTW1/+Xrob5Ud7Fevo6dD+196sG7YUCztLtLW1eXD5PgBBAc+wK1MIj+Pp+yv9x16/ektsbCxm5qZq6ebmpkl+3fqY88DuuAztRfvmvbl/zyfFfLlNcjFsTH9aNe5G2XKl8Pd9SID/IwL8H6Grq0NBBzu8PB98lf6kxNbGmnXL5hDxIZLw8AjMzUwYMdENG2tLtXzXb90l4NET5kwd+9kyzU1NsLezVUsraJePY6eS/4XqzdtQlq/dwrpls/G4503+fHlVj9i4WAIfP6WwfepGg9Lq1as3xMbGYm5hppZuYWFGUNDLr1KHnp4e8xdMpW+fERS0t0NHR5vz5xLWBvn5BlCuXGn+/uvEV6lLiOS8fR1KbGwsJuYmaukm5rl5FZz0i66NXV7y2lozf/1MVdq/010uPT5Jq6qdePrwmdo5xibG9BnRg74tBlLih2I88n/M44AnPA54go6uTsI0KC//dOhdyrLq5zvsdcLf79wf/f3OZZaLNy+TLkIGeBP8mtjYOOITLbZ94vsYEwsTdHR1iI2JVcuvo6dD/+n9mT90PlZ2Vmhra3P3csLav2cBTylctghXj2XsGsg3r//9+63+PjezMOFlMu/zfymVSh4FJKzfu3/XB/vCBXAe2l0VTCSW28SYgSP70LFpX0r/UIJAv0c89H/MQ//H6OroUMDeFp/7fl+3Y+KbIWsmPhIXE8eju/4UqVxClaZQKChSuQT+N5L/oqxnoE/8RwGD6sKkSJq/4cBWeJ6+xeN7ASi0tdBKtIuPtq4OWtoZ/88SExPDnVueVK3xoypNoVBQtXpFrl9NeZi+/+CeDB3Vj86tnblzK+m6g8SmzBjDavcNPH8WhLaWFrq6/8Wy2jraaGtl3G5GhgbZMDczITTsHReuXKd2tR/Vju8+eJhiRQpRtFDBz5ZVtlQxAh89UUt7+OgpVpYWyeaftXgVXdo2x9LCnLj4OGJj//tjFRcXT3xc+u8gERMTw62bd6lZs7IqTaFQUKNmZa5c+TrD1aPHuHDs2Blu37qHtrYWOtr//Xvr6OrIloIi3cXGxOJ1x4cKVZ1UaQqFgvJVnbhzPen1KtD3Ee1qdqVT3Z6qx5kj57l2/iad6vYk6FlwknNGTBnE1lXbCX7+Ei1tLXR0El3XtLXR1tD1PCt+vmNjYvH18KVUlf/W+SkUCkpXKY33jeQXxXteu49VfisUiv/+WFsXzMuroFdJAgmAdoPac/3UDfzu+qGlrYV24r/fOjpoa2ni3zuWe7e9qFS9gipNoVBQqVp5bl27k+pyFFpaKY6Kj/t1BOtWbiXoeXDCv/fHf7+/x+u5Mj7zPjIZGZlIxvHfDtJtnguPPPwJvOVL7V6N0DfU5+KOUwB0m+fC26DX7JudMAR65/h16vRqzJN7AQTcTJjm1GR4O+4cv47yozl3lg55cfq5EjMajwEgyPcpyvh4KretRdjLt1jaWxN4O+mUm4yw2n09C9xncOfmPW7e8KBP/y4YGBnwx+aEtR+Lls/g+fNgZk5dCMCAIb0YOXYgA/uM5vGjZ6pfwcLDI4gIj1Aru1rNShSwt2NI/4R1A7dv3sW+UAFq1a2KdV4r4uPi8fMNSPc+nr98HaVSiZ2tDY+ePGPesjUUsLWheeP6qjzvw8M5cvIsIwf2SbaMXoN/oU71ynRsnbBLRpd2zeniPIJV67fRoE51PDy92bn/LyaNHpzk3AtXbvDw8VNmTBgBQAnHwgQ8fMLZi1d5EfwSLS0t7PInP7f3a1u6ZA0rVs3l5k0Prl27zQCXHhgaGrJpY8I9NVaunsuzZ0FMmTQHSFjUWdQxYYcyPT1drKzzULKUI+HvI/D3f6hWdpGiDrRs9TNVK/8MgI+3H/Hx8XTp2pbgoJcULmzPjeup/yMnRFptXvkHkxeNw/O2F/du3adjnzYYGBpwYNshAKYsHk/wixCWzVhJdFQ0ft7q16F3oQlbnX6cDlCxejlsC+Zj0uDpAHje8iK/Q34q165IHmsL4uPjeOj3KJ17mLys+vne+9tehs0bhq/HA3xu+dCsVzOyGWbj2PZjAAxbMJxXL16xYdZ6AP7aeIifu/1Mn8l9ObjuANYFrGnj0oaDaw8kKTtfoXxUa1KNIQ0Tru1PfJ+gjI+nXrt6vHn5Bht7G3xup+/oekrWrtjMrCWTuXvLkzs37tHNuSMGhgbs2prQj9lLpxD0Iph505YB4DykOx637vM48Al6errUqFuFZm0aMXm0W5KyK9eoiJ29LaMHTgLgzk1PCjrkp3qdylhZ5yE+Lh5/34dJzhNZhwQTybh+8CLZTXLy87C25DTPxZP7gSzpNoN3IQnzIE3ymqlNXfpryS5QKmkyoj25LE14/yoMj+PX2Td3a5KyO7k5s3PaBqI/RAEQExXD+pHutJ/aCx19Xf5w/Z3QoOSHY9Pb/j1/Y2JmwshxAzG3MOOehxedWzur5r1a21gRnyg46tqzHfr6eqzesFCtnHkzlzF/lrvqebZs+kyfPZ7+PUeqXrfnz4KYOGYG85dOJzo6mqEDxhEZGZXufXz3PpyFK9YS9DIE45w5qFejKoOdu6Gb6NfEv46dRqmERvVqJlvG46fPeRP635qWko5FWOg2kUUr1rFi3RbyWlkyZogzP/9UW+28yKgoZsx3Z+7UsaqpE5YW5owd1p8JMxagp6vL9AkjyKav//U7nozdu/7EzMyEcROGkSePGR537tOqeXfVtDYbG2u1oX8rKwvOX/xvd5shQ/syZGhfzp65ROOGHdXKXrxkBuN+mU5ERMLe65GRUfR3Hs3cBVPQ19dj5PBJPH8elAG9FFnd0f0nyG2ai36je2FqboLPPV8GdRyp2nvfMm8etetaauln02P09GGM7TdJdV0Lfv6SORMW4rpgLDHRMUwaPIOoyKTbrGaErPr5PnfgLMYmxnQa3pnc5rnx9/RnUhdX3v6zKNvc2hxlon6HPA/BtYsrvV17s+TwUl4FveLA7/vZtXxXkrIHzhzIml9/I+qfv9/RUdEsHLGQfr/2R1dPl5WuK3gdpJl1Iof2HsXENDeDx/TD3MKU+3d96NVuEK/+WZRtZWNJfKJftA0MDZg8ewyWVhZERkbh/yCQUQMmcmjvUbVy9bPp4zpzNMP6jFW9z4OeB/PruDm4LXYlOiqGMYMmEZUBf79F5qVQfjyh/zvQ366tppugEftDPz3N6HsV+CDpL0hZgWn+uppugkZExMgfraykjOnnpxp+j3zCnmq6CRpRw7SYppugEd4fXmi6CRrh8/KappuQoohZSe8Cn1kYjlmr6SaokTUTQgghhBBCiDTReDDx4cMHzp07h6dn0jspRkZGsmHDhk+eHxUVRVhYmNojTvkd395dCCGEEEKITEKjwYSPjw+Ojo5Ur16dkiVLUqNGDZ4/f646HhoaSo8enx5mcnNzw9jYWO1xIzT5XRuEEEIIIYT4HGV8fKZ9ZDYaDSbGjBlDiRIlCA4Oxtvbmxw5clClShUePUr97hdjx44lNDRU7fGDcdF0bLUQQgghhBACNLyb04ULFzh27BhmZmaYmZlx4MABBgwYQLVq1Th58iRGRkafLUNfXx/9j3a/0VZ8h/sdCyGEEEIIkcloNJj48OGD2g1+FAoFy5cvZ+DAgdSoUYMtW7ZosHWpp9BS8PPQtlRoUY2c5rkIDXrNxZ2nE7aM/Y4NHNabhj/Xw6FQASIjI7l25RYzJs/Hzzcw3erU0lWiZxiPlo4SLW348FZ9cE2pVLLst43sPPA3796FU7ZUMSaOHEj+fHlVeULD3jFjvjunzl9GS0uLujWrMHZIPwwNDQBYtmYTy3/fnKRug2z6XD2+Vy3N/ffNPHz8lFmTRrNj3yH+PHqK+96+hEd84MLfO8iZI7ta/s/VHfDwCVPnLMEv8BHvw8OxMDOlUb2a9O/ZSbV97c79f7H/r+PksU54HhOt5F1oPDEx6bsxW+Uq5RkytC9lypbAyioPHdo58+fBo58/UYhvWLeBnRg0vh9bVm9nvusSTTcn3WTlz7dJHlO6j+2OUy0n9A30eR74nEUjF+J7RzP3fMoIHbq3okP31tjYWgHwwMufZfN+48zxCxpuWSaShi2jsyqNBhNFixbl2rVrODo6qqUvXboUgKZNm2qiWV/sp37Nqd65HutHLOPZgyfkL1mQrnMGEPkugpPr/tJ089LNj5XLs/63rdy66YGOjg6/TBzClt2rqfljUz78s//416ZQKImPhZgPWhjkSjpv8PfNO9i8cz/TJ4wgr5UlS1dvwHn4BPZtWom+fsKdPcdMmc3LkNesXjiD2NhYJsxYwOTZi5k9OeFGgj06tKJd80Zq5fYaPJYSjoWT1Hfy7EV6dU7YijgyMoqqFctRtWI5Fq5Iftu2z9Wto6NN04Z1cCzsQM4cRng/CGDSrEXExysZ2q87AFdv3KFRvZocPnoLpRKy59DGxFybly9iSc+plEZGhtz1uM/GDTvYsm1F+lUkRCZRrHRRWnZpis+97/dL5b+y6ufbyNiI2btn43HxDpO7TibsdSjWdta8/+dmhd+rF8+CmTdtKYH+j1CgoEX7n3HfMI/mtTvh6+2v6eaJb4xGg4kWLVqwdetWunTpkuTY0qVLiY+PZ8WKzH9RK+hUmNtHr3H35E0AXj95SfmmVclf2kHDLUtfnds4qz0fOmA8Hr7nKFWmGJcvXE+XOuOitYhT3QNK/ZuzUqlk4/a99O3WntrVKgEwY+JIajTpwPGzF2hUtyZ+gY84d+ka235bpAoOxg3rT/+Rrox06Y2FuSmGhgaqkQIArwf++AU+wnXUILX6nge9xDfgIVV/dAKgS7sWAFy5kfydX1NTd768VuTLa6U6x9oyD1dv3uHG7buqtFn/BB4uwxYCEPomjmwGOuhnU/AhIv1+STl65DRHj5xOt/KFyEwMDA34dZkr00fOptfQbppuTrrLqp/v1v1bE/I8hEUjF6nSgh5//zfUPHnkrNrzBTPc6dC9FWXKlZRgQnwxjS7AHjt2LIcOHUrxuLu7u9odOjMr/+s+FK1SAosCCV8C8zrmx75cEe6duqnhlmWsnDlzAPD2TahG6n/y7AUhr95QqVxZVVqO7EaUKlaE23cTdvi6ffc+OXNkVxtl+LFcWbS0FNzxTH4XsN0H/sYuX16cypRQSz917hLly5YieyrW9qS17kdPnnHu8jXKlS2ZYrkKRcLjG/ioCPHNGOM2jPPHL3LlbPr8MCIyhwr1KuJ75wFjlv/CxhubWHhoEfU7/KTpZmUoLS0tGjevj6GhATevJv9jWJakjM+8j0xGoyMT34vDy/eSLYcBk44vQBkXj0Jbi/1zt3F13zlNNy3DKBQKpriN4cqlG3jf18yUgJDXbwAwNcmtlm5qkpuQVwnHQl69wSSXsdpxHR1tjHPkUJ2fWFRUNAePnKR3l6R3VT9x9qJqBCRV7fuCujs5D+e+jy/R0TG0adaQgb2Tjt79K4exFnFxEBUp8zuF+BrqN6tD0ZKF6dqwr6abItKZZT5LGnZuxN7f9rJj6XYKlS5E3yl9iY2J4cTOE5puXroq7GjPH3+tRV9fj4jwD7h0H4WfT4CmmyW+QRJMfAVOP1eifLOqrB2ymGc+j7EpZkcb1+6EBr3h0q6sMWw8Y+4EijgWokXDlL/0fouOn7lARMQHmjasq5b+Pjyca7c8mDp2WLrUO3fqWCIiIvD2DWDest9Yt3UXPTu1SZLPKIcWBoZavHoZmy7tECKryWNtwYhfB+PSbjjRUdGfP0F80xRaCnzv+LJxdsINcv3v+ZO/SH4admr03QcTAb4PaVarIzlyZKdB0zrMWjKZTs36SkAhvpgEE19Bi7GdObJ8H9cOJOyC8Mz7MaZ5zflpQPMsEUxMmz2euj/VoGWjbjx/prm5pmb/jEi8ev0GczMTVfqr128oUsg+IY9pbl6/VZ+GFRsbR+i7d6rzE9t14G+qV6mQ5NjZi9ewt7PFKo956tv3BXX/W659gfzExcczZdZiurVvibb2f9seG2XXInsOLV6/jCM2JtXNEEJ8QtFSRTA1N2HTkd9UaTo6OpT9sTRte7Skcv4638T0W5E6b4Lf8PiB+r2tHj94TOWGVTTUoowTExPLo4AnANy740XJMsXo1rcDriNnaLhlmYTs5pRqEkx8BXoG+ig/msMWHx+PQqHQUIsyzrTZ42nQuA5tmnTn8aOnGm2LjbUlZqa5uXT9FkULJwQP78PDuePpTdsWjQEoXcKRsHfvuef1gOJFCwFw+fot4uOVlCqmfrPDJ89ecOXGHZbMmpSkrpPnLlHrC6Y4fWndicXHxxMbG0u8Usm/ocTvm3eQPacWr0Pi0n1LWCGykqtnr9GuZle1NNeFY3no+4j1SzdLIPGduX/Nk7z2NmppeQvmJfhJsIZapDkKLS309HU13QzxDZJg4ivwOH6dBi4tef00hGcPnpCvuB11ev3MhR0nNd20dDVj7kSat25Ez46DeP8+AnMLMwDehb0jMjIqfSpVJNxf4l9a2uDl44dxzhxYWVrQpW1zVq3fRn6bvOS1zsPS1RuxMDOlTrXKANjb2VL1x3JMnrUI11GDiImNZcaC5TSsWwMLc1O1qvYcPIK5qQnVfiynlh4bG8e5S9fo3qGVWnrIq9eEvHrDoyfPAHjgF4iRoQFWlhYY58yRqroPHj6Bjo4Ohezt0NPV5Z7XAxatWMdPdaqr7jOxZtN2lv62kdA3ccTFKtH6ZxsFpTLhkV6MjAwpaJ9f9dzOLh8lSzny5nUoT/7psxDfuojwD/h5q0/ziIyI5O2b0CTp35Os+vne99s+Zu+ZQxuXNpw7eI7CZQrzU8cGLP1lqaablq5GTHDh9PELPH/yAqPshjRp1YCKVZzo2XbQ508W4iMKpTI9v35oRn+7pItl05O+UTaajmhH6foVyGFmTGjQa67tP8+fi3cSFxOXYe3YH3ovw+oCePom+fqGDRjP9q1706VObd14DHIn/WWwWcO6TJ8wQnXTuh37/+bd+/f8UKo4E0a4YGf73y9PoWHvmD7fnVPnLqOlpaBuzSqMG9pfbTvY+Ph46rXqRtMGdRji3F2trkvXbjJ++nyO79molp7Sze6mjRtO88b1UlX3X8dOs3bLTgIfPUWJEus8Fvz8U226tmuhuk9G/VbdePYi6a9m78LieB+Wfr+aVq1WkUN/b02SvnnTTvo7j063ej8WEZNOgarIlMqYFtR0E1i5azHe9x5k6E3rfMIydqQ3s3y+a5gWy7C6/lW+Tnm6jumGtZ01QY+D2PvbXo5sPZyhbfD+8CJD65u+cCKVqpXHIo8Z78Le4+35gFVLNnDh9OUMbYfPy2sZWt+XCJ/cQdNNSJHR5KSfVU2SYOI7ktHBRGYR+OBAhtY3Y8Fy4uLimDhyYIbW+zHT/HU/n+k7JMFE1pIZgglNyOhgIrPQRDCRGWR0MJFZSDCRNpktmJBpTkJ8oUIF81O6hOPnMwohhBBCfOckmBDiC7Vp1kjTTRBCCCFEepLdnFJNo3fAFkIIIYQQQny7JJgQQgghhBBCpIlMcxJCCCGEECIxpdxTJrVkZEIIIYQQQgiRJhJMCCGEEEIIIdJEpjkJIYQQQgiRmOzmlGoyMiGEEEIIIYRIEwkmhBBCCCGEEGki05yEEEIIIYRIRBkvuzmlloxMCCGEEEIIIdJEggkhhBBCCCFEmsg0JyGEEEIIIRKT3ZxSTUYmhBBCCCGEEGkiwYQQQgghhBAiTWSakxBCCCGEEInJNKdUk5EJIYQQQgghRJpIMCGEEEIIIYRIE5nmJIQQQgghRGJKuWldasnIhBBCCCGEECJNJJgQQgghhBBCpIlMcxJCCCGEECIx2c0p1WRkQgghhBBCCJEmEkwIIYQQQggh0uS7nOa0+tl5TTdBZCDT/HU13QSNePXwmKaboBEG1tU03QSNWJCnlqaboBHDgk5qugkiA3l/eKHpJmjEvlwWmm6C+IhSpjmlmoxMCCGEEEIIIdJEggkhhBBCCCFEmnyX05yEEEIIIYRIM5nmlGoyMiGEEEIIIYRIEwkmhBBCCCGEEGki05yEEEIIIYRILD5e0y34ZsjIhBBCCCGEECJNJJgQQgghhBBCpIlMcxJCCCGEECIx2c0p1WRkQgghhBBCCJEmEkwIIYQQQggh0kSmOQkhhBBCCJGYTHNKNRmZEEIIIYQQQqSJBBNCCCGEEEKINJFpTkIIIYQQQiSiVMo0p9SSkQkhhBBCCCFEmkgwIYQQQgghhEgTmeYkhBBCCCFEYrKbU6rJyIQQQgghhBAiTSSYEEIIIYQQQqSJBBNCCCGEEEIkFq/MvI9UcnNzo3z58uTIkQMLCwuaN2+Ot7e3Wp7IyEhcXFwwNTUle/bstGrViqCgoC96qSSYEEIIIYQQ4jtz+vRpXFxcuHTpEkePHiUmJob69esTHh6uyjNs2DAOHDjAjh07OH36NM+ePaNly5ZfVI8swBZCCCGEEOI78/fff6s9X7duHRYWFly/fp3q1asTGhrKmjVr2LJlC7Vr1wZg7dq1ODo6cunSJX788cdU1SPBhBBCCCGEEIkoM/FuTlFRUURFRaml6evro6+v/8nzQkNDATAxMQHg+vXrxMTEULduXVWeokWLYmtry8WLF1MdTMg0JyGAPn274OF5huBX9zlxajdOTqVSzFvUsRAbN7vj4XmGsHB/Brj0SJKnbbtmeHqf4+GTm8yYOV7tmK1tXm7cOk6OHNm/ej9SEh4ewcyFK6jXshtOtZrRyXk4HvfV5036BT5i4OjJ/Fi/FeXrNKddr8E8fxGcYpkxsbEs/30zDdr04IdaTWnZbQDnLl1Ty3Pw8AnqtOhC5QZtmL14ldqxp8+DaNy+N+8TDbeK9GFdsQg//z6cHteWMOjxJgr+5PTJ/IYWuai/ZACdT89h4MMNVJvUOUmefNVK0Pn0HJw9V1NvYT+0dLVVx/RyGND59Bxy5DX96n0R4nM69WzDiev78Xh8nh1/r6NU2eIp5q3fuBa7jm7gmu9JbgWeZd/JzTRr00gtT88BnbnoeYSLnkfo2b+T2rFSPxRn97GNaGtroykG5Utgs3ISDuc24vjgENnrVvrsOQo9HcyHdcXh1DqK3NuH/cm1GLeupzpuVKUsBY+spvDNnVjPGQm6//32rJXdkIJHVqNjbZEu/RGf5+bmhrGxsdrDzc3tk+fEx8czdOhQqlSpQokSJQB48eIFenp65MqVSy1vnjx5ePHiRarbI8GEyPJatmrMjJnjmOm2mGpVmuDhcZ/d+9ZjZp78FyFDAwMCAx8x2XU2L5L5sm1impsly9yYMM6NFk270a59Mxo0qK06Pn/hr0xync27d+/TrU8fc525iItXb+LmOpI9G5dTucIP9BkyjqCXIQA8evKMrv1HUiB/PtYuncWu9e70694RPX29FMtcsmo9O/b9xbhh/dm3aSVtmzdiyNhfue/jC8Cbt6FMmrmIkS69WblgGgcPn+DU+cuq86fNXcrQfj3IbmSUvp0X6BroE3L/EacnrE9Vfm09HT68ese1xfsI8XyUNINCwU9LBnB30wl2NJ+MRakClOj433u88th23N10gndPX32tLgiRKo2a12Ps1GEsnbua5nU643XPhzXbl2BiljvZ/G/fhLFiwe+0a9iDJjXbs2vrAdwWu1K1VsIvskWKOTBkTD+G9R3HcOfxDB3bn8KO9gBoa2szde44Jo10Iy4uLsP6+DEtg2xEeQUQNMU91efkXTQWo8pleDZuIf71+/Bs2Cyi/Z8mHFQosJ4/mrdbDxHYZjjZSjqQu10D1bkWo3rwdushYp+l/GOTSF9jx44lNDRU7TF27NhPnuPi4sLdu3fZtm3bV2+PTHMSWd7AQb1Yv/YPNm/cCcDQwRP4qUEtunRtw4J5K5Lkv3HjDjdu3AFg8tTRSY4XsMtHWNg7du/6E4Azpy9RuKg9f/99gtZtmhATE8OB/YfTsUfqIqOiOHb6HItnTqJcmZIAuPTqzOnzl/ljz58M7tuNxavWU61SeUa49FKdZ2tj/clyD/x9gr7d2lO9cgUA2rf4mUtXb7Fu625mTRrNk2cvyJ7diIZ1awBQ/ofS+Ac+pmaVihw6egodHR3q1aySTr0WiT08dYeHp+6kOv+7JyGcnbwRAMd2NZIcNzDJgYFpTjw2HCMuKoaAozfIXSjh/WLpVAiL0gVTHbgI8TX16NeJ7Zv2snvrAQBcR7pRs15VWndsyqrFSd+TVy5cV3u+YdU2WrT7GaeKZTh38hIFC9nh7fmAS+cSRl29PX0pWMgOn/t+9B7YhasXb+BxyzP9O/YJ4WeuEX7m2ucz/sOomhOGFUriW7sn8aEJP2rFPP0vMNDOnRMdE2PebD6IMjqGd8cvo2dvC4BBWUeylSzMiynLv24nMqNMPM0pNVOaEhs4cCAHDx7kzJkz2NjYqNItLS2Jjo7m7du3aqMTQUFBWFpaprp8GZkQWZquri5lypbg5MnzqjSlUsmpk+epUKFsmsr08wvEwCAbpUoXI3duY35wKsW9u17kypWTCROHMXL45K/T+FSKi40jLi4efT1dtXR9fT1u3LlHfHw8Zy5cxS5fXvoOG0/1xu3p0Gcox89c+GS50TEx6Ompj1zo6+tx8849ICEYiYyM5L6PL6Fh77jn5UMRhwKEhr1jyeoNjBs+4Ot2VGSYD6/CeB/0BtvqJdHJpod1hSKE3H+Mlo42tWZ05+Qvv2fq+cbi+6Srq0Px0kW5cPq/EVClUsmFM1coUy7lqauJVapWngL2+bl68SYAPp6+2NnbYpU3D9Y2ltjZ2/Lgvh/57PLSskMTFs749r5U56hTkUiPB5j2aY3D2Q0UPLIaizG9UPwzEh33OpSYoFcYVf0BRTZ9DMsVJ8o7AHS0sZziwouJSyA+XsO9EKmhVCoZOHAge/bs4cSJExQoUEDtuJOTE7q6uhw/flyV5u3tzaNHj6hU6fPT5f4lIxMiSzM1zY2Ojg4vg0PU0oODQyhc2D5NZb59G0a/vqNYuXoeBtn02bZlD8ePnWWp+0xWrdxIfjsbtu1Yha6uDm7TF7Nv719foyspMjIypHQJR1as20rB/LaYmuTi0LHT3L7rhW1eK16/eUvEhw+s2bSdQX26Mbx/T85dvs7QcdP4fclMypdN/o9wlYpObNi2m3JlSpAvrxWXrt3i+OkLxMUnDPcb58zB9AkjGPfrPCKjomjSoA5VKjox0W0BHVs14enzFwwaM5nY2DgG9OpE/VrV0vV1EF/X3/2XUG1SZ6pN7szDk7e5/8dpnFya8OTCfeKiYmi12xUDkxzcWXuEO+uParq5IgvIbZILHR0dQl6+VksPCX5NQQe7FM/LnsOIsx5/oaenR3xcHJPHzFIFJH4PApk/3Z21OxOmEM2btgy/B4Gs27mMOVMWU7V2JQaN6ktsbCzTxs/l2j9BSGamm88Sg3LFiY+O4YnLNLRz58RysgvauXPy/JcFADwd4kaecX3JM8GZ96ev8XbnEcyc2xJx+Q7xUdHk3zYX7dw5ebNxP282HdRwj0RKXFxc2LJlC/v27SNHjhyqdRDGxsYYGBhgbGxMr169GD58OCYmJuTMmZNBgwZRqVKlVC++BgkmhEgXBw8c4eCBI6rnVapWoESJoowaMZlbHifp2X0IQUEvOXl6L+fPXyHkZfrOLXebOBJXtwXUbt4ZbW0tHAs70LBuDTy9fYn/5xfkWtUq0bV9CwCKFrbnlocn2/ceSjGY+GWIM5NnLaZJx74oFJDP2ormjeux5+B//a5bowp1a/w3lenqzTv4+AYwblh/GrXtxewpYzAzMaFDnyE4lSmJae5c6fciiK/q+VUftv/sqnqeq4AlRVtVZVuD8bTcOZHbvx/m4cnbdDzmxtPLXrzyeqzB1gqRsvD3ETSr1REjI0MqVSvP2KnDeBz4VDUFatv6XWxbv0uVv0W7xoS/j+DmNQ8OX9xFq/pdsbSyYMGqGdR2akpMdIymupI6WlqgVPJs+Gzi30cAEOy2mrxLxvFi0jKUUdF8uO5JYKuhqlP07PJi3Lw2/s0GYbdlNq/X7+P96WsUPLSciKt3ifIO1Exf0tN3MPiyfHnCyFnNmjXV0teuXUv37t0BWLBgAVpaWrRq1YqoqCh++ukn3N1Tv/4GJJgQWdyrV2+IjY3F3MJMLd3CwoygoJdfpQ49PT3mL5hK3z4jKGhvh46ONufPXQHAzzeAcuVK8/dfJ75KXSmxtbFm3bI5RHyIJDw8AnMzE0ZMdMPG2pLcuXKio62NvZ2t2jkF7fJx407Kc4FNcudi8UxXoqKieRsWhoWZKQuW/46NdfLzLKOjo5k2dxlurqN49OQ5cXFxqkAlf768eNzzombV1P8SIjKXWjN7cu7XLaClhUVJO3wPXiY2Mpqnl7zI+2NRCSZEunvz+i2xsbGYmZuopZtZmPAyOOUfbJRKJY8CngBw/64P9oUL4Dy0e5L1FAC5TYwZOLIPHZv2pfQPJQj0e8RD/8c89H+Mro4OBext8bnv93U79pXFBr8mNuiVKpAAiPJ7jEJLCx1LM2IePktyjuWvAwly+w2FloJsxR0I++scysgoIq54YFih5PcZTHwHlMrPTzfNli0by5YtY9myZWmuR9ZMiCwtJiaGWzfvUrNmZVWaQqGgRs3KXLnydYarR49x4dixM9y+dQ9tbS10tP+L4XV0dTJ0S0FDg2yYm5kQGvaOC1euU7vaj+jq6lLcsTABj56o5Q18/BRry89v/aevr0ceczNi4+I4euo8taolP89y5bptVP2xHMWKOBAfH0dsot1PYmPjiJM5uN+sYu1qEPn2PQFHb6ClrQBQbRWrrauNQlv+1Ij0FxMTy73bXlSqXkGVplAoqFStPLeupX4DAoWWVpL1YP8a9+sI1q3cStDz4ITreaItU7V1tDW6RWxqfbjhiY6FCQrDbKo0Pbu8KOPiiH0RkiS/cev6xIW+5/2Jy6CV0D+Fzr//1QH5fGd5MjIhsrylS9awYtVcbt704Nq12wxw6YGhoSGb/tndaeXquTx7FsSUSXOAhEXbRR0dANDT08XKOg8lSzkS/j4Cf/+HamUXKepAy1Y/U7XyzwD4ePsRHx9Pl65tCQ56SeHC9ty4nvo/cml1/vJ1lEoldrY2PHryjHnL1lDA1obmjesD0KNjK0a6zqRcmRJU+KE05y5d4/T5y6xdMktVxthf52JhZsqw/gn31bhzz4ugl68oWqggwS9f4f77JpRKJT07tU5Sv1/AQ/4+cYYda5cCUCB/PrS0tNh14DBmprkJePSYEo6F0/11yKp0DfUxtsujep7zf+zddVhU2RvA8S8wgIBFCyKCYnf32uuqa6+ta+va3e3aHatr59rduXYHCkioCIoKUtIIEvP7A3d0FnSRHzCo7+d55tF77rln3sPAzJx7Kp85ZsVtiQmNItI3mGpj25E9jzFnh69R5TErntRTpWukj4FpDsyK25IQF0/IE/W7lgamOak4pAX7W88AIDYsmjePX1G210/4XHbBpkYJ7qw4kgm1FAI2rd7OvBXTePjADWdHV7r164SBoQH736/uNP+P6fi/DmDRzKS7sP2GdsflgTsvnr1ET0+X2g1q0KJtE6aNSb5mf/XaVbAraMuYQVMBcL7vRgGH/PxQvzpW1pYkJiTi5fk82XUZTcswG3r5P6y+p2djiX6xAiSERhDvF4j5yO4oLE3xG7MIgLCjFzEb2BHrucMJXP4XOsa5sBjbi9B9Z1HGvlMrW8ckF2YDOvC8wygAEsMjifX0waR7S6KuOmJYrQxBf6b/UqNZgSwikXrSmBDfvQP7j2NmZsKEScOxtDTDxdmdNi27qyZl29hYk/jRXXMrKwuu3TiuOh46rC9Dh/XlyuWbNG3cSa3s5StmM2HcLKKj3wIQExNL/35jWLhkOvr6eowaMRU/P/8Mr2NEZBRLV2/CPzCIXDlz0LB2TYb064auIuktoEHtGkwZPYj12/YwZ8lq7GxtWDJrEuXLlFSV4ecfgLaWluo49t07Vqzbwkvf1xgaGFCrWiXmTB5Nzn9txqdUKpk2fzmjB/fB0CDpTlg2fX1mThzBrEWreBcXx4ThA7A0Vx9qJtKPRekCtN77YfPEfzahc997mXMj1mJkmZvsedV//h1Pz1b937J0AYq0qkH4i0C2VB+ulu+H6V15sPYkUf6hqrRzI9fQYHE/Svf8EcfVxwlw8sqAWgmR3IlDZzExNWbI2N8wtzDF/eFjerUfTPD7SdlWNnlIVH54PzcwNGDa/LHksbIgJiYWryfPGD1gMicOqS8aoJ9NnylzxzC8z3jV0BF/vwB+n7CAOcun8C42jrGDpxIbo74rcWYwKFmI/Ns/3PixnNgXgNADZ/EbuwSFhTG61uaq88roGHy6T8RySn/sDywjITSC8BNXCFyyNVnZlpP78WbjAeIDPkxq9x27GOv5IzD+tTlvNuwnxuVJBtZOfA20lKkZUPWVUejl1XQIIhMZ6qZ+reVvSfDzc5oOQSMMrL/PVZ+WWNbVdAgaMdz/gqZDEJmoQC4rTYegEYdzf5+7SRd7ckLTIXxSaOd6/51JQ3Jvz9h5ll9KeiaEEEIIIYT4mAxzSjWNNybc3d25efMm1apVo2jRonh4eLBs2TJiY2Pp0qUL9ep9vmUYGxtLbKx6t6JSqUTro+EYQgghhBBCiPSn0Sn4p06domzZsowaNYpy5cpx6tQpfvjhBzw9PXn+/Dk//vgj589/vitnzpw55MqVS+2hTIzIpBoIIYQQQgjx/dJoY2LGjBmMHj2a4OBgNm3aRKdOnejTpw9nz57l77//ZvTo0cydO/ezZYwfP56wsDC1h5Z2jkyqgRBCCCGE+OYkZuFHFqPRxoSrq6tqB7527doRERHBL798WFayc+fOODt/ftlMfX19cubMqfaQIU5CCCGEEEJkPI3Pmfjni7+2tjbZsmUjV65cqnM5cuQgLCxMU6EJkaLqNSoxdFhfypYriZWVJR3b9+P4sbP/fWE6i4qKZsW6rfx9+QZvQkIpWrgg44b1o1SxIgCUrNE4xetGDOil2gvC7ZEni1dtxNXjMdra2jSsU4Mxg/tiaGigdo3va3+adezLleO78H0dwB/rt+H26Am+rwMYO6QvXdu3SvY8O/cfZdOOfQS9CaGIQwEmDO9PqeJFVOf3Hj7B8bMXcX/kSVT0W66f2ptsWdmw8AhmL17FxWu30NbWpkGdGmhpwbe3Bp3mWVcpQvl+TTEvbU92S2OO916C1+kPOwAX/KkiJbvWx7yUHQbGOdjZaAJBbj4ajFiI/1/H7m3o2P0XbGyTVpF64uHFykXrufz3dQ1Hlr4MKpXEtHcbspVwQNfSlBf9fyfy3A21PHoF82ExugeGlUuhpaNDrKcPLwfNIt4vUENRi6+FRnsm7OzsePLkw/rEN27cwNbWVnXs4+ODldX3uUycyLqMjAx56OLOyOFTNRrHlLnLuHHnPnOmjOLgtj+pXrk8fYZOwD8waX+Mi0e2qz1+nzAcLS0tGtapAUBAYDC9h47H1saKHWuXsnrx73h6+zBx1qJkz3X+yk0qly+NoaEBb2NjsLHOw7D+PTAzNU4xtpPnLjF/xVr69+zM3o0rKOJgT78RkwgOCVXliYmJpWaVivT5tcMn6zh2+nw8vX1Yt3Q2K+dP496Dh5ibfZ9LAWc0XQN9gtx9uDRpS4rnFYb6+N5+xPXZuzM5MiEyzmvfABbN/INWDbrSusGv3Lx6l1VbF+FQpICmQ0tX2gbZiPXwxn/6qhTP69rmIf/OBbzzesnzLmPxajaAoJU7k21i9z1RJiqz7COr0WjPRP/+/UlISFAdlyxZUu38yZMn/3M1JyEy29kzlzh75pKmw+DcpassnzuVimVLATCwVxcuXbvF7oPHGdK3G2amJmr5L7xvEOTLm9RAv3T9FgqFgkkjB6KtnXRfYcroQbT+dQA+L32xtbH+6Nob/Fg3aX+HUsWKqHo/lv65KcXYtu4+yC/NGtPq/Q7bU0YP5vL1Oxw8dobeXdsBqHozbjumPJTx6TMfrt68y671y1S7Y08Y3j+pUfLmHQkJWe8N9Wv2/KIzzy9+eljpowPXAMhhI5sLim/HhTNX1I6XzF5Fx+5tKFuxFJ6Pvp3NFqMu3yXq8t1Pnjcf3o2oS3cJmL9RlRbn8zozQhPfAI32TPz22280bdr0k+dnz57N+vXrMzEiIb4OWlqQkJCIvp6uWrq+vh6Ozq7J8ge9CeHy9du0/rmRKu3duzh0dRWqhgQk7UwN4Oj0oYzwiEgcnV2pW7NqqmKLi4vD7dETqlYqq0rT1tamasWyOD10T1UZAE4P3cmZI7uqIQFQtWK593Fq9K1LCPEN0tbWpmnLHzE0NOD+nc/P1/ymaGmRvU4l3j17Rb6Nv1Po5g7s9i0he4Nqmo5MfCXkE1mIr5BSCWVKFmP15p0EBAaTkJDA0dPncXroQVDQm2T5j5w8h6GhAQ1q11ClValQluDgEDZu30dcXBxh4REs+TPprlRg8Icyrty4Q+GC9liYm6YqtpDQcBISEjE1UR8CZWpiTNCbkFTXMSg4BJPcudTSFAodEhOV6OjIIgtCiPRRuFhB7j+7zMNX15m+cDwDu4/m6WNvTYeVaXRMc6OT3RDTvm2JunwPnx6TiDhzHZuVEzGsXPK/C/hWaXrFJlnNSQiR0eZMHgVKJfVadqF83eZs33uYxg1qo6Wd/M/64LEz/PxjXfT19VRpDgXyM2vSSLbsOkDF+i2p07wTea3yYGpijLb2hy/r56/cTHWvhBBCfG28PZ/Tom4n2jbqzs7N+5i3YhoFC9trOqxMo/X+/T7i75u82XyIWHcvgtfuJfLCbXJ3bKLh6MTXQOOrOQkh0sbWxprNKxcQ/TaGqKhozM1MGDl5DjbWedTy3XvwEG+flyyYMT5ZGU1/rEvTH+sS9CYEw2zZQEuLrbsPYmOdNK8iLi6Oa7fu0ufX9qmOyzh3TnR0tAn+Vy9E8JsQzExSnrCdEjNTY96Eqq/mFh+fgLa2lsyXEEKkm7i4eHy8XwLg6uxBqbLF6da3I1NGzdZwZJkjPiQcZVw8sZ7qq7PFPn2BYYUSGopKfE2kZ0KIr5yhQTbMzUwIC4/g+u171Kul3otw4NhpihcpRNFCn16dxMzEGENDA079fQl9PV2qVUqam3Db0ZmcObJ/9tp/09XVpXiRQty6+0CVlpiYyK17DyhTsliqyylTshjhEZG4enxY8e3WvaQyY2KzYD+vEOKboKWtjZ6+7n9n/FbExfPW5TH69jZqyfp2eYnzDdBQUJqn6RWbZDUnIb5hRkaGFCiYX3VsZ5ePUqWLEfImjJcvfTMtjmu37qFUKrGztcHnpS+LVm7A3taGlu9XUAKIjIrizIUrjBrUJ8Uyduw7QtlSxTE0yMaNO/dZtHIDw/r3UO33cPHqLer8a4hTXFwcT7193v8/Hv/AYDweP8XQ0EC1AtSv7VsxcdYiShQtRMniRfhrzyHexsTSsmlDVTlBwW8ICg7B5/3P7MnTZxgZGmCVx4JcOXNQ0M6WmlUrMm3eMqaMHkxcfDyzl/xJZFS89ExkAF1DfXLZWaqOc+Yzx6y4LTGhUUT6BqOf24gc1qYYWSb1LhkXTOq9ig4MIzpQ9gMSX6eRkwZy6e/r+L18jVF2Q5q1+YkqNSrQs91gTYeWrrQMs6GX/8MKfXo2lugXK0BCaATxfoG8Wb+fvEvHEX3HhaibzmT/oQLZ61XheZexGoxafC20lMpvb/snhV5eTYcgMpGhbubuO1CzVhVOnNqZLH37X/vo329MpsWxfeMUlq7ehH9gELly5qBh7ZoM6deNHNmNVHn2Hj7BvGVruXBku1r6P8b/vpDL128T/fYt9vnz0b1jG5r/VF91vkHrX/l9/HBVTwXAKz9/Gv3SPVlZFcuVYvMf81XHO/YdYdOO/QS9eUPRQgUZP+w3Spcoqjq/csNf/Llxe7JyZk4YoWp0hIVHMGvxKi5evYW2thYN6tRg8cqD3+WmdUss62Zo+XmrFqP13onJ0t33XubciLUUbVuLhov7JTt/a/EBbi85kGFxDfe/kGFli6ynQK7M3Vtq1tLJVKtVCQtLMyLCI3nk9oS1K7Zy/dKtTI3jcG6LDC3fsHIp8m+flyw99MBZ/MYuASDXLw0x69cORR4z3nm/JHDZdiL/vpmhcRV7ciJDy/9/vGlVW9MhfJLJQc0vT/8xaUyIr15mNyayiuDn5zK0fLdHnvQaMo7Lx3ehq8g6nZgG1rU0HYJGZHRjIquSxsT3JbMbE1lFRjcmsqos3ZhokYUbE4ezVmNC5kwIIVKUkJDA+OH9s1RDQgghhBBZi3xLEEKkqFTxIpQqXkTTYQghhBAiC5PGhBBCCCGEEB9RyqKBqSbDnIQQQgghhBBpIo0JIYQQQgghRJrIMCchhBBCCCE+JsOcUk16JoQQQgghhBBpIo0JIYQQQgghRJrIMCchhBBCCCE+Iqs5pZ70TAghhBBCCCHSRBoTQgghhBBCiDSRYU5CCCGEEEJ8TIY5pZr0TAghhBBCCCHSRBoTQgghhBBCiDSRYU5CCCGEEEJ8RFZzSj3pmRBCCCGEEEKkiTQmhBBCCCGEEGkijQkhhBBCCCFEmsicCSGEEEIIIT4icyZST3omhBBCCCGEEGkijQkhhBBCCCFEmsgwJyGEEEIIIT4iw5xST3omhBBCCCGEEGkijQkhhBBCCCFEmsgwJyGEEEIIIT6m1NJ0BF+Nb7IxscSyrqZD0IhqykhNh6ARL+MNNR2CRtgVaqbpEEQmmvjmuqZD0IiIPztqOgSNqDXplqZD0IgrKxppOgSNUNTppOkQhEgzGeYkhBBCCCGESJNvsmdCCCGEEEKItJLVnFJPeiaEEEIIIYQQaSKNCSGEEEIIIUSayDAnIYQQQgghPqJMlNWcUkt6JoQQQgghhBBpIo0JIYQQQgghRJrIMCchhBBCCCE+Iqs5pZ70TAghhBBCCCHSRBoTQgghhBBCiDSRYU5CCCGEEEJ8RKmU1ZxSS3omhBBCCCGEEGkijQkhhBBCCCFEmsgwJyGEEEIIIT4iqzmlnvRMCCGEEEIIIdJEGhNCCCGEEEKINJFhTkIIIYQQQnxEmSirOaWW9EwIIYQQQggh0kQaE0IIIYQQQog0kWFOQgghhBBCfESp1HQEXw/pmRBCCCGEEEKkiTQmhBBCCCGEEGkiw5yEEEIIIYT4iKzmlHrSMyGEEEIIIYRIE2lM/It1lSL8vHEEPe6uYPCLvyjQqMJn8xta5ObHFQPocmkBg55vpdbULsny5KtVki6XFtDPbR0Nl/6Gtq6O6pxeDgO6XFpAjrym6V6XL5G9SnEcNk2k9N2NVHx5iNyNqnw2f45qJan48lCyh8I8tyqPSasfKH17PWUf/oXNlB5q1+vZWFDy8kq0sxtkRHVSzbRqUapuHUWjBytp+XoHVj9V/Gx+k8pFqHVkKk3c1tDMezP1ryykYN/GanlsWtfgx3sraOKxjpLT1H8fDPOZ0eDaIhQarvc/uvXuyE2nMzz1c+To2Z2ULV/qk3k7/foLB05sxdX7Oq7e19l1cH2y/P0Gdcfp8WWcHl+m38BuaufKVSjFyQt70NHRQdP6/9YNz8c3iQx/yvWrR6lUsexn87dp8zMPXS4RGf6U+47naPxTPbXzI4b3w/elE74vnRg+rJ/aucqVynHr5sksUe8+fbvi4naZgGB3zl88QIUKpT+Zt2ixQmzbvgoXt8uER3kxYGCPZHnatW+B26OrPH95n9lzJ6qds7XNi+ODv8mRI3u61yO1Ntx8Qqetl6m+5AR1/zjNsAO3eRYcmerrT7m/ouz8oww7cFstfcvtp9T94zR1/zjN1ttP1c65+IbQcctl4hMT06UO/4+23Vtx5PYernmfY/PxNZQoWyxV1/3Yoj53/a6wcNNstfQuv3XgjMsRzrgcoXO/9mrnSpQrzrbT6zX6e77hkgudVp2g+vSd1J29h2F/XeBZYNhnrzns+JSyE7epPSpP3a6WZ8sVV+rO3kPd2XvYetVN7ZzLi0A6rjxOfELmvd5RUdHMXbqahq27UaFuCzr3G4GL+yPVeaVSyR/rtlKneScq1G1B76Hjef7i1WfL3HXwGK1+7U+Vhq2p0rA1nfsO58qNO2p55i9fS/Wf2lK/VVeOnT6vdu70+SsMHDM1/SopvirSmPgXXQN9gtx9uDRpS6ry6+gpeBscwd3lhwly80meQUuLRisG8PCv8+xtOQ2L0vaU7PThi0j18e15+Nd5Il4Fp1cV0kTbMBvRbt74TFrzRde51BrAg3LdVY/4oKQ3boVxDuwWDOTF75t43Hkapq1rk6v+hy/q+Wf34+WcbSRGvk3XenwpHUN9wlyf4zx+U6ryJ0TH4LXxDFdazeDvH0bxaOlBio1rS/4uSa+pnkkOyi3qg+uM7VzvMId8v9TAsmE51fWl5/bEddYu4jVcb4DmrX5i6swxLJ63ip/qtMXt4SO271+DqZlJivmr1azE4f0naNesJ81/7Izvq9fsOLCWPFYWABQrUZjR4wcxoNdoBvYezeiJQyhavBAAOjo6zF08lXEjZpCQkJBpdUxJ27bNWbhgKr/PXEylKj/h5OzGiePbMTdPuUFfrWpFtm9byaZNO6lYuRFHjpxm/74NlChRBIBSpYoxbepoOncZQJeuA5kxfTQlSxYFkuq9cuVcBg4cp/F6t27TlNlzJzB3znJq1WiGi4s7Bw5vwewT9TY0MODZMx+mTZnP69cByc6bmBqzYuUcJk2YQ6vm3WjfoQU/fdTIWrz0d6ZOmU9EROq/vKe3ey+CaV/Onq1da7G6XVXiE5X033uTt+/i//PaV2HRLL7gRnkb9b+HxwHh/HnVg3nNKjC3WXlWXvXgSWA4APGJicw848zEH0uj0Nbsx2vD5vUYPm0Q6xZtpkuj3jx282TFzkUYm+b+7HVWNnkYOmUAjjcfqKU7FCvIb2N6MeG3aUzsP53+Y/tQsGgBIOn3fMK8kcwZs1Cjv+f3vANoX7UIW39rzOoeDYhPUNJ/89+8fRf32euy6+tybtwvqsfJ0a1V5x6/DuHPv52Y174Wc9vXYuXZBzx5HQJAfEIiMw/fYmKLKih0Mu/1njJ3GTfu3GfOlFEc3PYn1SuXp8/QCfgHBgGwcftetu87wpTRg9mxbikG2bLRb8QkYmPffbLMPOZmDP+tB3s2rmD3huVUrlCGweNm4On1HICLV29y/OxF1i6ZxcgBvZg6dxkhoUmf9xGRUSxfu4VJIwZmfOUzkTJRK8s+shppTPzL84vO3FywD69Td1OVP+JlEFembcNj/1ViI5J/QTQwyYGBaU5ctp7jzeNXeJ91xLiQNQB5KhTCokwBnDacStc6pEX4BUd8F+wg9NStL7ouPjiM+MBQ1eOftdT08+chITyakKPXiHbyJOL6Q7IVsgHApEUtEuPiCT15M72r8cUCzjvhPm8vfidT93qHPXzOq0M3iHj0iugXQbzcf42AC86YVUn6YmmY34K4iGheHb5J6AMvAq+5kaNQXgDytqyGMi4evxN3PvcUmabPgG7s2LqPPTsO8eTRU8aNmM7b6Bg6dGmdYv7BfceyZcMuXB968PSJN6OGTEFbS5uaP1QFwKGQPe6uj7l25RZXL9/C3fUxDoXsAeg/pAc3r9/F6f7DTKvfpwwf2of1G3awZese3N2fMGDgOKKj39Kje4cU8w8e3IvTpy+yaPFqPDw8mTptAffvP2RA/6Q79UWKOODi4s6Fi9c4f+EqLi7uFCniAMCokf25cuUmd+85ZVr9PmXQ4F5s2bSb7dv28cjDk2FDJvH27Vu6/to2xfyOjs5MnjiX/fuOpfglxN4uH+HhERzYfxxHR2cuX7pJ4aIFAfilbTPi4uI4euR0htbpv6xqW5UWpfLhYJaDIha5mNGkLH7hb3Hz//zd6oREJROOOdK/ZhHy5jZUO+f9JpJC5jmpnN+MKvnNKWSeE+/3vR1bbj+lfD5TSlrlzqgqpVrnfu05tP0oR3efwPvxM+aMWUjM2xiad2z6yWu0tbWZuXIKaxdu5NVzP7Vzdg62PHF7yt1rjty5eg9P96fYOdgC0HVARxxvOeHm5JGhdfovq7rXp0X5gjhY5qaIlQkzfqmOX2gUbq/efP5CLTDLYaB6mH7Uc+wdGEahPMZULmhFlYJWFMqTG+/3jcctV10pb2dJSRuzjKyWmpjYWM5dusqIgb2oWLYUtjbWDOzVBVsba3YfPI5SqWTbnkP07daBerWqUcTBntmTRxEQFMzfV65/stw6NavyQ/XK5M+XFztbG4b2646hQTacXJNeU6/nL6hUrhQlixWmScM6GBkZ8tLvNQCLV22gfcumWOWxyJSfgch6pDGRwd4GhxPpH4LtD6VQZNPDunIRgtxfoK3Qoe7s7lwYtxFl4te7mHHx00sofW8jhXdMI3vFoqr0GG9ftA30MShhj07u7BiVceCt+zN0chlhPboTPpPWaTDq9JOrZH5MKhUm6IY7AFFer9Ex0CNXyfzo5jbCuGxBwt180M1lRLGxbXGesFmzAb+nq6tL6bLFuXLxhipNqVRy9dJNKlQqk6oyDAyzodBVEPr+7pS72xPsHeywtrEibz4rCjjkx8Pdk/x2+WjfqRXzZy3PkLp8CV1dXcqXL83f56+o0pRKJX+fv0rVqikPaaxapYJafoAzZy+q8j986E6hQvbky2eNrW1eChUqgKurBwUK5Kdbt/ZMmTo/4yqUSrq6upQtV5ILF66p0pRKJRcvXKNy5XKfufLTnj59hoFBNkqXKY6xcS7KVyiN60MPcufOyaTJwxk1Ylr6BJ+OImOTeiRyZdP9bL411x9jYqhPq9K2yc4VMs/B85Ao/MKj8Q2L5vmbKBzMc/AiJIrDLi8YVLNoCiVmLoWugqKlC3Pryj1VmlKp5PaVu5SuUOKT1/Ue0Z03wSEc3nk82TlPDy9sC+TDMq8FeWwssS2Qj6ePvMmb35pm7Zvw59ys954eGZPUCM5lqPfZfG/fxdN4wQEazd/PsG0X8PQPVZ0rZGnM86Bw/EKj8A2J5HlQBA6WuXkRHMHhe08Z1LBsBtYguYT4BBISEtHXU/8d1tfXw9HZlZe+rwkKDqFaxQ9/1zmyG1G6eBGcHqausZeQkMCJcxd5GxND2fe9rEUcCuDq8YSw8AhcPZ4QGxuLbV5rHJ0e4vbIk85tm6dfJcVXR1ZzygSn+q+g1tQu1JrWhecXnHDffYkKA5vx8ro7CbFxtDkwBQOTHDhvOoPzlrOaDjdV3vm/4dnYVUQ7P0VLT4F5x4YU3jsTj2ZjiH7oRUJYFN7Dl2G/bBja2fQI3n+R8EsPyL9wEAGbTqBva0GhTRPQUujgu2QXIcdv/PeTZiGNHFegZ5oTbYUOHgv383zHRQDiwqJwHLKa8iv6o5NNjxd7rxBw0Zlyi/vgvfEMhrYWVNkyCm3dpOt8j93+/BNlEBPT3CgUCoIC1YfXBQYGU/B9b8J/mThtJP6vA1QNEs/HXsz7fSm7DiR9qZg7Yymej73YdXA9M6cuok69mowYN4D4uHimjJ/Drev3Pld8hjAzM0GhUBDgH6SWHhAQSNEiBVO8Jk8ec/wDAtXS/P2DyGNpDoCHhyeTJs/j1MldAEycNBcPD09On9zFuPEz+fHHOkyZPIK4uHhGjJjClatf1vuXHkxNjVEoFAQG/LveQRQunHK9/0toaDi/9R3NmnWLMMimz64dB/n73BX+WDWXtWu2kd/Ohl1716Krq2DOrOUcPnQyPaqSZolKJQv+fkjZvMY4mOf8ZL77L4M55OzD7u4/pHi+gGkOBtcqym+7k3pWh/xQlAKmOei3+wbD6hTj+rMAVl97jEJbizH1S1IhX+bPh8ttkguFQsGbQPU78m8CQ7BzyJ/iNWUql6JFx6Z0atgzxfPPnjxn1dy1rNq1BICVc9bw7MlzVu5ewvKZf1KtThX6jupBfFw8C6cs5/5NzfbGJSYqWXD8LmXzm+NgafzJfHZmOZnWuhqFLI2JjI1j6xVXuq85xf6hzbDMZUQBi1wMbliO3zadA2DIj+UoYJGLfhvPMuyn8lx/4svqv51Q6GgzpmklKthbZmi9jIwMKVOyGKs376RAfltMTXJz4twlnB56YJvXiqA3SUOwTE3U62xqYkxQcMhny3781JvO/Ubw7t07DA0MWDZ7MgXtk35falSpwM+N6tGh91Cy6esza9JIDA2y8fvClcycOILdB4+zY98RcufOxbQxQ3AokPLv2ddENq1LPWlMZAK/O4/Z8/MU1XFu+zwUbVOTXT9NpPW+yThtPM3zC050OjeHV7c8CPZ4ocFoUyfWy5dYL1/VcdS9R+jb5cGyT3O8hy4FIPTULbVhU9mrlsCwaH5eTFpLyaur8Rq0iLiAEIodW0DETTfigz8/9CArudJyBgrDbBhXcKDExA5Eer/m1aGkL9V+J++qDZsyrVaUnMVtcZ64hQY3lnC3/wpiA8KoffJ3gm568C4oXFPVSLOBw3rTvHVj2jbrrjYEZtumPWzbtEd13LZDCyIjo7h3x4nLd47RtF57rKzzsGr9QqqV/ZF3/zGW+Wuxdt021q7bpjru2rUtEZGR3Lx5D7eHl6lavSk2ea3Y/tcqHApX4927T49d/pocO3qGY0fPqI5r1KxMyZJFGT1yGg9cLtCz+1D8/QO5cOkQ167dTtZ4zUxzzrrgGRTB5s41PpknKjaeicfvM+Wn0hgb6n8yX9tydrQtZ6c6PvLwBYZ6CspYm9Bi/Xm2d61FQEQM447c43i/+ugpND/5/nMMjQyYsWISs0bPJ+zNp9+H9289zP6th1XHTdv+RHRUNC53H7L/6nZ+bdwXCytzZv85jeZV2hGnwb/vOUdv4+kfyua+jT6br4ytOWVszdWOWy89wr7bTxj4vtehbZXCtK1SWJXniONTDPV0KWNrToslh9nevwkB4dGM232F46NaZfjrPWfyKKbMWUK9ll3Q0dGmWGEHGjeojdsjz/+rXHtbG/ZvXklEZBRnLlxl4qxFbP5jvqpBMbBXFwb2+rCoyKqN26lasSwKhYI1W3ZxcOsqLl2/zYSZC9mzccX/FYv4ukhjQgPqzu3J1d93gLY2FqXs8Dx2i/iYd7y66UHeqkW/isZESqIePCF7pZRXC9HSU5B/Vj+8hy5F394KLYU2kTddgaSGiVG5woSdyxpzCVIj2ifpTnW4xwv0zXNRdFQbVWPiY9p6CsrM7cm9QaswsrNEW6FN8I2kruZILz9Myjnw+qxjpsYO8CY4lPj4+GSTb83NTZPdvf63foO6M3BYLzq07I276+NP5jM2yc3wsf1p07Qb5SqWxsvzOd5ePnh7+aCrq6CAgx0ebk/SpT6pFRT0hvj4eCws1cc4W1iY89o/MMVrXr8OxNLCXC3N0tLsk/lNTY2ZPHE4deu3oXLlcjx54oWnpzeent7o6upSuHABHqZyuEF6CQ4OIT4+HnOLf9fbDP9P1ONL6enpsXjJDPr2GUmBgnYoFDpcu5rU8/bU05uKFctw6uT5/yglY8w568Llp/5s7FgDyxyfXkntRWgUvmFvGbr/w3tR4vvbkxUWHONQ77rkMzZSuyYkOpY11x6zsVN1XHxDyG+cnfwmSY/4RCXPQ6Io9JmekIwQ+iaM+Ph4TMzVJ4+bmBsTHJC8QWdjl5e8ttYs3jJXlab9fgL5zRcXaFOzM6+e+6pdk8skF31G9qBvq0GULF8cH68XvPB+yQvvlyh0FUnDoDy8MqB2/23OkdtcfvSSjb1/xDKX0X9f8BFdHW2KWBvz4k1EiudDomJYc96ZjX1+xOVFEPlNc5LfLOkRn5DI86BwCuX5dE9IerC1sWbzygVEv40hKioaczMTRk6eg411Hsze90gEvwnB/KPFNILfhFCk0Od7IXV1dbG1SZrTWaJoIVw9HvPX3sNMHTMkWV6v5y84dvo8+zb9wYHjZ6hYtiQmxrlpVO8HJs9eQlRUNEZGhsmuE98mmTORyYq3r01MaCTeZx3R1kmakf/PUrE6ujpoZeKKEOnNsLg9cQEpd6NaDWlH2MX7RD/0Am1ttD66c6Olq/iq662lrYWOfspjsIsMa0XABSfCXJ6hpaON1kfLJmorNPd6x8XF4fzAjZq1q6rStLS0qPlDFe7d+fTwhP5DejJs9G90+aUfzg9cP/sc02ePZd2qrfj5+qOjrY2u7od7FzoKHXS0M/9ubVxcHI6OztSrW1OVpqWlRb26Nbl5M+VhVzdv3aNevZpqaQ3q//DJ/IsWTmfZ8nW8euWHjo4OCt0PvxsKhY5Gls6Mi4vjwf2H1KlTXZWmpaVF7TrVuX37fro8x5ixAzl37jJOD1zR0dFGofPh9VboKjRSb6VSyZyzLpx/8pq17aslm0z9b/am2dnXoza7u/+getR2sKSSrRm7u/9AnpzJGyILz7vSpWIBLHMYkKhUqi0JG5+oJEEDc+Li4+LxcH5M5Zof5gFpaWlRqWYFnO8l/7t95ulD+zq/0rlBT9Xj8plr3L12n84NeuLvm3w1r5HTB7Nz7R4C/ALR1tFGofjo71tHBx0NvLcplUrmHLnNeTcf1vZsSF6THF9cRkJiIp6vQzH7RKNz4Ym7dKlRDMtcRiQmavb1NjTIhrmZCWHhEVy/fY96taomNShMjbl574EqX2RUFM5ujyhT8svm8yQmKlPsPVYqlcyYv5wxg/tgaGhAYkIicfFJ85Hi3/+bkAWWRv5/aXrFpq9pNSfpmfgXXUN9ctl9GPOYM585ZsVtiQmNItI3mGpj25E9jzFnh39YQtWseNIkPV0jfQxMc2BW3JaEuHhCnqjfyTEwzUnFIS3Y33oGALFh0bx5/IqyvX7C57ILNjVKcGfFkUyoZXLahtnQt7NSHevns8CguD0JoRG88w0i77gu6OYx5dmwZQBY9GrGuxf+vH3sg5a+HuYdG5KjRiked5qerOxshWwwaV4Dt0YjAIh5+gplohKzDg2ICwghW8G8RDll7h3qf+gY6pPdPo/q2NDWnFwl8vMuNJK3r4IpPqE92axMcBz8JwD2PRry9mUwEZ5Jr61Z1aI49G+K1/rkq9bkKJyXvC2qcqHhBAAiPH1RJirJ37EOMYGhZHewJuTB02TXZZZ1q7awZNVsnO+7ct/RhT79u2JgZMDu7QcBWPbnbPz8Apg7YykAA4b2YtT4QQzqM4YXPr6qu9xRUdFER0WrlV2rTjXsC9oxtH9S3Z3uP6RgIXvqNqiJdV4rEhMSeerpnXmV/ciSZevYtGEJ9xyduXPnPkMG98HIyIDNW3YDsGnjMnx9/Zg4Keku7YoVGzj/9z6GD+vHiZPnaN+uBRUqlOa3AWOSld2gfi0KF7KnR8+hANy960TRIgX5qVFdbGysSUhI5NEjzbzmf6zYwOq1C7l/34W7d50YMLAHhoaG/LVtHwBr1i3E19ef6VMXAEl3KYsWS1qVSk9PFytrS0qVLkZUZDRe75eL/EeRog60bvMzNav/DMDjR09JTEyk66/tCPAPpHDhgjjec87E2iaZfdaFk+6vWNqqEkZ6CoIiY4CkpUCzvb+JM+n4fSyyZ2NI7WLoK3SSzafI8X6ydkrzLG48C+R5SBS/N02a7FrCKjfP3kRy1cuf1+Ex6GiDnYlm9tnYvmY305ZNwM3JA9cH7nTq0xYDQwOO7joBwPTlEwl4HcTK2Wt4F/uOp4/U/x4jwpJWqPp3OkCVHypiWyAfU4fMAsDtgQf5HfJTvV4VLK0tSExM4PnTFJZKz2Czj9zmpLM3S7vUxUhfl6D3Kyxmz6ZLtvc3MybtvYZFTgOGNCoPwJrzzpTKZ4ataQ4i3r5jy1U3/EKjaFXRIVn5Nzx9eR4Uzu9tkobKlbAx5VlgOFcfveJ1WBQ62lrYZUIv1LVb91AqldjZ2uDz0pdFKzdgb2tDy6Y/oqWlRdd2LVm7ZRf5bfKS19qSP9Ztw8LMlPq1PtxM6DVkHPV/qE6nX5ImTi/5cxO1qlXEytKCqOhojp+5yJ37zqxZPDPZ8+8/egrj3LmoUzPpZlS50sVZtfEvnB66c+XmXQra2ZJTg/vLiMwnjYl/sShdgNZ7P2y+9M8mdO57L3NuxFqMLHOTPa/6UIGOpz9s7GNZugBFWtUg/EUgW6oPV8v3w/SuPFh7kqiPVoo4N3INDRb3o3TPH3FcfZwAJ810CxuVcaDI3g9vGvmm9QIgaM95no1Yjq6FCfp5Pwz10NZTYDOlB3p5TEh8G0u0+3Med5xKxPXkS3/mnzeAF9M3kfg2FgBlzDueDV+O7ay+aOvp4jN5LXGv/2PpvgxiXLYANQ9MVh2XmtEVAJ/dl3AcuoZslrkx/GhDQS1tLYpPbI+hrTnK+ESinvnjOnMXz7b+nazssgt64zLtLxKik+qdGBOH47DVlJnTHW09XZwnbCbm9ecnxGWkIwdPYWJmwqgJgzC3MMPVxYMuv/RTjWu3trEi8aO7bL/2bI++vh7rti5VK2fR3JUsnrdKdZwtmz6z5k+kf89RKN8PEfHz9Wfy2Nks/mMW7969Y9iACcTExGZ8JVOwd+8RzM1MmDZlFHnymOPk5ErTn7sQ8H54l20+axI/uqt24+Zduvw6iBnTxzDz97E88fSmzS+9cHV9pFZutmzZWLZsFp0691fV+9UrP4YOm8z6dYuJjX1Hz17DiImJybzKfuTA/uOYmZkwYdJwLC3NcHF2p03L7qphbTY26vW2srLg2o0Pq/oMHdaXocP6cuXyTZo27qRW9vIVs5kwbhbR0Ulf3mJiYunfbwwLl0xHX1+PUSOm4ufnnwm1VLf3QVKjp/cu9SGI0xuXpUWpfAD4hb9FKw03+mLiEph71oV5zSug/b4AyxwGjK1fkqknndDT0WZGk3KqRktmO3vkPMamufltTC9MzU147OrJ4E6jeBOU9J6TJ6+l2t93auln02PMrOGM/22q6vc8wC+QBZOWMmXJeOLexTF1yGxiYzJ/XtDe20nDLnuvP6OWPr1NdVqUTxri4xcWpfZ6h7+N5fdDNwmKeEtOAz2KWZuypd9PFLTIrVZGTFw8c4/eYV77Wmhrv3+9cxkx9udKTD1wHT2FDjPaVFc1WjJSRGQUS1dvwj8wiFw5c9Cwdk2G9OuG7vveoZ6d2/L2bQzT5i8nIjKS8qVLsHrR7+jrf1jV6sUrP0LCPszXexMayoTfFxIY/IYcRkYUdrBnzeKZVK9cXu25g96EsHbLLv5avViVVqp4Ebp1aM2A0VMxMc7N7EkjM/gnILIaLaUya81XVyqVaKXlnf0jK/Il34X6e1BNqbnNoTTpZfz3OS5zYKzm9y7QBP+oUE2HoBGGup+eEPwt81+e8r4n37pakzJ/1a+s4MqKz0+Y/lYp6nT670zfIF2zApoO4ZOelsy6v4sFH2p2D59/y3ID1fX19XF3d9d0GEIIIYQQQoj/oLFhTiNGjEgxPSEhgblz52JqmjS0ZPHixSnm+0dsbCyxserDJeKUCehqZe2l+IQQQgghhPjaaawxsXTpUsqUKUPu3LnV0pVKJe7u7hgZGaVquNOcOXOYPl190u9POUrRJFfp9AxXCCGEEEJ8J5Rf/4JUmUZjjYnZs2ezdu1aFi1aRL169VTpurq6bN68meLFi6eqnPHjxyfr5VhfvF+6xiqEEEIIIYRITmNzJsaNG8fu3bvp378/o0aNIi4ubTtl6uvrkzNnTrWHDHESQgghhBAi42l0adhKlSpx7949Bg4cSMWKFdm+ffv/vZJTZrCuUoTy/ZpiXtqe7JbGHO+9BK/THzawKvhTRUp2rY95KTsMjHOws9EEgtwyf83t9Ja9SnHy/NYKw1IF0ctjgmevOYSe/rDiiN3iIZi1q6d2TdhFR550mZHZoaYr06pFKTTgZ3KVtscgjzG3ui/G79Rd1fmio9qQt0U1DPKakPgugVBnb9zn7Cbkvub2kMgIg4b3pvHPDXEoZE9MTAx3bz9g9rTFPPV8punQUqX/b90YOaI/efKY4+zsxtBhk7lz94FaniePbvBb/zH8ff4Kv/zSjHFjB1O4UAECA4NZ9ecmFi1erZa/Y8dWjBo5gEIO9oSFhXPq9AXGjpvJmzdJy2/26tmJrl1+oUSJIgA4OrowafLcZM+bFVWvUYmhw/pStlxJrKws6di+H8ePndV0WOluw80n/P3Yj2fBkejr6lDG2phhtYtjZ5p8nXylUsmgfbe45h3I4lYVqVfIKoUSvw3dBnVm8MTf2LFuD4unrNB0OOlmwyUX/nZ9wbPAsKTX29acYY3KY2eeS5Wn1/oz3PNWX8r4l0qFmNSy6r+Ly5ISEhJYtWE7x86cJyg4aSfslk0a0q97R9V3rOjotyz5cxPnr1wnNCyCvNaWdP6lBe1bNQXglZ8/jX7pnmL5i36fQKN6tTKrOhqTqMz630ezCo3vM5E9e3a2bNnCrl27aNCgAQkJCZoO6T/pGugT5O6D257LNF03LNl5haE+vrcf8eToLeov6J35AWYQbcNsRLt5E7T7HA7rx6eYJ+zCPbxHfPjgUaawe+bXRsdQnzDX5zzfeZEqm5IvHBD51A/nCZuJeh6AjoEuBfs2ofru8ZytNpx3wREaiDhjVK1eiS3rd/LgvgsKhYJxk4ey48A66lRtztv3+wtkVW3bNmfhgqkMGDiO23fuM2Rwb04c307xkj8Q+H5fjVKlimFsnItLl2/wU6O6bNuygqHDJnP23CWKFS3E6j/n8/ZtDKv+3AxA9WoV2bxxGSNHTePY8bPktc7DypVzWbN6Pm3b9QGgdu1q7Np9mBs37xITE8PoUQM5eWIHpcvWw9f3taZ+HKliZGTIQxd3tm3dy45dq//7gq/UvRfBtC9nTwmr3CQkJrLisgf9997kQM86GOipf0T+ddeLNG1K8ZUpXqYorbs257Grp6ZDSXf3vANoX7UIJfKaJr3eZx7Qf/PfHBjaDAO9D7vVt67owIAGZVXHmtovJC02/LWX3YeOM2vSSBzs8+Pq8ZhJs5aQPbsRXdq2AGD+irXcuufEnCljyGtlyfXb95i5aCUWZqbUrVWVPBZmXDyyXa3cvYdPsmnHfmpVraiJaoksTOONiX906NCBmjVrcu/ePfLnz6/pcD7r+UVnnl/89G6ujw5cAyCHjdkn83yNwi84En7B8bN5EmPjiQ8MzZyAMknAeScCzn96T4eXB6+rHT+c+hd2neuSs5gtQVddMzq8TNOlrfpcpGEDJuLieZXSZYtz6/q9T1yVNQwf2of1G3awZeseAAYMHEeTxvXp0b0D8xesBKB5s0acPnOR+Ph4Onduw+Ejp1m7bhsA3t4+zJv/B6NHDVQ1JqpWrcCzZy/4Y+VGAJ49e8G6dX8xetRA1fP+2m2wWhx9+42idasm1KtXk7/+2pfR1f6/nD1zibNnLmk6jAy3qq363eYZTcpS748zuPmHUSHfhw0rPfzD2HbHix2/1qLBqm+vh+YfBoYG/L5yCrNGzafXsG6aDifdrepeX+14xi/VqTd7L26v3lDB3lKVnk1PgVkOg8wOL108eOhO3VpVqV29MgB5rSw5cfYSLm4fNtp84OJOi8YNqFw+abGati2asPfwSVzcH1G3VlV0dHQwMzVRK/fvy9dpVL8WhoZf589FZJwstc+EjY0NLVq0wMjISNOhiDTKUa0kZR5spuSlldjO7odO7hyaDilTaenqYNe1HnFhUYR/A0PbPidnzqTXNjQkTMORfJ6uri7ly5fm7/NXVGlKpZK/z1+latUKqrSff27IkaNJGwHp6+sl26H77dsY8uWzJn9+GwBu3rxHvnzWNP4paWifhYUZbVo35eSp5Luh/8PQ0ABdXQUhb0LTq3oinUXGxgOQK9uHu9Rv4+KZcMyR8Q1LYZY9m6ZCyxRj5wzn2t83uH0la98gSC+R73fqzmWop5Z+8oE3dWbtoc2yIyw/7cjbd/GaCC9NypYsxq27D3jm8xIAjydeODq7qvUolC1VjAtXb+IfGIRSqeT2PSee+bxKtuP1P1w9nuDxxIvWP2fdjdzSm1KplWUfWU2W6ZkQX7+wi46EnLzBuxcB6OfPQ96xXSj812Tcm4+DxG97jTXLhuWotHowOgZ6xPiHcq39HN69+XaGOP2blpYW0+eM5fZNRx65Z+2hEGZmJigUCgL8g9TSAwICKVqkIADW1nkoXaoYp05dAODMmUssWjiNrVtrcuHiNRwc7Bk+PKlnxiqPJc+fv+T6jbt07TaYHdv/JFs2fXR1dTl67AyDh0z8ZCxzZk/E19efc39f+WQeoTmJSiUL/n5I2bzGOJjnVKUvPO9KGWsT6hbKo8HoMt6PLepTtFRhfm3cV9OhZIrERCULjt+lbH5zHCyNVemNS9thbZwd8xwGPH4dwrLT93kWFM7iznU0F+wX6N21HVHR0TTr1BcdbW0SEhMZ0rcbPzf6MKdxwvD+TJu3nPotu6LQ0UFLW4tpY4dSsWypFMs8cOw0BezyUa5U6lbaFN8XaUyIdBNy5Krq/289nhPt/ozS19eQo1pJIq59eljYtyDomhsX6o9HzyQHdl3qUmntEC41mcK7oHBNh5YhZi+cRJFihWjVuKumQ0kXzX7+kWvX7hAWlvR6rd+wnYIF83P40GZ0dXUJD49gxR8bmDplFInvG8bFihViyaLpzJy1hDNnL2GVx4K5cyexauVc+vYblew5xoweSPt2zanfsG2yjTZF1jDnrAueQRFs7lxDlXbxyWtuPw9md/cfNBhZxrO0tmDk70MY2H4E72LfaTqcTDHn6G08/UPZ3Ff9bvsvlQur/l8ojzHmOQzou/EcL4IjyGea9XvbT52/zLEzF5g3bQwO9vnxeOLFvGVrsDAzoUWThgBs33cEZ1cP/pg3Fas8ltx74MKsRauwMDOlWqVyauXFxMZy4uxF+nXvqInqiK+ANCZEhnnn409ccBj6dnm++cZEQnQsUc/8iXrmT4ijJw2uLyZ/xzo8WXFE06Glu5nzJ9KgUW1aN+mGn6//f1+gYUFBb4iPj8fCUn0Ok4WFOa/9AwFo9nNDjh47o3Z+/ITZTJw0lzx5LAgMDKZ+vZoAeHk/B2DsmMFcv3FXtcKTi4s7UVHRXLp4iClT5/P6dYCqrBHD+zFm9EAa/dQBFxf3DKurSLs5Z124/NSfjR1rYPnRWPnbPkG8DI2i1rJTavlHHbpLORtTNnSsntmhZoiipYtgam7CX2fWq9IUCgXlqpahXY/WVM9fX9WQ/hbMOXKby49esrH3j1jm+vzQ6lL5kt47Xrz5OhoTi1ZuoHeXdjRpUAeAwgXt8XsdwPpte2jRpCExsbEsW7OFZXMmq+ZVFHGwx+OJF5t37k/WmDhz4SpvY2Jp/lP9fz/VN02ZmPWGE2VV0pgQGUbXyhSFcQ7iAkI0HUqm09LWQkdf978zfmVmzp/IT03r07ZZd174vNJ0OKkSFxeHo6Mz9erW5MiRpDkRWlpa1Ktbk1V/bsLIyJA6daozcHDyFcoSExNVqy61b9+SGzfuEhT0BgBDw2zEx6uvPpeQkKgq/x+jRvZn/LghNGnamXuO33aj+mukVCqZe+4h55+8Zn2HauTNbah2vmcVB1qXtlVL+2XTJUbVK0Htgt/OsKc7V+7Svs6vamlTlo7nuacPW/7Y/s00JJRKJXOP3uG8mw/re/9IXpP/bhx4+CV9hn0tE7JjYmLR0lb/IqytrU2iUglAfHw88fHxaP9rZTIdHe0UX+cDx05Tt2YVTIxzZ1jM4usmjYk00DXUJ5fdh1UfcuYzx6y4LTGhUUT6BqOf24gc1qYYvR+DaVwwaS3y6MAwogOz9mTVz9E2zIa+3Yd11fXzWWBQ3J6E0AjiQyOxHtGekBM3iAsIRT9/HmwmdiP2mR/hl+5rMOr/n46hPtntP3xpMLQ1J1eJ/LwLjeRdSCSFh7bk9el7xASEomeSgwI9GpItjzGvjt7UYNTpb/bCybT8pQk9Ow0mMjIac4uku3UR4RHJJitnNUuWrWPThiXcc3Tmzp37DBncByMjAzZv2U2jRnV5/MSL589fqvKbmhrTpvXPXLp8nWzZstHt13b80qYp9er/ospz7Ng51qyeT7++v3Lm7EWs8liwaNF0bt92xM8vqcdm9KgBTJs6ii6/DuLZ8xdYWpoDEBkZRVRUdOb+EL6QkZEhBQp+WFnPzi4fpUoXI+RNGC9f+mowsvQ1+6wLJ91fsbRVJYz0FARFxgCQXV+XbLo6mGXPluKk6zw5DZI1PL5m0VFvefrIWy0tJjqG0JCwZOlfs9lHbnPS2ZulXepipK9LUETSstbZs+mSTVfBi+AITjp5U7NIXnIZ6vPkdQgLT9ylgp0FhfMY/0fpWUOdGlVYt2UXVpYWONjnx/2xJ1t3H6BV0x8ByG5kRMVypVi0cgP6+vpY57Hg7n0Xjpz8m9FD+qiV5fPSl3sPHvLnwq97vyiRsaQxkQYWpQvQeu+HSZa1pnYBwH3vZc6NWIt9w/I0XPxhGc2fViUtD3lr8QFuLzmQucGmI6MyDhTZO1N1nG9aLwCC9pzn+YTVGBS1w/SXuujkNCLOP4Twyw94tWA7yq9oFYyUGJctQM0Dk1XHpWYkzRPw2X2JB2M2ksPBCtt2w9AzycG7kEhCHzzlSssZRDz6Ou7cp1a3Xh0A2H98i1r68AET2bPzkAYiSr29e49gbmbCtCmjyJPHHCcnV5r+3IWAgCCaN2vEsRQ2Y/u1a1vmz5uMlpYWN2/eo36DtmqbzW3dtoccOYwYMKA7C+ZPITQ0jAsXrzF+wmxVnn59f0VfX5+9u9eplT3j90XM+H1xhtU3PZQrX4oTp3aqjufMmwTA9r/20b/fGE2Fle72PkgattZ71w219OmNy9KiVD5NhCQy0N7bjwHovV59WOP0NtVpUb4gujra3Hrqx/br7ryNi8cylxH1S9jSp07KE5OzognD+7Ni3VZmLlzJm5BQzM1MaNuiCf17dFLlWTh9HEtXb2bc9PmEhUdgnceCIf260b5lU7WyDhw7g6WF2SdXefqWve/IEamgpVR+ez+uFfm6aDoEjaimjNR0CBrxMv7buTv4JQbGfnrvi2+Zf1RoupWlo6OD70snfm7WJcvvSm2oq6/pEDTCf3lrTYegEbUm3dJ0CBpxZcX3s/ToxxR1Ov13pm+QrlkBTYfwSe6Fmmg6hE8q9uSEpkNQk6X2mRBCiMxkYpKbZcvXZfmGhBBCCJFVyTAnIcR3KzAwmNlzlmk6DCGEEFmMrOaUetIzIYQQQgghhEgTaUwIIYQQQggh0kSGOQkhhBBCCPGRRKUMc0ot6ZkQQgghhBBCpEmqeiaOHDmS6gKbN2+e5mCEEEIIIYQQX49UNSZatmyZqsK0tLRISEj4f+IRQgghhBBCo5QyzCnVUtWYSExMzOg4hBBCCCGEEF8ZmTMhhBBCCCGESJM0reYUFRXFpUuX8PHx4d27d2rnhgwZki6BCSGEEEIIoQlKpaYj+Hp8cWPi/v37NGnShOjoaKKiojAxMSEoKAhDQ0MsLCykMSGEEEIIIcR34ouHOQ0fPpxmzZoREhKCgYEBN2/e5Pnz51SoUIGFCxdmRIxCCCGEEEKILOiLeyYePHjAmjVr0NbWRkdHh9jYWAoUKMD8+fPp1q0brVu3zog4hRBCCCGEyBSyaV3qfXHPhK6uLtraSZdZWFjg4+MDQK5cuXjx4kX6RieEEEIIIYTIsr64Z6JcuXLcuXOHQoUKUbt2baZMmUJQUBDbtm2jZMmSGRGjEEIIIYQQIgv64p6J2bNnY2VlBcCsWbMwNjamf//+BAYGsnbt2nQPUAghhBBCiMykVGpl2UdW88U9ExUrVlT938LCglOnTqVrQEIIIYQQQoivg2xaJ4QQQgghhEiTL+6ZsLe3R0vr010sXl5e/1dAQgghhBBCaJJsWpd6X9yYGDZsmNpxXFwc9+/f59SpU4wePTq94hJCCCGEEEJkcV/cmBg6dGiK6StXruTu3bv/d0BCCCGEEEKI/9/ly5dZsGAB9+7dw8/Pj4MHD9KyZUvV+e7du7Nlyxa1axo1avRFc6LTbc5E48aN2b9/f3oVJ4QQQgghhEYkKrWy7ONLREVFUaZMGVauXPnJPD/99BN+fn6qx86dO7/oOb64Z+JT9u3bh4mJSXoVJ4QQQgghhPg/NG7cmMaNG382j76+Pnny5Enzc6Rp07qPJ2ArlUpev35NYGAgq1atSnMgQgghhBBCiM+LjY0lNjZWLU1fXx99ff00lXfx4kUsLCwwNjamXr16zJw5E1NT01Rf/8WNiRYtWqg1JrS1tTE3N6dOnToULVr0S4vLEPuVrzUdgkZMDPk+V9KKjov970zfoHZWlTUdgkbsibqt6RA0Ivj5OU2HoBE7y0zRdAga8SD4+3w/d+jzZcMrvhXb9Jw1HYJG1PPfo+kQPikrbg73jzlz5jB9+nS1tKlTpzJt2rQvLuunn36idevW2Nvb8/TpUyZMmEDjxo25ceMGOjo6qSrjixsTaQlUCCGEEEII8f8bP348I0aMUEtLa69Ehw4dVP8vVaoUpUuXpmDBgly8eJH69eunqowvnoCto6NDQEBAsvTg4OBUt2CEEEIIIYQQX05fX5+cOXOqPdLamPi3AgUKYGZmhqenZ6qv+eKeCeUndvGIjY1FT0/vS4sTQgghhBAiS/nSVZO+FS9fviQ4OBgrK6tUX5PqxsTy5csB0NLSYv369WTPnl11LiEhgcuXL2eZORNCCCGEEEJ87yIjI9V6Gby9vXnw4AEmJiaYmJgwffp02rRpQ548eXj69CljxozBwcGBRo0apfo5Ut2YWLJkCZDUM7F69Wq1IU16enrY2dmxevXqVD+xEEIIIYQQIuPcvXuXunXrqo7/mWvRrVs3/vzzT5ydndmyZQuhoaFYW1vz448/8vvvv3/RsKlUNya8vb0BqFu3LgcOHMDY2DjVTyKEEEIIIcTXIuVB/V+fOnXqfHKKAsDp06f/7+f44jkTFy5c+L+fVAghhBBCCPH1++LVnNq0acO8efOSpc+fP5+2bdumS1BCCCGEEEKIrO+LGxOXL1+mSZMmydIbN27M5cuX0yUoIYQQQgghNCVRqZVlH1nNFzcmIiMjU1wCVldXl/Dw8HQJSgghhBBCCJH1fXFjolSpUuzevTtZ+q5duyhevHi6BCWEEEIIIYTI+r54AvbkyZNp3bo1T58+pV69egD8/fff7Nixg3379qV7gEIIIYQQQmQmZRYcTpRVfXFjolmzZhw6dIjZs2ezb98+DAwMKFOmDOfPn8fExCQjYhRCCCGEEEJkQV/cmABo2rQpTZs2BSA8PJydO3cyatQo7t27R0JCQroGKIQQQgghhMiavnjOxD8uX75Mt27dsLa2ZtGiRdSrV4+bN2+mZ2xCCCGEEEJkusQs/Mhqvqhn4vXr12zevJkNGzYQHh5Ou3btiI2N5dChQzL5WgghhBBCiO9MqnsmmjVrRpEiRXB2dmbp0qX4+vqyYsWKjIxNCCGEEEIIkYWlumfi5MmTDBkyhP79+1OoUKGMjEkIIYQQQgiNUSKrOaVWqnsmrl69SkREBBUqVKBKlSr88ccfBAUFZWRsQgghhBBCiCws1Y2JqlWrsm7dOvz8/OjXrx+7du3C2tqaxMREzp49S0REREbGKYQQQgghhMhivng1JyMjI3r27MnVq1dxcXFh5MiRzJ07FwsLC5o3b54RMQohhBBCCJFpEpVZ95HVpHlpWIAiRYowf/58Xr58yc6dO9MrJiGEEEIIIcRX4P9qTPxDR0eHli1bcuTIkfQoTgghhBBCCPEVSNMO2EIIIYQQQnyrEmU1p1RLl56Jb1HLbs3ZdeMvznieYNXRFRQtW+Sz+bPnNGLozMHsv7ebM09PsO3yZqrUq6w636BVPfbc3sHRhwcZMOU3tWvz2Fiy7fJmDLMbZkhdvkSfvl1xcbtMQLA75y8eoEKF0p/MW7RYIbZtX4WL22XCo7wYMLBHsjzt2rfA7dFVnr+8z+y5E9XO2drmxfHB3+TIkT3d6yFSp+GvjVl2dQ2bH+1mxqF5FCzz+WWff+r5MwvP/8HmR7tYcWMdXSb3QFdfV3W+RssfWHFjHeuct9Flsvrvg5mNOYsurMQgu0GG1EV8EBUVzdylq2nYuhsV6ragc78RuLg/Up2fOHMRJWs0Vnv0GzEp1eWv37aHkjUaM3fparX0+cvXUv2nttRv1ZVjp8+rnTt9/goDx0z9/yr2hSyqFKHu5hH8cm8Fv776i3yNKnw+f6XC/HRoCu0f/kknz420uDSfYn1+Ustj36o6be4so73rGipO7ax2zsjGjJZXFqArv+Ma1a13R246neGpnyNHz+6kbPlSn8zb6ddfOHBiK67e13H1vs6ug+uT5e83qDtOjy/j9Pgy/QZ2UztXrkIpTl7Yg46OTobUJTVyVy1G6W1jqeG0mnr+ezBrXOk/r9HSU1BgfAeq311JHZ/tVLvzB1Yd66rOG/9QiqrXl/KD52aK/zEILd0P9dPJYUDV60vJZmOWIfURXx/pmUhB3WZ1GDDlNxaPX4b7fXd+6d2GBX/NpWvtHoQGhybLr9BVsHDHfEKCQ5nabwZBr4OwtLEkMiwSgFzGORm9YCRzhy/A18ePuVtmcv/afW78fQuAYbOHsHbOeqIjozOzmsm0btOU2XMnMGzoZO7eecCAgT04cHgLFco1ICgwOFl+QwMDnj3z4dDBE8yZl/yLiImpMStWzqF/v9E8837B3gPruXzxBqdOJX3JWLz0d6ZOmU9ERGSG100kV/XnGnSZ1IONE1fj+eAxjXs2Y9y2KYysO4jw4LBk+au3qEWHsV1ZO+YPHt/zwMremt8WDQHgr983kcM4B33mDWD1yBUE+PgzetMkXK+5cP/8XQB6zuzHrnnbeBv5NlPr+T2aMncZnl7PmDNlFBZmphw9fZ4+QydwePsaLM2TvgDUrFqRmROGq67R1dX9VHFqXNwfsffwCQo72KulX7x6k+NnL7J2ySx8XvoyefYSalSpgHHuXERERrF87RbWL52dfpVMBYWhPiFuPnjuukzdDcP+M398dCwem84S4u5DfHQsFpWLUHVeD+KjY3my/QL6xtmptqA310esIeJ5IPW2jsTvmiuvzj0AoMrs7jjO3k2c/I5rTPNWPzF15hjGjZjO/Xsu9P6tK9v3r+GHSj8THPQmWf5qNStxeP8J7t56QExsLAOH9mLHgbXUq9aC134BFCtRmNHjB9Gtw0C0tGDzrlVcunAdD7cn6OjoMHfxVMYMm0ZCQoIGaptE21CfSNdn+O44T+nNo1N1Tcl1w9Ezz4X7iNW89X6NnmVutLTe31/W0qLEn0N5vvwgby46UXL9CKy7NuDVxtMAFJzUmVdbzhLzUrYHEEmkZyIFbfu24fjOE5zac5rnT3xYPG4pMTGxNOnwU4r5m7T/iRy5czCp1xQe3nXl9Ut/nG4689TdCwCr/FZEhUdx4ehFHjk94v51J2wL5QegXou6xMclcOXk1cyq3icNGtyLLZt2s33bPh55eDJsyCTevn1L11/bppjf0dGZyRPnsn/fMWJj3yU7b2+Xj/DwCA7sP46jozOXL92kcNGCAPzSthlxcXEcPXI6Q+skPq1J7+Zc2HWWS3vP8+rJSzZMWE3s21hqt6ufYv7CFYry+J4H1w9fIehlIC5XnLh+5IqqN8PCNg/R4dHcPHYNL2dP3G64kLeQDQDVmtckPi6BO6duZlr9vlcxsbGcu3SVEQN7UbFsKWxtrBnYqwu2NtbsPnhclU9PVxczUxPVI1fOHP9ZdnT0W8ZNX8C0sUPJ+a8eRa/nL6hUrhQlixWmScM6GBkZ8tLvNQCLV22gfcumWOWxSN/K/gffC848mL+PF6fupir/G9fnPDt8g7DHr4h6GYT3gWv4XnTBokpSz3T2/BbERUTz7Mgtgp288L/uTm6HvADYtaiGMj4Bn5Opey6RMfoM6MaOrfvYs+MQTx49ZdyI6byNjqFDl9Yp5h/cdyxbNuzC9aEHT594M2rIFLS1tKn5Q1UAHArZ4+76mGtXbnH18i3cXR/jUCipId1/SA9uXr+L0/2HmVa/lLw5/wCvubsJOnknVflN6pYhd7XiOHWaQ8hlF2JeBBJ+9wlhd5J6L3VNc6BnlpNXm88Q9eglQafvYfT+vTxnxcLkLFuQF+tOZFh9sgolWln2kdVIY+JfFLoKipQqzL0rjqo0pVLJvSuOFC9fPMVrqv9YDTdHN4bNGsKB+3vZdG4dnQd1RFs76cf70vsV+gb6OJRwIEfuHBQtUwQvdy+y58pOr9HdWTZpRabU7XN0dXUpW64kFy5cU6UplUouXrhG5crl0lTm06fPMDDIRukyxTE2zkX5CqVxfehB7tw5mTR5OKNGTEuf4MUX09FVYF+qIA+vOqnSlEolD686U6h8ykP6Ht/zwL5kwQ+Nh3yWlK1bgQcX7gHw2tsXPQN98pewxyhXdgqWccDH/RlGOY1oO7ITm6eszfiKCRLiE0hISERfT72nQV9fD0dnV9XxnfvO/NC0Az936M2MBSsIDQv/z7JnLlrJD9UqUa1S8veEIg4FcPV4Qlh4BK4eT4iNjcU2rzWOTg9xe+RJ57Zf39LhJiXyY1GxEP43PACI8H6NjoE+JiXyo5fbCNMyBQhx90EvlyFlR//CrUlbNBzx901XV5fSZYtz5eINVZpSqeTqpZtUqFQmVWUYGGZDoasgNDSpd9bd7Qn2DnZY21iRN58VBRzy4+HuSX67fLTv1Ir5s5ZnSF0yklmjikQ4PSX/oBbUeLCaqteX4jC1K9rZkt4z4oLCiX39BpM6pdE20CN31aJEuj1HS6FDkfm9eTR6bdZcn1RojAxz+pdcJrnQUejwJjBELT0kKARbh3wpXmNta0We6uU4e+hvxv06gbx2eRk2ewgKXQVblmwjMiySOcPnM2HZWPSz6XFm/1nuXLrL6IUjObjpMFa2eZi96XcUCh02L9nKpeNXMqOqakxNjVEoFAQGqHdbBgQEUbhwwTSVGRoazm99R7Nm3SIMsumza8dB/j53hT9WzWXtmm3kt7Nh19616OoqmDNrOYcPnUyPqohUyGGcAx2FDmFB6sOZwoJCsS6YN8Vrrh++Qg7jnEzdNwu0tFDoKji37RSHV+4HICo8itUjl9N/8VD0sulxZf9FnC8/oM/8gZzZcgKLfJaM2jABHYWC/Ut3cfvEjRSfR/x/jIwMKVOyGKs376RAfltMTXJz4twlnB56YJvXCoAaVSvQoHYN8lpb8uKVH8vWbOa3kZPZvmbxJ8d+nzh3EffHT9m1flmK52tUqcDPjerRofdQsunrM2vSSAwNsvH7wpXMnDiC3QePs2PfEXLnzsW0MUNwKJA/w34G/682d5eTzSQHWgodnBYfwHPnRQDehUVzbdgaaiz7DZ1senjtu4rvJReqLezNo81nyJ7PnHqbRqiu8zmeujvFIn2YmOZGoVAkG5YbGBhMwUL2n7hK3cRpI/F/HaBqkHg+9mLe70vZdWAdAHNnLMXzsRe7Dq5n5tRF1KlXkxHjBhAfF8+U8XO4df1e+lYqAxjktyRX5aIkxsbh3GMBeiY5KTy3F7rG2XEf9icAD/ssodCMbhSa2YPgc/fx23mB/INbEnrNlcTYOMofnYGuSU5ebjipGv4kvl/SmEgHWtrahASHsmjMEhITE3ns8gSzPKZ0+K0dW5ZsA+DqqWtcPfXhrn+ZqqUpWLQAyyf9wfarW/h90GzeBLzhz2MrcbrpkuLcjK/RsaNnOHb0jOq4Rs3KlCxZlNEjp/HA5QI9uw/F3z+QC5cOce3a7RTnZoisoVjVErQY2IaNk9fy9P5jLO2s+HVqL1oNacvB5XsBuHv6FndP31JdU7RKCWyL5mfLlHUsufwnKwYvJiwwhN8Pz8fjlluKczPE/2/O5FFMmbOEei27oKOjTbHCDjRuUBu3R54ANGlQR5W3cEF7Che0p3G7nty570zVisl7Hfz8A5m7dA3rls5GX1/vk887sFcXBvbqojpetXE7VSuWRaFQsGbLLg5uXcWl67eZMHMhezZqvkf2U063+h2FkT7m5R0oP6E9Ed7+PDuc9OXyxam7asOmLKsWxbiYLbcnbaXVtUVcGbiSt4FhNDk2nYCbj4gJ/u8eH5E1DBzWm+atG9O2WXe1obvbNu1h26Y9quO2HVoQGRnFvTtOXL5zjKb12mNlnYdV6xdSreyPvHsXp4nwU01LWwuU4Np/OQkRSfN7PKdupeSGETwat57EmDjCbj/i7k8TVNcYFLAiT7sfuFN/DOUPT+fFupMEn79PlUuLCL3pTpSbj6aqk2ESNR3AV0QaE/8S9iaMhPgETMyN1dKNzYx5ExCS4jXBAcEkxCWQmPjhV++5pw+mlqYodBXEx8Wr5dfV02XYrCHMHjqXvPbW6Ch0cLrpDMBLr5cUK1eUG+cyd2x5cHAI8fHxmFuor85gYWGGv39gujyHnp4ei5fMoG+fkRQoaIdCocO1q7cBeOrpTcWKZTh18vx/lCLSQ0RIBAnxCeQyy6WWnsssN6GBoSle03ZkJ64evMTFXecAePHIB33DbPSe059DK/ahVKp3eyv0FPSc2ZdVw5dhaWeFto4OHreShtn4efviULYQjn/L+PKMYGtjzeaVC4h+G0NUVDTmZiaMnDwHG+s8KebPl9cK49w58Xnpl2Jjwu3RE96EhNKu5yBVWkJCIvcePGTngaM4XjiSrEfD6/kLjp0+z75Nf3Dg+Bkqli2JiXFuGtX7gcmzlxAVFY2RkeZXsEtJ5Iuk97xQj5dkM89FmZGtVY2Jj2nrKagyuztXh6wmh70lWgpt/G8mDYkK93qNWfmCvDx7P1Nj/569CQ4lPj4eM3NTtXRzc9Nkve7/1m9QdwYO60WHlr1xd338yXzGJrkZPrY/bZp2o1zF0nh5PsfbywdvLx90dRUUcLDDw+1JutQno8T6hxL7+o2qIQEQ9eQVWtra6FuZ8tb7dbJrii7sg+e0raCtTY7SBQg4eoPEt+8Ive6GcbXi32RjQqSezJn4l/i4eB65PKZ8zfKqNC0tLSrULIebo1uK1zy840peO2u0tD5MislXwIag10HJGhIAXYd05vbFOzx56Im2tg46ig8fwgpdHXR0Mv9liYuL48H9h9SpU12VpqWlRe061bl9O30+DMeMHci5c5dxeuCKjo42Cp0PbVmFrkKjS+t9bxLi4vF2eUqJGh+W/tXS0qJEjVI8cXyU4jX6BvpqDWaAxH9WMNFKPiGs1eC2OF26z7OHXmjraKOj+PB7raNQoK2B3/PvjaFBNszNTAgLj+D67XvUq1U1xXyvAwIJDYvA3NQkxfNVK5Tl4LY/2bd5pepRomghmv5Yl32bVyb721UqlcyYv5wxg/tgaGhAYkIicfFJ74Xx7/9NSPw67vtpaWmho5fyfbfSQ1vy6qIzbx4+Q1tbG+2Pfg7aujpoacvveGaKi4vD+YEbNWt/+D3X0tKi5g9VuHfH6ZPX9R/Sk2Gjf6PLL/1wfuD6yXwA02ePZd2qrfj5+qOjrY2u7offDR2FDjraWf9zLOyOB/qWxugY6qvSDAtaoUxIJNYv+egAq051iQuJIuj0PbTev29rvf/eoqWrAHkv/+5Jz0QK9q7dz/glY3jk9Aj3B4/4pXdrshlk4+TuUwCMXzqWoNdBrJu7AYDDW4/SqnsLBs8YyIGNB7Gxt6HzoE4c2HgwWdn5C9lSt3kd+jRK2mvC56kPykQlTTr8xJuAEGwL2uLhlPKXuYz2x4oNrF67kPv3Xbh714kBA3tgaGjIX9v2AbBm3UJ8ff2ZPnUBkDTZrWgxBwD09HSxsrakVOliREVG4+X1XK3sIkUdaN3mZ2pW/xmAx4+ekpiYSNdf2xHgH0jhwgVxvOecibUVJ9Yf4bdFQ/ByfspTpyc07vkz2QyzcWnv3wD0XzyEN6/fsHv+XwA4nrtD497Nee7qjeeDx1jmt6LtyE44nruD8l9fDPMWsqHqzzWZ0GQEAL6er1AmKqnTvj6hgUnzMp46eWZuhb8j127dQ6lUYmdrg89LXxat3IC9rQ0tm/5IdPRbVm3cTsM6NTAzNeHFK18Wr9qIrY01Nap8uInSa8g46v9QnU6/NMfIyJBCBezUnsPAIBu5c+ZIlg6w/+gpjHPnok7NpC915UoXZ9XGv3B66M6Vm3cpaGebbDWojKAw1CeHvaXqOLutOcYlbHkXEkWUbzDlxrXD0MqYa0PXAFCkWwOifIMJ8/QFwLJKUYr/1hSPFMaE5ypkjV3zKhz7MWlZ7LCnviiVShw61OZtYBi5CloR5OSV4XUU6tat2sKSVbNxvu/KfUcX+vTvioGRAbu3J30eL/tzNn5+AcydsRSAAUN7MWr8IAb1GcMLH19V73xUVDTRUerLtdeqUw37gnYM7Z80/Mfp/kMKFrKnboOaWOe1IjEhkaee3plX2fd0DPUxsP/Q62hga0H2EvmJC40k9lUwBSZ2RD+PCe6DVwLgv/8qdsPbUGzZALwW7EHPJCcOU7rgt/MCiTHqQ7R0zXJiN7wN936eDEB8WBRRj16Sr29T3lxywrhWSZ4tPZB5lc1EWXHVpKxKGhMpuHD0IrlNc9FjVHdMzI3xdHvKmK7jCQkKBcAyr4Xal6dAv0BGdx7HoGkD2Hh2HYGvg9i/4QA7V+1OVvaoeSNYNf1PYt7GAPAu5h1zh89n6Kwh6OnpsmzyCoJea2bewIH9xzEzM2HCpOFYWprh4uxOm5bdVd3DNjbWanemrawsuHbjw1KTQ4f1Zeiwvly5fJOmjTuplb18xWwmjJtFdHRSt2pMTCz9+41h4ZLp6OvrMWrEVPz8/DOhluIfN49dI6dpTn4Z0YHc5sY8d/Nm7q8zCH8/KdvU2pzEj1bsOLhiL0qlkrajOmGSx4Tw4HAc/77LngV/JSu795wB/PX7JmLfxgIQF/uO1SNX0P33Pujq6bJ56jpC/JOv+S7SR0RkFEtXb8I/MIhcOXPQsHZNhvTrhq5CQUJCAo+fenPk5DnCI6OwMDOheuXyDOrzK3p6H+ZDvHjlR0gqVnj6t6A3Iazdsou/Vi9WpZUqXoRuHVozYPRUTIxzM3vSyHSp538xLVOARvs+bJZZaVrSfA7PPZe5PnwtBpa5MbL+MLRTS1uLcuPakd3WHGV8IhHPA3CcvYvH25IPv6w2vxd3pm8n/v3veEJMHNeGr6HKrO7o6Cm4NWkrb1+nPDRWZJwjB09hYmbCqAmDMLcww9XFgy6/9FPNx7O2sVJ7X/u1Z3v09fVYt3WpWjmL5q5k8bxVquNs2fSZNX8i/XuOUg3p9PP1Z/LY2Sz+Yxbv3r1j2IAJxMTEZnwl/yVH2YKUPzhNdVxoRtLGen67LuI+dBX6FsZky/vh9zwhOpYH7WZSeHZPKp2eS1xIBAFHbuA1d1eysgvP7IHPn0d55//hd9lt6EqKLx9Ivt6N8Vl5hIgHTzOucuKroKX890Dnb0AdmwaaDkEjHEO+z7tg0XGZ/+adFbSzqvzfmb5Be/xuazoEjXjrm/mrvGUFO8tM0XQIGtEz8IKmQ9AIS6Pcmg5BI7bpldB0CBpRz3/Pf2fSkDOWHTQdwif96J+84adJ0jMhhBBCCCHER76OWV1ZQ5ZqTERFRbFnzx48PT2xsrKiY8eOmJqafvaa2NhYYmPV70wnKhPR1pIJQUIIIYQQQmQkjX7jLl68OG/eJI2bfvHiBSVLlmT48OGcPXuWqVOnUrx4cby9Pz+Zac6cOeTKlUvt4RPxLBOiF0IIIYQQ4vum0caEh4eHapnA8ePHY21tzfPnz7l9+zbPnz+ndOnSTJw48bNljB8/nrCwMLWHbQ67TIheCCGEEEJ8ixKz8COryTLDnG7cuMHq1avJlStpE63s2bMzffp0OnT4/AQYfX199PX11dJkiJMQQgghhBAZT+ONiX82eouJicHKykrtXN68eQkMTJ/dlzNS9xG/0n3Er2ppPp4+/Fqnp4YiyhzVa1Ri6LC+lC1XEisrSzq278fxY2c1HZbIIMuursE8n0Wy9DNbT7J58loNRPT9SkhIYNWG7Rw7c56g4BDMzUxo2aQh/bp3VL2nTpy5iMMnz6ldV6NKBdYsnqk6XrNlJ5ev3+HREy90dRXcOL0vxefzfe1Ps459uXJ8F4aGBmzbfZDdB4/j5x9I7tw5+bFOTYb91gN9/aSlZaOiolmxbit/X77Bm5BQihYuyLhh/ShVrAgAcfHxrFi7hSs37vLS14/sRkZUrVSO4b/1wML88/Pk0ptFlSKU6N8U01L2GOYx5kLPJbw4fQ9I2pir3JhfyFuvLNnzmxMX/ha/qw9xnL2bt/6hmRqnyBiDhvem8c8NcShkT0xMDHdvP2D2tMU89Xym6dDSVe6qxbAd2Jwcpe3Rz2OCc/cFBJ28k2LeIvP7kLdbQx5P3szLtScyOVLxNdJ4Y6J+/fooFArCw8N59OgRJUuWVJ17/vz5f07Aziq8PbwZ2XGM6jghPkGD0WQOIyNDHrq4s23rXnbsWq3pcEQGm9R8tNqu1fkK2zJhx3RuHb+mwai+Txv+2svuQ8eZNWkkDvb5cfV4zKRZS8ie3YgubVuo8tWsWpGZE4arjnV1ddXKiYuLp1HdWpQtWYwDx5JvzPaP81duUrl8aQwNDTh+5gJLVm/i9/HDKVuqOM98XjJp1mK0tLQYM6QvAFPmLsPT6xlzpozCwsyUo6fP02foBA5vX4OluRkxMbG4PXpKv+4dKeJQgPCICOYuW8OgsdPZs3F5Ov+0Pk9hqE+Imw+euy5Td8Mw9XMGepiUssN52SFC3HzQy2VIpeldqbtpBCeafJ9L1n5rqlavxJb1O3lw3wWFQsG4yUPZcWAddao25+37fZG+BdqG+kS6PsN3x3lKbx79yXxmjSuRs0IhYv1kHyDZtC71NNqYmDp1qtpx9uzqO6IePXqUWrVqZWZIaZaQkMCbwO9rg6KzZy5x9swlTYchMknEG/UNzJr3b83rZ36433TVUETfrwcP3albqyq1qyftNZLXypITZy/h4vZILZ+eri5mpiafLGdQ764AHDr++R7FC1du8GPdpPfiBy7ulCtVnKY/1lU9d5OGdXB28wAgJjaWc5eusnzuVCqWLQXAwF5duHTtFrsPHmdI327kyG7E+mWz1Z5jwoj+dOw9DL/XAVjlSd4DllF8Lzjje8E5xXNxEW8513GeWtrtSVtpemIGRtamRPlqZoNRkX66tO2ndjxswERcPK9Sumxxbl2/p6Go0t+b8w94c/7BZ/Po5TGm8OyeOHWYRem/xmVOYOKbkKUaE/+2YMGCTIrk/5fXPi/77u7iXWwcro5urJuzgQDfAE2HJUSG0NFVULNVbU6sP6LpUL5LZUsWY9+RkzzzeYmdrQ0eT7xwdHZlzOA+avnu3Hfmh6YdyJkjO5UrlGFI327kzpXzi54rPCISR2dX5kxOuptZtlQxjp05j4vbI0oVL8KLV35cvnGHZo3qAUm9sgkJiejrqfeC6Ovr4ej86YZnZGQ0Wlpa5Mhh9EXxZTa9nAYoExN5Fx6t6VBEBsiZMwcAoSFhGo4kk2lpUWLlYHxWHSHq0UtNRyO+Mhof5vQtcLvvztzhC3jh9QJTC1O6De/K8gNL6FG/N2+jvp1uUiH+UfHHyhjmNOLS3vOaDuW71LtrO6Kio2nWqS862tokJCYypG83fn7/hR6gRtUKNKhdg7zWlrx45ceyNZv5beRktq9ZjI6OTqqf68qNOxQuaK+ay9D0x7qEhIXTtf8oUCqJT0igXcsm9O2WtFiGkZEhZUoWY/XmnRTIb4upSW5OnLuE00MPbPNapfgcsbHvWPLnRpo0qE12o6zbmNDW16X8hA54H7pBXKS8t39rtLS0mD5nLLdvOvLI3VPT4WSq/INboIxP4OW6k5oOJctIlFFOqSaNiXRw+8KHSUxe7t6433dn180d1G1WmxO7TmkwMiEyRt32DXC66EhowPc1tC+rOHX+MsfOXGDetDE42OfH44kX85atwcLMhBZNGgLQpEEdVf7CBe0pXNCexu16cue+M1Urlkv1c52/cpO6Nauqjm87OrNu624mjRxI6RJF8Hnpy9xla1i9aQe/9egEwJzJo5gyZwn1WnZBR0ebYoUdaNygNm6Pkn9Bi4uPZ+Tk2SiVSiaPHpTGn0jG01LoUHv1YNDS4tb4zZoOR2SA2QsnUaRYIVo17qrpUDJVjtL22PRpwp0GYzUdivhKSWMiA0SGR/HS6yV57fJqOhQh0p1ZXnNK1izNkn7zNR3Kd2vRyg307tJO1WAoXNAev9cBrN+2R9WY+Ld8ea0wzp0Tn5d+qW5MxMXFce3WXfr82l6V9se6rTRrVI9fmv+keu63MbFMn7ecvt06oK2tja2NNZtXLiD6bQxRUdGYm5kwcvIcbKzzqJf/viHh6x/AxuVzs2yvxD8NCSMbU862myO9Et+gmfMn0qBRbVo36Yafr7+mw8lUuaoWQ88sJ9UdV6nStBU6FJr2K/n6NOFGpazbyBdZgzQmMoCBYTas7aw4c0Am54lvT+229QgLDuP++buaDuW7FRMTi5a2eh+8trY2iUrlJ695HRBIaFgE5p+ZkP1vtx2dyZkjO0ULFfjw3LGxaP/ruXW0k1b5Uv7r+Q0NsmFokI2w8Aiu377HiAEflsv+pyHh88KXjSvmfvFcjszyT0Mih70lZ9rOJjYkUtMhiXQ2c/5Efmpan7bNuvPC55Wmw8l0r/deJuSyi1pa2V0Teb3vMn47L2goKs1LlNWcUk0aE+mg/6S+XD93E/+X/phamtJjZDcSExL5+9C3/UdoZGRIgYL5Vcd2dvkoVboYIW/CePnSV4ORiYyipaXFD23rcWXfRRITsuI+nN+HOjWqsG7LLqwsLXCwz4/7Y0+27j5Aq6Y/AhAd/ZZVG7fTsE4NzExNePHKl8WrNmJrY02NKuVV5fi9DiAsPAI//wASEhLxePwUAFsbawwNDbh49RZ1PhriBFC7RhW27jpA0cIFKV28KD4vfVmxbiu1a1RRzcW4duseSqUSO1sbfF76smjlBuxtbWj5Pr64+HhGTJyF22NPVs6fTmJiIkHBSUtR5sqZI9kSthlJYahPDntL1XF2W3OMS9jyLiSK6IBQ6qwdgkkpO853W4SWjjbZzJM2Vn0XGkli3Le/BPi3bvbCybT8pQk9Ow0mMjIacwszACLCI4iJidVwdOlHx1AfA/sPPYMGthZkL5GfuNBIYl8FE/+vRnJiXDyxAaFEP/XL7FDFV0gaE+nA3MqcyX9MIKdxTsLehOFy+yEDmg8m7M23vRpEufKlOHFqp+p4zrxJAGz/ax/9+4351GXiK1ayZmnMbSy4uOdvTYfyXZswvD8r1m1l5sKVvAkJxdzMhLYtmtD//ZwFbR1tHj/15sjJc4RHRmFhZkL1yuUZ1OdX9PT0VOX8sX6b2sZ2v/RIGs6wccU8KpcvzYVrN/l9/HC15+7XLWljvBVrtxIQGIyxcS7q1KjCkL7dVHkiIqNYunoT/oFB5MqZg4a1azKkXzd0FUkfOQGBwVy4ejPpObsPVCv/n+fOLKZlCtBo30TVcaVpXQDw3HMZp0UHyNeoAgDNzqovZXv6l1n433DPtDhFxujWK2nhgP3Ht6ilDx8wkT07D2kgooyRo2xByh+cpjouNCPp79Vv10Xch676xFVCpI6W8t/90t+AOjYNNB2CRjiGeGk6BI2Ijvt27h59iXZWlTUdgkbs8but6RA04q3vlUx9PrdHnvQaMo7Lx3epGgGasLPM97k5XM/Ab7tn+1MsjXJrOgSN2KZXQtMhaEQ9/z2aDuGTDuXppOkQPqnl6x2aDkGN9n9nEUII8b1JSEhg/PD+Gm1ICCGEyPrkU0IIIUQypYoXoVTxIpoOQwghRBYnjQkhhBBCCCE+IkuMpJ4McxJCCCGEEEKkiTQmhBBCCCGEEGkiw5yEEEIIIYT4SKKWbFqXWtIzIYQQQgghhEgTaUwIIYQQQggh0kSGOQkhhBBCCPGRb25H5wwkPRNCCCGEEEKINJHGhBBCCCGEECJNZJiTEEIIIYQQH5FN61JPeiaEEEIIIYQQaSKNCSGEEEIIIUSayDAnIYQQQgghPpIoe9almvRMCCGEEEIIIdJEGhNCCCGEEEKINJFhTkIIIYQQQnwkERnnlFrSMyGEEEIIIYRIE2lMCCGEEEIIIdJEhjkJIYQQQgjxEaWmA/iKSM+EEEIIIYQQIk2kMSGEEEIIIYRIExnmJIQQQgghxEdk07rUk54JIYQQQgghRJp8kz0TkQmxmg5BI/IYmmg6BI3wCvPTdAgacSzISdMhiExkV6iZpkPQiGdPjmo6BI3oaV1L0yFohJHCQNMhaETLyLuaDkEjwjUdgEgX32RjQgghhBBCiLRK1HQAXxEZ5iSEEEIIIYRIE2lMCCGEEEIIIdJEhjkJIYQQQgjxEdm0LvWkZ0IIIYQQQgiRJtKYEEIIIYQQQqSJDHMSQgghhBDiI7JpXepJz4QQQgghhBAiTaQxIYQQQgghhEgTGeYkhBBCCCHER2TTutSTngkhhBBCCCFEmkhjQgghhBBCCJEmMsxJCCGEEEKIj8gwp9STngkhhBBCCCFEmkhjQgghhBBCCJEmMsxJCCGEEEKIjyhl07pUk54JIYQQQgghRJpIY0IIIYQQQgiRJjLMSQghhBBCiI/Iak6pJz0TQgghhBBCiDSRxoQQQgghhBAiTWSYkxBCCCGEEB+RYU6pJz0TQgghhBBCiDSRxoQQQgghhBAiTaQx8Qltu7fiyO09XPM+x+bjayhRtliqrvuxRX3u+l1h4abZauldfuvAGZcjnHE5Qud+7dXOlShXnG2n16Ojo5Nu8adV555tOX/vCC4vrrH31GZKlyvxybw/Nq3L/rNbuet5gQfPrnD4wnZatG2ilqfngC7ccDvDDbcz9OzfWe1c6fIlOHBuW5ao9/eqT9+uuLhdJiDYnfMXD1ChQulP5i1arBDbtq/Cxe0y4VFeDBjYI1medu1b4PboKs9f3mf23Ilq52xt8+L44G9y5Mie7vUQqdOtd0duOp3hqZ8jR8/upGz5Up/M2+nXXzhwYiuu3tdx9b7OroPrk+XvN6g7To8v4/T4Mv0GdlM7V65CKU5e2JOpf99RUdHMXbqahq27UaFuCzr3G4GL+yPV+ejot8xatIr6LbtQoW4Lmnfuy+6Dxz9b5qHjZylZo7Hao3zd5mp5Nu3Yxw9NO/BD0w5s3rlf7Zyzqwfteg4mPj4h/SoqPut7/RyT9/P0pczCj6xG5kykoGHzegyfNog5Yxfx8L4bHfu0ZcXORbSp2YmQ4NBPXmdlk4ehUwbgePOBWrpDsYL8NqYXw7qORUtLiyVb53Hz0h2eeniho6PDhHkjmTV6AQkJmv2wadKyIeNnDGfK6Dk43XtI934d2bBnBY2qteFNUEiy/KEh4axeshGvJ894FxdH3R9rMWf5FIKD3nD1wk2KFHdg6Njf6Nd5GFpaWqzZvoSrF2/y2P0pOjo6zFg4gckjZmm83t+r1m2aMnvuBIYNnczdOw8YMLAHBw5voUK5BgQFBifLb2hgwLNnPhw6eII58yYlO29iasyKlXPo3280z7xfsPfAei5fvMGpU+cBWLz0d6ZOmU9ERGSG100k17zVT0ydOYZxI6Zz/54LvX/ryvb9a/ih0s8EB71Jlr9azUoc3n+Cu7ceEBMby8ChvdhxYC31qrXgtV8AxUoUZvT4QXTrMBAtLdi8axWXLlzHw+0JOjo6zF08lTHDpmXq3/eUucvw9HrGnCmjsDAz5ejp8/QZOoHD29dgaW7G/BVruXXPiTlTxpDXypLrt+8xc9FKLMxMqVur6ifLzW5kyLGd6z4kaH3YGveRpzcr1//FygXTUCqVDBw9jeqVy1O4oD3x8QnMWLCCqWOHoFBo/svm9+B7/RyT93OhSdIzkYLO/dpzaPtRju4+gffjZ8wZs5CYtzE079j0k9doa2szc+UU1i7cyKvnfmrn7BxseeL2lLvXHLlz9R6e7k+xc7AFoOuAjjjecsLNySND65QaPX7rzJ6/DnFg51GePvZmyqg5xLyN4ZdOzVPMf/v6Pc6euMjTJ8948ewVW9fu4pGbJxWqlAWgQCE7Hrk94ebVu9y4codHbp4UKGQHQO9BXblzwxGXB26ZVDvxb4MG92LLpt1s37aPRx6eDBsyibdv39L117Yp5nd0dGbyxLns33eM2Nh3yc7b2+UjPDyCA/uP4+jozOVLNylctCAAv7RtRlxcHEePnM7QOolP6zOgGzu27mPPjkM8efSUcSOm8zY6hg5dWqeYf3DfsWzZsAvXhx48feLNqCFT0NbSpuYPSV+6HQrZ4+76mGtXbnH18i3cXR/jUMgegP5DenDz+l2c7j/MtPrFxMZy7tJVRgzsRcWypbC1sWZgry7Y2lireh8euLjTonEDKpcvTV4rS9q2aEIRhwJqvRcp0dLSwszU5MPDxFh1zvv5CwoXtKNKhbJUrViOwg72eD9/CST1WFQoW4pSxYpkXMWFmu/1c0zez4UmSWPiXxS6CoqWLsytK/dUaUqlkttX7lK6wqe7SnuP6M6b4BAO70zeZe7p4YVtgXxY5rUgj40ltgXy8fSRN3nzW9OsfRP+nLsuhRIzl66ughJlinL90i1VmlKp5Prl25St+Omu0o9Vq1UJ+4L5uXPjPgCP3TyxK2iLVV5LrG3yYFfQlifuT8lnl5fWHZuxdPafGVIX8d90dXUpW64kFy5cU6UplUouXrhG5crl0lTm06fPMDDIRukyxTE2zkX5CqVxfehB7tw5mTR5OKNGTEuf4MUX09XVpXTZ4ly5eEOVplQquXrpJhUqlUlVGQaG2VDoKggNDQPA3e0J9g52WNtYkTefFQUc8uPh7kl+u3y079SK+bOWZ0hdPiUhPoGEhET09XTV0vX19XB0dgWgbKliXLh6E//AoKT39XtOPPN5RfXK5T9bdvTbtzRs3Y36rboyeOx0PL2eq84VKmjHsxev8HsdgO9rf56/eIVDgfz4vPTl0ImzDOnza/pXVqToe/0ck/fzjJGolXUfWY0Mc/qX3Ca5UCgUvAlU7/Z/ExiCnUP+FK8pU7kULTo2pVPDnimef/bkOavmrmXVriUArJyzhmdPnrNy9xKWz/yTanWq0HdUD+Lj4lk4ZTn3bzqlb6VSwdgkNwqFgqB/1Tso4A0FHOw+eV32HEZccTmJnp4eiQkJTBs7T/VG/vTJMxbPWsWmfasAWDRzJU+fPGPzvpUsmL6cmvWqMXh0X+Lj45k5cSF33795i4xnamqMQqEgMCBILT0gIIjChQumqczQ0HB+6zuaNesWYZBNn107DvL3uSv8sWoua9dsI7+dDbv2rkVXV8GcWcs5fOhkelRFpIKJ6T9/3+rDHQIDgyn4vjfhv0ycNhL/1wGqBonnYy/m/b6UXQeSbobMnbEUz8de7Dq4nplTF1GnXk1GjBtAfFw8U8bP4db1e58r/v9mZGRImZLFWL15JwXy22JqkpsT5y7h9NAD27xWAEwY3p9p85ZTv2VXFDo6aGlrMW3sUCqW/fTcEbv8NswYP5wiBe2JiIpi8879dPltBIf+Wk0eC3MK2tkytF93+gybAMDQft0paGdL76HjGTGgJ9du32PVhu0oFDqMG/bbZ59L/H++188xeT8XmiaNif+ToZEBM1ZMYtbo+YS9Cftkvv1bD7N/62HVcdO2PxEdFY3L3Yfsv7qdXxv3xcLKnNl/TqN5lXbEvYvLjPD/b1GR0bSo2wkjI0Oq1arE+BnDefHsFbfff3HYtWU/u7Z8mJDYqn1ToiKjuX/XhdM39tPmx1/JY2XBkrWzqVeh+VdTb5GyY0fPcOzoGdVxjZqVKVmyKKNHTuOBywV6dh+Kv38gFy4d4tq12ymO5RVZz8BhvWneujFtm3VXGxKxbdMetm3aozpu26EFkZFR3LvjxOU7x2harz1W1nlYtX4h1cr+yLsM/vueM3kUU+YsoV7LLujoaFOssAONG9TG7ZEnANv3HcHZ1YM/5k3FKo8l9x64MGvRKizMTKlWKeU7uGVLFqNsyQ8LcJQtVZzmnfqy99BJBvdN6nVo36op7Vt9GAZ7+MRZDA0NKFOyGM069mHX+mX4BwQxespcTu/bhJ6eXgb+FMSXks+xlMn7uUgtaUz8S+ibMOLj4zExN1FLNzE3Jjgg+R+KjV1e8tpas3jLXFWatnbS6LGbLy7QpmZnXj33Vbsml0ku+ozsQd9WgyhZvjg+Xi944f2SF94vUegqkoZBeXhlQO0+LeRNKPHx8Zj9q95mFiYEplDvfyiVSny8k8YHuz98TMHC9vQb1l31JvwxY5NcDBrVh07N+1KmfEmePfXhudcLnnu9QFehwL6gLY/dn6ZvxUSKgoNDiI+Px9zCTC3dwsIMf//AdHkOPT09Fi+ZQd8+IylQ0A6FQodrV28D8NTTm4oVy3Dq5Pl0eS7xeW+C//n7NlVLNzc3TXY389/6DerOwGG96NCyN+6ujz+Zz9gkN8PH9qdN026Uq1gaL8/neHv54O3lg66uggIOdni4PUmX+nyKrY01m1cuIPptDFFR0ZibmTBy8hxsrPMQExvLsjVbWDZnMrWrVwagiIM9Hk+82Lxz/ycbE/+mq1BQrHBBfF75png+JDSMPzftYPPK+bi4PiJ/vryqR3xCPM9evKJwwdT1Bokv871+jsn7ecaQTetST+ZM/Et8XDwezo+pXLOCKk1LS4tKNSvgfM81Wf5nnj60r/MrnRv0VD0un7nG3Wv36dygJ/6+AcmuGTl9MDvX7iHALxBtHW0Uig9tOh0dHXR0Mv9liYuLx9XJg2o/VFalaWlpUa1WJR7cdU51OVra2p+86zbh95FsXrMTf78AdHS0Ueh+VG+FTpZYWu97ERcXx4P7D6lTp7oqTUtLi9p1qnP7dvp0048ZO5Bz5y7j9MA16fXW+fB6K3QV8npnori4OJwfuFGz9ocVi7S0tKj5QxXu3fn0sMr+Q3oybPRvdPmlH84Pkr//fWz67LGsW7UVP19/dLS10f3337d25r3ehgbZMDczISw8guu371GvVlXi4+OJj49HW0t9wLGOjjaJian/2pCQkMCTp88wNzVJ8fy85Wvp2q4leSzMSUhMID4+/qNrE0lMkK8oGeV7/RyT93OhadIzkYLta3YzbdkE3Jw8cH3gTqc+bTEwNODorhMATF8+kYDXQaycvYZ3se94+shb7fqIsKSl0v6dDlDlh4rYFsjH1CGzAHB74EF+h/xUr1cFS2sLEhMTeP7UJ4NrmLJNq7czb8U0Hj5ww9nRlW79OmFgaMD+nUcBmP/HdPxfB7Bo5koA+g3tjssDd148e4meni61G9SgRdsmTBszJ1nZ1WtXwa6gLWMGTQXA+b4bBRzy80P96lhZW5KYkIiX5/Nk14mM88eKDaxeu5D79124e9eJAQN7YGhoyF/b9gGwZt1CfH39mT51AZA0ya9oMQcA9PR0sbK2pFTpYkRFRuPlpf7aFSnqQOs2P1Oz+s8APH70lMTERLr+2o4A/0AKFy6I473Uf7iL/9+6VVtYsmo2zvddue/oQp/+XTEwMmD39oMALPtzNn5+AcydsRSAAUN7MWr8IAb1GcMLH1/VXc+oqGiio6LVyq5Vpxr2Be0Y2j9p3oDT/YcULGRP3QY1sc5rRWJCIk89k78fprdrt+6hVCqxs7XB56Uvi1ZuwN7WhpZNf0RXoaBiuVIsWrkBfX19rPNYcPe+C0dO/s3oIX1UZYz/fSEWZqYM75+07v6fG7dTukRRbG2siYiMYtOOffi+DqBNs0bJnv/6bUeev3jF7EkjAShZrDDez19y5cYdXgcEoq2tjV1+mwz/OXzPvtfPMXk/F5okjYkUnD1yHmPT3Pw2phem5iY8dvVkcKdRqjWq8+S1JDHxy7cN0c+mx5hZwxn/21SUyqTrA/wCWTBpKVOWjCfuXRxTh8wmNib5Mm2Z4cShs5iYGjNk7G+YW5ji/vAxvdoPJvj9ZDYrmzwkKj/cVTMwNGDa/LHksbIgJiYWryfPGD1gMicOnVUrVz+bPlPmjmF4n/Gqevv7BfD7hAXMWT6Fd7FxjB08ldiY2MyrrODA/uOYmZkwYdJwLC3NcHF2p03L7qphLzY21mp3bK2sLLh248NqZUOH9WXosL5cuXyTpo07qZW9fMVsJoybRXT0WwBiYmLp328MC5dMR19fj1EjpuLn558JtRT/OHLwFCZmJoyaMAhzCzNcXTzo8ks/1Thnaxsrtfe1X3u2R19fj3Vbl6qVs2juShbPW6U6zpZNn1nzJ9K/5yjV37efrz+Tx85m8R+zePfuHcMGTCAmE/6+IyKjWLp6E/6BQeTKmYOGtWsypF83dN/3/i6cPo6lqzczbvp8wsIjsM5jwZB+3Wjf8sN8Bz//ALXei/CISKbNW07QmzfkzJGD4kUc+GvNIgraqy/IERMby+zFq1g4Y7xqAfWpJgAAiNNJREFUqGseC3PGD+/PpNlL0NPVZdakkWTT18/wn8P37Hv9HJP38/QnfYipp6X856/iG1LRqpamQ9CI8Pi3mg5BI7zC/P470zfIUPf7/FISHfd9NjotjXJrOgSNePbkqKZD0AgD6+/zc6xALitNh6ARr6OTbxz5PQiPytz5oV9ikW0XTYfwSSN9/tJ0CGpkzoQQQgghhBAiTTTamHB0dMTb+8M42m3btlGjRg3y5ctHzZo12bVr13+WERsbS3h4uNrj4y5MIYQQQgghvoQyCz+yGo02Jnr06MHTp0lLqK1fv55+/fpRsWJFJk6cSKVKlejTpw8bN278bBlz5swhV65cao/XkS8yI3whhBBCCCG+axqdgP3kyRMKFSoEwKpVq1i2bBl9+nxYVaNSpUrMmjWLnj1T3lkaYPz48YwYMUItrU7hxhkTsBBCCCGEEEJFo40JQ0NDgoKCyJ8/P69evaJy5cpq56tUqaI2DCol+vr66P9rdQxtLZkKIoQQQggh0iZR67/ziCQa/dbduHFj/vzzTwBq167Nvn371M7v2bMHBwcHTYT2f+k2qDN3/a4wYsZgTYeSoTp2b8ORiztx9LqIo9dFdp/YyA/1q//3heKrVL1GJXbvXccjzxuER3nR9OeGmg5JZKBBw3tz/O/dPPK5jdPjy2z4azkFHew0HRZRUdHMXbqahq27UaFuCzr3G4GL+6MU806fv4KSNRqzbffBFM+/e/eONt0GUrJGYzweJ9+1+M59Z+q36prq5504cxElazRWe/QbMUktzzOflwweO52aTdpTpWFruvYfye17n944UGSs7/VzTN7PRXrSaM/EvHnzqFGjBrVr16ZixYosWrSIixcvUqxYMR49esTNmzc5eDDlD4GsqniZorTu2pzHrp6aDiXDvfYNYNHMP3jm5YMWWrTq8DOrti6iZb3OeD7Kusu9ibQxMjLkoYs727buZceu1ZoOR2SwqtUrsWX9Th7cd0GhUDBu8lB2HFhHnarNeRutuWWop8xdhqfXM+ZMGYWFmSlHT5+nz9AJHN6+BktzM1W+c5eu4ezqgYWZ6SfLWrRqIxZmJjzyTPn96sKVm9SpUeWLnrdm1YrMnDBcdayrq6tW5sAx07C1sWbD8rlk09dj255DDBwzlZN7NmL2iV21Rcb5Xj/H5P1cpCeN9kxYW1tz//59qlWrxqlTp1Aqldy+fZszZ85gY2PDtWvXaNKkiSZD/CIGhgb8vnIKs0bNJyIsQtPhZLgLZ65w6dw1nnu94JmXD0tmryI6KpqyFUtpOjSRAc6eufQ/9u47rqmrDeD4L+yhslGGoKi49151a6111Dpr3bvuWfdW1Lq31rqto66qde+9xYULFygIMgTZI3n/oG8kBZRSIAjPt598as49997nJOQm557F9GkLOHjgmLZDEZngx7Z92bltH08ePcPj/mOG/jQex/z2lClXQmsxRUVHc+LsBYYP6EmlcqVxcrRnQM8fcXK0Z8fejwtw+b0LwG3hSuZMHo2enm6yxzp/+TqXrt1i5MBeKZ7v9IUr1KtVLdXnBTDQ18faylL9MMuTW70t+H0Ir7zf0OvHdhQtXBDn/A4M69edyKhonj7XzsrJOV1O/R6T6/nnKbPwI6vR+grY5ubmzJ49m9mzZ2s7lP/sZ7dhXDx5mWvnb9JzaFdth5OpdHR0aNqiISYmxty+flfb4Qgh0lmev38Uvw8O0VoM8XHxxMcrMTTQvNtvaGjArbsPAFAqlYydNo9uP7ShsItzcochICiYKXMWs9htEkZGRsnm8Xz+iqDg91StWJaYmNjPnvf/rt++y1fNOpAndy6qVCzL4D5dMTfLA4C5WR4KOjmy/8hJihctjIG+Pjv/PISlhTklin55XXqzG/keEyJttF6ZyC4at2xAsdKudGnaR9uhZCrX4oXYcXg9hoYGRIRHMqDbKJ49+fSgeSHEl0WhUDDV7WeuXbnF44fa68JpampC2VLFWbVhGy7OTlhZmnPoxFnu3H+Ek0PCysm/bfkDXV0dfmzbMtljqFQqJsxcQLtWzShV3JU3vn7J5jt1/jI1q1ZEX18ffX39z54XoGa1ijSsUxMH+7x4v/Fl8eoN9Bsxka2rF6Crq4tCoeDXxbMYPGY6VRu1RkdHgaW5OasXTNdowRCZS77HhPhvpDKRDvLa2zJi+mAGtB9OTHSMtsPJVC88X9Gy3g/kzp2Lr1s0YM7SKXRq2UcuxEJkI7PmTaBo8SJ817SztkPBbeJIJrktpH6rH9HV1aG4a2GaNqyDx2NPHjx6ypY//uSPdUtRKJKfimXrrv2ER0TQq3O7T57n9IUrdPy+earO+3/fNKyr/rdroYK4FipI03Y9uH77LtUqlUelUjFz/gqsLMzYuOIXjAwN2X3gCANHT2H72iXYWMuYCW2Q7zGRnKy4OFxWJZWJdFCsTFGsbCzZcmytOk1PT4/y1crSrntrajg3QKnMir3c/rvY2Di8XrwG4MHdR5QuV4KufToyaeQsLUcmhEgPM+aOp2GTOrT+piu+Psnfxc9MTo72bFj+CxGRUYSHR2BjbcmIiW442ufj1p37BAW/p9H3XdT54+OV/LJsLZt37uPY7o1cu3mHO/cfUaFeC43jtu81mGaN6jFr4kjeBQTx8Mkz6tSokqrzpiS/gx0W5nnweu1LtUrluXrTnbOXrnHpyE5ymZoCUKLoQC5fv82fh098toIjMoZ8j4ns7Ny5c/zyyy/cvHkTX19f9u7dS6tWrdTbVSoVkydP5tdff+X9+/fUrFmTlStXqteBSw2pTKSD6+dv0L5uF420SYvG8srTi43LtmbbikRyFDo6GBjqfz6jECLLmzF3PF83a0Db5t3w9nqj7XA0mBgbYWJsREjoBy5du8nwn3rQqG4tqlUur5Gv77AJNP+6Pq2+aQzA2KH9GNTn4/Xa/10gfYdPYN7UsZQuWRSAMxevUK508WS7HiV33pS89X/H+5AP2Pw9S1NUVDSQdC0kHYUiR31PZHXyPSayk/DwcMqWLUuPHj1o3bp1ku1z585lyZIlbNy4kYIFCzJx4kSaNGmCh4dHimPK/kkqE+kgIjySZ481m0OjIqJ4HxySJD07GTFhAGdPXsL39VtMc5nQ/PuvqVqzIj3aZe/1NXIqU1MTXAp9HNBaoEB+SpcpTnBQCK9f+2gxMpERZs2bSKs239Djh0GEhUVgY5sw/emH0A/qH8XacPHqTVQqFQWcHPF67cP85b9R0MmRVs0ao6+npx7s/H96erpYW1pQ0NkRALt8thrbTYyNgYRWhHy2NgCcvnCVerWqpfq8ABERkaxYt5VGdWtibWWJ9xsfFqxYh5OjPTWrVgCgbKni5Mmdi3Ez5tOv+w8YGRqwa/8RXvv68VUNzUVbRebIqd9jcj3/PGU26ejUtGlTmjZtmuw2lUrFokWLmDBhAi1bJowz27RpE3nz5mXfvn106NAhVeeQyoRIM0trS+Yum4ptXms+hIbx2OMpPdoN4tLZq9oOTWSA8hVKc+jINvVztzkJi3Ft3bKL/n1HaysskUG69kz4Etn910aN9GE/jWfntn1aiCjBh7BwFq1aj9+7AMzy5KZRnVoM7tsVfb30+TqLiIzi6g13xgzp+6/Oq6Orw5NnL9h/+AShYeHYWltSo0oFBvbugoGBAQAW5masmj+dJWs20nPwGOLi4ihc0JmlsydRrIhLusQv/p2c+j0m1/MvW3R0NNHRmjd1DA0NMTQ0/FfHefHiBW/fvqVhw4bqNDMzM6pWrcrly5dTXZlQqFSq7FH1SqSSXW1th6AVoXHaW0hKm56H+Go7BK0w0f93F43sIiJWe3fFtSmvqbm2Q9CKl08PZOr5jp+5yNJfN7J/65pMPe8/GdvnzO8xFzO7z2fKht5GBGk7BK0IDc+6CwPOdO6k7RBSFNu9CFOnTtVImzx5MlOmTPnkfgqFQmPMxKVLl6hZsyY+Pj7Y2X387LVr1w6FQsGOHTtSFY+0TAghhBB/MzE2Ynj/lMdBCCFyhqw8imns2LEMHz5cI+3ftkqkJ6lMCCGEEH+rWbWitkMQQohPSkuXpuTky5cwG52fn59Gy4Sfnx/lypVL9XF0Pp9FCCGEEEIIkZ0ULFiQfPnycfLkSXVaaGgoV69epXr16qk+jrRMCCGEEEIIkUh2GVAcFhaGp+fHxTVfvHiBu7s7lpaWODk5MXToUGbMmEGRIkXUU8Pa29trrEXxOVKZEEIIIYQQIhu6ceMG9erVUz///1iLrl27smHDBkaPHk14eDh9+vTh/fv31KpViyNHjqR6jQmQyoQQQgghhBDZUt26dfnUxK0KhYJp06Yxbdq0NJ9DKhNCCCGEEEIkkpVnc8pqZAC2EEIIIYQQIk2kMiGEEEIIIYRIE+nmJIQQQgghRCJKhbYj+HJIy4QQQgghhBAiTaQyIYQQQgghhEgT6eYkhBBCCCFEIspss2xdxpOWCSGEEEIIIUSaSGVCCCGEEEIIkSbSzUkIIYQQQohEpJNT6knLhBBCCCGEECJNpDIhhBBCCCGESBPp5iSEEEIIIUQiSm0H8AWRlgkhhBBCCCFEmkhlQgghhBBCCJEm0s1JCCGEEEKIRGTRutSTlgkhhBBCCCFEmkhlQgghhBBCCJEm0s1JCCGEEEKIRKSTU+ply8rEBFV+bYegFeXz+2s7BK2wf7hT2yGITGRsX1vbIWiFX/h7bYegFTn1/Y70Oa/tELQi7szv2g5BK/Tq/qDtEIRIM+nmJIQQQgghhEiTbNkyIYQQQgghRFrJonWpJy0TQgghhBBCiDSRyoQQQgghhBAiTaSbkxBCCCGEEInIonWpJy0TQgghhBBCiDSRyoQQQgghhBAiTaSbkxBCCCGEEIlIJ6fUk5YJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiERk0brUk5YJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiERUMp9TqknLhBBCCCGEECJNpDIhhBBCCCGESBPp5iSEEEIIIUQiMptT6knLhBBCCCGEECJNpDIhhBBCCCGESBPp5iSEEEIIIUQiSpnNKdWkZUIIIYQQQgiRJlKZEEIIIYQQQqSJdHMSQgghhBAiEenklHrSMiGEEEIIIYRIE6lM/INVtWJU2zSSJu7LafX2d+y+rvTJ/JZVilJ7/2S+8VhN8xcbaHB+HoX6NNXI49i6Jo1vLuWbR79SasqPGttM8lvT8OJ89HIZp3tZ/g3DCqWxWTQdh6Pbcb51AuO6NT6Z32rKKJxvnUjysPtjrTqPadP6OBz6Hccze7EY3k9jf127vNjv3YDC1CRDyvNv+L0L4Oepc6nZtB0V67Xku879uf/wSYr5x8+YT6maTZM8Wnbqq85z8OgpGnzXmRpft2XukjUa+7/x9aNZh16EhYdnWJn+6Yb7PQaMnky9Fp0oVbMpJ89dSpLn2UsvBo6eQrXG31O5QSva9xyM71v/Tx538469fNuhFxXrtaTBd52Zs3g10dEx6u1Z7XUQIjv63Of7+JmL9B46jppN21GqZlMePXn22WN6Pn/F0HEzaPx9V0rVbMrmHXuT5Mlqn+/fzt7jhxWHqDF1G/Vm7WToltO8fBeS6v2P3H1BufGbGbrltEb6xvMPqDdrJ/Vm7WTTBQ+Nbfe839Fx+V/ExWfeqgSf+85SqVQs+3UTdVv8QMV6Lek1ZCyvvN989rjbdh+g8fddqVCvBR17D+Wex2ON7XOXrKHG121p8F1nDh49pbHt6KnzDBg9OX0KKL440s3pH3RNDAl58IpX285Qdf3wz+aPj4ji+bpjhD70Ij4iGssqRSn3S0/iIqJ5teUUBpa5KT+/N7eGriL8lT/Vt4zi3cUH+B2/DUCZ2T14MHM7cWGRGV20T1IYGRH75Dlhfx7Bdv7Uz+YPmreC4KUfKw4KXV3stq8h4sQ5AHTM82A5cQSBU34h7rUvtktmEHX9NpHnrwJgNXYwwUvXogqPyJgCpVJI6Ac69xtBlQplWTV/OhbmZrzyfkOe3LlS3GfM0H4M699d/TwuPp7vuw6gcf3aAAS/D2Hy7MXMGD8cR4d8DBg5mSoVy1K3ZlUAZsxbxtB+3cllapqxhUskMjKKooVd+K5ZY4aOm5Fku9drH7r0H0nrb5swoNePmJqY8OyFFwaGBike869jp1m4aj3Txw6jXOkSvPR6zYSZC1AoFIwe3CdLvg5CZEef+3xHRkVRoUxJmtT/iilzFqfumNFRONrno3H9WkkqCpA1r3M3X/jTvlpRSjpYEa9UsvSYO/03nGTPkOYYG+h/ct83wWEsOHyLCgVsNdKfvA1m5ck7LOlcDxUweNNpqhe2o0g+C+Lilcz48yoTW1VDTzdz7s2m5jtr3dY/2LprPzMnjMDBLh/Lft1E3+ET+HPLagxTuKYfPnGWuUvXMGnUIMqUKMrmnfvoO3wCB7b9ipWFOWcuXOGv42dYs3AmXq99mDhrITWrVsTC3IwPYeEsWbORtYtmZcprkFlkNqfUk8rEP/ifuoP/qTupzh9y/xUh91+pn0d4B2D/TWWsqxbl1ZZTmDjbEvshgjd/XgHg3UUPchdxwO/4bRxaVUcVG4fvoevpXo5/K+rSdaIupT4OVVg4qrCPd5yM69ZAJ08uwvYfAUDPwQ5VWDgRx84kHP/GHfQLOhN5/iomTeqhiosn8tSFdC1DWqzb+gf5bG2YMf5jxdHRPt8n98mdy5TcuT5+QZ48d4nQD2F816wRAK993pIrlylNG9YBoHKFsjx/6U3dmlU5dPwMenp6NKpbMwNKk7La1StTu3rlFLcvWbOR2tUrM2JAT3Wak6P9J4/pfu8h5UuXoFnjegA42OXlm0Z1uevxCMiar4MQ2dHnPt8tvm4AJLQWpFbp4kUpXbwoAItWrk+yPSt+vld0a6DxfFqbGtSf9Qceb4KoWDBvivvFK5WM23mB/g3KcOulPx+iPrauvngXQpF8FlQpZAdAkXzmvHgXSpF8Fmy88IAKBfJSytE6YwqUjM99Z6lUKjbv3Eefrh2oX7s6ALMmjqRO846cPH+JbxrWTfa4m3bspU3zpnzXrDEAk0YN4tyl6+w9eIxendvx/JU3lcuXplRxV0oVd2X24tW89n2LhbkZC1b8RvtWzbDLZ5vssUX2J92c0plZKWcsK7sScPkhAOHP36JrbIBZKWf0zU2xKFeIUA8v9M1MKf5zW+6O26DdgNNJrlZNibp6i3jfhG4xcV5vUBgZol+0MDp5cmNQoigxT5+jkzsX5j91I2jOUi1HnOD0hSuULFaE4RNm8lWzDrTpNoBd+w//q2PsOXiUapXKYZ8v4cvKydGeqKgoHj7xJCT0Aw8ePaFo4YKEhH5g6a+bGDf8p4woSpoplUrOXbpOgfwO9Bk2nq+adaBj76HJdoVKrFzp4ng89lQ3hXu/8eXc5evUrpbwo+ZLex2EEKn3JXy+w/6uFJiZpNzCCrD61D0sTY34rlKRJNuK5LXgVUAovu/D8QkO41XABwrnNcc78AN/3nzGwEblMiL0FH3uO+u1z1sCAoOpXqm8Oi13LlPKlCjKnfuPkj1mbGwsHo+fUq1yOXWajo4O1SqV4879hN8yRQu78ODR07/f66dER0fj5GDPrTv38XjsSae2LTKmwOKLIC0T6aTJraUYWOVBR0+XR/N28+r3MwDEhoRza/AqKiztj66RAd5/nMf/zF3KL+jNi3XHMHGyperGkejoJ+znc/CadguSBrrWVhjXqELA+I9NnMoPYQRMnov1tJ9RGBkQ/tdxoi7fwGrSCD7s+BM9h3zYLpwOerqErN5ExMnzWon9tc9bduz7iy7tW9O7S3vuP3yC28JV6Ovp0fKbRp/d3/9dIBeu3GDO5J/VaWZ5cjNzwgjGTZ9PVHQ0zb9uQM2qFZnotpAfvm/OG9+3DPp5CnFx8fzUsxON69XOyCJ+VlDweyIiI/lty04G9e7K8P49uHD1JkPHzWDd0tlULl8m2f2aNa5HcEgonfuPBJWKuPh42rX6hj5dOwBf3usghEi9rP75VipV/PLXDco521A4r0WK+W6/9GffTU92DGyW7HYXWzMGNSpPv/UnABjcuDwutmb0XXecoV9X4NJTH1advIOerg6jm1X+ZAtIevjcd1ZAUDAAVpaaZbaytCAgMDjZYwa/DyU+XpnsPi+8XgNQs2pFvm1Snw69hmBkaMjMCSMwMTZi+rzlzBg/nB17/+L3XfsxNzdjyujBFHZxzoDSZ67MGwXz5ZPKRDo532oaeiZGWFQsTMnxHQh78ZY3+y4D4Hv4Br6Hb6jzWlUvRp4STtwdv5GGlxdyo/9Sov1DqHN4OgFXHhETEKqtYqSJafPGKD+EEXH6okZ65OmLRCZKM6xQBv0iLgTNXYb9nxsJGDuL+MAg7DYtJ+rWPZTB7zM58oQvnJLFijC0XzcAirsW5unzV+zcdyhVlYk/D58gd65cNPiqukZ6wzo1aVjnYxP/9dt3eeL5gnHD+vNNu57Mnfoz1paWdOw9hIrlSmNlYZ6exfpXlMqEfqH1alenS4fvACjmWgj3ex7s3HcoxcrEtVt3+XXTDiaMGECZkkXxeu3D7MWrWbX+d/p1/wH4sl4HIcS/k5U/324HruHp954NfZqkmCc8Opbxuy4wqVU1LEyNUszXtqorbau6qp/vv/UMEwN9yjrZ0HLhn2zt/w3+oRGM2XGev0Z+h4GebrqWJbH/+p31Xwzo+SMDen6cRGbFuq1Uq1QOPT09Vm/czt5NKzh76RrjZsxj57qs0ftAZA7p5pROIrzeEfrIm1dbT+O55jDFRn6fbD4dAz3Kzu6B+6jfMC2QFx09HQIvPyLsmS9hz32xLF84kyP/73K1bEL4oRMQF5dyJn19LMcOJmjmQvTy26PQ1SX61l3iXr0m1us1hqWLZV7AidhYWVKogJNGmkuB/Pj6vfvsviqVir1/HaN5k/ro66c8uC8mJoYZ85YzefRgvF77Eh8fT+XyZSjo7IhzfgfuPUi+6TmzWJjnQU9X91+/Dst+3UTzJvVp0+JrXAsVpGGdmgzp2421m3eiVCa9p5PVXwchRNplpc+32/5rnHv8mrU9G5HXLOUB4N6BH/AJDmfIltNUnLiFihO3cND9OWcfvabixC14B35Isk9weBSrT91lTPPK3PMOwNkqD87Weajsko+4eCWvMvhm4Oe+s6z/bl0IDNJshQgMCsbaKvkWGgvzPOjq6iS/j2Xy+zx/5c3Bo6cY1LsL12/fpVK5UlhamNOk/ld4PPYkXMuTq4jMJZWJDKDQUaBrmPyPy6JDv8P/9B1C7r1EoauDQvfjHQwdPV0UmTQjRHoxrFgWfSdHwvZ9epyBWa9ORF26TswjT9DRhUTlVujpgo52yl2+TMIsRIm98nqTqoFk12/fw+u1D62bp3znC2D1hu3UqlaJEkULo1TGExcfr94WFxdPfDI/vDOTvr4+JYu7qpuz/++l9xvsP/E6REVHo6Oj0EjT/ft9VKmSzoKR1V8HIUTaZYXPt0qlwm3/NU55eLGmRyMcLHN/Mn9BGzN2Df6WHQObqR91ijlSuWA+dgxsRj6zpFOXzzt0gx9rFievmSlKpYq4ROWKU6qIV2bsDECf+85ytM+HtZUFV266q7eHhYdz1+MxZUslf9NOX1+fEkWLcPXGx32USiVXb7pTtlTxJPlVKhXT5i5h9KDemJgYo4xXEvv3zcS4v/+fHa7nqiz8X1Yj3Zz+QdfEkFwFP86MYOJkg1lJZ2LehxH5JpAS49pjZGfJrUErASjYvRGRrwP54OkDgHW1YhTu34zna48mOXZuVwccWlbjdKNxAHzw9EGlVOHcsS5R796Tq7A9we6fn/87IyiMjdDL76B+rudgh75rIZShH4h/64/5wJ7o2loTOGmOxn65Wn1N9L2HxD57meKx9Qs6Ydq4Lr4dE9aaiHvpBUoVuVp+TXxgMPoFnIh58DjF/TNS5/at6Nx3BGs2bufrBl9xz+Mxu/YfZvLoweo8C1euxz8gELeJIzX23XPwKGVKFKWIS4EUj//sxSuOnDrHH+uXAVDQOT86OjrsPnAUaysLXnh5U6q4a4r7p5eIiEi8Xvuon7/x8ePRk2eY5cmNXT5buv/wPSMnzaZSuVJUqVCWC1ducPbiVdYv/fh+j50+D1trK/W0uHVqVmXT9j0Ucy1EmRLF8Hrtw9JfN1GnZlV0dTWb+bPK6yBEdvS5z3dI6Ad83/rjHxAIoL5xYG1lgbWVJZD08x0bG8uzF15//zsOv3eBPHryDBMT4yQzvWWVz/es/dc4fPcFi36sh6mhPgEfEqZcz2Wkj5F+ws+dCX9cxDaPMYObVMBQXzfJeIrcRgmDtZMbZ3HZ04dXAaFM/z6ha1dJRytevgvlwuM3vA0JR1dHQQGbPBlZxM9+ZykUCjq3a8WajdtxdnTAwT4vy37djK21FQ1qf1w/qufgMTT4qgY/tEkYON2l/XeMnzmfksWKUKpEUbbs3EdkVDStmiXtOrX7wBEszM2oW6sakFDBWbFuC3fuP+T8lRsUKuD0yenVRfYjlYl/sCjnQq09E9XPS0/rDIDXjrPcGrIao7zmmDhYqbcrdBSUGN8eEycbVHFKwl/68WDGdl5uOpnk2OV+6cW9KVuIj4gGQBkVy62hqyjr1g0dA33ujttA1NvkB0hlNIMSRcn363z1c8sR/QEI23+UwCm/oGttid4/7lIrcpliUr82wfNWfPLYlhOGE7xgJaqoKABU0TEETpmL5ZjBKPT1CZqzlPh3gelcotQpXbwoi9wmsnjVBlZt+B0Hu3z8PKQv3zapr84TEBiEr5/m4m0fwsI5ceYiY4b2/ech1VQqFVPmLmHUoN6YGCf0xzUyNGTG+OHMnL+CmNhYxg37ibw2GT+t4P1HT+kx6OMg8blLE+aNb9m0ITMnjKBhnZpMGjWQtZt34rZwFQWcHFk4cwIVypZS7+Pr54+O4mNLRN+uHVEoFCxdswn/d4FYWJhRt2ZVBvfpqnHurPQ6CJEdfe7zffr8FSbMWqDePmrybAD69+ik7gP/z8+3f0AQbboPVD/fsG03G7btplL50mxYNlednpU+339cS1i4rdfaYxrpU7+vQcsKhQDwDQlHoUiy62dFxcYx+8B15rSvrW6RzWtmys/fVmbynksY6Oky7fsa6kpLRknNd1aPTm2JjIxiytwlfAgLo0KZkqyaP11jjQnvN74Eh3zsktW0YR2C34ewbO0WAoKCKFakEKvmT0/SzSkgKJg1G7ezZdXHv6fSJYrStUNrfho1GUsLc2ZNGJGBr4DIihSq5PojfOH25ftB2yFoRXn7T69WnF3ZH0u6oJLIvoztZdYnkf1F+mhnhjttizvzu7ZD0Aq9ujnzd4u+tYu2Q0hRjwJttB1Cita93KXtEDR8WR30hRBCCCGEEFmGVisTgwYN4vz5/3b3JTo6mtDQUI1HrCr+8zsKIYQQQggh/hOtViaWL19O3bp1cXV1Zc6cObx9+/ZfH8PNzQ0zMzONx+5wjwyIVgghhBBC5ATanrHpS5rNSevdnI4dO8Y333zDvHnzcHJyomXLlhw8eDDZeeqTM3bsWEJCQjQe35uWyOCohRBCCCGEEFqvTJQuXZpFixbh4+PDli1biI6OplWrVuTPn5/x48fj6en5yf0NDQ3JkyePxkNfkXGrTwohhBBCCCESZJmpYfX19WnXrh3t2rXDy8uLdevWsWHDBmbPnk18fNYaA2FVrRhFfvoWszIFMc5nwdVuC/A9ckO9vdjI73FoWR1jB0uUMfG8v/uCh247CL6tnTUk0othhdLk6dIOg+JF0LOxxn/4JCLPXFJvd751Itn9ghetIXTTzswKM935vQtgwYp1XLhyg6ioaJwc7Zk+bph63vSAoGAWrljHpWu3+BAWTsVypRg3rD/Oidbt+BLccL/H+t934fHIk3eBQSx2m0iDrz7OS16qZtNk9xv+U096dEqY9WLg6Ck88nxOUPB78uTORbVK5Rnevwe2NlbJ7iuESN7nPo/Hz1xk576/8HjsSUjoB3atX0Yx10LJHkulUtF/5CQuXLmR5DgAPm/9aN6xD+f/2o7PW3+Wrd2Mx+On+Lz15+fBfejc/rskx9y2+wDrf99FQFAwRQu7MG5Yf0qXKApASOgHlq/dzKVrt/D1e4eFhRn1a1dnUO8u5M71cUXqew8fs2jlejwee6JQKChV3JUhVewoameZHi9hsn47e4+TD7x5+S4EQ31dyjrZMLRJBQrYmKnz9Fx7jJsv/DT2a1O5CBNaVcuwuNLb5763Pvf388bXjyZtuiV77PnTx9GkfvafVe/LX3Yv82SZykRiTk5OTJkyhcmTJ3PiRPI/ULVJ18SQkAeveLXtDFXXD0+yPeyZL3fHbSD8lT+6xvoU6vMNNXaM5Xj1YcQEftBCxOlDYWRE7JPnhP15BNv5U5Ns927UVuO5cc0qWE0aQcTJL3eKw5DQD3TuN4IqFcqyav50LMzNeOX9Rr0gj0qlYsiYaejp6bFkziRymZiyacceeg0Zx59bV6vnXf8SREZGUbSwC981a8zQcTOSbD+zf6vG8/NXbjDJbRGN6tZUp1WpUJbeXdpjY22J37tA5i1by7AJM9m6esE/DyeE+ITPfR4jo6KoUKYkTep/xZQ5iz95rM079vGppRVOnb9ClQplMDExJjI6Ckf7fDSuX4u5S5KfdvvwibPMXbqGSaMGUaZEUTbv3Eff4RM4sO1XrCzM8Q8IxD8giJEDe+FSwAlfP3+m/bKMdwGBLJw5AUhYaK/f8InUq1WNCSMGEh8fz/LfNvPThpMcGf09+roZ03Hi5gt/2lcrSkkHK+KVSpYec6f/hpPsGdIcYwN9db7WlQrzU8Ny6udG+l9Oj4fPfW/B5/9+8tlaJ7nm//HnYdb/vpva1SpleBnEl0WrlQlnZ+ckK+UmplAoaNQo6eqL2uZ/6g7+p+6kuP313ksaz+9P3kKBTvXIU9yJgAsPMjq8DBN16TpRl66nuF0ZqLngnkmdGkTdcCfujW9Gh5Zh1m39g3y2NswY/7HS6Gj/cYX0V95vuPPgEfs2r6KwizMAE0cOpG7zHzh0/AxtWnyd6TGnVe3qlaldvXKK2/+/Uu7/nf77B0h+Bzt1WpcOH+9g2ufLS68f2zF47DRi4+LQ18uS9y6EyJI+93ls8XUDIOEO8qc8evKMjdt3s+O3JdRt0SnZPKfPX6ZxvYQ7zaWLF6V08YQWhkUr1yebf9OOvbRp3pTvmjUGYNKoQZy7dJ29B4/Rq3M7irgUYNGsCer8To72DO7TlTHT5hIXF4+eni7PX3kTEvqBAb06Y5fXBkhYRK/1mYv4vg/DySpjVpJe0a2BxvNpbWpQf9YfeLwJomLBvOp0IwM9rHMbZ0gMGe1z31vw+b8fXV3dJNf8k+cu0aRBbUxMvszXRWQcrY6ZePHiBVZW2bv7g0JflwKd6xMbEk6oh5e2w8k0OpbmGNeqSti+I9oO5T85feEKJYsVYfiEmXzVrANtug1g1/7D6u0xsbEAGCS6o6Wjo4O+gT637365FcfPCQgK5tyla7T+tkmKeUJCP3Dw2GnKlS4uFQkhtCAyKorRU+cwfsSAJD8M/y/0Qxi37j6gXq3UdeGJjY3F4/FTqlUup07T0dGhWqVy3Ln/MMX9PoSFk8vUBD29hBuIBZ0cMTfLw56DR4mNjSUqOpo9B47iYmOGvXmuFI+T3sKiYgAwMzHQSD/s/oK6M3fy/eL9LDl6i8iYuEyL6b/63PdWWjx49JRHT59/8pqf3ShVqiz7yGrkGz6D5G1UnsqrBqFrbECU33sutncjJujL7eL0b+Vq3hhlRAQRp77cLk4Ar33esmPfX3Rp35reXdpz/+ET3BauQl9Pj5bfNKKgc37s8tqyePUGJo0ahImxEZt27MXPP4B3gUHaDj/D7D98AhMTYxrWqZlk24IVv7Ft9wEio6IpW7IYy39J2iVOCJHx5i5ZQ7lSJahfu3qKec5fvo5roYKpHtcU/D6U+HglVpYWGulWlha88Hqdwj4hrN6wjTYtPo67MjU1Yf2yOQweM43VG7YB4Oxoz/Ku9dHLoC5O/6RUqvjlrxuUc7ahcN6P5WlapgD2FrmwyW3Mk7fBLD56m5cBoSzoVDdT4vqvPve9lRZ7Dh7FpUB+ypeW2TJFUlqfzSm7CrjowekGYzn37RT8T9+h8prBGFhnTLNtVpSrxdeEHz4FMbHaDuU/USpVFHctzNB+3SjuWpi2Lb/h+xZfs3PfIQD09fRYNGsCL73eULNpOyo1aMW1W3epXa0SOjrZ9+O19+Axvm1cD0NDgyTbuv/Qhj/WL2PNwpno6Oowdvo8VFnwTooQ2dnp81e4evMOY4b0/WS+U+evpLpVIi3CwsP5adRkChV04qeeP6rTo6KjmeS2iPKlS7B1zQI2r5xHYRdnBm06RVRs5rQCuB24hqffe+a01xxM3KaKKzWK2FMknwXNyrkwo00NTnl44/2FjHn83PfWvxUVHc2h42dyVKuE+Hey768dLYuPiCb8pR/Btzy5PfxXVHFKnDvW1XZYmcKwfCn0CzoRtjdtF66sxMbKkkIFnDTSXArkx9fvnfp5yWJF2L1xOZeP7uL0n1tZvWAG70M/JOmjml3cdL/PC6/XtG6e/HgQC3MzCjg5UqNKBX6ZOobzl69z58GjTI5SiJzt6k13vN/4Uv3rNpT9qhllv2oGwLDxM+k2cDSQ0GXp4tUb1P0XlQkL8zzo6uoQGKQ5Ri4wKBjrf7RWhIdH0Hf4RExNjFk8a6JGd8e/jp3hja8fM8YPp3TxopQtVZy5U37mTXAYZx56p7XYqea2/xrnHr9mbc9G5DUz/WTe0vmtAfD+QnoXpOZ76984dvoCkVHR6nEWOYUqCz+yGunmlEkUOgp0DfU/nzEbyNWyKdEej4l9+lzbofxn5cuU4OU/mu5feb3BLp9tkrz/n/LwlfcbHjx6ysBenTMlxsy25+BRShQtQrEiLp/Nq1ImXPZivvAWKiG+NL06t+P7f0wA8V3n/owe3Ie6NasCcO3WXfLkzpWqz/L/6evrU6JoEa7ecFdPMatUKrl6052O37dQ5wsLD6fvsAnoG+izdM7kJK2YUVFR6OgoUCg+zjOlUOigUChQZuCvJZVKxewD1znl4cXaXo1xsMz92X0e+SZUnL6UAdn/5nsrNfYcPEq9WlWxtDBPh+hEdiSViTTQNTEkV8GPd51NnGwwK+lMzPswYoLDcB3SirdHbxLl/x4Dy9y4dG+EUT4L3hy4osWo/zuFsRF6idZO0HOwQ9+1EMrQD8S/9U/IY2qCSaOvCF6wWlthpqvO7VvRue8I1mzcztcNvuKex2N27T/M5NGD1XmOnjqPhbkZdnltePr8JbMXraJ+7erUrFpRi5H/exERkXi99lE/f+Pjx6MnzzDLk1v9JRQWHs6x0+cZObB3kv3vPnjE/YdPqFCmJHny5ML7jS9Lf91Mfgc7ypUqlmnlECI7+NznMST0A75v/fEPCARQj1ewtrLA2spS/fgnu7w26lbTMxeuJmmViI2N5dkLr7//HYffu0AePXmGiYkxTo72AHRp/x3jZ86nZLEilCpRlC079xEZFU2rZgn98cPCw+kzdDyR0dEsnjSK8PAIwsMjgISWS11dXapXqcD8Fb8xY/5yfmjTApVSxdotO9HVUVA50axK6W3W/mscvvuCRT/Ww9RQn4APkQDkMtLHSF8P78APHL7zglpFHTAzMeTp22DmHbpBxQK2uOaz+MzRs4bUfG997u/n/7xe+3DT/T4r503L3EKIL4pClQ07M+/L90OGHt+6RnFq7ZmYJN1rx1ncR6+j0ooBWFQojIFlbmKCw3jv/ozHi/bx3j1j79SXt/fP0OMbVixLvl/nJ0kP23+UwCm/AJCrdTMsRvTndZP2qMLCMzSe/7M/lvxc6OnlzMWrLF61gVev3+Bgl4+uHb7TGEi45Y8/Wf/7LgKD3mNjZUmLrxvQr3tH9PW/rJaoa7fu0mPQz0nSWzZtyMwJIwD4489DzFm8htP7t2osPgXw5NkLZi9azWPP50RGRWFjZUnNqhXp260jeW2s0y1OY/vsv1iSEGcPLv/k53HfX8eZMCvp+i39e3RiQKKxCYmVqtlUY9G6hq27MH3sMKpXLq/Ok9JiZZXKl2bDsrnq57/v2s/633cTEBREsSKFGDu0H2VKJtw0SOlaAnB01wYc7BIqC5eu3WLl+q14Pn+FQqGguGshBlSyo4yTTQqvyn9XbvzmZNOnfl+DlhUK8fZ9OOP/uICn33siY+PIa2ZK/RL56V23NLmMko4RSy96ddP3d8vnvrdS+/ezaNUGDh47xbFdGzJkHKC+depbxTLbD85JF2vMKn5/tVfbIWiQykQ2ktGViawqoysTImuRyoTICSJ9MnYmPI/HnvQcPIZzf23PUlM3x535XdshaEV6Vya+FFKZSJusVpmQAdhCCCFEDhMfH8/YYf2zVEVCCPFlkquIEEIIkcOULlGU0iWKajsMIbIsVZacNylrkpYJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiESU2g7gCyItE0IIIYQQQog0kcqEEEIIIYQQIk2km5MQQgghhBCJKGU2p1STlgkhhBBCCCFEmkhlQgghhBBCCJEm0s1JCCGEEEKIRGTRutSTlgkhhBBCCCFEmkhlQgghhBBCCJEm0s1JCCGEEEKIRGTRutSTlgkhhBBCCCFEmkhlQgghhBBCCJEm0s1JCCGEEEKIRFQqmc0ptaRlQgghhBBCCJEmUpkQQgghhBBCpIl0cxJCCCGEECIRpSxal2rSMiGEEEIIIYRIE6lMCCGEEEIIIdJEujkJIYQQQgiRiCxal3rSMiGEEEIIIYRIE6lMCCGEEEIIIdIkW3ZzmqHw1nYIWvHk8Rtth6AVuYs013YIWlEnj6u2QxCZqGm+8toOQSt8Y0O0HYJWGNvX1nYIWhHpc17bIWhFzLLx2g5BK/SnbNN2CClSyWxOqSYtE0IIIYQQQog0kcqEEEIIIYQQIk2yZTcnIYQQQggh0koWrUs9aZkQQgghhBBCpIlUJoQQQgghhBBpIt2chBBCCCGESESlkm5OqSUtE0IIIYQQQog0kcqEEEIIIYQQIk2km5MQQgghhBCJKLUdwBdEWiaEEEIIIYQQaSKVCSGEEEIIIUSaSDcnIYQQQgghElHJonWpJi0TQgghhBBCiDSRyoQQQgghhBAiTaSbkxBCCCGEEIkopZtTqknLhBBCCCGEECJNpDIhhBBCCCGESBPp5iSEEEIIIUQiKpV0c0otaZkQQgghhBBCpIlUJoQQQgghhBBpIt2chBBCCCGESERmc0o9aZkQQgghhBAim5kyZQoKhULjUaxYsXQ/j7RMCCGEEEIIkQ2VLFmSEydOqJ/r6aX/T3+pTAghhBBCCJGIKgt3c4qOjiY6OlojzdDQEENDwyR59fT0yJcvX4bGI92cUtC223fsv7aTiy9OsOGv1ZQsVzxV+zVu2YAbvueZt36WRvqP/Tpw7N5+jt3bT6e+7TW2lSxfgs1H16Krq5tu8adV7z6duedxDv/Ah5w6s4eKFcukmLdY8SJs3rqCex7nCA1/zk8DuifJ0659SzweX+DV69vMmj1eY5uTkwO33E+SO3eudC/Hv9W1V0eu3DnGM99bHDi+jXIVSqeY94cubdhzaBMPXlziwYtLbN+7Nkn+vgO7cefJOe48OUffAV01tpWvWJrDp3dmife7UZemLL6wmg2PdzBt3xwKlS2SYt4J26fz+6u9SR6j1n98X5v1acnKmxtYeXMD3/RuobF/oXJFmHlwHjq6ctnRlm+6NGPtxd/Y/WQP8/6cT5Gyrp/Mb5rHlH7T+7Hxxib2PN3LqjOrqVivknp7nVZ1WXdlPdvubafnxF4a+9o62rLqzGqMcxlnSFn+jZx6Pc/uwsMjmL1oFY1ad6VivZZ06jucew8fq7ePnzGfUjWbajz6Dp/wyWNu33uQ77r0p2qj1lRt1JpOfYZx/vJ1jTxzl6yhxtdtafBdZw4ePaWx7eip8wwYPTn9CpkK+rVaYtR7BiZj12EyahWGHYajsLL75D66xStj1GcmJmPWYjJuPUb93NArU0sjj16NZpiMWoXJqFXoVW+msU3HoRBGfWaCjlzPtcHNzQ0zMzONh5ubW7J5nz59ir29PS4uLnTq1AkvL690j0daJpLRqEV9hk0ZiNvP87l/24OOvduydNt8vq/1A8GB71Pcz84xH0Mm/cStK+4a6YWLF6Lf6J4M7fwzCoWChZvmcOXsdZ49eo6uri7j5oxg5qhfiI+Pz9iCfUbr75sxa/Y4hg6ZyI3r7vw0oDt7/txIxfINCXgXmCS/ibExL196sW/vIdzmJL1AW1pZsHS5G/37juLlC2/+2LOWc2cuc+RIwsV3waLpTJ40lw8fwjK8bJ/S4ruvmTxjNGOGT+X2zXv06teZrbtX81XlbwkMCEqSv3qtyvy5+xA3rroTFR3NgCE9+X3PGupXb8lbX3+Kl3Rl1NiBdO0wAIUCNmxfwdnTl3jk8RRdXV1mL5jM6KFTtP5+V/u2Jj9O6M668avwdH9C0x7NGbN5EiPqDSQ0MCRJ/oV956Bn8PGSkcs8N7OPLOTqX5cAyF/MmTbDO/JLj5koFDBq3XjunXPH+7EXOro69JzVj7VjVqKMV2ZaGcVHtZrXptfEXiwft5wn7o9p0bMl07ZMo1/dvoQk837r6esxfet03geEMLufG4FvA7F1sCUsNByAPBZ5GDR3EItGLMLv1VsmbZjM3Ut3uH4y4YdX/xk/sXH2BiLDIjO1nP+UU6/nOcGk2YvxfP4St0kjsbW24sDRU/QeMo4/t64mr401ALWqVWLGuGHqffT19T95zHw21gzr1x3n/A6oVCr+PHyCQWOmsWv9Mgq7OHPmwhX+On6GNQtn4vXah4mzFlKzakUszM34EBbOkjUbWbto1ifPkd50ChQn7vox4t88R6Gjg36DDhh1Hkvk8lEQG53sPqrIMGLP7UUZ4APxcei6VsCgVT9U4aHEP7uLIq8TBvXaEvX7LwAY/TCa+Gd3Ufl7g44OBt/2IubAr6CU67k2jB07luHDh2ukJdcqUbVqVTZs2EDRokXx9fVl6tSp1K5dm/v375M7d+50i0eqlMno1Lc9+7Ye4MCOQ7x48hK30fOIioyiRcdmKe6jo6PDjOWTWDNvHW9e+WpsK1DYiacez7hx8RbXL9zE8+EzChR2AqDzTx25dfUOHnceZWiZUmPgoJ5sXL+DrZt38fiRJ0MHTyAyMpLOXdomm//WrbtMHD+b3bsOEh0dk2R7wQL5CQ39wJ7df3Hr1l3Onb2Ca7FCALRp25zY2FgO7D+aoWVKjd4/deX3TbvY+fs+nj5+xpjhU4mMiKLDj62TzT+oz89s/G07D+4/4tnTF4wcPAkdhQ61vqoGQOEiBXn44AkXz1/lwrmrPHzwhMJFCgLQf3B3rly6wZ3b9zOtfCn5plcLTm8/ztk/TvHm6Wt+G7eK6Mho6rRrkGz+8JAwQt69Vz9K1y5LdGS0ujJhX8gBr4cv8bh0jwcX7+H18BX2hRwB+LZvKx5d9eD5Xc9MK5/Q1KpXK45uO8rJP07g/dSbFWOXEx0ZTaP2jZLN37B9I3KZ52Zm7xk8vPEQ/9f+3L96n5cPXwCQ1ykfEaERXDhwnqd3n3Lv8l0cC+cH4KsWXxEXF8flI5czrXwpyanX8+wuKjqaE2cvMHxATyqVK42Toz0Dev6Ik6M9O/b+pc5noK+PtZWl+mGW59M/oOrWqsZXNargnN+BAk6ODOnbDRNjI+48SHhPn7/ypnL50pQq7so3jepiamrCa9+3ACxY8RvtWzXDLp9txhU8GdFbZhPnfg7Vu9co/byI3rcSHXMbdOwLpriP8uVD4h/dQBXggyrYn7irR1D6eaHjVBQAHWt7lH5eKF88SHj4eaFjbQ+Afo3mKF89ROnzPFPKpy1KlSrLPgwNDcmTJ4/GI7nKRNOmTWnbti1lypShSZMmHDp0iPfv37Nz5850fa2kMvEPevp6FCvjytXzN9VpKpWKa+dvUKZiyRT36zW8G0GBwfy57a8k2zwfPcfJJT95HWzJ55gXJ5f8PHv8Agdne5q3/4aVs3/NkLL8G/r6+pQrX4rTpy+q01QqFWdOX6RKlfJpOuazZy8xNjaiTNkSWFiYUaFiGR7cf4S5eR4mTBzGyOFT0if4/0BfX58y5Upw/szHHz0qlYoLZ69QsXLZVB3D2MQIPX093r9PuLv70OMpBQsXwN7RDof8drgUdubRQ0+cC+Sn/Q/fMXfmkgwpy7+hq69HwdKFuH/hjjpNpVJx/8JdilQomqpj1G3fkCsHLhAdmXDny/uxF3Yu9ljZW2PtYIOdiz3eT7ywdcpHnbYN2Dlva4aURXyenr4ehUsX5s4Fd3WaSqXC/YI7RSskP7NH1YZVeXTzEf1m9GfTzc0sO76ctgPaovN3twafl28wNDbEpaQLucxyUaSsKy8fvsTUzJROI39k9cRVmVG0T8qp1/OcID4unvh4JYYGmi0NhoYG3Lr7QP38+u27fNWsA9926MW0X5byPiQ09eeIj+fQiTNERkVRrlTC56RoYRcePHpKSOgHHjx6SnR0NE4O9ty6cx+Px550atviM0fNeAojEyCh9SG1dAqWRMfKjvhXCZUmpZ8XOlZ2KMysUJhZo2OVD6W/NwoLW/TK1yHmVPr+GBWZw9zcHFdXVzw90/fGnnRz+gdzSzP09PQIeqfZvSXoXTAFCjsnu0/ZKqVp2bEZPzTqkez2l09fsWL2GlZsXwjAcrfVvHz6iuU7FrJkxkqq161Kn5HdiYuNY96kJdy+cifZ42QkKysL9PT0eOcfoJHu7x+Aq2uhNB3z/ftQ+vUZxepf52NsZMj23/dy8sR5lq2YzZrVm3Eu4Mj2P9agr6+H28wl/LnvcHoU5V+xtDJHT08vSTeud+8CKVQk5bs6iY2fMgK/t/7qConnk+fMmb6I7XsSflTMnrYIzyfP2b53LTMmz6du/VoMH/MTcbFxTBrrxtVLNz91+AyR2yI3unq6hARodm8JCXiPfSGHz+5fqGwRnIo58+vo5eo0H8/X7Ji7lbFbpgCwfc4WfDxfM27rFLa5baRMnfJ8P7QD8XFxbJryG4+ueaRrmUTK8ljmQVdPl+CA9xrp7wPe4/h369E/5XPKS5kaZTiz7wxTu03BroA9/Wf0R1dfj+2LthEeEs7C4QsZtnA4BkYGnNp9itvnbjFo7mD+2niQvPnzMuG3iejp6/H7wt+5dOhisufJSDn1ep4TmJqaULZUcVZt2IaLsxNWluYcOnGWO/cf4eSQMF6gZrWKNKxTEwf7vHi/8WXx6g30GzGRrasXfHJMy5NnL+jUdzgxMTGYGBuzeNZEChVM+HupWbUi3zapT4deQzAyNGTmhBGYGBsxfd5yZowfzo69f/H7rv2Ym5sxZfRgCrsk/3eWYRQKDL7uQrzXI1T+rz+d19AYkxErQFcPVEpi/lqP8vk9AFQBPsSc3IFR53EAxJzcgSrAB6Mu44g5/ju6hctgULcNqvh4Yo5sRPlKWuO+BGFhYTx79ozOnTun63GlMvEfmZgaM23pBGaOmktIUNJ+x/+3e9Of7N70p/p5s7ZfExEewb0b99l9YStdmvbB1s6GWSun0KJqO2JjYjMj/Ax38MAxDh44pn5es1YVSpUqxqgRU3C/d5oe3Ybg5/eO02f3cfHitWTHZmRlA4b2okXrprRt3k2jq9fm9TvZvP7jnZu2HVoSFhbOzet3OHf9IM3qt8fOPh8r1s6jernGxHxh73fd9g3weviSZ3eeaqSf3HqUk1s/dl2r/X09IsMieXLrMfNPLWdii1FY2lkxaNkIhtTqS1xMXGaHLlJJoaNDSOB7lo9ZhlKp5Nm9Z1jltaJ1v9ZsX7QNgCtHL3Pl6MdWvVJVS1GweAHWTFrN6vNrmDfwF4LfBTN//wIeXL2f7NiMrESu518Wt4kjmeS2kPqtfkRXV4firoVp2rAOHo8T7rp+07CuOq9roYK4FipI03Y9uH77LtUqpdziXtDJkd0blvMhLJxjpy8wfuZ8Niybq65QDOj5IwN6/qjOv2LdVqpVKoeenh6rN25n76YVnL10jXEz5rFz3dKMKXwKDL7pjo5tfqLWTfl85pgoIleNQWFghE7BUhg0+RFlsB/Klw8BiLtxgrgbiaYULfsVqugo4r2fYjJoPpFrJqDIY4lhm8FELhoM8dnrep5153JKvZEjR9K8eXOcnZ3x8fFh8uTJ6Orq0rFjx3Q9j1Qm/uF9UAhxcXFY2lhqpFvaWBDon/SHrmMBBxyc7FmwcbY67f/dAK54n+b7Wp1488pHYx8zSzN6j+hOn+8GUqpCCbyee+P94jXeL16jp6+X0Gz+KHP7IgYGBhMXF4eNrbVGuq2tNX5+79LlHAYGBixYOI0+vUfgUqgAenq6XLxwDYBnni+oVKksRw6f+sxR0ldQ4Hvi4uKwtrHSSLexsUrSSvNPfQd2Y8DQnnRo1YuHD56kmM/C0pxhP/fn+2ZdKV+pDM89X/HiuRcvnnuhr6+HS+ECPPJ4muL+GeFD8Afi4+IxszbTSDezNuf9u/ef3NfQ2JDqzWuxa8H2T+bLbZGb74e2Y1rbCRQu58rbFz68fenL25e+6OrpYlfQHu/H6T+rhEgqNCiU+Lh4LKzNNdLNrc0Jfhec7D7B/kHExcWjTDTA8rWnN5a2lujp6xEXq/nDQc9Aj/4z+7Ng6ALsCtihq6vL/asJY4N8XrzBtXxRrp+4lr4F+4ycej3PKZwc7dmw/BciIqMID4/AxtqSERPdcLRPfhrM/A52WJjnweu17ycrE/r6+jg5JowPKFmsCA8ePWHLH38yefTgJHmfv/Lm4NFT7Fq/jD1/HaNSuVJYWpjTpP5XTJy1kPDwCExNTdKnwJ9h8E03dF0rELV+KqrQpJOHJKFSoQryQwUo375Cx8Ye/Votif67MqHBJDf6dVsTtX4auo6FUQb6ogp6iyroLQodXRRWdgmDs0WW8vr1azp27EhgYCA2NjbUqlWLK1euYGNjk67nkTET/xAXG8eju0+oUquiOk2hUFC5VkXu3nyQJP9LTy/a1+1Cp4Y91I9zxy5y4+JtOjXsgZ+Pf5J9RkwdxLY1O/H3fYeOro7GAiK6urroamHqzNjYWNxv36du3RrqNIVCQZ26Nbh27Xa6nGP0zwM4ceIcd9wfoKurg57ux3Lr6etpZSrF2NhY7rp7UKtONXWaQqGg1ldVuXk95e4J/Qf3YOiofvzYpi933ZP+XSQ2ddbP/LpiE74+fujq6KCvn+j91tNFVyfzyx0fG8eLe88oWfPj1L8KhYKSNUvz9NbjT+wJVZvVQM9Anwt7z34y34+TenDotwMEvQ1ER1cHXf2P5dTV05UpYjNRXGwcnvc8KVPz4zgghUJB2ZpleXwr+e4JHjceYudsh0KhUKfZuzgQ6BeYpCIB0H5QB26eucWz+88S3m+9xO+3HrpamEIyp17PcxoTYyNsrC0JCf3ApWs3qV+7WrL53vq/433IB2ysLJPdnhKlUpVs67FKpWLa3CWMHtQbExNjlPFKYuMSPhtxf/8/PpNmOzL4phu6xSoTtXEGqvdpvAGo0EGhl/xsV4ZNOhN7+XBCJUWhAJ1E96J1dFDIFLFZ0vbt2/Hx8SE6OprXr1+zfft2ChVKW9f1T5GWiWRsXb2DKYvH4XHnEQ/cH/JD77YYmxhzYPshAKYuGY//2wCWz1pNTHQMzx6/0Nj/Q0jCoKd/pgNU/aoSTi75mTx4JgAe7o9wLuxMjfpVyWtvi1IZz6tn2rlbu2zpb6xaM4/bt+9x48YdfhrQHRMTE7Zs3gXA6l/n4ePjx9TJCVPF6evrU6x4YQAMDPSxs89L6TLFCQ+L4PnzVxrHLlqsMK2//5ZaNb4F4MnjZyiVSjp3aYe/3ztcXQtx6+bdTCztR7+u2MjCFbO4e/sBt2/do3f/zhibGrNj614AFq+cha+vP7OnLQLgpyE9GTl2IAN7j8bby0fdmhMeHkFEeITGsWvXrU7BQgUY0j+h3+md2/cpVKQg9RrWwt7BDmW8kmeeSf9OMsOhtfvpN38wz+8+49mdpzTt8S1GJkac/eMkAP0XDCbobRA75m7R2K9u+4bcPHaVsPcfUjx2qVplsStoz6rhCYPNn9/xxL6QA2XrVsDKzgplvBKfZz4p7i/S3761+xg2fxie957yxP0JLXu2xMjEiBM7E7oxDFs4nMC3gWyasxGAw5sP8W3Xb+k9pQ8HNxzAvqA9bQe05eD6A0mOnb9Ifmo3r82Qpgl3bl97vkalVNKofSOC3wXjWMiRJ3cyt/Xt/3Lq9TwnuHj1JiqVigJOjni99mH+8t8o6ORIq2aNiYiIZMW6rTSqWxNrK0u83/iwYMU6nBztqVm1gvoYPQePocFXNfihTcLA6YUr11O7eiXs8toSHhHBX8fOcP32XVYvmJHk/LsPHMHC3Iy6tRIqL+XLlGDFui3cuf+Q81duUKiAE3kyYR0lg2Y90Ctdg6ht8yEmEkWuhBZnVVQExCVUggy+648qNJjYkwktyvq1WhLv8xxVsB/o6qFbpDx6ZWoR89e6JMfXcSmNwsqOuH0rAVD6PEfH2h7dwmVRmFmBSpUwxWw2o8wWHZ0yh1QmknF8/yksrMzpN7onVjaWPHngyaAfRhIUkNAdIJ9DXpTKf/9HZmhkwOiZwxjbbzIqVcL+/r7v+GXCIiYtHEtsTCyTB88iOirpNKuZYc/uv7C2tmTchGHkzWvNvbsP+b5VN3V3H0dHe40uD3Z2tly8/HG2kyFD+zBkaB/On7tCs6Y/aBx7ydJZjBszk4iIhDnno6Ki6d93NPMWTsXQ0ICRwyfj6+uXCaVMav/eI1haWzJy3EBsbK15cO8RP7bpqx6/Ye9op/F+d+nRHkNDA37dtEjjOPNnL2fBnBXq50ZGhsycO57+PUaq329fHz8m/jyLBctmEhMTw9CfxhEVlfw84BntysGL5LHKQ5vhHTC3seCVxwtmd5lG6N+Dsq3sbZL8ndu52FOsSglmdZqS4nH1DQ3oNq03SwfOU5c76G0gGyavpe8vA4mNiWXliCXEJjOdsMg4Fw6cx8zSjE7Df8TCxoLnHs+Z3HkS7/8elG1jb4Mq0ec7wDeASZ0n0WtSL5YeXUagXyAH1u1n98rdSY49cPZAfpu+Vj2zV0x0DItGLKLf9P7oG+izetIqgvy0Mx4qp17Pc4IPYeEsWrUev3cBmOXJTaM6tRjctyv6enrEx8fz5NkL9h8+QWhYOLbWltSoUoGBvbtgYGCgPob3G1+CE83wFPT+PeOmz+NdYBC5TU1xLVyQ1QtmUKNKBY1zBwQFs2bjdrasWqBOK12iKF07tOanUZOxtDBn1oQRGf8iAPqVE6Z3Nu4+SSM9et9K4tzPAaBjZo1Slejv3MAQw2bdUeSxgrgYlAE+RO9ZTvyDK5oH19PH8JtuRO9aAn/vrwoNIubwBgxa9YO4WKL3rlRXWkTOpFCpVNmu6lXJrra2Q9CKJ6FvtB2CVuQ20P4Ku9pQJ8+nVy/Ornb6Zm6/+6yiab60TdH8pfONzdqDtjOKe2DOHGcR6XNe2yFoRcyy8doOQStMp2zTdggpqulQX9shpOjim8wdX/o50jIhhBBCCCFEItLNKfW0PmJm2bJldOnShe3bE/rxbd68mRIlSlCsWDHGjRunHsSUkujoaEJDQzUeSpUs7y6EEEIIIURG02plYsaMGYwbN46IiAiGDRvGnDlzGDZsGJ06daJr166sXbuW6dOnf/IYbm5umJmZaTzehsn0ZEIIIYQQQmQ0rXZz2rBhAxs2bKB169bcuXOHihUrsnHjRjp16gRAsWLFGD16NFOnTk3xGGPHjmX48OEaaXVdm2Zo3EIIIYQQIvvKhkOKM4xWKxM+Pj5UqlQJgLJly6Kjo0O5cuXU2ytUqICPz6enGzM0NMTQ0FAjTUeh9d5bQgghhBBCZHtarUzky5cPDw8PnJycePr0KfHx8Xh4eFCyZEkAHjx4gK2trTZDTJOuAzsxaHw/fv91JwsmLdV2OBmmRs3KDBnah3LlS2Fnl5eO7fvy18Hj2g4rww0c1oum3zaicJGCREVFceOaO7OmLOCZ50tth5ahFl9YjU3+pJ/HY5sOs2HiGi1EJDKaZV4ruo3tRsV6FTE0NsT3pS+LRy7C866ntkPLNDnlep5VhYdHsPTXTZw8d5mg4PcUcy3EmKF9KV28KLFxcSxds5Hzl2/w2seXXKamVKtcnmH9umNrY6U+xkuv18xf/hu373kQGxuLa+GCDOrVhSoVy2qcy+etH8079uH8X9vRN9Bn7aYd/Hn4BP4BgRRwcmR4/x7UqlZJnb/x913xeZt0IcMOrb9lwogBGmkqlYr+Iydx4coNFrtNpMFXNZLsl5H0a7VEt3hldKztIS6GeO8nxBzfhirQNyGDsSkGdduiW6g0CjNrVBGhxD+6QcypnRAdmamxii+PVisTnTp1okuXLrRs2ZKTJ08yevRoRo4cSWBgIAqFgpkzZ9KmTRtthvivlShbjNadW/DkQfb/sjU1NeH+vYds3vQHv29fpe1wMk21GpXZuHYb7rfvoaenx5iJQ/h9z6/UrdaCyIjse9Gd0GKUxqrV+V2dGPf7VK7+dVGLUYmMYmpmytw9c7l3+S5TukwhNCgE+wL2hP29iFtOkJOu51nVpNmL8Xz+ErdJI7G1tuLA0VP0HjKOP7euxsTYGI/Hz+jbrSNFC7sQ+uEDsxevZuDPU9m5bon6GANGT8HJ0Z7flszGyNCAzTv3MWD0ZA7vXId1otWwT52/QpUKZTAxMWbBit84ePQ0U34eTEHn/Fy8dpMhY6ezZfV8irsmLNa6fe1ijbWXnj5/Re+h42hcL+n09Jt37EORJDXz6BQoTtz1Y8S/eY5CRwf9Bh0w6jyWyOWjIDYaRW4LFLnNiTm2FeW71yjMbTD8tieGuS2I3rlIi5Frj8zmlHparUxMnToVY2NjLl++TO/evRkzZgxly5Zl9OjRRERE0Lx5888OwM5KjE2Mmb58EjNHzqXn0K7aDifDHT92luPHzmo7jEz3Y9u+Gs+H/jSee54XKFOuBFcv3dRSVBnvQ1CoxvMW/Vvz9qUvD6880FJEIiO16d+GAN8AFo9crE7z89bOwpLakNOu51lRVHQ0J85eYMnsyVQqVxqAAT1/5OzFq+zY+xeD+3Rl7eJZGvuMG96fjr2G4vvWH7t8tgS/D+GV9xumjRlK0cIFARjWrzvb9xzk6fNXGpWJ0+cvqysCB46cok/XDnxVowoAHb77livX3dmwbQ9zJo8GwNLCXOPcazfvJL+DHZXLl9ZIf/TkGRu372bHb0uo26JT+r1A/0L0ltnqf6tIWNDOdPQadOwLonz1CJX/a41KgyrYn5iTOzBsPQB0dEAps2SKlGl1cIGOjg7jxo3jwIEDjB07FoVCQYcOHfDy8iIgIID169djamqqzRD/lZ/dhnHx5GWunc++PyhFUnny5AbgfXDOWVxLV1+PWt/V4ezOk9oORWSQKo2q4nn3KT+vHMPmW1tYdGgxjTs20XZYmUau59oXHxdPfLwSQwN9jXRDQwNu3U3+JkZYWAQKhYLcuRN+O5ib5aGgkyP7j5wkIjKKuLh4dv55CEsLc0oULazeL/RDGLfuPqBerWoAxMTGaqyU/f/z3k7hvLGxsRw8dprvmjVGofjYBhEZFcXoqXMYP2KARsVF2xRGJgCoIlNuaVQYmSR0cZKKhPgMWbQunTRu2YBipV3p0rSPtkMRmUihUDDV7WeuXbnF44c5pytEpcZVMMljytk/stYqnCL95Mufj6Y/fsO+tfv4Y9lOipQtQp+pfYiLjeXUruz9vsv1PGswNTWhbKnirNqwDRdnJ6wszTl04ix37j/CycEuSf7o6BgWrlzHNw3rkOvvG5EKhYJfF89i8JjpVG3UGh0dBZbm5qxeMB2zv28EAZy/fB3XQgXVYy1qVq3Ipu17qFSuFPkd7Lhyw52TZy8Rr4xPNtaT5y7zISyMVt800kifu2QN5UqVoH7t6un1svx3CgUGX3ch3iuhRSJZJrnR/+o7Ym/m3BtGKunmlGpSmUgHee1tGTF9MAPaDycmOkbb4YhMNGveBIoWL8J3TTtrO5RMVa99Q+6cucV7/2BthyIyiEJHgeddTzbP3QTA8wfPcS7qTNNO32TryoRcz7MWt4kjmeS2kPqtfkRXV4firoVp2rAOHo81b97ExsUxYuIsVCoVE0cNVKerVCpmzl+BlYUZG1f8gpGhIbsPHGHg6ClsX7sEG+uE1oJT56+oWyUAxgzpy5Q5S2j+Qx8UCshvb0erZo3Ye/BYsnHuOXiUWtUqaQz8Pn3+Cldv3mHX+mXp+ZL8ZwbfdEfHNj9R66Ykn8HQGKMfRqN894bYM7szNTbxZZLKRDooVqYoVjaWbDm2Vp2mp6dH+Wplade9NTWcG2gM0hLZw4y542nYpA6tv+mKr0/O6Utu7WBDqVplWNh3rrZDERko2D8Y76deGmneT72p0bSmliLKHHI9z1qcHO3ZsPwXIiKjCA+PwMbakhET3XC0z6fO8/+KhI+fP+uWzFa3SgBcvenO2UvXuHRkpzq9RNGBXL5+mz8Pn6BX53bExsZy8eoNendpr97P0sKcJbMnER0dw/vQUGytrVi4cp3Gef/P560fV264s2jWBI30qzfd8X7jS/WvNSeSGTZ+JhXKlmTDssy/hhp80w1d1wpErZ+KKjQomQxGGP04BmIiid6xAFJoiREiMalMpIPr52/Qvm4XjbRJi8byytOLjcu2yhdPNjRj7ni+btaAts274e31RtvhZKo6besTEhjC7VM3tB2KyEAPb3jgUMhRI83BxQH/10mnwsxO5HqeNZkYG2FibERI6AcuXbvJ8J96AB8rEl7ePqxbOhtzszwa+0VFRQNJ15/SUSjU7+W1W3fJkzsXxYq4JDmvoaEBeW2siY2L4/iZizSp/1WSPHv/Oo6lhRlfVa+ikd6rczu+b/G1Rtp3nfszenAf6tas+i9fgf/O4Jtu6BarTNSG6ajev0uawdA4oSIRH0fUtnkQF5vpMWYlsmhd6kllIh1EhEfy7PELjbSoiCjeB4ckSc9OTE1NcCnkrH5eoEB+SpcpTnBQCK9ff3qxwS/ZrHkTadXmG3r8MIiwsAhsbK0B+BD6Qf3FlV0pFAq+aluf87vOoIyXH1XZ2Z9r/2Tu3l9oO6AtFw5ewLWcK01++JplY7JWl430llOv51nVxas3UalUFHByxOu1D/OX/0ZBJ0daNWtMbFwcw8fPxOOJJ8vnTkWpVBIQmHC33SxPbvT19Slbqjh5cudi3Iz59Ov+A0aGBuzaf4TXvn7qmZrOXLhK3URdnADuPniE37tAihVxwf9dICvWbUGlUtGjk2Yrg1KpZN9fx2nZtCF6eroa26ytLJMddG2X1ybZFo6MZNCsB3qlaxC1bT7ERKLIZQaAKioiodJgaIxR57Eo9A2J2j4fhaExGBon5AkPBflhLT5BKhMizcpXKM2hI9vUz93mJDTxbt2yi/59R2srrAzXtWcHAHb/tVEjfdhP49m5bZ8WIso8pWqVwcbRljMyi1O29/TuU2b1mUmXn7vSYUhH/Lz9+HXqr5zdd0bboYkc5ENYOItWrcfvXQBmeXLTqE4tBvftir6eHm98/Th94QoAbbppLhK3bukcqlQog4W5GavmT2fJmo30HDyGuLg4Chd0ZunsSeqWiNMXrzB97DCN/aNjYlj660Ze+7zFxNiY2tUr4zZxFHly59LId/n6bXz9/PmuWeMMfBX+O/3KCQPDjbtP0kiP3reSOPdz6NgVQNexCAAmQxZr5IlYNAjV+4DMCVR8kRSqbNiOU8ku6YIxOcGT0JzV3eb/chsYazsEraiTx1XbIWjFTt9r2g5BK5rmK6/tELTCNzbnTLmcmHvgc22HoBWRPucz9Xwejz3pOXgM5/7ajr6e9u6vxiwbr7Vza5PplG2fz6QlFexqaTuEFN3yvaDtEDRodZ0JIYQQQghtiY+PZ+yw/lqtSAjxpZNPjxBCCCFypNIlilK6RFFthyHEF00qE0IIIYQQQiSSDUcBZBjp5iSEEEIIIYRIE6lMCCGEEEIIIdJEujkJIYQQQgiRiBLp5pRa0jIhhBBCCCGESBOpTAghhBBCCCHSRLo5CSGEEEIIkYhKujmlmrRMCCGEEEIIIdJEKhNCCCGEEEKINJFuTkIIIYQQQiSilEXrUk1aJoQQQgghhBBpIpUJIYQQQgghRJpINychhBBCCCESkdmcUk9aJoQQQgghhBBpIpUJIYQQQgghRJpIZUIIIYQQQgiRJjJmQgghhBBCiERkatjUk5YJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiERkatjUk5YJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiERkNqfUy5aVidC4SG2HoBX5TCy1HYJWPA/x1XYIWuFj+kHbIYhMdDbQQ9shCJHhqpfuqu0QtOLyvY3aDkGINJNuTkIIIYQQQog0yZYtE0IIIYQQQqSVzOaUetIyIYQQQgghhEgTqUwIIYQQQggh0kS6OQkhhBBCCJGIzOaUetIyIYQQQgghhEgTqUwIIYQQQggh0kS6OQkhhBBCCJGIzOaUetIyIYQQQgghhEgTqUwIIYQQQggh0kS6OQkhhBBCCJGISqXUdghfDGmZEEIIIYQQQqSJVCaEEEIIIYQQaSLdnIQQQgghhEhEKbM5pZq0TAghhBBCCCHSRCoTQgghhBBCiDSRbk5CCCGEEEIkolJJN6fUkpYJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiERkNqfUk5YJIYQQQgghRJpIZUIIIYQQQgiRJtLNSQghhBBCiERkNqfUk5YJIYQQQgghRJpIZSIFnXq05dTN/dzzvsgfRzZQpnzJFPM2blaP3cc3ccPzNO4vz/Pn6a20bPuNRp4eP/3IZY9jXPY4Ro/+nTS2lalQkj0nNqOrq5shZfk3cmq5c6pWXVuw/fIWjnkeYsWBpRQrVzTFvF+3bcyZ1yc0Hsc8D2nkad+3LXvd/2Cv+x+069NGY1vx8sVYfWgFurpy2dGW3n06c8/jHP6BDzl1Zg8VK5ZJMW+x4kXYvHUF9zzOERr+nJ8GdE+Sp137lng8vsCr17eZNXu8xjYnJwduuZ8kd+5c6V6OfyunljunatvtO/Zf28nFFyfY8NdqSpYrnqr9GrdswA3f88xbP0sj/cd+HTh2bz/H7u2nU9/2GttKli/B5qNrM/V7LDw8gtmLVtGodVcq1mtJp77DuffwsXp7REQkM+evoEGrH6lYryUtOvVhx96/PnnM42cu0q7HYKo3aUPlBq34vusA9h85qZFn/e+7+KpZB75q1oEN23ZrbLv74BHtegwiLi4+/QoqvhjSzSkZ37RqxNhpw5g0yo07N+/TrW9Hftu5lCbVvycoIDhJ/vfBoaxauI7nT18SExtLvca1cVsyicCAIC6cvkLREoUZ8nM/+nYaikKhYPXWhVw4c4UnD5+hq6vLtHnjmDh8JvHx2v0Q5tRy51T1mtflp0n9WDB2MQ9vP6RNr+/5ZctsOtfpzvvA98nuExYaTpc63dTPEzcDuxQvSPeRXRnbdQIKhQK3jTO4fu4mLx69QFdXh+FuQ5n380Li45UZXDKRnNbfN2PW7HEMHTKRG9fd+WlAd/b8uZGK5RsS8C4wSX4TY2NevvRi395DuM2ZkGS7pZUFS5e70b/vKF6+8OaPPWs5d+YyR46cAmDBoulMnjSXDx/CMrxsn5JTy51TNWpRn2FTBuL283zu3/agY++2LN02n+9r/UBwCtc1ADvHfAyZ9BO3rrhrpBcuXoh+o3sytPPPKBQKFm6aw5Wz13n26Dm6urqMmzOCmaN+ydTvsUmzF+P5/CVuk0Zia23FgaOn6D1kHH9uXU1eG2vmLl3D1Zt3cJs0Gge7vFy6dpMZ85dja21FvdrVkj2mWZ7c9OnanoLO+dHX0+PspWtMnLUAKwtzalatyGPPFyxfu4Xlv0xBpVIxYNQUalSpgGuhgsTFxTPtl6VM/nkwenrZ5+agUro5pZrcIkxG936d2LllH3u2HeDZkxdMGulGVGQUbX5okWz+a5ducvzQGZ49fYn3yzdsWrOdxx6eVKxaDgCXIgV47PGUKxducPn8dR57eOJSpAAAvQZ25vrlW9xz98ik0qUsp5Y7p2rb53v+2naIIzuP8uqpFwvGLCIqKppvOnyd8k4qFUHvgtWP4ID36k1OhZx4/vAFty+5c+vibZ49fI5TofwAtO/XnjtX7/L4zuMUDiwy2sBBPdm4fgdbN+/i8SNPhg6eQGRkJJ27tE02/61bd5k4fja7dx0kOjomyfaCBfITGvqBPbv/4tatu5w7ewXXYoUAaNO2ObGxsRzYfzRDy5QaObXcOVWnvu3Zt/UAB3Yc4sWTl7iNnkdUZBQtOjZLcR8dHR1mLJ/EmnnrePPKV2NbgcJOPPV4xo2Lt7h+4SaeD59RoLATAJ1/6sitq3fwuPMoQ8uUWFR0NCfOXmD4gJ5UKlcaJ0d7BvT8ESdHe3Xrg/u9h7Rs2pAqFcrgYJeXti2/oWhhF43Wi3+qUqEMDevUpFABJ5wc7encrhWuhQpy684DAF688sa1UAGqVixHtUrlcS1ckBevXgMJLRYVy5WmdPGUW7ZF9iaViX/Q19ejZNliXDp7VZ2mUqm4dO4a5Sql3DSeWPXalSlYyJnrl28D8MTDkwKFnLBzyIu9Yz4KFHLi6cNn5C/gQOuOzVk0a2WGlOXfyKnlzqn09PUoWtqVm+dvqdNUKhU3z9+iRIUSKe5nbGrM9itb2Xntd2b8No0Crs7qbc8fvcDRxQFbe1vyOtiSv6AjLx6/xN7Zjqbtm/Db3PUZWiaRMn19fcqVL8Xp0xfVaSqVijOnL1KlSvk0HfPZs5cYGxtRpmwJLCzMqFCxDA/uP8LcPA8TJg5j5PAp6RP8f5BTy51T6enrUayMK1fP31SnqVQqrp2/QZmKKXfZ7TW8G0GBwfy5LWlXIM9Hz3FyyU9eB1vyOebFySU/zx6/wMHZnubtv2Hl7F8zpCwpiY+LJz5eiaGBvka6oaEBt+4m/PAvV7o4py9cwe9dQEL5b97hpdcbalSpkKpzqFQqrty4zUuv11QsVwqAIoUK8NL7Db5v/fF568cr7zcUdnHG67UP+w4dZ3DvLulbUPFFkW5O/2BhaY6enh4B74I00gP8g3ApXCDF/XLlNuX8vcMYGBigjI9nys9z1D/Mnz19yYKZK1i/awUA82cs59nTl2zYtZxfpi6hVv3qDBrVh7i4OGaMn8eNv3+MZ6acWu6cyszSDF09XYLeaXZfCw4Ixqlw/mT38XrmzZwR83j+8DmmeUxp37cty/YtoXuDnrzzDcDL04u1s9cxb9scAH6d/Rtenl7M3zaX1TPXUKVuJboN60JcXDxLJy/n7tV7GV5OkcDKygI9PT3e+QdopPv7B+DqWihNx3z/PpR+fUax+tf5GBsZsv33vZw8cZ5lK2azZvVmnAs4sv2PNejr6+E2cwl/7jucHkX5V3JquXMqc0sz9PT0CPrH91jQu2AKFHZOdp+yVUrTsmMzfmjUI9ntL5++YsXsNazYvhCA5W6refn0Fct3LGTJjJVUr1uVPiO7Excbx7xJS7h95U76FuofTE1NKFuqOKs2bMPF2QkrS3MOnTjLnfuPcHKwA2DcsP5MmbOEBq06o6eri0JHwZSfh1CpXOlPHvtDWDj1W/1IbEwsOro6TBgxQF0BKVTAiSF9u9F76DgAhvTtRqECTvQaMpbhP/Xg4rWbrPhtK3p6uowZ2u+z5/oSqGTRulSTykQ6CQ+LoGW9HzA1NaF67cqMnTYM75dvuHYp4Q7J9o272b7x44Cl79o3Izwsgts37nH08m6+b9yFfHa2LFwzi/oVWxAbE6utovwrObXcOZHHrYd43Hqofn7/xgM2nVlH807fsm7eBgD2bznI/i0H1XmatGlERHgED256sPnsBvp+OwAbO2smLR9Pxxqd5f3+wh08cIyDB46pn9esVYVSpYoxasQU3O+dpke3Ifj5veP02X1cvHgt2TEKX6KcWu7sxsTUmGlLJzBz1FxCgkJSzLd705/s3vSn+nmztl8TER7BvRv32X1hK12a9sHWzoZZK6fQomq7DL+uuU0cySS3hdRv9SO6ujoUdy1M04Z18HjsCcDWXfu5++ARy+ZMxi5fXm6632Pm/BXYWltRvXLKLXKmJsbs3rCciIhIrtx055elv+Job0eVCgm9E9p/14z2333sLvbnoeOYmBhTtlRxmnfszfa1i/HzD2DUpNkc3bUeAwODDH0dRNYhlYl/CA56T1xcHNY2lhrp1raWvPNP+QtBpVLh9SKh/+DD+08o5FqQvkO7qX9UJ2ZhacbAkb35oUUfylYoxctnXrx67s2r597o6+lRsJATTx4+S9+CfUZOLXdOFRIUQnxcPJY2FhrpFtYWBPknHWyfnPi4eJ7e98ShgH2y280s8tB1WBeGtBlG8fLF8X7xmjcv3vDmxRv09PVwdHHkxaMX/7ks4vMCA4OJi4vDxtZaI93W1ho/v3fpcg4DAwMWLJxGn94jcClUAD09XS5euAbAM88XVKpUliOHT6XLuVIrp5Y7p3ofFEJcXByW//ges7SxIDCZ7zHHAg44ONmzYONsdZqOTkLv7yvep/m+VifevPLR2MfM0ozeI7rT57uBlKpQAq/n3ni/eI33i9fo6esldIN69DwDSveRk6M9G5b/QkRkFOHhEdhYWzJiohuO9vmIio5m8eqNLHabSJ0aVQAoWrggj54+Z8O23Z+sTOjo6ODkmHA9L+ZaiOcvvVm7eYe6MpFY8PsQVq7/nQ3L53LvwWOc8zuoH3Hxcbz0foNroYIZ8wKILEfGTPxDbGwcD+48ovpXVdRpCoWC6rUr437jbqqPo9DRSbFWPm76CDas3oafrz+6ujro6X+s0+nq6WplqtScWu6cKi42jsf3nlCh1sc+tAqFgoq1yuNxK3WD4nV0dHApVpBA/6Bktw+Y0p8/1u7mnW8AOro66Okler91ddHVkctPZomNjcX99n3q1q2hTlMoFNSpW4Nr19Kne+Honwdw4sQ57rg/SPh86358v/X09bR0XcuZ5c6p4mLjeHT3CVVqVVSnKRQKKteqyN2bD5Lkf+npRfu6XejUsIf6ce7YRW5cvE2nhj3w8/FPss+IqYPYtmYn/r7vkr+uZeLU1ybGRthYWxIS+oFL125Sv3Y14uLiiIuLQ0eh0Mirq6uDUvnvZtJTqpTExCbfyjJnyRo6t2tFPlsb4pXxxMXFqbfFxytRZoNZ+1QqVZZ9ZDXSMpGM9au2MmfpFO67e3D31gO69v0BYxNjdm87AMDcZVPxe+vP/BnLAeg7pBv33B/i/fI1Bgb61GlYk5Ztv2HKaLckx65RpyoFCjkxeuBkAO7e9sClsDNfNaiBnX1elPFKnnu+yrzCJpJTy51T/bFmN2MXjubxncc8dH9Mm16tMTI24vCOIwCMXfQzAW8D+HX2bwB0GfojHrce8ualD7nymNKhXzvyOublr22Hkhy7Yu0KOLo44jZ0LgCP7zzGqXB+qtSrjK29LUqlEq/n3plXWMGypb+xas08bt++x40bd/hpQHdMTEzYsnkXAKt/nYePjx9TJ/8CJAxeLla8MAAGBvrY2eeldJnihIdF8Py55me1aLHCtP7+W2rV+BaAJ4+foVQq6dylHf5+73B1LcStm6m/KZGecmq5c6qtq3cwZfE4PO484oH7Q37o3RZjE2MObE+4Tk1dMh7/twEsn7WamOgYnj3WbB39EJIwpe8/0wGqflUJJ5f8TB48EwAP90c4F3amRv2q5LW3RamM59UzrwwuIVy8ehOVSkUBJ0e8Xvswf/lvFHRypFWzxujr6VGpfGnmL/8NQ0ND7PPZcuP2PfYfPsmowb3Vxxg7fR621lYM65+wjsqvm3ZQslgR8jvYERMby/nL1zl45BQTRg5Mcv5L127xyvsNsyaMAKBUcVdevHrN+cvXeev/Dh0dHQo4O2b46yCyDqlMJOPQvuNYWlkw+Od+2Nha8fD+E3q2H0Tg34O67BzzoVR9rHUbmxgzZe7P5LOzJSoqmudPXzLqp4kc2ndc47iGRoZMmj2aYb3HqmuWfr7+TB/3C25LJhETHcvPgyYTHRWdeYVNJKeWO6c6feAM5lZmdB/ZDUsbCzw9njG681j1dK95HWxRJbqTldssNyPnDsfSxoKwkDAe33vKgJZDePVU88vTwMiAITMGMa3/DPX7/c43gCUTlzFm/ihiYmJxGzqXmKik026KjLNn919YW1sybsIw8ua15t7dh3zfqpt6cLKjo73GnUs7O1suXv44u82QoX0YMrQP589doVnTHzSOvWTpLMaNmUlERCQAUVHR9O87mnkLp2JoaMDI4ZPx9fXLhFImlVPLnVMd338KCytz+o3uiZWNJU8eeDLoh5HqtZLyOeRFqfz3d3YNjQwYPXMYY/tNVl/X/H3f8cuERUxaOJbYmFgmD55FdCZc1z6EhbNo1Xr83gVglic3jerUYnDfruj/3Uoyb+oYFq3awJipcwkJ/YB9PlsG9+1K+1Yfxzv4+vlrtF5ERkUxY/5y/PwDMDQ0oKBzftwmjaJpwzoa546KjmbWghXMmzZW3SUsn60NY4f1Z8KshRjo6zNzwgiMDA0z/HUQWYdClRXbS/4jV5tK2g5BZKLnIb6fz5QN1bJN3aqu2c0F/4efz5QNmejLl3NOEhGbM2+ulLNy0XYIWnH53kZth6AV+tZZ9/22Mcu662a8C8laazZptWXC19eXlStXcuHCBXx9fRP6YLu40KpVK7p16yZ9TYUQQgghhMjCtDYC8saNGxQvXpxDhw4RGxvL06dPqVixIqampowcOZKvvvqKDx8+fPY40dHRhIaGajwSd8URQgghhBBCZAytVSaGDh3KsGHDuHHjBufPn2fDhg08efKE7du38/z5cyIiIpgwYcJnj+Pm5oaZmZnGIzjibSaUQAghhBBCZEfanrHpS5rNSWtjJkxMTLh//z4uLgn95ZRKJUZGRnh7e5M3b16OHz9Ot27dePPmzSePEx0dTXS0Zt/SCi510VHItJM5hYyZyFlkzITICWTMRM4iYyayHus8rtoOIUUBoU+0HYIGrY2ZsLW1xdfXV12Z8PPzIy4ujjx58gBQpEgRgoKSn78+MUNDQwz/MWuAVCSEEEIIIYTIeFr71d2qVSv69evHkSNHOH36NJ06daJOnToYGxsD8PjxYxwcHLQV3r/Ssdv37D+zjVvPz3Dr+Rl2HFrHVw1qfH7HL1xOLXdO1W14F868PqHx2HRmnbbDEhmkRs3K7PjjVx57XiY0/DnNvm2k7ZAyRU4tt0jQdWAnbvieZ/i0QZl63vDwCGYvWkWj1l2pWK8lnfoO597DjzP2BAQFM37GfOq16ESl+q3oO3wCr7w/9twICf3ArAUr+LZDLyrWa0nD1l2YtXAlH8LCk5zL560fFeu1JCIiEs/nrxg6bgaNv+9KqZpN2bxjb7Lxbdt9gMbfd6VCvRZ07D2Uex6aswlFR8cwY/5yajZtR+WG3zF03AwCgoI18ly5cZtOfYdTpWFr6jT/gQUrftNY7C6rUapUWfaR1WitMjFjxgxKlChB8+bNadCgAdHR0axb9/GHiUKhwM0t6eJnWdFbH3/mz1jGdw0707phF65cuMGKTfMpXDTrNt+lh5xa7pzsxaMXtC7fVv0Y9N1QbYckMoipqQn37z1kxLDJ2g4lU+XUcgsoUbYYrTu34MkDz0w/96TZi7l8/TZuk0ayd/NKalSpQO8h4/B7F4BKpWLImGm89nnLkjmT+GP9Muzz2dJryDgiIqMA8A8IxD8giJEDe7F380pmjh/Oxas3meS2MMm5Tp2/QpUKZTAxMSYyOgpH+3wM7d8dayuLZGM7fOIsc5euoX+PTvyxbilFCxek7/AJBAa/V+eZs2Q1Zy5eZcGMcWxYNpd3AYEMHTdDvf3R0+f0HzmJWlUrsmvDMuZNG8PpC1eZP39++r6QQiu01s0pV65c7Nixg6ioKOLi4siVK5fG9saNG2spsn/v9LHzGs8XzlpBx27fU65SaTwfP9dSVBkvp5Y7J4uPjyfoXfDnM4ov3vFjZzl+7Ky2w8h0ObXcOZ2xiTHTl09i5si59BzaNVPPrULFibMXWDJ7MpXKlQZgQM8fOXvxKjv2/kWLrxtw58Ej9m1eRWEXZwAmjhxI3eY/cOj4Gdq0+JoiLgVYNOvjpDVOjvYM7tOVMdPmEhcXj57ex6n2T5+/TON6tQEoXbwopYsnrKewaOX6ZOPbtGMvbZo35btmCb/LJo0axLlL19l78Bi9OrfjQ1g4ew4eY+6U0VStWA6A6eOH0+KHPty5/5CypYpz5OQ5XAsVpH+PTur4RvzUgxGTZjNgwIAkvwHFl0XrgwuMjIyy1R+Rjo4OzVo1xsTEmNvX72o7nEyTU8ud0zgUdGDXje38fnEz45eOxdbeVtshCSHEf/az2zAunrzMtfM3tXB2FfHxSgwN9DVSDQ0NuHX3ATGxsQAYJNquo6ODvoE+t+8+SPGoH8LCyWVqolGRCP0Qxq27D6hXq1qqIouNjcXj8VOqVS6nce5qlcpx537CZBgej58SFxdHtUrl1XlcnPNjl9eWO/cfqY9jaGDwj/IZEh0dzYMHKZdBm7Q9Y9OXNJuTVhety05cixdix+H1GBoaEBEeyYBuo3j25IW2w8pwObXcOZHH7YfMHvYL3s+9sbK1ouuwzizZs5DuDXoRGR6p7fCEECJNGrdsQLHSrnRp2kcr51egQ9lSxVm1YRsuzk5YWZpz6MRZ7tx/hJODHQX//mG+ePUGJo0ahImxEZt27MXPP4B3gclPVBP8PoTVG7bRpkVTjfTzl6/jWqggtjZWqYot+H0o8fFKrCw1u0BZWVrwwus1AAGBwejr65End65/5DEn4O+JdGpUqcDmnfs4dPwMTerXJiAomFXrfwfg3bt3qYpFZF1ab5nILl54vqJlvR9o26Qb2zbsYs7SKRRyLajtsDJcTi13TnTt9HXO/nWO5w9fcP3sDcZ0GUeuPLmo17yOtkMTQog0yWtvy4jpg5kwYDox0TFai8Nt4khQqajf6kcq1GvB1j/+pGnDOih0dNDX02PRrAm89HpDzabtqNSgFddu3aV2tUro6CT9GRcWHs5PoyZTqKATP/X8UWPbqfNXUt0qkZ5qVq3IiAE9mfbLUirUa8G3HXpRu3plgGTLIL4s0jKRTmJj4/B6kVBLf3D3EaXLlaBrn45MGjlLy5FlrJxabgFhoeG8fv4ahwJfxqxrQgjxT8XKFMXKxpItx9aq0/T09ChfrSzturemhnMDlEplhsfh5GjPhuW/EBEZRXh4BDbWloyY6IajfT4AShYrwu6Ny/kQFk5sbCyWFuZ07D2UksWKaBwnPDyCvsMnYmpizOJZE9HX+/gzLzY2lotXb9C7S/tUx2VhngddXR0C/zEzU2BQMNZ/t1ZYW1kQGxtH6IcwjdaJwKD3WFtaqp937dCaLu2/411AEHny5OKNrx+LVq3H0dEx9S9UJlKS9boTZVVSHcwgCh0dDAz1P58xm8mp5c6JjE2MsC9gR6B/oLZDEUKINLl+/gbt63ahU8Me6scD94cc2XOcTg17ZEpFIjETYyNsrC0JCf3ApWs3qV9bsxUhdy5TLC3MeeX9hgePnmq0MoSFh9Nn2Hj09fVYOmcyhoaaYxSu3bpLnty5KFYk9TMu6uvrU6JoEa7ecFenKZVKrt50p2yphIVTSxQtgp6enkaeF69e4+vnT9lSxTSOp1AosLWxwsjQkMPHz2BnZ0fJkiVTHY/ImqRlIh2MmDCAsycv4fv6Laa5TGj+/ddUrVmRHu0yd57qzJZTy51T9Z/Qh0snruD32g+rvFZ0H9EVZbySk/tOazs0kQFMTU1wKeSsfl6gQH5KlylOcFAIr1/7aDGyjJVTy51TRYRH8uyx5ji/qIgo3geHJEnPSBev3kSlUlHAyRGv1z7MX/4bBZ0cafX3DEpHT53HwtwMu7w2PH3+ktmLVlG/dnVqVq0I/F2RGDqeyOhoFk8aRXh4BOHhEQBYmJuhq6vLmQtXqfuPLk6xsbE8e+H197/j8HsXyKMnzzAxMcbJ0R6ALu2/Y/zM+ZQsVoRSJYqyZec+IqOiadUsYQ2W3LlMaf1tY+Yu/RWzPLkxNTVh1sKVlC1VXF3hAFi3dRe1qlVER6HDibMXWbvlDxYvXoyuri7iyyaViXRgaW3J3GVTsc1rzYfQMB57PKVHu0FcOntV26FlqJxa7pzKxs6GicvGkcciDyFBIdy7dp+fWgwiJChE26GJDFC+QmkOHdmmfu42J2Haya1bdtG/72hthZXhcmq5hXZ9CAtn0ar1+L0LwCxPbhrVqcXgvl3V3ZTeBQYxd+kaAoPeY2NlSYuvG9Cve0f1/h6Pn3H374XkvmnfU+PYR3dtwMEuL6cvXmH62GEa2/wDgmjTfaD6+YZtu9mwbTeVypdmw7K5ADRtWIfg9yEsW7uFgKAgihUpxKr509XdnAB+HtwXHR0dho6fQWxsLDWqVGTiyAEa57pw5Qa/btpOTEwsRQsXZOnsSdRv2DAdXr2MkRVnTcqqFKps+Gq52lTSdggiEz0P8dV2CFpRy7b45zNlQxf8H2o7BK0w0TfUdggiE0XERms7BK0oZ5UzFz29fG9jhh7f47EnPQeP4dxf2zXGUWibvnXWfb/zmGbd2ELDs9ZaXjJmQgghhBAiG4uPj2fssP5ZqiIhsg/5qxJCCCGEyMZKlyhK6RJFtR3GF0WZ/TruZBhpmRBCCCGEEEKkiVQmhBBCCCGEEGki3ZyEEEIIIYRIRCWL1qWatEwIIYQQQggh0kQqE0IIIYQQQog0kW5OQgghhBBCJCKzOaWetEwIIYQQQggh0kQqE0IIIYQQQog0kW5OQgghhBBCJKKSbk6pJi0TQgghhBBCiDSRyoQQQgghhBAiTaSbkxBCCCGEEInIonWpJy0TQgghhBBCiDSRyoQQQgghhBAiTaSbkxBCCCGEEInIbE6pJy0TQgghhBBCiDSRyoQQQgghhBAiTaSbkxBCCCGEEIlIN6fUk5YJIYQQQgghRJpIZUIIIYQQQohsavny5RQoUAAjIyOqVq3KtWvX0vX4UpkQQgghhBAiEVUWfvwbO3bsYPjw4UyePJlbt25RtmxZmjRpgr+//788UsqkMiGEEEIIIUQ2tGDBAnr37k337t0pUaIEq1atwsTEhHXr1qXbOaQyIYQQQgghxBciOjqa0NBQjUd0dHSSfDExMdy8eZOGDRuq03R0dGjYsCGXL19Ov4BUIt1ERUWpJk+erIqKitJ2KJlKyi3lzgmk3FLunEDKLeUWWd/kyZOT9H6aPHlyknxv3rxRAapLly5ppI8aNUpVpUqVdItHoVLJ3FfpJTQ0FDMzM0JCQsiTJ4+2w8k0Um4pd04g5ZZy5wRSbim3yPqio6OTtEQYGhpiaGiokebj44ODgwOXLl2ievXq6vTRo0dz9uxZrl69mi7xyDoTQgghhBBCfCGSqzgkx9raGl1dXfz8/DTS/fz8yJcvX7rFI2MmhBBCCCGEyGYMDAyoWLEiJ0+eVKcplUpOnjyp0VLxX0nLhBBCCCGEENnQ8OHD6dq1K5UqVaJKlSosWrSI8PBwunfvnm7nkMpEOjI0NGTy5MmpanrKTqTcUu6cQMot5c4JpNxSbpG9tG/fnnfv3jFp0iTevn1LuXLlOHLkCHnz5k23c8gAbCGEEEIIIUSayJgJIYQQQgghRJpIZUIIIYQQQgiRJlKZEEIIIYQQQqSJVCaEEEIIIYQQaSKViXS0fPlyChQogJGREVWrVuXatWvaDilDnTt3jubNm2Nvb49CoWDfvn3aDilTuLm5UblyZXLnzo2trS2tWrXi8ePH2g4rw61cuZIyZcqQJ08e8uTJQ/Xq1Tl8+LC2w8p0s2fPRqFQMHToUG2HkqGmTJmCQqHQeBQrVkzbYWWKN2/e8OOPP2JlZYWxsTGlS5fmxo0b2g4rQxUoUCDJ+61QKBgwYIC2Q8tQ8fHxTJw4kYIFC2JsbEyhQoWYPn06OWFumg8fPjB06FCcnZ0xNjamRo0aXL9+XdthiS+QVCbSyY4dOxg+fDiTJ0/m1q1blC1bliZNmuDv76/t0DJMeHg4ZcuWZfny5doOJVOdPXuWAQMGcOXKFY4fP05sbCyNGzcmPDxc26FlKEdHR2bPns3Nmze5ceMG9evXp2XLljx48EDboWWa69evs3r1asqUKaPtUDJFyZIl8fX1VT8uXLig7ZAyXHBwMDVr1kRfX5/Dhw/j4eHB/PnzsbCw0HZoGer69esa7/Xx48cBaNu2rZYjy1hz5sxh5cqVLFu2jIcPHzJnzhzmzp3L0qVLtR1ahuvVqxfHjx9n8+bN3Lt3j8aNG9OwYUPevHmj7dDEl0Yl0kWVKlVUAwYMUD+Pj49X2dvbq9zc3LQYVeYBVHv37tV2GFrh7++vAlRnz57VdiiZzsLCQrV27Vpth5EpPnz4oCpSpIjq+PHjqjp16qiGDBmi7ZAy1OTJk1Vly5bVdhiZ7ueff1bVqlVL22Fo3ZAhQ1SFChVSKZVKbYeSoZo1a6bq0aOHRlrr1q1VnTp10lJEmSMiIkKlq6urOnjwoEZ6hQoVVOPHj9dSVOJLJS0T6SAmJoabN2/SsGFDdZqOjg4NGzbk8uXLWoxMZIaQkBAALC0ttRxJ5omPj2f79u2Eh4dTvXp1bYeTKQYMGECzZs00PufZ3dOnT7G3t8fFxYVOnTrh5eWl7ZAy3P79+6lUqRJt27bF1taW8uXL8+uvv2o7rEwVExPDli1b6NGjBwqFQtvhZKgaNWpw8uRJnjx5AsCdO3e4cOECTZs21XJkGSsuLo74+HiMjIw00o2NjXNEC6RIX7ICdjoICAggPj4+yWqCefPm5dGjR1qKSmQGpVLJ0KFDqVmzJqVKldJ2OBnu3r17VK9enaioKHLlysXevXspUaKEtsPKcNu3b+fWrVs5qj9x1apV2bBhA0WLFsXX15epU6dSu3Zt7t+/T+7cubUdXoZ5/vw5K1euZPjw4YwbN47r168zePBgDAwM6Nq1q7bDyxT79u3j/fv3dOvWTduhZLgxY8YQGhpKsWLF0NXVJT4+npkzZ9KpUydth5ahcufOTfXq1Zk+fTrFixcnb968bNu2jcuXL1O4cGFthye+MFKZEOI/GDBgAPfv388xd3KKFi2Ku7s7ISEh7Nq1i65du3L27NlsXaHw9vZmyJAhHD9+PMldvOws8Z3ZMmXKULVqVZydndm5cyc9e/bUYmQZS6lUUqlSJWbNmgVA+fLluX//PqtWrcoxlYnffvuNpk2bYm9vr+1QMtzOnTvZunUrv//+OyVLlsTd3Z2hQ4dib2+f7d/vzZs306NHDxwcHNDV1aVChQp07NiRmzdvajs08YWRykQ6sLa2RldXFz8/P410Pz8/8uXLp6WoREYbOHAgBw8e5Ny5czg6Omo7nExhYGCgvmtVsWJFrl+/zuLFi1m9erWWI8s4N2/exN/fnwoVKqjT4uPjOXfuHMuWLSM6OhpdXV0tRpg5zM3NcXV1xdPTU9uhZCg7O7sklePixYuze/duLUWUuV69esWJEyfYs2ePtkPJFKNGjWLMmDF06NABgNKlS/Pq1Svc3NyyfWWiUKFCnD17lvDwcEJDQ7Gzs6N9+/a4uLhoOzTxhZExE+nAwMCAihUrcvLkSXWaUqnk5MmTOaY/eU6iUqkYOHAge/fu5dSpUxQsWFDbIWmNUqkkOjpa22FkqAYNGnDv3j3c3d3Vj0qVKtGpUyfc3d1zREUCICwsjGfPnmFnZ6ftUDJUzZo1k0z1/OTJE5ydnbUUUeZav349tra2NGvWTNuhZIqIiAh0dDR/Cunq6qJUKrUUUeYzNTXFzs6O4OBgjh49SsuWLbUdkvjCSMtEOhk+fDhdu3alUqVKVKlShUWLFhEeHk737t21HVqGCQsL07hL+eLFC9zd3bG0tMTJyUmLkWWsAQMG8Pvvv/Pnn3+SO3du3r59C4CZmRnGxsZaji7jjB07lqZNm+Lk5MSHDx/4/fffOXPmDEePHtV2aBkqd+7cScbDmJqaYmVlla3HyYwcOZLmzZvj7OyMj48PkydPRldXl44dO2o7tAw1bNgwatSowaxZs2jXrh3Xrl1jzZo1rFmzRtuhZTilUsn69evp2rUreno54+dB8+bNmTlzJk5OTpQsWZLbt2+zYMECevTooe3QMtzRo0dRqVQULVoUT09PRo0aRbFixbL17xaRQbQ9nVR2snTpUpWTk5PKwMBAVaVKFdWVK1e0HVKGOn36tApI8ujatau2Q8tQyZUZUK1fv17boWWoHj16qJydnVUGBgYqGxsbVYMGDVTHjh3TdlhakROmhm3fvr3Kzs5OZWBgoHJwcFC1b99e5enpqe2wMsWBAwdUpUqVUhkaGqqKFSumWrNmjbZDyhRHjx5VAarHjx9rO5RMExoaqhoyZIjKyclJZWRkpHJxcVGNHz9eFR0dre3QMtyOHTtULi4uKgMDA1W+fPlUAwYMUL1//17bYYkvkEKlygHLPAohhBBCCCHSnYyZEEIIIYQQQqSJVCaEEEIIIYQQaSKVCSGEEEIIIUSaSGVCCCGEEEIIkSZSmRBCCCGEEEKkiVQmhBBCCCGEEGkilQkhhBBCCCFEmkhlQgghhBBCCJEmUpkQQogsplu3brRq1Ur9vG7dugwdOjTT4zhz5gwKhYL3799n+rmFEEJ8GaQyIYQQqdStWzcUCgUKhQIDAwMKFy7MtGnTiIuLy9Dz7tmzh+nTp6cqr1QAhBBCZCY9bQcghBBfkq+//pr169cTHR3NoUOHGDBgAPr6+owdO1YjX0xMDAYGBulyTktLy3Q5jhBCCJHepGVCCCH+BUNDQ/Lly4ezszP9+/enYcOG7N+/X901aebMmdjb21O0aFEAvL29adeuHebm5lhaWtKyZUtevnypPl58fDzDhw/H3NwcKysrRo8ejUql0jjnP7s5RUdH8/PPP5M/f34MDQ0pXLgwv/32Gy9fvqRevXoAWFhYoFAo6NatGwBKpRI3NzcKFiyIsbExZcuWZdeuXRrnOXToEK6urhgbG1OvXj2NOIUQQojkSGVCCCH+A2NjY2JiYgA4efIkjx8/5vjx4xw8eJDY2FiaNGlC7ty5OX/+PBcvXiRXrlx8/fXX6n3mz5/Phg0bWLduHRcuXCAoKIi9e/d+8pxdunRh27ZtLFmyhIcPH7J69Wpy5cpF/vz52b17NwCPHz/G19eXxYsXA+Dm5samTZtYtWoVDx48YNiwYfz444+cPXsWSKj0tG7dmubNm+Pu7k6vXr0YM2ZMRr1sQgghsgnp5iSEEGmgUqk4efIkR48eZdCgQbx79w5TU1PWrl2r7t60ZcsWlEola9euRaFQALB+/XrMzc05c+YMjRs3ZtGiRYwdO5bWrVsDsGrVKo4ePZrieZ88ecLOnTs5fvw4DRs2BMDFxUW9/f9domxtbTE3NwcSWjJmzZrFiRMnqF69unqfCxcusHr1aurUqcPKlSspVKgQ8+fPB6Bo0aLcu3ePOXPmpOOrJoQQIruRyoQQQvwLBw8eJFeuXMTGxqJUKvnhhx+YMmUKAwYMoHTp0hrjJO7cuYOnpye5c+fWOEZUVBTPnj0jJCQEX19fqlb9X3t3E0rdFsdx/CtyeoiRlzh1UAaOkrzUkwkZKDORmaRISSKhTAykMDc4hs6AotRJztzLhAGZIaRkZnpIwr2j59yr5+E+dhnce7+f4Vr/vfbaa7Dr19qr/T3dl5WVRWNj40+fOv1wcnJCZmYmLS0tvz3ny8tLHh4eaGtre9P+9PREXV0dAKenp2/mAaSDhyRJ7zFMSNIntLa2EovFyM7OprS0lKysv16jubm5b2pTqRQNDQ2srq7+NE5hYWGg+3/79u3T16RSKQCSySThcPhNXygUCjQPSZLAMCFJn5Kbm0tlZeVv1dbX17O+vk5RURH5+fm/rCkpKeHw8JDm5mYAnp+fOTo6or6+/pf1NTU1vL6+sru7m/7M6e9+7Iy8vLyk26qrqwmFQtzc3Ly7oxGNRtna2nrTdnBw8M8PKUn6X/MAtiR9kZ6eHgoKCujo6GB/f5/r62t2dnYYHR3l9vYWgLGxMRYXF0kkEpydnTE8PPzhPyLKy8vp6+ujv7+fRCKRHnNjYwOAsrIyMjIy2N7e5u7ujlQqRV5eHpOTk4yPjxOPx7m6uuL4+JilpSXi8TgAQ0NDXFxcMDU1xfn5OWtra6ysrHz1EkmS/uUME5L0RXJyctjb2yMSidDV1UU0GmVgYIDHx8f0TsXExAS9vb309fXR1NREXl4enZ2dH44bi8Xo7u5meHiYqqoqBgcHub+/ByAcDjM7O8v09DTFxcWMjIwAMDc3x8zMDAsLC0SjUdrb20kmk1RUVAAQiUTY3NwkkUhQW1vL8vIy8/PzX7g6kqT/gow/3jvlJ0mSJEkfcGdCkiRJUiCGCUmSJEmBGCYkSZIkBWKYkCRJkhSIYUKSJElSIIYJSZIkSYEYJiRJkiQFYpiQJEmSFIhhQpIkSVIghglJkiRJgRgmJEmSJAXyJzcRFn0oN8sUAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1138,7 +1123,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1347,7 +1332,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 24, "metadata": { "tags": [] }, @@ -1390,7 +1375,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -1439,12 +1424,12 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1454,7 +1439,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1514,14 +1499,14 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 27, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1531,7 +1516,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1594,12 +1579,12 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 28, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1609,7 +1594,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1619,7 +1604,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1629,7 +1614,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1769,7 +1754,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -1790,12 +1775,12 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 30, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1805,7 +1790,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1815,7 +1800,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1825,7 +1810,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1835,7 +1820,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1845,7 +1830,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1855,7 +1840,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1865,7 +1850,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1910,7 +1895,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -2051,11 +2036,11 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ - "from tqdm.notebook import tqdm\n", + "from tqdm import tqdm\n", "\n", "def train_denoising_model(train_loader, model, criterion, optimizer, history):\n", " \n", @@ -2107,7 +2092,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -2150,78 +2135,19 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 37, "metadata": {}, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "8e2d8fdf6e024991b23e573e22ebce68", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/937 [00:00" ] @@ -2285,7 +2211,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 39, "metadata": {}, "outputs": [], "source": [ @@ -2299,12 +2225,12 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2314,7 +2240,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2324,7 +2250,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2334,7 +2260,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2344,7 +2270,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2354,7 +2280,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2364,7 +2290,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2374,7 +2300,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAU1UlEQVR4nO2daYxURReGC0FRh11kGZRNkN2FTTYRMC4QATcUCSpGcCNG8Q9GMTHRRI0hGiAqomhCFAkgIEYWoyMoo0R2RNZRBlBEZJVNRPl+fPnuV+dp6DuX6R5mpt7nV72pnu7q25cu+pxT76lw8uTJk04IIUSwnHO2FyCEEOLsoo1ACCECRxuBEEIEjjYCIYQIHG0EQggRONoIhBAicLQRCCFE4GgjEEKIwKlU1AdWqFAhm+sQGSYb5wRbtWpldM+ePdM+/rfffovGW7ZsMXP9+/c3esmSJUYPHDjQ6HHjxhk9ePBgo0+cOBGNf//9dzN3/vnnGz19+nSjr7nmGqN79epl9OrVq432r8OGDRvMXGFhYdrXXr9+vdHt27c3+siRI0bn5uZG402bNpm5Cy64wOjGjRsbPWXKFJcNqlSpYvS///6b9vHpvjs4V5LnW/na1Hxf6d4n1x33fZn0+zTd4885x/5/nms5dOhQ7PPrF4EQQgSONgIhhAgcbQRCCBE4FYpqOqccQdkiG7HWJk2aGN2xY0ejDx8+bPQvv/wSjdu0aWPmpk6davSAAQOMrl+/vtF+DsA555YvX2509erVo/H+/fu5dMMff/xhdPfu3Y1mnD5dTDwnJ8fM/fjjj0b7MX7+rXPO7dq1y2jG/StV+n8aLz8/38xdfPHFaV+LeZdMwTUSxqx9kn6PJL2P/cfzb6krVqyYaG3+Z+Gcc3///fcZrzOOdLmTuNwGUY5ACCFELNoIhBAicLQRCCFE4ASXI7j88suN/uKLL4xeu3at0f369cv6mrJBNnIEnTp1Mnr37t1G81xBuhgq8w3NmjUzuqCgwOiffvrJaNbn+/Fb5g+Yb2Cst2vXrkZv3brV6Llz5xr90ksvRePXX3/dzNWsWdPoatWqGT1v3jyjX375ZaM//vhjo/08wHnnnWfmZs6cafS9995r9OTJk102YI4gro49yXdH3GPj7ut08+eee67R/C649tprjfZzXM6lnifZu3dvNGZeqTi5jVNRnO9f5u5OhX4RCCFE4GgjEEKIwNFGIIQQgVNkr6HywqRJk4xm7fXIkSNLcjllCtbbM97N2PH27dujMX1wVqxYYfTs2bONZsy0adOmRnfp0sXo999/PxrzHEHbtm2N7tOnj9FLly41mvmHQYMGGT1nzpzTrvPo0aNGjxo1yuiDBw8a/c477xhdu3Zto/1zCZxjTNv3dipJipOPKm5OIM7nyKdly5ZGjx071uhatWoZ/dZbbxnNHIMPzyT8888/adcSl0eJOwORjjPJJ+gXgRBCBI42AiGECJxyHxq65557jKYtwosvvmj0J598kvU1lVX++usvo48fP260HwpyzrmGDRtGY5Z/shTyscceMzovL89olvX++uuvRvtllixj/fbbb43mPJ+L74sloH7Jcbt27cwcw1IsD2X4hmGoyy67zGi/xJGW1wxV0IajtJDOHiGphXWS0tRGjRoZ/eyzzxrNUNGnn35qNL8LGNbzy6OT2j4kDf2ku4aZQL8IhBAicLQRCCFE4GgjEEKIwCl3OQI/Lu1cqgXAsmXLjH7ttdeyvaRyw8KFC41mCSctlffs2RONGXc/duyY0QsWLDC6efPmRrO0jzkDv7SS+QjmH2gr8ueffxpN2+l169YZ7cfimTdp0KCB0WyD+fXXXxvNHAPzGfXq1YvGtBOuWrWq0bxGJUVc3L84rSrjYucs06xRo0Y0HjFihJljC1K2/uR3AVueci2+tUY66+1T/W1SkuQFzuS19ItACCECRxuBEEIEjjYCIYQInHKXIxg/frzRPJb/xhtvGB3X1lD8n/79+xtNy2W2gPRj1rSfOHDggNFr1qwxmrmeSy+91GjmCPznpxUGY9aM4zPOz9gw22z69fu0edixY4fRvCY8J7Bt27a0a/UthNmakvbZbJOZLeLi1Ulr6tMRF+9mbL5Vq1bRePDgwWaOnzO/CzZu3Gg0100biSTrTHoeIsl5iUxYzusXgRBCBI42AiGECBxtBEIIETjlIkfQt2/faHzjjTeauZUrVxrNGnJRdFjHznp91sT7rfwYx2QsnK0q169fb3R+fn7a12rRokU0Zpyenzk9aLiWDh06GM17qHPnztF40aJFZo61/fRf4vkItkMcPny40X6bTLZNffXVV42md062SBqT9q9vXFvLpK994YUXGj1s2LBoXLduXTM3Y8YMoz/77DOj2cKU90W6tRb3PESSnEHSHE1R0C8CIYQIHG0EQggRONoIhBAicMpFjuDxxx+PxvS0GT16tNGs6xZFhzFU1uOvWrXKaP8sAOv+6cHD1pV16tQxmvX69I734/aM8X/33XdGM05NX3/mJ1j7X1hYGI0Zo+Z5h82bNxvte9g7l5rrmDZt2mnXNn/+fDPHa8g2mdkiaVzfj1knjZUTflZ+vwbnbL7wyJEjZu6jjz4ymt8F7A2RDd///xGXE0jn15SJcwNEvwiEECJwtBEIIUTgaCMQQojAKZM5gjFjxhh98803R+NJkyaZOZ0byBzst8u4Jr1cfB8dP3brXGpsnbX6vseOc859+eWXRrPPhB9bp6/RddddZzT7JjBWvHr1aqPZ09j3MmIvA/oB0fP++++/N/rWW281mtfFz7t069bNzLE/RFz/30yRzdh5XD0++w8MGTLEaP/sAPNSzEOxb3YSf59TPT4JSb2FlCMQQgiRVbQRCCFE4GgjEEKIwCkTOQLWfffs2dNo/+wA/VdE5mjatKnRu3fvNpr9Cfy6bPbiZTyb5wQIa+QZ//XzEfTlZ38Besz4PkXOpdaqMzfix6mZE+BrM19Rv359oxm3HjBggNFLly6Nxsw3+F5OzqX2kM4WSeLZmYZ9mekt5n82PD+yb98+o5OuO0ncPi4HEPfc2cgDpEO/CIQQInC0EQghROCUidDQU089ZfT1119v9NNPPx2Nt2zZUiJrCpHp06cbXa1aNaNr1KhhtG/NQOtnhpEYOvJbDjqXGq7hT+cnn3wyGq9bt87MzZw502jaEvTq1cvoH374waXDt43gOhiGuv32242eOHGi0bwuBQUFRvuWFLzeffr0MZqlrGeLpGWY6WB7yPbt2xvNVrR+uPLzzz83cwwvsnw06Tr9xzN8HWcZkcTiuijzxUW/CIQQInC0EQghROBoIxBCiMApEzmCO++802ge+WfsWmSHESNGGL1161ajWc7ol4+eOHHCzO3cudNoxu39sknnnLvllluMZpvMjRs3RmO2bGT5J20JaGndqVOn0z63c87l5uZG43r16pk55ghYYktLCZbBsnWl/1pse8l8AktTS4pMlovyuZgjoF0IraN9C49vvvkm7XMzrh+3FuoqVapEY5YJ026F1hi0yKY9eZJ1ZQL9IhBCiMDRRiCEEIGjjUAIIQKnVOYIaGVw9dVXG812foxVi+ywePFioxkHpYWynxdgfPuiiy4ymsf//TaXzqXGWK+66iqjfetonhvgc82ePdtoWpYsWLDAaOYc/NgwW1FWrVrV6Llz5xpNSwrGlplz2L9/fzTOyckxc82aNTOaNfXZIq5mPpP2zLyn2J6T9fizZs2KxszP8FontYXwP3fnbL6C7UyZA1uyZInRzBHwmvJ+99eW1MK6KOgXgRBCBI42AiGECBxtBEIIETilMkfAeFmlSmdvmZ07dzb6zTffjMaMGTJXMWjQIKMPHjyY2cWVMH5LUOdSfZ0YS/fj9h06dDBzixYtMpox0zZt2hjNlqOMDfv1+PwcGjRoYHTv3r2Npl3xJZdcYjRzVn7cms/NtpcPPPCA0cuXLzea5yv8GLdzNhfC+HheXp7RJXV/ZdKGOi6fUKdOHaMbN25sNO8b/z6J8/uJWze/d5o0aWJ0x44dozG/Jxjjp836hAkTjI7zSPPXrlaVQgghMo42AiGECBxtBEIIETilMkcQB1v2ZZKpU6cazdaBfkySMUXWdbOG/KabbjL62LFjZ7zOs8GyZcuMZnyW2o+XMwbKumvGghk7X79+vdH33Xef0b6vP+PIrPXn+2A+grXrzFn53kVxbS0J3yef2z834Jx9L7wGhYWFRmezRWRJQc8d5md4zmLNmjVG+y1Li9uKkp8t4/75+fnR+OeffzZz9M7q0aOH0UOHDjWaOYNdu3addp3KEQghhMg42giEECJwtBEIIUTglMkcAev3iwPjyYzl9evXz2i//p09T6dMmWI0zxGMHDnS6LFjxyZa69mGvXx5bfwzFs7ZnEn16tXNHHsUM7/CWPArr7xidLdu3Yz268cZd2cPgMmTJxvdvHlzoxkLZi7H98BnbTr98VlfzlwJe2vwOh04cCAaswcDPbiYV8kWSevzkzwXoTcT3yOv36FDh6Jx5cqVzVxcbJ3vg/cBczK+5vuglxbviyuuuMJonlHYs2eP0f7auS5yJjkE/SIQQojA0UYghBCBo41ACCECp1TmCNj3lbFRxt7Hjx8fjdnzNQ7mBCZOnGg0PXF8jh8/bvTdd99t9F133WU0ey+XtRwBPXgYa2/RooXRAwcOjMYLFy40c4yJMhbMuDyvHfsn+70RGOtlLoeeSYz91q1b12jWtvvPv2PHDjNXq1Yto9kPuXXr1kavWrXKaPZH9r2GunTpYuaqVatmNM9HZIukMWg/fh73t5znZ0mYM/CvP++huNdm7J39Nqj9tTFHwHXNmTPH6MGDBxvN3BDft+97xPuZr5Wk//H/0C8CIYQIHG0EQggROKUyNEQ73Q8++MDo5557zugXXnghGj/zzDNmLu7I//Tp089kiUWCP0WzcTS8JOFPbf58ZejCL+WjvQZDIAzBsRXlHXfcYfQNN9xgtG81wJJC2kyz7JWfS8WKFY2mLYT//Awj0Z7i8OHDRq9YscLoYcOGGf3VV18Z7YcB2AaTlhN8rWxRHBvquMfS1oFWC7TgaNu2rdFdu3aNxvPnzz/tOpyLb11J0r0vhmd4DzFkWKNGDaP79OljNMPO/nVh+Jv2FnHhtFOhXwRCCBE42giEECJwtBEIIUTglMocAfFzAM6lWgL4cVa28xszZozR8+bNM7o4VtCMAz744INpH//hhx+e8WuVBmity3g420n69grM1bCl4/Dhw9O+NmPr69atM9ovJ2V5He8f/i1LV2kDwVi8b43MWC5tkwsKCoy+//77jaYtCdfit8LMzc01cxs2bDCaNgbZIs4WIl2sPe5v+R6Y96DNCS3Ex40bF42ZG5o2bZrRzFMxt8TvBpaX+vc/PxvmsIYMGWI0W5zyPklXIurn3pxLzQnIYkIIIURitBEIIUTgaCMQQojAqXCyiAGl0twGb9SoUdF49OjRZo4xV8aHGYPcuXOn0Xl5eUa3a9cuGtMGuH379kYznunXODuX2toxk2TjzELfvn2NZk038wAdOnSIxnv37jVzPK7PWv2aNWsazdg7a6l922r+be3atY3eunWr0bxHWLvOevScnJxoXL9+fTNHKwzeT8w30I6ba/NtJBg/Z5yZz8368kzB+vs4fFvwuDMbvpWCc6mfHc+A0C7EzxHSgoP5nN27dxvN+5f3GO8LP0dAW2l+Nnzt2bNnG/3uu+8azXyF/++FFhL8buY1Lsr5Ev0iEEKIwNFGIIQQgaONQAghAqdc5Ah86OHx0EMPGU3Pmo4dOxodF2/zYex4xowZRr/33ntp15pNspEjGDp0qNF+G0XnUtvz+fbOjHmyRSjzDazZZn6F3i7+Wnr37m3m/Npy51L9fZivYHtJ5n58u/EnnnjCzNEynXFn1v7zOjRs2NDomTNnRmPafPP6MyfFnEGm4PmRJMR9j8R5D/Hfd6NGjYz2zxjxPuDnSCt0wtdmnN+/v/nvjfkF5gRoT858Be/vdFbevGZs1aocgRBCiFi0EQghROBoIxBCiMApdzkC8V+ykSNge0jGQdmPYNu2baccO5daf895toBkG1A+3u9HQE8k1vJXqVLFaLZG5b3OMw5+vwzGdnk2hDFs5iPizpr4Zwd4joAeM1z3rFmzXDbgOYKkcX+fpPcpzxlUrlzZaMbxfeJ6AhDG2uk95H/W+/btM3Os9S9ub5Ik3798rHIEQgghYtFGIIQQgaONQAghAqdM9CMQpQPGSBnfZgzWr3NnD2LGUPlcjAWzHwHjtw8//HA0zs/PN3P0rF+wYIHRt912m9FxZxr8WnV65fB9MEfA52K9eP/+/Y1+++23T/m6zqX68GTr3ADJZk4g7rl5vXgf8b7wod8Ve2Lws+Fa0z13XA4gLp9ztnOw+kUghBCBo41ACCECRxuBEEIEjs4RlFOycY6A/RdYj888wOLFi6Mxa/HpV8P8Q/fu3Y1eu3at0XXr1jV68+bN0bhly5ZmjucIjh49ajRr+xkL5uP9uuyVK1eauUcffdRo5hD8dTqX6mfDtfhnB5g3YY9o9ovIVo/spF5D6XxySpKktfxxHj7+38f5/8Q9d5K1Jc0v6ByBEEKIWLQRCCFE4Kh8VBQZhlhoKcFQhH/8Pzc318xt2rTJaJZ4Tp061egrr7zS6IKCAqP9n78sKWSZIG0hOnXqZHTbtm2NnjNnjtG9evWKxrS64DXwWyeeam3dunUzeunSpUb7lgm8hgy38bnPFunCHElDzElDLkn+trhrKc5zFzdMlWn0i0AIIQJHG4EQQgSONgIhhAgclY+WU7JRpufHxp1LLSNMZ//MI/a0XmBpJKEtBNtJLlmyJBqzzLVq1apG5+XlGZ2Tk2N0zZo1jabt8qFDh6Ixy0NZ1tquXTujN27caDTti9na0m99yfe1a9cuo1u1amV0SZWPZvO7IZN2zSVZulrca5JkrSofFUIIUWy0EQghROBoIxBCiMDROQJRZFgTv3DhQqNp4+vbOfOcAGvgJ0yYYHTr1q2N5vH+7du3G+23zRw5cqSZe/75541+5JFHjGYM1c83OJdqLe3nJ9iuk7YbhYWFRvP8BK9Djx49jPZzCnxss2bNjPZtv0uSJLX+nGPuKGk9fXFaOBbH5oF/X9z8Q5L3kc4O27nUa1qk50z8F0IIIcoV2giEECJwtBEIIUTgFPkcgRBCiPKJfhEIIUTgaCMQQojA0UYghBCBo41ACCECRxuBEEIEjjYCIYQIHG0EQggRONoIhBAicLQRCCFE4PwH0r3TyQ+87SUAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -2462,7 +2388,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -2491,14 +2417,14 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 42, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAXx0lEQVR4nO2dV4xV1RfGN39FsYuKKFUGEESqSBHpijAELGBQ1IAgGtGgiSE8GY0xUQH1wURelNgRIwhKpEgzgPQOAgICUgQRURB7+7/drPWb4Zx7mLmjsL/f0/my555297l7zrfWXrvSP//8808QQggRLf/7t09ACCHEv4sGAiGEiBwNBEIIETkaCIQQInI0EAghRORoIBBCiMjRQCCEEJGjgUAIISLn9Hz/sFKlSoU8D1HOFGKeYM+ePZ2uU6eO0wcOHHD6p59+ym1fdNFFri2tP1WuXNnpiy++2OmpU6c63b1799z2N99849ouuOACp5s2ber0xo0bna5WrZrTy5Ytc/rGG2/MbX/xxReurVatWk6z/ZprrnF627ZtTrdu3drpyZMnH/eze/bscbpevXpOjxs3LhSCM8880+m//vrLafa9LL8d/Nu0flyR82HLcl1plGVf//uf/3+e3wd1qfs44aMLIYQ4JdBAIIQQkaOBQAghIqdSvkXnFCM4uSiEd1pcXOz0n3/+6XRRUZHTts/8/PPPru2XX35x+ttvv3W6SpUqTjds2NDpJN/zvPPOc/r33393+rvvvnP6t99+c/qPP/5w+oorrnB69+7duW1eF+MTzZs3d/qyyy5zes6cOU537drVaRtnYWzjhx9+cPrQoUNOv/jii6EQnHbaaU5n8c5Ppt+RsjxDWa8z7R7adralHYv9uTT0RiCEEJGjgUAIISJHA4EQQkRO3vMIhGAuP+cN/Pjjj07T57d069bN6UmTJjndv39/p2fMmOE0c6d37tyZ2+7Tp0/ieXH+w6+//uo0ff/TT/ePyd9//53bZm7/kSNHnOZ8iLPPPtvpNm3aOG2vIwQ//2L79u2J533OOeeEiiDNo07yuwuZi59G1mOX5dzSPlue51Ie8UC9EQghRORoIBBCiMjRQCCEEJFzyscIstYuYQ56x44dnaZXnXQs5lsz7z4LWT3HQsDc/S5duji9aNEipw8ePJjb7tu3r2tbs2aN02eccYbTs2bNctrm7ocQwuWXX+50s2bNjvtZ5t9bjz+EELZu3er0999/7/SFF17o9Ndff53b5rwA+vb8LOMV/DznBlSvXj23zdpCGzZscHrkyJHhv0hSDnxWrzytn2eJR5Q1PmH7EffFPlZIyiPuojcCIYSIHA0EQggROad8iQnaM7Q3GjRo4PSwYcOcZimE+fPn57ZpAyxfvjzTufGeMiXStqfZSuVpQx2PO++802m+/l5yySVO165dO7c9d+5c18bUUpa4tvc5BF9qIYQQLr30UqdtqWlr3ZTGueee6zTLVzBddN++fU7XqFEjt71lyxbXxmOzdAaPTc2y1WeddVZuu1OnTq6N5aBZOmPChAmhELCvpdkitj2rNZTFCkoj7XlLev5CKPlM2evk7wr3lXYu5Wntcl/52FR6IxBCiMjRQCCEEJGjgUAIISLnlE8fTYsR2CUOQ/DLEIYQwt69e522vizLBfTo0cPpV1991WmWKKaXl1RamV4yfT+WRSgE9M65pOO8efOcbtWqVW77yiuvdG3t27d3+tNPP3WapXOPHj2a2G59+/PPP9+1scw0r4PpooxH8F7bpS1ZdoMlItq1a+c040r8PLW9x1dddZVrY/+ZPXt2+DfI4m/zXmb10rOcS9bPpsU+WMLD9iv2x7QYHe9Z2n2wf1+IVHG9EQghRORoIBBCiMjRQCCEEJFzyscIuEwhYRlgLktI39B6eSxlYD3xEEIYM2aM0ytXrnSaJQI2b97sdNu2bY97nosXL3Z6yZIlodDQI/3qq6+ctj59CCHUrVs3t81rff31151mDIHlmxl/mTZt2nH/3pZuDqFkuWzum769Pe8QSvq/dm4JYxeMffC61q9fH5Jgf7OlNxi7YGkMziMoFGUp3VDWmAA/z3NJihHws7Z8RwghtG7d2unGjRs7zTjc2rVrc9uMDbGUCONUaTECtts+yDhL1rhLaeiNQAghIkcDgRBCRI4GAiGEiJxTLkaQVsODXvO1117rNL09+uLW86X/u2LFCqe5tCDnAlx33XVO9+vXz2nrC3LfrIlED7IQ8N4yX5/5+XbeBP+WSzym1UrasWOH08OHD3fazkNIm3NAb9jW8wmhZGno++67z+lnnnkmt01/lrWFGBc6duyY07wO/r0tt805LfzOed6FopBLPGb1zpPiE2xjifmBAwc6XVxc7DRjTdu2bXO6Vq1aue1Vq1Yl/i3nELHWFuNr7P+2DLst7x6ClqoUQghRDmggEEKIyNFAIIQQkXNSrkeQ5Vx4eUuXLnWa8wbSjmW9u7Q5CsxPp5+8evVqpxlTsMfq1auXaysqKnK6Zs2aTheiHgnzrJs3b+70kSNHnL7lllty25s2bUrcN317+uH0/enF2xo9zLdn3GfUqFGJx/rss8+cZj653R8/y7pF9erVc5oxAM4Poe9v+0DVqlVdG/sPr5P1m8qLpLk1ISTXvy/r70jWNQUsXHb2+eefd5q/BfTpuYzo4cOHc9ucU8N1KXjedv2MEEouabpu3Tqnp0+fntu2ta5CKNlneP/zWZtEbwRCCBE5GgiEECJyNBAIIUTknJTzCMrif9PDtXnaIZRco5jrwtpcec4LYEyA+en07rgGbYcOHZy2fifX6J05c2aoaBgT4PWx3dbHZy2kQYMGOT1lyhSnmW/PORddu3Z1etmyZbltzv1gfOKpp55y+oYbbnCatYaS1npo1KiR01x/4PPPP3eaawrQC2ZNJtsnmIverFkzp3ft2nXc8ywkWZ7HrGsUp8UUko7N9UIY62HMhc8nvXdb9ykEv0Y35yjwu+F1cF/s74w/2vgbf2dY54gxsnzQG4EQQkSOBgIhhIgcDQRCCBE5J2WMoCzQN0zLQ6Y/bL061n9nHnKa38lj8dzsGsb0L2vXrh0qGl5v06ZNneaauTaGcvvtt7u2L7/80umePXs6PX78eKcXLlzoNGM5tlYL40ADBgxwuk6dOk4PHjzY6XHjxjnNOQ42f9z6xCGUnEtBL5hzFPr06eM017TYv3//cdvoI9v6+IUkq49fnvvKEo9grSDGBAi9dz77SWuMc25F2nrkrH/FGEPLli2dttfCPsb4AvedD3ojEEKIyNFAIIQQkXNSWkNJFgtfwZjiyXKvTBGjZvqofR3nqyOnidNKofVD24AlAuw0dC5xyOtiOe1CwLLbCxYscJrWhLWDmEbJ11dez+jRo52mpcISE7YExaFDh1wb+4QtRxFCCI8//rjTtBCsFRSC72+TJ092bUxH7tu3r9N79uxx2lo/IZQsZ3z//ffntj/++GPXRvuB6cf/RcpaYiKLNUTrNa00Bp919htacXZ/LMGetpxkWrlt/lZYK5htLL9yIun1eiMQQojI0UAghBCRo4FACCEi56SMEdADs14dfb077rjDaS7nR685rSyELV/AFE56iPQc6YvTV+SxrZf98ssvuzaml3FfhYDnP2TIEKfnzp3rtF2ektPe7TJ/pe170aJFTrPkMlNEbYyEy2AmLWcYQsmSwYzVME3WxhCYMsw40eLFi51mKW/GBJgWa8um0xvmPbnppptCRVCWpSrLmnqaJb2UKZksPZJWrpmaz3flypWPex78HeL3yvvAeCHjGfb5Yd9n+qhiBEIIITKjgUAIISJHA4EQQkTOSRkjoB+etGRk2rJu9PnozdHrs+WgOSWd8wa47ypVqjhNz5Len10G8a677nJtY8eOdZpLcBYCnu+KFSucppf+3nvv5bbpx7L0M0sss6wDl3zksoF2DkOTJk1cmy1RHULJGAL3zRLCV199tdN2jsNDDz3k2ljimkuIsv9xzkL9+vWdtmWr58yZ49o4J4Z9YOjQoaEQ8LtMK6+QRHnHDOy58P6wT6XNE0jT9tx5Dzg/5MCBA8f9bAghNGzY0GmWLrFxAM6TYSxDMQIhhBCZ0UAghBCRo4FACCEip9xiBEleHeto8G+ZQ04PktATS2L69OlOM5+d+b3M56XfZucd0BdkDCCtHGzaddv9cxlIlqKtCOjLr1mzxmmW/bXazikIoWTuPstSp8VuGK+wNX5Yz4d1jDj/g8tF2hpPIYTw1ltvOd27d+/c9htvvOHa2rdv7zTrL9Er5tKWjH+98847uW3OWWC8gUsWFgo+z2metH3e+eynPev83vl5zq0oKirKbffq1cu1sR4XP8sYAI/FeT72PjCXnz4+v3f2MR6bv0tW83eG30eW38fcPjJ/QgghxCmFBgIhhIgcDQRCCBE5JxwjSMu3PxGfKl86d+7sdP/+/XPb119/vWvjmgHM9WdMgB4tr8vuj/eAtYXo5dFL5bkRe270IPv16+f0tGnTEvdVHnDeBPPrGfOwOfS8F6znc8899zhNT3Xbtm1OM9ff+uXc18CBA522ufkheF85hBBeeOEFp++++26nN23alNtmrII+MudWsNYV/55rDtg+0KlTJ9dm52mEEEKbNm1CRZBWuykJPl+8f9WqVXOa+fRsZz/o2LFjbpv3nrGitPo/7LP08e28H/4WcDlUrlPB3wrGDLg/287rmj9/vtOMg+aD3giEECJyNBAIIUTkaCAQQojIOeEYAb3zJJhfzhogrLPBdvrhXDvX+sPMqaUPz/Vqmc9OH5wxBFtriJ4h85JZi54eJWMdzKm2cwXovzNfvSLg9TGvnXEh66Ha+xZCyfuetl5B3bp1nW7UqJHTU6dOzW2zBtJtt93mdLdu3ZyeNWuW0+wj7777rtPWt6YvT8+bazUzrrJr1y6n6YHbeAZrJrGvc13nQpE0Z6g0besptWrVyrVR0/+m1875KPyu7PyTtJpk/A1LW0OcvyW2v/M3jv2A/ZvfHc+Vz5q9zqT1WEI4sXWh9UYghBCRo4FACCEiRwOBEEJEzgnHCOhRP/30005br5PruNKbo8fFmjb0nundWe+P/hhzhenbDxgwwOmVK1c6zXVPbTyCHjlhjjP3xZo49CBtjjnjC/TMKwJ+L+vXr3e6S5cuTttcaX7nzPXnmgCsPfTRRx85TQ/VzllgTjb732uvveb0k08+6fT7778fkrB+L/f94YcfOl1cXOw08+JZk4ZesY1ZNW7c2LWx3hTnQxQKPmP0u3ketjZT3759XRtjQdwXNX38pNpgfPYPHz6cuG/2KdZy4rwCG6+gb88YGPfN8yaMCdrfOMYx2WcUIxBCCJEZDQRCCBE5eVtDtG9eeuklpzmF2loBSWUaSoOvTfw8X/kstAVooTz33HOJ+xo+fLjTSemlc+fOdW07duxwmmmxTHVjOhtLL9tXV74q2nLYFQXPj6UaJk6c6PSIESNy20xtZCmFHj16OM20wdatWzvNe2dLUkyePNm1MbWPKZxcBpRLWd56661O2/LbM2bMcG208DZv3uw0vzf2iQ4dOjhtS2Szv7HMciHLulhog9AeYwqo/W5pp9LW4DWklbxOKvvA1F0uh8pjM32b18X+bq3StNI1/F2ifcNzSbII2Yd43rKGhBBCZEYDgRBCRI4GAiGEiJy8YwSDBg1ymt470/2sV0rflJ4toRdNf41pl9bHZ5oWfUEuLUj/l+Wc6Wnaa6FvzdIF9DfpZ7IUbVJKGeMkvEdcfrEQMJ2O18NyAdY/Z0mIm2++2Wmmj7799ttOjxo1yukFCxY4bVNtH3zwQde2detWp7lk4cGDB53mdY0fP95pmwbMFGF6xSxvMXr0aKfZv/hs2KUs2T9WrVrldFpKYnnBMg/169d3mqXgbdol+3Fav+Z3wWs8evSo0zZGkLbcKT/L745/v3//fqft881nmfFBlhvnsRk3ZYzAXgv7SNpSofmgNwIhhIgcDQRCCBE5GgiEECJy8o4R0EelT59UioF/y5gBfT96kJwa/tVXXx13f5wXwOnYzFOeMmWK0xs2bHA6ycOlf8kSDMz957GZ/0tP07YzN5j3jKW5C0GLFi2c7t69u9Pz5s1z2nrznGeydu1ap3lvOJ+D8Ql+r/b+0F9lSZIlS5Y4zVINDzzwgNOcl2C/Z3rB27dvd5qxM5ZU4PfGUhr2Pt17772ujf2Lxy4UnOPBOSDMt7ffLZ8ReutpJSb4HNAft89QgwYNXBs9f84Rql69utOMJfH5tOfO3yz2V2r2d5av4G+DPVbz5s1dG5c/5e9jPuiNQAghIkcDgRBCRI4GAiGEiJy8YwT79u1zmt7c3r17nbZLtbH0Ln1CluJlLQ16vvQVrXdHr42xC3qOPDb9TS4xZ+MdNme5tPPivtNiBmy3ucf0Aelrt2zZMhQaeo8LFy50mnV3bC0c+tecc8DvmH/PPsF5LPZ7YpyHtW9Wr17t9KOPPuo0+zb/3tYmevPNN10by5rbJTRDCKFJkyZOcwlPttsYAvsiSzo/8cQToSJgfIZeO+OJdp5B2twZPhPsF4RzjOzzzn0xnsOy3lwmlDEF+vy2PS3+x3vGeQX83SI2Hsnz4LwCxmTzQW8EQggRORoIhBAicjQQCCFE5OQdI2De9wcffOD00KFDnba+Iev00y/jvALm69JPo69ovTr6Z6xlQv+XNT5YT4R/b/eXVDM8hJLXlTbvIGkeAj1I1uZhTaVCMH36dKdHjhzpNP1uG29hbRXWhKKvSS+Z8xB4723+PX12xmr4vXBthMGDBzvNOlvW/61Ro4ZrO3bsmNPDhg1zetKkSU7zOul52zgM7xljIW3atAkVgV37IYSSa03Qa7f9gM8y4fPL3wIbe0yDzz4/m1a3iL8N9P1tH2Q8gcdmn0uKc4ZQ8nnfvXt3bnvmzJmubePGjU4z1pgPeiMQQojI0UAghBCRo4FACCEip9I/eRazTlsHs7i42GnrH9M7pmdLb5z+Gv03entJXl2W2iSlaR7LtqfdE7an+fg8lvUkOY9g/fr1TjN/vTxqlBPW/2Fuf+fOnZ22XjLr03B9AnrrixcvdnrFihWJ5zJr1qzcNtfyZT0prkVbVFTkNOdH8FztfAquSUFvl/fkkUcecZpzAVgT3+a6W584hJL9ifN1xowZEwoB+yn9bsZo7G8Dr5e1vPjs8xnKstYv2zgPg3NxeH85N4pzkOx607z3jOekxSt4D/k82HVSxo4d69p4HYxlMO5SGnojEEKIyNFAIIQQkaOBQAghIifvGAG9d/pQSXAt32effdZpxhCYS01vjudivUB6cYR1UHj5rKnE67TeHc+DcN/M72WeMq9z9uzZue3Nmze7NnroaccuD7g+L9eqpQdr2+mZco1l1h7iPBX6+PTHbb0V+vJLly51mt4v6xaxphLjMba/ck0G5vazDgz7NueWtG3b1ulXXnklt00f2XrUPK8QQnjsscdCIUhbM4BxNvvds5Z+7969nWb9n7RnhthYGuMJ69atc5rfFetbcb4E5wnZ74PnXbVqVad5T9LWqubcKzv/hLE5xqX47LO9NPRGIIQQkaOBQAghIqfc0kfLE75mpZWxtsv/7dq1y7Xx1ZJLB56qFMIaGjJkiNMs8c17be0b2kqffPKJ0zVr1nSar7O0gmiL2PRUvmbTDqQ1RHuGy0fSUqCVZOErP78H2k60ilhqw5ZrYJkNLsHJ8g2FSh/NmqJt29OWnqTOaklbu4Z9iPumjcx9J5WX4f7SzjsN/j3P3R477dlOO+/S0BuBEEJEjgYCIYSIHA0EQggROXmXoa5ItmzZkunvWYZVFAam1zH1j2UgbCyHHipTirdu3eo0y/ZyCVGWRbflAVhagP4rvXWmwS5fvtxpeu82FsJSAEyPZNkCxjYYz2B5Cxs7mTdvnmtr0aKF00xRrCiyxKPow6fFF1geIS2mkFROISl2kc+5pLVb0q6TME6Vduws+84HvREIIUTkaCAQQojI0UAghBCR85+cRyDKTiHmEYwYMcJpzsmgz2lL7dK/3rlzp9OcR8BcfZavYImKCRMm5LYffvhh17ZgwQKnmbvP6fw8NuMVNobF+EOaT9+uXTunly1b5jRLZNt5CSxxwOtgGZKJEycmnsuJklZign3P6rL2y7RjJf1OZY0RpH0+y3Vl/f3kdSbti5rxCZWYEEIIkYoGAiGEiBwNBEIIETl5xwiEEEKcmuiNQAghIkcDgRBCRI4GAiGEiBwNBEIIETkaCIQQInI0EAghRORoIBBCiMjRQCCEEJGjgUAIISLn/0JQxIIGQKmMAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -2508,7 +2434,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2518,7 +2444,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2528,7 +2454,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2538,7 +2464,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2548,7 +2474,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2558,7 +2484,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2568,7 +2494,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2663,78 +2589,19 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 43, "metadata": {}, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "fb5a58852423438b89bef7f869097e83", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/1875 [00:00" ] @@ -2784,7 +2651,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2794,7 +2661,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2804,7 +2671,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2814,7 +2681,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2824,7 +2691,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2834,7 +2701,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2844,7 +2711,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAV3ElEQVR4nO2de7CN1RvHly6kXBLJpZzkmkvIpVxyRnJNqUTKdNFFNSrFTLfRX5lppkYMJmTKjOskpcg9IUYIuVPkEiKhKJUov79+76znszv7Pa9jH+dY389f6ztrn73Xfveb1fs8z/o+RU6fPn3aCSGECJYLzvUChBBCnFu0EQghROBoIxBCiMDRRiCEEIGjjUAIIQJHG4EQQgSONgIhhAgcbQRCCBE4F+X2hUWKFMnkOsRZJhPnBAcOHGj0iRMnjC5ZsqTR27dvj8b16tUzc+vXrze6devWRn/11VdGX3SRvVUvvPBCo/37s3jx4mZu165dRnfp0sXof/75x+iFCxca/fXXXxvdpk2baHzbbbeZuYMHDxq9efNmo/m96tata3TDhg2NPnz4cDTmb7p69Wqj+/TpY3T37t1dJuBvwXWlu/cuuCDZ/3vy350k/w5deumlRvO+KFGihNFVq1Y1ev/+/Ubv2bPH6H///Tca//nnn2nXwnUnuWYk6X/bvL//Cz0RCCFE4GgjEEKIwNFGIIQQgZPrHIEQhw4dMnrdunVGt23b1ug//vgjGlesWNHMTZ482ej27dsbzXxDXGz5+PHj0fjKK680c8wRjBs3zuinn37a6Fq1ahnNWHLNmjWj8fjx483cNddcYzS/B+PQzI3s3bvX6KVLl0bjChUqmLn69esbPXbsWKMzlSPwY+POJYv7ZzrXWLRo0Whcrlw5M8ccAX/n559/3uhffvnF6NGjRxu9c+fOaMz8QdKcQV5yCGfjmuqJQAghAkcbgRBCBI42AiGECJzgcgR+fNc55xYsWGD0hg0bjO7cuXPG11RYYH39gAEDjF60aJHRN954YzRmzfvVV19tNOP21atXN/rAgQNGX3fddUY3atQoGh85csTM3XLLLUYvXrzYaOYUateubfSECROM9uPQrNE+deqU0X4c2bnUuPSsWbOMvvjii432rxPzCz/88IPR7dq1c+eCuHh2JvMCfO9LLrkkGvO3ufzyy43mmY1WrVoZ/fvvvxvNe9j/7GPHjpk55lF45obr5uuTwOt9Ju+lJwIhhAgcbQRCCBE42giEECJwgssRjBkzxuhKlSoZ3bdv3/xcTqGC+RLWvDdr1sxoPxbPmuxSpUoZzRpv5gTuvfdeo5mP+OSTT6KxHyd2LrVW/5577jH6119/NXrUqFFGt2zZ0mjG8X1uuukmo1etWmX0DTfcYPSOHTuM5tmAyy67LBqvXLnSzNFvibmRgkhcvXzSvyf++/31119m7o477jDa94xyzrklS5YYzbMBR48eNdr3MipbtmyO6/ivtfCcAeeT5FXy4sf0f/REIIQQgaONQAghAue8Dw3df//9Rjdp0sToQYMGGT19+vSMr6mwwpJNlkZWqVLFaD/cwxJOhpVYsunbUziXauVA+wS/ZI6WEv369TOaYSbeE82bNzf65MmTRv/888/RmCWILBPkNaG1Ro8ePYymbbVv+UyLj6uuuspohtMyRdLQg//6pNYKnGc4jPYWfsiR9xTLnefPn280w3gsz+X19+9RrovhQ4Z+WNoad039+bhrlNTq2zk9EQghRPBoIxBCiMDRRiCEEIFz3uUIGJMdOnSo0YwDDhkyJNNLOm+gfUL58uWN/vbbb43u2rVrNPbtlJ2z9hPOOTdz5kyjaTHx7LPPGj1v3jyj/faTLKP85ptvjM7Ozk4775dsOpdaNujnN3icn1bcLBNkroS5EJYs+rYHNWrUMHOMgU+bNs3lB0nj+j68Xkli485Ze4//mvdj9U899ZSZ4+84Z84co2k3w7X+/fffadfqw/9WSFy7z9y0l8zpb2UxIYQQIjHaCIQQInC0EQghROCcdzmC4cOHG812de+8847RtBcQOcP6fFpJly5d2uiRI0dGY1r8sq6atfuTJk0ymm0aaQm8cePGaMy8EHMGrA+nPTFtR3bv3m20b2HBWn62qmR9eZkyZYz+7bffjD58+LDR/v3Lcxt16tQxOisry+UHSW0hkvwtY/6MlTP+zVg7f0ufL774wui5c+caTRsUWpWkWytf69tPOJd6H1DT8jpJLiUvv8f/0ROBEEIEjjYCIYQIHG0EQggROOdFjqBTp07RuH379maONeKsFRa5J85Kl+cK/BaQ27dvN3O+bbRz9jd0zrlu3boZzZaO9D06fvx4NJ46daqZ27Jli9HMG9HSmv4/bG3p1/7Tx2jixIlGt2jRwugZM2YYXbduXaNpU71t27ZoTC+hNWvWGJ2kzr2gEBcLZw6A5whKlixpdLVq1aLxZ599ZuaWL19uNL2D+Nlx1tC+pw/XSX8qnivge5N0ZzXiznHIa0gIIURitBEIIUTgaCMQQojAKXI6l0WoZ9L+LL/w48dsK8i2hKHkCM5GbTF57733jP7ggw+MZhzU/y38WLdzqbHztWvXGs06a8Zc2RLy2LFj0Zi15/SG5zo3bdpkNL2GKleunOPr69WrZ+Z4loL5ieuvv95ov7fBf63dP3fAeDpj4PRzysQ94Fy8T04S4voTsD6fOQFe/1q1akVj+jbxd46L0zPWzt/Gn2fuolixYkb7OSznUvM5vL/pi5TOPyjOWyg33kN6IhBCiMDRRiCEEIGjjUAIIQKnUJ4jGDhwoNEdO3aMxmPGjDFzoeQE8oPvvvvOaNa8f/TRR0b7cXzWwM+ePdtoxoavvfZaoxlTZbzWj6lynfR9YX6iV69eRu/bt8/owYMHG+37HtGHiOtmvwHWsjP/wPMWvv+Nf587l9p7+a677nLnAv526WLSSXONzNdQs2+Ff5/wnuNvwTxU2bJljWYuhPeFH9eP68nA+5Wfzfub19DXcecEziRnoycCIYQIHG0EQggRONoIhBAicApFjoAxsdatWxvtx9feeuutfFlTiLAnMf1+mjVrluPfsi6a9fSc53tv3brVaPYY8GE/ZHrKsLaftfx+LbpzzvXu3TvHtXAdjO3yezVo0MBo9h84ePCg0X6/A+YX6Ku1YsUKVxBI530Td26A9fe+X5VzqdeXZwH835q1+4TnSdgTgL0NmDPw18J18RowT8XX07eLJPEPOpMzX3oiEEKIwNFGIIQQgVMoQkP9+/c3um3btka//PLL0Zjld+LswcdbhiKqVKlitN8asG/fvjnOOZdqJcA2mHw0rlq1qtG+xcS6devMHMsI2aqS7SU//vhjoxny8kMGDHExVEHrAT62s1Vldna20X6Ige/95ZdfGs02mAWRuNAQy0PZopStZXlNfE3bhjjLCL4XQ4YM5/h2F/wsan4vhpnYJpNrTVcSGmdLnRv0RCCEEIGjjUAIIQJHG4EQQgROocgR8Cj9jz/+aPSHH36Yn8sJFsY1H3zwQaOnTJlidMOGDaMx46+NGjUymhbKfD1LVxnf9WOsV1xxhZmjzsrKMpo5BOYEePy/SZMm0Xjz5s1mjnF72mUzzhxXVuhDSw/+Hn6paX4SF8/2Y9i0VuD3L168eFpNm4h07VP5t4yl8724bmquvUSJEtGYpacsB6UVOu9Jlg1zbcw5pEM5AiGEEInRRiCEEIGjjUAIIQKnQOYIaC/AeDJbJO7atSvTSxLOuZ9++snoTz/91Ohy5coZ7VsyM5a7YcMGo5s2bWo06+sZ9+Txf//9lyxZYua6dOliNOP6hGcUZs6cabRvQcE6d8bpWffOa1SxYkWjufbatWtHY973zZs3N3rVqlUuP2BOIO5sgP965gR4fsSPuzuXGiuPs5jw7xOuk3F5roXE2UD4ZwP4Xv65FudSvxfPFXCeZxiSxP1lMSGEECIx2giEECJwtBEIIUTgFMgcAWN7rJfOT1hTPnLkyGjMuB5zFd27dzeaccPCRrVq1Yxu1aqV0bRUXr16dTSmtTNbOjJnQDti1nDv3LnT6Pnz50dj5gTYupLfgzXg/Ozbb7/daD82z5j+gAEDjGZcn3FqnmHgPbVs2bJo/Mwzz5i5uXPnGp1fXkOMnfN6pTtHULp0aTNXvnx5o3lm48SJE2nXwvp6/3wJryXPFfDfGa6NpGttyVwQz4/ws3gN+W8H/83juZl06ByBEEKIxGgjEEKIwNFGIIQQgVMgcwRxMOZ7Npk8ebLRd955p9F+XTPrdatXr270jBkzjO7QoYPRrIEu6LAFJH39ef7D9+pnjJP9BhjrZTyW7UnT5RToyTNu3Li061y4cKHR9LaqXLmy0W+//XY05v2xe/duo5lH4RkGetCUKlXKaD/W7OdcnEv9HrymmYJr5lkA36ef8/R5qlSpktG8T9iqskaNGkaz98SOHTtyXBfj8tT8bNb6Mwfjx/WZ//PzB86lnvmIa4vJPhbMnfjEeSTlBj0RCCFE4GgjEEKIwNFGIIQQgVMocwSsD84LrGdnTLdz585GL168OBozjjd+/HijeY6AfXsHDx6caK3nmkOHDhnNPquMi+7duzcas58Aexb36NHD6OnTpxv9xBNPGL1mzRqj/T7W7777rpmjH9D3339vdJ8+fYxm7Tr7YPv3zIgRI8xcz549jT5+/LjRHTt2NJrnEOrWrWu07zmzZ88eM8d8Aq9JpmBujPX5jKX7uTBeD95D9GriPUVvJtbf+7kiemPxevHcAHtXM9fBczJ+Xouf5d/7zqXmb5hnYU8V5jf8uD/vzyS9CnJCTwRCCBE42giEECJwtBEIIUTgFMgcAft3+rXBzqXG3ocPHx6N9+3bl+izmBMYPXq00X5OgLC297777jOacW/Wpxe2HAH78fL7Dhs2zGg/dsk4Zrdu3YxmbPjxxx83+sknnzSaMVffs4Yx1Dgv+P379xvduHFjo3k2wI9Ts3cBa7gffvhho9lvmzFy5iP8tbRr187MbdmyxWjmuzIF6+95vemf5OfS6EtETx2ejWB+Z+PGjUbzeh09ejQa85wOfY14X9AHijkE+gn5OQeeQeA14W/DfBvXyvfzvYp4zZQjEEIIkWe0EQghROAUyNAQj2tPnDjR6Ndee83o119/PRq/+uqrZo6PqYRlW2eTs3H0uyDBkAntEtiuzy/9Y+kdW1FOnTrV6Iceeshoho5oD+5bTjBkxRaOtKFmiO+VV14xmuFD3w6A4QS2M3zzzTeNZriBIQCWOPpWBGvXrjVztOKmbcHAgQNdfsDvwNCFXwrJ/wYYbqHVAu2b+fe0oPCtSfhaWqLwsxgCZJtM4n/PuPAM7UFYCszfLr/RE4EQQgSONgIhhAgcbQRCCBE4BTJHQPwcgHOpVrSPPPJINGaLOMZJZ8+ebXRerKBplfzYY4+lff2kSZPO+LMKAps2bTKax+CZM/BbPM6ZM8fMMZbeq1cvo/3Wk86lxvH5934J8XPPPWfm0pUYOpdqW+DbZzuXGiueNWtWNKZVAHMhLVu2NJo2EO3btzd6xYoVRvvxd5a9Mj/Rr18/lx8wJ8ByUsbm/Tg/f0e+lteTOT7aWdx6661G+/82LFiwwMxNmzbNaMblmbdiaS/v91OnTkVjlqYyF8S8J68Dy5B5Tf3P4v0Y184zN+iJQAghAkcbgRBCBI42AiGECJwip3NZ3E7r2YLECy+8EI1feuklM8c6Y8a5aYtLuwG2Maxfv340btSokZljK0ceh2e7urg65byQiTML/fv3T/QZ27Zti8Zs48lYOq0F2IKwSZMmRi9atCjHtbFFKOP0PO/w/vvvG81zKqxl92vfWXs+ZcoUo/mb0yZi5syZRjM2XLNmzWhMy2raadM22c9lnE0Yx6dtBO3Z/dwGX1ulShWjGfM/cuSI0bw+tInw25Ty3yzmghjH5/XjmQ7eB35+kbbTtMlhfocWE/x3hrY6/r8VPD/CPIqfT3AuNafzX+iJQAghAkcbgRBCBI42AiGECJxCcY4gjiFDhkTjsWPHmjm2IaT9MT1rGFfs2rVrjp/L2nhaJ3Mt5xt+G0XnUv1TfE8ftgHMzs5O+94rV640mvFZPxbsnHPr16+PxsuXL0+7Tp5ZYA037wG2yRw1alQ05vd69NFHjX7jjTeMZq0618Z5/7vwfAPP09CyOVMwN8SaeMbxfU8exsrp98PcEXN2rP3nZ/vnNOhPVblyZaOzsrKM5jkB5gwYa/fzHXHnSdiadevWrUaz1SXPN/nXNM7D7EzyuXoiEEKIwNFGIIQQgaONQAghAue8OEcgUsnEOYLJkycbzRp4+vz7Mde4WDhjx6z137Vrl9Ft2rQx2o/Jsgab9y7zD2x96vdRcM65F1980ehOnTpFY7YgZP34zTffbDSvWdOmTY1etmyZ0R07dozG9FfyezA4lxqnzlSOiv0GeH2p/d+Svytr+Rmnj4ud87P8GnpeD+YTmHfi9eV701vM/6y4a0BY689ryjMM/jzPHzFvwhyNzhEIIYSIRRuBEEIEjjYCIYQInPPiHIHIH1j7TJ8Y9oT1697p7e7H2Z1LjakOHjzYaPo6bdmyxWjfm5/x1zp16hjNGu/PP//caNa2+34/zjlXpkyZaMycAGPg7EFRrlw5oxnvpafSvn37ojHzKrVq1TKa85kirm6d837snXNx8WveN+l6HThn4+Nx/Y7jvgfXRu3/fVxOLm6e700vIj9HwNfGXf/coCcCIYQIHG0EQggRONoIhBAicJQjELmGsclVq1YZXa9ePaPnzZsXjdmbd8KECUYzLj9o0CCjR4wYYfQDDzxg9LBhw6Jx27ZtzZzvQ+RcakyVvX+ZU2DPCr/GO+58BOP4fG/2XWD9eIsWLaKx35fZudSa+5MnT7pzQZKcAc8BMJ9DWBMfN+9/VtzfxtX6x8Xe/fePO0cQ915x2v9tM3GmS08EQggRONoIhBAicBQaErmGpZK08GZbUD9U5LetdM65xo0bG03L4MWLFxvNNoO0mvatHhjCatCggdHz58832rdxcC7V7pnhHr9Mlsf7W7VqZfSCBQuMZviGa6Wlgm+ZzXDY7Nmzje7Zs6c7FyQJizDkQdsGlnyeOHEi7WcnsWBOGq5JV5rqnF173N8mLenMi0WMbKiFEEIkRhuBEEIEjjYCIYQIHOUIRK4pUaKE0StWrDC6fv36RhctWjQaMxZO+2H/tc45d+DAAaNZKkn750qVKkXjI0eOmDke12ebS5Y00vKaLQ47dOgQjYcOHWrmfEsI51LthWmNzHJR6rvvvjsasxVo7969jeY1yxR5KY2MywnwvThP4kpEk/xtUivpvLx3XLlofqMnAiGECBxtBEIIETjaCIQQInCUIxBnTHZ2ttG0C/DPCrA95KZNm4xu3ry50cwJ8BwBLa99zfwBcwSs5ae9Bc8wtGvXzuhZs2ZFY7aaLFasmNG8JsxPbN682eilS5ca7X+XChUqmDnaWzDPkimS2jv78HqwPSTfO86C4myeI0ja4tH/7LgcQNJ8Q5KcQV7PLDinJwIhhAgebQRCCBE42giEECJwipw+1wWsQgghzil6IhBCiMDRRiCEEIGjjUAIIQJHG4EQQgSONgIhhAgcbQRCCBE42giEECJwtBEIIUTgaCMQQojA+R8WpVVQ4pN3lgAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -2860,12 +2727,12 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 45, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2875,7 +2742,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2885,7 +2752,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2895,7 +2762,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAV0UlEQVR4nO2daYwU1feGLyqyOQiKiLIIsoiCgAiIyL5FRBCiiKIiYlRiMMYQDfEDMdEE+GCIIVExLjHEDRJEEAkKCKOAbI4gsokomyCrbCqK8v9W/3ueZup2MdOj+d33+VRvbk91dXV13an3nHtOpTNnzpxxQgghouW8f/sAhBBC/LtoIhBCiMjRRCCEEJGjiUAIISJHE4EQQkSOJgIhhIgcTQRCCBE5mgiEECJyLsj3hZUqVSrkcYhyphDrBMeOHWv0RRddZPQVV1xh9Pbt25Pt3377zYz98ccfRvfv39/o+fPnG924cWOja9eubbT/eTdv3mzG+N5///230Xz9s88+a/Svv/5qtP+5f/jhBzN28cUXG718+XKjmzZtanSrVq2M3rNnj9Fr165Ntm+++WYztm3bNqOLioqMnjx5sisE1atXN5rXGrV/7+B9hDrrdcvXn3fe//9v+88//2R6L/9vz6b//PNPo6tVq5Zsnzp1yoydf/75RvNYCMfTji3rOfv9999Tx53TE4EQQkSPJgIhhIgcTQRCCBE5eccIhDh58qTRXbp0MXrv3r1GV6lSJdk+evSoGevQoYPRxcXFRl933XVGHz58uNR9O+fcwoULk+0LLrCXNX371q1bG33XXXcZvWbNGqPpFXfq1CnZpm/PeAOPs379+kbPnDnT6NOnTxvtn3PGOhhXOXjwoKsIQt57GqF4QhavPPT3ob8loc/lxwScc65mzZrJNuNOjBlQ871Cnyvt2HmcPJZ80BOBEEJEjiYCIYSIHE0EQggROYoRiLwpKSkxmp4pc/3r1q2bbNepUyf1b5s3b270Tz/9ZDQ9U77XkCFDku0NGzaYsQsvvNDorVu3lnqczjm3Y8cOoy+99FKjv//++2R73bp1ZqxBgwZG0wt+5513jKa/y7UYQ4cOTbaZD/7VV18ZfezYMVcRhPLWQ3EAn6zrCkI+vq/Lc02Cc85VrlzZaP+64hqDrL596FjT1iGE1ijkg54IhBAicjQRCCFE5GgiEEKIyFGMQOQN1wLQQ2X+vl8Lp3379mbs9ddfN7pRo0ZGDx482OhPPvnE6FmzZhntrwVgLZyff/7Z6JUrVxp9ww03GD1w4ECjV69ebbS/doDxhV27dhnNczR69Gijp0yZYjT3t2nTpmSbXjDjCYyzFIqsMQK/7k7I8+c1REJ+uO/Nc1+hdQQcZy2tGjVqGO2vT+Fvg/GcUCwktH4iC+cSM9ATgRBCRI4mAiGEiBxZQyJvnnjiCaN928I556ZNm2b0qFGjkm2Wne7atavRPXr0MJplqGl7sJSDXyr6r7/+MmO0CAYMGGD0kSNHjKYFwPRR3/5hieqePXuW+lrnci2ukSNHGs101AMHDiTbLLvRpEkTo5nCWCjSykw7l14uIZRaGkqzDL1XllIMoXRRph3zOvKvM5b/yGr1lGU89H3kg54IhBAicjQRCCFE5GgiEEKIyFGMQOQNyyds3LjRaL88s3POjRgxItmePn26GQu1Xdy9e7fR11xzjdG9evUy2i/nzLLTTNlk+8jXXnvN6KlTpxo9aNAgo2fMmJFs9+7d24zNnj3baHrHLHnNVpcnTpww2o85+KUtnMuNT7BU9/333+8KAdswhnx+31vPWn6ZhFJAWcbbJ+Sdc9/8nEwn9c8/PzO/d8LzkCUtlmQp6VEaeiIQQojI0UQghBCRo4lACCEip9KZPA2lc8lNFf8eZVmiXhpPPvmk0cyvp2ftL7P38+Gdc65jx45GX3vttUZ//vnnRteuXdtolqGuWrVqss3yzPv37zea+fc7d+40ulu3bkZzDcTcuXOT7Xr16pkx5vJffvnlRvP1hw4dSj02fz0Ff4M33nhj6nFOnDjRFQLm19NbD8UB0l5LQqUY0u5LWffNdQIsVZL23mxFyZhBqLRG6NiyxAj43vm0rtQTgRBCRI4mAiGEiBxNBEIIETlaRyDyhl4vffpvv/3WaL80b+fOnc0Y2yoWFxcb3bRpU6PXrFljNMtaL1u2LNlmWel9+/YZzfLNBw8eNJr1fli7qEWLFsk289arVKliNMsR83NyfQRbdPrjRUVFZuyXX34xmmsQCkWoZk8WPzu076zjPqE1B4S+PWMuafGKLLGLfI6tPNt75oOeCIQQInI0EQghRORoIhBCiMhRjEDkzfHjx41mC8irr77aaL9fAWvqcM0BfU7WamFO98KFC432/fO1a9eaMa4rYM0Yeu+MP7BVZbt27ZJtxgiuvPLK1L+lN8w1CzzH/rFzTcKePXuMZo2liiLkUfv+eZbeBfnoNN8+aywj61qpNJ8/tLYiFFNIW4sRWifAdR75oCcCIYSIHE0EQggROZoIhBAichQjCDB48GCjv/nmm2SbNWpI1h6pofojPszLpw9eCPh5mGe9Y8cOo7ds2ZJss6ZOv379jKY3ztfTi+e59OMCw4cPN2Pr1683mn0V+LlKSkqM5noJP37x0UcfmbG+ffsazdpDXCfg1y1yLrcv8WWXXZZsf/nll2aMMYOsefPnSlq/gRBZc9zL07cPxQj8elXOOVenTh2j+bn9NSInT55M3XcoJhA6L35vBH5G/xpxLve3kw96IhBCiMjRRCCEEJGjiUAIISIn+n4E9913n9GsU8Peun6eOOvzz5kzJ9N70+uj9n3x5557zoyxH22zZs2MLkQ/gpdfftlo1hZiT91LLrkk2W7ZsqUZY50c1uDh56GvX79+faP9eA3z6enfcp0A+xUwfvHmm28a7fdh8D+jc859+umnRvM77dOnj9FcX8F1CP6xs4cu+x9PmjTJ6Pfff98VAtZTKkutm6x/G3q9r0M9iFlzqmHDhkYz1uSvi3HOfndc03HkyBGjeQ2GYl6VK1d2pcGYVfPmzY3mNchaWmdDTwRCCBE5mgiEECJy/ufTR7t27Wo02/uNGzfOaD6qM/1v9+7dyTYfxflY/+qrr6YeW2jZuc8tt9xiNMskDBo0KPW9yoNt27YZzdLQPXr0MNq3f5g2yUf8CRMmGD1z5kyj9+7dazStIT+FkY/l3bt3N5rH8sUXXxg9ZMgQo2lr+TbAVVddZcauv/56o2lDscQ1U3BZtsO3AZhiS+unTZs2riLIUnaarw+lUJNQm0XaPf7+qlWrZsZ4ftgWlKXP/VIizuX+vn1Lhtccr9ft27cb7adWO5drHfH69suRs3Q527zSwsoHPREIIUTkaCIQQojI0UQghBCRUyExAvqALJNKHz5LqQXnrLf3+OOPmzH6fFw2ztSqWrVqGX3q1KlS35elkSdOnGj0K6+8YjTTEFn6gCmT/rHzuA4fPmx0z549Sz3O8oL+LuMSS5YsMXrMmDHJNs8jy1AznsKYCK+hxYsXG+2XZuCSe/q3PJeMbXDfjIV06tQp2Wa8gdcy21zeeuutLo2lS5ca7aeyMkWRn5PntFDQl89CqOw00yp5L2A5C/4G/d93x44dzVjr1q2NrlmzptEsMcF7A4/VTzdlCXYeN9NBQ/dAXqN+zIDHwVjIqlWrXFb0RCCEEJGjiUAIISJHE4EQQkROhcQI6Jcxd5rQ92P+7vPPP2+07xvSZ6c3feLECaPpxfFYma/vlxQ4evSoGWOeN9st3n333UaznEWa97p169bU92LeciHwS3A759yAAQOMHj16tNGLFi1KtllSgt8xc6GZP75x40aju3TpYrR/LvlezHOnP8t903N94IEHjPZ9aOaHMwbFGMK+ffuMfuaZZ4zmsc+aNSvZZtnpH3/8MfW4C0VZSirTKw+tI2AZCMZFuI7DjwP4pUCcy/3eQ+sfeI3Wq1ev1P1x3zwH/G3zvsL34j3Sv4+lxS2dy4035IOeCIQQInI0EQghRORoIhBCiMj5V2oNMW+bObgPPfSQ0fTD6cf5ucfM/WXJXJYopp/GPGbmoPtt4OhBhvxO1pFhHjPrjfhrBegLtmrVymi/bV6h4NoFv+6Sc7lxCj/P+sCBA2aMOd6sAcWS1swBZ868f40cO3bMjLHM9IoVK4xm7IZlqFn3qHfv3sn21KlTzdj8+fON9j1+53K9X65R4PoJ/5qgv/7xxx8bzXNYKLg2okaNGqmv9/PzGZPjOh/eG/h6ngP+Lnzfn78nxmcYz2EMhr/vLPC3nVYTybls7T/5W+f3oVaVQgghMqOJQAghIkcTgRBCRE7eMQLW4ejfv7/R9Ndq166dbDNn1h9zLtcHDOXEp+X60z9jLj81fULGCJir7R8rYxX0JBmPoE9On5D10X0/lGsW6IOntbYrL/waO845161bN6MZj/n666+TbX6nzAfneZ43b57RdevWNZrrCPza8PThx44da/QHH3yQetzLli1LPVa/ZtRjjz1mxt577z2juVZk165dRrPHQ1rciX0T3n33XaOffvppVxEwt5/fBc+XH7/hWge2WeTvkd46f3P8jfnrfPhavje9dd47eJ9hPNH/brhugO/NOEro9Wl9Gxh/YDyB99t80BOBEEJEjiYCIYSIHE0EQggROXnHCO68806jWX+FXp6fz0/Plvno9I/pcTFXuEGDBqUeJ31Axh/op9Fj5DhjH74XT285VDudPjfPC31/f//sm8v3Yk55IeB5Z+38oUOHGu1/HvrZM2bMMLpDhw5Gs67LiBEjjOY6guXLlyfbrFv08MMPG01Pm7Ws+L3Qk73pppuS7WHDhpmxyZMnG00/nXEhaq7NKC4uTrafeuopM8betOxlWyh4vpj736JFC6P96zhU7ydUFypEWv59qO8J46C8N/C+5N9reN8J9VngugEeC++n/uficZ5LbSGiJwIhhIgcTQRCCBE5mgiEECJyKp1JKx7uQX+7bdu2RjMf2M8lDvmkrCPDngI7d+5MPTY/95heHOt80+9lbj/zvOnb+/EN1qKnb83aJqwBwjxm1qL3vT9+LvqCrKdDD7I8ePDBB432c7ady63L5MeVFixYYMaYf89eB4TeL9ds+H0muCbhtttuM5prSZi7P2XKFKO5vsP/nrlOgOs5+L117tzZ6OnTpxvN9SL+9crj5LoOxl3eeustVwgYr/L7RTuXG9/xYxe8j7CfAK/b0HVOb94/336fX+fCaxRYC4y9JKj93yvjCfTxQ/WYeB/ivcO/vrlvxjEXLlxodElJSep7O6cnAiGEiB5NBEIIETl5W0N89CFM8aTt4cM0LKaIMS2T+6a15D/i8dGSrSlpCxSSUGocbQQ+PqalzoXOUSFaV44fP95oPubzPX37htYhbbT169enjjMFdNWqVUb79s+HH35oxkJWUFFRkdFLliwx+o477jDat/j8VFLnnJszZ47RLLHO0iy0Cz/77DOj+T37sOQ1LRqm7JYXtFtpVfC69VMj+Xn4t7wdMZWX3xXvJf5viL8JXgfcdyhVle/l28a0v0Op5KE02bRS6rRFQ/c82o1nQ08EQggROZoIhBAicjQRCCFE5ORdYoKeFaHf7ad10R/ja+lxsRwsfUXGH3yvj54j00VZApswpYxenj/OWAVTBbkvfk5+jrRS0vQ76aWGvp/ygL7nhg0bjGYa8I4dO5JtfjbGBHr16mU0v0eeK55rv8QEz/uePXuMZqkM+vRso8l0SL8MRCjlkOmlkyZNMprlGBh38dMnGTcZNGiQ0YwZFAp666Hr2P/9Mh2U1zXjZNwX29ZS+78x7jtU6pm/dV6DvOZ8vXXrVjPGa5CE3pv3TP+3x98h95UWny0NPREIIUTkaCIQQojI0UQghBCRk3eMIAR9qXPxqcqDivDKY2Xjxo1Gjxkzxuhp06YZ3bt372S7UaNGZowlkxkz6Nq1q9Es/fHdd98ZPXz48NIOO8fj37Jli9GjRo0ymvnmLH/x0ksvJdtvvPGGGWvXrp3Rb7/9ttGMCaxbt87ofv36Ge3H2thCs0+fPkY3bdrUVQSMjdHPZizMP5/8W8YbmAPP19NLJ/44vXTGDNLif87lXgfcn39s3BdfG1pTFIoZpH1unu88l4YZ9EQghBCRo4lACCEiRxOBEEJETt61hkLenPhvcS4+YYgJEyYYzTUaLEvtl0G+/fbbzRi9ccaUuCaB8Qlej36+/po1a8wY62SxfDO94Xnz5hndt29fo30fO1TLyi/H7lxufIJtH3lOFy9enGzzHPI7ZhnzF154wRUC5uPTx+dxleVazHrf8V8fOo6QL5/Ftw/9LQntO42s78XYyNnQE4EQQkSOJgIhhIgcTQRCCBE55baOQPzvw1o3bAVI/3vo0KHJNvPF2bKRufqbN282mvn3rBm1bdu2ZJs1kKZOnWr0I488YvSAAQOM7tGjh9F+HSPnbH8C/32dy41P+OfAudz+BNRsM+ivp2Br1JUrVxo9bNgwVxFk9ajL4qVnpSwtWsvi62f9WxJad5D2WnIu8Vw9EQghRORoIhBCiMjRRCCEEJGjGIHIG+aPs0cx88n9dQXFxcVmrFatWkYz15/9d5s1a2b0wYMHS31v1vSfNWuW0SNHjjS6pKTEaNYxGjhwoNGrV69Otnfu3GnG2Nd20aJFRtO/rVOnjtGMuzA+4RPq4/xfIUscoKwxgzR/PGu9n0KsxSlt31l8/azrH/JBTwRCCBE5mgiEECJyNBEIIUTkKEYg8qZly5ZGL1261OgmTZqU+rfsN3DvvfcazZo79O39/sfOOXfgwAGj/To81atXN2OsB8Se2OwBwPx8xiP8vrusLcSeAOyjwBxw9vBljMGPGbB/L3sxc+1FocjqQfuvz+rDZ82JT+sRkPW9+PpQTaW0fWXtV5B2nkKfg8eZD3oiEEKIyNFEIIQQkSNrSOTN7NmzjR43bpzRLIPsl5wYP368GVuwYIHRtFDY/rB9+/apx+LbN1WrVjVjc+fONbpt27ZG++0gnct9TGfqql/CgumeTINlm8zGjRsbzfLbLLd9zz33JNsvvviiGWvYsKHRLJddKPjdnD592ujyLNdcltdnsXLONh6yWNJsq1CKZ1b7Jq2cxblYQURPBEIIETmaCIQQInI0EQghROQoRiDyhv725MmTjW7Xrp3RK1asSLZZNpqppixDzdefPHnS6I4dOxrtp5vSt3/00UeNZmtKln5mOinLY3Tv3j3ZDrWqZOnu/fv3G83YCPfnl7BgvKFKlSpGHz9+3FUEjAlkbQGZ9trQeCid1H99KHbBFM6ypLJmbXOZlbRjC5Wlzgc9EQghRORoIhBCiMjRRCCEEJGjGIHIG5ZaYIvHQ4cOGe3n/jNfftOmTUbTG6enyrUALHfh+/bHjh0zYyxH0aZNG6NZ3oK6VatWRvtePL1btsls1KiR0UVFRUbzc7MEtn/eeNxk9+7dqePlRWgdQZaWjlnXCWRp6ch9hWICWeIPWcbOZTztvJQ13nA29EQghBCRo4lACCEiRxOBEEJETqUzhezHJoQQ4j+PngiEECJyNBEIIUTkaCIQQojI0UQghBCRo4lACCEiRxOBEEJEjiYCIYSIHE0EQggROZoIhBAicv4P14LBX+X347YAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -2905,7 +2772,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAX+ElEQVR4nO2dZ6xU1feGN5afDbGAIEoTEZBegoBGEEFpUQRpagCNCVgJ+EHFGKMfNGo0RgOo+EEiAmoUQrGiEECB0IsUBUSaqBQBASv6/zZZ67ncs2e4DPxlv8+n82bPPXPmzDmz73nX2muV+/fff/8NQgghkuWUE30AQgghTiyaCIQQInE0EQghROJoIhBCiMTRRCCEEImjiUAIIRJHE4EQQiSOJgIhhEic0/J9Ybly5Yp5HOIYU4x1gjfeeKPT//vf/5yuX7++03v27Mltt2nTxo0tXbrU6XXr1jndq1cvpydNmuT0zp07nW7QoEGpY7fddpvTq1evdnrHjh1OX3TRRU7XrVvX6dmzZ+e2f/nlFzfWsWNHp3mO9u3b5/Rpp/lb8PTTTy/12M477zw3tmbNGqfPOussp995551QDM4880ynTz31VKd57VnNsX/++adMx5L1XvzNiml+jkI+Fz8H913Wz3nKKaX/zx6713/77bf4/gs+IiGEECcVmgiEECJxNBEIIUTi5B0jEIJeZJMmTZzevXu309bXnD59uhvr1KmT04cOHXJ6xowZTl944YVOn3/++U4vXrw4t92+fXs3NmXKFKc3bdrkdMWKFZ2mv1u5cmWnW7VqVeq+GDNYtmyZ04xP9OvXz2nGDH788cfc9u+//+7Gevbs6fSWLVvC8aBQvzvLw+a5jvndZYlVZnn8R+Lw4cOZ72117Lg4Ts8/FmPIei/qP/74I/NYjoSeCIQQInE0EQghROJoIhBCiMQpl29jGq0j+G9RjHUEw4cPd3rVqlVO01NdsWJFbrtPnz5ujLn7f/75p9NLlixxmmsUmjZt6nSFChVy2xMnTnRjXAfQoUMHp+26gBBC2LVrl9P16tVz2n6uK6+80o39/fffTvNzXnbZZU5v3brV6erVqzv93Xff5bYZkzlw4IDTNp4QQggzZ84MxYBrHQrxx3ldFuqtF3Jd03enL1/W+MRff/2V2+Y5iZ0jHkssHmHvD34uvpc9Lv5taeiJQAghEkcTgRBCJI4mAiGESJzkYwRl8SCPNbVq1XK6efPmue3Jkydn/m3MczwWDB061GnmyNMvv+CCC3Lb69evd2P00q3HH0LJ3P29e/c6zdx/m7/P+j6E54bxh3nz5jl96aWXOm2/l3HjxrkxvjfjC6w1RJ+fdWHOOOOM3DZr3/z6669Oc23FhAkTQjGwx5QPheTbxyjk/uRreY+ce+65TrNW09lnn+10pUqVnLbXMOtbEa4P4ZoQwjiA1bx+GRPgNRV7rxD0RCCEEMmjiUAIIRInuRITsaXdZMCAAU736NEjt3399de7MWuFhFB4qty2bducPnjwYG6bpZHHjx9f6muLhU2bDCGExo0bO127dm2n33333dw2baPy5cs7fc455zi9YMECp/k9sJyCtW9Y6oLHzdTTqlWrOs1zfckllzhtUzq7du3qxjZu3Jj5XkwfXb58udO0wKxdaMtohBDCTz/95DQ/d7GIXddZ13lZrddCy0RYaNvR4rL3dgghXHPNNU7zOrH7Y1kHWp/8baAtRUuQ97NNQ2b5lTlz5jitEhNCCCEKRhOBEEIkjiYCIYRInORiBEzBY4yAnm/fvn2dtuWQ6dHu37/faXp19DO59JstAG1K5f333+/GxowZE443LH/AdpNMoRs4cGBum2mT1mcPoWSrSp4rpqpy3LZx/PTTT90YW1Wy5DXjLbfeeqvTL730ktM2XsGyDtw3U1Nt3ORIf9+tWzenbTtKXi/t2rVzmnGWYhGLs2XFEGKtKrNaMuaD3X9sX0wPZRyrTp06TjMF1P6WMAbA92Y8IlYmgqnA9r1ZaoRxpqNBTwRCCJE4mgiEECJxNBEIIUTinPQxAnp1XI5NBg8e7DR9Qev7M9eXecrMDbY+dgglPXUucbe+Ils9nghY0qBGjRpOL1q0yOkGDRrktvnZmKtPD5V52CxRwZxuu/yfufux77x169ZOT5061emGDRs6bb+3jh07ujGuj3jllVecfuCBB5xmKQ2eY1tSm9cLX1uzZk2nH3nkkXA84LqBQlpZlrXkRNbfMx7I1zJGwGuK1w3/3u4/tpaC++L1zt8OXv923UzsOjia8jJ6IhBCiMTRRCCEEImjiUAIIRInuRgB/cuePXs6zdxhthK0+b70+RhPoAdJzzLmSdp1CcwrPhF8++23TjPvun///k7v2bMnt82YAPPnbRnpEEp+Xq5ZYOtLO858e7v2I4QQVq5c6TR9eq4HadGihdP2Gnj//ffdGOMJrVq1ctquCzjSsbHGkl0bwM/MVqFca1EsCq33Y+/BQutvFVrXyL6e9xv3xXUXLG0eW4dg98dSz7F1BLzX+dvB3yl7fzA2x7pFR1PPSU8EQgiROJoIhBAicTQRCCFE4px0MQJ6hszHJb169XJ6+/btTme1u6OvR1+Qx2I98xBKrjPg31vNevzDhg1zOpYrfyxgLX362ZdffrnTtrY+66HQ1+Tfsq5/7969nWYLSNszgJ4/1yAwdsP4BGs+cf2HrZM0ZMgQNzZ//nynZ82a5TRbcjJeUbduXadtjwrGVXj9dOjQIRwPYjGCLN8+FhOItY6N1TUqZA0DYwL8brjvrJggfwsKXVsR+1x2rQBji9WqVXOadbzyQU8EQgiROJoIhBAicTQRCCFE4px0MQLW9WZOeZs2bZy+4oornKa/Rr/Z1syhlxxbs8DaRMxjpgdvvesffvjBjdGbHjlyZCg29EibNWvm9Nq1a522viZjAuy/S5+TnivrqTBv264j4HtxLQjjEbwmOnfu7PTo0aOdtr1s2XOCPjNryNxwww1Os0cx4wD2c7LGDNdasM7R8SLm62f1Iyh0XyQrXsH4IO9P2+c6hJLnk/cv43B2f1yzkBXvO9Lr+Tl4Xdnzwt4HLVu2dJrrS/JBTwRCCJE4mgiEECJxNBEIIUTinBQxAuufMSZA7rvvPqeZQ06flTEHm4PO19Lfpa9N/5h/zx7I9nPRrzwRMYJNmzY5bXsSh1CyZ4L14unpX3311U7TE50xY4bTPXr0cJq+v43tPPzww26M9YAY96EvzWM5cOBAqeOs78N1A23btnV63rx5TsdqLtn1EjyH7CHNWlDFoiw9BApZc5DPOLGxJfrwjAmwb0Xsvbk/SywekXWcIcSvOXsdcF0LYwTsi50PeiIQQojE0UQghBCJc1JYQ/Yxiyle7du3d7px48ZOb9682WmmkDFVy47v27fPjbF8MdNLmUpIK4iPnja9lI+tLOtcv379UGyY7jplyhSn+ehtrTA+6tLmYEmJq666ymmWibAlJULwj86rV6/OfG2tWrWcZiorPwdLN9jvmWXL77rrLqeZ9ksraNCgQU6zLLW1mvgdv/nmm06z5HWxKLQ0dJaVVKj1EzsWa8mwlAivqSZNmjhN+5X3I21i+94cy7KRjgRbufI6sL87PGe0ofi580FPBEIIkTiaCIQQInE0EQghROL8J2ME9MSySjDfe++9TrMUNPdFH5/lCux7HTp0yI3RQ6dXR1+cPiJLOFgv8PDhw5nHTV+7GDA1t2bNmk6zNPQnn3yS26Y/S5+TPj7LVbAUCOMzNoWO5ZnZapLppN27d3faln4OoWRa5nPPPZfbfuyxx9xYu3btnGaZc37Hu3btcnr37t2ljs+dO9eNjR071ukRI0aE40Gh7Sat916odx5776xSDbw+u3bt6jTvbRKLdVhfn79BPE7+rsTK4zNekVXOgmnpihEIIYQoGE0EQgiROJoIhBAicf6TMQIuz7beNb1o5l6zTALXCXD5dtZScHpxsfZ0zBXOykvm3zNGQI/xaHzBQmEMgJ+Pvr3N52eZaXqq1FWqVHGaMQS+t/XSWUr84osvdtqWkQ6hpC/PdQY8li+//DK3zfO+YsWKkMW6deucbt26tdPTpk0r9VgYY+K1HPO8TxSFxAViufyE95C9Bxs1auTGWOad93ZsDQOPzf4WZHn6RxqnLuS3IBaT4W9FPuiJQAghEkcTgRBCJI4mAiGESJz/RIyAnlhWqel77rnH6R07djhNH5UeL318Yv035oTT14uVpuXr6QHbz8kytRUrVnSaZZmLAY+f6yiY5967d+/cdpcuXdwY6wHxb/m9sLwz/V2bp833mjlzptOs08Q1GKwPxHLi48aNK/W9atSo4XQsn/z55593mrWKxo8fn9tmKW5eq1w/cbyI1QvK8rdjfnds3QDvC7t2gOsGYjG9rLaXR3q9vQZjJatj9z5fz/3ZGBqvobKuzQhBTwRCCJE8mgiEECJxNBEIIUTi/CdiBLH83p49e+a22QJxzZo1TtPXZ88A+m3U1mdk7jv9SsYy+Hrm+/L19ljZJ6Fq1apO08cuBuyfwM9jW1OG4I+ZNf/5ncZqKcXqMtnzwbUh/fv3d5qxGNYS4utXrlzptPX12VKTrSZ//vnnzON+7733nGY+uV1HcPDgwczjmjx5stNjxowJxSDWhpFktVzNqhV0pNcz7sbzab+7Zs2aubFYrn6s/wC1/e2I5e5z34yv8ZrNqqfGffGcZNVeKw09EQghROJoIhBCiMTRRCCEEImTd4ygrL1FC9l3rGZPpUqVnH7qqady2zt37nRjXDfA3GvmFtMHpPdn/Td6cczj5udgfXTGBPg57Tg9xVh8oRjUrl3baebbsx6QrYXDOkWsA8Ncf9YDotfOmlK2RhT7H1evXt1pfg9cg7Fo0SKn2Z/gwQcfzG1znQp7ZE+YMMFprn/o2LGj0+xVu2TJktz2tdde68Z4ztj74HgRWwtgx2P59oX2Db7pppuctjECnutYbSHqWIzP3pO8Hxl7ZCyDv1OMEfA82LhW+fLlM1/Lc5QPeiIQQojE0UQghBCJo4lACCESJ+8YQazuRlbeN8eyfPcjvRd5++23nbZeHvPp2UeYHiy9u5j3bnN22f+Y9X/YZ5f56Q888IDTTZs2dXr79u2hNI5ljCZfXnvtNadZ++ajjz5y2tZ9WrhwoRtjbIa+PfPxGzRo4DTPld3fgQMH3Nh1113n9OzZs53mNcAYA69fGyth/IF1i1hL6OGHH3aax2p7HYTgYwSMwbCPAuNIxYKeNOH5st48x3juuW/WhWrcuLHT7Blt167wXmaMgL87sZo9PPas2AdjkYwZ8BpjDI3HZt871tuA65nyQU8EQgiROJoIhBAicfK2hvjYxMeumC6EJk2aOP3oo49m7tu2JuSjJEsz8BGNcBk/rSGbIso0LlpBbI33/fffO/3ss886HXvkO9EMGjTIaX4PzZs3d9p+XpbOZYobU1FpsbAsBMtZfPDBB7lttqb8/PPPnV61apXT/J6WL1/uNEtLW3uCrU1pTTJ9lJbBvHnznGbpZLs/Wlrt2rVzOstKPJbQYuFnom1px2kJ8n6lvdqyZUunW7Ro4TSvK3u/0q7h9VroeBY8Dlo7n332mdOTJk1ymuXMs1pwxmzho2lbqycCIYRIHE0EQgiROJoIhBAicfKOEcQ8/8qVKzvdqlWr3DY9WKY3sXRBtWrVnKZPTz/Zph6yPHOFChWcjrWH5LFx3KafMkZQiKcYQrxFoo3LxPzLY9GuLgbTE1kG4umnn3b67rvvzm0zVsNyHAMHDnR6ypQpTvMa+eqrr5zu3r17bpslIlgGgvEFlmpgKQemqk6fPj23zbLnI0eOzDxunrNu3bo5/cUXXzht01NZVpllCjZs2BCOB0z5ZOov7wub+lunTp3Mv2V6N733mP9t74tYu8iski4hxOOJNpWcvxujRo1y+tNPP3Wa9zN/Z/i5LbF2nUfTslRPBEIIkTiaCIQQInE0EQghROIcdavKoUOHOk0v1PpvLCFMf5ut1rZs2eK0bdcXQkmP1+YiZ+UVH+m9me9Lr4554nac6wYKhbnCPJas3GH6m8ztLgZs6cjyHcOHD3falgBn/IN+N338Z555xml6wyx3Yc/d+vXr3RjLMz/55JNO9+nTx2n61Nzfrl27ctuMiwwePNhprhOYO3eu07wGGE+78847c9ss4bF582anGR8rFiyrwbUPLAdiXx8rz8zrmOcn1tqykPVLha51Yoxh3759ue3Ro0e7salTpzr9448/Os2y0/aaCqFknNR+Tp4jlho5mra1eiIQQojE0UQghBCJo4lACCESJ29jecSIEU7bEsMhhLB27Vqnrb/N3GF64fQB2V6SnhjzlK13x5xaesvcF2sLMcbA0r9cl2CJtfPMyg0OoaTvb/8+qwRuCMcnRmDXBYRQMv7Cujr9+vXLbTPfnusK3nrrLaf5vdEbZt0mW2+K8arFixc73aZNm8xxvlfr1q2dtq1Sb7/9dje2bt26zH2xHtCCBQuc5r3yxBNP5LZZl+fjjz/OPM5iwZgd24aylay9NlmXiNdtrAx8bK2O/XvGI2LvFWs3yfvTxqn4XbCMOq9n7otrQljfKqv9JONvR1PnTU8EQgiROJoIhBAicTQRCCFE4uRtLE+cONFp+pH169d3mjnmFnrnXEfAWhn00+i72r/nvukx7t2712l6d/wcrAdUFuidbtu2zems/gP8XLGaSMVg69atTvPzPP74406PHTs2t/3JJ5+4Mdbc6dSpk9PM5X/jjTecZo2azp07l3pcfG+uK5gzZ47TAwYMcHrMmDFO23O9Zs0aN8ZWk6xbxPgFe29UqVLFabvu4IUXXnBjvAbYR6FY8B6K9Xew9yDX5fC7Yj+CrLr8IZT0/a2OrVfi38ZievwNtNcVYz+xOkWM+THuyWOxv3mMsfI4tY5ACCFEwWgiEEKIxNFEIIQQiZN3jIB527fccovT7EfQvn373DZrrtNDpG/KWibMPabXt3///tw2fT/6Z/Ti6KvSo9yzZ0/IF/p+zOdlbjB9xCxvj3ERrmc4HusIDhw44DTr5vB7tcds+/yGEMLq1atLfW0IJa8B1mZhfRvbn+Cbb75xY/Sh6cuzXhDz5Nkr2F7PrCnToUMHp5ljz961devWdXrlypVODxkyJLfN62fjxo1OT5s2LRwP2O/h66+/dpq+vr1/ed3ye27YsKHTrOfF3wr+7ljos8fWK9naQSGEMGvWLKdffPFFp23MLLZGgfEKxndYJ4q/cfZ3jL9hjKfxdygf9EQghBCJo4lACCESRxOBEEIkTrl/aaSV9sIC+/GWBebyszY3+xHUq1cvt80aNuxtMGPGDKfZ+7Ys0Cekz9elSxenbZ59CCXrk9hzTv+SnnmLFi2cPppc4hjDhg1zOtYL2MZu6KXbHsMhlMy/Z8yAMSnmbdt6Qffff78bo3fOWkP0ihm/uPjii5223nCjRo3cGD1+xqjsOQkhhEcffdRpnidbe4j+Ofvgvv76606zj8Kxgh40Y3hZOfT8HeE6Ht4zXHdg7/UQSsYYbEyB5ytWZ8z2og6hZIyA637o81v4OXnOeM2xtwT3bf+e54z1qm6++Wan84lz6olACCESRxOBEEIkzv9La0iUnTy/1oJ46KGHnN6wYYPTLHNhU/0OHTrkxmLlhWl9MY2Qdk/fvn1z2yxvsmzZMqdZKrpt27ZO83PxUdxaBixTzhacfG/C0t6jRo0q9dhom7D0O9N758+fn/neRwvTMGOpy9bW4GtpKzHtkqmStJ2YPmqtI/4trTLaxrRneI3y/NuSMLHfR7bkZMrnyy+/7DS/S2v18r2mTJniNNuj0o48EnoiEEKIxNFEIIQQiaOJQAghEqf4dQnESQPLZNNTZUqcTQNmGemmTZs6bctIh1CybAFLHbM8uPVJmXrHMg4sYU3veNOmTU7Tr7VlJGyLzBBC+PDDD51mSWvGNpgyzFIctpzDHXfckXlcsVaoxwqmQma1WA3B+/4soczXMgbAtGm2dGQa8dKlS0vdN4kdC3VWmfhYjID74nu/+uqrma+3Pj9jNCw1wusiH/REIIQQiaOJQAghEkcTgRBCJI5iBCJvmBPPksss/2yXtjOeQD+bXjlboTIXmqUHbOlolgagj8x1AfT5WSqDnqtt1ci4SLt27ZxmGQOuh2CrS3ritoQ2S6YzbsK4S7HgWgB651leOmE8h945S43EyHp9LAbANQzUWfvjZ47FUbiuZuHChZmvt8fC4+I55JqFfNATgRBCJI4mAiGESBxNBEIIkTh51xoSQghxcqInAiGESBxNBEIIkTiaCIQQInE0EQghROJoIhBCiMTRRCCEEImjiUAIIRJHE4EQQiSOJgIhhEic/wPEr4ePkLbKmgAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -2915,7 +2782,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2925,7 +2792,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2935,7 +2802,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAaC0lEQVR4nO2dd6wV1deGN/YGVkBBmoCA0kGKGAQpIiogJQQjKk0iiTWYGILGWDFqokSJmIh0FZUgBkFAwKggVYqAgHQBCyBi799f32St51xmc/See8lv3uevebPPmTNnZs/szLvWXrvMP//8808QQgiRWY4r7QMQQghRumggEEKIjKOBQAghMo4GAiGEyDgaCIQQIuNoIBBCiIyjgUAIITKOBgIhhMg4JxztB8uUKVNsP8p95Tun7ZJLLnH6yiuvTLZffPHF/7TvGI8//niyPWbMGNf25Zdf5rWv447z4/Dff//97w8MFGKe4DPPPOM0/+/evXudbtmyZbJ9wgm+q73xxhtON27c2OmaNWs6feDAAaf/+usvp9u1a5dsz54927XZ/hFCCNOmTXP69NNPd7ps2bJO79ixw+lbb7012X7//fdd286dO52+6KKLnOb/tscdQgiVKlVy+qyzzkq2v/32W9e2bt06p88//3ynJ02aFArBSSed5DT7Wj73Nz/Le+KMM85w+rTTTnO6SZMmTjdv3jzZPvPMM13br7/+6vTWrVud3rVrl9O8H88555xwJLZv356qf/rpJ6f//PPP1N+itueQ5yz2bP7jjz9S20PQG4EQQmQeDQRCCJFxNBAIIUTGKXO0Ref+S4wg35hAjx49nB44cKDTe/bscdr6bU2bNnVtixcvdpq+4C+//OI0PcnbbrvN6cOHDyfb06dPd23lypVzesmSJU7PnTs3lBSFiBHUq1fP6RtuuMHp7777zunvv/8+2e7UqZNr27Jli9P0fumHd+vWzWmeW/t/6WHbWEUIIezfv9/pjRs3pmr60DZewf5Dn57HcuKJJzo9YcIEpzt27Oi07WPcN8/pV1995TRjWMUF/0Ps/s7H365YsaLTvHZ8NlSrVs1pe/8y9mPjLSHk+vT79u1z2t7rRR3rzz//nGwfOnTItf34449Oz5kzx2n2X947sZiBhXEV8vvvv6e2h6A3AiGEyDwaCIQQIuNoIBBCiIxz1PMI8sX6VrH8+IcffthpzhOgX0xvz/q0y5cvd23nnXee08wFZs44P8989Q0bNiTb9EoPHjzodJs2bZxu1KiR0+PHj3ea/zOfc1gS9OnTx2l61vT5bR73b7/95to2b97sNL3g8uXLO805C/z+2rVrk+06deq4Ns4D6Nq1q9M1atRwmvnk9I5tn/jhhx9cW61atZzmvADOI+D/XLZsmdP9+/dPtj/55BPXxjx59v1CkU9MgJrf5T3UpUsXp6+77jqneb/ynrH61FNPTf2tU045xWnOVWGMgPeg7QecJ8Br0717d6cZr3jzzTedZuzJks/5Plr0RiCEEBlHA4EQQmQcDQRCCJFxChYjsLVlmMfaq1cvp5mnTY+WviL9t+OPP/6Iv8X83di+Lr30Uqfpe9v4BH1v/vbnn3/uNOMTgwcPdvqJJ55wOs1bLcQ8gRis1fLuu+86zfNhr8uUKVNc27Bhw5ymV848a7azdtGIESOS7ZkzZ7o29jfO56hateoRjzuE3P45b968ZJsxJfrQu3fvdrpu3bpOt2/f3mnWD7J9xsZBioL1mQpFrO/lU1uIMZW+ffs6zXkYjNkxDmDjasyvP/nkk51mfMfOeynqt7g/e7+zz8Tu1xYtWjht5ySEkBszsPsrxL2vNwIhhMg4GgiEECLjFMwa4muVhWmVfOViqQZO3+ZUejuVvHLlyq6NZX457fzcc891mq+L27Ztc9qWt6BVwvIU33zzjdO0TmhvkDRrqDRgaV2+ln/99ddO2+tqrZsQQvj000+dvv76653mdWBqH4/Fpl3eeeedro0WHc+lTQkOIbfP0O6xZa3Zn5iSOHny5JAG02aZXmqtyIYNG7o22k68LwpFzPZIa6eF0rlzZ6dp09Gu4T3H37IpnrSVaN1yX7wfaQvz+/YZFyudwe8yBb527dpO85mYz7Pg3zwr9EYghBAZRwOBEEJkHA0EQgiRcUolRlC9enWnuZQap1/Tu6PfZks70JenrlChgtP0CZcuXep0lSpVnLbxC8YXON2d8H/RY+f/tD7isZA+yhLf9KT5/2w8hctDjho1yukZM2Y4zTIjXAazZ8+eTs+fP/+Iv8WSE1w+0qaDhpAbk2K58eHDhyfbCxcudG1MD+V90KxZM6eZJsv0ZVvOuHXr1q5t5cqVTnfo0CGUBPmWNLB+N337tm3bOs0yDuz3jDHQS7exJT4nuC/69Izh8dqxtLQ9Fp6DWDkLan6fsSdbwqI4SkoQvREIIUTG0UAghBAZRwOBEEJknGKLEeTjYcfy6ek1M4ZAb89OHedUbe6b3h2XveTUb5aWtrnyjD+wFC39Xv42PUh62evXr0+26Y2WRllq+pacss+yvQ0aNEi26fGPHTvWafrfnDfA8grMN7fnjnEdlvTlHATGevhb9LGtN8+4yRdffOE0y1twzgL7J/vARx99dMTjuuCCC5y2cZIQQhgyZEgoBP8lRkBPn3NvuC/2e/Y5PhvsPcj7i/vmd/n5WMnstONMK31R1G+zpDvL0fDZYonN4zga9EYghBAZRwOBEEJkHA0EQgiRcUokRsBSz4wB0FtmrnFs+UirOS+A+2btEvp+PFbGHKyfzCUQmzdv7nS1atWc3rRpk9M8VtZJsjGCY4HPPvvM6Xr16jnN5SRt/RQuwdiqVSun6f3SU+3Xr5/Ts2fPdtp67TxvrBnDXH5eB5a8ZgzBznlgvR/mh/Oacg4D971o0SKnbd9mXvyKFSucZuytUMQ86LSYAe83xp3YznggvXje37Yf8LvcN58zjNewTzIuZ+cV8Jxw39SMEbDfcIlT288KUXdMbwRCCJFxNBAIIUTG0UAghBAZp9hiBPR0rZ9Gr5zeGz3FsmXLOs2YAP02m89PT5++Hv1f+tr8bdbYt/nt9BSZv07fL+0chZBbB8lSGrWFCHObuaYAlxhdtWpVss1zwT6xc+dOp+mD8rrS17dee8WKFV0bYzmNGjVy+tFHH3Way2hyTQo7h4H53ewD/J8TJ050umPHjk6zb1tPnPMfuMylnXNQSGJ9Ma02P88P5xEwBsB7jPcQ+5WNo/C5wXgEzzXhc4oxGPu/GIfiPAIeZ2y+E+cV5HP//5tnhd4IhBAi42ggEEKIjKOBQAghMk6xxQjSat8wVzq2vie9PHpezA+2/hrryvC4mMdN3zWWa2zb+b94nKw1ZD3zEHL9TvqnlrT1HUoKeqRNmjRxesuWLU7beQRcbzdWK37OnDlOjxkzxmnWhBo3blyyzbkgvXv3dnrBggVOM260bt06p1kfyNKlSxeneZ0+/PBDpy+++GKn6RVzrWZ7bJwfsXHjRqfptx8r2GvLdSZ4r7Mf0KdnDIFzktLWEY6tYcx4D+9nXtu09ZH5HInVPOOx8n/lg2oNCSGEyBsNBEIIkXE0EAghRMYp2JrFFq5RTGIxA3rp9Kqt30bPn7nvNWrUcDrmVdPLsx4l64Uwd5g1kmLrsfJYLcfCPAL62VyjmTnz1t9m/IDfrV+/vtMPPvig06zFz3hKjx49ku3Fixe7Ntbk4XVjjIA1lZjTbddW4HHxHJx99tlOc54K+x/XxW3Tpk2yTT+da0ZzfYxjBXvP1KpVy7XRW4+t/ZsWHwzBxxTo+fO5EVv7gPcr72+7fx4Xn1n8HzwW7ps1qtJqKBVH7SG9EQghRMbRQCCEEBmnRNJHaXnwlYzTrwmnb/MVzu6PJSOYLsrj5Os1U8SYxmVLG/C4Dx06FNLg6x9fF8uVK3fE7+azFGihYOnol156yemuXbs6PX78+GSbyz3S2mEqqi31HEJuWQiW/li+fHmyzf7GlEWml9IqYp+gtmmaXIKTfZX97/nnn3eaKca0od57771km2XOuVznI488Eo4F0voml9eMLd8aW4Yx7bdopdGu4XOE7bSdYqVu0oj9Dx5L2rMgdu+rxIQQQoi80UAghBAZRwOBEEJknBJJH6VPGlumjd4bUw3p/dnS0CxPTH+Ynj+XhGOKJKe4W802Hic1vWuWw6BHaT9/8OBB11YaMYPVq1c7zXPNshDdunVLtm25iRByUzSnTp3qdN++fZ1mmqWNCYQQQufOnZNtLglKr7dmzZpOs4QE+9dVV13l9OjRo5NtertMC+Rxc19MZ2Z5C3udec7YnxiHKSlifdGeIz4LeP74bGB7rDSDjcPxusd8ev424XPKLnvL3+K+GZvkvc74Q1raOtNHY//raNAbgRBCZBwNBEIIkXE0EAghRMYpkRgBSy3Qh+c0fPr2I0eOdPrpp5922k7zZ64+l3+k90bfL81zDMH7gvXq1XNts2fPdrply5ZO0x+lH8x5CPbYGSOIeYyFgCWSmRPOHPjJkycn25wH0KdPH6e5VCXnGbDk8oABA5yeNm1ass3c/sOHDzu9aNEip/k/WAbClnkIIYQGDRok22lLZoaQG1dZuHCh088995zT9H/tb7F/zJo1y2n2r2MF62/HyiuzXzNeyPPD+9eW6GB8hvuOee3UjANYzVgGYYwgtiQn+5F9bjGWwX1rHoEQQoi80UAghBAZRwOBEEJknILFCGzNFfpd1mcPITev+80333R6woQJTo8dO9ZpWw6WniGX76OnS2+Ofhtrftgcc3rmderUcfquu+5ymt40ywbb+RAhhNC6detk+/PPP3dtpVFriB4rPditW7c6bfvA3Xff7dp43pcsWeI0vXXGU1hTaunSpck24zqE+fe7du1ymjECnntb6px9l/EJLlXJ2kK2llAIubGRuXPnJtuco3DhhRc6vX///lAaxMrI235QsWJF1xar70MYC2MftO3cV2yeAO/9mLbE5iTE5gnwfmYftOeQMdZYbONo0BuBEEJkHA0EQgiRcTQQCCFExilYjOCKK65IttNqA4WQ68OvX7/e6WuvvTb1t6wvy7xj5ohbLzmEXI+SmnMgrNdHT5b1dJgzvmfPHqfpAzJmYHPISZpfWSi4jGKsdlKXLl2SbcZmGC8ZOHCg06yrwzgTfdCOHTsm28ynZ10i1hbivrn+AM+1nefCOQb0pbk+Af3dNWvWpH7exjs++OAD18b1B/bt2xdKg9jSsnY+DNeCoHfO+l2E3js/b581sbUNCP8H5xkQ+6yJzU+KrWXAeQVp6xPwuVMc8UK9EQghRMbRQCCEEBlHA4EQQmScgsUI7DoAsZodzOPu3r2706zZQw/X5lfT06d3R5+b0JvjnAcLvVB6d5xHsHv37tTv89jq1q2beqwlDWvpc74H/4+Nmbzzzjuu7eKLL3aadYpYX4o+PWsX2fgEYy+M3fA6tGvXzmnm/rP/2v/J+MMXX3zhNM8Z4yiMCzGOVKtWrWT7oYcecm333Xef01x74/777w+FIFbvnu021hXLn2c7zxd9+7S6/bH4Q2yNAOq0dYZjcxR4nNx3Wh8LwT/Xtm3blvpb/wa9EQghRMbRQCCEEBlHA4EQQmScgsUIbE0V+u5pXlsIuTXLWU+Etfmtj0ivmfuO1aHhbzGv20Ifj7EL+uCsFcM6SPQ/rdfN2Edp1JWZMWOG05wfwutma/TwujB3n/n0t99+u9P0iu0axSF4v5y5+tQ8bs5Z4HXhdbPnnvum579582anOfdi0KBBqcdqazA99dRTru2ee+5J/e1CEattw/vbxrro07PP02tnvn3sWOz9HvP4ObeFMYXY9+2zInYOYnMtqHmeeP+koVpDQggh8kYDgRBCZJyCWUP2dTCW8sVXdZZ35iscv2/3z2Uvv/32W6dpFXHftJ3SrCG+tnJJREJbiq/BX3/9tdPWkmAZjtKwhlj2mCmhLLFsra1evXq5tk2bNjlN+6V69eqpxzJ+/HinK1eufMR98VzRlmIpaFsaI4TctF573VkOu2nTpk7T0mIfYXoyj+W7775Ltnv37u3aaEWydEahiKWP0ppIszVox8TKwnPfactR8l6PlZxge+z79lhjS1Hmu5wkP29Lc8S+K2tICCFE3mggEEKIjKOBQAghMk7BYgRVq1ZNtnfu3OnaWKKVvmBsujV9fbs/W/I2hNx4AqGHy/Q9xgHs/njc9AVj/jGXX2QcwPrH9erVc22FmGYegyltLAXCeEq3bt2SbXrf9Fv79+/v9KhRo5zu2rWr0+3bt3d62rRpyTavIUsv0JcfOnSo0+yv9GtbtGiRbK9atcq12VhFCCGsXLnSacaBmjdv7jSXqrTlGRiTYX+JlU8pLmKlGXgf2DRqxm94r7OP2WVoiyKtxASPi/A42X/5PxmPsDE/tsV8+lj8gfFDXmtLLFX1aNAbgRBCZBwNBEIIkXE0EAghRMYpWIygfPnyyfaWLVtcG707eu30uOjVpeXsssxBbJp4rFQtj83OeWCsgh4j5zDQ57e+dgi5+dbW873ssstc26xZs0JJw2UGOWeDS4xaP5ylnpnLz/M+ePBgp20+fQi5JbDt/mxpixBCaNKkidN16tRxeuzYsU4/++yzTg8YMMBpu/wpz8mCBQuc5jW98cYbnb7zzjudZtxl2bJlybZd/jWEXP+c8YVCEVsmlfNlbNyO9xPjhbw/+Xner2nzCGKxi9izgO2MPaXtm9eG/ZuxR8Z3eOy2NAnPSawE9tGgNwIhhMg4GgiEECLjaCAQQoiMU2wxAvpWtiQuaw3RH46VcKU3x9+yZYPp2RJ6zSzvzN/isVivbseOHa6N/4M1k2J+KH1De96Yn14a2Jz2EEKYP3++06zTZJdpfOutt1zbyy+/7PSQIUOc3rt3r9MsFc34RMWKFZPtSpUquTZeJ8ZuDh065PTcuXOd5twUe13p5bJv23hCCLnLZNaoUcNpHrudL8J+v3DhQqcbNmwYSoJYnjpz++3n2UYvnfcQnx2xeKElFl+I1RoiPBZLvnHNtPkPRe3P1u3ic4IxAs0jEEIIkTcaCIQQIuNoIBBCiIxTbDGC+vXrO209r1htEvryaesNFPV5O2fBemkh5Ppl9LG5vB9jBml1wXkc/F/0njmfwtasCSGEjRs3Om3jAqw9Ty/6wIEDodCMGzfOaea1M3980qRJyTbnUPDczJs3z2l6x7Vq1XKaczjsGgJcHpJ1jmw8IYQQGjdu7DSvA4/VzungeWf/W7t2bUjjmmuucXr58uVO2yU5p06d6toYJ/n0009Tf6u4oLdOL54etq3dxHUmYv42axOlxR94LLwfY/V/+Hne+/xftj02t4I1zfj52Hmw93ts2cvYsRSF3giEECLjaCAQQoiMo4FACCEyTrHFCAYNGuT0f/G0Yl4e68nbeiP04ljDg9/t2LGj0/Qw6RfbGALrnNBDpM/NY+MawHv27HHa1i7iZ1mPn7V3CgFr9jDmQb/7tddeS7avu+4613bHHXc4vX37dqeZ608vnv74k08+mWyzdjvXUq5du7bTixYtcnrgwIGpx2LXQH7llVdcW6dOnZxu1aqV02vWrHGa/ZNrVDzwwAPJNtdptmt+hJD7PwtFrM4/fXx7D9m5JSHE1/QgsXkG9p7kc4W/FVsHJW1eD3+Lz4JYDICxj9j8JfssiM05UIxACCFE3mggEEKIjKOBQAghMk6xxQgee+wxp209Fuab0xdl/nnMTzt8+LDTtuY7YwDMfWcOOdfCZX76xIkTnbY55XXr1nVt9EZZ+4U1b2zdohD8WgchhPDxxx8n26tXr3ZtrJlUEvA60JvkerytW7c+YtvixYudZp1+/l+u/0w/t1GjRkf8rX379jm9YsUKp4cNG5b623aOQgghTJ8+PdkePXq0a+McBvb1Dh06OM01j/v16+f066+/nmwzJsCYE+cwFIpYLRvev/Z60L+OrT/AOv6x2vu2XlC+6w3E6vynxTP4DGN8MG2d9aKOjb+9a9euZJv34b+JCRC9EQghRMbRQCCEEBmn2KwhlkAYMWJEss1yuUzvi2HLTIcQwuWXX+60fc2y09lDyH01Z1lgWklMzeLrtn2VZ9kD2hc9e/Y84ndDyH2lo93DJRRLG5bnYEooSznYMtU33XSTa2NqHpeX5HmnHchXa2uh8Lzztd2mf4aQ2z9XrlzpNJc/tdeZqagzZ850+uqrr3a6WrVqTvN/33vvvU7ffPPNyTbLuDCltnnz5qEk4D1Cm473HP+jhSmZvAdol9LOSbNYaNXSbokdN6032j32WGjt8LssP85UbH6eNrItVRJbfjeWglsUeiMQQoiMo4FACCEyjgYCIYTIOMUWI0ijW7duTrP8Msv8Mt7A0gv0WW1638iRI10bfVRbsrqodpZ3pldtPUumh9KLZuobmTJlitM2XZTE0uiKI4UsBtMyWTKZHustt9ySbDNGYNtCyE3ztd54CLnXZfjw4U4PGDAg2W7ZsqVrmzFjhtP0evn5OnXqOM3lT22ZCMakevXq5bRN+wvBxzJC8KUDQsiNf9nSG1u3bnVtjNG88MILTjNtu1DQo2aqpC3hwVI0jAHw2rB8edpykSH4lG5eR/rwhLFLanrz9trz2vC5wnIsfK4wNsK4itWxFNpYCZAiv5P3N4QQQvxPoYFACCEyjgYCIYTIOGX+idV8/v8PRqaVHyvYchMhhNCsWTOn586d6zT9Nua3v/rqq06//fbbyTZLFWzYsCG/gwU8x/bS5Lsc3VFe1rxgKQZOuWeMwB5DhQoVXBu9cS5VyfIdzP3n9+11Z9lo5ngz95zXnPEYu2RoCH4+yPr1613b0KFDnd62bZvTLCvCnG8ee5UqVZLtWbNmHbEthBDatm3rtI2bFCc8X2n9NgTfdxlviZVWiJWJYLmFtH3xXMdKSsTmS3CegoXxQt6vLBfCPsk4qS3ZY7eLOk7CmE1R6I1ACCEyjgYCIYTIOBoIhBAi4xx1jEAIIcT/JnojEEKIjKOBQAghMo4GAiGEyDgaCIQQIuNoIBBCiIyjgUAIITKOBgIhhMg4GgiEECLjaCAQQoiM83/IbN1Q07k46gAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -2981,78 +2848,19 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "metadata": {}, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2e9d28e7727041ba8bdd65e7f6873d58", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/1875 [00:00 Date: Sat, 17 Aug 2024 15:43:05 +0100 Subject: [PATCH 13/51] added new dense model and unet --- solution.ipynb | 404 +++++++++++++++++-------------------------------- 1 file changed, 136 insertions(+), 268 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index e4d4794..7b98abd 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -302,7 +302,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -537,31 +537,26 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "selected torch device: cuda\n" + ] + } + ], "source": [ - "import torch.nn as nn\n", - "import torch.nn.functional as F\n", - " \n", - "# Dense model:\n", - "class DenseModel(nn.Module):\n", - " def __init__(self):\n", - " super().__init__()\n", - " self.fc0 = nn.Linear(784, 256)\n", - " self.fc1 = nn.Linear(256, 120)\n", - " self.fc2 = nn.Linear(120, 84)\n", - " self.fc3 = nn.Linear(84, 10)\n", + "import torch\n", + "from classifier.model import DenseModel\n", + "\n", + "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", "\n", - " def forward(self, x):\n", - " x = torch.flatten(x, 1) # flatten all dimensions except batch\n", - " x = F.relu(self.fc0(x))\n", - " x = F.relu(self.fc1(x))\n", - " x = F.relu(self.fc2(x))\n", - " x = self.fc3(x)\n", - " return x" + "print(f'selected torch device: {device}')" ] }, { @@ -574,7 +569,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -607,7 +602,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -633,7 +628,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -647,15 +642,18 @@ ")" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Initialize the clean and tainted models\n", - "model_clean = DenseModel().cuda()\n", - "model_tainted = DenseModel().cuda()\n", + "model_clean = DenseModel(input_shape=(28, 28), num_classes=10)\n", + "model_clean = model_clean.to(device)\n", + "\n", + "model_tainted = DenseModel(input_shape=(28, 28), num_classes=10)\n", + "model_tainted = model_tainted.to(device)\n", "\n", "# Weight initialisation:\n", "def init_weights(m):\n", @@ -682,7 +680,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -704,7 +702,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "tags": [] }, @@ -713,8 +711,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "938it [00:07, 118.31it/s] \n", - "938it [00:07, 118.33it/s] \n" + "938it [00:08, 114.99it/s] \n", + "938it [00:08, 116.51it/s] \n" ] }, { @@ -728,8 +726,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "938it [00:07, 119.75it/s] \n", - "938it [00:07, 119.71it/s] " + "938it [00:08, 116.86it/s] \n", + "938it [00:08, 117.20it/s] " ] }, { @@ -785,7 +783,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -794,13 +792,13 @@ "Text(0, 0.5, 'negative log likelihood loss')" ] }, - "execution_count": 19, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAACe5ElEQVR4nO2dd3gUxRvHv5eQSkioKbSE3gOhhaKgEIqFZqH+pEiRJh0R6SDSiyJNEFAUKVJEmkAg1EgJRkAgQCihBEJLQgKk3fz+OHK5frt7u7d7l/fzPPfc3ezszDu7szPvvvPOjIoxxkAQBEEQBOEkuMgtAEEQBEEQhJiQckMQBEEQhFNByg1BEARBEE4FKTcEQRAEQTgVpNwQBEEQBOFUkHJDEARBEIRTQcoNQRAEQRBORQG5BbA3arUa9+/fR6FChaBSqeQWhyAIgiAIDjDG8Pz5c5QsWRIuLpZtM/lOubl//z7KlCkjtxgEQRAEQQjgzp07KF26tMU4+U65KVSoEADNxfH19ZVZGoIgCIIguJCamooyZcpo+3FL5DvlJncoytfXl5QbgiAIgnAwuLiUkEMxQRAEQRBOBSk3BEEQBEE4FaTcEARBEAThVOQ7nxuCIIj8SE5ODrKysuQWgyAs4u7ubnWaNxdIuSEIgnBiGGN48OABkpOT5RaFIKzi4uKCcuXKwd3d3aZ0SLkhCIJwYnIVG39/f3h7e9PipYRiyV1kNzExEWXLlrWprpJyQxAE4aTk5ORoFZtixYrJLQ5BWKVEiRK4f/8+srOz4ebmJjgdcigmCIJwUnJ9bLy9vWWWhCC4kTsclZOTY1M6pNwQBEE4OTQURTgKYtVVUm4IgiAIgnAqSLkhCIIgCMKpIOWGIAiCyBeEhIRg8eLFcothV6ZOnYo6derILYbdIeWGIOTkxQu5JSAIxaFSqSx+pk6dKijdM2fOYMCAATbJ9tZbb2HEiBE2pSEmW7duxVtvvQU/Pz/4+PggNDQU06dPx9OnT+UWTVZIuSEIuVi7FihYEFi9Wht05gzw5ZdAWpqMchGEzCQmJmo/ixcvhq+vr17YmDFjtHEZY8jOzuaUbokSJZxq5tiECRPQpUsXNGjQAHv37sXFixexYMEC/Pvvv1i/fr3c4skKKTcEIReffqr57t9fG9SwITBnDjBtmkwyEU4PY0B6ujwfxrjJGBgYqP34+flBpVJp/1+5cgWFChXC3r17Ua9ePXh4eOD48eOIj49Hhw4dEBAQAB8fHzRo0AAHDx7US9dwWEqlUmH16tXo1KkTvL29UalSJezcudOm67t161bUqFEDHh4eCAkJwYIFC/SOL1u2DJUqVYKnpycCAgLw0UcfaY/9/vvvqFWrFry8vFCsWDFEREQgPT3dZD6nT5/GN998gwULFmDevHlo0qQJQkJC0KpVK2zduhW9evUyK+Pq1atRrVo1eHp6omrVqli2bJne8XHjxqFy5crw9vZG+fLlMWnSJL2tO3KHutavX4+QkBD4+fmha9eueP78uZBLJgm0iB9BKJCLF+WWgHBWXrwAfHzkyTstTWOsFIMvv/wS8+fPR/ny5VGkSBHcuXMH7777LmbOnAkPDw/8/PPPaNeuHeLi4lC2bFmz6UybNg1z587FvHnzsGTJEvTo0QO3b99G0aJFecsUExODzp07Y+rUqejSpQtOnjyJwYMHo1ixYujduzfOnj2LYcOGYf369WjSpAmePn2KY8eOAdBYq7p164a5c+eiU6dOeP78OY4dOwZmRiP89ddf4ePjg8GDB5s8XrhwYbPnTZ48Gd9//z3CwsLwzz//oH///ihYsKBWISpUqBDWrVuHkiVL4sKFC+jfvz8KFSqEL774QptOfHw8duzYgV27duHZs2fo3LkzZs+ejZkzZ/K+bpLA8hkpKSkMAEtJSZFbFCK/o3mR1XwMgtq2lVEuwml4+fIlu3TpEnv58qU2LC1Nv+rZ85OWxr8Ma9euZX5+ftr/hw8fZgDYjh07rJ5bo0YNtmTJEu3/4OBgtmjRIu1/AGzixIk61yaNAWB79+41m2bz5s3Z8OHDTR7r3r07a9WqlV7Y2LFjWfXq1RljjG3dupX5+vqy1NRUo3NjYmIYAHbr1i2r5WKMsXfeeYeFhoZajTdlyhRWu3Zt7f8KFSqwDRs26MWZMWMGa9y4sdk05s2bx+rVq6eXpre3t145xo4dy8LDwznJbglTdTYXPv03WW4IgiDyEd7e8vl0ienuUr9+fb3/aWlpmDp1Knbv3o3ExERkZ2fj5cuXSEhIsJhOaGio9nfBggXh6+uLpKQkQTJdvnwZHTp00Atr2rQpFi9ejJycHLRq1QrBwcEoX7482rZti7Zt22qHxGrXro2WLVuiVq1aaNOmDVq3bo2PPvoIRYoUMZkX4zrGp0N6ejri4+PRt29f9NcZDs/Ozoafn5/2/6ZNm/Ddd98hPj4eaWlpyM7Ohq+vr15aISEhKFSokPZ/UFCQ4OsmBaTcEIQCEdBuEQQnVCrxhobkpKBBIcaMGYMDBw5g/vz5qFixIry8vPDRRx8hMzPTYjqG+xepVCqo1WrR5QU0wz3nzp1DVFQU9u/fj8mTJ2Pq1Kk4c+YMChcujAMHDuDkyZPYv38/lixZggkTJuDUqVMoV66cUVqVK1fG8ePHkZWVxXkPprTXWu2qVasQHh6ud8zV1RUAEB0djR49emDatGlo06YN/Pz8sHHjRiPfIXteNyGQQzFBEATh8Jw4cQK9e/dGp06dUKtWLQQGBuLWrVt2laFatWo4ceKEkVyVK1fWKg8FChRAREQE5s6di/Pnz+PWrVs4dOgQAI2C0LRpU0ybNg3//PMP3N3dsX37dpN5de/eHWlpaUbOwLkkJycbhQUEBKBkyZK4ceMGKlasqPfJVaBOnjyJ4OBgTJgwAfXr10elSpVw+/ZtoZdENshyQxAKhLYCIgh+VKpUCdu2bUO7du2gUqkwadIkySwJjx49QmxsrF5YUFAQRo8ejQYNGmDGjBno0qULoqOj8f3332sVkF27duHGjRto1qwZihQpgj179kCtVqNKlSo4deoUIiMj0bp1a/j7++PUqVN49OgRqlWrZlKG8PBwfPHFFxg9ejTu3buHTp06oWTJkrh+/TpWrFiBN954A8OHDzc6b9q0aRg2bBj8/PzQtm1bZGRk4OzZs3j27BlGjRqFSpUqISEhARs3bkSDBg2we/duswqWklGE5Wbp0qUICQmBp6cnwsPDcfr0aU7nbdy4ESqVCh07dpRWQIIgCELRLFy4EEWKFEGTJk3Qrl07tGnTBnXr1pUkrw0bNiAsLEzvs2rVKtStWxebN2/Gxo0bUbNmTUyePBnTp09H7969AWhmMG3btg0tWrRAtWrVsGLFCvz222+oUaMGfH19cfToUbz77ruoXLkyJk6ciAULFuCdd94xK8ecOXOwYcMGnDp1Cm3atEGNGjUwatQohIaGmp0K3q9fP6xevRpr165FrVq10Lx5c6xbt05ruWnfvj1GjhyJoUOHok6dOjh58iQmTZok+jWUGhUT4pUkIps2bULPnj2xYsUKhIeHY/HixdiyZQvi4uLg7+9v9rxbt27hjTfeQPny5VG0aFHs2LGDU36pqanw8/NDSkqKkYMUQdgVXfPM68cwN6htW2DvXhlkIpyKV69e4ebNmyhXrhw8PT0tR37xAnj+HChRAnBRxHsvkQ+xVGf59N+y1+CFCxeif//+6NOnD6pXr44VK1bA29sba9asMXtOTk6O1uGpfPnydpSWIOwDORQTdufSJeDOHeDRI7klIQibkVW5yczMRExMDCIiIrRhLi4uiIiIQHR0tNnzpk+fDn9/f/Tt29dqHhkZGUhNTdX7EARBEGYwsyIuQTgSsio3jx8/Rk5ODgICAvTCAwIC8ODBA5PnHD9+HD/++CNWrVrFKY9Zs2bBz89P+ylTpozNchOE1JBDMUEQhHBkH5biw/Pnz/HJJ59g1apVKF68OKdzxo8fj5SUFO3nzp07EktJEARBEIScyDoVvHjx4nB1dcXDhw/1wh8+fIjAwECj+PHx8bh16xbatWunDcud6legQAHExcWhQoUKeud4eHjAw8NDAukJgiAIglAislpu3N3dUa9ePURGRmrD1Go1IiMj0bhxY6P4VatWxYULFxAbG6v9tG/fHm+//TZiY2NpyIlwGsihmCAIQjiyL+I3atQo9OrVC/Xr10fDhg2xePFipKeno0+fPgCAnj17olSpUpg1axY8PT1Rs2ZNvfNzdz41DCcIgiAIIn8iu3LTpUsXPHr0CJMnT8aDBw9Qp04d7Nu3T+tknJCQABdac4EgCIIgCI4oQmsYOnQobt++jYyMDJw6dUpvQ6+oqCisW7fO7Lnr1q3jvIAfQTgKNFuKkA0nrnwhISFYvHix3GLIzrp167SjHnLw1ltvYcSIEZLmoQjlhiAIfcjnhsjPqFQqi5+pU6cKSvfMmTMYMGCATbLZo2O2xtSpU61eI0t06dIFV69e5ZWnEsrNB9mHpQiCIAgFoQDNOjExUft706ZNmDx5MuLi4rRhPj4+2t+MMeTk5KBAAevdWYkSJcQVVCbGjBmDgQMHav83aNAAAwYMQP/+/Tmd7+XlBS8vL6nEUwRkuSEIgiAURWBgoPbj5+cHlUql/X/lyhUUKlQIe/fuRb169eDh4YHjx48jPj4eHTp0QEBAAHx8fNCgQQMcPHhQL13DYSmVSoXVq1ejU6dO8Pb2RqVKlbBz506bZN+6dStq1KgBDw8PhISEYMGCBXrHly1bhkqVKsHT0xMBAQH46KOPtMd+//131KpVC15eXihWrBgiIiKQbmLFaB8fH71r5OrqikKFCmn/b9iwAbVq1ULBggVRpkwZDB48GGlpadrzDYelpk6dijp16mD9+vUICQmBn58funbtiufPnwMAevfujSNHjuDbb7/VWoZu3boFALh48SLeeecd+Pj4ICAgAJ988gkeP36sTTs9PR09e/aEj48PgoKCjK6HVJByQxAEkZ9gTLPFguHn5cu8j6njYnxEtAp9+eWXmD17Ni5fvozQ0FCkpaXh3XffRWRkJP755x+0bdsW7dq1Q0JCgsV0pk2bhs6dO+P8+fN499130aNHDzx9+lSQTDExMejcuTO6du2KCxcuYOrUqZg0aZLWb/Ts2bMYNmwYpk+fjri4OOzbtw/NmjUDoLFWdevWDZ9++ikuX76MqKgofPDBBxCyt7WLiwu+++47/Pfff/jpp59w6NAhfPHFFxbPiY+Px44dO7Br1y7s2rULR44cwezZswEA3377LRo3boz+/fsjMTERiYmJKFOmDJKTk9GiRQuEhYXh7Nmz2LdvHx4+fIjOnTtr0x07diyOHDmCP/74A/v370dUVBTOnTvHu0y8YfmMlJQUBoClpKTILQqR39E09ZqPQVDbtjLKRTgNL1++ZJcuXWIvX77MC0xL06979vykpfEuw9q1a5mfn5/2/+HDhxkAtmPHDqvn1qhRgy1ZskT7Pzg4mC1atEj7HwCbOHGizqVJYwDY3r17zabZvHlzNnz4cJPHunfvzlq1aqUXNnbsWFa9enXGGGNbt25lvr6+LDU11ejcmJgYBoDdunXLarkMMSyXIVu2bGHFihXT/je8plOmTGHe3t56co0dO5aFh4dr/5sq94wZM1jr1q31wu7cucMAsLi4OPb8+XPm7u7ONm/erD3+5MkT5uXlZfYamqyzr+HTf5PlhiAUiALcHghC0dSvX1/vf1paGsaMGYNq1aqhcOHC8PHxweXLl61abkJDQ7W/CxYsCF9fXyQlJQmS6fLly2jatKleWNOmTXHt2jXk5OSgVatWCA4ORvny5fHJJ5/g119/xYsXLwAAtWvXRsuWLVGrVi18/PHHWLVqFZ49eyZIjoMHD6Jly5YoVaoUChUqhE8++QRPnjzR5mWKkJAQFCpUSPs/KCjI6nX4999/cfjwYfj4+Gg/VatWBaCxBMXHxyMzM1NvBnTRokVRpUoVQeXiAyk3BEEQ+QlvbyAtzfhz9Kjmc/Gi6eNifLy9RStGwYIF9f6PGTMG27dvxzfffINjx44hNjYWtWrVQmZmpsV03Nzc9P6rVCrttj5iU6hQIZw7dw6//fYbgoKCMHnyZNSuXRvJyclwdXXFgQMHsHfvXlSvXh1LlixBlSpVcPPmTV553Lp1C++//z5CQ0OxdetWxMTEYOnSpQBg8VoIuQ5paWlo166d3q4BsbGxuHbtmna4TS5othRBEER+QqUCDBQDAEDu7Blvb9PHFc6JEyfQu3dvdOrUCYCm4811erUX1apVw4kTJ4zkqly5MlxdXQFo9kGMiIhAREQEpkyZgsKFC+PQoUP44IMPoFKp0LRpUzRt2hSTJ09GcHAwtm/fjlGjRnGWISYmBmq1GgsWLNAugLt582aby+bu7o6cnBy9sLp162Lr1q0ICQkxOVutQoUKcHNzw6lTp1C2bFkAwLNnz3D16lU0b97cZpksQcoNQRAE4fBUqlQJ27ZtQ7t27aBSqTBp0iTJLDCPHj1CbGysXlhQUBBGjx6NBg0aYMaMGejSpQuio6Px/fffY9myZQCAXbt24caNG2jWrBmKFCmCPXv2QK1Wo0qVKjh16hQiIyPRunVr+Pv749SpU3j06BGqVavGS7aKFSsiKysLS5YsQbt27XDixAmsWLHC5jKHhITg1KlTuHXrFnx8fFC0aFEMGTIEq1atQrdu3fDFF1+gaNGiuH79OjZu3IjVq1fDx8cHffv2xdixY1GsWDH4+/tjwoQJdtl1gIalCIIgCIdn4cKFKFKkCJo0aYJ27dqhTZs2qFu3riR5bdiwAWFhYXqfVatWoW7duti8eTM2btyImjVrYvLkyZg+fTp69+4NQLMX4rZt29CiRQtUq1YNK1aswG+//YYaNWrA19cXR48exbvvvovKlStj4sSJWLBgAd555x1estWuXRsLFy7EnDlzULNmTfz666+YNWuWzWUeM2YMXF1dUb16dZQoUQIJCQkoWbIkTpw4gZycHLRu3Rq1atXCiBEjULhwYa0CM2/ePLz55pto164dIiIi8MYbb6BevXo2y2MNFWP5y3UxNTUVfn5+SElJga+vr9ziEPkZ3VVEXz+GuUFt2gD79skgE+FUvHr1Cjdv3kS5cuXg6elpOfLZs5rvYsWAcuWkF44Qj5wc4PFjoHBhwMNDbmlswlKd5dN/k+WGIAiCIByZe/eAO3eAS5fklkQxkHJDEARBEI5Maqrm28DhNz9Dyg1BEARBEE4FKTcEQRAEQTgVpNwQBEE4Ofls3gjhwIhVV0m5IQiCcFJyV521tOw+QSiJ3FWUcxc9FAot4kcQBOGkuLq6onDhwto9gry9vaHSXYLAFDk5wKtXdpCOEA3dxQod+N6p1Wo8evQI3t7eJlc85gMpNwShQGgUgRCLwMBAALC+GeTjx5rvly+BrCyJpSJEJSkJyM7W/Oa5F5XScHFxQdmyZa0r4VYg5YYgCMKJUalUCAoKgr+/P7IsKS25K+F27AjMnm0X2QiRGDw4T6m5ckVeWWzE3d1dlO0ZSLkhCAVi40sLQRjh6upq2Y/h9m3Nd3IyYG01Y0JZ3L+fd//o3gEgh2KCIAhCFxoTJZwAUm4IgiAIgnAqSLkhCAVCL88EQRDCIeWGIAiCyIMcvggngJQbglAg1L8QBMEZajCMIOWGIAiCIBwZGsc2gpQbglAg1FYRBEEIh5QbgiAIgiCcClJuCIIgCIJwKki5IQiCIAhHhhyKjSDlhiAUCLVVBEFwhpz0jCDlhiAUCLVVBEEQwiHlhiAIgiAIp4KUG4IgCCIPGhN1POieGUHKDUEQBEEQTgUpNwShQOhFjJANcvhyPOieGUHKDUEoEGqrCIIghEPKDUEQBJEHmQ0dD7pnRpByQxAEQRCEU0HKDUE4IpmZwOPHcktBEAShSEi5IQhHJDQUKFECuHlTbkkIZ4OGOBwPctIzgpQbgnBE4uI03zt3yisH4XxQR0k4AaTcEARBEIQjQ9Y2I0i5IQiCIAjCqSDlhiAIgsiDrACEE0DKDUEQBEEQTgUpNwRBEEQe5FBMOAGk3BAEQRAE4VSQckMQBEHkQT43hBNAyg1BKBAaGSAIghAOKTcEQRAEQTgVpNwQhAKhkQGCIAjhkHJDEARBEIRTQcoNQRAEQRBOBSk3BKFAyKGYIAhCOKTcEARBEHmQwxfhBJByQxAKhPoXQjbIbEg4AbyVm5cvX+LFixfa/7dv38bixYuxf/9+UQUjCIIgCIIQAm/lpkOHDvj5558BAMnJyQgPD8eCBQvQoUMHLF++XHQBCSI/Qi/PhGyQ2ZBwAngrN+fOncObb74JAPj9998REBCA27dv4+eff8Z3330nuoAEQRAEQRB84K3cvHjxAoUKFQIA7N+/Hx988AFcXFzQqFEj3L59W3QBCYIgCIIg+MBbualYsSJ27NiBO3fu4K+//kLr1q0BAElJSfD19RVdQILIj9DIAEEQhHB4KzeTJ0/GmDFjEBISgvDwcDRu3BiAxooTFhYmuoAEQRAEQRB8KMD3hI8++ghvvPEGEhMTUbt2bW14y5Yt0alTJ1GFI4j8CjkUEwRBCIe3cgMAgYGBCAwMBACkpqbi0KFDqFKlCqpWrSqqcARBEARBWIHGsY3gPSzVuXNnfP/99wA0a97Ur18fnTt3RmhoKLZu3Sq6gARBEIQdoY7S8SBTrxG8lZujR49qp4Jv374djDEkJyfju+++w9dffy26gARBWIA6IkJsqKMknADeyk1KSgqKFi0KANi3bx8+/PBDeHt747333sO1a9dEF5Ag8iOcdRbqiAiCIIzgrdyUKVMG0dHRSE9Px759+7RTwZ89ewZPT0/RBSSI/AjpLARBcIYsuEbwdigeMWIEevToAR8fHwQHB+Ott94CoBmuqlWrltjyEQRBEPaEOkrCCeBtuRk8eDCio6OxZs0aHD9+HC4umiTKly8v2Odm6dKlCAkJgaenJ8LDw3H69Gmzcbdt24b69eujcOHCKFiwIOrUqYP169cLypcgHB7qiAiCIFOvEYKmgtevXx/169cHYwyMMahUKrz33nuCBNi0aRNGjRqFFStWIDw8HIsXL0abNm0QFxcHf39/o/hFixbFhAkTULVqVbi7u2PXrl3o06cP/P390aZNG0EyEITDQo0aQRCEEbwtNwDw888/o1atWvDy8oKXlxdCQ0MFW08WLlyI/v37o0+fPqhevTpWrFgBb29vrFmzxmT8t956C506dUK1atVQoUIFDB8+HKGhoTh+/LjJ+BkZGUhNTdX7EARBEAThvPBWbhYuXIhBgwbh3XffxebNm7F582a0bdsWAwcOxKJFi3illZmZiZiYGEREROQJ5OKCiIgIREdHWz2fMYbIyEjExcWhWbNmJuPMmjULfn5+2k+ZMmV4yUgQBDeysoB164CbN+WWhHAkNm0CGjcGEhLklsSBoeFpI3gPSy1ZsgTLly9Hz549tWHt27dHjRo1MHXqVIwcOZJzWo8fP0ZOTg4CAgL0wgMCAnDlyhWz56WkpKBUqVLIyMiAq6srli1bhlatWpmMO378eIwaNUr7PzU1lRQcwnlQUKO2ZAkwerTmN42WEVzp2lXzPXQosHOnvLIQzgNv5SYxMRFNmjQxCm/SpAkSExNFEcoahQoVQmxsLNLS0hAZGYlRo0ahfPny2plbunh4eMDDw8MuchFEfubwYbklIByZlBQ7ZzhzJhAVBezeDbi72zlzkaG3CSN4D0tVrFgRmzdvNgrftGkTKlWqxCut4sWLw9XVFQ8fPtQLf/jwoXbvKlO4uLigYsWKqFOnDkaPHo2PPvoIs2bN4pU3QTgF1KgRhDAmTgQOHtSMixFOB2/LzbRp09ClSxccPXoUTZs2BQCcOHECkZGRJpUeS7i7u6NevXqIjIxEx44dAQBqtRqRkZEYOnQo53TUajUyMjJ45U0QhLiQnkXYgmz159UrmTIWEQUNTysF3srNhx9+iFOnTmHRokXYsWMHAKBatWo4ffo0wsLCeAswatQo9OrVC/Xr10fDhg2xePFipKeno0+fPgCAnj17olSpUlrLzKxZs1C/fn1UqFABGRkZ2LNnD9avX4/ly5fzzpsgHB5q1AjCNkgrd0oErXNTr149/PLLL6II0KVLFzx69AiTJ0/GgwcPUKdOHezbt0/rZJyQkKBdKBAA0tPTMXjwYNy9exdeXl6oWrUqfvnlF3Tp0kUUeQiCEAbpWU6CTDeS6g8hJpyUGz5rw/j6+vIWYujQoWaHoaKiovT+f/3117T7OEHkQm+dBEFQO2AEJ+WmcOHCUFlRq3NXKs7JyRFFMILIzzhiW+WIMhMmkOlGUv0hxISTcnOY5ngShDIhWz5B2IYzaFXUDhjBSblp3ry51HIQBKGDI7ZVjigzYQLyuSGcAEF7SxEEoRAU9NapIFEIgjukVTklpNwQBEEQsiObcqybcU4OsH07YKfV9gnpIOWGIBQI54ae3joJQjxWrgQ++ACoWlVuSQgbIeWGIAiCkB1F6Om7d2u+eSx/QigTUm4IQoEooqEnCDtCPluEmHCaLRUWFmZ1nZtczp07Z5NABEEQBGE3SKtySjgpN7mbWgLAq1evsGzZMlSvXh2NGzcGAPz999/477//MHjwYEmEJIj8hiO2t2Rtcg4ys1Vwl1sIgrARTsrNlClTtL/79euHYcOGYcaMGUZx7ty5I650BEE4DI6okBHGxJ5jaChDvopQjhUhBCEGvH1utmzZgp49exqF/+9//8PWrVtFEYogHJlTp4A1a+SWgnB2EhKAvn2BCxfETTf9hbjpcUURyjEpN04D713Bvby8cOLECVSqVEkv/MSJE/D09BRNMIJwVBo10nyHhAAtWghLg9pYwhoffQScOQOsXw9kZoqZMlU+wvHhrdyMGDECgwYNwrlz59CwocZ4eerUKaxZswaTJk0SXUCCcFTi4oQrNwRhjX//1XxnZckrh8OjCJMRITa8lZsvv/wS5cuXx7fffotffvkFAFCtWjWsXbsWnTt3Fl1AgsiPUHtL5DfIWkmICW/lBgA6d+5MigxBWIEUFEJKnE0ZoOeFEBNByg0AxMTE4PLlywCAGjVqICwsTDShCIIgCIIghMJbuUlKSkLXrl0RFRWFwoULAwCSk5Px9ttvY+PGjShRooTYMhKEQ2LLm7WzvZUThGLRNRnRg+c08J4K/vnnn+P58+f477//8PTpUzx9+hQXL15Eamoqhg0bJoWMBJHvIBM9YQ3qhwktVBmM4G252bdvHw4ePIhq1appw6pXr46lS5eidevWogpHEITjQAoZQcgEPXxG8LbcqNVquLm5GYW7ublBrVaLIhRBEARB2B2ygDgNvJWbFi1aYPjw4bh//7427N69exg5ciRatmwpqnAEQTgO1C/YF2e73s5WHr4kJ2s+hDjwVm6+//57pKamIiQkBBUqVECFChVQrlw5pKamYsmSJVLISBAOCVmKCYI7+fl5ycwEihTRfLKz5ZbGOeDtc1OmTBmcO3cOBw8exJUrVwBoFvGLiIgQXTiCIByH/Nw5ORX53YQiA48e5f1OTwf8/HgmQPfMCEHr3KhUKrRq1QqtWrUSWx6CcBqovSEckXynoypMK09OFqDcKKwMSoD3sBQAHDlyBO3atUPFihVRsWJFtG/fHseOHRNbNoJwaPJbe0PKnH2R6nqrZKq4+bn+6F7ynj3lk8OZ4K3c/PLLL4iIiIC3tzeGDRuGYcOGwdPTEy1btsSGDRukkJEgCAcgvylzzopcSoYi6o8CNKyjR+WWwDngPSw1c+ZMzJ07FyNHjtSGDRs2DAsXLsSMGTPQvXt3UQUkCIIg7AeD/B28IBgDHj4EAgPllsT+KEApUxq8LTc3btxAu3btjMLbt2+PmzdviiIUQTgD1N4QUkL1y4B+/YCgIGDrVn7nKcJkRIgNb+WmTJkyiIyMNAo/ePAgypQpI4pQBOEM2LXNzM4G5swBzp61Y6YEoSDWrNF8T50qPA1H1RhJQTOC97DU6NGjMWzYMMTGxqJJkyYAgBMnTmDdunX49ttvRReQIAgOrFgBfPml5jc1dATBHRsUmidPgMKFAVdX8cQhxIG3cjNo0CAEBgZiwYIF2Lx5MwDNOjebNm1Chw4dRBeQIBwVu74EXrhgx8wIk9y5A2zZAvTtK2AuLyEbAl8GYmOBsDCgRQvAxGCGfXFUi5OECFrnplOnTujUqZPYshCEU5HfDCj5vn1t0gS4exeIiQF+/VXy7PL99ZaZVas034cO2Z5Wfmsr7IEg5QYAMjMzkZSUZLRZZtmyZW0WiiAIxyPfN9B372q+9++XVw5byc9KE2mMTgNv5ebatWv49NNPcfLkSb1wxhhUKhVycnJEE44gEBUFeHsDDRvKLQlB5Ascdiq4nVGUHpTv3yyM4a3c9O7dGwUKFMCuXbsQFBQElaLuMOFUPHoEvP225rcDPrz0aBBS4mwrFMtGfitvPoG3chMbG4uYmBhUrVpVCnkIIo8HD+SWwCaozSQckvyslNv5jeTCBc12C599ZmNC9CZlBO91bqpXr47Hjx9LIQvhIKSnA9u2ab4JaSDFiJAPB+8o7dTRi5HNBx9oZl0NGmR7WoQ+nJSb1NRU7WfOnDn44osvEBUVhSdPnugdS01NlVpeQgH07g18+CHQq5fckhD0xkYQBjjQm0FystwSOC+chqUKFy6s51vDGEPLli314pBDsXQcPw4ULKhZU0EJ/P675pvvKucEdzjrLA7UkBPiQnqtA/PoEVCihNxSODWclJvDhw9LLQdhhqQk4M03Nb+pHyMIgrACX61PYMMqWLmcOhWYNg1YvhzAQIGJENbgpNw0b95cajkIM9y7J7cEMqLb6DCWr15VSZElCCdl2jTN96BBQHFSbqSCk3Jz/vx51KxZEy4uLjh//rzFuKGhoaIIRhAEB/KRwkfoQ7deAuiiOg2clJs6dergwYMH8Pf3R506daBSqcBMvFqSzw1hiqwsICcH8PTkeSI1NNYhEw+Rz8jIADw85JaCmielw0m5uXnzJkq8dn66efOmpAIRzkdIiGb33JQUno1SPu64qeEk5IIpuPIdOwY0awZMmgRMny5Sovm4nXFmOCk3wcHBJn8TBBfu39d8X78O1KghMJF85nNDEHKh5BWKhw3TfM+YIaJyowu1MU4DJ+Vm586dnBNs3769YGEI54Z3m5mPGxrO10pB10jBfaJToqBbbzeojhFc4aTcdOzYkVNi5HNDGGJTY0QtGUEQCiU/KpeOBCflRq1WSy0HQViGFB3TKOi6UGPvHCjZ50bBohEKg/feUrq8evVKLDkIwph83JLxLroCrpWC9Kx8gQJuud2RvI456EWlR88Y3spNTk4OZsyYgVKlSsHHxwc3btwAAEyaNAk//vij6AISjo3hOny5xMZy2PQ7H/eWvH1u8vG1Igg9HGjjTLFEffJEnHScCd7KzcyZM7Fu3TrMnTsX7u7u2vCaNWti9erVogpH6OMs/deVK5p9soKCeJzkLIUnCIXjmLYLG3CCtoU24DSGt3Lz888/44cffkCPHj3g6uqqDa9duzauXLkiqnCEw1pJLRIdzTGiMxZebHIbZge5VsOGadYpyc6WWxLCHI7f1duAgzxHhHV4Kzf37t1DxYoVjcLVajWysrJEEYrIw9FfKswNS/E+mbCMg1yrJUs0C7Ht3y+3JI4P9cPyoqTrz/Kfvc0qvJWb6tWr49ixY0bhv//+O8LCwkQRijCNg/Rf0pCvC28BJbWwPKAVI2xHqlvvmDUqf6PK3/Y2k3CaCq7L5MmT0atXL9y7dw9qtRrbtm1DXFwcfv75Z+zatUsKGfM1Dtp3EfZGYEVhDHj5EvD2lk0EggDA7f1FknccGV+c6J1NOnhbbjp06IA///wTBw8eRMGCBTF58mRcvnwZf/75J1q1aiWFjPkaR6/8poalHL1MisLGi9q+PVCwIHDrlniiEITDwkNDJ2Ve2fBWbu7evYs333wTBw4cQFJSEl68eIHjx4+jdevW+Pvvv6WQkXhNvu488nXhpSPX2Lp2rbxyEPYnIwNYsQJ4vZqH7MimLMiopZCCJB28lZvWrVvj6dOnRuEnTpxA27ZtRRGKyIMqP2GR3ApCFSXfYestnz0bGDQIMJwforQVijMzgagojTImCU7w4kQOxcbwVm4aNWqE1q1b4/nz59qwo0eP4t1338WUKVNEFY7QxwmeQYIgFEJUlOZbKe2KOTmGDQPefhv47DP7ymMNJemA5FBsDG/lZvXq1ShbtizatWuHjIwMHD58GO+99x6mT5+OkSNHSiEj4cAopeEkCMIxWblS8/3TT/LKQTgWvJUbFxcXbNy4EW5ubmjRogXat2+PWbNmYfjw4VLIRzgRtEO4BdLTAVoniuCBrZYDc+c7vOuLLQkpyRyjEFatAtatk1sK/nCaCn7+/HmjsKlTp6Jbt2743//+h2bNmmnjhIaGiishocUZ+/e5c4EvvpBbCmngdb98fICyZQHclkocgtDDXP10wmbGMk7QsErlc/PkCTBggOZ3ly6Al5ck2UgCJ+WmTp06UKlUYDqVIPf/ypUr8cMPP4AxBpVKhRxanYvQwVq7MW6c8yo3vElIkC1remEl5Ea2dW4Ekh+emfT0vN+OtmUKJ+Xm5s2bUstBEJaxQ6uWlKRxsuzYEdDZE1Yw+aHxM8dPPwHz5wN//AGULy+3NIQplDYsRQjHHg7FjtaecVJugoODpZaD4ICS3lqEoPRF/Bo1Am7eBKZMAaZOlVsax6Z3b833kCHA3r2yiuK0SNXZyDWtWBGdpyKEIMSAk3Kzc+dOvPPOO3Bzc8POnTstxm3fvr0oghHOgVIVGVPkGii3bxdHuXGkskvFq1dyS0DwRa5pxY72vJAepGw4KTcdO3bEgwcP4O/vj44dO5qNRz43hGTYseVztEZWyZgd+lB4x6BWaxwoK1YEZs2SQQDGJL9ISr8HdsMJHnhaxM8YTlPB1Wo1/P39tb/NfUixkRZHfwYdXX6+OFLnIZWsLrwXm1AGf/8N/P67ZhVfu7NlC1CsGBAZaXRIrc777Uj1y2Ggi6qHI7fZDtr0EI6CIz4cYrVvjlh2WzBVXkdVbiRb6p8LnTsDz54BERF6waNHA4GBwIMH0mavZJ+b/PZMcYUcio3hNCz13XffcU5w2LBhvIVYunQp5s2bhwcPHqB27dpYsmQJGjZsaDLuqlWr8PPPP+PixYsAgHr16uGbb74xG9+ZyG8PdkICUDb3j5MUfvNmYNo0jVWgmtzC2AFzyo3Sb6cSG/KFCzXfixYBc+bIK4sUKL1O5AeePwe++UYzJFunjtzS2AYn5WbRokWcElOpVLyVm02bNmHUqFFYsWIFwsPDsXjxYrRp0wZxcXHaoTBdoqKi0K1bNzRp0gSenp6YM2cOWrdujf/++w+lSpXilbez8uwZsGePZkpzwYJySyMcsd+eDx4EJk7UrLhZq5a4aZvCVAfZpYvm+5NPgLPSi2BXTJXXUS03joB0KxQ7uJbB98II1KrEUIBFsxKLZG378ktg2TLNcCxjjq1wyr7OzcKFC9G/f3/06dMHALBixQrs3r0ba9aswZdffmkU/9dff9X7v3r1amzduhWRkZHo2bOnZHI6Eu3aASdOaDrQn3+WVxYhD8fWrcCjR0DLEuLK0qqV5rt9+7yZUVJiqey6i2M5C6bK66gOxfkBR+64LGJLwXhUTGesw7GxcksgHrK+V2VmZiImJgYROmPLLi4uiIiIQHR0NKc0Xrx4gaysLBQtWtTk8YyMDKSmpup9HBWuz+yJE5pvAz1QMBMmAPXqAS9e2JYOV/k/+ggYNMhgwV4RW+LHj0VLSjKcpeNxVMuNM3ZcXGEyFT4/X3NCfGRteh4/foycnBwEBATohQcEBOABR6+5cePGoWTJknoKki6zZs2Cn5+f9lOmTBmb5VYisbHA5MnSWAS++QY4d068XXm5dtzJyabPYQz46y/g4UPuea5axT2usygWSoA6LPER65oq7d6I9twprWB2QKqhREduCzkNSymV2bNnY+PGjYiKioKnp6fJOOPHj8eoUaO0/1NTU51SwQkL03y/fCldHkL2FpHi4di4EejeHfD25q7M5W7+Zk/yWxtLPjf2Jb/VL6WR366/oyk6sio3xYsXh6urKx4avII/fPgQgYGBFs+dP38+Zs+ejYMHD1rcidzDwwMeHh6iyCs3XCqX7pipUh8+W+Xas0fzLXSYzFr+SpgKbu97J0Z+zjQVnCAkR6USTWGgRfyMkbXpcXd3R7169RCps1iVWq1GZGQkGjdubPa8uXPnYsaMGdi3bx/q169vD1EJEbBlbymmzjvJ0d4g8jNKVbCt4ahy88ERyyj5s++IF0VCHLmt5W25OX/+vMlwlUoFT09PlC1blpelZNSoUejVqxfq16+Phg0bYvHixUhPT9fOnurZsydKlSqFWa/XQJ8zZw4mT56MDRs2ICQkROub4+PjAx8fH77FIXggSClx4IdDSqxdF0e8bs40LGWqLElJwLvvAv36AQMH2l8mQ6gfFgmFTQUvi9vAyXtAkya2ZyAijtYm8VZu6tSpA5WFu+rm5oYuXbpg5cqVZv1gdOnSpQsePXqEyZMn48GDB6hTpw727dundTJOSEiAi04LuXz5cmRmZuKjjz7SS2fKlCmY6uRbOTta5RIT3bJL3ajn5+tsiZwcwNXV/HE+U8EdkcmTgZgYzUcJyo1UKPmWcalPqc8BXykzkJjbCAGaAvj3X8CCywVhGd7vVdu3b0elSpXwww8/IDY2FrGxsfjhhx9QpUoVbNiwAT/++CMOHTqEiRMnck5z6NChuH37NjIyMnDq1CmEh4drj0VFRWHdunXa/7du3QJjzOjjrIoN32dNN74CnlM9eCsNhlOknAil3Rtr7NsHeHkBOo8iJxzVcmOKtDS5JdAguXKv4MrJpRm4d096OezCmTNyS6CHozXBvC03M2fOxLfffos2bdpow2rVqoXSpUtj0qRJOH36NAoWLIjRo0dj/vz5ogqb33G0ygXYJrNU5VVw261FaTK2a6eZLdenD9C7N/fzlFYOW3DE508IKgcvKDnXEoAAy82FCxcQHBxsFB4cHIwLFy4A0AxdJSYm2i4dYRNuyAL+/FOzH4MjotMzMgYgLg549sxhOhlbOnbeZVSoFuGolhtTl1Np9U6ht1x2eK/5IqPPjdQkJwNffKEZ4RKC0uo8H3g3PVWrVsXs2bORmZmpDcvKysLs2bNRtWpVAMC9e/eMFuYj7M+X6m80ew28/bbcoghD98mKiwOqVgWKFZM8WyVMBVd0ZomJwMmTnKI6qnKTn1HysBTBjxEjgHnzxNkE09EUHd7DUkuXLkX79u1RunRp7foyFy5cQE5ODnbt2gUAuHHjBgYPHiyupATvytVdvV7zQ6jaLgDGgKgozcaUxYuLt9aLKupwXgYS42gPsRQ8faox+n3wAVCokMHBkiU138ePA02bWkzHGfpJxpyjHIY4Y5kAAcNSSnVUFEGWc+dEkMNB4a3cNGnSBDdv3sSvv/6Kq1evAgA+/vhjdO/eHYVet4KffPKJuFISgpBjd99Nm4Bu3YASJTRTZ3XhqzToNlIXLqpQx3bxnBcbG0LD0zt00Oguf/0FbNhg5qSoKKvKjTnLjZL6EFPoyper3ChN6VX6NZQLGpYSD6uX5skToEgRRZpoBa1QXKhQIQx05rmQToIcz94ff2i+Hz0SITGdJ+uXX+FUyo21RoN3wylmz5uVhdvHEwGUxcaNFpQbDnkqsM3jhKFyo/tNyIek9yAzU/MhTGJ07U+fBsLDNa4PuQ2/ghCk3MTHx2Px4sW4fPkyAKBGjRoYNmwYKlSoIKpwhD6O2LgqUWZHeOPidd0YA3bvFi/zpk2RgDNoiuOIcbdsmbGGoyo3plBKXXaE+isngmZL5eQApUoBjx+LL5CMSFpnv/1W871zp4SZCId30/PXX3+hevXqOH36NEJDQxEaGoq///4bNWrUwIEDB6SQkXAyOD9wurOlZJ7emZMjbnqidlD79gF374qX3uv1NXpjHdzdLcTjUAg95SY7G3g9ZKAURYELzmq5ISVJh2fPnE6xEQNHXmqMt3Lz5ZdfYuTIkTh16hQWLlyIhQsX4tSpUxgxYgTGjRsnhYwED/R840T2udm8WbM6K9f8DbFpET8Z+fZboGBBIDpabknMcPy4JMmq4WJZuQGQkWH5Nmnrw8uXQMmSiMJbYolnN6KiNFsuJCfLLYk+Uikncuo8WVma0Q6xXyYswhigVtsxQ8Ie8FZuLl++jL59+xqFf/rpp7h06ZIoQhGmkbuvP3EC4LtPqSMuyW8o34gRmk6cz+J1jobJdV2gsqjcvHihmUn17rvm42gtN0ePAo8eoTmOms0vL2MGnD0LpKZalVsqdOVr1Qr48UdAKYZpyVcollG96ddP48YxYYKdM7bQuKrVwK+/AvHx+uFKb8fyO7yVmxIlSiA2NtYoPDY2Fv7+/mLI5FScPQskJMiTtxyzpbg88JaUNL1jMg1LmZNPzMZMNEVVwhbWmnJz8aLmTXvfPvNx+IiXmAiMHAncXbkbaNAAqFmT+8mEaMjRbuTy88+a7zlz7JyxhQdy/Xrgf/8DKlbUD5dcuZFBexLV8i4zvB2K+/fvjwEDBuDGjRto8nrX0hMnTmDOnDkYNWqU6AI6MteuadpoQJyKwTcNORspU+TKz9kCrFNguX1uAPu3NZGRmhGnSZMsOOZK2OIwqODhwSO+CVH4OBR3764ZAmpQYAu6A8CdO9xPzoeQ5UBELDRKEo36AlDePXQ0BcYSvJWbSZMmoVChQliwYAHGjx8PAChZsiSmTp2KYcOGiS6gI5OfF1DKxfBh+eEHyzsq6zmwSSOSYMSc+cPFfyMiQvNdqZKm47c3DCq4uVmOYQ0+jffp05rv7Gz577zSOh1CYiz06o5QF8y9/NmqrDiyQzFv5UalUmHkyJEYOXIknj9/DgDaxfsIwhqffcYntjStitDGSsxG7uFD7nFv3BAvXz5YG5YyxNT1caap4M6GufqsBCupObh1sDzlF+hQrCSlR2lWeiUgaJ2bXEipsS+OoDnzeeC98AIv4QXzjZGyCmyfxozB8HpYvO8S+9y4uvKI74DO4+ZwVLkJQFC7YUG5kbIuOEKb7qhwUm7CwsKg4niHz9FYjGJQqZjxc374sGYdk7Fj7dKCmzNrBuE+7qMUDiACwAGTcZSGXB2exWsisc8NoVwkmwqeH2+7khseG+Dtp2lw751+WKpjx44Si0FIgUlTZYsWmu9KlYBOncTPk2PD2AO/AgBa4aDoMkiFMzf65qaCWzlLGlkUYrH7EL/jEUrgKJrLLYrkZGQAub7jUnRiWVmw4r8lJgLqJa1zA8DxFBhLcFJupkyZIrUcBAe4VDzOHbBcjhxWMFdGNf9VC0THHsqNCsxIqZCrweFruTF1ffhcMyU1rJ53ruF3fAxAOcpWLuauaXY2cOUKUKNGXpz79zXvMIMGGa/TpJvOjz8CgyWRFli8WDPFPzIy791KWgRsnCnAoVhJU8HJymqM/D0GIQpv4ihWYgAKZiVrw5Swzo0SzZpCGyW+zrF2Ka/EPjdClRMX5MADr8QXygKPHgFr1wLp6ban5Z4k4nYWEmF4b7p3B2rVApYsyQsbO1YzC61PH8tp6W50W/jFfY1GItKSzCNHar6tySArMlluxHp8zbX1YrZBSmm/uULKjYTYcxjjKJpjAFahz7Xx9svUBKI+AAp7mOxluTFEsT43FvL+B2F4jkJwz0zjna9Qpbx1a+DTT4GhQwWd7vBs2aL5njs3L4zrIs+6dbvurW0ajaRfP/GEEwlJZktZSVipw9FbtgCdOwNp/B+xfIFNs6UI+8LlwS6Vfk16QSREf4VinXAFmF35NnJiNYqKHZYyOKxb3lBcAACEJEYDaCWuYGbIXTj99981FhxbUGqHZlfE3Gke9qvHgrLhIdz9+5p9NsWqIy7IgRo8piW+pnNnzXe1asD/xBHFISzvXCHLjRNDw1LiopjZUna6kHwVSpNTwZVmfssHOPpzJgs8poKXKqXZGUSMBbQbZR5FCvzQHz8ITiMpSbyXP8O648h1SbByk5mZibi4OGRnZ4spD2EBbhXNMWojpxU1FVYURQ5LKcjnhrAPuffE7CJ8Ap4be9xna3KJ1ZEKKoqAzM+fF5KRPitTusAH6fgBJlY3FeGmOLJyYiu8lZsXL16gb9++8Pb2Ro0aNZDwelfIzz//HLNnzxZdQGfl7FlgyBDgyRPL8Wyp30qw3EiBrQ+sElYodgTkGgpUhLUnH9xsm4t47RqwcqVmnrcOz55pltMyNIYouqOVyaE4CzyWALeAWM+MM1neeSs348ePx7///ouoqCh4enpqwyMiIrBp0yZRhXNmGjQAli0DrG3H5SybZToD9uzvODcqjrKIn4GcSl/1NR/oNnoIKm/lypqN4r79Vi84LEwz5funn+wggxhYmQpuCX88xEk0BtasEXR+horHzrQy4MjtN2/lZseOHfj+++/xxhtv6K1aXKNGDcTHx4sqXH7g0iXucR1d0eGCqGv5iIw9poJzGpZSis+NDWI4cqOpR3Ky5k1l/ny7Z60YBezECb2/t29rvnNnb+Wi6HsucG+pmZiAxvgb6NtXULaZIik3Um2c6cjwni316NEj+Pv7G4Wnp6dz3qKByMNa5eM9Q8cBFRouOOJsKbGwh8+NqWTUcLE9+dzzeSRkax22631atEgzxnz2rN2ytFY+IR3apEnARGHiiIZYHbGgtkLg3lKF8Jx/XjpkQlmWG0sOxY6mKPG23NSvXx+7daYI5io0q1evRuPGjcWTjHBITI3Zvo1D+B5DoHphfXU1cw+QEpSbqmlngTp1gIPctowQ0snmduxKeE9QwjVXPC9eyJa1rXXE3nVMjM7RbBo6C/oIUo5l6rktDkspoRFwYHhbbr755hu88847uHTpErKzs/Htt9/i0qVLOHnyJI4cOSKFjE4NnxkEnIZsdCIpxYpzCC0BAAm/FAHwtaA0dDtaud4gFl1qDWQ/A1q14iSEaG+izuBz42CoXDiWXYGvs1zbDKWJblNfHhgo/FzGBFluxNA9xLLckEOxMbwtN2+88QZiY2ORnZ2NWrVqYf/+/fD390d0dDTq1asnhYwOi0oFDMZStMJ+wWlMmCCiQHbA0gPvmXiLX2ISPU1CGyXf7GfiCmIBuRQavWx4LuJnMooZWZ3mpdTRWnwpMHMN7LpmysuXeflwqZgKWdBFLJ8bqXDk6i1oheIKFSpg1apVYsvidBS9Go2lyF0Lnn8tSUrSXyRUKofihATghx80U9ODgvjlYQ09zd/F+iqcnMrIGKTakVpuxFjnJj0dKFjQdllonRsOyNj6c1nnxtL9U9q9lbUjFehzYyuZKtungqtU5FBsCt6Wm4iICKxbtw6pXDctycd4P06w6fzMTAEnCXgQIyKAmTM1uwdLCXMVZ7cPoSbYariE7/A5AtX3RZHDGnJtv+DjA9wVYd/HyZiB6mmnbUpDaR2o6OTn3sMKCjGOcEPRwsmHxWEphT/cvJWbGjVqYPz48QgMDMTHH3+MP/74A1kGizgR3LH0TAlySBXgc3Pt9XZUp07xz48P/C035ryLhTVE/yAMn+N7rHzeXdD5fGFMc22fv55Q8YzDqJYph2Ihxf3tN/7nmOLHi+HiJMQDpfiKccLEG3+aCLuS24Kj9tOy9pUy+dxYfBtVgPKghOFxofBWbr799lvcu3cPO3bsQMGCBdGzZ08EBARgwIAB5FAsMY6wzo1FhzQOyo05dM2uQsvlAY0prHZ2jGA5+HDhgmadszJlNP/HjuV+rr0bFYvt6Pz5+DGnN8Rc2GbjRqtRxMpK0jQS7xtH1HH/kAQppoJLAV/LjV3lNsxMphWKHQml1CuuCNpbysXFBa1bt8a6devw8OFDrFy5EqdPn0aLFi3Eli9fY8tUYrtz6RLw998Wo+gqN7bMxHGUN/u9ezXfKSma7ytXhKUje6Mydix6sp/wNg7rh3PovF680KxzZ8j69aJJJyu//648nxt7ne9UyKTcSD0j0da2Q/a2xwZs2hX8wYMHWLFiBebMmYPz58+jQYMGYsmVb3DkyqNHjRpA48Yo/DLRbBS+w1K6Q2zLMMRkpJAQIIaDIaY2Yq1HkhgunQlvh+K0NODhQ+FC8aAg+I+37N0HFCkCZGY71iJ+XJ9LJSraTtOm2AuBU8HFQK2wiRGDbn2B86iFgkgD4Nh1ibeHZ2pqKrZu3YoNGzYgKioK5cuXR48ePbBp0yZUqFBBChnzLZaGeMwjb20snnYLQN6UK1uGpcyV1wV5DdHt28AHH+Qt+W6O02iY90em9kRoI2nxvo8fLyxRCbBUvmdPgQD7iWJEZibg6qr5cEKvMOZn5ylRubE7IvWAXJ4PSTrbQ4c000V5Yvvq3SrFrSXV4948AEBvrAO0M301OJpDMW/lJiAgAEWKFEGXLl0wa9Ys1K9fXwq5nA7GBGylYKvZWWENr1XlhjEUmDcb7VADf6K9xXi6cPFxcAd3p3exGlDD+8fHcmPRoVjKhfuYcN1PqW95r14BAQFAcDBw/rx46WqulfKGpZRyHxzG5+bwYfPxIGEfLmKBzYkoNAtX5Nh0vhLgrdzs3LkTLVu2hAvfXQTzIXrvfgxQHT8GjBoFLF0K6FoSRM2T/2wpUbHwNFhVbqKi4DHtK+xEruxmFoAzCFeqL6AtjaK9GxWVSrOCfVgYIOb2t/asgx54hfo4i4usEXSbtpgYTdkuXOCQyJMnQNu28PcN1gapwEy+Ycul3Cj8hVlZvHoFeHrKLYUFxLmZUtVCR1ZueGsorVq1IsVGAIwBaNZMs8Fe8+b64WYQNiwlLUXw1OJxi7OlrK1zc5/b+jNSKzdSdR5CHxsh911IGX78Ebhxg/95YiNUYfgN3XAcb+KrzKnCM589Gzh7FkUPbbUqj1qtPOsooJwl8+Va54blVv5lyzSrWf7xh03pSaZMWktYRi3WnDJvOUBZcGpu69ati2evF+kICwtD3bp1zX4I0+jVg1evOJ1j62wpsRvebtiApyiGryFsTwi1DVPB9WCOYbkxRKhDsRCEtDu8r6NBeYpl3McpNEQvrBNHIJ50wg4AwKCsb4Unks7daVouy417xnPg669RIUvg9LvXKM0CJLo8Q4ZoKvWAASInLBLMtEVQCA4wcmZ3OA1LdejQAR4eHtrfKqU9FQ6AGG/fcle0pa9nLE3AN5iImfwT4KncmNuX6FGSYyg3kq1QLHdFyMVAjP5xY9AQZ9AQfTicaL82RCzfNZfXfghqaOqxXMpN6/1jgHM/YA8m8Z9dZ0cU43NTqpRNmUm7iJ84iH3pOFluFA4n5WbKlCna31OnTpVKFudDp/abqxhiVxhzCoG9sKSQqVXizJY6ckRa5UYqh2Iuw1JK7qys4ZX9XJR0ZB3qMdFjaea0qHEeoVCBoSYuAnABY/oz9+xFmbsn7Z6nQ2FYfby8ZBHDKipV3hCaRHBtOzIygMREIETg+UqEtxdA+fLl8eTJE6Pw5ORklC9fXhShCA2OXLFMwTjPw7WMrT43ck2/lGQquJLgWD4l+qlYoxieoAYuoTouowQeIT4eePttZZZFqfVFqXIJxebycEggIQG4ft16Ura2aA0bAuXKGYfz3bRXSfBWbm7duoWcnByj8IyMDNwVY7c+J0WMB/uvvzjlpP2ltIaX8bTcmJPf8G3ZRHXM9whvd2yoMyZO1d5DhTaEXJ5LU/Xwk0+A6GjlPWN80L8ljlEOTu2oyFVNymEpSy9ajGmWL6hUSTPbz3I6tsFliQRHU045TwXfuXOn9vdff/0FPz8/7f+cnBxERkainCnVLz+jUxuEDEsZHuvbF/j0U+7ZK6Hh1Zu5oeKnS5u7No46FVz3vw9MD+HIPSzFr87ox7VXfUtJAXx9be9cvvxSs8FoTAxQvLjluIZly10UWqwyDxwIxMUBBw8Ctto39Vb5NrhGaWlA+/ZAp042ZsJTDlP/hVITF1AS9wG0EZ6ICMKIsYgf1+N37mgWgbcXuUqXoyk0unBWbjp27AgAUKlU6NWrl94xNzc3hISEYMGCBaIK50zYq5LIrdAY5a+r4Ok4nXAaGjJz0QzzEN1vSaL1aXR9bmJRR5pMBKJSvf7Yof5o1o0Rxt9/A40bA926ARs22CbHnDma78WLga+/Nh/PqL6JsImrIStXar6PHQPeEiVF03z/vWbNusOHgXbt8sInCJkgIBMXEKr58d9Fu/T4Ui7iZ81yk4u1FzixF/ET63w54fwqrVaroVarUbZsWSQlJWn/q9VqZGRkIC4uDu+//76UsiqaCxeARo00WwGYQkglsceYruTomW6En6qL1JYbqS6bbiNZAaYXlJHbcsPPQVa/SRXky/TffxrziU4hLSkMuQrJb7/xz8oc1q6voTxSLrcg9RBrWprp8K8xSfS8bLXcnD5t5dk2txOtApo9sbHWxontmOwMs6V4+9zcvHkTxa3ZcPMh6enAqVPAv//mhVlcQt9KuNIpiif4E+8DW7fqhRvNllJbsJELxFbLDWNA587SD2dJNhVcQqSy3Fy9aiaPmjWB7t21DmXF8ciiDILWfrLyHNpyfcW+XmLca65pyNH27N4N9Ohh3YcEAMLDgW9tWLJIi9CCvj5PMp8bk3tLmZbVmtKbmSHNzcy9dC7IgVfkLuDRI0nykQLe2y8AQHp6Oo4cOYKEhARkZmbqHRs2bJgogjkauUMO5jpMt3GjeKepZMXna0zE+9gNfLTbspbAwe+Iy7m6iNGhbNmi8V9q29bmpHD2LPD0KdC6tX64kKngpnAG5eZ5qpV0z51Dz+z7WIm+kuRvC6aGpXLvrdzDwHwRS+F+/Biw9oprynKTa9wPCgLmz7eez7JlAoTjUkaRHiqb7r9Iw1LXrlnMwiZyzx+MZQjoNwwoXVrjAOQA8FZu/vnnH7z77rt48eIF0tPTUbRoUTx+/Bje3t7w9/fP98qNOQ3bfekivf+FkIpBWI5zmR8DEG8Kvb32lvJHkslwMadZcx2WEgqXDTe50KCB5vvWLaBMGfPx+KxQrLuXn2IX8TOA633JjZeaCvjqhC/M/lwCqfRhjH8Hb1iuDvgD57PaIR6BilRuuG6/YIuiU68ecFv46bh3j1s8w2nQeuXJygKOHtWYeHTjGLZBtqzBYOFccR5DlcE/0y+DlpQbLlPFbeUDbNP8cKAZ0bzfJUeOHIl27drh2bNn8PLywt9//43bt2+jXr16mM9FFXdScpdw0a2ElsZBF2ME5uBLbLsVZjaOlH2YrR27XqNuwV9Cb1hKJJTYoQDAbVtae4Vgz2s7QdguHjZh6pniuy3GKgzAX3erG4WLgdR6K5ehci4kJPA/R/SyjR2r2aevXz87Z6xB8tlSOsi13EXupZNrbTBb4K3cxMbGYvTo0XBxcYGrqysyMjJQpkwZzJ07F1999ZUUMjoE1oalDGmBQwCAQmrzg89CnskqyadRAxcBWG54T5/mn7Yu5tI2el51h6V4PiBm8xCpQxF7FoThvTdc61Lo3lJits1Hj2pmGj14IEZq5mcRceHiRd2TOVp9OGah69Nh7Ry+DsUAUFj9DIA8KxRbw+6GPbksiblWhF9+4X8uB5lnfcOkLZqJYSm9uqZTca06FIusfDiiMmMIb+XGzc1Nuyu4v78/El6r8H5+frjjIGNxUsBXuZHyDTkaja3GsdW73pzlxjgj4eU0d6rUHYotVmxdmV/vNStKumLRvDmwcSMweLDp45LVS53C5+bx4oXOcRELqQKDnx9g6l3LajZmIphr7JVoRUxPB7ZvN33MnmspKnT0VOMzUrGi1WgzJmXg6BFm8ZqJrQQIGZYyPE8XmgrOg7CwMJw5cwYA0Lx5c0yePBm//vorRowYgZo1a4ouoKNgk3Jz6RIePgRatNB0PLkIrViFkGach2H+dqq1usNS4u2AK63sNk6uMItoyo0I9+7mTTNDNCJfWymth9aYNUuzZw5XHxRzaOa0SGtF5AOXavTBB/bxxXBIxo/n5DuSCl9UGaa/UKClBRJ5Y7C31GjMxwgsNhnV0rCUFAqr4SJ+jmjJ4a3cfPPNNwgKCgIAzJw5E0WKFMGgQYPw6NEj/PDDD6IL6CjoKjd37lh3mNNrFB8+xBdfaJxIu3UTTya7NbwWegxbZxOInqaEiKHciFU2n9T7Gl+Ec+c4xbfnG73JMoo4LKXbEHt6An10NikXqtwIOWYPgnAf5qYPmzKk8/G54Vqy1FSDIUYz6SvGCpCVxSlaAeQg8MIBSRfx02U+xmI+xpo8rNRV2JUM79lS9evX1/729/fHvn37RBXIUclVbtLTgbJlNb9PDDcf37BRfPrUOI5iGgMTcG7Uzfjc9MNqwXm7Igfd8Sui0Rg3dWaarVoFZGYCQ4ZYEUmitxC7WW6sUBlxGDijqubPjz+aH2qx2XLDo0AyVua4OOnSltuh+D5KYS7GApjLKS0+dTA7G3DjEC/qCNChlubZc+NygtxIMFQuPD1uN0SQz01cHNzVwQA8+cuVHy03hGlylZtXr/LCDJYAsoj5h4ZhGQZhGiYLFU16LDzx+sNSGt7AMVTHZcHJfoo1+BX/ww1U0Ia9egUUHNAdQUM/wONH8nSkarU0U2/5Nqj/wY6b0FjBVOc/ECsQiET9QHsNk4psueHq/6XbLojNF5gn6Lzduy0fz87ml55hGRVjubExY8ksN1LOltq7F6haFZsfvMnzRH2U/IJtDd6Wm7CwMKhM3BSVSgVPT09UrFgRvXv3xttvvy2KgI4C3wXaLDWYkyYBY8ZoKlZVXMEgrAAATMF0W0QUFbNTwS3MlsqlIjg6A5h5st7GYaOwzKdp6A7Nmvz3b90HSpTKO2jG+cDeG1WLNlvKSotTANZbwthY/WGLTZs0I1gFLdRL629v3FrCbzECw/Gt2S0opMTiCsVLlwLLlxsdt3VYatEiYNQoYMcOoEMHfvJlZAAeHgZxbKi4Ct2cnTNyd7aiW25EWMTP5J5wa9YAAGpnnrVFPF6o1cIXKpUC3qK0bdsWN27cQMGCBfH222/j7bffho+PD+Lj49GgQQMkJiYiIiICf/zxhxTyKhYxlZuvvwaGvx7S8oLwBWnkcXa08LrGzMQxg+FUarN5AGDZFjr0SpU45WcrUg1LScUbb+T9znXN4deRM4Pj3CmPmwZJiedzYwmL2Qwdaj5fGxyKR71enLxnT6tRjWjiGYPopmP05rZbmgxQHf9hOibBFyk2D0uJjdyKiRbFCGL5dUBX8eHtcyNSGTXJWF5JGQCePwdCQvT92+SGt3Lz+PFjjB49GseOHcOCBQuwYMECHD16FGPGjEF6ejr279+PiRMnYsaMGVLIq1hyF/HTxdLMeGuN4qlTmoollYIi6kZrZiw3X3+t7+8Qc45fnr+a2fXZtENq3tOvcpGnBc8bljLTESpgnRtdxF5s1KZxeQV1OIbIOVsqBvXR+OQC4MsvOcX/DzUxCV9jAUYDUJ5CncvGjcDBg9KkLfr0bDNO2Jau7cmTQJMmmq1ZLMHV50aMRfx093fjSsiayXiAQJSB5WVefvtN09+tWydMNingrdxs3rwZ3UxM6enatSs2b94MAOjWrRvipPTiUyCmLDd/7jIfn+9S9UKQcpYHl/MnTQI+/DAv3tkYzbfZxsegteDVoZjZoNOc34AHXqHBnI80XsgiwRjgMmYk7qAMisLY7GRTR8OYZkqKgFaOj94gtF4MGGB+x2klIbYOxed62ZT3hQu8ojfAGdvztBFrPjetWkmTr9wz2ACgaVMgOlqzrpQluEoqxiJ+tWvrnsAsOlXlplfulxkIQBKqwnJ/rsR3E97KjaenJ06ePGkUfvLkSXh6aryy1Wq19nd+waZhKRM1w3BBOCEobSp47gNjq1ymnDhZjo7lxjXvZpgTrR9Wo2T0Vk2vLBJqNeD63WKUxj0MwVKj4zY5FM+bB9Sqpdntk2fFePNN6aeSrloFvLTgNPss2cZlgnlgqX7Jsc5NOdxASVheG6IuYtAaf/EXzgJKG5ZSDDwrAdfp86aO6S1UafIcyz43xfAYl1ANlbZ8Y0VK6+g5fHftChQvbrzSqECcQrn5/PPPMXDgQAwfPhy//PILfvnlFwwfPhyDBg3Sbpr5119/oU6dOmLLqmjE9LkBNMM5w4cr4y3EFObk0l323lI80fPW6b25NOCFkSyeQCYwpYDZNCw1/bUz+c8/85blxAngsvXJaWbz18ph5e3Q0rle61dyE8AKkvrcmMvTFuUmORk3UAH3UNqi7DGoj7/QFl6J0jpZ87l+XnjFaQMwrqvj2qsDlGrasgtyoDqwH4WhUQgMr6WQ8lk7ZxzmoBquoMYGy/eBdzu7eTOQkqK/aqyuXA449dsQ3srNxIkTsWrVKpw+fRrDhg3DsGHDcPr0aaxatQoTXj8IAwcOxJ9//im6sErGJuXGTIuzc6dhpbWhdeC4cBVXzFmeDkaaj2f1gTF40vl0KHoOxbpr69hRN9Qbjzcho5zbL1ibivw1JiASLeAO8+sX2KKofoDtgs+VGi7XV7Byo7ObKpd8PBNvmgy/es36uZLwje0Wg1xs3axXLnKf20FYjgLvtcFpNDQZj8v91fXWYADUliw3gMXn0VA+e2HK716JlhveU8EBoEePHujRo4fZ415eXoIFclSMlRuGeogxG99QOeBSORojGnhRB/D25i9g3boG4/Z8nwjzAp45AzTQpqofzxvGdllJ/H10fFHM7c8iBeamawpVbsxeGxtbsIwMy8cnQNOJdcQOwXlI6VCcng4ULKgfduMGUL686fjmyD55GmlPk+DT9X3O50i9QrFm4kBugqav4cOHOvE51gW5h6WU2OEBECxYV2isHJXMLGXBJdkWLaAdoGQMUFt6ZniIaU9Ly9KlwPffQ6/ASlxBWdCs9OTkZKxevRpfffUVnr5eWvfcuXO4Z23PASfGULnpgk0YZ2LVUL7oNp4n0RRo08ZCbPPnmlwfnSPLMAg3UQ6+0JmOqpN28+bmn8ITaKr9be4B/OknjYWUK1aVG52ZU+YaHL6NQVncthpHNy+hw1KcEhfQOFtTbnLxgPmItgxLWcVCmYYNA3x8gGPH9K9hhQqaumOUlAU5C7cJh0+3dkg98o82zNp9sTQsJTZSKwRC6uClS+LLYQqlKkNcrxkX+e/f149vcbaUkh2kZs4ENpiZzqoQeCs358+fR+XKlTFnzhzMmzcPycnJAIBt27Zh/PjxYsvnMBgqN91h+cZzGZYyigcAx48D7dpxUpUtNsg8nptBWIEQ3IYrx9VY+2I1OmMTACCEg1LQuzfQvbspEXkMS+k4FIvdSnbHr7iNEJPHzOkcYio3YhSHq3Jjz40zubJkieZ74kTjYzNnCkvT96262t+2DEtZhUPiSu3Uc/nvP27x7FEOOa7V8+fc4gmxXlgcluJYVpuuiZlGyerLn8HDqMQ6zFu5GTVqFHr37o1r167pzYh69913cfToUVGFcyQM17l5hiIW41ubLWUyXi67dmnGghSCroylcRer0R+b0JVXGnv2CMsvF12fG7EtNxPxNad4YvjcFMVTjME8lIK4i9AkrdwOdZmyaAzjmY66iK3cvIljeBuHrEcU2Drao1EVzXLDSYsS721d7mEpvthrg0q+lea7716fZtBmWHIo9sILvIM98IBlZze+s69MYfK62UUzEj0ZUeGt3Jw5cwafffaZUXipUqXw4MEDUYRyRAwtN7yUGyE0aqR9VTh2jH8etrYj5tIupre+izQ13uRUcB3lRm8/KxMisNfdFVe4LpEuhnKzGv0wD1/gLsrAFTw397FAzx0fwOXuHezFO0bHwpC3c7jYys04zMUhtBQ1TV1MvS1LYX0SI00us4qUOCzFBW+kw332dD2/PiV2eLZgrQ7olvcn9MIevIcVGGjxHIs+N5Z49AhSta8A/2F7p/C58fDwQKrhfF8AV69eRYkSJXgLsHTpUoSEhMDT0xPh4eE4ffq02bj//fcfPvzwQ4SEhEClUmHx4sW885MKQ+UmDT4W44uyiN81zRSKZs04JcWJdev4z2rQldGVw75G5hMSvoifVLOlGOOu3OhuYcV1Q0VD3sRx7e/+MLPAoA2FMjX7YimsbKPOEalXKFapxJl+KxZ9sRolcd96RCtIWYa6Sfu4Wc4swEUhmo7J8Jw1BQgNFZzPiROCT1UEuvfxY/wOAOgNE05heicJyOinnwB/f3yDrwScbICSTXk2wlu5ad++PaZPn46s11OLVSoVEhISMG7cOHz44Ye80tq0aRNGjRqFKVOm4Ny5c6hduzbatGmDpKQkk/FfvHiB8uXLY/bs2QgMDOQruqQYKjd8nS/NNXCW/WbEr5h9+gDjxlmPZ04u3U5dqiXrrTkUi/kaoZnRwO0x0V0hX4yp4E1eDyFJPuNLp65KtSK2WOzcqf9fzmGp1eiPMMTySkccebhRIPUppp95B4fQ0iYrIJdrXB/G+wzIarmZqz+Z46uvgPfff91MSDQUIyRZS5Ybs33I558DAMZjNgD76yfF8NgoTIlWOt7KzYIFC5CWlgZ/f3+8fPkSzZs3R8WKFVGoUCHM5Ondt3DhQvTv3x99+vRB9erVsWLFCnh7e2PN6x1NDWnQoAHmzZuHrl27wsNwq1yZEXsRP1vpiO2C8+C756k5y41h/uI17pYtN9aGpQDuVgY+lhtdDC03Snn4rd0D2RaNNHeBDLabMLQq2uu62mtYSsyeqsDzZ9rfuc+lLcmfOaPZ1dwhdtYxeEObNQvYvRs4ZIMRi8+wlKNjqc2LQT3j+AosO+91bvz8/HDgwAEcP34c58+fR1paGurWrYuIiAhe6WRmZiImJkZvhpWLiwsiIiIQHR3NVyyzZGRkIENnqoipITUx4Kvc6HV+ZixVgHDLzXZ8wE8gHWypqFwsN1wRPFtKbd2hmCvmLDevXml20q5b18RJJmTkup1GJtzgDhMLLorUeih1xWuz5StUCG9iH47B9NirGJfFWhpCfG6WLwcGDTJORy5y87ZFuWn4eu06rlPD5erwLHXMmdbXxBOer4DyWntxknz9GgEVIhgJRmFOodzk8sYbb+CNN94QnPHjx4+Rk5ODgIAAvfCAgABcuXJFcLqGzJo1C9OmTRMtPXPYpNx064ZuFa9iLyYbxZOjQeQ7NVb3tyVfEyktN7pv+FwsN1wx18D06AFs25a3K4Ihliw3KgvXyKRiY0ooiVCc8vPyJTahC0oi0WQ7bK9hKb4MHgw0bgzU4RBXModiicYrbki7Q4TNWL1fIg5LSb1gqBjPowdeoT12IhItARTTP+jEs6UEKTeRkZGIjIxEUlIS1Ab+DeaGlORi/PjxGDVqlPZ/amoqypQpI3o+Ro6OPH1uPrk+BT1NKDeWYFAhS8I3EUuYe+gsDUtJmbc6i5/Pja3DUtu2ab5z12CxJiNjeXVEd2FDrjLY0lH1M+eYDOAbjEcTiGcptTfmZsPxwaaVoy2QmAjUCbKeBjOzoz0fTF4HBxqy44qtZRJT3+Prc5NgbPCwy8rCMzEBo7EQsaiN06djtRY4MVGicsPb52batGlo3bo1IiMj8fjxYzx79kzvw5XixYvD1dUVD3XXFQfw8OFDUZ2FPTw84Ovrq/eRCsO1bixhrUGoixicQX20RKTZOMOGqwTtxCAGXCw3tvrc8HJIzuE3W0osn5uiRU2HW7LcNMbfnPI2mwBPViFv53P9NYnuaJ0STR23KwLLJ4bvuNjDUiXwGAVMWODMpiFCz2DyOjDjZ9SJJ8doMXxedbsYKctv7TaWK8czPZEUn9xtI+rgX8yYYXBQ74LotJs881aicsPbcrNixQqsW7cOn3zyiU0Zu7u7o169eoiMjETHjh0BAGq1GpGRkRhqamcuB4DPg2NtqvBfaIPieIL6Fvan2rMXgideW5JVap8bqWdLiTUslXPsJDL+Om4yPxfkYD9aIyW5Cj7EMhPHTSg3jGEJPuecvxRvdbpl8TSxwJjihqWsoNRF/LLgjrsLegLzRliNq1dfBd5zmxZ843mOndeHs5lbt3iaWARiTtGOjtYMUZo6bul+Z2/YjOHYqv0fGQm0tHHJKJ11d42w5dlXyr3Whbdyk5mZiSZNmoiS+ahRo9CrVy/Ur18fDRs2xOLFi5Geno4+ffoAAHr27IlSpUph1qxZ2rwvvfZmy8zMxL179xAbGwsfHx9UrFhRFJlsQbcRsNZIWVNuiusthmcaqUyahj4ApnJphYPa3/aeLWXq2ukOSxUb8AGwcC7Qvr3ZNLhcO9dmTeELwJTP8Bs4jpY4BDw8BJhQbkwNS1V6dBJDsdRqvubS0EtMBMSuP1Kvc2PptIwMIHf+pBQKmpA0S0f+DMS+lRdg1ozIc1iKo+/R02fiTPG3BxE4AD+kYCs+klsUznAdlnrnHeD1LkW8KBa1Ve9/RASPx8RMREuTjFVOZrnhPSzVr18/bBBpw6wuXbpg/vz5mDx5MurUqYPY2Fjs27dP62SckJCAxMREbfz79+8jLCwMYWFhSExMxPz58xEWFoZ+/fqJIo+t8HkrkqWxsUMNFLp4HaCZfaQLL8uPzmuRW3ycZs4qpCtyASvrhphSbrwyeewOanCuWEg5FVyqjTNziYoyf5q59Tyr4RJ+xieohKuCRbOpXDrTczj53AjE1OUbPSbvt9TDUqY6Q671tgFO4wBa43d8jNK4I7Jk+njfv268WBJHhE4Ff2VhBwZBLwQGGRnd088+Ay5fNnkqV+XGRpEUAW/LzatXr/DDDz/g4MGDCA0NhZubm97xhQsX8kpv6NChZoehogxas5CQEDAlXsXX8Gk4uG5CKTfmLDe62G65YQBUmL8AVrYbtZCOGZuwXNXFUMl79Up44yFmGXTlsoczoyXGYB6neFzWGdJZ9V+PY3gTxfAUb+IYyuEWTwnzEGPjTHPtg1TKjS5SKze2dIynEa797Y8k3IX4Ez5yqft1J9HSEmMRPzGeQaN8f/jBbFxLw1KiyqAAeCs358+fR506dQAAFy9e1Dumyg/eahbgMywlBrzz4FgDbamoHshbU8ies6XMdRBCHIrFeFANlZv584GiChgacLFieranRXEevsj7Y6NDscE7lpZieAqA2+705pB840yd8L9PqSBk0J+rcpNLYTzDGnyKn9ETO8Cvw5fT58ZWRdAngeMiPQKwm3JjkFHprJuohYtmIuvnQT43Fjh8+LAUcjgFYuh2hZCKIRz9MpSi3Og+FKOwyGS4qf+64cZlMd+h8FFuTMF340yuMlg6fvEi0JznhTUn4587GdrxSok7cvlmXL0KlBJwXu4lLSB4xS5NGvfvAyXNHLdJuVFZ93vRrbvbtgOjTMayjLUp8YaWm+mYjE7YgU7YwXFdGGW8uNpSP7viN6gk3OFRrg5+2qPBnOO6uxsEcKifXFCicsPb54YwjxjKzQKMxiyOG6LZxTokQaWVYraUSeVm3Djg6VOTaVi6dmLcR0MZXVxsnAqvcyM+6WmTaNzztEJmhv5/W+rjH8LcILSXxajR5oFnRgpOz/hLeAKWiDE/2zEXMYalrPXZhvc1AA/NxDSBlUagsg3+TPYgt+y/obuk+QhpK8V4mfBWp3HPz8IjaotDsS7PngFPrM+HkRwb3ncIQ8QYlmqGo9zz4/lgqHOYJNosVwuLZcsNtzTNHVPnmIg/dy4KXrfuoDh9et6ifGJhOCzFdwVrXaR6K7J1WOroMeHnGhKIB4LOy702usNSfJ+9fptboeyDM2aP22S5WZW3gKJhGhcuACEhgIrZ3qnw9bnhlY9V5eYaUuBn8thDHjoUIK3Du1D88RBReAvVoL9yvuEaWLmX6fRpQHedPKm9NcR6yRXLcpO79ldGhm0vHbZClhsRsbfLEd/KuH69zrkcZbWlY+UqH9/1cHTD+2I1yiABI4abjlsg1ni3YkOmTAH+/ZeDoFbQXaTLpHKjRNutDbx6KV55PsEvKIgXJo9x8Y/SHZay7LhujCXFJjc9MTpV3TSOHAFCQ4FGjZTvUMyl7MVN7BR99iwg4nqsgrG185+M6UaKjcl8Xl+m8HDzxwwRo14xHjfVUj0Reyo4jzV9JYGUGxFRuj/1rj/5+dxERwNNOewUYKvlhk+ahsdWoz/OIxRZWeL4swDCdZAKFfJ+G8rv6sq/ITMno1hvr3I7FIuBNYdiXWSb5m6C3NnIly5BFKWXr0OxmJYbMeG7bQ2XNGy9d7qTJPTyMUjW3NCgSqWjhBusXO3Ood5aytgTL3ndS67KDV9Mld0WPzgxIOVGRKTw1RArLgC4qPgpN02aaEysUmOqHJbKZmgVKYwU8/Ht2TDrZCWGz43U2KrcyD2VXBcuyo1QpLDclC2bF647pCr1sJSgfBRkceRyH+R6zixdJrUamIuxeAkvvfDSpW2T9Sf0gljOBmL53GjTk7l5IOVGRMTwuZFSueFa2ZKSeCXLe1hJinTFVm5ePbbspGfSqdmKcsNXltw07Nm3KE0Bs4YpnxtzyF023fx132pZju0bvXJRbrKygOHDrWZl8lxrGMpXFE8QINCPylEwt85NPRgPhTMGjMV8FDDYMMfW/r8ztlitG3prWxk5N4qjgZiqfzlC9wYSCVJuRETpPjemLDcvTLs5IDZWgEAGGMrngQwUQBan4Sq+DsXm4qc+M/2EWWoQCqgzERfc2uxxc+g+4K4GjZgtDsX25FOskVsEq7ghE72wDmWQoDWHS7Wzd+55YitGeluccPC5Ebo6bi7hOIVbLT+F/+tZUnxevp6nMl6zX1RQ4wmK4wGC4I107idygZOmL4/JIFe0s2igF65SWdhXSoxNU1WWG5eSyFvlX6phKVPpSjjrnhMO0uQ6BkpXbgzlGzoUKFjQdNzr122XwzB8NsbjJspJYtExl+bzFDMrF1toAL94OBq1X0TzlkuvwzJI32afGxM7PEtBedyULG2x+AJzsQ59cBnVtJdl0iTp8pNiWMqcciPU4mttU8bdeB+Vjq3FSnzGO5+jA39FbPGWKGbCadhUXrqKfWnc5ZwPF9K4z3q2O5YUhy1bjMOk9J0zG5eUG8IWZmMcpmOK5PnYarlZamGtQKmGQkrjnpGDnjllRYxhKSEPbPen3/M+B9A4YJvLV2O5EXZRX74UdJpV5B6m4Yph490GmjVpCuIF1Grzw6j+Bmu5yO1QbE65MbmMAU8Mn9faOG9S5qqvZ/3w6RB/RD+0xCHMxASbZBSDp0+5DJHZBz7bL3zyidlUbJdDJEuVGLOlPPAKP+MTfIzNpNw4EyoVUAJJGIe5cotiEnvvK2Mu3HDTSZsWt7OShrmNPKVwhs0wPakCLsjBW3ErUSpF2NLvO3dC9JvnamXjTy4oQTliTLM3ZVvsNTq2BR/r/Zd9WIqZVm64DEsJ8bkxVfdNl4Nb2Yrgmfn8deSTrl4wfosPvsZe9ZTvC6F4bZByLDdD8T0+wS/YjC6yKze0iJ+IqFTWd4sWNT++ldHOsx7MyedmMB2Sz7nmjtlmuWHgO07P59r3w2r87/hAXukb5SHivSuOR4hDFZxDXdHSlBKLdUEFsNTn2It3tWG5nUYz6K8yaItyIzbmLDdcpv8nPlDB30J6uayA+TonRBnh2hlLpUx8g68wHrM55G8fuFpuzL2XqMB4P9evXgGeBudIsc4NX3LT1VU+5VZuyHIjIioVkANX++UHhmq4hNKwvgovAPhlPuKcNp9njq9i4Y5Mm84Xw3KjSy3kbSkdLGjnaMsXqyHEnU9va+fxGVaiKJ4hApEiSSQfjMHIEUOKzlWMNHWHhflabqxh6nlthYNGYdoZeDoqQLANm4qaQuwpxblwUWzkhK9yI4SVK40zUvPoxi3NlhJjWEr3PFJunAgfpKEHfrUpDT6NaCAe4BJq4A7KWo8MYMnOYKFiWYRvwy+35cZw48zxmKX9fRWVrcpmizx8kGodGXOLkjkqXBtRRxiWEuqAy/VlxFQ5hNR5S3B5odByU9+BXQlDnUKxXA9Nt0N8y5uaaipl+btxUm6cnPHpE7EQo+2WXxTeFnyutbcJMUZBbLXcmIO7LwG3hlb3zcedg+LFNW+lYnj9hWKvRfys5WOuEVUbnCfU30TqqeC6w1K/G/gJaeML8LmxGF8nPTeOQ+lcrwGva1W+vN5fXoqRGZTmUFw35wyeoJhRuGZYSgQ5FORzowutc+NEtMkUuLWxArHnsJQ2TwM/AClnS+m9YQh4DMroDAVq8uBnaZITsZQbJTAie75Z5YbLEHFj8J/yLxQpZ0vxtV5JqZjKPSvNFL5IEXyu2TbEhHJz/rxxvLWvuqKoWWdsEe49j3vp/9j8pAYxlBuy3DgpD11K2pyG0jpCW+DqUNwOfyICBzida+0Y17i6D6EQP6kf0U/7uyie4hZCMN9OVrvVOnkLwZmUm9k5Y+F5+qjJY4ZKq6mdxwvhudU8pFjnRhe+i/iZHGrlOSwltnJjTT6uiGG5MVWyZRhsQ3rG5SmL2yaVm/ff53Y+kLuIn2Cx9NPhyOiN9fX+P36ct2kw+dwQhAF8GzPDznUTuuIAWqM19gvOz5ZhKVs7riFYimAkYDQWipamETotaSfssCkpoT43hhYqpSjipUZ3NRluqLTeRHmT8bggRlnTX+StWSTccsPNimAOqe6ZOeWGbyfZHjtRysaF/3LUxnlGmHCutoVY1DG65iXHdMf/7hsvA2LZqszvfpi6z3x8btyz9RfN+nI8UKeOrjzCoEX8nB3l7CNoladPLR/nMyxlrrPkOxW8OY7ondvKwJpjKV1bpoL3ws9W41iCi4O0rYgwoUaLUMuNUpQZrog1c7ED/sAA/GBzOiowbNqk+S1knZtg3MJdlEaozuw+7XG7Wm6MM9N9ibDF+jIes3EXZQSfDwCvRPaXN1XviyDZ6Jr77fkN3+SMM4pr8d7weKRckIOQG4c088F1EDKsnpe9uOsTkeWGkJ3DUZaP81FubqCCyXBbfG7a4U+MwQLO6cq5iJ/hPlJSIGZDIVTeYniCkVgkniAS4Y0XOI9aKATra/VzqQdz8CX6irDnlgpM62QpZCr4bHyJUrhv8pi9FpD7BD/jMYqjMU7qhQsZlnoTpocTxUZKpdwmawdUUDHuD/YQLEXPn1qaTIdfxsJfBPkkKbdyQ4v4iYoI28TL/HYcjr9RFgkAOtucFl/Lje5Das5qYy7drzGRlwxiYkpZEHutDzGVMaFprcWnosnAB77yuoChFi5KJI1t5M5SFLJxpiWl1F6Wm5/RCwCwDR9YzQMA/JCCD7AVu/EeMuCpF28uvhAkg73h6lDM9/wCyEHre2s5y9ELP5kM5+NQbAlb/KZyFRmy3BCK5W80xmZ0QeFbsZLlwcVsnW1B7zb14FXADV55iaksVMNlozAxlKrW2A/310N+ciu9YvMvQgWd1x2/4k0cF1ka+6AC01NuyiABBZAlymypRo24yyAGhs+VuY5xJ9pjKz7CQoySTBapMduG2NnPyXy7KY7lRj9FfjK7qLPREgfho2MtpangzoQD+dxY69wLPbhmcx7mHhAuwyKW/CXEni1lK+9hj2hp6RKIh/gOwwAA2SLu6iFm2X2RgjdxFCoRZrmYowzuwuV1nfkV/5MsH6nRrYulbh5HAoJxGG9z9rmxdN8e8txySUgd4DqDUfd3SSQCMG11cBTlxhx23s3GrHLD23IjwbBUi9OzcBCtMBzf5clFlhtCDqxVZDGWhLfFD8aS5YaPw6IYU0ttxZZG4zMRHFkNscUB0ZBTCMdRNEdvrBMtTVOM0pmJ5sjkWm5qx2h8eN7ACVGeNc75yzQVXKpVvO2BrcNSYmHupZD383zR9JCtLcNSjS6uNpaLlBvnwYEMN3p0wUZ0xia9MDFM5eYekA4wvdgh17VnlGa54ZOvEtITs+xVEQcA6IbfREvTFOb8DRwJFRj69weePAGyCuT5n3B51lRgoty33Hpkas0fa1jKX6zZUlJhy7WTyueGL6INsYeFmQwWu80i5caJsLXxCRDQ4NiKL1KwEd2wCV1RUGe8VJ0txmJaPNdw4Gi5EUO5cRTEchbURQrFTurrLEX67bATS/C56OmaQwWG7Gzg88+BbFcd51o7mgBcoEZ9nEF7/GlTOnwX2fTEK5xBfczFWE5p2ILdtgVRzLAUz26cw7CUGPeGlBtnQoRnisuKqWLijRfa37rr1YhhueGLFJYbUw2CvRo/MciCGwDHklkKpOgId6IDquCq6Ola48oVIEtHuVGlJFs9R6z7Xwr3cQYNBZ0rxOcmFxcw1EcMxmI+p/RswdS1UuKWEHwx79hsm1WqGB5rf4sJKTdOhMHaSrzJgStKvK5ocpOTbXtFv4Tqgs8Vy3JjqkEohqeogf8EyWVvPJCJbzAeniLu5C2mz00u+V354kJuvVWr9ZWbqj3qWT23EJ6jCzZLJputCHnrl0ppELt+K322lC3P3mr0x2OUQAtE2ma5UeA6N6TcKAgpOh1LvI1DWGNm7ZLsLNsfSB+k84ovxbCUq5kGYRiWcBdMAGI23OMxW7S0AGUMS/GVQSlvz7ZgTrnhQhhiLR4/iJaobSWOlChZuZEsH56bldqKlMtajMcs0X2laCo4ocWeDTiDCofQEu9gn8nj6pcZmIcxaMVxvyexEWtYijBGLOVGdxgzApGipGkOZ7rnajWQ5eIhapotcQiRMF69VioM74fuf66dpFT3VOjeaeZQSt0zd13TXtj+POfA1VhBTUzkfH7RtASjMLktN7RCsYjY2mnY8yFaZGJRLV3CTq9AO5w1uwWCFFTDFU7xXBTS2DgqYik3XbFR7//72C1Kus5K7vNd5uVVuGVa3xqCL8VgZcM4CRHbGdUWGuNvozAprJVKcSgWo2w5cDVOv2RJm9Ik5YbQoqQplEWemV7x117I3UA6M2I19J4Q7mRW5fUUcq44Q31QgaE2YrH3RhjMLKjtsChpWEpsnG4quAlMWm5sTZOGpYhc5H7Y9So3jw3dnIEGOA0/JIuWnpLeZA2pi3NyiwAvnoqRC9Si3h85UIGhvZk1nhyBdjrTxy0NS5FyIw2OptyIuaq6EEi5URByW250K7R3RrJ8gsD+Dd8wfIdkFLFrnnLRAGdFSScAPNf8t4FKuO4U98dROnRTWJqxx69jZBzjiYcUU8GVskKxGKjhInr/k2V6f2S7QcqNgpC74ZPy4VE6bzjoZoxyUiAf1xchyP18i4ktlpvFGMEpnljYmo/Sh6XEwNByI0ZemRny1ndSbhSE3I2fkpQbe18LKafh95F43yXCMdBsfek8Co45rHWMupsr2guptl/gkq6j+NyIvYWG3MoNORQrCLmHpfKzclMeN0VNTwWGiriGtmam2hP5E2dVbpTscyPVApM37OwU7miWm+xMNeS0n5ByIyKONBXcFPbe+sEScl8LMbiGynKLQCgIZ6jT5tDtDLmW014vcyowBNrgH6aU+2buevWH8Y7cfDFUbpZjsM1pZmXI+7JOw1IK4kuRV6Lly3+oKWv+uijJikQQYuBMw1KWfG6CwG3xN7kt1Vwxd89Udl6sUGrLzVf4RtQ0NZYb+SDLjYIYhBVyi6AYHKXhM4ezdGKEuEzGDLlFkATd+r4T7Tmdw+UZ98RLbEIX7ML7gmWzlU7YYTL8KJqhOi5ZPd8Wq5EuUraJarigO34TNU25LTek3BCKhCw3hLORXxReP6Ryiselsx6IFWiPP9FeZ40dpfAGTtg1P6ktN2Ijt+WGhqUIReLolhuCMMSZlRshZePyjBd28IUbxYTvwpd8kGK2KCk3ToRUXvn5EbLcEIRyseRzIzQNQj6yJRjEkXtYipQbQpE4uuWGGm7CEGeuE0LKZukFphge2yKOHs583cVCimEpdTYpN04DWW7Egyw3hLPhzJ2skJcRS8/4Y5RAOWfbXVTBSLGwIssh5cZpcObGy94MxVK5RSAIwgyFkWJzGtYUog+wzeY8CBlRk3JDEE6HN17ILQKhMJz55UcKh2KxrpczX3clQ5YbJ4KGpYhcWuGg3CIQCsOZO1kpHIpJuXFsSLkhCIIgHBqy3BCGkHJDEASRD3DmTlbJyo2jz7x0VEi5IQiCyAc4s3IjBGszIkm5cXDIoZggCML5KYebcosgGUIUkQLItnh8Fr4SRTGpjss2p0Hwhyw3TgQ5FBMEYY6FGCW3CJLhIkC5cUOW1TiT8LUQcQglQJYbgiAI5ycQD+QWQVG4WbHcEI4NWW4IgiDyAc9QRG4RCMJukHJDEASRDyiDu3KLQBB2g9GwFEEQBEEQTgVZbpwHcigmCIIgCJBDsdNw+zYiECm3FARBEAQhOzQs5Szcvy+3BIQD87RgablFIAiCEA8alnIS3N3lloBwYJJ9ysgtAkEQhGjQbClngZQbwhZcyF+LIAgngoalnARSbgTxS7fdcougCFQqUm4IgnAiSLlxEtzc5JbAISng5hid+iMUlzYDstwQBOFEFE+/LWv+pNyIBVluBOHmLm2n/hda84r/BEVNhks9zT8/qTYv4CW3CIJZjb7I9KGVhm1lHsbILQIhMV/GdpU1f1JuxEIi5aYX1kmSrlR8iVm84kut3PyDMF7xH6GEyXC1xI+KSmbLzQI7buqYBce1cl5FZRQo6CG3GA7PGCyQWwTCySHlRiwkUm5cfX2QDD9J0paCOfiSV3yph6X4KiVJ8DcZ/lJia4OLq7zKjT07G0dWbpq+7QEXD7LSEoTSIeVGLHgqNzVxAQcHbbUaL6SyGzIg7ptiFgqImp4hkzAdZ1Df5LE4VNb7n108UDI51CoXZILffXlqZljqBbzFEMksLvnoScyWuP5JSbkq7oCHc1pufvf9FPiS38sJQSiVfNSkSgxPh+JrqIRX3qY7Ul3ULm4IQJJe2CsblZ0ElLXpfADIKBpk9tjXmISGOGPyWCLyzjuIlnhZKdRmWczh4u6G7zCM1zkv4I0BWGkyXErU7p74D9UlzUMp6Co3L8Lfkk8QARTwto9y89zbtAVRSqaU/hH4/HO756tEMt0L2nT+ETQTSRLT3C5mfbj9oRkrdH5BEcrN0qVLERISAk9PT4SHh+P06dMW42/ZsgVVq1aFp6cnatWqhT179thJUgsU0HkbDTOueHGojEFYpv2fBTd4PH9sNVl1AWPLQxp8zMYPxi2L6d1GWSzGCItxYlEbKfDFIjPx/kUoPB4mWEzDHCk6Q2zLMQienoKS4UaBAniGoliHXpxPudR2NH7HR0bhUg9LvXTzxaRmR9HZaycyPh0oKI3TaCDovKZVn/A+J6s6D6X06FG9vzvRXvvb+9h+o+isTh3e8tgLVy93oF49yfPx6tJB8jwMKVAAQFHrL1yOTCK4WYqXf5NsUz5vIQovIU3j9vh6Mm5WtD5R4uv3T0mSP1eOFbN/HdZFduVm06ZNGDVqFKZMmYJz586hdu3aaNOmDZKSkkzGP3nyJLp164a+ffvin3/+QceOHdGxY0dcvHjRzpIboLtOSY8eRocz4Y6ieKr9z+CCDO+8WRfq3zaZTLZGHWOL0HMUMitGAoLxJ943ezwEt/Aj+hofOHRI+3MhRqEonuIiappMo3inN/WVORNs2ACgc2ej8DYf+Wp/uyIHBS28IPXDKr3/zMsLKGJ5psr3HqPz/ri6AuA3DDJtVz2kw1goyZUblRd+P1wM65+1g8f3C3lZBy6jKn4LGoUqHaoJyvvoxaL47z8eJ9SsCbfDBwB/jm+G3t6YN/k5vPACBZGGVis/zjvm5gbc1p8yqurWTf/8p0+hFAoU9AAWLcJ+tDJ5/Boqan8nmXFO55SPjb5oaZ+PNwpjgeatrb/jQ80jbe5tY4EAn6wKFfifIzF/gFuHW66ScZsxr9IPPHJSSdNmzJ6N4hX8wBizHO+tt7DkzxCguMRLWFgg1VXmWYVMZho2bMiGDBmi/Z+Tk8NKlizJZs2aZTJ+586d2XvvvacXFh4ezj777DNO+aWkpDAALCUlRbjQ5nj6lLH79xnLzGQM0PvEIIwtwnDtf4Cx5cvUjH3/PWPR0Yyp1UbnMIBlHYs2CrvRvDc7/dEck/GbN2csPrSDyWO5+QKMsZQUxipVYqxuXcYOHNDI//rglrarGcBYP4+fjdMIDtacqxPfZPqMadI1jLN8ufb3yHpHWHY2Y+l1mxrFexe7mAo5mmuTG168uP5/E5/sI8fz/hcpwu7eZexZl8+0YQ1wSv+cX39lrHFjpis4YFy2fvjBbJ59scqiTFw+N+p+qF+Xbt9mrEwZxmbP1o/bt6/Jaz5zJmMsMZGxhg0Z+/FHxlq14p5/LrphDRsy9oOZMqemauI/f54XtmKF+fQfPWKZmYz98gtjd+++zuvgQcbu3NFmrfb1ZQxgai8vxh4+1J6rdnHRRDAjS8qzHHaw93qbrz/XT+LP+xljjNWrx1goYvWOZR05wVrUS9b+/wXdhef1/fcsrYCvUfh8jOJ2/vXrxmH//Wc2viuy2MqVJupB7ic2lrGdO/mV4fZtdrXUW3a7N9Y+EzGdFcRz1gTHrcaNj2fs9zHRrCs26F/TatUsnvekdRcWuyKaVa3K2Nk5By3n07at6fAmTcyfk5PDGGMsecQUy2nnPqPLlsl2vbcE5PXrYsGn/4boufMgIyODubq6su3bt+uF9+zZk7Vv397kOWXKlGGLFi3SC5s8eTILDQ01Gf/Vq1csJSVF+7lz5w7ni2MTBjd6EJayEZ55HXtue6HHrVvGleTZM8Zq1sz737mzJowxxq5c0YubNXSEJvzaNU1Y3bqaDqhDB8YAtnF8LAMY++231/mp1aZlvnSJvXrF2O0Td0w+WFp69mSsRAn2Hv7UxmnSRKOvadMfM4ax0FBNpgsWMJadrWkkZ8/Oy//JE7bl3TVs9/80DUnO6LHsyy8Z27fvdToFC2rS//hjxl68sPxQvXyZ9/vQIc35sbGMAezfwNasa1fG7riWzYvDmEbBARirVYsxxtiqVYxFYD+LrDVcGy8UsexrfKX9/3dAO8bc3RkDWNLJa3oyjIWO4vnpp4x99RU7/fFcdrNJN7NyZ0+ZblyHcq9PXJwmXvfu+v9ff379VaNP65GdrTl/40aW+WGXvPj+/nrnXug5N++cRo004dWqMfbokeZ+69a7y5fzGs1c/v037zp/+61+uWJiNMe5cPKk5lo9fqz5P306Y++9x1hysuZ/VpbmeG7aLVowNnJk3nVq0CCvnuh+atdmbOBA8RrtW7e0lzctjeWFf/KJtihH5kSzpRjE/PCMdcQ2ozTWfPCn5TyGD2csK4tl/HuZ3e8/mR3p+5P2WLXyr8yel1GvEWOVKzMWFaURROfYMgzUhE2cyNj77+sdyxw4lP39t05zoJvu6NGMTZmiCc/JYWzcOM19eX38Ruu8F4fU4Br65zLGUp7lWC6rGJ+33rIa53pAE1a4MGPnz78u4+LFRnGyPLwZA9jUsB1MrdZcj3XLddqbhw81gTt3Mla9Onu1+Q/2/DljrHlzzXF3d+N63aePebm+/to47NmzvHaza9e88LFjGfvrr7x0k5NNpvlqy07NS04ur15p7vekSawFDrIElGZb3v5e85bB5xqvWcP+xHtmj1/tP1e/TpUpz9LiH3B79nngMMrNvXv3GAB28uRJvfCxY8eyhg0bmjzHzc2NbdiwQS9s6dKlzN/f32T8KVOmMABGH8mVm8OHGXv7bcZOn2aPth5hI4fnsCvnMxhbuJA9PHienTpl5rzsbE0j8uQJY/fuacKSkhhbuVKjqBjy+++aByE9XT/cUHF5zYsXFmR++NCoM8p4pWbqzVs0b9qmyMpicXGMnV90QPNmYytPnxrLfuUKYxMmaI4xpmm8Dx/WyHr9OmOXLmkamMhIzfFXrxjLyNBP4/HjPOXs/n3GZs3Ks0Cp1YydOmX6+sbHM3bgALtyhbGFs16xlx/2YMcH/6o5NTlZc5wxjXYxbBhjUVEsNpax1V0PsDu7DTr2rCzGzp1jbNs2lvb1Qpb191nG/vxT05kZymuIoWKZk8NYt26MzZhh+TzGNHVj5Ej9e5iRwdQPk/TjPXnC2O7d+nldvKhpWJ88sZ5PLklJr3t+Cdi+nbFdu8wfv3BBYyL66iuNUnPrlqbST5/O2D//6FuYDhzQlDc8XKOYdejA2IMHLGnUN+xyqRbszonbmms8Zw5j8+dr0jBk+XKN8q41SeXx4AFjQUGMvRd8gb2Yt4Sxn3/W1E3GGNuzR1NfXr3SKI3vvqtRGsaNM0onMz2TrSs0hP3PczNLTWUs88Yd9nLmAo28773HMoeOZOqDkcay/fUXYwC7PHsHu3DB4Fhu722Kly8ZmztXY+kxRU4OYyNGaMqTm9axY5qOeetWjaKp++a2enXeNT9+XBP39f8/+v/JLtTWWLjUq3/UpH33LlO/2YyxsDDG2rfXPP+NG2s6+wsXNHW5QgXNS1+fPprnuGFDTZrNmmmu55MneRro118zduGCcXFfvNAoewBjZ86YLitjmns/c6b54xkZjK1Zo1V8jRg7ljFfX41C/s47jPXvz9jNm5oXha5dNdf6iy8YW7pU/zy1mrHNmzXlMcXdu5pnQa1mLCHBSuOuaTKHDdPcXu35q1axyKWX2b1FGzX16Y8/NP3A48csq3Zd9qpoIFNfiWOMMfboXga7vjmGZb7I0tyDH39k7NtvWc6j121DTAxL6vslOxtloh0VCT7KjYoxxmQaEcP9+/dRqlQpnDx5Eo0bN9aGf/HFFzhy5AhOnTJ2iHJ3d8dPP/2Ebjrj8suWLcO0adPw8OFDo/gZGRnIyMjQ/k9NTUWZMmWQkpICX19fo/gEQRAEQSiP1NRU+Pn5ceq/ZV1wonjx4nB1dTVSSh4+fIjAQNNe7YGBgbzie3h4wMNJ16UgCIIgCMIYWWdLubu7o169eoiMjNSGqdVqREZG6llydGncuLFefAA4cOCA2fgEQRAEQeQvZF8qdNSoUejVqxfq16+Phg0bYvHixUhPT0efPn0AAD179kSpUqUwa5Zmz6Lhw4ejefPmWLBgAd577z1s3LgRZ8+exQ8/8JmmRxAEQRCEsyK7ctOlSxc8evQIkydPxoMHD1CnTh3s27cPAQEBAICEhAS46KxN36RJE2zYsAETJ07EV199hUqVKmHHjh2oWdP0miwEQRAEQeQvZHUolgM+DkkEQRAEQSgDPv237CsUEwRBEARBiAkpNwRBEARBOBWk3BAEQRAE4VSQckMQBEEQhFNByg1BEARBEE4FKTcEQRAEQTgVpNwQBEEQBOFUkHJDEARBEIRTQcoNQRAEQRBOhezbL9ib3AWZU1NTZZaEIAiCIAiu5PbbXDZWyHfKzfPnzwEAZcqUkVkSgiAIgiD48vz5c/j5+VmMk+/2llKr1bh//z4KFSoElUolatqpqakoU6YM7ty5ky/2raLyOjdUXucmv5UXyH9ldrbyMsbw/PlzlCxZUm9DbVPkO8uNi4sLSpcuLWkevr6+TlGRuELldW6ovM5NfisvkP/K7EzltWaxyYUcigmCIAiCcCpIuSEIgiAIwqkg5UZEPDw8MGXKFHh4eMgtil2g8jo3VF7nJr+VF8h/Zc5v5dUl3zkUEwRBEATh3JDlhiAIgiAIp4KUG4IgCIIgnApSbgiCIAiCcCpIuSEIgiAIwqkg5UYkli5dipCQEHh6eiI8PBynT5+WWyRBzJo1Cw0aNEChQoXg7++Pjh07Ii4uTi/OW2+9BZVKpfcZOHCgXpyEhAS899578Pb2hr+/P8aOHYvs7Gx7FoUTU6dONSpL1apVtcdfvXqFIUOGoFixYvDx8cGHH36Ihw8f6qXhKGUFgJCQEKPyqlQqDBkyBIDj39ujR4+iXbt2KFmyJFQqFXbs2KF3nDGGyZMnIygoCF5eXoiIiMC1a9f04jx9+hQ9evSAr68vChcujL59+yItLU0vzvnz5/Hmm2/C09MTZcqUwdy5c6UumkkslTcrKwvjxo1DrVq1ULBgQZQsWRI9e/bE/fv39dIwVSdmz56tF0cp5QWs3+PevXsbladt27Z6cZzlHgMw+TyrVCrMmzdPG8fR7rEoMMJmNm7cyNzd3dmaNWvYf//9x/r3788KFy7MHj58KLdovGnTpg1bu3Ytu3jxIouNjWXvvvsuK1u2LEtLS9PGad68Oevfvz9LTEzUflJSUrTHs7OzWc2aNVlERAT7559/2J49e1jx4sXZ+PHj5SiSRaZMmcJq1KihV5ZHjx5pjw8cOJCVKVOGRUZGsrNnz7JGjRqxJk2aaI87UlkZYywpKUmvrAcOHGAA2OHDhxljjn9v9+zZwyZMmMC2bdvGALDt27frHZ89ezbz8/NjO3bsYP/++y9r3749K1euHHv58qU2Ttu2bVnt2rXZ33//zY4dO8YqVqzIunXrpj2ekpLCAgICWI8ePdjFixfZb7/9xry8vNjKlSvtVUwtlsqbnJzMIiIi2KZNm9iVK1dYdHQ0a9iwIatXr55eGsHBwWz69Ol691z3eVdSeRmzfo979erF2rZtq1eep0+f6sVxlnvMGNMrZ2JiIluzZg1TqVQsPj5eG8fR7rEYkHIjAg0bNmRDhgzR/s/JyWElS5Zks2bNklEqcUhKSmIA2JEjR7RhzZs3Z8OHDzd7zp49e5iLiwt78OCBNmz58uXM19eXZWRkSCkub6ZMmcJq165t8lhycjJzc3NjW7Zs0YZdvnyZAWDR0dGMMccqqymGDx/OKlSowNRqNWPMue6tYUegVqtZYGAgmzdvnjYsOTmZeXh4sN9++40xxtilS5cYAHbmzBltnL179zKVSsXu3bvHGGNs2bJlrEiRInrlHTduHKtSpYrEJbKMqY7PkNOnTzMA7Pbt29qw4OBgtmjRIrPnKLW8jJkuc69evViHDh3MnuPs97hDhw6sRYsWemGOfI+FQsNSNpKZmYmYmBhERERow1xcXBAREYHo6GgZJROHlJQUAEDRokX1wn/99VcUL14cNWvWxPjx4/HixQvtsejoaNSqVQsBAQHasDZt2iA1NRX//feffQTnwbVr11CyZEmUL18ePXr0QEJCAgAgJiYGWVlZeve2atWqKFu2rPbeOlpZdcnMzMQvv/yCTz/9VG8TWWe6t7rcvHkTDx480Luffn5+CA8P17ufhQsXRv369bVxIiIi4OLiglOnTmnjNGvWDO7u7to4bdq0QVxcHJ49e2an0ggjJSUFKpUKhQsX1gufPXs2ihUrhrCwMMybN09vmNERyxsVFQV/f39UqVIFgwYNwpMnT7THnPkeP3z4ELt370bfvn2NjjnbPbZGvts4U2weP36MnJwcvcYeAAICAnDlyhWZpBIHtVqNESNGoGnTpqhZs6Y2vHv37ggODkbJkiVx/vx5jBs3DnFxcdi2bRsA4MGDByavR+4xJREeHo5169ahSpUqSExMxLRp0/Dmm2/i4sWLePDgAdzd3Y06goCAAG05HKmshuzYsQPJycno3bu3NsyZ7q0hufKZkl/3fvr7++sdL1CgAIoWLaoXp1y5ckZp5B4rUqSIJPLbyqtXrzBu3Dh069ZNbxPFYcOGoW7duihatChOnjyJ8ePHIzExEQsXLgTgeOVt27YtPvjgA5QrVw7x8fH46quv8M477yA6Ohqurq5OfY9/+uknFCpUCB988IFeuLPdYy6QckOYZciQIbh48SKOHz+uFz5gwADt71q1aiEoKAgtW7ZEfHw8KlSoYG8xbeKdd97R/g4NDUV4eDiCg4OxefNmeHl5ySiZ9Pz444945513ULJkSW2YM91bIo+srCx07twZjDEsX75c79ioUaO0v0NDQ+Hu7o7PPvsMs2bNcshl+7t27ar9XatWLYSGhqJChQqIiopCy5YtZZRMetasWYMePXrA09NTL9zZ7jEXaFjKRooXLw5XV1ejGTQPHz5EYGCgTFLZztChQ7Fr1y4cPnwYpUuXthg3PDwcAHD9+nUAQGBgoMnrkXtMyRQuXBiVK1fG9evXERgYiMzMTCQnJ+vF0b23jlrW27dv4+DBg+jXr5/FeM50b3Pls/SsBgYGIikpSe94dnY2nj596rD3PFexuX37Ng4cOKBntTFFeHg4srOzcevWLQCOV15Dypcvj+LFi+vVYWe7xwBw7NgxxMXFWX2mAee7x6Yg5cZG3N3dUa9ePURGRmrD1Go1IiMj0bhxYxklEwZjDEOHDsX27dtx6NAhI1OlKWJjYwEAQUFBAIDGjRvjwoULeg1IbqNavXp1SeQWi7S0NMTHxyMoKAj16tWDm5ub3r2Ni4tDQkKC9t46alnXrl0Lf39/vPfeexbjOdO9LVeuHAIDA/XuZ2pqKk6dOqV3P5OTkxETE6ONc+jQIajVaq2i17hxYxw9ehRZWVnaOAcOHECVKlUUZ77PVWyuXbuGgwcPolixYlbPiY2NhYuLi3boxpHKa4q7d+/iyZMnenXYme5xLj/++CPq1auH2rVrW43rbPfYJHJ7NDsDGzduZB4eHmzdunXs0qVLbMCAAaxw4cJ6M0ochUGDBjE/Pz8WFRWlN23wxYsXjDHGrl+/zqZPn87Onj3Lbt68yf744w9Wvnx51qxZM20audOFW7duzWJjY9m+fftYiRIlFDNdWJfRo0ezqKgodvPmTXbixAkWERHBihcvzpKSkhhjmqngZcuWZYcOHWJnz55ljRs3Zo0bN9ae70hlzSUnJ4eVLVuWjRs3Ti/cGe7t8+fP2T///MP++ecfBoAtXLiQ/fPPP9rZQbNnz2aFCxdmf/zxBzt//jzr0KGDyangYWFh7NSpU+z48eOsUqVKetOEk5OTWUBAAPvkk0/YxYsX2caNG5m3t7cs02YtlTczM5O1b9+elS5dmsXGxuo9z7mzYk6ePMkWLVrEYmNjWXx8PPvll19YiRIlWM+ePRVZXmtlfv78ORszZgyLjo5mN2/eZAcPHmR169ZllSpVYq9evdKm4Sz3OJeUlBTm7e3Nli9fbnS+I95jMSDlRiSWLFnCypYty9zd3VnDhg3Z33//LbdIggBg8rN27VrGGGMJCQmsWbNmrGjRoszDw4NVrFiRjR07Vm8tFMYYu3XrFnvnnXeYl5cXK168OBs9ejTLysqSoUSW6dKlCwsKCmLu7u6sVKlSrEuXLuz69eva4y9fvmSDBw9mRYoUYd7e3qxTp04sMTFRLw1HKWsuf/31FwPA4uLi9MKd4d4ePnzYZP3t1asXY0wzHXzSpEksICCAeXh4sJYtWxpdhydPnrBu3boxHx8f5uvry/r06cOeP3+uF+fff/9lb7zxBvPw8GClSpVis2fPtlcR9bBU3ps3b5p9nnPXNYqJiWHh4eHMz8+PeXp6smrVqrFvvvlGTxFgTDnlZcxymV+8eMFat27NSpQowdzc3FhwcDDr37+/0Yums9zjXFauXMm8vLxYcnKy0fmOeI/FQMUYY5KahgiCIAiCIOwI+dwQBEEQBOFUkHJDEARBEIRTQcoNQRAEQRBOBSk3BEEQBEE4FaTcEARBEAThVJByQxAEQRCEU0HKDUEQBEEQTgUpNwRBEARBOBWk3BCEDLz11lsYMWKE3GJoYYxhwIABKFq0KFQqlXZPKSmZOnUq6tSpw+uckJAQLF68WBJ5nAUh15UgnA1SbgiCwL59+7Bu3Trs2rULiYmJqFmzplGcdevWoXDhwqLlOWbMGL1NLLlw5swZDBgwQDQZCIJwTgrILQBBEOKQk5MDlUoFFxf+7yy5O6E3adLEZjkyMzPh7u5uNZ6Pjw98fHx4pV2iRAmhYhEEkY8gyw2Rb3nrrbcwbNgwfPHFFyhatCgCAwMxdepU7fFbt24ZDdEkJydDpVIhKioKABAVFQWVSoW//voLYWFh8PLyQosWLZCUlIS9e/eiWrVq8PX1Rffu3fHixQu9/LOzszF06FD4+fmhePHimDRpEnS3esvIyMCYMWNQqlQpFCxYEOHh4dp8gTxLys6dO1G9enV4eHggISHBZFmPHDmChg0bwsPDA0FBQfjyyy+RnZ0NAOjduzc+//xzJCQkQKVSISQkxOj8qKgo9OnTBykpKVCpVFCpVNprFRISghkzZqBnz57w9fXVWlbGjRuHypUrw9vbG+XLl8ekSZOQlZWlTdNw+KR3797o2LEj5s+fj6CgIBQrVgxDhgzRO8dwWEqlUmH16tXo1KkTvL29UalSJezcuVNP9p07d6JSpUrw9PTE22+/jZ9++gkqlQrJyckmrxWguc/9+vVDiRIl4OvrixYtWuDff/8FADx69AiBgYH45ptvtPFPnjwJd3d3rSUqPj4eHTp0QEBAAHx8fNCgQQMcPHhQL4+QkBB8/fXX6NmzJ3x8fBAcHIydO3fi0aNH6NChA3x8fBAaGoqzZ89qz8m95zt27NCWqU2bNrhz547ZsgDA6tWrUa1aNXh6eqJq1apYtmyZ9lhmZiaGDh2KoKAgeHp6Ijg4GLNmzTKbVlRUFBo2bIiCBQuicOHCaNq0KW7fvq09/scff6Bu3brw9PRE+fLlMW3aNG1ds3Ztgbx6sX79eoSEhMDPzw9du3bF8+fPLZaRIPSQd99OgpCP5s2bM19fXzZ16lR29epV9tNPPzGVSsX279/PGGPaXZX/+ecf7TnPnj3T21U5d8feRo0asePHj7Nz586xihUrsubNm7PWrVuzc+fOsaNHj7JixYrp7bLbvHlz5uPjw4YPH86uXLnCfvnlF+bt7c1++OEHbZx+/fqxJk2asKNHj7Lr16+zefPmMQ8PD3b16lXGGGNr165lbm5urEmTJuzEiRPsypUrLD093aicd+/eZd7e3mzw4MHs8uXLbPv27ax48eJsypQpjDHGkpOT2fTp01np0qVZYmIiS0pKMkojIyODLV68mPn6+rLExESWmJio3UU5ODiY+fr6svnz57Pr169rd1WfMWMGO3HiBLt58ybbuXMnCwgIYHPmzNGmOWXKFFa7dm3t/169ejFfX182cOBAdvnyZfbnn38aXZPg4GC2aNEi7X8ArHTp0mzDhg3s2rVrbNiwYczHx4c9efKEMcbYjRs3mJubGxszZgy7cuUK++2331ipUqUYAPbs2TNzVYNFRESwdu3asTNnzrCrV6+y0aNHs2LFimnT3b17N3Nzc2NnzpxhqamprHz58mzkyJHa82NjY9mKFSvYhQsX2NWrV9nEiROZp6cnu337tl5ZihYtylasWMGuXr3KBg0axHx9fVnbtm3Z5s2bWVxcHOvYsSOrVq0aU6vVeve8fv367OTJk+zs2bOsYcOGrEmTJmav6y+//MKCgoLY1q1b2Y0bN9jWrVtZ0aJF2bp16xhjjM2bN4+VKVOGHT16lN26dYsdO3aMbdiwweR1ycrKYn5+fmzMmDHs+vXr7NKlS2zdunXach09epT5+vqydevWsfj4eLZ//34WEhLCpk6dyvnaTpkyhfn4+LAPPviAXbhwgR09epQFBgayr776yuz9IghDSLkh8i3Nmzdnb7zxhl5YgwYN2Lhx4xhj/JSbgwcPauPMmjWLAWDx8fHasM8++4y1adNGL2/dTosxxsaNG8eqVavGGGPs9u3bzNXVld27d09PvpYtW7Lx48czxjQdHQAWGxtrsZxfffUVq1Klil5eS5cuZT4+PiwnJ4cxxtiiRYtYcHCwxXTWrl3L/Pz8jMKDg4NZx44dLZ7LmKYTrVevnva/KeUmODiYZWdna8M+/vhj1qVLF728DJWbiRMnav+npaUxAGzv3r2MMc01rVmzpp4cEyZMsKjcHDt2jPn6+rJXr17phVeoUIGtXLlS+3/w4MGscuXKrHv37qxWrVpG8Q2pUaMGW7JkiV5Z/ve//2n/JyYmMgBs0qRJ2rDo6GgGgCUmJjLG8u7533//rY1z+fJlBoCdOnWKMWZ8XStUqGCkrMyYMYM1btyYMcbY559/zlq0aKFXP8zx5MkTBoBFRUWZPN6yZUv2zTff6IWtX7+eBQUFMca4XdspU6Ywb29vlpqaqj0+duxYFh4eblU+gsiFfG6IfE1oaKje/6CgICQlJdmUTkBAgHYoRjfs9OnTeuc0atQIKpVK+79x48ZYsGABcnJycOHCBeTk5KBy5cp652RkZKBYsWLa/+7u7kZlMOTy5cto3LixXl5NmzZFWloa7t69i7Jly/IrrAnq169vFLZp0yZ89913iI+PR1paGrKzs+Hr62sxnRo1asDV1VX7PygoCBcuXLB4jm75CxYsCF9fX+09jIuLQ4MGDfTiN2zY0GJ6//77L9LS0vSuMwC8fPkS8fHx2v/z589HzZo1sWXLFsTExMDDw0N7LC0tDVOnTsXu3buRmJiI7OxsvHz50mjY0LDeAECtWrWMwpKSkhAYGAgAKFCggF6ZqlatisKFC+Py5ctGZUtPT0d8fDz69u2L/v37a8Ozs7Ph5+cHQDMc2KpVK1SpUgVt27bF+++/j9atW5u8NkWLFkXv3r3Rpk0btGrVChEREejcuTOCgoK01+7EiROYOXOm9pycnBy8evUKL1684HxtQ0JCUKhQIe1/oc8lkX8h5YbI17i5uen9V6lUUKvVAKB1zGU6fjC6/h/m0lGpVBbT5UJaWhpcXV0RExOj19kD0HPC9fLy0lNa5KJgwYJ6/6Ojo9GjRw9MmzYNbdq0gZ+fHzZu3IgFCxZYTEfIdbP1WhuSlpaGoKAgPf+mXHRni8XHx+P+/ftQq9W4deuWnlIyZswYHDhwAPPnz0fFihXh5eWFjz76CJmZmWZlz72PpsKElictLQ0AsGrVKoSHh+sdy61XdevWxc2bN7F3714cPHgQnTt3RkREBH7//XeTaa5duxbDhg3Dvn37sGnTJkycOBEHDhxAo0aNkJaWhmnTpuGDDz4wOs/T05PztRX7nhL5D1JuCMIMuTNzEhMTERYWBgCirv9y6tQpvf9///03KlWqBFdXV4SFhSEnJwdJSUl48803bcqnWrVq2Lp1Kxhj2s7yxIkTKFSoEEqXLs05HXd3d+Tk5HCKe/LkSQQHB2PChAnaMF2nU3tRpUoV7NmzRy/szJkzFs+pW7cuHjx4gAIFCph0rgY0Trj/+9//0KVLF1SpUgX9+vXDhQsX4O/vD0BzfXv37o1OnToB0CgZt27dsrk8gMbqcvbsWa2VJi4uDsnJyahWrZpR3ICAAJQsWRI3btxAjx49zKbp6+uLLl26oEuXLvjoo4/Qtm1bPH36FEWLFjUZPywsDGFhYRg/fjwaN26MDRs2oFGjRqhbty7i4uJQsWJFk+dxubYEIQY0W4ogzODl5YVGjRph9uzZuHz5Mo4cOYKJEyeKln5CQgJGjRqFuLg4/Pbbb1iyZAmGDx8OAKhcuTJ69OiBnj17Ytu2bbh58yZOnz6NWbNmYffu3bzyGTx4MO7cuYPPP/8cV65cwR9//IEpU6Zg1KhRvKaNh4SEIC0tDZGRkXj8+LHR7C9dKlWqhISEBGzcuBHx8fH47rvvsH37dl5yi8Fnn32GK1euYNy4cbh69So2b96MdevWAYBZi1dERAQaN26Mjh07Yv/+/bh16xZOnjyJCRMmaGcuTZgwASkpKfjuu++0s8I+/fRTbRqVKlXCtm3bEBsbi3///Rfdu3cXzfLg5uaGzz//HKdOnUJMTAx69+6NRo0amR1umzZtGmbNmoXvvvsOV69exYULF7B27VosXLgQALBw4UL89ttvuHLlCq5evYotW7YgMDDQ5JpGN2/exPjx4xEdHY3bt29j//79uHbtmlaxmjx5Mn7++WdMmzYN//33Hy5fvoyNGzdqnxsu15YgxICUG4KwwJo1a5CdnY169ephxIgR+Prrr0VLu2fPnnj58iUaNmyIIUOGYPjw4XoL1K1duxY9e/bE6NGjUaVKFXTs2BFnzpzh7SNTqlQp7NmzB6dPn0bt2rUxcOBA9O3bl7ei1qRJEwwcOBBdunRBiRIlMHfuXLNx27dvj5EjR2Lo0KGoU6cOTp48iUmTJvHKTwzKlSuH33//Hdu2bUNoaCiWL1+utSbp+sjoolKpsGfPHjRr1gx9+vRB5cqV0bVrV9y+fRsBAQGIiorC4sWLsX79evj6+sLFxQXr16/HsWPHsHz5cgAahaFIkSJo0qQJ2rVrhzZt2qBu3bqilMnb2xvjxo1D9+7d0bRpU/j4+GDTpk1m4/fr1w+rV6/G2rVrUatWLTRv3hzr1q1DuXLlAACFChXC3LlzUb9+fTRo0AC3bt3Cnj17TCq+3t7euHLlCj788ENUrlwZAwYMwJAhQ/DZZ58BANq0aYNdu3Zh//79aNCgARo1aoRFixYhODiY07UlCLFQMV2HAoIgCCdn5syZWLFihdW1YZTIunXrMGLECItr9BAEQT43BEE4OcuWLUODBg1QrFgxnDhxAvPmzcPQoUPlFosgCAkh5YYgCKfm2rVr+Prrr/H06VOULVsWo0ePxvjx4+UWiyAICaFhKYIgCIIgnApyKCYIgiAIwqkg5YYgCIIgCKeClBuCIAiCIJwKUm4IgiAIgnAqSLkhCIIgCMKpIOWGIAiCIAingpQbgiAIgiCcClJuCIIgCIJwKv4PK0lQ7p8sBJYAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -961,7 +959,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -991,7 +989,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { "tags": [] }, @@ -1013,7 +1011,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -1074,26 +1072,26 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2490912/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" ] }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxMAAANXCAYAAABOkwIqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd1hURxfA4R9dQEGKKIiIggW7Yom9xmisscfYGyr2jl2jYu8SS4y9xN5ibLH3giLSFEGxIIgFkF72+4N8G1dAkQhL5LzPs4/u3Llzzyx3Yc/O3LkaCoVCgRBCCCGEEEJ8Jk11ByCEEEIIIYT4b5JkQgghhBBCCJEpkkwIIYQQQgghMkWSCSGEEEIIIUSmSDIhhBBCCCGEyBRJJoQQQgghhBCZIsmEEEIIIYQQIlMkmRBCCCGEEEJkiiQTQgghhBBCiEyRZEIIkS5bW1t69eql7jBypAYNGtCgQYNM7ftffl179eqFra2tusMQQgiRQ0gyIUQu9PDhQ5ycnChevDh58uTByMiI2rVrs2zZMmJiYtQdXoY9evQIDQ0NNDQ0mDVrVpp1fvrpJzQ0NMibN282R/ffEhERwYwZM6hYsSJ58+ZFX1+fcuXKMX78eJ4/f67u8D6Lra2t8rzQ1NQkf/78lC9fngEDBnDt2rV/1facOXM4cODAlwlUCCG+AtrqDkAIkb3++OMPOnbsiJ6eHj169KBcuXLEx8dz8eJFxo4di5eXF2vXrlV3mJ8lT5487Nixg8mTJ6uUR0VFcfDgQfLkyaOmyP4bAgICaNKkCUFBQXTs2JEBAwagq6vL3bt3Wb9+Pfv37+f+/fvqDvOzVKpUidGjRwMQGRmJj48Pu3fvZt26dYwcOZLFixdnqt05c+bQoUMH2rZt+wWjFUKI/y5JJoTIRQIDA+nSpQtFixbl9OnTWFpaKrc5Ozvj7+/PH3/8ocYIM+f7779n3759eHh4ULFiRWX5wYMHiY+Pp1mzZpw+fVqNEeZciYmJtGvXjpCQEM6ePUudOnVUts+ePZt58+apKbrMK1y4MN26dVMpmzdvHl27dmXJkiWUKFGCQYMGqSk6IYT4esg0JyFykfnz5/Pu3TvWr1+vkkj8n729PcOHD/9oG2/fvmXEiBEUKVIEPT097O3tmTdvHsnJySr1Fi5cSK1atTAzM0NfXx9HR0f27NmTqj0NDQ2GDBnCgQMHKFeuHHp6epQtW5Zjx45luF81a9akWLFibN++XaV827ZtNGvWDFNT0zT3c3Nzo2zZsujp6WFlZYWzszNv375NVW/t2rXY2dmhr69P9erVuXDhQprtxcXFMW3aNOzt7dHT06NIkSKMGzeOuLi4DPflfVFRUYwePVr5WpcqVYqFCxeiUChU6v2b13Dv3r14eHgwadKkVIkEgJGREbNnz/5oG8nJySxdupSyZcuSJ08eChYsiJOTE2/evFGpd/DgQVq0aIGVlRV6enrY2dnx888/k5SUpFKvQYMGlCtXDm9vbxo2bIiBgQGFCxdm/vz5n+zPx+jr67NlyxZMTU2ZPXu2yuuYkfNVQ0ODqKgoNm3apJxG9f9rXx4/fszgwYMpVaoU+vr6mJmZ0bFjRx49evSvYhZCiJxOkgkhcpHDhw9TvHhxatWqlan9o6OjqV+/Plu3bqVHjx4sX76c2rVr4+LiwqhRo1TqLlu2jMqVKzNz5kzmzJmDtrY2HTt2THPk4+LFiwwePJguXbowf/58YmNjad++Pa9evcpwbD/++CM7d+5UfkAMCwvjxIkTdO3aNc3606dPx9nZGSsrKxYtWkT79u1Zs2YNTZs2JSEhQVlv/fr1ODk5UahQIebPn0/t2rVp3bo1T548UWkvOTmZ1q1bs3DhQlq1asWKFSto27YtS5YsoXPnzhnux/8pFApat27NkiVLaNasGYsXL6ZUqVKMHTs21WsNmX8NDx06BED37t0/O8b/c3JyYuzYscrrbnr37s22bdv47rvvVF7LjRs3kjdvXkaNGsWyZctwdHRk6tSpTJgwIVWbb968oVmzZlSsWJFFixZRunRpxo8fz59//pnpOAHy5s3LDz/8wLNnz/D29laWZ+R83bJlC3p6etStW5ctW7awZcsWnJycALhx4waXL1+mS5cuLF++nIEDB/LXX3/RoEEDoqOj/1XMQgiRoymEELlCeHi4AlC0adMmw/sULVpU0bNnT+Xzn3/+WWFoaKi4f/++Sr0JEyYotLS0FEFBQcqy6OholTrx8fGKcuXKKRo1aqRSDih0dXUV/v7+yjIPDw8FoFixYsVH4wsMDFQAigULFiju3bunABQXLlxQKBQKxapVqxR58+ZVREVFKXr27KkwNDRU7hcaGqrQ1dVVNG3aVJGUlKQsX7lypQJQ/Pbbb8qYLSwsFJUqVVLExcUp661du1YBKOrXr68s27Jli0JTU1N5/P9bvXq1AlBcunRJWfbh65qWAwcOKADFrFmzVMo7dOig0NDQUHm9/s1rWLlyZYWxsfFH67yvZ8+eiqJFiyqfX7hwQQEotm3bplLv2LFjqco/PCcUCoXCyclJYWBgoIiNjVWW1a9fXwEoNm/erCyLi4tTFCpUSNG+fftPxli0aFFFixYt0t2+ZMkSBaA4ePBgurGld74aGhqm+bNLq29XrlxJ1Q8hhPjayMiEELlEREQEAPny5ct0G7t376Zu3bqYmJgQFhamfDRp0oSkpCTOnz+vrKuvr6/8/5s3bwgPD6du3bq4u7unardJkybY2dkpn1eoUAEjIyMCAgIyHFvZsmWpUKECO3bsAGD79u20adMGAwODVHVPnTpFfHw8I0aMQFPzn1+D/fv3x8jISPlt9M2bNwkNDWXgwIHo6uoq6/Xq1QtjY+NUr42DgwOlS5dWeW0aNWoEwJkzZzLcF4CjR4+ipaXFsGHDVMpHjx6NQqFI9Q19Zl/DiIiIf31OGBsb8+2336r029HRkbx586r0+/1zIjIykrCwMOrWrUt0dDS+vr4q7ebNm1flmgddXV2qV6/+WedEev6/sldkZGSasX3qfE3L+/snJCTw6tUr7O3tyZ8/f4bbEEKI/yK5AFuIXMLIyAhQ/QD1uR48eMDdu3cpUKBAmttDQ0OV/z9y5AizZs3izp07KtcMaGhopNrPxsYmVZmJiUmqOfef0rVrVxYtWsTIkSO5fPkyEydOTLPe48ePAShVqpRKua6uLsWLF1du//+/JUqUUKmno6ND8eLFVcoePHiAj49Phl6bjHj8+DFWVlapPug7ODioxPZ/mX0NPzdp+9CDBw8IDw/HwsIize3v99vLy4vJkydz+vRpZXL7f+Hh4SrPra2tU50rJiYm3L17N9Ox/t+7d+8A1cT6c87XtMTExODq6sqGDRt49uyZyvUYH/ZNCCG+JpJMCJFLGBkZYWVlxb179zLdRnJyMt9++y3jxo1Lc3vJkiUBuHDhAq1bt6ZevXq4ublhaWmJjo4OGzZsSHWRNICWllaa7Sk+uND4U3788UdcXFzo378/ZmZmNG3a9LP2/zeSk5MpX758ukuOFilSJEuPn9nXsHTp0ty+fZsnT55kKsbk5GQsLCzYtm1bmtv/n1y9ffuW+vXrY2RkxMyZM7GzsyNPnjy4u7szfvz4VBfwf6lzIi3/fw/Y29sDn3++pmXo0KFs2LCBESNGULNmTYyNjdHQ0KBLly6p+iaEEF8TSSaEyEVatmzJ2rVruXLlCjVr1vzs/e3s7Hj37h1NmjT5aL29e/eSJ08ejh8/jp6enrJ8w4YNn33Mz2FjY0Pt2rU5e/YsgwYNQls77V9xRYsWBcDPz09lhCE+Pp7AwEBl//5f78GDB8rpSpAyjSUwMFBlGVo7Ozs8PDxo3Lhxhr/N/piiRYty6tQpIiMjVb5B//90oP/H9m+1atWKHTt2sHXrVlxcXD57fzs7O06dOkXt2rVVpvp86OzZs7x69Yp9+/ZRr149ZXlgYGCm4s6sd+/esX//fooUKaIc5fmc8zW9n+2ePXvo2bMnixYtUpbFxsamuTqYEEJ8TeSaCSFykXHjxmFoaEi/fv0ICQlJtf3hw4csW7Ys3f07derElStXOH78eKptb9++JTExEUj5VllDQ0Nlyc9Hjx5ly52DZ82axbRp0xg6dGi6dZo0aYKuri7Lly9X+aZ7/fr1hIeH06JFCwCqVq1KgQIFWL16NfHx8cp6GzduTPUhsVOnTjx79ox169alOl5MTAxRUVGf1Y/vv/+epKQkVq5cqVK+ZMkSNDQ0aN68+We1l54OHTpQvnx5Zs+ezZUrV1Jtj4yMZNKkSenu36lTJ5KSkvj5559TbUtMTFS+Tv8faXj/9Y6Pj8fNze1f9iDjYmJi6N69O69fv2bSpEnKxOBzzldDQ8M0EwQtLa1UoyYrVqxIteytEEJ8bWRkQohcxM7Oju3bt9O5c2ccHBxU7oB9+fJldu/erVw3Py1jx47l0KFDtGzZkl69euHo6EhUVBSenp7s2bOHR48eYW5uTosWLVi8eDHNmjWja9euhIaGsmrVKuzt7b/InPePqV+/PvXr1/9onQIFCuDi4sKMGTNo1qwZrVu3xs/PDzc3N6pVq6a88FdHR4dZs2bh5OREo0aN6Ny5M4GBgWzYsCHVNRPdu3dn165dDBw4kDNnzlC7dm2SkpLw9fVl165dHD9+nKpVq2a4H61ataJhw4ZMmjSJR48eUbFiRU6cOMHBgwcZMWKEysXW/4aOjg779u2jSZMm1KtXj06dOlG7dm10dHTw8vJi+/btmJiYpHuvifr16+Pk5ISrqyt37tyhadOm6Ojo8ODBA3bv3s2yZcvo0KEDtWrVwsTEhJ49ezJs2DA0NDTYsmXLF5m2lJZnz56xdetWIGU0wtvbm927d/PixQtGjx6tXNIV+Kzz1dHRkVOnTrF48WKsrKwoVqwYNWrUoGXLlmzZsgVjY2PKlCnDlStXOHXqFGZmZlnSPyGEyDHUto6UEEJt7t+/r+jfv7/C1tZWoaurq8iXL5+idu3aihUrVqgs0ZnWEqaRkZEKFxcXhb29vUJXV1dhbm6uqFWrlmLhwoWK+Ph4Zb3169crSpQoodDT01OULl1asWHDBsW0adMUH/7aARTOzs6pYszI8qnvLw37MR8uDft/K1euVJQuXVqho6OjKFiwoGLQoEGKN2/epKrn5uamKFasmEJPT09RtWpVxfnz5xX169dXWRpWoUhZTnTevHmKsmXLKvT09BQmJiYKR0dHxYwZMxTh4eGf1TeFIuW1HjlypMLKykqho6OjKFGihGLBggWK5ORklXr/5jX8vzdv3iimTp2qKF++vMLAwECRJ08eRbly5RQuLi6K4OBgZb0Pl4b9v7Vr1yocHR0V+vr6inz58inKly+vGDdunOL58+fKOpcuXVJ88803Cn19fYWVlZVi3LhxiuPHjysAxZkzZ5T16tevryhbtmyqY6R37LT6DSgAhYaGhsLIyEhRtmxZRf/+/RXXrl1Lc5+Mnq++vr6KevXqKfT19RWA8vV98+aNonfv3gpzc3NF3rx5Fd99953C19f3s34GQgjxX6ShUGTR10JCCCGEEEKIr5pcMyGEEEIIIYTIFEkmhBBCCCGEEJkiyYQQQgghhBAiUySZEEIIIYQQ4ivzyy+/UKFCBYyMjDAyMqJmzZr8+eefyu2xsbE4OztjZmZG3rx5ad++fZrLxn+KXIAthBBCCCHEV+bw4cNoaWlRokQJFAoFmzZtYsGCBdy+fZuyZcsyaNAg/vjjDzZu3IixsTFDhgxBU1OTS5cufdZxJJkQQgghhBAiFzA1NWXBggV06NCBAgUKsH37djp06ACAr68vDg4OXLlyhW+++SbDbco0JyGEEEIIIf4j4uLiiIiIUHnExcV9dJ+kpCR27txJVFQUNWvW5NatWyQkJNCkSRNlndKlS2NjY8OVK1c+K56v8g7YCWEB6g5BLcyKNvl0pa9QPl19dYegFiFRb9UdglrUsXBQdwhq4f4md/5eK2Rgqu4Q1CIgPFjdIaiFgY6eukMQ2SgiKuf+XsvJnyVdV25mxowZKmXTpk1j+vTpqep6enpSs2ZNYmNjyZs3L/v376dMmTLcuXMHXV1d8ufPr1K/YMGCvHjx4rPi+SqTCSGEEEIIIb5GLi4ujBo1SqVMTy/tRLxUqVLcuXOH8PBw9uzZQ8+ePTl37twXjUeSCSGEEEIIIf4j9PT00k0ePqSrq4u9vT0Ajo6O3Lhxg2XLltG5c2fi4+N5+/atyuhESEgIhQoV+qx45JoJIYQQQggh3peclHMf/6ZbycnExcXh6OiIjo4Of/31l3Kbn58fQUFB1KxZ87PalJEJIYQQQgghvjIuLi40b94cGxsbIiMj2b59O2fPnuX48eMYGxvTt29fRo0ahampKUZGRgwdOpSaNWt+1kpOIMmEEEIIIYQQX53Q0FB69OhBcHAwxsbGVKhQgePHj/Ptt98CsGTJEjQ1NWnfvj1xcXF89913uLm5ffZxvsr7TOTkK/CzkqzmlLvIak65i6zmlLvIak4iN8jRqzmF+Kk7hHTpFCyl7hBUyDUTQgghhBBCiEyRZEIIIYQQQgiRKXLNhBBCCCGEEO9LTlZ3BP8ZMjIhhBBCCCGEyBRJJoQQQgghhBCZItOchBBCCCGEeI9CIdOcMkpGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvS05SdwT/GTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifrOaUYbl+ZCIqKpq5S1fzbbueODZsw09Oo/D08VNuj46OYfYiNxq37YZjwza0/mkAv+//45PtRkS+Y9aiVTRo3ZXKDVrRoks/zl++rtx+5PhpGv/QnVrNOjJ/+VqVfZ8Fh9CiSz/eRUV9uY5mUP8B3fH0Pk/oKx9On92Ho2OFdOuWdijBlm1ueHqfJyIqgMHOvVPV6dS5Dd5+F3n89DZz5k5S2WZjUxj3O3+RL1/eL96Pz9Wz349c9TjBw2B3Dp/cQaUq5dOt27VHB/Yd3YxX4GW8Ai+zc/+vqeo7DemFx/3zeNw/j5NzT5VtlR3L8+eZXWhpaWVJX8Snte3Zmp1XtnLC/yhuh1dQulKpdOs269iUs09PqTxO+B9VqdPZqSP77+xm/53ddBrQQWWbQ+XSrDnqhpaW+n/d5tb39099OnL61iE8n1xi97GNVKhcNt26TVs0ZO/Jzdz0P8OdRxc4eGYbbTp+r1Knz+BuXPE+wRXvE/QZ9JPKtgpVyrLv1BZ5f6tRbj3Pc2u/hfqp/6+bmk2du4wrN27jOnUM+7f8Qq3qVeg/fCIhL8MAmL9iLRev3cR16jgObV9L905tmbPEjTMXrqbbZkJCAv1HTORZcAiLZ03iyI5fmT5+GBYFzAF48zacaXOXMca5H2uWzOLI8dOcvXRNuf+shSsZMbA3eQ0Ns7bzH2jXvgVz5k5kruty6tZuhaenD/sObsK8gFma9Q309Xn0KIjpU+fz4kVoqu2mZiasWOXK5Imu/NC6J527tKFZs0bK7YuX/sy0qfOJjHyXZX3KiNY/NGParHEsnudGswYd8b7nx7a9azAzN02zfs061Ti49yidWvWhddOfeP7sBdv3raWQpQUADmVLMtZlCIP7jsW531jGThpG6TIlANDS0mLu4mlMGDWTpCS5uEsdGrZqwOCpA9m4ZAv9mw/koXcAC7bOJb9Z/nT3eRcRRbvKHZWPzt90VW4r7lCM3mN6MnPwbH52nkPfcb0pVroYAFpamoxyHcFil2UkJan3W67c+v7+vu23uMwcycqF62jbuBu+XvdZv2sFpuYmadZ/+yaC1Ut+o3Pz3rRq0IW9Ow7junwqdRp+A0CpMvYMHz+QkQMmMsppEiNcBlHSwQ5IeX/PXDiRaWNc5f2tJrn1PM+t/RY5Q65OJmLj4jh17iKjnPtStVJ5bKytcO7bDRtrK+Xowx1PH9o0b0L1KhUobFmQjm2+p5R9cZXRiw/tO3KC8IhIls+dSpUKZSlsWZBqlStQukRxAJ4+f0HevIY0b1Kf8g6lqFalIgGPngBw9ORZtLW1+bZB7ax/AT4wZGhfNm34nW1b9uDn68+IYZOJiYmhe4+OadZ3d7/LlElz2bvnCHFx8am2F7MtQkREJPv2/oG7+13On7tKydIpf3Q7dGxFQkIChw8dz9I+ZUT/wT3ZvnkPu7Yf4IHfQyaMmkFMdCxdurVLs/7QAePZtH4nXvd8efggkDHDpqKpoUmdeikfNuxLFMPH6z6XLlzj4vlr+Hjdx75EyofLQcN6c/XyTTxu38u2/glVHQe0548dRzm26ziPHwSxeMJSYmPj+L5Ls/R3Uih4/fKN8vEm7K1yk42dDQE+gdy+fAf3S7d56BOAjV0RADoP7IzHtbv4eaT/+yK75Nb3d++BP7Fr6wH27TjMw/uBTB3jSmxMLB26tk6z/vXLtzh59CwPHzziyaNnbF67Ez9vfxxrVAKgeAlb/LwfcPXiTa5cuIGftz/FS9gC0G9Id25cccfzjnc29U58KLee57m131kqOTnnPnKYXJ1MJCUmkZSUjJ6ujkq5np4u7ne9AKhU3oEzF68S8jIMhULB9VsePAp6Rq3qVdJt9+zFq1Qs58DsRauo1/JH2nYbyNpNO5XfVNlYWxEbG4vPfX/CIyLx8r1PKftihEdEsmLdZiaOGpx1nU6Hjo4OlSqX48yZS8oyhULB2TOXqF69cqbafPjwEfr6eahQsQwmJsZUcayA1z1f8uc3YvKUkYwZNf3LBP8v6OjoUKFSGS6cvaIsUygUXDx3FcdqFTPUhr5BHrR1tHn7NhwAH+8HFLO3xcraksJFLCluXxRfH3+K2hahc9cfmD97eZb0RXyato42pcqX5NYFd2WZQqHg1gV3ylQpk+5++ob67Ly6jV3XtzNr/UxsSxZVbgvwDcS6eGEsrCwoWNiCIsWsCfR7hFVRS5p3/o718zdkaZ8yIve+v7UpW7E0l8/9M/KrUCi4fP46laqmPwXkfTXrVqOYXVFuXLkNwH1vf2ztbLAsXBAr60LY2tnwwOchRWwL0+7HViyd80uW9EV8Wu49z3Nnv0XOkasvwDY0NKBiOQdWb9xB8aI2mJnm5+ipc3jc88WmsCUAE0cOYvq85TRu2x1tLS00NDWYPn44VSulP6f+6fMXPHP3oEXThvyycCZBT58za9EqEpOSGNznJ4yN8jF78mgm/ryI2Lg4WjVrTO0ajkxxXULX9q14FvyCoeOnk5iYxOC+P9G0Yd0sfy3MzEzQ1tbmZWiYSnloaBglS9plqs23byMYOGAsa9YtQj+PHju37+evUxdY6TaXtWu2UNTWmp2716Kjo43r7OUcPPDnl+jKZzE1y4+2tjZhL1+plL98+Qq7v0cTPmXS9NGEvAhVJiT+9wOY9/NSdu5bB8DcmUvxvx/Azv2/MmvaIho0qsOoCYNJTEhkqosr1y7f+rKdEukyNjVGS1uL1y/fqJS/CXuDjX2RNPcJeviEeaMXEuATgKGRIZ2dOrLywHJ6N+7Ly+AwgvyD+HXubyzcMQ+AdXPXE+QfxKId81kzey3VG1Sl18geJCYmsWLaKu5e88zyfn4ot76/TUz///5+rVIeFvqa4va26e6XN58hFzz/RFdXl+SkJKaPn6dMSB4+eMTi2W5s2OMGwKJZq3j44BEb96xiwYzl1GlUk6FjB5CYmMisSQu5+XcSIrJebj3Pc2u/Rc6Rq5MJANcpY5jquoRGbbuhpaWJQ0l7mjepj7efPwDb9hzirpcvK+dNw7JQQW7d8WT2IjcszM2oWS3tjD9ZocDUJD/Txw1DS0uLsqVLEBr2ig3b9zC4T8rFek3q16ZJ/X+mMt24fZf7/oFMHDmI7zv1Zf6M8ZibmvJj/+E4ViqPmUn+LH8tssKRwyc4cviE8nntOtUpV640Y0dP547nGfr0Gk5IyEvOnDvApUvXU32oz+mcR/SjdbvmdGzVS2WoeMuGXWzZsEv5vGOXNrx7F8WtGx6cv3GEFo06Y2lVCLdfF1KzUlPi4xPUEb7IAG93H7zdfZTP7930YvPZ32j1U0t+W7gRgENbj3Bo6xFlne86fEt0VDRet7zZcm4jTi2dKWBpztRVk/ixVncSvpKf99f6/o56F02bhl0xNDSgZt1quMwcyZNHz7j+d+K/c9Nedm7aq6z/Q+cWRL2L5vZNT45f2Uv7pj0oZGnBkrVzaOTY+qv5eedWX+t5/im5td//p5DVnDIs1ycTNtZWbFy1gOiYWKKioilgbsroKa5YWxUiNi6OZWs2scx1CvVrVQeglH0xfB8EsHHH3nSTiQJ/f0vw/moexYsWIezVGxISEtDRUZ1WFR8fz6yFq3CdOpagp8EkJSVRrXLKEHzRIoXx9PKlQZ1vsugVSPHq1RsSExMpYGGuUm5hYU5IyMsvcgxdXV0WL5nJgP6jKW5ni7a2Fpcupqxw9dA/kKpVK3Lsz9Nf5FgZ9frVWxITE1NdpFaggFmqb3k+5DSkF84j+tKlbT98vO6nW8/END8jxw+ifYueVK5agQD/xwQGBBEYEISOjjbF7W3x9X7wRfojPi78dThJiUmYFlC9+NbE3ITXoW/S2UtVUmISD+75U9jWKs3txiZG9BzZg+EdRuJQ2YEngU95FviMZ4HP0NbRxrq4NYG+gf+6L58jt76/37z+//tbdTEFcwtTXoam/8FHoVAQFPgUAJ9797ErWQynEb2UycT7TEyNGTKmP11bD6BilXI8ehjE44AnPA54go62NsXsbLjv8/DLdkykKbee57m13yLnyNXXTLzPQD8PBcxNCY+I5PL1WzSq+w2JiYkkJiaiqaGhUldLS5Pkj1wAU6l8WYKePlep8+jJMwqYmaZKJADWbNxJnW+qUqaUPcnJSSS+twpIYmISSdlwsU1CQgJ3bt+jQYNayjINDQ3qN6jF9etfZph+3HhnTp06j8cdL7S0NNHW+ieX1dbRVstSigkJCdy9402d+v8kaxoaGtSpV4NbNzzS3W/QsD6MGDuQbh2cuHvH66PHmDFnPOvcNhP8PAQtTU10dP7pt5a2FlqasoRkdklMSMTP8z5V6vxzzZOGhgaOdSrj7Z6xi2Y1NTUpXroYr0Jfp7ndefogdv+6l5fBYWhqaaKt/d7PW0sLLc3s/7Wbe9/fiXh5+FKzXnVlmYaGBjXrVuPOzbsZbkdDUxNdXd00t038eTQb1+wgJDg0pd8fvr9lidhsk3vP89zZb5Fz5PqRiUvXbqFQKLC1sSbo6XMWrVpPMRtr2rZoio62NlUrl2fRqvXo6elhVciCm7c9OfTnX4wd1l/ZhsvPC7EwN2PkoJR1mjv/0IIdew8xd+lqunZozeOnz1m3+Xd+6ph69ZCHgY85dvo8uzesBKBY0SJoamqy9/BxzM1MCAx6QjmHktnyWqxcsZ7Vaxdy+7YnN296MNi5NwYGBmzdsgeANesW8vx5CDOmLQBSLvoq7WAPgK6uDpZWBSlfwYGod9EEBDxWabtUaXvatW9JnVotAbjv95Dk5GS69+hEaMhLSpa0w/1Wxv+4f0nr3DaxxG0Od297cdvdk/6DuqNvqM/v2/YDsOyXOQQHhzJ35lIABg/vyxiXIQzpP44nQc+V3wZFRUUTHRWt0nbdBjUpZmfL8EETAfC4fQ+7EsVo2KQOVoUtSU5K5qF/9n5LndvtXrsXlyXj8PPww+eOHx36tSOPfh7+/P0YAC5LxxP2Iox1c9cD0GNEN7zdfXj26Dl5jQzpMrATBa0L8seOo6nadqxbBevi1riOmA+An4cfNvZFqN6wGhZWFiQnJxMU8CT7Ovue3Pr+3rB6G/NWTOfeHW/uunvR06kr+gb67N1xGID5K2cQ8iKURbNWAeA0vBeed3x48ugpuro61G9SmzYdv2f6ONdUbdeqXwNbOxvGDZkGwN3b3hS3L0q9xrWwtCpIclIyAf6PU+0nsk5uPc9za7+zVA5cNSmnyvXJROS7KJau3kDIyzCMjfLxbf06DHPqic7f3yYunDGBpas3MmHGfMIjIrEqZMEwp550bttC2UZwSKjK6IVlwQKsWTKb+cvW0K7nYCzMzejWsQ19u6ku0aZQKJg+fzljh/bHQD8PAHn09Jg1aRSzF7kRn5DAxJGDKVhAdegyq+zb+wfm5qZMnDySggXN8bzrQ/u2vZTTfaytrVRGWywtLbh05Z8b+A0fMYDhIwZw4fxVWjTvqtL28hVzmDhhNtHRMQDExsYxyGkcC5fMQE9PlzGjphEcHJINvUzt0P5jmJqbMmbiEApYmOPl6Uu3Dk7K+Z9W1pYkJyuU9Xv06Yyeni7rNi9VaWfR3FUsnuemfJ4njx6z509iUJ8xKBQp+wc/D2HK+DksXjmb+Ph4RgyeSGxsXNZ3UiidOXyW/GbG9B7TC9MCJvh7P2Rcdxflcq8FC1ugeO88z2ecjzHzR2FawIR34e/w83yAc5vhPH4QpNKubh5dhs8aysxBs5Q/75fBYSyfspIJi8YSH5+A64j5xMemXoYxO+TW9/fRAycxNTNh2PiBFLAww+feffp2Hsqrvy/KtrQuRPJ7c6P1DfSZPn88hSwtiI2NI+DBI8YOnsLRAydV2tXLo8fUueMY2d9F+fMOCQ7l54kLcF0+lfi4BMYPnUacvL+zVW49z3Nrv0XOoKH4/2/Br0hCWIC6Q1ALs6JN1B2CWuTT1Vd3CGoREvVW3SGoRR0LB3WHoBbub3Ln77VCBmnfPPJrFxAerO4Q1MJAR0/dIYhsFBGVc3+vxT24rO4Q0qVXotanK2UjtY5MhIWF8dtvv3HlyhVevHgBQKFChahVqxa9evWiQIEC6gxPCCGEEELkRrKaU4ap7QLsGzduULJkSZYvX46xsTH16tWjXr16GBsbs3z5ckqXLs3Nmzc/2U5cXBwREREqj7g4GVYWQgghhBAiq6ltZGLo0KF07NiR1atXo/HBakkKhYKBAwcydOhQrly5kk4LKVxdXZkxY4ZK2eSxw5g6bvgXj1kIIYQQQgjxD7VdM6Gvr8/t27cpXbp0mtt9fX2pXLkyMTExH20nLi4u1UiEZuQz9PRy37xLuWYid5FrJnIXuWYid5FrJkRukKOvmfA9p+4Q0qVXur66Q1ChtpGJQoUKcf369XSTievXr1OwYMFPtqOnp5cqcUiI//jNxoQQQgghhBD/ntqumRgzZgwDBgxg+PDhHDp0iGvXrnHt2jUOHTrE8OHDGThwIOPGjfsix4qKimbu0tV8264njg3b8JPTKDx9/FTqPHwUxJBx0/mmaXuqNW5L577DCH4RqlLnzj0f+gydQLXGbanxbTt6Dh5L7AejIrFxcVRr3Jagp88B2LH3MK26DsCxYRtadunHwT9PpYpvy+/7admlH44N29D4h+7MW7aGuDjV5SN37D1M0/Y9qdKwNT/2H4Gnt1+qdrJbrdrV+H33Ovz8rxARFUCLlt+qO6RsMWRkP/7463f8gq7jcf8867cux87eVt1hiSzSa1QPzj49pfLYfPY3dYeV5XLr+/vHXu05dHYH7gFncQ84y+9Hf6Ne45y1cor4cnLreZ5b+y2yhtpGJpydnTE3N2fJkiW4ubmR9Pddn7W0tHB0dGTjxo106tTpixxr6txl+Ac8wnXqGCzMzTh8/DT9h0/k4LY1FCxgTtDT5/QYNIZ2Lb/DuV83DA0MeBgYhK7eP3c8vXPPh4GjJtOve2cmjhyElpYWfv4Bqe6OfeX6bSwLWWBjbcXO/UdYunoD08cPp5xDSTx9/Jg+dznG+fLSoE7KHZf/OHGGJas38LPLSCqVL8OjoKdMnr0YDQ0Nxg0bAMCfp84xf8Vapo4dSoUypdiy6wBOoyZzeMc6zEzyf5HXKDMMDQ245+nDls272b5ztdriyG7f1KrGpl93cOe2J9ra2kyYMpzt+9bR4JvWxER/fFqe+G8K9A1k9I//fLmRlJj0kdpfh9z6/n7xPJRFs1byKCAIDTT4oUtL3DYvom2jn/D3y7lTMkTm5NbzPLf2+7PIak4ZptalYTt37kznzp1JSEggLCxlapK5uTk6Ojpf7BixcXGcOneR5XOnUbVSeQCc+3bj3KVr/L7/D4YN6MnytZuoW7Mao537KvezsbZSaWf+sjX81KEN/br/k+AUK2qd6ninL16h4d+JwuFjp+nY5nuaN0mZ21aksCVePg9Yv223Mpm44+lD5fJlaNG0IQCFLQvy/bcNuOvtq2xz8+/76dCqOT+0aArA1LFDOX/5BvuPnFCJJ7udPHGOkydy7pzCrNKto5PK8xGDJ+Hpf5EKlcpw7fItNUUlslJSUhKvX75RdxjZKre+v8+cuKDyfMkcN37s1Z5KVctLMvEVyq3neW7tt8gaapvm9D4dHR0sLS2xtLT8ookEpHyDmJSUjJ6uart6erq43/UiOTmZ85dvYFukMANGTqJeiy782H8Ef53/52Ylr9685a63H6YmxvzkNIp6LX+kl/NY3D3uqbSZnJzMuUvXaVi3JgAJCQno6eqmOq6n930SEhMBqFTeAW8/f+W0pSfPgjl/5QZ1v6mmbMPb7wHfVKukbENTU5NvqlbC457Pl3mRxL9iZJQPgLdvwtUcicgqhYsVZs/NnWy/tIVJK1ywsLJQd0giG2hqatKibVMMDPS5feOuusMRQogcSa0jE9nB0NCAiuUcWL1xB8WL2mBmmp+jp87hcc8Xm8KWvH7zluiYGNZv3cXQ/j0ZNagPF6/dYsTEWfy2Yi7VKlfg6bOUVTXcftvGmCH9KF2iOIf+/Iu+w104sGU1RYsUBsDDK2U0oUKZUgDUqu7I3iPHaFSvJmVK2ePl+4C9h4+TmJjI27cRFDA3pUXThrwJj6D7oDGgUJCYlESntt8zoGcXAN68jSApKRkzUxOVfpmZmhAY9DS7XkaRDg0NDWa4juf6VXf8fPzVHY7IAt63fZg7cgFPAp5gZmFGz5HdWb5vCb0b9yMmSqa1fY1KOtjx+58b0NPTJToqBudeY3l4P1DdYQkhslOyTHPKqK8+mQBwnTKGqa5LaNS2G1pamjiUtKd5k/p4+/mTnJyyMm7DujXp0eUHAEqXtOOOpze7DhylWuUKJP+9em7HNt8rpxo5lLTn6q077DtygpGDegNw5sIV6teujqZmyoDPwN4/Evb6NT8NGIkCBWYmJrRp3pjftu1BQzPlWovr7ndZt/l3Jo92pkLZUgQ9fc7cZWtYvWE7A3t3zdbXSXy+OQsnU8qhBD80767uUEQWuX7mhvL/AT6B+Nz2YefV7TRsVZ+jO4+pMTKRVQL9H9OmYVfy5ctLs9aNmbdiOj+1GSAJhRBCpCFXJBM21lZsXLWA6JhYoqKiKWBuyugprlhbFcIkvxHaWlrY2dqo7FPctgjud70BKGCWss65XbEP6hS14UXIPys+nbl4TZlYAOTR02PWxFFMGzeMV6/fUMDMlN2H/sTQQB/T/MYArFy3mVbfNaJD62YAlLQrRkxsHDPmLWdAzy6Y5DdCS0uTV69V52u/ev0G8w9GK0T2mjV/Ek2+q0+773sS/DxE3eGIbPIuIoqnAU8pbFtY3aGILJKQkEhQYMrIr9ddX8pXKkPPAT8ydcwcNUcmhBA5T464ZiK7GOjnoYC5KeERkVy+fotGdb9BR0eHsg4lU00ZevTkGVaFUuZFF7YsiIW5GY8eq9Z5/OQploUK/v3/ZwS/CKVmtcqpjqujrU0hiwJoaWlx7NQ56teuoRy9iI2LQ1NTdUUorb+3KRQKdHR0KFOqBNdu3lFuT05O5tqtO1Qslztv3pUTzJo/iWYtGtOpdR+eBD1TdzgiG+kb5MHK1pJXoa/UHYrIJhqamujqfdnr+YQQOZwiOec+cphcMTJx6dotFAoFtjbWBD19zqJV6ylmY03bv6cs9e7anjFT51K1UjmqV6nIxas3OXfpGhtWzANS5sX37tqeVeu3UqpEMUqXsOPg0VMEPn7K4lmTADh94QrfVK2Efp48yuM+CnqKp899KpQpRUTkOzbt3MeDgMfMnjxGWad+7Rps3rmP0iXtqFCmNEFPn7Ni3Wbq166BlpYWAD06/8Ck2YsoW7oE5cqUYuuuA8TExtG2hXrXhTY0NKC4XVHlc1vbIpSv4MCb1+E8/fs+G1+jOQun0LbD9/TpOpR376IpYGEOQGREJLGxcZ/YW/zXDJo8gMunrhLyNASzgmb0Ht2T5KRk/jpwRt2hZanc+v4ePdmZc39dJvjpCwzzGtCqfTNq1HakT6eh6g5NZIHcep7n1n6LrKGhUPx9QcBXJCFMdfm+Y3+dZ+nqDYS8DMPYKB/f1q/DMKee5MtrqKyz78hxft2yi5DQMGxtrHHu141Gf6/K9H+/btnFjn2HiYiIpKR9cUYP7kOViuUA6DFoDK2bN1FOV4KUG+GNnz6PR0HP0NbWonqViowc1EdlSdnExCTWbt7J4WN/EfryFSYmxjSoXYNhA3pilC+vst72PYfYsH0vYa9fU7qEHS4jBlKhrOrdw82KNvn3L95nqFO3BkeP7UhVvm3rHgY5fZkbDmZEPl39bDsWwLM3XmmWjxw8iV07DmRbHCFRb7PtWDlJHYvsHZGbumoSFWqUx8jEiPDX4Xhev8ev83/j+ePgbI3D/U32LkuaU97fhQxMs+1YALOXTqFm3WpYFDQnMuIdft4PWLtiM5fPXcvWOALCs/f8yikMdPSy9Xg55TzPbjml3xFROXe55bh7J9UdQrr0yuWsmwzmimQiq715G07D1j9x6sAWtV7HkN3JRE6R3clETiHJRO6S3clETpHdyUROIcmEyA1ydDJx97i6Q0iXXoXv1B2Cilx1zURWCY+IZOzQ/nJBtBBCCCGEyFVyxTUTWc3Wxhpbm9R3wxZCCCGEEOJrJsmEEEIIIYQQ71EoktQdwn+GTHMSQgghhBBCZIokE0IIIYQQQohMkWlOQgghhBBCvC8H3hwup5KRCSGEEEIIIUSmSDIhhBBCCCGEyBSZ5iSEEEIIIcT7kmWaU0bJyIQQQgghhBAiUySZEEIIIYQQQmSKTHMSQgghhBDifbKaU4bJyIQQQgghhBAiUySZEEIIIYQQQmSKTHMSQgghhBDifclJ6o7gP0NGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvS5ZpThklIxNCCCGEEEKITJFkQgghhBBCCJEpMs1JCCGEEEKI98lqThkmIxNCCCGEEEKITPkqRyb0reqqOwS1iHl+Qd0hqEVZh07qDkEtChqqOwL1uBjqo+4Q1MJAR0/dIajFi+jX6g5BZKMqJsXVHYJauL8JUHcIQmTaV5lMCCGEEEIIkWmymlOGyTQnIYQQQgghRKZIMiGEEEIIIYTIFJnmJIQQQgghxPtkmlOGyciEEEIIIYQQIlMkmRBCCCGEEEJkikxzEkIIIYQQ4j0KRZK6Q/jPkJEJIYQQQgghRKZIMiGEEEIIIYTIFJnmJIQQQgghxPtkNacMk5EJIYQQQgghRKZIMiGEEEIIIYTIFJnmJIQQQgghxPsUMs0po2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+Wc0pw2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+Wc0pw2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+Wc0pw2RkQgghhBBCCJEpkkwIIYQQQgghMkWSiVwqKiqauUtX8227njg2bMNPTqPw9PFTbo+OjmH2Ijcat+2GY8M2tP5pAL/v/+OjbSYkJvLLb9to1rE3VRq2pl3PwVy8elOlzpHjp2n8Q3dqNevI/OVrVbY9Cw6hRZd+vIuK+nIdzaCf+nTk9K1DeD65xO5jG6lQuWy6dZu2aMjek5u56X+GO48ucPDMNtp0/F6lTp/B3bjifYIr3ifoM+gnlW0VqpRl36ktaGlpZUlfPkfPfj9y1eMED4PdOXxyB5WqlE+3btceHdh3dDNegZfxCrzMzv2/pqrvNKQXHvfP43H/PE7OPVW2VXYsz59nduWIfudW/Qd0x9P7PKGvfDh9dh+OjhXSrVvaoQRbtrnh6X2eiKgABjv3TlWnU+c2ePtd5PHT28yZO0llm41NYdzv/EW+fHm/eD8+V27td27Vtmdrdl7Zygn/o7gdXkHpSqUytF+j1g04+/QUs36doVLe2akj++/sZv+d3XQa0EFlm0Pl0qw56oaWlvo/Tsl5/oUpknPuI4dR/9kv1GLq3GVcuXEb16lj2L/lF2pVr0L/4RMJeRkGwPwVa7l47SauU8dxaPtaundqy5wlbpy5cDXdNles3cTug38yceQgDm5dQ6e23zPc5Wd87vsD8OZtONPmLmOMcz/WLJnFkeOnOXvpmnL/WQtXMmJgb/IaGmZt5z/wfdtvcZk5kpUL19G2cTd8ve6zftcKTM1N0qz/9k0Eq5f8RufmvWnVoAt7dxzGdflU6jT8BoBSZewZPn4gIwdMZJTTJEa4DKKkgx0AWlpazFw4kWljXElKSsq2Pqal9Q/NmDZrHIvnudGsQUe87/mxbe8azMxN06xfs041Du49SqdWfWjd9CeeP3vB9n1rKWRpAYBD2ZKMdRnC4L5jce43lrGThlG6TAkgpd9zF09jwqiZau93btWufQvmzJ3IXNfl1K3dCk9PH/Yd3IR5AbM06xvo6/PoURDTp87nxYvQVNtNzUxYscqVyRNd+aF1Tzp3aUOzZo2U2xcv/ZlpU+cTGfkuy/qUEbm137lVw1YNGDx1IBuXbKF/84E89A5gwda55DfL/9H9ClkXZNAUJzyu3lUpL+5QjN5jejJz8Gx+dp5D33G9KVa6GABaWpqMch3BYpdlJCWp9wOenOdCnSSZyIVi4+I4de4io5z7UrVSeWysrXDu2w0bayvl6MMdTx/aNG9C9SoVKGxZkI5tvqeUfXGV0YsPHT52mv49OlOvVnWKFLakyw8tqVuzGht37APg6fMX5M1rSPMm9SnvUIpqVSoS8OgJAEdPnkVbW5tvG9TO+hfgA70H/sSurQfYt+MwD+8HMnWMK7ExsXTo2jrN+tcv3+Lk0bM8fPCIJ4+esXntTvy8/XGsUQmA4iVs8fN+wNWLN7ly4QZ+3v4UL2ELQL8h3blxxR3PO97Z1Lv09R/ck+2b97Br+wEe+D1kwqgZxETH0qVbuzTrDx0wnk3rd+J1z5eHDwIZM2wqmhqa1KmXkkTZlyiGj9d9Ll24xsXz1/Dxuo99iZQ/uoOG9ebq5Zt43L6Xbf0TqoYM7cumDb+zbcse/Hz9GTFsMjExMXTv0THN+u7ud5kyaS579xwhLi4+1fZitkWIiIhk394/cHe/y/lzVylZOiVp7tCxFQkJCRw+dDxL+5QRubXfuVXHAe35Y8dRju06zuMHQSyesJTY2Di+79Is3X00NTWZtMKFDYs2ERwUrLLNxs6GAJ9Abl++g/ul2zz0CcDGrggAnQd2xuPaXfw80v+7mF3kPBfqJMlELpSUmERSUjJ6ujoq5Xp6urjf9QKgUnkHzly8SsjLMBQKBddvefAo6Bm1qldJt934hAR0dXVTtXn77zZtrK2IjY3F574/4RGRePnep5R9McIjIlmxbjMTRw3+wj39NB0dbcpWLM3lc/+MkCgUCi6fv06lqukPEb+vZt1qFLMryo0rtwG47+2PrZ0NloULYmVdCFs7Gx74PKSIbWHa/diKpXN+yZK+fA4dHR0qVCrDhbNXlGUKhYKL567iWK1ihtrQN8iDto42b9+GA+Dj/YBi9rZYWVtSuIglxe2L4uvjT1HbInTu+gPzZy/Pkr6IT9PR0aFS5XKcOXNJWaZQKDh75hLVq1fOVJsPHz5CXz8PFSqWwcTEmCqOFfC650v+/EZMnjKSMaOmf5ng/4Xc2u/cSltHm1LlS3LrgruyTKFQcOuCO2WqlEl3vx4ju/H21VuO7jyWaluAbyDWxQtjYWVBwcIWFClmTaDfI6yKWtK883esn78hS/ryOeQ8zyLJyTn3kcPI0rC5kKGhARXLObB64w6KF7XBzDQ/R0+dw+OeLzaFLQGYOHIQ0+ctp3Hb7mhraaGhqcH08cOpWin9OfW1aziyeec+qlYqR5HClly9eYe/zl0mKTllWouxUT5mTx7NxJ8XERsXR6tmjaldw5Eprkvo2r4Vz4JfMHT8dBITkxjc9yeaNqyb5a+FiWl+tLW1CXv5WqU8LPQ1xe1t090vbz5DLnj+ia6uLslJSUwfP0+ZkDx88IjFs93YsMcNgEWzVvHwwSM27lnFghnLqdOoJkPHDiAxMZFZkxZy8+8kJDuZmv2/369Uyl++fIXd36MJnzJp+mhCXoQqExL/+wHM+3kpO/etA2DuzKX43w9g5/5fmTVtEQ0a1WHUhMEkJiQy1cWVa5dvfdlOiXSZmZmgra3Ny9AwlfLQ0DBKlrTLVJtv30YwcMBY1qxbhH4ePXZu389fpy6w0m0ua9dsoaitNTt3r0VHRxvX2cs5eODPL9GVz5Jb+51bGZsao6WtxeuXb1TK34S9wca+SJr7lK9WjhZdmtOvqVOa24P8g/h17m8s3DEPgHVz1xPkH8SiHfNZM3st1RtUpdfIHiQmJrFi2iruXvP8sp3KADnPhbpJMpFLuU4Zw1TXJTRq2w0tLU0cStrTvEl9vP1Srm/YtucQd718WTlvGpaFCnLrjiezF7lhYW5GzWppf9MxYbgT0+ctp1XXAWhoQBErS9q2+Jb9R04o6zSpX5sm9f+ZynTj9l3u+wcyceQgvu/Ul/kzxmNuasqP/YfjWKk8Zib5s/R1yKyod9G0adgVQ0MDatathsvMkTx59Izrf39A3rlpLzs37VXW/6FzC6LeRXP7pifHr+ylfdMeFLK0YMnaOTRybE1CfIK6upIpziP60bpdczq26qUyRL5lwy62bNilfN6xSxvevYvi1g0Pzt84QotGnbG0KoTbrwupWakp8f+xfgtVRw6f4Mjhf97ftetUp1y50owdPZ07nmfo02s4ISEvOXPuAJcuXU+VvP5X5dZ+f230DfWZuGw8C8YtJvxNRLr1Dm09wqGtR5TPv+vwLdFR0Xjd8mbLuY04tXSmgKU5U1dN4sda3f9zv8/TI+e5yChJJnIpG2srNq5aQHRMLFFR0RQwN2X0FFesrQoRGxfHsjWbWOY6hfq1qgNQyr4Yvg8C2Lhjb7rJhKlJfpbPnUpcXDxvIyKwMDdjyS+/YW1VKM368fHxzFq4CtepYwl6GkxSUhLVKqdMLSpapDCeXr40qPNN1rwAf3vz+i2JiYmYF1C96NjcwpSXoen/YlQoFAQFPgXA59597EoWw2lEL2Uy8T4TU2OGjOlP19YDqFilHI8eBvE44AmPA56go61NMTsb7vs8/LId+4TXr/7fb9WL8woUMEv17daHnIb0wnlEX7q07YeP1/1065mY5mfk+EG0b9GTylUrEOD/mMCAIAIDgtDR0aa4vS2+3g++SH/Ex7169YbExEQKWJirlFtYmBMS8vKLHENXV5fFS2YyoP9oitvZoq2txaWL1wF46B9I1aoVOfbn6S9yrIzKrf3OrcJfh5OUmIRpAdXFM0zMTXgd+iZV/cJFrbC0scR1wyxlmYamBgB/PTpO9/q9eP5Y9RoKYxMjeo7swfAOI3Go7MCTwKc8C3zGs8BnaOtoY13cmkDfwCzoXfrkPM8iOXA6UU4l10zkcgb6eShgbkp4RCSXr9+iUd1vSExMJDExEU0NDZW6WlqaJGfgzaWnp0vBAuYkJiVx8uwlGtatmWa9NRt3UuebqpQpZU9ychKJ763yk5iYRFI2vJETEhLx8vClZr3qyjINDQ1q1q3GnZt3P7KnKg1NzVTXi/zfxJ9Hs3HNDkKCQ9HS0kRb558cXktbSy1LpSYkJHD3jjd16v+TrGloaFCnXg1u3fBId79Bw/owYuxAunVw4u4dr48eY8ac8axz20zw8xC0NDXR+bDfmrJEbHZJSEjgzu17NGhQS1mmoaFB/Qa1uH79y0yzGzfemVOnzuNxxyvlPNf65+etraOttvM8N/Y7t0pMSMTP8z5V6vxzbZ+GhgaOdSrj7Z560Yugh0H0btyPft85KR+XT1zh9uU79PvOidDnqT+IO08fxO5f9/IyOAxNLU20td/7vaalhZZm9n+skvNcqJuMTORSl67dQqFQYGtjTdDT5yxatZ5iNta0bdEUHW1tqlYuz6JV69HT08OqkAU3b3ty6M+/GDusv7INl58XYmFuxshBKetT3/XyJeTlK0qXKE7oy1e4/bYVhUJBn586pDr+w8DHHDt9nt0bVgJQrGgRNDU12Xv4OOZmJgQGPaGcQ8lseS02rN7GvBXTuXfHm7vuXvR06oq+gT57dxwGYP7KGYS8CGXRrFUAOA3vhecdH548eoqurg71m9SmTcfvmT7ONVXbterXwNbOhnFDpgFw97Y3xe2LUq9xLSytCpKclEyA/+Ns6eeH1rltYonbHO7e9uK2uyf9B3VH31Cf37ftB2DZL3MIDg5l7sylAAwe3pcxLkMY0n8cT4KeK78Fi4qKJjoqWqXtug1qUszOluGDJgLgcfsediWK0bBJHawKW5KclMxD/+z99i63W7liPavXLuT2bU9u3vRgsHNvDAwM2LplDwBr1i3k+fMQZkxbAKRc1FnawR4AXV0dLK0KUr6CA1HvogkIUD1nS5W2p137ltSp1RKA+34PSU5OpnuPToSGvKRkSTvcb2U8Of+Scmu/c6vda/fismQcfh5++Nzxo0O/duTRz8Ofv6dcXO2ydDxhL8JYN3c98XEJBPo9Utn/XUTKUqcflgM41q2CdXFrXEfMB8DPww8b+yJUb1gNCysLkpOTCQp4kqX9S4+c50KdJJnIpSLfRbF09QZCXoZhbJSPb+vXYZhTT3T+/pZl4YwJLF29kQkz5hMeEYlVIQuGOfWkc9sWyjaCQ0JVRi/i4uNZsW4TT5+/wEBfn7o1q+E6ZSxGH9zURqFQMH3+csYO7Y+Bfh4A8ujpMWvSKGYvciM+IYGJIwdTsIDqkG1WOXrgJKZmJgwbP5ACFmb43LtP385DefX3RdmW1oVIfu8mMfoG+kyfP55ClhbExsYR8OARYwdP4eiBkyrt6uXRY+rccYzs74JCoQAgJDiUnycuwHX5VOLjEhg/dBpxsXHZ0s8PHdp/DFNzU8ZMHEIBC3O8PH3p1sFJOe/VytqS5GSFsn6PPp3R09Nl3ealKu0smruKxfPclM/z5NFj9vxJDOozRtnv4OchTBk/h8UrZxMfH8+IwROJVVO/c6t9e//A3NyUiZNHUrCgOZ53fWjftpdyWpu1tZXKyKOlpQWXrvxzo8rhIwYwfMQALpy/SovmXVXaXr5iDhMnzCY6OgaA2Ng4BjmNY+GSGejp6TJm1DSCg0OyoZep5dZ+51ZnDp8lv5kxvcf0wrSACf7eDxnX3YU3YW8BKFjYAkUmRr118+gyfNZQZg6apfy99jI4jOVTVjJh0Vji4xNwHTGf+NjUy6xmBznPs0AOvDlcTqWh+P+74iuirVtY3SGoRczzC+oOQS3KOnRSdwhqEZUYo+4Q1CIk6q26Q1ALAx09dYcgslF0Qu5MtutYOKg7BLVwfxOg7hDUIiIq5/Y75shidYeQLv2Wo9Qdggq5ZkIIIYQQQgiRKTk6mXjy5Al9+vT5aJ24uDgiIiJUHl/hYIsQQgghhMgu6r4x3X/opnU5Opl4/fo1mzZt+mgdV1dXjI2NVR6K5MhsilAIIYQQQojcS60XYB86dOij2wMCPj2XzsXFhVGjVOeOmZiV/ldxCSGEEEIIIT5NrclE27Zt0dDQ+Oi0JI0P7nXwIT09PfT0VC9M/NQ+QgghhBBCpEtWc8owtU5zsrS0ZN++fSQnJ6f5cHd3V2d4OVqePJoUKpiHokUMsCuWFwMD1RvGnDx7if4jJlK7eSfK1W6O733VOyyHR0QyZ7EbLbv0w7FhG5q068GcJb8Q+S5KWcf3QQBjp82l8Q/dcWzYhlZdB7Bl14E04zl49CTdB43O0LEBdh88Sq8h46jxbTvK1W5OROS7VHWGjJtOk3Y9qNKwNQ1ad2XCzAWEvvznrtTPgkMoV7s5GqaRKg+0klK19SX92Ks9h87uwD3gLO4BZ/n96G/Ua1zr0zv+xw0Z2Y8//vodv6DreNw/z/qty7Gzt1V3WCKL1Kpdjd93r8PP/woRUQG0aPmtukPKFrm137lVr1E9OPv0lMpj89nf1B1WlpPzXHxJak0mHB0duXXrVrrbPzVqkZtpamgQH59M2Ku0lw+MiY2lSoWyjByU9gXsoWGvCA17zZgh/di/5RdmTxrFpWu3mOq6RFnH2+8Bpib5mTt1LAe2rmZAzy4sW72R7XtST087feEqDet8k6FjQ8o61XVqVKV/jy7p1qlepSKLZrpwZMc6lsyezJNnwYycPDtVPUWEPoo3hsoHSVl7Wr94HsqiWSv5oUl32jXpwdWLN3HbvAj7UsWz9Ljq9k2tamz6dQetmv7Ij+36o6OjzfZ969A30Fd3aCILGBoacM/Th9Ejp6k7lGyVW/udmwX6BtKuckflY+gPI9QdUpaT81x8SWqd5jR27FiioqLS3W5vb8+ZM2eyMaL/juiYJKJj0v8GvnWzxkDKt/dpKVHclqVzJiuf21hbMWxATybMnE9iYhLa2lq0a/mdyj5FClvicc+HU+cu07VDa2V5XFw8l2+4M3xgrwwdG6B75x8AuO6e/l0ze3T5Qfl/q0IF6detE8NcZpKQmKi8uR4ACg1QZF9efOaE6v08lsxx48de7alUtTz+fjl3zex/q1tHJ5XnIwZPwtP/IhUqleHa5fS/FBD/TSdPnOPkiXPqDiPb5dZ+52ZJSUm8fvlG3WFkKznPMyAHrpqUU6k1mahbt+5HtxsaGlK/fv1sikZEvosir6EB2tpaH61jbKR6R+urt+5Q0NyM4kWLZFls4RGRHDlxhkrlHVQTCYC8MaBByohErC4kZN9prampSfPWTTAw0Of2jfQTo6+RkVE+AN6+CVdzJEIIkXmFixVmz82dxMcl4OXuzTrX9YQ+D1V3WEL8Z6g1mRA5x5u34azZuIMOrZunW+e2pzfH/zrPqgUzVMrPXLhCg7+nOH1pi93Ws2PvYWJi46hYtrTKsQ308zB2aH/mz9qWUqCbmJJYvNPP8oSipIMdv/+5AT09XaKjYnDuNZaH9wOz9Jg5iYaGBjNcx3P9qjt+Pv7qDkcIITLF+7YPc0cu4EnAE8wszOg5sjvL9y2hd+N+xETFqDs8If4TcvR9JkT2eBcVxeCx07ArZsPgvt3SrPMg4BHDJsxgUJ+fqF3DUVmuUCg4e+ma8nqJL6131w7s3rCStUtmo6mlicvPC5XX0ZjkN6Znl3aQpJXyiNGDeG3IE58lsbwv0P8xbRp2peN3vdixcQ/zVkzHrmSxLD9uTjFn4WRKOZRgcN8x6g5FCCEy7fqZG5z74zwBPoHcOHeTCT0mktcoLw1byayIXE+RnHMfOYwkE7lcVFQ0TqOmYGigz7I5U1JPIQIeBj6m7zAXOrRujlOvH1W2eXr7kZSURKXyDlkSn0l+Y2xtrKlVvQoLZkzgwpUbeHj5pr9DohZoZf0bLSEhkaDAp3jd9WXRrFX4et2n54AfP73jV2DW/Ek0+a4+HVv1Jvh5+tfFCCHEf827iCieBjylsG1hdYcixL/m6upKtWrVyJcvHxYWFrRt2xY/Pz+VOg0aNEBDQ0PlMXDgwM86jiQTudi7qCgGjJyEjo42K+ZNQ09PN1Ud/4DH9B46gTbNmzDcqVeq7acvXKVezepoaaV/ncWXokhOGZGIj09Iv5JWMiRn/31GNDQ10dXTyfbjZrdZ8yfRrEVjOrXuw5OgZ+oORwghvih9gzxY2VryKvTVpysLkcOdO3cOZ2dnrl69ysmTJ0lISKBp06apFj/q378/wcHBysf8+fM/6zhyzcR/lIYG6Oj8kwvqaGvie/8hxkb5sCxkQXhEJMEvQgkNS/mFGBj0FABzMxPMzUxTEokRk4iJi2PZ1LFERUUTFRUNpIwGaGlp8SDgEX2HTqBWDUd6dvmBsFevgZSLjk1N8gNw9uJVnPt1V4ntU8cGCHv1mrBXbwh6+hyABw8fYWigj2UhC4yN8nHXy5d7PvepUqEsRkZ5efIsmBXrtlCksCWVyqXc4fzg0ZPo6OiA5t+rWukmgl4CROX5oq/1h0ZPdubcX5cJfvoCw7wGtGrfjBq1HenTaWiWHlfd5iycQtsO39On61DevYumgIU5AJERkcTGpr1EsfjvMjQ0oLhdUeVzW9silK/gwJvX4Tz9+337Ncqt/c6tBk0ewOVTVwl5GoJZQTN6j+5JclIyfx34uleSlPM8A76C1ZyOHTum8nzjxo1YWFhw69Yt6tWrpyw3MDCgUKFCmT6OhuIrvJGDtu7XPzyZJ48WhS1Tr+/fpnkTZk8ezYE/TjJ5zuJU2wf1+Qnnvt247n6XPkPHp9n28T0bKWxZkFXrt/LLb9tSbbcqZMGJvZsIevqctt0HcvHoLgz0//kA/6ljA+m2PWviKNq2+Jb7DwOZu3QNfv4BxMTGUsDMlNo1HHHq9SMFC6R8iD149CTrt+3mYeATUADJmhCjCwlZO0Iwe+kUatathkVBcyIj3uHn/YC1KzZz+dy1LD3uh6ISs/fiwGdvvNIsHzl4Ert2HMi2OEKi3mbbsXISAx29bD1enbo1OHpsR6rybVv3MMhpXLbGkp1ySr+jE3Jngl7HImumzKZn6qpJVKhRHiMTI8Jfh+N5/R6/zv+N54+DszUO9zfZu6x4TjnPI6Jy7nLqMXtmqTuEdGm2GktcnOrvCD09PfT0Pv53wt/fnxIlSuDp6Um5cuWAlGlOXl5eKBQKChUqRKtWrZgyZQoGBgYZjkeSia9IzPMLn670BW3auY+rN27zy6Kfs/W4Hyrr0Emtx1eX7E4mcgpJJkRuIMlE7pLdyUROIclE5sy7l8iMGaora06bNo3p06enu09ycjKtW7fm7du3XLx4UVm+du1aihYtipWVFXfv3mX8+PFUr16dffv2ZTgemeYkMq1gAXP6de+s7jCEEEIIIb6sHDzNycXFhVGjRqmUfWpUwtnZmXv37qkkEgADBgxQ/r98+fJYWlrSuHFjHj58iJ2dXYbikWRCZFqzxvU+XUkIIYQQQnwxGZnS9L4hQ4Zw5MgRzp8/j7W19Ufr1qhRA0iZEiXJhBBCCCGEELmUQqFg6NCh7N+/n7Nnz1Ks2Kfvh3Xnzh0ALC0tM3wcSSaEEEIIIYR431dwSbGzszPbt2/n4MGD5MuXjxcvXgBgbGyMvr4+Dx8+ZPv27Xz//feYmZlx9+5dRo4cSb169ahQoUKGjyPJhBBCCCGEEF+ZX375BUhZsel9GzZsoFevXujq6nLq1CmWLl1KVFQURYoUoX379kyePPmzjiPJhBBCCCGEEF+ZTy3YWqRIEc6dO/evjyPJhBBCCCGEEO/Lwas55TSan64ihBBCCCGEEKlJMiGEEEIIIYTIFJnmJIQQQgghxPtkmlOGyciEEEIIIYQQIlMkmRBCCCGEEEJkikxzEkIIIYQQ4n0KmeaUUTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifrOaUYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifQqHuCP4zZGRCCCGEEEIIkSmSTAghhBBCCCEyRaY5CSGEEEII8T5ZzSnDZGRCCCGEEEIIkSmSTAghhBBCCCEyRaY5CSGEEEII8T6Z5pRhX2UyUcfCQd0hqIW+VV11h6AWMc8vqDsEtbAt0UrdIahFcWNLdYegFgHhweoOQS0MdPTUHYJadLKsru4QRDZyV3cAQvwLMs1JCCGEEEIIkSlf5ciEEEIIIYQQmaaQaU4ZJSMTQgghhBBCiEyRZEIIIYQQQgiRKTLNSQghhBBCiPcokhXqDuE/Q0YmhBBCCCGEEJkiyYQQQgghhBAiU2SakxBCCCGEEO+Tm9ZlmIxMCCGEEEIIITJFkgkhhBBCCCFEpsg0JyGEEEIIId4nN63LMBmZEEIIIYQQQmSKJBNCCCGEEEKITJFpTkIIIYQQQrxPblqXYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHif3LQuw2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+meaUYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifQm5al1EyMiGEEEIIIYTIFEkm0tG2Z2t2XtnKCf+juB1eQelKpdKt26xjU84+PaXyOOF/VKVOZ6eO7L+zm/13dtNpQAeVbQ6VS7PmqBtaWvLjyGpRUdHMXbqab9v1xLFhG35yGoWnj59ye7nazdN8/LZtT7ptrlq/NVX9Vj/2V6kzf/laajXrSOMfunPk+GmVbcdPX8B53LQv29EM6tnvR656nOBhsDuHT+6gUpXy6dbt2qMD+45uxivwMl6Bl9m5/9dU9Z2G9MLj/nk87p/HybmnyrbKjuX588wutLS0sqQvn+OnPh05fesQnk8usfvYRipULptu3aYtGrL35GZu+p/hzqMLHDyzjTYdv1ep02dwN654n+CK9wn6DPpJZVuFKmXZd2pLjuh3btV/QHc8vc8T+sqH02f34ehYId26pR1KsGWbG57e54mICmCwc+9UdTp1boO330UeP73NnLmTVLbZ2BTG/c5f5MuX94v343N926M5yy6uYaPf78w8MA+7iiXSrTt5589sf7w/1WPshn/612JAG365tZFfbm3k+/6tVfa3q1SC2UcWopkD/o7l1n7n1vNcqJ9Mc0pDw1YNGDx1IItdluFz24cO/dqzYOtcutfvzdtXb9Pc511EFD3q91I+V7w3PFbcoRi9x/TEpedkNDQ0cN00ixvnbxHoG4iWliajXEewcPwSkpJk5YCsNnXuMvwDHuE6dQwW5mYcPn6a/sMncnDbGgoWMOfsoW0q9S9cvclU16V826D2R9u1L1aUX5fNUT5//4Pj2YtX+ePkWdYumU3Q0+dMmbOE2jUcMclvTOS7KJav3cSvS+ek1WyWav1DM6bNGseEUTO4fcuTfgO7s23vGupVa8mrsNep6tesU42De49y89odYuPicB7el+371tKoZhteBIfiULYkY12G0LOLMxoasHGnG+fOXMbX+wFaWlrMXTyNcSOmk5SUlO19fd/3bb/FZeZIpo51xePWPXo5/cj6XSv4rmZ7Xoe9SVX/7ZsIVi/5jYAHj4hPSKBh07q4Lp/Kq7DXXDxzlVJl7Bk+fiBOP41AQ0ODNduWcPHsVe77PERLS4uZCycyZdRstfc7t2rXvgVz5k5kxPAp3Lxxh8HOvdl3cBOOlZsQ9vJVqvoG+vo8ehTEgf1HcZ03OdV2UzMTVqxyZZDTWB4FPmH3vl85f/YKx46lfEmweOnPTJs6n8jId1net4/5pmVtuk3uzW+TVuN/5z7N+7RiwpapjG44hIhX4anqL3Gah7buPx8J8ubPx9xjS7j2x2UAipQuSodRP7Kgz2w0NGDsb5PwPH+HJ35BaGpp0nfOQH6d8AvJav47llv7nVvP8ywlqzllmPpT6Ryo44D2/LHjKMd2HefxgyAWT1hKbGwc33dplv5OCgWvX75RPt6EvVVusrGzIcAnkNuX7+B+6TYPfQKwsSsCQOeBnfG4dhc/D790GhZfSmxcHKfOXWSUc1+qViqPjbUVzn27YWNtxe/7/wDA3MxU5XHmwlWqV6lAkcKWH21bS0tLZT+T/MbKbQGPn1CtcnnKOZTk+28bYGhowNPgFwAsdltP57YtsCxkkXUdT0f/wT3ZvnkPu7Yf4IHfQyaMmkFMdCxdurVLs/7QAePZtH4nXvd8efggkDHDpqKpoUmdet8AYF+iGD5e97l04RoXz1/Dx+s+9iWKATBoWG+uXr6Jx+172da/9PQe+BO7th5g347DPLwfyNQxrsTGxNKha+s061+/fIuTR8/y8MEjnjx6xua1O/Hz9sexRiUAipewxc/7AVcv3uTKhRv4eftTvIQtAP2GdOfGFXc873hnU+/Eh4YM7cumDb+zbcse/Hz9GTFsMjExMXTv0THN+u7ud5kyaS579xwhLi4+1fZitkWIiIhk394/cHe/y/lzVylZ2g6ADh1bkZCQwOFDx7O0Txnxfb/WnNl5knO7T/PswVPWT1xNXEwc9Ts1TrN+VPg7wl++VT7K161IXEyc8kO1lV1hgnwe4X3ZE69LngT5PMbKzhqAlk5t8b3mTcBd/2zrX3pya79z63kucgZJJj6graNNqfIluXXBXVmmUCi4dcGdMlXKpLufvqE+O69uY9f17cxaPxPbkkWV2wJ8A7EuXhgLKwsKFragSDFrAv0eYVXUkuadv2P9/A1Z2ieRIikxiaSkZPR0dVTK9fR0cb/rlap+2Os3nL98nXYtv/tk20FPn9Gw9U8069ib8dPnEfwiVLmtlH1xvHwfEB4RiZfvA+Li4rApbIW7xz28/fz5qWPaH2Kzko6ODhUqleHC2SvKMoVCwcVzV3GsVjFDbegb5EFbR5u3b1O+7fPxfkAxe1usrC0pXMSS4vZF8fXxp6htETp3/YH5s5dnSV8+h46ONmUrlubyuWvKMoVCweXz16lUNf0pAe+rWbcaxeyKcuPKbQDue/tja2eDZeGCWFkXwtbOhgc+DyliW5h2P7Zi6ZxfsqQv4tN0dHSoVLkcZ85cUpYpFArOnrlE9eqVM9Xmw4eP0NfPQ4WKZTAxMaaKYwW87vmSP78Rk6eMZMyo6V8m+H9BS0ebYuXtuHfRQ1mmUCi4d/EuJaqkP2X3fQ06N+Hq4YvExcQB8MQvCMviVphZmWNeuACWxa14cj8IC5tC1O/YmF0Lt32ixayXW/udW89zkXPINKcPGJsao6WtxeuXqtMd3oS9wca+SJr7BD18wrzRCwnwCcDQyJDOTh1ZeWA5vRv35WVwGEH+Qfw69zcW7pgHwLq56wnyD2LRjvmsmb2W6g2q0mtkDxITk1gxbRV3r3lmeT9zI0NDAyqWc2D1xh0UL2qDmWl+jp46h8c9X2zSGHk49OcpDAz0aVL/41OcKpQpxaxJo7G1sSbs1WvcfttGj8FjObDlFwwNDahdw5GW3zWiS7/h5NHTY/bk0Rjo5+HnhauYNWkUv+//g+17DpE/vzHTxw3DvnjRjx7vSzA1y4+2tnaq4e+XL19h9/dowqdMmj6akBehyoTE/34A835eys596wCYO3Mp/vcD2Ln/V2ZNW0SDRnUYNWEwiQmJTHVx5drlW1+2UxlgYvr/fqtO4woLfU1xe9t098ubz5ALnn+iq6tLclIS08fPUyYkDx88YvFsNzbscQNg0axVPHzwiI17VrFgxnLqNKrJ0LEDSExMZNakhdz8OwkRWc/MzARtbW1ehoaplIeGhlGypF2m2nz7NoKBA8ayZt0i9PPosXP7fv46dYGVbnNZu2YLRW2t2bl7LTo62rjOXs7BA39+ia58lnwm+dDS1iI8THVaT3jYW6zsCn9yf7uKJbApXZR141Ypy577P+X3+dtw2TodgJ3ztvLc/ykTt01nh+smKtSvTPsRXUhKTGTz9PX4Xs/+0bjc2u/cep5nuWRZzSmjJJn4ArzdffB291E+v3fTi81nf6PVTy35beFGAA5tPcKhrUeUdb7r8C3RUdF43fJmy7mNOLV0poClOVNXTeLHWt1JiE/I7m7kCq5TxjDVdQmN2nZDS0sTh5L2NG9SH2+/1MPU+4+coGXThujp6X60zbo1qyn/X8q+GOXLlKJp+54cO32B9q1SRjWc+3bDuW83ZT2337bxTdVKaGtrs2bTTvZvduPc5etMnLWQXb+t+EK9zTrOI/rRul1zOrbqpTJEvmXDLrZs2KV83rFLG969i+LWDQ/O3zhCi0adsbQqhNuvC6lZqSnx/5HzPOpdNG0adsXQ0ICadavhMnMkTx494/rfCdHOTXvZuWmvsv4PnVsQ9S6a2zc9OX5lL+2b9qCQpQVL1s6hkWNreX//xx05fIIjh08on9euU51y5UozdvR07nieoU+v4YSEvOTMuQNcunQ9zTnrOVmDzo0J8nnEQ48HKuV/bTvOX9v+mdpSt31DYt7FcN/dj0WnVzGl9VhMLc0YunI0w+s4kRifmN2h/yu5td/p+drPc/HlyDSnD4S/DicpMQnTAiYq5SbmJrwOTX1xZlqSEpN4cM+fwrZWaW43NjGi58geLJ+yEofKDjwJfMqzwGfcueyBto421sWt/3U/RNpsrK3YuGoB10/t59S+Lez8dRmJiUlYWxVSqXfrzj0Cg57SrtVHrpNJh1G+vBQtUpigp8/T3B7w+AlHjp9maP8e3Lh9l6qVymFqkp/vGtXD28+fqKjoTPXtc7x+9ZbExETMC5iplBcoYJbq260POQ3phfOIvnRt1x8fr/vp1jMxzc/I8YOYMn4OlatWIMD/MYEBQVy+eB0dHe2PjgRklTev/99vU5VycwtTXoam/4dQoVAQFPgUn3v3+e2XbRw//BdOI3qlWdfE1JghY/oz02UBFauU49HDIB4HPOHapVvoaGtTzM7mS3ZJfMSrV29ITEykgIW5SrmFhTkhIS+/yDF0dXVZvGQmw4dNoridLdraWly6eB3/B4E89A+katWMTRv8kiLfRJKUmISxubFKubF5ft6+fPvRffX09ajZqg5nf//ro/XymeSj/YhObJr2K/aVSvIi8DkvHgXjfeUeWtpaWBZL++9fVsqt/c6t57nIOSSZ+EBiQiJ+nvepUqeKskxDQwPHOpXxds/Y8KWmpibFSxfjVWjqFXEAnKcPYveve3kZHIamliba2v8MEGlpaaGlKT+WrGagn4cC5qaER0Ry+fotGtX9RmX7viPHKVOqBKVLFP/stqOjY3jyLJgC5qaptikUCmbOX864of0xMNAnOSmZhMSUb7ES//43KRtWkEhISODuHW/q1P+n3xoaGtSpV4NbNzzS3W/QsD6MGDuQbh2cuHsn9XUm75sxZzzr3DYT/DwELU1NdHTeO8+1tdDSzP6lUhMSEvHy8KVmverKMg0NDWrWrcadm3cz3I6Gpia6ummPWE38eTQb1+wgJDgULS1NtD/stywRm20SEhK4c/seDRrUUpZpaGhQv0Etrl//MtPNxo135tSp83jc8Ur5eWv98/PW1tFWy887KSGRQM+HlK39z3VAGhoalK1dngfuH1/so0aLWmjr6nBx/7mP1us2tQ9H1x/m9YtXaGppoqXzTz+1tLXUslRqbu13bj3Ps5wiOec+chiZ5pSG3Wv34rJkHH4efvjc8aNDv3bk0c/Dn78fA8Bl6XjCXoSxbu56AHqM6Ia3uw/PHj0nr5EhXQZ2oqB1Qf7YcTRV2451q2Bd3BrXEfMB8PPww8a+CNUbVsPCyoLk5GSCAp5kX2dzmUvXbqFQKLC1sSbo6XMWrVpPMRtr2rZoqqzzLiqKE2cuMGZI/zTb6DtsAo3r1aJrh5QLpxesXEeD2jWwKlSQ0LBXrPp1K1pamnzfpH6qffcePoZJfmMa1En5EF+5QhncftuKxz0fLly9iZ2tDUbZtG73OrdNLHGbw93bXtx296T/oO7oG+rz+7b9ACz7ZQ7BwaHMnbkUgMHD+zLGZQhD+o/jSdBz5bdgUVHRRH8wmlK3QU2K2dkyfNBEADxu38OuRDEaNqmDVWFLkpOSeegfmC39/NCG1duYt2I69+54c9fdi55OXdE30GfvjsMAzF85g5AXoSyalTJv2ml4Lzzv+PDk0VN0dXWo36Q2bTp+z/RxrqnarlW/BrZ2NowbknLfkLu3vSluX5R6jWthaVWQ5KRkAvwfZ19nBStXrGf12oXcvu3JzZseDHbujYGBAVu3pNw7Zs26hTx/HsKMaQuAlItZSzvYA6Crq4OlVUHKV3Ag6l00AQGqP7tSpe1p174ldWq1BOC+30OSk5Pp3qMToSEvKVnSDvdbGU9Sv6Sjvx5i4KJhBNx9yEOPBzTv05I8Bnk4tzvlm/dBi4fx+sVrfp+/VWW/Bp2bcOvENd69jUy37XJ1KmJZzIrVo1IWVQjw8MfKrjAVG1TBzNKM5KRknj9Me2Q2q+XWfufW81zkDJJMpOHM4bPkNzOm95hemBYwwd/7IeO6uyiXey1Y2ALFe98e5zPOx5j5ozAtYMK78Hf4eT7Auc1wHj8IUmlXN48uw2cNZeagWcr7ULwMDmP5lJVMWDSW+PgEXEfMJz429TJt4suIfBfF0tUbCHkZhrFRPr6tX4dhTj3ReW906M9T51Ao4PtvG6TZxpNnwbwJj1A+DwkNY9y0ebyNiMA0vzGVK5Rl25olmJrkV9kv7PUb1m7aydbVi5Vl5cuUomeXdgweOw1Tk/zMmTz6i/b3Yw7tP4apuSljJg6hgIU5Xp6+dOvgpJz3amVtSfJ7F6D16NMZPT1d1m1eqtLOormrWDzPTfk8Tx49Zs+fxKA+Y5TnefDzEKaMn8PilbOJj49nxOCJxMbGZX0n03D0wElMzUwYNn4gBSzM8Ll3n76dh/Lq74uyLa0LkfzeNz/6BvpMnz+eQpYWxMbGEfDgEWMHT+HogZMq7erl0WPq3HGM7O+i7HdIcCg/T1yA6/KpxMclMH7oNOLU1O/cat/ePzA3N2Xi5JEULGiO510f2rftpZzOZ21tRfJ7v88tLS24dOUP5fPhIwYwfMQALpy/SovmXVXaXr5iDhMnzCY6OgaA2Ng4BjmNY+GSGejp6TJm1DSCg0OyoZepXT1yCSMzIzqM6kL+AiY89g5kbo+ZRPx9cbKZVQGV9zeAZXErSlcvw5yfpqfbro6eLr1m9mfFkIXK8/z1i1dsnPYrTguGkBCfwC+jl5OQxnKj2SG39ju3nuciZ9BQvH93ta9EA+sm6g5BLS6G+ny60lco5vkFdYegFrYlWqk7BLUw1NZXdwhqERAerO4Q1MJAR0/dIahFS3OZg56bHAlLf3rp1ywiKkDdIaQrel7qu4LnFAbjc9YtBWRyvhBCCCGEECJT1J5MxMTEcPHiRby9U1/cHBsby+bNmz+6f1xcHBERESqP5Bx4cYoQQgghhBBfG7UmE/fv38fBwYF69epRvnx56tevT3DwP0P54eHh9O798WEmV1dXjI2NVR5BkY+yOHIhhBBCCPG1UiQn59hHTqPWZGL8+PGUK1eO0NBQ/Pz8yJcvH7Vr1yYoKOjTO//NxcWF8PBwlYdNPtusC1oIIYQQQggBqHk1p8uXL3Pq1CnMzc0xNzfn8OHDDB48mLp163LmzBkMDQ0/2Yaenh56eqoX6GlqqH32lhBCCCGEEF89tSYTMTExKjds09DQ4JdffmHIkCHUr1+f7du3qzG6jOs1qge9RvVQKQvyD6JHgz5qiujrlSePJvmNddHT1URbW5PgkBiV7QqFglW/bmHP4WNERkZRuUIZpowZQtEihZV1wiMimbPYjbOXrqGpqUmTBrVxGT4QAwN9lXY27tjLnkPHeP4iBBNjYzq3a4FTzx9Vjnfw6En2HD7Gll8WcfLsJXYd+ANvP3/CIyLZs2ElpUvaqdSPi4tnwcp1/HnqHPEJCdSu7sjkMc6Ym6bccf1teATjZ8znvn9gylKzJvlpVKcmwwf2JO/fyfXJs5f4ff8fGJqn3OQuOQniozRJis/aJHrIyH40b/kt9iWKERsby83rd5gzfTEP/R9l6XHV7cde7fmxVwesbSwBeOAbwKpFv3L+r8tqjkxkhVq1qzF8xAAqVS6HpWVBfuzsxB9HTn56x/+4ZRfXUKCIRaryE5v/ZOOUtWqIKHvk1n7n1vP8syR/dYudZhm1JhOlS5fm5s2bODg4qJSvXLkSgNatW6sjrEwJ9A1k9I/jlM+TEpPUGM3XS1NDg/j4ZCIjEyhUMPUSob9t2822PYeYPXk0hS0LsXLdZpxGTebg1jXo6aXcsXj8jPm8DHvNuqVzSExMZPKcJUyfv5z508cr23Fdupor190Z49yPEna2hEdEEh6R+mZGpy9cpeHfN6CLiY2lSoWyfNeoHtPnLUsz/nnL13D+yg0Wz5pIXkND5ix2Y8TEWWxdvQhISagb1v2Gof17YGpiTNDT58xe5Eb4gkhlfLfueFKremVOn7iLQgE6eZLJY5xMzBsNkhM1/t0L/BHf1KrGpl93cOe2J9ra2kyYMpzt+9bR4JvWxETHfLqB/6gXz0NZNGsljwKC0ECDH7q0xG3zIto2+gl/v5y7rKHIHENDA+55+rBl826271yt7nCyzeTWY1Xu3lykpA0Tt8/g2h+X1BhV1sut/c6t57nIGmpNJn744Qd27NhB9+7dU21buXIlycnJrF793zjJk5KSeP3yjbrD+OpFxyQRHZN2oqZQKNiy6wADenahUd2aAMyZMob6rX7krwuX+b5JAx4+CuLi1Zvs/HUZ5RxKAjBx5CAGjZnKGOd+WBQw4+GjIHbt/4P9W1ZTrKg1ANZWhVIdLy4unss33Bk+sBcArZs1BuBZOjfviXwXxb4jJ5g/fRw1HCsB8POkUbTuOgCPez5ULOeAsVE+uvzQUrmPVaGCdG7Xkg3b9yjLJowYCMDM6SkrncVHaaGll4iWriJLk4luHZ1Uno8YPAlP/4tUqFSGa5dvZdlx1e3MCdX7mCyZ48aPvdpTqWp5SSa+QidPnOPkiXPqDiPbRb6OUHneelA7XjwKxueql5oiyh65td+59TwXWUOtFxe4uLhw9OjRdLe7ubmp3LExJytcrDB7bu5k+6UtTFrhgoVV6mFTkbWePn9B2Ks31KxaWVmWL68hFcqUwuOeLwAe93wwypdXmUgAfFO1MpqaGtz1Tqlz7tI1rK0Kce7yNb7r0Ium7Xsy1XVpqpGJq7fuUNDcjOJFi2QoPm+/ByQmJvLNe/EVL1oEy4IWyvg+FPryFafOXaJqpfIfaVmBhgaQzSOyRkb5AHj7Jjx7D6xGmpqatGjbFAMDfW7fuKvucITIElo62tT5oT7ndv2l7lCyVW7tt0iHIjnnPnIYtY5MfC28b/swd+QCngQ8wczCjJ4ju7N83xJ6N+5HTNTXO/0jpwl7nTIyZPb39Qf/Z2ZqQtirlG1hr95gmt9YZbu2thbG+fIp93/y7AXPQ0I5cfoCcyaPISk5mfnL1zBy0mx+WzFXud+ZC1do8PcUpwzF9+oNOjraGOXL+0F8+Ql7/VqlbOy0uZy5cJXYuDga1K7BzAkj0m1XxyAlmUiMzbpRiQ9paGgww3U816+64+fjn23HVZeSDnb8/ucG9PR0iY6KwbnXWB7eD1R3WEJkiapNq2NgZMi53afVHUq2yq39FuLfkmWPvoDrZ25w7o/zBPgEcuPcTSb0mEheo7w0bFVf3aGJTFAokomPT2DOlDE4VipH9SoVmOkykuvuHgQ+fvp3HQVnL11TXi/xpY0fNoBdG1awYu40njwLZv6KtC8E1NZLRtcwmdhwTRSK7Esm5iycTCmHEgzuOybbjqlOgf6PadOwKx2/68WOjXuYt2I6diWLqTssIbJEw85N8DjrztvQ3DV1N7f2W4h/S5KJLPAuIoqnAU8pbFv405XFF/P/FZFevVb9Q/Dq9RvMzVK2mZuZ8Pqt6rScxMQkwiMjlfubm5miraWFrY21sk5x25SpTMEhoQB4evuRlJREpfKqiwd8ND4zExISEomIfPdBfG8xNzX9oK4pxYsWoWHdb5g2bii/7/+Dl2GqoxfaesnoGaUkEkkJ2fdWnjV/Ek2+q0/HVr0Jfp729SFfm4SERIICn+J115dFs1bh63WfngN+/PSOQvzHmBcuQLk6FTiz85S6Q8lWubXf4iOSFTn3kcNIMpEF9A3yYGVryavQV+oOJVextiqEuZkJV2/dUZa9i4rirrcfFcuVBqBiOQciIt/h5ftAWefarTskJyuoUCalTuXyZUhMSiLo6XNlnUdBzwCwKpRyLczpC1epV7M6WlpaGY6vTKkSaGtrc+3mP/EFPn5KcEioMr60JCtSfnHEJyQoy46ePPtPIpHFS8K+b9b8STRr0ZhOrfvw5O/XJDfS0NREV09H3WEI8cXV79iI8Ffh3D59U92hZKvc2m8hvgS5ZuILGDR5AJdPXSXkaQhmBc3oPbonyUnJ/HXgjLpD++poaICOzj8fnnW0NfG9/xBjo3xYFrKge6e2rN20k6LWhSlsVZCV67ZgYW5G47q1ALCztaHON1WZPm8ZU8cOJSExkTlLfqF5k/pYFDADoGa1ypQpZc9U1yWMH+5EcrKC2YtWUbNaZeVoxdmLV3Hup7oKWXhEJMEvQgkNS0kiA4NSpkSZm5lgbmZKvryGtGvZlPkr1mFslA9DQwPmLPmFiuUcqFguZYTj/OXrvHrzlnIOJTHQ18c/8DGLVv1K5QplKGxZEIA/Tpxh0qxFxL3TJDlRAw3NlGRDoQCycKrTnIVTaNvhe/p0Hcq7d9EUsDAHIDIiktjYuCw7rrqNnuzMub8uE/z0BYZ5DWjVvhk1ajvSp9NQdYcmsoChoQHF7Yoqn9vaFqF8BQfevA7n6XtfMHyNNDQ0qNexERf2nCU5Kedd5JlVcmO/c/N5Lr48SSa+gAKWBZiyciJGJkaEvw7H8/o9BrceSvjr3LPKTXbR09OisOU/95cwN9OjQ+8htGnehNmTR9Pnp47ExMQyff5yIt+9o0qFsqxe9LPyHhMA86aNY/ZiN/oOc0FTU4MmDWozccQg5XZNTU1WzpvOnCW/0HPwOPT181D3m6qMHdofgKCnzwl69pzaNRxVYjtz4SqT5yxWPh87LeVi7UF9fsK5bzcAxg9zQlNTkxGTZpGQkECt6o5MGeOs3CePnh57Dh1j/vK1xMcnUKhgAZrUr0Xfbp2UdXYf+pPEpCTy5APy/XP8hBgN4iIzPlLyuXr27QLA3j82qZSPHDyJXTsOZNlx1c3U3JT5K2dgUdCcyIh3+Hk/oE+noVw+d03doYksULlKeY4e26F87jpvMgDbtu5hkNO49Hb7KpSrU4EC1haczWWrGeXGfufm8zzD/iOrieYEGgqFIudNvvqXGlg3UXcIanEx1EfdIahFzPMLn670BW3auY+rN27zy6Kfs/W4H7It0Uqtx1cXQ+3UNyvMDQLCg9UdgloY6OipOwS1aGleUd0hiGx0JMxD3SGoRURUzr1XT9T0nHtdnOH0HZ+ulI3kmgkhPlPBAub0695Z3WEIIYQQQqidTHMS4jM1a1xP3SEIIYQQIivlwFWTcioZmRBCCCGEEEJkiiQTQgghhBBCiEyRaU5CCCGEEEK8TyGrOWWUjEwIIYQQQgghMkWSCSGEEEIIIUSmyDQnIYQQQggh3ierOWWYjEwIIYQQQgghMkWSCSGEEEIIIUSmyDQnIYQQQggh3qNIltWcMkpGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk2lOGSYjE0IIIYQQQohMkWRCCCGEEEIIkSkyzUkIIYQQQoj3KeSmdRklIxNCCCGEEEKITJFkQgghhBBCCJEpMs1JCCGEEEKI98lqThkmIxNCCCGEEEKITJFkQgghhBBCCJEpX+U0p4uhPuoOQWSjdlWGqTsEtXj04LC6Q1ALfau66g5BLR6Wc1B3CGphdy93/j4/F3Ff3SGoxYS8ldUdglp0yveNukMQH1DINKcMk5EJIYQQQgghRKZIMiGEEEIIIYTIlK9ympMQQgghhBCZJtOcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvS05WdwT/GTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifrOaUYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifTHPKMBmZEEIIIYQQQmSKJBNCCCGEEEKITJFpTkIIIYQQQrxHoZBpThklIxNCCCGEEEKITJFkQgghhBBCCJEpMs1JCCGEEEKI98lqThkmIxNCCCGEEEKITJFkQgghhBBCCJEpkkwIIYQQQgjxvmRFzn1kkKurK9WqVSNfvnxYWFjQtm1b/Pz8VOrExsbi7OyMmZkZefPmpX379oSEhHzWSyXJhBBCCCGEEF+Zc+fO4ezszNWrVzl58iQJCQk0bdqUqKgoZZ2RI0dy+PBhdu/ezblz53j+/Dnt2rX7rOPIBdhCCCGEEEJ8ZY4dO6byfOPGjVhYWHDr1i3q1atHeHg469evZ/v27TRq1AiADRs24ODgwNWrV/nmm28ydBxJJoQQQgghhHiPIgev5hQXF0dcXJxKmZ6eHnp6eh/dLzw8HABTU1MAbt26RUJCAk2aNFHWKV26NDY2Nly5ciXDyYRMcxIC+L5HC369tJ699/ex8OAiSlQs+dH6hkaGDPx5IJtubmbfg/2sPrsGx4ZVldvrt23Ab1c3sMNzJ32n9FPZ18LagtVn16CfVz9L+pKWqKho5i5dzbfteuLYsA0/OY3C0+efeZOTZi2iXO3mKg+nUZM/2ubNO544j5tGw9Y/Ua52c/46fzlVnQ3b91CvRRfqtejCxh17Vbbd9fKlU5+hJCYmfZlOinTpVSlPgaU/U/j4Toq6n0K/Qa2P1jebPpai7qdSPSx3/6qsY9i8EYWPbsf67H5MRg1U2V/LsiBW+zeiYWiQJf0RGdOz349c9TjBw2B3Dp/cQaUq5dOt27VHB/Yd3YxX4GW8Ai+zc/+vqeo7DemFx/3zeNw/j5NzT5VtlR3L8+eZXWhpaWVJXzLCqkYpWv42it43VzD0yVaKf+f40foGFvlpumIw3c4tYMjjzdSd1i1VnSJ1y9Ht3AKcvNfx7dKBaOr80z/dfPp0O7eAfIXNvnhfPofZN6X5ZvMYvruzirYvtmPZrOpH65tWL0XdQ9P43nsNrQI30vjCQuwGNFepY92uNk1vreB733WUm676uhgUMafJpUVoZ+PfMKHK1dUVY2NjlYerq+tH90lOTmbEiBHUrl2bcuXKAfDixQt0dXXJnz+/St2CBQvy4sWLDMcjIxMi16vTqi79pvRj1cRV3L/jR+u+bZi5dSYDGzgR/io8VX1tHW1+3vYzb8PCmTvQlVcvXmFR2IJ3ESlzEI1MjBg6fyhLRy8l5PELpm6cxt3LHtz46wYAg2YNZtPcjcS8i8m2Pk6duwz/gEe4Th2DhbkZh4+fpv/wiRzctoaCBcxTXodvqjJr4kjlPjo6Oh9tMyYmllL2xfmhRVNGTJyVaruffyCrft3KqgXTUSgUOI+dTq3qVShpV4zExCRmLljBtPHD0NZW34eP3EIjTx4S7gfw7uAxLBbN+GT91wvdeLPin8RBQ0sLy51riT51HgDN/EaYThnNq+kLSHwajMXyWcTeuE3MhWsAmLkM482KX1FERWdNh8Qntf6hGdNmjWPCqBncvuVJv4Hd2bZ3DfWqteRV2OtU9WvWqcbBvUe5ee0OsXFxOA/vy/Z9a2lUsw0vgkNxKFuSsS5D6NnFGQ0N2LjTjXNnLuPr/QAtLS3mLp7GuBHTSUpS35cDOvp6hPkE4b3rPC3WjfhkfS1dbWJeRXJz+UEq9WuWuoKGBt+tGMzNVYcJOneX5quHUa5rI+5uOglALZfO3Nt6mshnr75wTz6PloEe4V6PebzjLDU2jPpk/aToWAJ+O0GETxBJ0XGYVi9FpQV9SYyO4/HW0+ia5qPyov64j1hN1ONQam4dy8tLXoScvA1Ahbl98Jq9k8Rs/BsmVLm4uDBqlOrP+lOjEs7Ozty7d4+LFy9+8XgkmRC5Xtt+bTm+4zh/7T4FgJvLKqo1qsa3nb9lj9ueVPWbdP6WvPnzMfaHsST9/a166NNQ5faCNoWIjojm4uELAHheuYu1fRFu/HWDeq3rkZiYyJVjV7KhZyli4+I4de4iy+dOo2qllG8anft249yla/y+/w+GDUj5hlFXRwdzM9MMt1u3ZjXq1qyW7vbAx08oaWdLDcdKAJS0L0bg46eUtCvGhu17cKxUnvIOpTLfMZFhsZdvEHv5RobrK95FoXj3zwV6+g1qoWmUl3eHUubfahe2RPEuiugTZ1Pav+mBTrGixFy4hsF3DVEkJhFz+sv/wRIZ139wT7Zv3sOu7QcAmDBqBo2b1qNLt3asWvprqvpDB4xXeT5m2FS+b/Utdep9w57fD2Ffohg+Xve59HfC6ON1H/sSxfD1fsCgYb25evkmHrfvZXm/Pubx2bs8Pns3w/Ujn4ZxYfoWABw610+1Xd80H/pmRnhuPkVSXAKBJ90xKWEFQCHHElhULM65yZu+TPD/QuhpD0JPe2S4fvi9x4Tfe6x8Hv0kDKvvq2FeoxSPt57GoKgFCZHRPDt4FYCXl7zJV6IwISdvU7htTRQJiQQfzfjvk/+sHDzNKSNTmt43ZMgQjhw5wvnz57G2tlaWFypUiPj4eN6+fasyOhESEkKhQoUy3L5McxK5mraONvbl7fG4eEdZplAouHPxDqWqlE5znxpNauB7y5eBswax+dYWVp5cRUfnjmhqprydnj96hp6+HsXLFievcV5KVCzJI59HGBob8tOYbqyZsjo7uqaUlJhEUlIyerqqIw16erq43/VSPr9x+y71WnShZZd+zFywgrfhEf/quCXsbHn05BnBL0J5/iKEx0+eYV+8KEFPn3Pg6EmG9e/xr9oX2Sdv2+bEXnMnKTglaU4MeoZGHj10StmjaZQP3TKliH8QgGa+vOQf3IvX81aoOeLcTUdHhwqVynDh7D9fWigUCi6eu4pjtYoZakPfIA/aOtq8fZsyOuvj/YBi9rZYWVtSuIglxe2L4uvjT1HbInTu+gPzZy/Pkr6oU8yrCN6FvMGmXnm08+hiVb0UYT5P0NTWouGcXpyZ8FuOnlefUcblimJarSRhV3wAiAp4gZa+LsbliqKT3xCTSnZEeAehY2yIw/iO3J24Ub0BiwxTKBQMGTKE/fv3c/r0aYoVK6ay3dHRER0dHf766y9lmZ+fH0FBQdSsWTPDx5GRCZGrGZkaoaWtxZuwtyrlb8PeYm1nneY+hWwKUqFWBc4eOMuMXtOxtLVi0KxBaOlos3PpDqLCo1gyagkjl4xCN48up/ee5vZ5d4bOH8Yfm45QsEhBJq+fgraONtuXbOfy0UtZ2kdDQwMqlnNg9cYdFC9qg5lpfo6eOofHPV9sClsCUPsbR5rUr01hq4I8eRbMsjUbGTh6CtvWLM70HGg7WxuGO/Wi/4iJAAx36oWdrQ39hrswanAfLl2/hdv6bWhrazFhxEDlqInIWbTMzdCvVZ2wSXOUZcmR7wibNh/zmePRyKNL1B8nib1yE7Opo4n8/SDahQthseRn0NYifM1mov+6oMYe5D6mZvnR1tYm7KXq9JuXL19hV6JYOnupmjR9NCEvQpUJif/9AOb9vJSd+9YBMHfmUvzvB7Bz/6/MmraIBo3qMGrCYBITEpnq4sq1y7e+bKfU5NigFdSd1o2607vx+IwHPr+fw9G5FU8v+5AUl0D7fVPRN83H3Q0nlNOf/iu+c1+BrpkRmtpa+C7cy+PtZwFICI/CfdhqqqwYhFYeXZ7svkDo2btUXtyfwN9OYGBjQY1NY9DUSdnv+ZHr6u2ISJezszPbt2/n4MGD5MuXT3kdhLGxMfr6+hgbG9O3b19GjRqFqakpRkZGDB06lJo1a2b44muQZEKIz6ahqUn4q7esmrCS5ORkHno+xKygGe0GtmPn0h0AXD1+havH//lWsFyNchRzsGXt1DWsubCWhUMW8OblGxYdWozXtXtpXpvxJblOGcNU1yU0atsNLS1NHEra07xJfbz9/AH4vkkDZd2SdsUoaVeM5p36cOP2Xb6pWjnTx+38Qws6/9BC+fzg0ZMYGOhTsZwDrX7sz85flxESGsbYqXM5vmcDurq6mT6WyBqGrZqSHPmO6DOqSW/MmUvEvFemV6UCOiWK83r+SqwObiLMZQ5Jr15juXkVse6eJL95m82Ri8xyHtGP1u2a07FVL+Li4pXlWzbsYsuGXcrnHbu04d27KG7d8OD8jSO0aNQZS6tCuP26kJqVmhIfn6CO8L+o4Bv32dVyqvJ5/mKFKN2+DjubTaLdnil4/Hacx2c86HrKlWfXfHnl+0SN0X6eC21nom2QBxNHe8pO6sK7wBc8O5Dydyv4z5sE/3lTWdesZmmMythwd9ImmlxZws1BK4gLDaf+nz8TdtWX+LB/N5KdIyWrO4B/75dffgGgQYMGKuUbNmygV69eACxZsgRNTU3at29PXFwc3333HW5ubp91HEkmRK4W8TqCpMQkTMzzq5TnN8/Pm5dv0tznTehrEhOTSE7+5zfNU/8nmFqYoq2jTWJCokp9bV1tBs0exOIRi7G0tURLS4t711LmFj8PfEbJyqW4cSprv9mxsbZi46oFRMfEEhUVTQFzU0ZPccX6f+zdd1hT1xvA8W9IwlTZKEMEwVn3nnVUraOOWme1at1776117133to66qq277r0noAIqDmTJRpCR3x+0aAoq8gOC8n6eJ0+be8899z3kmuTNGdcu5TGRee1tMTfLhc8z3/8rmXhXcEgov677jfVLZ3Hn3n3y5bVPesTFx/H46XMKuqTuV1OReXI0/ZbIA8cgLu79hdRqLEb1J2jcDFR57VAolcRcTxy7HuvzDIPihXl9+mImRSxeBYUQFxeHlbX2KkPW1pYE+Ad+8NgefTvRZ2AX2jTrivu9B+8tZ25hxqARvfihUUdKlyuBt+cTHnn78MjbB7VaRX5XJzzcHqZLe7KSWjM6c/aX30BPD5viTnj+eYm46Dc8v+iBfaXCn1UyEeUTAECYx1MMrE0pPPSHpGTiXXr6KkrO6My1vsswccqNnkqPoAseAER4+2JR2pWXR69nauwidTSajw/DMzQ0ZOnSpSxdujTN55E5EyJbi4uNw/OOJyWqvh1HrFAoKFm1JPeve6R4jNtVd2zz2aJQKJK22eW3J8gvKFkiAdC6XxuunbyO110v9JR6KN9ZvUipUqHUy7x/hsZGhlhbWRAaFs75y9eoXT3lbsyX/gGEhIZj/QkTsj9m5qKV/NSqGXlsrIlPiCfunS+n8fEJJMR/AT8DfWEMypZE7ehAxN6DHyxn2rUd0eev8MbDE/SU8M7QOIVKCZl4jQuIjY3l9k03qtV4++9boVBQ7euKXLvy/om6vfp3ZuCwnrRv0YPbN++9txzApGkjWLVsI74v/FDq6aFWv/1tUqlSotT78lZpK9q6BtEhETw6eh09ZeL7/79LxSrVShTKz/c6V+gpUBqkvIJfoYHf43/iFqF3HqNQ6qF459+3nurzbrdIH9IzIbK9vav3MmjuIDzvPOTBzQc07dIUQ2NDju1IXN1p0PzBBL0MYuPMxFU7Dm46wHcdv6PbxO78uX4/ds52tOzTkj/X7U9Wd94CeaneuDoDGvQH4JnnMzQJCdRtXZfggGAcXBx4cCvjf707d+kaGo0GJ0cHfJ69YO7SNTg7OtCsUT2iol6zbO0W6tasipWlBU+fv2DesrU4OthRtWKZpDq69B/JN19X4ccWTQCIinqNz7MXSfufv/DD44EXprlyYpvHRuv85y9f58nT50wbOwSAYkUK8ujJM85cuMJL/wD09PRwypfyHBXx/1MYGaLKa5/0XGVvi7qgCwlh4cS/9MesbxeUNlYEjZ+pdVyOZvWJueNOrNfj99atdnbEpF5NfNsm3msi7rEPJGjI0bQ+8UHBqJ0ceXPv/nuPFxlj1bINzF82jds37nHj+h269foJIxMjtm/ZA8DCX6fh6+vPjMkLAOg9oAtDR/Wlb7fhPPV5gbVN4pLRkZFRRP1nid/qNSvj7OLEgF6J86Fu3biLSwFnatWphp29LQnxCXh5Psq8xv5DbWyAqVPupOe58lpjVdSR6JBIIl4EUXlEK3LkMefooBVJZayKOiYea2KAkWVOrIo6Eh8bR/DDF1p1G1nmolz/puxqPhmAmNAoXj14Tqku9fE5fQeHql9xZfG+TGhlckpjA3I4v+1lNna0xvSrfLwJieD18yCKjm6Noa0F1/slDnlx/rkur58FEe6Z2EarSoVx7dUI79WHk9Wds6A99k0rcaJu4msd7vkCTYKGfG1rEh0QQg5XO4JvemVCKzPflzC5PrNIMiGyvbP7z2BqYUq7we0xtzbH282bCT+NJ+SfSdnWdtZo3hnSFOgbyPifxtN1fFcWH15CkF8Q+9fuY9evu5LV3XdGX9b8spqY14l3qnwT84YFQxbQ85deqPXVrBi/nFd+Gb9GeXhEJAuWr8MvIBDTXDmpW6Ma/Xt0RK1SER8fzwOvR+w7eIywiEhsrCyoUqEMfbt10JrD8PS5L8HvrPB01+Mhnfu9XU5y1uKVADRtUIep/yQNkLg07bR5y5gzeVTSild5bKwZNagXY6fNR1+tZurYIRh+wjJ34tPoFy1EnlVzk55bDOkFQMS+wwRNnI3SygLVfxJARQ4TjGtXJ3jOh8fOWowdTPC8X9FERwOgiXlD0MRZWIzsj0Kt5tXMxcQH6HYd/uxo355DWFhZMHR0X6xtrLh3x4P2LXokTcq2c7Al4Z0vSx06t8bAQJ9VGxdo1TN3xlLmzXx7DRgaGjB11hh6dR6aNITC94Uf40ZMY96Sqbx584aBvUcTHa19d97MYFMiP81/H5P0/N+b0Ln/fppjg1diktuMHPZWWse0Pfx2YYHcJfJT6PuqhD0NYEOVQVrlvp70EzdXHiTSLyRp27EhK6gzrwclOtfj+vK/8L/lnQGt+jjzUvmptntc0vPik38CwGf7Ka4PWIFhbjOM37mxnkJPQdExrTF2tEYTl0DkYz/uTdnG441/J6u71Oyu3Jm4mfioxNczITqW6wOXU3J6J/T01dwevZ7olykPCRbZh0KTmgFVnxmVvv3HC4kvRoM86TOm/3Oz+/qXtxRjahjZVdd1CDrhVayIrkPQCZe77roOQSdym5jpOgSdGJkje76f543NnsM8m738TdchvFdIu9q6DuG9zLYc13UIWqRnQgghhBBCiHfJMKdU03ky4e7uzsWLF6lcuTKFCxfGw8ODhQsXEhMTQ/v27ald+8OZYUxMDDEx2t2pGo1Ga3KsEEIIIYQQIv3pdAr+oUOHKFWqFEOHDqV06dIcOnSIr7/+Gk9PT548eUK9evU4fvzDXTnTp0/H1NRU66FJCM+kFgghhBBCCJF96TSZmDx5MsOGDSMoKIh169bx448/0q1bN44ePcrff//NsGHDmDFjxgfrGDVqFKGhoVoPhV7OTGqBEEIIIYT44iRk4UcWo9Nk4t69e0l34GvVqhXh4eG0aNEiaX+7du24ffv2B+swMDAgV65cWg8Z4iSEEEIIIUTG0/mciX+/+Ovp6WFoaIipqWnSvpw5cxIaGqqr0IR4L4vclnQa1YmytcpiYGSA72NfFg5dgOdtz0yLITIyisWrNvL36Qu8Cg6hcEEXRg7sQfEihZLKeD32Yf6ytVy9eYf4+HjyOzmyYOrYpPtA/P7HAf46ehL3+55ERr3m/KHfyZUzR7JzRcfEUL1ha3ZtWIaRoSGzl6zinsdDfJ69oF2LJowc2DPZMYePn2HJqo08f+lHPgd7BvX6ma+rVEjaf/TkOXbs/Qu3+56EhoWzc90SChd00aojJuYNs5es4uCxU7yJjaVqhbIo9RTEy8S4dGdQpji5OrRCv0gBVNZW+A8ez+uT55P257t+LMXjghesJGzjjswKU2SQvoO60uC7urgWcCY6Opqrl28ybeI8vDwf6zq0dGVXsRBlejTCuoQzOXKb81fX+Xgfvpa036V+OYr99A3WxZ0wMs/J1m9HE+jmo8OI04dlpcIU6P0dpiWcMcpjzqVO8/A9dDVpf+GhP2DftDJG9hYkvIkn5PYj3KdvJ/jGl3kPCZG+dNoz4eTkxMOHb2/YdeHCBRwdHZOe+/j4YGtrq4vQhHgvE1MTZu2eRXxcHBM7TKTPN71Z+8saIkIjMjWO8TMWcuHKDaaPH8qeTb9SpUIZug0YjV9AIAA+z17QoddQnPPlZd2SmezasIyenX5E3+DtvSOio2OoVrEc3Tq0+eC5Lly+gW0eGxwd7HgTG4u5mSndO7ahkKtziuVv3HFj+MQZfP/dt/y+bgm1q1em/6hfeOj9OKnM6+hoypT4ikG9Or/3vDMXreDkuUvMmzKa9UtmERAYRO7chp/wVxKppTA0JPaBN69mLE5x/9O6LbUegRNno0lIIOrvM5kcqcgIlaqUZ8PqrTSu15a2zbuhVqv4bfcqjIyNdB1aulIbGRDo7sOpsRtS3K8yNuDF5fucn7Y9kyPLWEpjA0LvPeH2qHUp7o/w8uX26PUcrzmSM00nEvU0gCrbR6FvmX2HjWsSNFn2kdXotGeiV69exMfHJz0vVqyY1v6DBw9+dDUnITJbi14tCPQNZOHQhUnb/J76ZWoMCSRw7NRZFs2YQLlSxQHo06U9p85dYvuev+jfvSOLVm6geuXyDOnTJek4Rwc7rXp+av09AJevf3g44fGzF6hVrRIA9ra5GfVPT8Sev46kWH7zjj+oWrEcndslDlvs170DF65c57ed+5kwvB8ATep/A8Bz35T/duERkez+8wizJg6nYtlSAPwyZjBNfuyOgYEeMTFZcODoZyz6/BWiz1957/6EIO0bUxnXqEL01ZvEPffN6NBEJmjfsofW84G9x3DH8ywlShXl0vlr7znq8/Pk5G2enHz/+9393ecAyOlg9d4ynyP/47fwP37rvfuf7Tmv9fzuhM04tatFriKOBJ69l9Hhic+cTnsmevbsSaNGjd67f9q0aaxevToTIxLi4yrUrYjn7YeM+HUkm65vZsGBhdRr+22mxxEfn4CBvlprm4GBPtdv3yMhIYHT56/glNee7oPG8HWjNrTtNpC/T59/T23vl5CQwKlzl6lVvXKqj7l1z53K5UppbatSsSy37qX+BmRu9x8SFxdHpXJvb2KVP19eYuMSMDRQproekf70LMwwqlaRiL2HdB2KyCC5ciX+Ih0SLEONsxuFWonTT7WJDY0k7AsY4iUynk6TCSE+R3ny5qFB+4a8ePSCCT+N5+DmA3Sf1J3aLTKvF00PPUoWK8Ly9VvxDwgiPj6e/YePc+uuB4GBr3gVHELU69es2byDahXLsXL+VL75ugoDR0/hyo0P90L81617HgCUKFroIyXfCgwKxtLCXGublYU5gf/5dftjdajVqmRzOOLjNSiVssiCLuVoXI+EqCiijssQpy+RQqFg0vQRXL54nfvumTcPTOhW7rql+c5rLU2ebMClewPOtZ7Om1fZeKl9Xa/Y9Bmt5qTzCdhCfG4Uego8b3uyadZGALzveZOvUD4atGvI8Z2Zd4v76eOGMn76fGo3a49SqUeRgq40qFMDt/ueJPwzprJW9cp0aJM4lKlwQRdu3nFjx94DlC9dItXnOXHmAjWqVkBPT357EIlyNKlP5MHj8CZW16GIDDBtzlgKFSnA9w1+0nUoIhMFnnPjxDej0LfIiVP7WpRf2Z9TDcfzJjBM16GJLE6+HQjxiYL9g3n6ULvr9+nDp1jbW2dqHI4OdqxfOpvLx/ZwbPcmtq1eSFxcPA52eTA3y4VKqcTFyVHrmPxOefH1C/ik85w4eylpvkRqWVmaE/RKuxci8FUwVpbm7zki5TpiY+MIC9ee2K5UKoiPz3oT0LILg9LFUDs7ErHngK5DERlgyqwx1Pm2Bi0b/4zvi8ydCyZ0Kz4qhsjHfgRf9+TG4FVo4hLI17amrsMSnwFJJoT4RO5X3bB3cdDaZp/fHv9n/jqJx9jIEGsrC0LDwjl/+Rq1q1dCrVbzVZGCPPJ5plX28dPn2P2zLGxqPHn6HN+X/lQuX/rjhd9R8qsiXLx2U2vbhSs3KPlVkVTXUbRQAVQqFZeuvq3n0ZNnqFV6RMfEv/9AkaFyNG1AjNt9Yh966zoUkc6mzBpD/Ubf0KpJZ576PNd1OELHFHoKlAbqjxf8Qul6xSZZzUmIL9gfq/9g1p7ZtOzTkrN/nqVgqYJ8+2N9loxckqlxnLt0DY1Gg5OjAz7PXjB36RqcHR1o1qgeAD//+ANDx8+gXKliVChTkrMXr3Lq3CXWLZ6ZVEdg0CsCg4LxefYCgIdejzExNsI2jw2muXJy/MwFKpUrhZGh9nKsHg8S1x6PioomOCQUjwdeqNUqXJzzAdC+VVN+7jOc9Vt38XWVChw8dop7Hg+ZOKJ/Uh2hYeH4vvTHPzAIICnxsbI0x8rSgpw5TGj+XT1mLV6Faa6cmJgYM23+r0RHx8tKThlAYWSIKq990nOVvS3qgi4khIUT/zIxUVaYGGNc92uC563QVZgig0ybM45mLRrS+cd+REREYW2TuJpReFg40dExOo4u/aiNDTB1yp30PFdea6yKOhIdEknEiyAMzEzIaWeJSe7EXlRzl8Tl6aMCQokK+HwnoyuNDcjhnCfpubGjNaZf5eNNSARvgiMoOKAZLw9fI9o/BH2LnOT/uS6Gecx5vv+iDqMWnwuFRqPJeinO/0mlb//xQuKL0SDPp/1qnh7Kf1OeDiM6Yudkh99TP/au3suRrYczNYbus1uwYPk6/AICMc2Vk7o1qtG/R0dy5jBJKrP7z8Os3rQDP/9AnBwd6NO1PbXfWZVp6ZrN/Lp2S7K6p4weTLNGdenQayhNGtShRZP6WvuLVW2Q7Bi7PDYc2fV27fbDx8+weOWGpJvWDe7dWeumdXv/OsrYafOS1dOrczv6dGkPvL1p3YGjJ4mNjaVKhbKs2Xw0Ww5z8iqW+l6dtDAoW5I8q+Ym2x6x7zBBE2cDkKN5I8yH9OLZt63RRERmaDz/crmb+hXAviS5Tcwy9XzPg1Ne/nNQ7zHs2Lo30+IYmSNj38/tKxWh+e9jkm13//00xwavpHDL6tSd1yPZ/kvzdnN5/u4MiytvbMb+QGJVpQjVdo9Ltt1n+yluDl9LuWV9MC/jir5FTt4ERxBy04v7C/YScjNjeyCbvfwtQ+v/f7z6voauQ3gviz2ndB2CFkkmxGdPF8lEVrD7+qIMrT84JJRaTdpxbO8mrCxSP9choxnZVdd1CDqR0clEViXJRPaS0clEVpXRyURWlaWTiaZZOJn4I2slEzJnQgiRotCwcIb165alEgkhhBBCZC0yZ0IIkSInRwecHB0+XlAIIYQQ2ZYkE0IIIYQQQrxDkz1HnqWJDHMSQgghhBBCpIkkE0IIIYQQQog0kWFOQgghhBBCvEuGOaWa9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iGrOaWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iXDnFJNeiaEEEIIIYQQaSLJhBBCCCGEECJNZJiTEEIIIYQQ75DVnFJPeiaEEEIIIYQQaSLJhBBCCCGEECJNJJkQQgghhBBCpInMmRBCCCGEEOIdMmci9aRnQgghhBBCCJEmkkwIIYQQQggh0kSGOQkhhBBCCPEOGeaUetIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHiXRqHrCD4bkkx8QYzVBroOQSfuv36p6xB0wsiuuq5D0InXL87oOgSdyK6vd3Z9X/OLDNF1CDox5s15XYegE4/r5dV1CEKkmQxzEkIIIYQQQqSJ9EwIIYQQQgjxDlnNKfWkZ0IIIYQQQgiRJpJMCCGEEEIIIdJEhjkJIYQQQgjxDk2CrOaUWtIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHiHrOaUetIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHiHRiOrOaWW9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iGrOaWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3qFJkNWcUkt6JoQQQgghhBBpIsmEEEIIIYQQIk1kmJMQQgghhBDv0Gh0HcHnQ3omhBBCCCGEEGkiyYQQQgghhBAiTWSYkxBCCCGEEO+Q1ZxST3omhBBCCCGEEGkiyYTQ0q37T9xxO41/kDvHT+6mbNkS7y1buEgBNm1Zxh2304RFetO7z8/JyrRq3RS3+2d58uwG02aM0drn6GjP9Zt/kzNnjnRvx6dq17klx6/t487Tc/x+aD0lSn/13rL1GtVi19GNXPU8wc3HZ/jjxBaatmyoVaZz7/ZccDvCBbcjdO7VTmtfiTJfsfvYJpRKZYa0RbwVGRnFjAXLqdu8I2VrNaVdj8Hccb+ftL9Y1QYpPtZu2fneOpeu2ZysfOO23bTKzFq0kir1W/LN9z/x5+HjWvsOHz9Dn+ET0reh4oOy6/tadpXdXm9V0RLkGD0dszW7sNhzCnWFah89xqBBM0wXb8R82xFMl2xCv+a32nWWLIfp0s2YbzmAyYAxoHo7kEVhbILp0s3oWedO97aIz5MMcxJJmv/QiGkzRjNwwDiuXrlJ7z4/s/uPDZQtXYfAgKBk5Y2NjHj82Ie9ew4wfebYZPstLM1ZvHQ6vXoM4/Gjp/y+ezWnT17g0KHEL1fzFvzChPGzCA+PyPC2fUjDZnUZNXkQ44dN59a1u3Tq0ZY1OxbzbeUfeBUYnKx8SHAYy+evxfvhY97ExlKrXnWmLxpPUOArzp64SKGirgwY0ZMe7QaiUChYsWU+Z09e5IG7F0qlkslzRjNu8FTi4+N10NrsZfyMhXh6P2b6+KHYWFmy//Bxug0YzR9bVpDb2oqT+7ZolT9z8Srjpy+gbs2qH6zX1TkfqxdOS3r+bmJ48uxF/jp6kpXzp+Lz7AXjps2nasWymJuZEh4RyaKVG1i9YFpK1YoMkF3f17Kr7Ph6KwyNiH/sSczfB8g5cspHyxt82xTj9t2JXDabOE8PVAWKYNJ7GJqIcGKvngeFghyDxhG9ewuxNy6TY/hkDOo2JubgHgCMfupBzOF9JAT4ZXTTdEqGOaWe9EyIJH37dWHDuu1s2bST+x6eDOw/ltevX/NTh5Yplr9+/Tbjxsxg184/iYl5k2y/s1NewsLC2b3rL65fv83pUxcpWNgFgBYtGxMbG8v+fYcztE2p8XPPduzYvJfdW/fj9eAR44dOJ/p1NC1+bJJi+cvnr3H0wEm8Hj7m6ePnbFy5jftunpStWAqA/AWcuO/2kItnr3LhzBXuu3mSv4ATAF37/sSVC9e5c9Mtk1qXfUXHxHDs1FkG9+lCuVLFcXSwo0+X9jg62LF9z18AWFlaaD1OnLlIhTIlyGtv+8G6lUql1nHmZqZJ+7yfPKV86eIUK1KQhnVrYmJizDPflwDMW7aG1s0aYZvHJuMaLrRk1/e17Co7vt6x1y/x+rc1xF46k6ry+jXrEX1kH2/OnSDBz5c3Z48TfWQ/hs3bAqDIZYqeqRnRB/cS//Qxby6fQ5k3HwCqQl+hci1E9J/v770V2Y8kEwIAtVpNqdLFOHHiXNI2jUbDyRPnqFChdJrq9PJ6jJGRISVKFsXc3JQyZUtw764HZma5GDtuEEMHT0yf4P8ParWKr0oW5vypS0nbNBoN509fplS593eNv6ty9fI4u+TjyoUbADxw88TJxRFb+9zYOeTBycWRh+5e5HWyp3nbxiyY9muGtEVoi4+LJz4+AQN9tdZ2AwN9rt++l6x84KtgTp+/TPPvvk227798nj2nVpN21G/5MyMmzsT3pX/SvkKu+bnn8ZDQsHDueTwkJiYGR3s7rt+6i9t9T9q1TDlJFekvu76vZVfyeqeOQq2GN/9JnN7EoHItAkolmtAQEl4Foi5VDvQNUBUtQfxjL1AqMe4xmMhf50JCgm6CF1mSDHMSAFhamqNSqQjwD9Ta7u8fSMGCLmmqMyQkjJ7dh7Fi1VyMDA3Y9tse/j52hiXLZrByxSbyOTmw7feVqNUqpk9dxB97D6ZHUz6JuYUZKpWKwIBXWtsD/V+R39XpvcflyGnCmTsH0dfXJyE+nokjZiYlJF4PHzNv6jLW7VwGwNwpS/F6+Jj1O5cye9IiqtWuTL9h3YmLi2PKmDlc/ScJEenLxMSYksWKsHz9VvLnc8TSwowDx05x664Hjin0POw7eAxjYyPq1PjwEKcSRQsxZcwQnBwdCAx6xbK1W+jQexh7N/2KiYkxVSuW5btva9Om6wAMDQyYOnYIxkaG/DJnKVPGDGb7nr/4bec+zMxMmTi8P67582XUnyDby67va9mVvN6pE3vjCgZ1vuPNpbPEez9A6VIIgzqNUKjVKHKZogl+RcSciRj/3BfjLv2JvX6RmL8PYNi8HXF3b0DsG3JOW4JeLlOi/9qdNPzpSyM3rUs9SSZEhvpz/xH+3H8k6XnVahUoVqwww4ZM5OadE3TuNAA/vwBOnNrLuXOXUxzTmhVFRkTRtNaPmJgYU7l6eUZNHsTTx8+5fP4aANs27GLbhl1J5b9v3YjIiChuXL3D4Qu7+KFeB/LY2jB/5TRql21C7JtYXTXlizZ93FDGT59P7WbtUSr1KFLQlQZ1auB23zNZ2T1/HuG7erUwMND/YJ3VK5dP+v9Crs4UL1qIej905NDxM/zQOLFXo0+X9vTp0j6p3LK1W6hUrhQqlYoVG7axZ+MyTp2/zOgpc9ixdnE6tVZkli/1fU2k7Et7vV//vgE9cwtyzfwVFKAJCSbmxGGMmv8ICYnfoOPc7xA2vEfSMXp2DhjU/JbQIV3JNWUR0X/tJPb6JUwXrifO7RbxT7x11RyRBcgwJwFAUFAwcXFxWNtYaW23sbHCzy8gXc6hr6/PvPmTGdB/DPldnFCplJw7exnPh4/w8nxEuXIl0+U8nyL4VQhxcXFYWVtobbeysSDA//0fCBqNBp9Hz3C/+4C1v27h8P6/6TGwU4plzS1M6Tu0G5NHzaZkmWI89vLhifdTLp27hlqlwtnFMT2bJN7h6GDH+qWzuXxsD8d2b2Lb6oXExcXjYJdHq9y1m3d55POM5o3rf/I5cuXMQb689vg8e5Hifu8nT/nz8HH6devAlRu3KVeqGBbmZnxb+2vc7nsSGRmVpraJj8uu72vZlbzeqfTmDZFLZhLcph4hPdoQ0r0VCf4v0URFogkLSfEQk55DiVq/FBQKVC4FeXPuJJrQEOLu3UL1ValMDV9kPZJMCABiY2O5eeMuNWtWSdqmUCioUbMKly+nzzCc4SP6cOzYaW7dvIdSqYdK+bZjTKVW6WSp1NjYOO7d8qDy1xWStikUCipXL8/Nq7dTXY9CTw99/ZR/0R79yxDWr9iKn69/YrvVb9utVCllidhMYGxkiLWVBaFh4Zy/fI3a1Stp7d/952GKFipA4QL5P7nuqKjXPH3ui7WVRbJ9Go2GybMWMbxfN4yNjUiITyA2Lg6AuH/+Gy9jjzNMdn1fy67k9f5E8fFoggIgIQH96rV5c/VCimN79L9piCYijNgr51HoJX5tVPy7VKxSCXpf5ldJTYIiyz6yGhnmJJIsWbyG5SvncOPGHa5evUXvPj9jbGzM5k2JqzasWDWHFy/8mDRhNpA42a1wEVcA9PXV2NrlpniJIkRGROHt/USr7kKFXWn+w3dUq/IdAA/ue5GQkMBPHVrh7xdAwYIuXL+W+i/v6Wnd8i3MXDyRuzfduH39Hh17/IiRsRG7tu4HYNaSSfi99GfulKUA9BjQiTs33Xn6+Bn6+mpq1KlK05YNmTh8erK6q9SoiJOLI8P7Jt5X4PYNN/K75uPrb6pga5ebhPgEvD2fJDtOpI9zl66h0WhwcnTA59kL5i5dg7OjA80a1UsqExEZyZETZxjat1uKdXTpP5Jvvq7Cjy0SJ07PXrKKmlUrYpcnN/6BQSxdvRmlUo+GdWokO3bX/kOYm5lSs1pi8lK6RFGWrd3MrbvunLl4FRcnR3LJ/QgyVHZ9X8uusuXrbWiEMo990lO93LYonVzRRISREOiPUftu6FlYE7kocUlqPTsHVAWKEPfADUWOnBg2boXS0ZnIhck/wxSmZhi17EDYqD4AaCIjiH/6GIPvWhB36yrqEmV5vXNz5rRTZFmSTIgku3f9hZWVBaPHDiJ3bivu3Hbnh2adkiazOTjYkfDOr6i2tjacu/BX0vMBA7szYGB3zpy+SKMGP2rVvWjxNEaPnEpU1GsAoqNj6NVjOHPmT8LAQJ+hgyfg66ubNasP7D2KhaU5/Uf0xNrGEve7D+jSuh9B/0zKtnXIQ4LmbbuNjI2YOGsEeWxtiI6OwfvhY4b1HseBvUe16jUwNGD8jOEM6jYKzT+/9vj5+vPL6NlMXzSeNzGxjOg3gZjomMxrbDYTHhHJguXr8AsIxDRXTurWqEb/Hh1Rv3MDpoPHTqHRQMO6NVOs4+lzX4JDw5Ke+/kHMnzCTELCwrAwM6V0ia/YsmI+FuZmWscFvgpm5YZtbF4+L2lb8aKF6NimOb2HTcDC3IxpY4eka3tFctn1fS27yo6vt8qlELmmLEx6btK5LwAxxw8SuXgGeuaW6Fm/sxy1nhLDJq1R2udFExdH3N0bhI3sQ0LAy2R1G3fpT/Qf29EEvx32G7F4Ojn6j8bwux94vXcb8Z4eGdc48VlQaDRZa766RqNBofj/unBU+vYfL/QFMlYb6DoEnchjnHx4SXbgHeqr6xB04vWL1K2l/qUxsquu6xB0Iru+r0XFZs8fGbLr6/24Xl5dh6ATFntO6TqE9/Iq9vFlwnXF5W7WupdNlhvoZmBggLu7u67DEEIIIYQQQnyEzoY5DR48OMXt8fHxzJgxA0tLSwDmzZuXYrl/xcTEEBOj/QtOevRuCCGEEEIIIT5MZ8nEggULKFmyJGZmZlrbNRoN7u7umJiYpCohmD59OpMmTdLaptDLgUKZKz3DFUIIIYQQ2YRGFtpLNZ0lE9OmTWPlypXMnTuX2rVrJ21Xq9WsX7+eokWLpqqeUaNGJevlMLcsnK6xCiGEEEIIIZLT2ZyJkSNHsn37dnr16sXQoUOJjU3bHYANDAzIlSuX1kOGOAkhhBBCCJHxdLo0bPny5bl27Rp9+vShXLlybNmyRRKBz0iVquUZMLA7pUoXw9Y2N21b9+CvP49+/MDPXNtOP9C2UwscHG0BeOjhzdK5qzn993kdR5Y9RUZGsXjVRv4+fYFXwSEULujCyIE9KF6kEABjpszlj4PHtI6pWrEsK+ZNAeDy9dt07jcixbq3rl6QVA/AlRu3GTl5Nn/v2fTR80LiDe3m/7qO42fOExIajr1dbtq1aErr7xsBEBoWztLVmzh/+Tq+fgGYm5tSu3pl+nXrQM4cJun6dxKpk13f17Kr7PJ6q4qWwLBZW1QuBdGzsCJ8+hhiL59N2q8wNce4Qw/UpcqjMMlB7L1bRK1eSILvcx1GrVsJGvk+mlo6v89Ejhw52LBhA9u2baNOnTrEx8frOiSRSiYmxty9486mjb/z27blug4n07x84c/cKUt47O2DAgXft/mOZRvn0qx2Ozzve+s6vGxn/IyFeHo/Zvr4odhYWbL/8HG6DRjNH1tWkNvaCoBqlcoxZfSgpGPUanXS/5cuXoST+7Zo1bl41SYuXbtJscIFtbafOHORmlUrpvq8sxav5NK1W0wfPxx729ycv3yNKXOXYmNlSa3qlfAPDMI/8BVD+3Ylv5Mjvn7+TJ69hIDAIOZPHZshfy/xYdn1fS27yi6vt8LQiPjHnsT8fYCcI6ck259z1FQ0cXGETx+DJioSwyatyDlxHqH9O0JMtA4iFp8TnScT/2rTpg3VqlXj2rVr5MuXT9fhiFQ4euQUR49k3TWiM8qJI9r3OZg/bRltO/1AqXLFJZnIZNExMRw7dZZFMyZQrlRxAPp0ac+pc5fYvucv+nfvCIC+Wo2VZcr3I1H/Z19sXBwnzlzgxxZNkvWUnjh7kTGDe6f6vDfvuNO0QR0qlCkBQMumDfn9j4Pccb9PreqVKJDfiQXT3iYNjg529O/ekZGTZxEXF49KpUynv5RIrez6vpZdZZfXO/b6JWKvX0pxn56dA6pCXxHavyPxTx8DELViHmbr9mBQ/Rtijv2V4nFC/CtL3WfCwcGBpk2bYmIi3fvi86Cnp0ejZvUwNjbixpXbug4n24mPiyc+PgEDfbXWdgMDfa7fvpf0/MqN23zdqA3ftenK5NmLCXnnjtb/dfLMRULCwmnWqK7Wdk/vJ7wKDqFi2ZKpPm+p4kU4cfYifgGBaDQaLl+7xWOf51SpUOa95w+PiCSHibEkEkKITKFQ6QOgiX3zdqNGgyY2FlWR4jqKSvc0GkWWfWQ1WaZnQojPScEiLmw/uA4DA32iIl/Tp9MwvB480nVY2Y6JiTElixVh+fqt5M/niKWFGQeOneLWXQ8c7RPntFStVJY6Napib5ebp899WbhiPT2HjGPLinkolcm/sO/+8zBVK5Qhj4211vbjZy5QtWJZ1Go1arX6o+cFGD2oFxNnLuKbZj+hUipR6CmYOGJAUm/GfwWHhLJi/VZaNGmQjn8lIYR4v/jnT4j3f4lR++5E/ToHTUw0ho1borSyIcHcUtfhic+AJBNCpMEjzyc0rfUjOXPmoH6Tb5i5eCLtmnaXhEIHpo8byvjp86ndrD1KpR5FCrrSoE4N3O57AtCwTs2ksgVdnCno4kyDVp25cuM2lcqV1qrrpX8A5y5fZ+7kUcnOc+LsRdr+0DjV5wXYsnMft+95sGTmBGzz5ObazTtMnbsMGytLKpfXPndEZCS9h03AxdmR3l3ap8efRgghPi4+noiZ4zDpOxzzzX+hiY8j9tY13ly7CLIojkgFSSaESIPY2Dh8Hj0D4N5tD4qXKkrH7m0ZP3SajiPLfhwd7Fi/dDZRr6OJjIzC2sqCIeOm42CXJ8Xyee1tMTfLhc8z32TJxN6/jmKWKyc1q1fS2h4Q+Ar3B17UqFIh1eeNjolh4YoNLJw+Lum4Qq7OeDz0Zv3WXVrJRGRkFD0Gj8PE2IiF08ahVslbsxAi88R7PyBscFcUxiagUqEJCyXXzF+J87qv69B0RpMgiVRqZak5E0J8rhR6eugbqD9eUGQYYyNDrK0sCA0L5/zla9T+T0Lwr5f+AYSEhmP9nwnZGo2GvQeO0rjBN8m+zJ88d5FSxYtgmitnqs8bFxdHXFwcev/5ZU+p1CMh4e2tVSMiI+k+aAxqtYrFMydgYKCfpvYLIcT/SxMViSYsFD1be5QuhXhz6ezHDxLZnvz8JdLMxMSY/C5vV95ycspL8RJFCH4VyrNnL3QYWcYaMrYPp/4+j++zl5jkMKbxD/WpWLUsnVv103Vo2dK5S9fQaDQ4OTrg8+wFc5euwdnRgWaN6hEV9Zpla7dQt2ZVrCwtePr8BfOWrcXRwY6qFbUnQV+6dpNnL17yQ+P6yc5x4uwlalXTTk4+dF6AHCYmlCtdnLlL12BgYIBdHhuu3rjDvoN/M6x/N+CfRGLgGF7HxLBw/DAiI6OIjIwCwNzMNMU5HSJjZdf3tewq27zehkYo89gnPdXLbYvSyRVNRBgJgf6oq9REExpCQqAfynz5Me7Sj9jLZ4m7dVWHQYvPhSQTIs1KlynOgUNbk55Pn5m4xOWWzTvp1WO4rsLKcBZWFsxaMgmb3FaEh0Vw3+0hnVv14/yplJfdExkrPCKSBcvX4RcQiGmunNStUY3+PTqiVqmIj4/ngdcj9h08RlhEJDZWFlSpUIa+3Tqgr6/dA7D7zyOUKl6U/Pnyam2Peh3Npas3GTmgR6rP+685k0ayYPl6Rk6aRWhYOHZ5bOjfoyOtmyXetM7tvhe33RKHETRs3UWr/sM712Nvmzvd/k4idbLr+1p2lV1eb5VLIXJNWZj03KRzXwBijh8kcvEM9MwtMfy5D3qm5iQEB/Hm5GFe/75RV+FmCRqNriP4fCg0mi/vz6XSt/94oS+QsdpA1yHoRB7jlO8f8KXzDvXVdQg68frFmY8XSkdHT55j8aoN7NuyMlPP+19GdtV1en5dya7va1GxMboOQSey6+v9uF7ejxf6Alnsybr3+HAv0FDXIbxXkYcHdB2CFpkzIYQQH2BsZMjgXp11HYYQQgiRJckwJyGE+ICqFcvqOgQhhBCZTFZzSj3pmRBCCCGEEEKkiSQTQgghhBBCiDSRYU5CCCGEEEK8I0Ejw5xSS3omhBBCCCGEEGmSqp6Jffv2pbrCJk2apDkYIYQQQgghxOcjVclEs2bNUlWZQqEgPj7+/4lHCCGEEEIIndLIMKdUS1UykZCQkNFxCCGEEEIIIT4zMmdCCCGEEEIIkSZpWs0pMjKSU6dO4ePjw5s3b7T29e/fP10CE0IIIYQQQhc0Gl1H8Pn45GTixo0bNGzYkKioKCIjI7GwsCAwMBBjY2NsbGwkmRBCCCGEECKb+ORhToMGDaJx48YEBwdjZGTExYsXefLkCWXLlmXOnDkZEaMQQgghhBAiC/rknombN2+yYsUK9PT0UCqVxMTEkD9/fmbNmkXHjh1p3rx5RsQphBBCCCFEppCb1qXeJ/dMqNVq9PQSD7OxscHHxwcAU1NTnj59mr7RCSGEEEIIIbKsT+6ZKF26NFeuXKFAgQLUqFGD8ePHExgYyKZNmyhWrFhGxCiEEEIIIYTIgj65Z2LatGnY2toCMHXqVMzNzenVqxcBAQGsXLky3QMUQgghhBAiM2k0iiz7yGo+uWeiXLlySf9vY2PDoUOH0jUgIYQQQgghxOdBblonhBBCCCGESJNP7plwdnZGoXh/F4u3t/f/FZAQQgghhBC6JDetS71PTiYGDhyo9Tw2NpYbN25w6NAhhg0bll5xCSGEEEIIIbK4T04mBgwYkOL2pUuXcvXq1f87ICGEEEIIIcT/7/Tp08yePZtr167h6+vLnj17aNasWdL+Tp06sWHDBq1jvv3220+aE51ucyYaNGjArl270qs6IYQQQgghdCJBo8iyj08RGRlJyZIlWbp06XvL1K9fH19f36TH1q1bP+kcn9wz8T47d+7EwsIivaoTQgghhBBC/B8aNGhAgwYNPljGwMCAPHnypPkcabpp3bsTsDUaDS9fviQgIIBly5alORAhhBBCCCHEh8XExBATE6O1zcDAAAMDgzTVd/LkSWxsbDA3N6d27dpMmTIFS0vLVB//yclE06ZNtZIJPT09rK2tqVmzJoULF/7U6jJEbhMzXYegE36RIboOQSdeRr3SdQg6Ucoyv65D0Im6pbrrOgSdeP3ijK5D0AnPyn11HYJOVHzhoesQdCKnvpGuQ9CJLVfz6joEnein6wA+ICveHO5f06dPZ9KkSVrbJkyYwMSJEz+5rvr169O8eXOcnZ3x8vJi9OjRNGjQgAsXLqBUKlNVxycnE2kJVAghhBBCCPH/GzVqFIMHD9baltZeiTZt2iT9f/HixSlRogQuLi6cPHmSb775JlV1fPIEbKVSib+/f7LtQUFBqc5ghBBCCCGEEJ/OwMCAXLlyaT3Smkz8V/78+bGyssLT0zPVx3xyz4TmPXfxiImJQV9f/1OrE0IIIYQQIkv51FWTvhTPnj0jKCgIW1vbVB+T6mRi0aJFACgUClavXk2OHDmS9sXHx3P69OksM2dCCCGEEEKI7C4iIkKrl+HRo0fcvHkTCwsLLCwsmDRpEj/88AN58uTBy8uL4cOH4+rqyrfffpvqc6Q6mZg/fz6Q2DOxfPlyrSFN+vr6ODk5sXz58lSfWAghhBBCCJFxrl69Sq1atZKe/zvXomPHjvz666/cvn2bDRs2EBISgp2dHfXq1eOXX375pGFTqU4mHj16BECtWrXYvXs35ubmqT6JEEIIIYQQn4uUB/V/fmrWrPneKQoAhw8f/r/P8clzJk6cOPF/n1QIIYQQQgjx+fvk1Zx++OEHZs6cmWz7rFmzaNmyZboEJYQQQgghhMj6PjmZOH36NA0bNky2vUGDBpw+fTpdghJCCCGEEEJXEjSKLPvIaj45mYiIiEhxCVi1Wk1YWFi6BCWEEEIIIYTI+j45mShevDjbt29Ptn3btm0ULVo0XYISQgghhBBCZH2fPAF73LhxNG/eHC8vL2rXrg3A33//zW+//cbOnTvTPUAhhBBCCCEykyYLDifKqj45mWjcuDF79+5l2rRp7Ny5EyMjI0qWLMnx48exsLDIiBiFEEIIIYQQWdAnJxMAjRo1olGjRgCEhYWxdetWhg4dyrVr14iPj0/XAIUQQgghhBBZ0yfPmfjX6dOn6dixI3Z2dsydO5fatWtz8eLF9IxNCCGEEEKITJeQhR9ZzSf1TLx8+ZL169ezZs0awsLCaNWqFTExMezdu1cmXwshhBBCCJHNpLpnonHjxhQqVIjbt2+zYMECXrx4weLFizMyNiGEEEIIIUQWluqeiYMHD9K/f3969epFgQIFMjImIYQQQgghdEaDrOaUWqnumTh79izh4eGULVuWihUrsmTJEgIDAzMyNiGEEEIIIUQWlupkolKlSqxatQpfX1969OjBtm3bsLOzIyEhgaNHjxIeHp6RcQohhBBCCCGymE9ezcnExITOnTtz9uxZ7ty5w5AhQ5gxYwY2NjY0adIkI2IUQgghhBAi0yRosu4jq0nz0rAAhQoVYtasWTx79oytW7emV0xCCCGEEEKIz8D/lUz8S6lU0qxZM/bt25ce1QkhhBBCCCE+A2m6A7YQQgghhBBfqgRZzSnV0qVn4kvUsWtbLt46gpfvdfYf3UqpMsXfW/bHDi3YfWAj9x6d596j82zbszpZ+R59O3HrwWluPThNjz4dtfaVLlucgyd2oFQqM6Qt4uO6df+JO26n8Q9y5/jJ3ZQtW+K9ZQsXKcCmLcu443aasEhvevf5OVmZVq2b4nb/LE+e3WDajDFa+xwd7bl+829y5syR7u34VC07fc++yzs49+gY6/9awVeliqTquHpNv+Gq7xnmrJumtb19zzYcubOPI3f20a5Ha619X5UuyqbDq7PEdd6sYxO2XdjMEc8DLNu/mMKlCn2wfI5cJgyY0o9d17ZzxOsAm06vp2LtCkn763xfmx2Xf2P/3T30Ht9T69g8DrnZdHo9xjmMM6QtKYmMjGLGguXUbd6RsrWa0q7HYO6430/aP2bKXIpVbaD16DF47Afr3LbnT77v0IuKdZtTsW5z2nUfxJkLV7TKzFq0kir1W/LN9z/x5+HjWvsOHz9Dn+ET0q+RqWBUvhgOKybgenYTRR4eIEedyh89JleTmjjvW0Kh27spcG4zttMHojTLmbTfpGpp8h9ZRcEbO7GbPRTUb3+T08thTP4jq1DZ2WRIez5Vdn1fy26f33YVC/Hd2sH8fHUx/Z5uJv+3ZT9Y3qV+OZpuGUHXm8vo4baKFnsn4FhDu80Fm1Wh06WFdLuzgmrj22nty+lgRftTs1HnMEr3tojPkyQTKWjyfX0mTBnOvJnLqF+zJW5377Nl1wosrSxSLF+5Wnn+2HWAVo0706ReO148f8lvu1eSxzbxA6XIVwUZNqovvbsMo0/XYQwb05/CRRPv1aFUKpkxbwIjB08mPj4+09oo3mr+QyOmzRjNjOmLqF61MXfuuLP7jw1YWVumWN7YyIjHj32YOH4WL1/6J9tvYWnO4qXTGTt6Ot836UjrNk2pX7920v55C35hwvhZhIdHZFibUqNuk9oMmtiXVXPX0/7brjxw82Tx1rmYW5p98DhbhzwMGN+b6xdvam13LeJCz+FdGN1zImN6TaLXiG64FM4PJF7no2cOYfrwOTq/zms1rknv8T1ZP38T3Rr0xMvNm9mbZ2D2nnar1Crm/DaLPHnzMKHHZDrU+Jk5w+cR6Ju4NLapeS6GzR7Cr7+sZGi7kdRt/g2Vv6mYdPzAaf1ZOX01URFRmdE8AMbPWMiFKzeYPn4oezb9SpUKZeg2YDR+AW+X865WqRwn921JesyaOOKDdeaxtmJQz5/ZsXYx29csokLZkvQbORlP7ycAnDx7kb+OnmTl/KkM6d2FCTMWEhwSCkB4RCSLVm5g7OA+GdfoFOgZGRLj8Qi/SctSVd6oTFHsZg0hZOcRvBv24ln/aRiWKEieqf0TCygU2M0bTsjWAzxuORjD4q6Yt66fdLzNsJ8J2XqAuBfJ3xcyW3Z9X8uOn99qIwMC3X04NXZDqsrbVSzM0zN32ddxDtsajuX5BXe+WzsEq6/yAWBonoNvZnfl3JTf+KP9TAp9XwWnb0olHV9zaicuTN9ObMTrjGiO+AxJMpGCbr078tvGnez4bS8P73sxcvAkXkdF06Z98xTL9+s+gg1rtnHvrgdeDx8xtP949BR6VPu6EgCuBZxxv/eAc2cucfb0JdzvPcC1gDMAvfr/zMXzV7l1426mtU9o69uvCxvWbWfLpp3c9/BkYP+xvH79mp86tEyx/PXrtxk3Zga7dv5JTMybZPudnfISFhbO7l1/cf36bU6fukjBwi4AtGjZmNjYWPbvO5yhbUqNdj1as3fLfvZvP8CjB4+ZPnwO0a+jadK20XuP0dPTY8rS8aycs5bnT3y19jm5OvLQzYur565z5ew1PN29cHJ1BOCn3m25fukWbrc8MrRNqdGy+w/8tfUAh3Yc5slDH+aNXEB0dAwN29RPsXzD1vXJaZaTsV3Gc/fqPV4+8+PWxdt4uXsDYJvPlsiwSE7sP8n9W/e5cf4WjgUSP5RrN61FXGw8Zw6ezazmER0Tw7FTZxncpwvlShXH0cGOPl3a4+hgx/Y9fyWV01ersbK0SHqY5sr5gVqhZrVKfF2lAvny2uPk6MCAHp0wNjLk1r3E19T7yVPKly5OsSIFaVi3JiYmxjzzfQnAvGVraN2sEbZ5MvcX+8jTVwmYv5HwoxdSVd6odGFin/sTvHEfsc/8eH3NjZBtBzEqkdhzpTTPhcrClOAtf/LG04fwvy+h7+L4z7FFMCxekFcb/siw9nyK7Pq+lh0/v5+cvM3F2TvxPnQ1VeXPTNrM9eV/4X/Lm9DHflyYuYOQRy9xrlMaANN8NsSERfFw/yX8b3nz/II75q72ABRoWpmEuHi8Unmuz5kGRZZ9ZDWSTPyHWq2mRKminDn59sNHo9Fw9tRFypYvmao6jIwNUalVhPzzq5y720OcXZ2wc7DFPq8t+V3z4eHuST6nvLT+8XtmTV2UIW0RH6dWqylVuhgnTpxL2qbRaDh54hwVKpROU51eXo8xMjKkRMmimJubUqZsCe7d9cDMLBdjxw1i6OCJ6RP8/0GlVlG4REEunbmWtE2j0XD5zFVKlP3qvcd1HdyJV0HB/LH1r2T7PD28ccyfl9z2NuRxyI1j/rx43X+EfT47GrduyK8zVmVIWz6FSq2iUPGCXDtzPWmbRqPh2pnrFC1TNMVjqtSrjNt1NwZO7c/uG7+z7tgq2vVti55e4tvns0fPMTAywPUrV3Ka5aRwyUJ4u3uTwzQHXYZ1YuHYxZnStn/Fx8UTH5+Agb5aa7uBgT7Xb99Len7lxm2+btSG79p0ZfLsxYSEhqX+HPHxHDh2ktfR0ZQqVhiAQq75uefxkNCwcO55PCQmJgZHezuu37qL231P2rXM+kuHv77hgTqPFSY1ygGgtDQjZ/1qRJxMHM4V/yqUWL8gTKqVQWFogHG5r4i5/whUSvJM6sPLcYshIUGXTQCy7/uafH6nkUKBfg5DYkIiAQh59BK1kQFWX+XDwMwEmxL5CfLwwcDUmEpDW6S6B0RkHzIB+z8sLM1QqVQEBgRpbQ8ICMLln18jPmbMxCH4vfRPekPzfODNzF8WsG134pepGZMX4PnAm217VjNlwlxq1q7G4JG9iYuNY/yo6Vw6f+1D1Yt0ZGlpjkqlIsBf+27u/v6BFCzokqY6Q0LC6Nl9GCtWzcXI0IBtv+3h72NnWLJsBitXbCKfkwPbfl+JWq1i+tRF/LH3YHo05ZOYWZiiUql4FfBKa/urgGCcXPOleEzJCsVp2rYRP9btnOL+xw+fsGzGSpZtmw/A0ukrePzwCUu3z2fRlF+pXLMi3Yf+TFxsHHPGL+LGxVvp26hUMLUwRalS8iogWGt7cGAwjq55UzzGztGWPFVKc3Tv34zsMBp7J3sGTuuPSq1iw/xNRIRGMH3QLEYvHIGBoT5Hdh3lyqmrDJszhD3r/sDWMQ/T1v2CSqVk/fyNnPrrTIa20cTEmJLFirB8/Vby53PE0sKMA8dOceuuB472tgBUrVSWOjWqYm+Xm6fPfVm4Yj09h4xjy4p5Hxz7/cDrEe16DObNmzcYGxmxcNo4XJwTr5eqFcvy3be1adN1AIYGBkwdOwRjI0N+mbOUKWMGs33PX/y2cx9mZqZMHN4f1/wpX2e69Pq6G8+HzMZ+wUj0DPRRqFWE/32Rl+8Mk3o+YDq5R3cn99geRJy6SsjOI1j1aEXUpdskxLwh37Y5KM1zEbxpH8Gb/9RJO7Lr+5p8fqdNmR4NUZsY8vDPSwDEhEZxdPAK6i7oicpQH49dZ/E5dYfas7tye/0Rcjla893aweiplVyatxuvA1c+cgbxpZNkIp31GdiVJs0b0LJxJ62u4k3rdrBp3Y6k5y3bNCUiIpJrV25x+sqfNKrdGlu7PCxbPYfKperx5k2sLsIX6eTP/Uf4c/+RpOdVq1WgWLHCDBsykZt3TtC50wD8/AI4cWov585dTvbhl9UYmxgxefFYpg6bReir0PeW27XxD3ZtfDvMo1HL+kRFRnHn6l12nd1ChwbdsbG1ZtqvE2lSsRWxn8F1rtDTIzgohLnD55OQkMCDOw+xymNJm56t2DB/EwBnD53j7KG3vwKXrFQCl8L5WTR2CVvObuCXvtN45f+KX/9cyq2LdwgJCsnQmKePG8r46fOp3aw9SqUeRQq60qBODdzuewLQsE7NpLIFXZwp6OJMg1aduXLjNpXKvf+Xa2dHB3atX0p4RCRHTpxlzNS5rF8yKymh6NOlPX26tE8qv2ztFiqVK4VKpWLFhm3s2biMU+cvM3rKHHaszdwem9TQd81L7rE9CFy6lcgz11BZW2Azogu2k/viO3ohAK+vufH4h4Fvj3Gyx7RZbbyb9sPpt1m82vAHEaeukv/Ar0RduUvM/ce6aUwG+NLe1/4rO35+F2xWmQqDvuevLvN5HfS2d9L70FWtYVN2lQpjVcSR0+M28tPZuRzuu5Qo/1Ba7Z/Ei0v3tY79Uui+j/HzIcnEf7wKCiEuLi7ZJDVra8tkv/L8V4++negzsAttmnXF/d6D95YztzBj0Ihe/NCoI6XLlcDb8wmPvH145O2DWq0iv6sTHm4P06U94sOCgoKJi4vD2sZKa7uNjRV+fgHpcg59fX3mzZ9M925DyO/ihEql5NzZywB4eT6iXLmSHDp4/CO1pK+QV6HExcVhYa09KdHC2pwg/+RfAByc7LF3tGPehhlJ2/4d5nPx6Ql+qNaO509eaB1jamFKtyE/0/37vhQrUxQf76c8ffSMp4+eoVKrEodBeXhnQOveL/RVKPFx8VhYm2ttN7cy55V/cIrHBPkHER8bT8I7w1eeePpgmdsSlVpFXGycVnm1vpqBU/szbcAM7J3tUKqU3Lp4G4Bn3s8oUrowF45dTOeWaXN0sGP90tlEvY4mMjIKaysLhoybjoNdnhTL57W3xdwsFz7PfD+YTKjVahwd7AD4qnAB7nk8YPPvfzBheP9kZb2fPOXPw8fZuW4Ju/86QrlSxbAwN+Pb2l8zbtp8IiOjMDHJvBWuUsOqR2teX3fj1epdAMTcf8zL19E4bZtDwPyNxAUkv0by/NIXv+mrUegpMPzKlbCDZ9FExxB1+Q7GFYrrJJnIru9r8vn9aQo0qUTtWV051HMxT8/ee285PX0VNad04ujA5Zg65UZPqceLi4lzpUIevSR3aRceH7uRWWGLLEjmTPxHbGwst2+6Ua1GpaRtCoWCal9X5NqV9w/L6NW/MwOH9aR9ix7cvvn+f5QAk6aNYNWyjfi+8EOpp4f6naUFlSolSj3dL52ZXcTGxnLzxl1q1qyStE2hUFCjZhUuX06fN8fhI/pw7Nhpbt28h1Kph0r59vVWqVU6WVIwLjYOj9sPqFDt7RKCCoWC8tXKcvta8uv3sacPrWt2oF2dzkmP00fOcfXcDdrV6YxfCqvXDJnUj60rd+DvG4CeUg+V6p3rXKlEqcz8t5+42Dju33lAmWplkrYpFArKViuN23W3FI+5e+Ue9k52KBRvJ73lze9A4MvAZIkEwE/923H55BUe3vVET0+JUvX29VWpM7fdxkaGWFtZEBoWzvnL16hdvVKK5V76BxASGo61Zcor3rxPQoImxV9hNRoNk2ctYni/bhgbG5EQn0BsXOLfKu6f/8ZngbkF/6UwMoAEjfbG+H/iVCSf9Gjaoh7xoRFEHL8E/7xvK1T//lcFOrjGIfu+r8nnd+oVaFqZOnO7c7jvUh4fv/nBsuX7N8Pn1G0C7j5GodRD7533ND2VEj0dXeci65CeiRSsWraB+cumcfvGPW5cv0O3Xj9hZGLE9i17AFj46zR8ff2ZMXkBAL0HdGHoqL707Tacpz4vkn4NioyMIipSeznI6jUr4+zixIBeowG4deMuLgWcqVWnGnb2tiTEJ+Dl+SjzGitYsngNy1fO4caNO1y9eovefX7G2NiYzZt2ArBi1RxevPBj0oTZQOKvs4WLuAKgr6/G1i43xUsUITIiCu9/lsn8V6HCrjT/4TuqVfkOgAf3vUhISOCnDq3w9wugYEEXrl+7nYmtfWvLiu1MXDgat1se3Lvpzo/dWmJkbMT+bQcAmLRoDP4vA1k6bQVvYt7gdV/7ugwPTVwC8r/bASp+XQ7H/HmZ0H8qAG43Pcjnmo8qtSuS286GhIR4nnj5ZHALU/b7yl2Mmj+c+7fu437zPi26NsfQyJCD2w8BMGrBCAJfBrJqxhoA/ti4n+87NaXf5D7sXrsHB2cH2vX9kd1r9ySrO18BR2o1qUm3bxPvNeHj5YMmQUPDNvV55R+Mo4sjHrfuJzsuvZ27dA2NRoOTowM+z14wd+kanB0daNaoHlFRr1m2dgt1a1bFytKCp89fMG/ZWhwd7Kha8W2S1aX/SL75ugo/tkicOD3/13VUr1wO29w2REZF8deRk1y5cZsV86YkO/+u/YcwNzOlZrXEL3WlSxRl2drN3LrrzpmLV3FxciRXJtyPQGFsiH4+u6Tn+g65MSiSn/iQcOJ8A7Ae0glVbkt8h88FIOL4JWyn9Mfsx4ZEnrmOytqC3GO68/rWfeL8tecXKS1MserdhidthgKQEBZBjKcPFp2aEXn2OsaVSxL467YMb+P7ZNf3tez4+a02NsDUKXfS81x5rbEq6kh0SCQRL4KoPKIVOfKYc3TQCiBxaFOdeT04M3Ezfje8MLY2BSAu+g1vwrWXezUvYEeBxhXZVj/xPjTBXi/QJGgo2roGUQGhmLvY4ncrc3uYM0tWXDUpq5JkIgX79hzCwsqCoaP7Ym1jxb07HrRv0SNp/Kedgy0J7/x61aFzawwM9Fm1cYFWPXNnLGXezLcT9wwNDZg6awy9Og9Fo0k83veFH+NGTGPekqm8efOGgb1HEx0dk/GNFEl27/oLKysLRo8dRO7cVty57c4PzToldYs7ONhpDXGxtbXh3IW3qxkNGNidAQO7c+b0RRo1+FGr7kWLpzF65FSiohLfoKOjY+jVYzhz5k/CwECfoYMn4OvrlwmtTO7ovuOYW5rRc3gXLK0teHDPk34/DuVVYOJQjjz2ubWu89QyMNRn+NRBjOo5Iek69/cNYPbYBYyfP4rYN7FM6D+NmOjky09mhhP7T2JmacrPQzthYW2Op5sXw38aRXBgCAC57W3QvPN6B/gGMKzdSPpO7M3ao6sIeBnIrjW72bpse7K6h84czLJJvxL9OhqAN9FvmDFoFgOm9kdfX83CcYsJfJnx48jDIyJZsHwdfgGBmObKSd0a1ejfoyNqlYr4+HgeeD1i38FjhEVEYmNlQZUKZejbrQP6+vpJdTx97kvwOys8vQoJYfQvcwgIekVOExMKujqzYt4UqlQoo3XuwFfBrNywjc3L5yVtK160EB3bNKf3sAlYmJsxbeyQDP8bABgVK0C+LTOTnuce0x2AkN1H8R0xH5WNOWo766T9obuPoWdihEX7xuQe2ZX4sEiiLt7Cf/a6ZHXnHteDV2t3ayUZL0bMw27WYMw7NOHVml1E39HdcJfs+r6WHT+/bUrkp/nvb28iWH1C4rwl999Pc2zwSkxym5HD/u2Qt69+rI1SraLm1E7UnNopafu/5d9Ve0YXzk7eQtzrxHbFR8dybPAKakzphFJfxalxG4l8mfIQUZF9KDT//qv4gtibv39pyy+ZX2SIrkPQCWO1ga5D0ImCuex1HYJO5FBmz9f76M2VHy/0BfKs3FfXIehExRe6vyeLLuTUz553VR6ZI21L9n7u+j3drOsQ3utI7ja6DuG96vnprtczJdIzIYQQQgghxDuy3qyurCtLJRORkZHs2LEDT09PbG1tadu2LZaWlh88JiYmhpgY7W5FjSYBhUImBAkhhBBCCJGRdPqNu2jRorx6lTje9OnTpxQrVoxBgwZx9OhRJkyYQNGiRXn06MOTmaZPn46pqanWIzz6w0vACSGEEEIIIf5/Ok0mPDw8kpYJHDVqFHZ2djx58oTLly/z5MkTSpQowZgxYz5Yx6hRowgNDdV65DS0+uAxQgghhBBCvE9CFn5kNVlmmNOFCxdYvnw5pqaJS5TlyJGDSZMm0abNhyfAGBgYYGCgPSFThjgJIYQQQgiR8XSeTPx7I6jo6GhsbW219tnb2xMQkD5368xIfQd1pcF3dXEt4Ex0dDRXL99k2sR5eHk+1nVoIgNUqVqeAQO7U6p0MWxtc9O2dQ/++vOorsPKdB37tqPfmJ78tmoH88Yv1nU4GabT4A50GtxBa5uPpw8danbWUUSJ4uPjWbZmC38eOU5gUDDWVhY0a1iXHp3aJr2vjpkylz8OHtM6rmrFslr3hggNC2favGWcPHcJPT096tSsyqgBPTE21l5V58qN24ycPJu/92xK1bkDXwUzf9lazl++TnhEJGVLFWP0oF7ky2ufdN6lqzdx/vJ1fP0CMDc3pXb1yvTr1oGcOUwy8k+nxah8MSy7/oDhV66oc1vytNcvRBy7oFVG3yUvNsN+xrhCcRRKJTGePjzrO5U436z/+ZRa2fV9Lbt8fttVLESZHo2wLuFMjtzm/NV1Pt6HryXtd6lfjmI/fYN1cSeMzHOy9dvRBLrp5l5A4vOj82Tim2++QaVSERYWxv379ylWrFjSvidPnnx0AnZWUKlKeTas3srNG3dQqVSMHDeA33avomalJryOev3xCsRnxcTEmLt33Nm08Xd+27Zc1+HoRNGShWn+UxMe3PPUdSiZ4pHHI4a0HZ70PD4uXofRJFqz+Xe27/2LqWOH4Oqcj3seDxg7dT45cpjQvmXTpHLVKpVjyuhBSc/VarVWPSMmzSIg8BWrFkwjLi6OsdPmM3HWImZNHKFV7sSZi9SsWjFV59ZoNAwYORmVSsWimePJYWzCxu276TpgNH9sWYGxkSH+gUH4B75iaN+u5HdyxNfPn8mzlxAQGMT8qWMz8C+nTc/IkBiPR4TuPILDsnHJ9qsd85Bv62xCdx4hYNFmEiKiMHDNhyZGN/dJySjZ9X0tu3x+q40MCHT3wW3HaRqtGphsv8rYgBeX7/Nw/yW+md018wPMguSmdamn02RiwoQJWs9z5NC+I+r+/fupXr16ZoaUJu1b9tB6PrD3GO54nqVEqaJcOn/tPUeJz9XRI6c4euSUrsPQGSNjI35ZOp6pQ2fRZWBHXYeTKeLj43kVkLVuzHTzrju1qleiRpUKANjb5ubA0VPccdO+w7a+Wo2VpUWKdXg99uHsxatsW72QYkUKAjB6UC96DR3P0D5dsbF++2POibMXGTO4d6rO/eTpc27d82DvpuW45s8HwLihfanZ+EcOHD1Jiyb1KZDfiQXT3iYNjg529O/ekZGTZxEXF49KpUyPP9NHRZ6+SuTpq+/dbz2oI5GnruI/a23Stlifl5kRWqbKru9r2eXz+8nJ2zw5+f67kt/ffQ6AnA4y51R8uiyVTPzX7NmzMymS9JUrV04AQoJDdRyJEOlvxPRBnPv7ApfPXMs2yYS9sz07r27jTUws9667sWr6Gvxf+Os0plLFirBz30Ee+zzDydEBj4feXL99j+H9ummVu3LjNl83akOunDmoULYk/bt3xMw0FwC37rqTK2eOpEQCoFK50ujpKbjt5kGdGlUB8PR+wqvgECqWLZmqc7+JjQVAX/9tL4ienh5qfTU3bt+jRZP6KbYpPCKSHCbGmZZIfJRCQY6a5Xm1ehd51/6CYVEXYp/5Ebh8R7KhUOLLIJ/fQnw6nQ9z+tIoFAomTR/B5YvXue+ePYaAiOyjXtNvKFy8IB0adNd1KJnG7YY7MwbN5qn3UyxtLOk46CcW7Z7Pz9905XWk7oZBdP2pFZFRUTT+sTtKPT3iExLo370j331bO6lM1UplqVOjKvZ2uXn63JeFK9bTc8g4tqyYh1KpJDAoGAszU616VSolpjlzEvjqbU/M8TMXqFqxbNIQqY+d2zlfXmxz27BwxXrGD+uHsZEhG7fvwc8/kICgVym2JzgklBXrt9KiSYP0/lOlmdLSDGUOYyy7tyRg/kb8Z68jR/WyOCwdg89PI4m6fFfXIYp0JJ/f4l0JMsop1SSZSGfT5oylUJECfN/gJ12HIkS6ym1nw5Bf+tOn9WDefGHjxT/k8okrSf/v7f4I9xvubLv4G7Ua1+DAtkM6i+vQ8dP8eeQEMycOx9U5Hx4PvZm5cAU2VhY0bVgXgIZ1aiaVL+jiTEEXZxq06syVG7epVK50qs914uxF2v7QONXnVqtULJg2lvHTF1C1QSuUSj0qlStN9Url0KRQf0RkJL2HTcDF2ZHeXdqn9U+S7hR6id8mwv++yKv1ewGIcffGqEwRzNo2lGTiCyOf30KkjSQT6WjKrDHU+bYGzRt2xPeFn67DESJdFS5RCEtrCzYfWZ20TaVSUbpSSVr93Jwq+b4hISErroCdviLCInnm/Qx7J3udxjF36Rq6tm+VlDAUdHHG96U/qzftSEom/iuvvS3mZrnweeZLpXKlsbI051WI9nCOuLh4QsPDsbIwByAg8BXuD7yS5kek9txfFS7Arg1LCY+IJDY2FgtzM9p2G8hXhQtonS8yMooeg8dhYmzEwmnjUKuyzsdSXHAYmtg4Yjy1V7WJ8XqKcdmvdBSVyAjy+S1E2mWdd+3P3JRZY6jf6BtaNu7EU5/nug5HiHR35cxVWtfUXiJ1/IJRPPH0YcOSLdkikQAwMjbEzsmWI7uDdBpHdHRM0i/n/9LT0yNBk9Jv/4le+gcQEhqO9T8TsksWK0JYeAT3PB4mfcm/dO0mCQkaShQtDMDJcxcpVbwIpv+MJf/Uc/+7zOuTp8+55/GQvl3f/uobERlJj0FjUeurWTxzAgYG+p/yJ8h4sXG8vvMAA2cHrc0GTvbE6njOjEg/8vktUpIgqzmlmiQT6WDanHE0a9GQzj/2IyIiCmubxNUQwsPCiY6O0XF0Ir2ZmBiT3yVf0nMnp7wUL1GE4FehPHv2QoeRZayoyNd43X+ktS06KpqQ4NBk278kvcZ25/yxi/g988MytyU/D+lIQnwCf+89odO4alatyKoN27DNbYOrcz7cH3iycftuvm9UD4CoqNcsW7uFujWrYmVpwdPnL5i3bC2ODnZUrVgGABcnR6pVKsfEmQsZP6wfsXFxTJv/Kw3q1EhayenE2UvUqlbpk84NcPj4GczNTLHNbc1D78fMWLCc2tUrU7ViWSAxkeg+cAyvY2JYOH4YkZFRREZGAWBuZopSmTmTsBXGhujns0t6ru+QG4Mi+YkPCSfON4BXq3dhv2AkUVfuEHnxNjm+LkuO2hV50n7EB2r9/GTX97Xs8vmtNjbA1Cl30vNcea2xKupIdEgkES+CMDAzIaedJSa5E3skzV0S7/sVFRBKVIBMRhcfptBoPvAz1mfK3jxzu5+fB99Lcfug3mPYsXVvpsXhFxmSaefKSozVBh8vlI6qVa/IgUNbk23fsnknvXoMT+GIjFEwl26H2QCs2LWI+/ceZupN63IoM/f1Hr90DCUqFieXeS5CX4Vy5/JdVs9ay4snvpkax9GbK7WeR0ZGsXjVRv4+fYFXwSFYW1nQsG5Nev38I2q1muiYGPqPnIzHAy/CIiKxsbKgSoUy9O3WIWkIEyTePG7qvGWcPHsJPT0FdWpWZfTAXhgbGxH1OprqDVuzZ9OvODrYpfrcAJt//4N1v+0k6FUI1pYWNKn/DT1/bpu0//L123Tul/IX8sM712Nvm/jFx7Ny33T9O/6XcYXi5NsyM9n2kN1H8R0xHwDTFnWx6tEKVR4r3jx6RsDCLUT8fTFD46r4wiND6/+vrPK+llPf6OOF0lFW+fwemSP1c5jSwr5SEZr/PibZdvffT3Ns8EoKt6xO3Xk9ku2/NG83l+fvzrC4+j3dnGF1/7/+yPOjrkN4r6Yvf9N1CFokmfiCSDKRvWSFZEIXMjuZyCr+m0xkyjlPnmPxqg3s25L55/5XRicTWVVmJxNZRWYnE1lFRicTWVVWTib2ZuFkolkWSyb0dB2AEEKIrMnYyJDBvTrrOgwhhBBZmMyZEEIIkaJ/5zcIIYQQ7yPJhBBCCCGEEO/IHusTpg8Z5iSEEEIIIYRIE0kmhBBCCCGEEGkiw5yEEEIIIYR4R4JCblqXWtIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHjHF3dH5wwkPRNCCCGEEEKINJFkQgghhBBCCJEmMsxJCCGEEEKId8hN61JPeiaEEEIIIYQQaSLJhBBCCCGEECJNZJiTEEIIIYQQ70iQe9almvRMCCGEEEIIIdJEkgkhhBBCCCFEmsgwJyGEEEIIId6RgIxzSi3pmRBCCCGEEEKkiSQTQgghhBBCiDSRYU5CCCGEEEK8Q6PrAD4j0jMhhBBCCCGESBNJJoQQQgghhBBpIsOchBBCCCGEeIfctC71pGdCCCGEEEIIkSZfZM9EmZzOug5BJ+6rXuo6BJ2IjHut6xB04maQt65D0InBdl/rOgSdcCrQWNch6MTjh/t1HYJORNlV13UIOpFT30jXIejEIL8Tug5BJ/rpOgCRLr7IZEIIIYQQQoi0StB1AJ8RGeYkhBBCCCGESBNJJoQQQgghhBBpIsOchBBCCCGEeIfctC71pGdCCCGEEEIIkSaSTAghhBBCCCHSRIY5CSGEEEII8Q65aV3qSc+EEEIIIYQQIk0kmRBCCCGEEEKkiQxzEkIIIYQQ4h1y07rUk54JIYQQQgghRJpIMiGEEEIIIYRIExnmJIQQQgghxDtkmFPqSc+EEEIIIYQQIk0kmRBCCCGEEEKkiQxzEkIIIYQQ4h0auWldqknPhBBCCCGEECJNJJkQQgghhBBCpIkMcxJCCCGEEOIdsppT6knPhBBCCCGEECJNJJkQQgghhBBCpIkMcxJCCCGEEOIdMswp9aRnQgghhBBCCJEmkkwIIYQQQggh0kSSifdo2KERq8+tYdeD3cz5Yy4FShb8YHmTXCb0/KUnG65uZPfDPSw/uYKytcol7a/RrCZrL65j651tdBnXVetYGwcblp9cgVEOowxpy6do17klx6/t487Tc/x+aD0lSn/13rL1GtVi19GNXPU8wc3HZ/jjxBaatmyoVaZz7/ZccDvCBbcjdO7VTmtfiTJfsfvYJpRKZYa05VN07NqWi7eO4OV7nf1Ht1KqTPH3lv2xQwt2H9jIvUfnuffoPNv2rE5WvkffTtx6cJpbD07To09HrX2lyxbn4IkdWaLd2VXln+oy8uwipt7fQN+9v5C3pMt7y+qplNTp35wRpxYw9f4GBh6cQcEaJbXKlG5aldHnlzDx1iq+G9tea5+5gxXDjs/DIAv8+/7Sr/PIyChmLFhO3eYdKVurKe16DOaO+/2k/cWqNkjxsXbLzvfWuXTN5mTlG7ftplVm1qKVVKnfkm++/4k/Dx/X2nf4+Bn6DJ+Qvg0VH/SlX+cic2iy8COrkTkTKajWuDpdx3Vl6eilPLh5nyZdmjJ582R61uxBaFBosvIqtYpftvxCSGAoM3pOJ+hlEDb2NkSERQKQyzwX/Wb1Y8GQBfg9ecn49RO4ff4WV/6+AkCvKb3ZMGM9ryNeZ2o7/6ths7qMmjyI8cOmc+vaXTr1aMuaHYv5tvIPvAoMTlY+JDiM5fPX4v3wMW9iY6lVrzrTF40nKPAVZ09cpFBRVwaM6EmPdgNRKBSs2DKfsycv8sDdC6VSyeQ5oxk3eCrx8fE6aO1bTb6vz4Qpwxk5eBI3rt2ha8+f2LJrBV+X/46gwFfJyleuVp4/dh3g6qWbRMfE0GdAF37bvZLalZvy0tefIl8VZNiovnRs0weFAtZvW8apE+fxcHuIUqlkxrwJDB84Ueftzq5KfleJxmN/YvfYNfjc8KR65wZ02TiS2bWHEBkUlqz8t0NbUaZZNXaNXIW/1wsK1ihBxxWDWfrDBF7ce4yxeU5azOzOjqG/EuTjT+e1w/E6fw/34zcA+P6XzhycuZUYHf/7zg7X+fgZC/H0fsz08UOxsbJk/+HjdBswmj+2rCC3tRUn923RKn/m4lXGT19A3ZpVP1ivq3M+Vi+clvT83S+OJ89e5K+jJ1k5fyo+z14wbtp8qlYsi7mZKeERkSxauYHVC6alVK3IANnhOhciq5GeiRQ069qMw1sP8/fvx3j68CnLRi0l5nUMdVvXTbF8ndZ1yWGWk6ndpuB+1R3/Z/7cvXSXx+6PAMjtmIeosCjO7j/Dw9sPuXPhNg6ueQH4usnXxMXFceHQhUxr3/v83LMdOzbvZffW/Xg9eMT4odOJfh1Nix+bpFj+8vlrHD1wEq+Hj3n6+DkbV27jvpsnZSuWAiB/ASfuuz3k4tmrXDhzhftunuQv4ARA174/ceXCde7cdMuk1r1ft94d+W3jTnb8tpeH970YOXgSr6OiadO+eYrl+3UfwYY127h31wOvh48Y2n88ego9qn1dCQDXAs6433vAuTOXOHv6Eu73HuBawBmAXv1/5uL5q9y6cTfT2ie0Ve/aiEvbjnP191P4ez5n95g1xL5+Q/lWNVMsX/b76hxfuhePkzd59dSfi5uP4XHiBl93bQSApaMN0eFR3PrzIs9ue+N10Q0bV3sASjWpQnxcPHcPX8ms5r3Xl36dR8fEcOzUWQb36UK5UsVxdLCjT5f2ODrYsX3PXwBYWVpoPU6cuUiFMiXIa2/7wbqVSqXWceZmpkn7vJ88pXzp4hQrUpCGdWtiYmLMM9+XAMxbtobWzRphm8cm4xoutHzp17kQWZEkE/+hUqtwLe7KrbM3k7ZpNBpunr1JoTKFUzymYp2KeFzzoOeUXmy8toklR5fSsk9L9PQS/7wvHj/HwMiA/F/lJ4dpDgqULMhj98eYmJrQbmh7VoxbnhlN+yC1WsVXJQtz/tSlpG0ajYbzpy9TqlyJVNVRuXp5nF3yceVC4i+yD9w8cXJxxNY+N3YOeXByceShuxd5nexp3rYxC6b9miFt+RRqtZoSpYpy5uTbZE6j0XD21EXKli/5gSPfMjI2RKVWERKS2Gvl7vYQZ1cn7Bxssc9rS37XfHi4e5LPKS+tf/yeWVMXZUhbxMcp1Ursiznjee7th79Go+HhubvkK1Mg5WP0VcTFxGpti42Oxal8IQACH71EbaiP3VdOGJma4FAiP74ePhjlMqHe4JbsHb8u4xqUStnhOo+Piyc+PgEDfbXWdgMDfa7fvpesfOCrYE6fv0zz7779aN0+z55Tq0k76rf8mRETZ+L70j9pXyHX/NzzeEhoWDj3PB4SExODo70d12/dxe2+J+1apvxjjEh/2eE6F5knQZF1H1mNDHP6j1wWuVCqlAQHhmhtDwkMwcHFIcVj8jjmpkSVEpzce5JJnSZi62RHrym9UKpVbFuwlcjQSOYPns+g+YPRN9Tn+K7j3Dh9nX6z+vPXhj/JnTc3Y9eMQ6VW8dv83zh/4FwmtFSbuYUZKpWKwADtbuBA/1fkd3V673E5cppw5s5B9PX1SYiPZ+KImUkJidfDx8ybuox1O5cBMHfKUrwePmb9zqXMnrSIarUr029Yd+Li4pgyZg5X/0lCMpOF5b/tDtLaHhAQhMs/vz59zJiJQ/B76Z/0Aeb5wJuZvyxg2+5VAMyYvADPB95s27OaKRPmUrN2NQaP7E1cbBzjR03n0vlr6dso8V4m5on/vsMDtYcrRgSEYuNil+IxD07fpnrXRjy67EHQEz9cqxajWP3yST8WvA6LZPvQX2k9txdqQ32u7z7Dg9O3aTGzO+c3HsEirw2dVg9DqVJydMFO7hy8nOHt/K/scJ2bmBhTslgRlq/fSv58jlhamHHg2Clu3fXAMYWeh30Hj2FsbESdGh8e4lSiaCGmjBmCk6MDgUGvWLZ2Cx16D2Pvpl8xMTGmasWyfPdtbdp0HYChgQFTxw7B2MiQX+YsZcqYwWzf8xe/7dyHmZkpE4f3xzV/voz6E2R72eE6FyIrkmQiHSj09AgNCmHpyCUkJCTgdccLy9yWNO/ZnG0LtgJw8fAFLh5++2tJsYrFcC7ixMrxK1hxZiVz+s4mOCCYufvmce/S3RTnZmRFkRFRNK31IyYmxlSuXp5Rkwfx9PFzLv/zhrptwy62bdiVVP771o2IjIjixtU7HL6wix/qdSCPrQ3zV06jdtkmxL6Jfd+psqQ+A7vSpHkDWjbuREzMm6Ttm9btYNO6HUnPW7ZpSkREJNeu3OL0lT9pVLs1tnZ5WLZ6DpVL1ePNZ9bu7GTfpA38MKMbQ/+ei0aj4dUTP67+fkprWNS9w1e5d/hq0vP8FYtgW9iRPyasZ8SpBfzWfzHhASH03TsF78seKc7NyMo+l+t8+rihjJ8+n9rN2qNU6lGkoCsN6tTA7b5nsrJ7/jzCd/VqYWCg/8E6q1cun/T/hVydKV60EPV+6Mih42f4oXFir0afLu3p0+XtxPtla7dQqVwpVCoVKzZsY8/GZZw6f5nRU+awY+3idGqtSG+fy3UuRFYjycR/hL0KIz4uHnMrM63tZlZmBAckn4QMEOz/iri4eBIS3t7i5JnnUyxsLFCpVcTFxmmVV+mr6DW1F/MGzsPWyRalUsndS4nDLl48ek7B0oW4cixzf70MfhVCXFwcVtYWWtutbCwI8A96z1GJXcg+j54B4H73AS4FnekxsFNSMvEucwtT+g7txo9NulOyTDEee/nwxPspT7yfolapcHZx5IG7V/o27CNeBf3bbkut7dbWlgT4B37w2B59O9FnYBfaNOuK+70H7y1nbmHGoBG9+KFRR0qXK4G35xMeefvwyNsHtVpFflcnPNwepkt7xIdFBif++85pZaq1PYe1KeEBISkf8yqcjd3noTJQY2yWgzC/YBqMbEuQj3+K5ZX6Kpr90pntg5Zi6ZQHPaUe3pfcAQh85ItjKVfc/76eru36mOxynTs62LF+6WyiXkcTGRmFtZUFQ8ZNx8Euj1a5azfv8sjnGbMnj/rkc+TKmYN8ee3xefYixf3eT57y5+Hj7Fy3hN1/HaFcqWJYmJvxbe2vGTdtPpGRUZiYGKepfeLDsst1LjKH3LQu9WTOxH/ExcbheceTElXfjq9UKBSUrFqS+9c9UjzG7ao7tvlsUSjeDmSzy29PkF9QskQCoHW/Nlw7eR2vu17oKfVQqt6uDKJUqVDqZf7LEhsbx71bHlT+ukLSNoVCQeXq5bl59Xaq61Ho6aGvn/IvfaN/GcL6FVvx8/VHqdRDpX6byypVSp0srRcbG8vtm25Uq1EpaZtCoaDa1xW5duXWe4/r1b8zA4f1pH2LHty+mXw89rsmTRvBqmUb8X3hh1JPD/V/260nSwpmlvjYeJ7ffYRrlWJJ2xQKBa5VvuLJ9Q9/AYiLiSXMLxg9lZLi9SvgdvRqiuW+6fs9D07d4vm9x+gp9dB799+3WomeUhf/vrPXdW5sZIi1lQWhYeGcv3yN2tUrae3f/edhihYqQOEC+T+57qio1zx97ou1lUWyfRqNhsmzFjG8XzeMjY1IiE8gNi7xMyDun//GJ8hXlIyS3a5zIbIK6ZlIwd7Vexk0dxCedx7y4OYDmnZpiqGxIcd2HANg0PzBBL0MYuPMDQAc3HSA7zp+R7eJ3flz/X7snO1o2aclf67bn6zuvAXyUr1xdQY06A/AM89naBISqNu6LsEBwTi4OPDglm5+1Vi3fAszF0/k7k03bl+/R8ceP2JkbMSurYntmLVkEn4v/Zk7ZSkAPQZ04s5Nd54+foa+vpoadarStGVDJg6fnqzuKjUq4uTiyPC+ieut377hRn7XfHz9TRVs7XKTEJ+At+eTzGvsO1Yt28D8ZdO4feMeN67foVuvnzAyMWL7lj0ALPx1Gr6+/syYvACA3gO6MHRUX/p2G85TnxdY21gBiWvcR0VGadVdvWZlnF2cGNBrNAC3btzFpYAztepUw87eloT4BLw8H2VeYwVnVv9Fq7m9eHbHm6c3PanWpQH6xgZc/f0UAK3n9iLUL5hDs7YBkLeUC6a5LXjh9oRcecypO7AFCj0FJ1ck//dt42pPye8qs6BR4i/e/p7P0SRoKN+qJuEBoVi72PH0Vub2vv0rO1zn5y5dQ6PR4OTogM+zF8xdugZnRweaNaqXVCYiMpIjJ84wtG+3FOvo0n8k33xdhR9bJE6cnr1kFTWrVsQuT278A4NYunozSqUeDevUSHbsrv2HMDczpWa1xC+zpUsUZdnazdy6686Zi1dxcXIkV84cGdBy8a/scJ0LkdVIMpGCs/vPYGphSrvB7TG3NsfbzZsJP40n5J9J2dZ21mje+XUp0DeQ8T+Np+v4riw+vIQgvyD2r93Hrl93Jau774y+rPllNTGvYwB4E/OGBUMW0POXXqj11awYv5xXfu8fVpSRDuw9ioWlOf1H9MTaxhL3uw/o0rofQf9MyrZ1yEOC5m27jYyNmDhrBHlsbYiOjsH74WOG9R7Hgb1Hteo1MDRg/IzhDOo2Co0m8XYrfr7+/DJ6NtMXjedNTCwj+k0gJjom8xr7jn17DmFhZcHQ0X2xtrHi3h0P2rfokTSJz87BloSEt7eJ6dC5NQYG+qzauECrnrkzljJv5rKk54aGBkydNYZenYcmtdv3hR/jRkxj3pKpvHnzhoG9RxOto3ZnV7f+vIiJRS7qDWpBTmszXrg/YU3HGUT8MynbzN4q6fUCUBvo8+3QVlg42vAmMgaPEzfYPmgZ0WFRyer+YXpX/pyyidh//n3HxcSyY+ivNJv8MyoDNX+MX0+YX8rDJTNadrjOwyMiWbB8HX4BgZjmykndGtXo36MjatXbj7qDx06h0UDDujVTrOPpc1+CQ9/OafHzD2T4hJmEhIVhYWZK6RJfsWXFfCzMzbSOC3wVzMoN29i8fF7StuJFC9GxTXN6D5uAhbkZ08YOSdf2iuSyw3UuMof0IaaeQvPup+YXorHjd7oOQSfuv36p6xB0IjJOtzcD0xW/yBBdh6ATg+2+1nUIOrElNPXDDb8kjx8m7wHKDozsqus6BJ3IbWKm6xB0Iru+n8e9ea7rEN5rrmP7jxfSkSE+m3UdghaZMyGEEEIIIYRIE50mE9evX+fRo7fjCzdt2kTVqlXJmzcv1apVY9u2bR+tIyYmhrCwMK1HvEZuay+EEEIIIdJGk4UfWY1Ok4mff/4ZL6/EyYirV6+mR48elCtXjjFjxlC+fHm6devG2rVrP1jH9OnTMTU11Xp4hulmgqMQQgghhBDZiU4nYD98+JACBQoAsGzZMhYuXEi3bm9X2ChfvjxTp06lc+fO761j1KhRDB48WGtbm69aZ0zAQgghhBBCiCQ6TSaMjY0JDAwkX758PH/+nAoVKmjtr1ixotYwqJQYGBhgYGCgtU2pkHWehRBCCCFE2iQoPl5GJNJpMtGgQQN+/fVXVq9eTY0aNdi5cyclS769WdyOHTtwdXXVYYSpZ5Hbkk6jOlG2VlkMjAzwfezLwqEL8LztqevQMkzbTj/QtlMLHBxtAXjo4c3Suas5/fd5HUeWsfoO6kqD7+riWsCZ6Ohorl6+ybSJ8/DyfKzr0EQGMTAxpN6QVhSrV44cVqY8v/eYfZM28Oy2t65DyzBZ9TqPjIxi8aqN/H36Aq+CQyhc0IWRA3tQvEghAJau2cyhY6d46R+AWq2maCFX+nfvSImvCier682bN7TtNoj7nt7sXLeEwgVdtPZfuXGbkZNn8/eeTR89L8CYKXP54+AxrTqqVizLinlTkp4/9nnG3KVruHHHjdjYWAq6OtOvawcqlC2JyHxZ9ToX4nOi02Ri5syZVK1alRo1alCuXDnmzp3LyZMnKVKkCPfv3+fixYvs2bNHlyGmiompCbN2z+LOhdtM7DCRsFeh2DnZEREaoevQMtTLF/7MnbKEx94+KFDwfZvvWLZxLs1qt8Pz/pf7JatSlfJsWL2VmzfuoFKpGDluAL/tXkXNSk14HZU9l6n90rWY2Z3cBfOybfAywvyCKfN9NbptHsPcukN1dt+IjJZVr/PxMxbi6f2Y6eOHYmNlyf7Dx+k2YDR/bFlBbmsrnPLaM3pwbxzs8hAT84aN2/fQfdAYDmxfk+zeEHOXrcXGyoL7nim/X504c5GaVSum6rz/qlapHFNGD0p6rlartersM3wijg52rFk0A0MDfTbt2Euf4RM4uGMtVpbJ76otMlZWvc6F+JzodAK2nZ0dN27coHLlyhw6dAiNRsPly5c5cuQIDg4OnDt3joYNG+oyxFRp0asFgb6BLBy6kIe3HuD31I8bZ27w8smXfd+HE0fOcOrYOZ54P+Wxtw/zpy0jKjKKUuWK6zq0DNW+ZQ92bN3LAw8v3O7eZ2DvMTjktaNEqaK6Dk1kAJWBmmL1K3Bg+m88uuxB0BM/ji7YRdCTl1RuX1fX4WWYrHidR8fEcOzUWQb36UK5UsVxdLCjT5f2ODrYsX3PXwA0qleLyuVLk9feFtf8+RjevxsRkVE88NIeMnvmwhXOX77O0L5d33u+E2cvUqtapVSd91/6ajVWlhZJD9NcOZP2BYeE8uTpc7q2b0UhV2fy5bVnUM+feR0dw0PvJ+n4lxKplRWvc5E1JGThR1aj8ztgm5mZMWPGDGbMmKHrUNKsQt2K3Dh1nRG/jqRYxWIEvQziwKYDHNl6WNehZRo9PT0aNKmDsbERN65kr5tr5frny0JIcKiOIxEZQalSolQpiYt5o7U9NvoNTuULveeoL09WuM7j4+KJj0/AQF/7134DA32u376XrHxsbCy//3GQnDlMKOSaP2l74KtgJs5cyMLp4zE0NEzxXJ7eT3gVHELFsiV58yY21ee9cuM2XzdqQ66cOahQtiT9u3fEzDQXAGamuXB2dGDfob8pUsgVfbWaHX8cwMLcjKKFPo8hvV+6rHCdC/G50Xky8SXIkzcPDdo3ZO/qvfy+ZAcFShag+6TuxMXGcnzncV2Hl6EKFnFh+8F1GBjoExX5mj6dhuH14MOT5r8kCoWCSdNHcPnide67f7nzY7KzmMhoHl97wDf9m+Pv+YLwwBBKNalKvjIFCXr8Zfc+/iurXOcmJsaULFaE5eu3kj+fI5YWZhw4dopbdz1wtLdNKnfy3CWGTZhBdHQM1pYWrFwwFXMzUwA0Gg1jp86jVbNGFCtSkOe+fime6/iZC1StWBa1Wo1arU7VeatWKkudGlWxt8vN0+e+LFyxnp5DxrFlxTyUSiUKhYJVC6fRf+QvVKzbHD09BRZmZqyY94tWD4bQjaxynQvxuZFkIh0o9BR43vZk06yNAHjf8yZfoXw0aNfwi08mHnk+oWmtH8mZMwf1m3zDzMUTade0e7ZJKKbNGUuhIgX4vsFPug5FZKBtg5bSanZPxl5eRnxcPM/vPuLmvvPYF3fWdWiZIitd59PHDWX89PnUbtYepVKPIgVdaVCnBm733375q1CmJLvWLyU4JJSd+w8xdNx0flu1AEtzM7bs3EdkVBRdf2r1wfOcOHuRtj80/qTzNqxTM+n/C7o4U9DFmQatOnPlxm0qlSuNRqNh6txlWJqbsmHZbAwNDNi1/xB9h09k2+pFWFvJnAldykrXudC9rHhzuKxKp3MmvhTB/sE8feijte3pw6dY21vrKKLMExsbh8+jZ9y77cHcKUvxuPeAjt3b6jqsTDFl1hjqfFuDlo1/xvdFyr9uii/DKx9/lreezJginZhWuS9Lmo1DqVbyysdf16FluKx2nTs62LF+6WwuH9vDsd2b2LZ6IXFx8TjY5UkqY2xkiKODHSWLFeGXUYNQKpXs3p847PTytVvcuutBmVpNKPl1Ixq2TryPUeuu/Rn9yxwAAgJf4f7AixpVKnzSef8rr70t5ma58HnmC8Clazc5df4ysyePpEyJryhayJVxQ/tiYGCQbBUokbmy2nUuRHo5ffo0jRs3xs7ODoVCwd69e7X2azQaxo8fj62tLUZGRtSpU4eHDx9+0jkkmUgH7lfdsHdx0Npmn98e/2df/heN/1Lo6aFvoP54wc/clFljqN/oG1o16cxTn+e6DkdkktjXMYQHhGCUy4SCX5fA7ehVXYeUobLydW5sZIi1lQWhYeGcv3yN2tUrvbdsQkICb2JjARg1sCe7Nixl5/rEx7LZkwGYM2kU/Xt0BODkuYuUKl4kxaFHn3Lel/4BhISGY/3PKk3R0TEA6Cm0P3r1FAoSErLitMrsIStf50L8vyIjIylZsiRLly5Ncf+sWbNYtGgRy5cv59KlS5iYmPDtt98SHR2d6nPIMKd08MfqP5i1ZzYt+7Tk7J9nKViqIN/+WJ8lI5foOrQMNWRsH079fR7fZy8xyWFM4x/qU7FqWTq36qfr0DLUtDnjaNaiIZ1/7EdERBTWNonLQoaHhSd9WRBfloJflwCFggCvF1g55aHR6B/x93rBld9P6Tq0DJNVr/Nzl66h0WhwcnTA59kL5i5dg7OjA80a1SPqdTQrN2yjVrWKWFtZEBwSxtbd+/EPDOLbWtUBsM1jo1WfsZERkNiLkMcmsTf5xNlL1KpWKdXnBYiKes2ytVuoW7MqVpYWPH3+gnnL1uLoYEfVimUAKFmsCLly5mD0lLn0/PlHDA302bnvEM98/fi6ivZNW0XmyKrXudC9hC9koFODBg1o0KBBivs0Gg0LFixg7NixNG3aFICNGzeSO3du9u7dS5s2bVJ1Dkkm0sHD2w+Z1n0qHUZ0pM2Atvg99WPVpFWc2ntS16FlKAsrC2YtmYRNbivCwyK47/aQzq36cf7UJV2HlqE6dkn8x7Xrrw1a2wf1HsOOrXt1EJHIaIY5jWkwvA2meSyICo3gzsHLHJ6znYS4eF2HlmGy6nUeHhHJguXr8AsIxDRXTurWqEb/Hh1Rq1QkxCfw6MlT9h08RnBoKGa5clGsSEE2LJuNa/58qao/6nU0l67eZOSAHqk+L4CeUo8HXo/Yd/AYYRGR2FhZUKVCGfp264C+vj4A5mamLJ/7C4tWbqBL/5HExcXh6pyPxTPGU7hA/mSxiIyXVa9zIT4kJiaGmBjtZNfAwAADA4NPqufRo0e8fPmSOnXqJG0zNTWlYsWKXLhwIdXJhEKj0XwZqdc7Gjt+p+sQdOL+6+yxssx/RcZlzxsL+UWG6DoEnRhs97WuQ9CJLaHZa8nlfz1+uD9Tz3f05DkWr9rAvi0rM/W8/2VkV12n59eV3CZmug5BJ7Lr+3ncm6w7rGxqvna6DuG9Yn8uwKRJk7S2TZgwgYkTJ37wOIVCwZ49e2jWrBkA58+fp2rVqrx48QJb27cr07Vq1QqFQsH27dtTFY/0TAghhBD/MDYyZHCvzroOQwihY1l5FtOoUaMYPHiw1rZP7ZVIT5JMCCGEEP+oWrGsrkMQQogPSsuQppTkyZO4Gp2fn59Wz4Sfnx+lSpVKdT2ympMQQgghhBDZjLOzM3ny5OHvv/9O2hYWFsalS5eoXLlyquuRngkhhBBCCCHe8aVMKI6IiMDT8+3NNR89esTNmzexsLDA0dGRgQMHMmXKFAoUKICzszPjxo3Dzs4uaV5FakgyIYQQQgghxBfo6tWr1KpVK+n5v3MtOnbsyPr16xk+fDiRkZF0796dkJAQqlWrxqFDhzA0NEz1OSSZEEIIIYQQ4gtUs2ZNPrRwq0KhYPLkyUyePDnN55BkQgghhBBCiHdk5dWcshqZgC2EEEIIIYRIE0kmhBBCCCGEEGkiw5yEEEIIIYR4R4JC1xF8PqRnQgghhBBCCJEmkkwIIYQQQggh0kSGOQkhhBBCCPGOhC/mtnUZT3omhBBCCCGEEGkiyYQQQgghhBAiTWSYkxBCCCGEEO+QQU6pJz0TQgghhBBCiDSRZEIIIYQQQgiRJjLMSQghhBBCiHck6DqAz4j0TAghhBBCCCHSRJIJIYQQQgghRJrIMCchhBBCCCHeITetSz3pmRBCCCGEEEKkiSQTQgghhBBCiDSRYU5CCCGEEEK8QwY5pd4XmUxcD3+k6xB0okxOZ12HoBP1NGa6DkEnNhg+0XUIOuGeEK7rEHTCLzJE1yHohJFddV2HoBOvX5zRdQg6Ia+3EJ8fGeYkhBBCCCGESJMvsmdCCCGEEEKItJKb1qWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iE3rUs96ZkQQgghhBBCpIkkE0IIIYQQQog0kWFOQgghhBBCvEMGOaWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iE3rUs96ZkQQgghhBBCpIkkE0IIIYQQQog0kWFOQgghhBBCvEMj6zmlmvRMCCGEEEIIIdJEkgkhhBBCCCFEmsgwJyGEEEIIId4hqzmlnvRMCCGEEEIIIdJEkgkhhBBCCCFEmsgwJyGEEEIIId6RIKs5pZr0TAghhBBCCCHSRJIJIYQQQgghRJrIMCchhBBCCCHeIYOcUk96JoQQQgghhBBpIsnEe3Ts2paLt47g5Xud/Ue3UqpM8feW/bFDC3Yf2Mi9R+e59+g82/asTla+R99O3HpwmlsPTtOjT0etfaXLFufgiR0olcoMacunaNihEavPrWHXg93M+WMuBUoW/GB5k1wm9PylJxuubmT3wz0sP7mCsrXKJe2v0awmay+uY+udbXQZ11XrWBsHG5afXIFRDqMMaUtq2FUsxHdrB/Pz1cX0e7qZ/N+W/WB5Yxsz6i3uTftTs+n7ZCPVJ7RPViZv9WK0PzWbHm6rqLugJ3rqt6+rfk4j2p+aTU57y3RvS1q07PQ9+y7v4NyjY6z/awVflSqSquPqNf2Gq75nmLNumtb29j3bcOTOPo7c2Ue7Hq219n1VuiibDq+W61yIdBYZGcWMBcup27wjZWs1pV2Pwdxxv59i2UmzFlOsagM2bd/z0Xq37tpPvR86UqZWE9p2G8gdN+06Zy1aSZX6Lfnm+5/48/BxrX2Hj5+hz/AJaW+USLVte/7k+w69qFi3ORXrNqdd90GcuXDlveV37jtIh15DqVK/JVXqt6TrgFHJXtt1v+3k60Zt+LpRG9Zv3aW17/Y9D1p17kdcXHyGtEd8fiSZSEGT7+szYcpw5s1cRv2aLXG7e58tu1ZgaWWRYvnK1crzx64DtGrcmSb12vHi+Ut+272SPLY2ABT5qiDDRvWld5dh9Ok6jGFjmu8oGwAAdNZJREFU+lO4aAEAlEolM+ZNYOTgycTH6/YfZrXG1ek6ritbF2xlYKMBPHJ/xOTNkzG1NE2xvEqt4pctv2DjkJsZPafTs1YPloxYTNDLIABymeei36x+rJ26lvHtxlHz+5qU/6Z80vG9pvRmw4z1vI54nRnNS5HayIBAdx9Ojd2QqvJKfRWvg8K5uugPAt18khdQKPh2cW/ubj7O780mYlPCmWI/1k7aXWVUa+5uPk7486D0akKa1W1Sm0ET+7Jq7nraf9uVB26eLN46F3NLsw8eZ+uQhwHje3P94k2t7a5FXOg5vAuje05kTK9J9BrRDZfC+YHE63z0zCFMHz5HrnMh0tn4GQu5cOUG08cPZc+mX6lSoQzdBozGLyBQq9yxU+e4fc8DG6uP/5hx8NgpZi1eSa/O7fh97WIKuTrTY/BYgoJDADh59iJ/HT3JyvlTGdK7CxNmLCQ4JBSA8IhIFq3cwNjBfdK9rSK5PNZWDOr5MzvWLmb7mkVUKFuSfiMn4+n9JMXyV67fpmHdmqxdNIPNK+aRx8aa7oPGJF0v9z0fsXT1ZmZPHsmsSSNYvHIjD7weARAXF8/k2YsZN6wvKpXufxjKSAlosuwjq5FkIgXdenfkt4072fHbXh7e92Lk4Em8joqmTfvmKZbv130EG9Zs495dD7wePmJo//HoKfSo9nUlAFwLOON+7wHnzlzi7OlLuN97gGsBZwB69f+Zi+evcuvG3Uxr3/s069qMw1sP8/fvx3j68CnLRi0l5nUMdVvXTbF8ndZ1yWGWk6ndpuB+1R3/Z/7cvXSXx+6Jbzq5HfMQFRbF2f1neHj7IXcu3MbBNS8AXzf5mri4OC4cupBp7UvJk5O3uTh7J96HrqaqfPizQM5M3ITHrrPEhCf/cmhkkRMjy1zc2XiMVw+e8+jodcwL2AGQp2wBbErm59aaQ+nahrRq16M1e7fsZ//2Azx68Jjpw+cQ/TqaJm0bvfcYPT09piwdz8o5a3n+xFdrn5OrIw/dvLh67jpXzl7D090LJ1dHAH7q3Zbrl27hdssjQ9uUGtnxOhdfruiYGI6dOsvgPl0oV6o4jg529OnSHkcHO7bv+SupnF9AINPn/8rMCcNT9SVw4/Y9tGjcgO8b1cPFOR/jh/XD0MCAPX8eAcD7yVP+1959h0V1dAEc/sEuICBIV4qAgL332GKJGo2xxt6w99h776ixd429a2wxamKLvQuKioCiKCoIKIoK0vf7g3yrK5gQAqzCefPsE3fu3LlnuLuwZ2fu3IplS1KiaCG+q1cLY2MjnoQ8A2D+8rW0adYI23w2mdNpoaFW9a/4umolnPLb4+zowKDeXTAyzIW3T+q/b2dPHkXbFt9TpJArLk75mTJ6EElJSVy6dgOAwEePKeTqTOXyZfiqQlkKuRUg8NETIHnEonyZkpQsWjiruie+AJJMfERPT49SZYpx9tT7P/4qlYpzpy9RvmLpNLVhaJQLpZ6SV399S+N75x4F3Jyxc7DFPr8tLm5O+PkG4OScnzbtmzNnxuJM6cu/odRT4lbSDe9zN9RlKpWKG+duULhckVT3qVy3Mn6efvSZ3pdNnptZemwZrfq3Qlc3+WUV/PApBoYGuBR3IXee3BQsXYiHvg8xzmNMh+EdWTVhZVZ0LUu9e/Gat6Evcfy6JMpc+thVKsxz38foKhXUntmFk6PXoUrS/rcKSj0lRUoV4vJZT3WZSqXiytlrlCpf/JP79RjahYgXL/l1+6EU2wL8HuDokp+89jbkc8iLo0t+7vsHYu9kR+M237Fi1s+Z0pd/Q17nIrtJTEgkMTEJA309jXIDA328bvoAkJSUxJipc+nSviVuLk7/2GZ8fDx3/O/xVcUy6jJdXV2+qlAG79u+ABR2c8HH7x6Rr9/g43eP2NhYHO3t8PK+zR3/ADq0apJxnRRplpiYyOHjp3gXE0OZEqn/TvtYTEwsCQmJ5DE1AaCgqzMPHz8l5FkYwc9CefT4KW4uTgQ9CWb/4WMM7Nk5M7sgvkCymtNHLCzNUCqVPA/XnIYSHv4C179GE/7JuMnDCH0Wpk5IAu4+YPa0hezYm/xhatbUhQTcfcCOfWuYPmketepUZ+jofiTEJzBxjAeXL3j+XfOZwtTCFIVSwcvnrzTKXz1/hYOrQ6r75HPMS6mqpTi1/xRTukzG1tmOvtP7otBTsmPhdqIio1gwdAFDFgxFP5c+f+75k+tnvPhxzkAObTxI3vx5Gb92Ako9JdsWbOPC4fNZ0NPM90ffJdSY1JEakzvy6KQ3vjtPU75/Y55c8CUxNp4f9k7E0MKEm+uPcnPjMa3EaGaRB6VSSUR4hEZ5RPhLnN1S/7BRulJJmrZrRPt63VLd/vDeI5bPWs3yHQsAWOaxiof3HrFs5wIWT19BlVqV6TW8KwnxCcyduJjrl7wztlNpIK9zkd0YGxtRukRRVm7YjouTI5YWZhw+fhrv23442tsCsHbLLygUunRs1TRNbb589ZrExCQsLcw1yi0tzAkMSv6Gulrl8nz/bR3a9hhELgMDZowfhpFhLqbNXcb0cUPZue8Q23YfwMwsD5NHDkxTEiPS7+79QDr0HkpcXBxGhoYsmjkB1wJp+5nPX7EOaysLqlQoC4CrsyODeneh5+CxAAzq3QVXZ0d6DBrD0H7dOH/Fk+Vrt6JUKhg9uA8Vynz6mtIvWZK2A/iCSDKRwfoP7kGTFg1p1bgLsbFx6vLN63exef0u9fNWbZvy9m0Unle9OXP1II3qtMHWLh/L18ylSpn6xMXFayP8f0VHV5fIF69YNnopSUlJ3L91H8u8lrTo04IdC7cDcOnIRS4deT/KU6JyCQoUdWb1xFWsOruauQN+4mX4S+YdmI/P5dtEvojUVncyTMjVu+z6fqL6uVmBfBT5oTo7Goyjxe4JeK87wqOT3rQ/7sHTy3688HusxWjTxsjYkKlLxjNjxBwiIz59jvZs+pU9m35VP2/UqgHRUdHcunabPee20rlhL2xsrZm5YjJNKrcmXl7nQvxnHhOGM9FjAXWadUSh0KVoITca1q3JHf8AfPzuseWXX/ll3RJ0dHQy9Lj9u3ekf/f3i1AsX7eVryqUQalUsmrjDvZtWs7pC1cYO30uu9YtydBjC00FHB3Ys2EZb95GcfTkOcbNmMeGpXP+MaFYs3kXvx8/zfqlczAw0FeXt2neiDbN3095/fXwMYyMDCldoiiN2/Vkx5pFhIY9Z8TEWRzZvR59ff3Umhc5hCQTH4l48YqEhASsrDUvULO2tiQ87Pkn9krWe0AX+g/uTttmPfD1ufvJeuYWZgwZ1ZcfGrlTtkIpHgQ8IvBBEIEPgtDTU+Li5ozfnXsZ0p+0eh3xmsSERMytzDTKzazMeBn+MtV9XoZFkJCQSFLS+/z9ScBjLGwsUOopSYhP0Kiv1FfSd0Zf5g+ej62zLQqFgtuXk68VCQ58SqGyhbl6/ErGduwzUHtWN85N2wa6utiUdCbg4GUSYuJ4eskP+6+KaCWZeBURSUJCAhbWmosKWFib8yIs5cXhDs722DvaMX/jLHXZ/6f5XHp8kh+qd+Dpo2CNffJY5KHnsK70aj6AEuWKEfTgMY8Dn/A48AlKPWXyNCi/B5nQu0+T17nIjhwd7Niw7Cei38UQFRWNtZUFwyZ44GCXDy/v20S8fEW9H95PTUlMTOKnpWvYvGs/R/ekXHzC3MwUhUKXFxGa74kXES+x+mi04v8ePHrMwSN/snv9UvYeOkqFMiWwMDfj2zpfM2HmAqKiojE2NsrYjgs1PT09HB2Sr88rXqQgPn532fLLr0waOfCT+6zftpu1W3bx88KZFHb79MyLl68iWbF+GxuWzeGWjz9O+e3Vj4TEBB4+fkoh17TN3BDZk1wz8ZH4+Hhu3rhD9Zpfqct0dHSo/nVlPK9+elpG34HdGDyiDx1b9ubmDZ+/PcaUmaP4efkmQoJDUejqoqf3PqdTKBUodLN+hYSE+AQCbgVQqtr760J0dHQoXa00/l6pX8R155ovtk62Gt922bnY8yL0RYoPWABtfmyL5ykv7t++j65CF8UHFwEqlEoUutnv5VisTU1iXr0l8JgXuorkn9P/l4pV6CnQUWinzwnxCfjdvEul6u+XwtXR0aFi9fLc9Ez5+n0YEESbWp3pULeb+nHm6Hmunb9Oh7rdCA0OS7HPsCk/sn31LsJCwtFV6KJUfvA6VyhQaKHv8joX2ZmRYS6srSyIfP2GC1c8qVPjKxo3+Ia9m5aze8My9cPGypKu7X9g1fwZqbajp6dHscIFufzXBbmQfN3FZc8blC6RcvlolUrF1DmLGfljT4yMDElKTCI+Ifm9kfDX/xOTZNJIVkpKUv3tDId1W39h1YbtrJw3jRJF/35p7NmLV9OpdTPy2ViTmJSoPqeQnJgmJWbPc6v6jP/73MjIRCp+Xr6RBctncvO6D9e9btGzbycMjQ3ZuTV5Xe5FK2YSEhLGrKkLAeg3qDvDxwxgQM+RPA4KxtrGCkhe+zs6Klqj7Rq1qlDA1ZlBfZPnInpfv41rwQLUrlsdO3tbkhKTuB8QmHWd/cD+NfsZMm8IAbfucffGXZp2b0ouo1wc33UcgCELhvLi2Qs2zU7+Juv3zYf53v17ek7uxcENv2FXwI5W/VtxcP1vKdrOXzA/NRrXYFDD5G9JngQ8QZWURL029XgZ/hIHVwfuemftaAyAnpEBeZzzqp+b5rfGqpgjMa+ieBv8giqjWpM7nznHhqxS17EqlrxCkZ6xAYaWJlgVcyQxPoGX9zS/mTe0NKXCwKbsaTEVgNjIaCLuPqVM9wYEnbmFQ7XiXF1yIAt6mbqtq3YyedFY7nj74XPDl/Y9W2FoZMhvOw4DMGXxOMKePWfZzFXExcZx31/zdfkm8i1AinKAyl9XwNElP5MGJn9YuXPDDyc3J6rWqUxeOxuSkhJ5dD+VpXWzQE58nYvs7fxlT1QqFc6ODgQ9CWbesrUUcHSgWaP66CmVmOUx1aivVCqwsjCngNP764S6DxzNN19XpX3L5AunO7dpzrgZ8yhepCAlihVmy679vIuJpVmjlKue7fntD8zN8lCrevKXcGVLFWP5ui143/bl7KVruDo7YmqSOxN/AjnbghXrqVGlArZ5bYiKjubQ0VNcvX6TVfOnAzBm2lxsrCwZ0rcrAGu37GLpms3MmTQKe9u8PH+RfO2ckaEhRkaa98O5cMWLR4+fMnP8MABKFC1E4KMnnL14lWdh4ejq6uLslPr1ZiLnkGQiFQf2/YGFlQXDxw7A2sYKn1t+dGzZW31Rtp2DLUkfrMjTuVsbDAz0+XnTQo125s1axvzZy9XPc+UyYMaccfTtNhyVKnn/kOBQJoyayfylM4iLi2Nwv7HExMRmfidTce63s+SxyEOHoR0xtzbnwZ0HTOo0kVd/XaxqbWeN6oNvl56HPGdip4n0mNiDJUeW8iL0Bb+tO8CeFXtStD1g1gDWTltD7LvkvsXFxrFw2EL6TOuLnr4eqyauJCI06++9YFPKhRa/jFM///9N6Hx/OcPxoasxzmtGbnsrjX3aHXl/o7a8pVwo3Lwarx+Hs7HqEI16X0/pxI3VvxMV+kpddnzYKurO702pbvXxWnmIMO+snebzoWMH/sTc0ow+I7tjaW3BXZ8Afmw/nIjnyVMb8tnn1Xidp5VBLn1GzhjCmD6T1K/zsJBwfhq/kIkLxhAfF8+kgTOJjYn7h5YyR058nYvs7c3bKBauXE9o+HPymJpQr2Z1BvZ2R0+Z9j/xj5+G8DLytfp5w7o1efkqkqVrtvA8IoIiBV1ZOW9aimlOzyNesnrjDrasnK8uK1msMO5tW9BvxCQszM3UH0RF5oh49Yqx0+YS/iICE2NjCrkVYNX86VStVA6AkNAwdD8YWd257xDx8QkMGa85MtW3WweNa2BiYmOZOX85c6eOUU9rzWdjzZghfRk/cwH6enrMGD+MXAYGWdBL8TnTUf3/r302Ym/+6aUts7NyJjlzzmJ9lZm2Q9CKjQmp35Aou7PVS/3mctnd78+uazsEkYXeBZ/VdghaYWhXQ9shaEVOPd96Vi7aDuGTujm31HYIn7Tu4W5th6BBJu8KIYQQQggh0kWrycSPP/7I2bP/LRuPjY3l9evXGg+VKnteDCSEEEIIIcTnRKvJxLJly6hVqxaFChVi9uzZPHv27F+34eHhQZ48eTQeb2L+fglXIYQQQgghPkXbKzZ9Sas5aX2a09GjR/nuu++YO3cujo6ONG3alIMHD2qs6f53xowZQ2RkpMbDJJfVP+8ohBBCCCGE+E+0nkyULFmShQsXEhwczJYtW4iNjaVZs2bkz5+fcePGERAQ8Lf7GxgYYGpqqvHQ0dF6t4QQQgghhMj2PpulYfX09GjdujWtW7cmKCiIdevWsWHDBmbNmkViYqK2w/tbA4b0oOH39XArWICYmBiuXbnBzMnzuR/wUNuhZTqLvJZ0GdOF8rXLY2BoQMjDEBYNX0jAzb9PAr8kdpULU653I6xLFSB3XnMO9VjAgyOe6u2uDSpQotM3WJd0xtDchO3fjuX5He3cQyEruQ/owI/j+rDt513Mn7hE2+FkqpzwOhefl6ioaJb8vIkTZy4S8fIVRQq5Mnpwb0oWLayuc/9hEAuWr+PajVskJibi4uzIwhnjsc1no65z47Yvi1dt5NYdP3R1dSlS0JVVC6ZrLOcZExtLje/asGfjcgxz5eKnpT/j43ePoCfBdGjZhNGD+6SI78ifZ1n68yaePgvFycGeIX278nXVSgDEJySwZPVGzl68xpPgEHIbG/NVxbIM6dMVG2tLdRsPg54wb9lart+6Q3x8PIXcCpArl4KYmM/7b/6XaMe+g+zcd4jgkFAA3Ao40adre2pUqQjAlDmLuXj1OuHPIzAyykWZEsUY0q8bLk75tRm2VsnVt2n3WX6F7+joyOTJkwkMDOSPP/7Qdjj/6KuqFdm4ZjuN67ejXYue6Okp2bb3Zww/uvlLdmOcx5g5e+eQmJDA5M6T6f9NP9ZNW8vbv25mll3oGRrw3DeI0+M3prpdaWRA8BV/LszcmcWRaU+x0kVo0akJd32y/4fpnPI6F5+XibMWcfHqdTwmDmff5hVUrVSOnoPGEhqefE1g0JNgOvcdTgGn/KxfOps9G5fTp0t79A301W3cuO1Ln6HjqVqpHNt/XsSONYtp90NjjXsOAFy8ch3bfDY4OtgRFx+PuVkeerm3pbBb6suNX791h5GTZ9H8+2/5Zf1S6tSowsAx07j34CEAMTGx3PG/T+8u7di1bikLZ47nYdATBoyaotFO/5GTSUhMZO3iWexat4TCbi7Y5s2FQqGTylHFf5HP2oohfbqya90Sdq5dTKXypflx9FQCHiQvMV6ssBvTxw3lwLbVrJo/A5VKRa8h4z77L3PF50GrIxNOTk4oFIpPbtfR0aFevZR32/zcdGzVW+P54H7juBVwjlJlinH5gucn9vrytezbkuchz1k0fJG6LPRxqBYjyhyPTt3k0ambn9zuv/c8ACYOOeNaHUMjQ6Ytm8iM4XPoPthd2+FkupzyOhefDx0dOH76HItnTaJCmZIA9O/ekdPnL7Nz3yEG9nJn8eqN1KhSkWH9u6v3c3Sw02hnzqJVdGjZlB6dWqvLCqRyt+I/z12k9l93r7a3zcuYv0Yi9h06mmp8W3b9SrXKFejWIXkd/h97debiVS+27f6NSSN/xCS3MWsWzdTYZ+zQvrTrMZiQZ2HY5rPh5atIHj1+ytTRg9VJy5A+Xdmx9yD6erq8kw+xGer/dyf/v0G9u7Bz3yG8ffxwc3GiVdPv1NvsbfPyYy93fnDvx9OQ0BSvKyE+ptWRicDAQCwtLf+54hfG1NQEgFcvI7UcSeaqVK8yATfvMWrFaDZ7bWHh4UXUb/ettsMSmWyUxxDOn7jIlbPZN1H+kLzOhTYkJiZhoK+nUWZgoI/XTR+SkpI4c+Eqzvnt6TVkHF83aku7noM5ceaCuu6Ll6+4eccfC/M8dOg9lK+/b0eX/iPw8r6t0WZSUhKnz1+hdo0qaY7N28eXKhXKaJRVrVwebx/fT+7z9m00Ojo6mJgYA2CWx5QCjg4c+OME0e9iSEhIZNevh0lITCI2ThKJzJSYmMjh46d4FxNDmRJFUmyPfhfD/kNHcbDLh21eay1E+HlIUqk+28fn5rOc5vQl09HRYYrHKK5c8sLfN3tPAcmXPx8NO35HcGAwkzpN5Pcth+k1pRd1WtbRdmgik9Rv+g1FShZi6cxV2g4ly8jrXGQ1lQpKlyjKyg3bCQt/QWJiIr8d+RPv2348fx5BxMtXRL97x9otu6heuQKrF8zgm6+rMnjsdK5eTx5FffI0BIDl67bSskkDVs2fRtFCbnQfNIZHj5+qj+Xt4wdAqWKFUwbyCc9fvMTSwlyjzMrCnOcvXqZaPzY2jgUr1vFd3ZrkNk5OJnR0dPh50Ux8796ncr0WlK/ThE079hHyLIY0LuYo/qW79wOpWLc55Wo3YdpPS1k0cwKuBZzU23fsPUjFus2pVLc55y5dY/WCGejp6f1Ni0Ik+2wuwM4uZs4dT+GiBWnesJO2Q8l0Oro6BNwMYPOcTQA88HmAU2EnGnb4jj93/6nl6ERGy2tnw7BpA+nfZihxsXHaDifLyOtcaIPHhOFM9FhAnWYdUSh0KVrIjYZ1a3LHP4CkpORvJmvXqELnts0BKFLIlRu37rBr/2Eqli2l/vayVdPvaN6oPgBFC7lxyfMGew8eZUjfrgCcPHuRmtUqoaubOd8txickMGzCTFQqFRNGDFCXq1QqZsxbjqV5HjYu/4lcBgbs+e0PQkJ/40nwOxITP79vX790BRwd2LNhGW/eRnH05DnGzZjHhqVz1AlFo/q1qVKxLOEvItiwbQ/DJ3qwecU8DD64DkeI1EgykYGmzxlH3W9r0uI7d0KCs/+c6pdhL3l8T3PVosf3HlO1YTUtRSQyU5FShbG0tmDL0TXqMqVSSdmvStO6awuqOn2T5vvDfEnkdS60wdHBjg3LfiL6XQxRUdFYW1kwbIIHDnb5MDczRalQ4OrsqLGPi3N+vG7eAcDa0gIA1wIf1XFy5FlomPr5yXOX1YlFWllZmvMiQnMU4nnES6wsNUcr/p9IBIeGsW7xLPWoBMBlzxucvnCFC3/sUpcXKzyAzbt+wyS3kleR8f8qJvHP9PT01Nc/FC9SEB+/u2z55VcmjRwIgEluY0xyG+OU357SxYtQtUErTpy5wHf1amkxau2RdDbtJJnIINPnjKNBo29o1bgLj4Oe/vMO2YDvtTvYu2pezGfvYk/Yk7BP7CG+ZFfPXqNNrc4aZRMXjuFRQBAbl27NlokEyOtcaJeRYS6MDHMR+foNF654MrRfN/T09ChetBCBQU806j58/BS7v5aFtbfNi42VJQ8fadZ59PgJ1b+q+Ne/nxLyLIwqFcv+q5hKFy/KJc8bdGrTXF128ep1Shcvqn7+/0Qi6HEw65bMwiyPqUYbMTGxAOh+fF8o+QSXZZKSVMTFpZ60qVQqVCo+uV2ID0kykQFmzp1As5bf0a39j7x9G421TfKqPm9ev1H/wsyOfl3zK3P2/USr/q04d/AchcoU4tv2DVg6eqm2Q8tQekYG5HHOq35umt8aq2KOxLyK4m3wCwzMjDGxs8Q4b/K3cuautgBEh0cSHZ59LsKPjnrHff9AjbKY6BhevYxMUZ6d5JTXufi8nL/siUqlwtnRgaAnwcxbtpYCjg40+2vKUtf2PzB84iwqlClBpXKlOXfpGqfPX2b9ktlA8jUJXdv/wLK1WyhcsABFCrry6+HjBD56wvzp4wD48+xFvqpQBsNcuTSO7Xf3PgDR0TG8fBWJ39376Okp1dNhOrZuStf+I9mwfQ9fV63E78dP4+N3j8mjkr/hjk9IYOi4Gdy5G8CyOVNISkri+YsIAPKYmqCnp0fpEkUxNcnN2Onz6NO1PbkM9Nl94A/09HSIficXYGe0BSvWU6NKBWzz2hAVHc2ho6e4ev0mq+ZP5/HTEP44cYaqlcphYZaHZ+HPWbt5FwYG+tSoWlHboYsvgI5K9RleFv4f2ZsXz9LjPX3pk2r5kH7j2LV9f5bFUc4k9TXBM1PFbyrSeZQ7ds52hD4OZf+a/RzdfiRLY6ivMsvU9u2/KkqLX8alKPf95QzHh66mSKsa1JvfO8X2y/P3cmXB3kyLa2PCo0xrO61W7VmMv8+9LL1pna1eniw71v99Dq/z359dz9LjCe3at3kGC1euJzT8OXlMTahXszoDe7tjkvv9VKG9B4+wZvMuQsOe4+zoQP8eHanz0apMazbvYvve33j9+g2F3FwY1q8b5UqXAKBz3+E0aViXlk0aaOxTolrDFPHY5bPh6J7399o58udZlqzeqL5p3dB+3dQ3rXsaEsq3Lbuk2q91S2ZTqVwpAG773mXx6o34+N0jISEBtwJO/HHieo5MJt4Fn83U9id4LODytRuEv4jAxNiYQm4F6NahFVUrlSMs/AWTZi3Exz+A12/eYmlhRoXSJejTtUOqSwlnJD0rl0xt/79o79T8nytpybZH+7QdggZJJrIRbSQTn4PMTiY+V59DMqEN2kgmPgeSTOQsmf3h8uWrSGo36cDx/Zux+mhlJm0ytKuh7RC0IrPP9+dKkon0+dySCVkaVgghhMhhIl+/YcSPPT+rREII8WWSayaEEEKIHMbZ0QFnx8ydwiLEl0wlqwGkmYxMCCGEEEIIIdJFkgkhhBBCCCFEusg0JyGEEEIIIT6QPe+clDlkZEIIIYQQQgiRLpJMCCGEEEIIIdJFpjkJIYQQQgjxgSRZzSnNZGRCCCGEEEIIkS6STAghhBBCCCHSRaY5CSGEEEII8QG5aV3ayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gNy07q0k5EJIYQQQgghRLpIMiGEEEIIIYRIF5nmJIQQQgghxAdUKlnNKa1kZEIIIYQQQgiRLpJMCCGEEEIIIdJFpjkJIYQQQgjxgSS5aV2ayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gNy07q0k5EJIYQQQgghRLpIMiGEEEIIIYRIl2w5zalDnlLaDkErVoZf1nYIWuGlb6jtELTiTdw7bYegHabaDkA7jPQMtB2CVpjk0Pe3pVNdbYegFe+Cz2o7BK1wLz9M2yFoxbZH+7QdwiepZDWnNJORCSGEEEIIIUS6SDIhhBBCCCGESJdsOc1JCCGEEEKI9JKb1qWdjEwIIYQQQggh0kWSCSGEEEIIIUS6yDQnIYQQQgghPqBSyTSntJKRCSGEEEIIIUS6SDIhhBBCCCGESBeZ5iSEEEIIIcQHkrQdwBdERiaEEEIIIYQQ6SLJhBBCCCGEECJdZJqTEEIIIYQQH1DJTevSTEYmhBBCCCGEEOkiyYQQQgghhBAiXWSakxBCCCGEEB9IkmlOaSYjE0IIIYQQQoh0kWRCCCGEEEIIkS4yzUkIIYQQQogPqFQyzSmtZGRCCCGEEEIIkS6STAghhBBCCCHSRaY5CSGEEEII8QFZzSntZGRCCCGEEEKIbGby5Mno6OhoPIoUKZLhx5GRCSGEEEIIIbKh4sWLc/z4cfVzpTLjP/pLMiGEEEIIIcQHVJ/xNKfY2FhiY2M1ygwMDDAwMEhRV6lUki9fvkyNR6Y5fUKVTvUYfW4xM/w3MmD/NPKXdv1kXV2lgroDWzDq9EJm+G9k8O+zKFSztEadsk2rMfbCUiZ7/8z34ztqbDN3sGLEn/MxyG2YKX35N3r26sStO2cIe+HLn6f2Ur58qU/WLVK0IJu3LufWnTO8jnpAv/5dU9Rp3aYpd/zP8ejJdWbOGqexzdHRHq8bJzAxyZ3h/fi33Hu045L3Ue6HePHbse2UKVfyk3Xbd27J3sOb8Am8gE/gBXbsW5Oifu8BXfC+ewbvu2fo3d9dY1vZ8iX5/eQuFApFpvTl38ip57tVl+YcuLKL84HH2XBoFcXLFE3TfvWbfsO1kLPMXT9To7xjn7YcvXWAo7cO0KF3G41txcsWY/ORNXK+tUje39nzfEdFRTNr4UrqtXCnfO2mdOg9lFu+/urtJao1TPWxbuvuT7Z57cYt+o+cRO0mHShRrSEnzlxIUWf9tt183agtXzdqy4btezS23fTxo3W3H0lISMy4jqZRvc4NWXRuFRv8dzJ1/2xcSxf8ZN3xO6ax7dG+FI8R69+f10a9mrLCcwMrPDfwXc8mGvu7linIjINz0VXIx0ht8PDwIE+ePBoPDw+PVOveu3cPOzs7XFxc6NChA0FBQRkej7wKUlH6+69oPL4TxxftYVGjsYTceUT3TaMxtjRNtf63w1tTuf03/DppA/PqjuDS1uO4rxqKXXFnAIzMTWg5uxeHZm5hTScPyjWrTtE6ZdX7N5/Wjd9nbyf27bus6N4ntfihETNnjWWWx2JqVGvMrVu+7P11I1bWlqnWNzI05OHDICZPnMOzZ2EptltYmrNkmQfjx3rQvIk7bdo2pUGDOurt8xdOY9LEObx58zbT+pQWTZo3YNL0kcyfvZwGtVpx57Y/W/eswtLKItX6VapX5Nc9h2nduBtN6ncg+Okztu1dTT5bGwCKFi/EiDED6Nd9BP17jGDEuIEUKZb8S12hUDBr/iRGD51KYmLW/7H5UE493/Wa1GHI5AH8PG8DHb/twd07ASzZPg9zS7O/3c/WIR+DJvbD69INjXK3oq70GdmdsX0mM67vFPqO6olrERcg+XyPnT0Mj5Fz5Xxriby/s+/5njhrERevXsdj4nD2bV5B1Url6DloLKHhzwE4dWCrxmPa2CHo6OhQr1a1T7b57l0Mhd1cGDesX6rb/QMCWbZmCz9NHc2cKaNYsnoTd+8HApCQkMjUn5YwYcQAlMqsTSa/+r4aHcd3Ze+inYz7fhhBvg8ZvXkippZ5Uq2/oPds+lboqn6MqDuQxIRELh9KTp7yF3Gi5dB2LPlxHksHzqP18PbkL+wIgK5Cl+4z+7B27EqSEpOyrI/ivTFjxhAZGanxGDNmTIp6lStXZsOGDfzxxx+sWLGCwMBAatSowZs3bzI0HkkmUlGjRyMu7/iTa7+cJizgKXvHrSX+XRwVW9dKtX755jX4c9l+/E7dIOJxGJe2HMfv5HW+7tEIAEtHG2LeRON98BJPbj7g/qU72LjZA1CmSVUSExK5feRqVnXvkwb82J2N63eydfNu/P0CGDxwPO/evaNT51ap1vfyusmEcbPYs/sgsbFxKbYXcM7P69dv2LvnEF5eNzlz+hKFiiSP8LRs1Zj4+Hh+O3AkU/uUFj37ubNt0252bdvPPf/7jB46hXfRMbTt2CLV+j/2GsXGtTvwue3H/XuBDB84EV0dXap//RUAbgUL4Otzl/NnL3PuzGV8fe7iVrAAAH0HduXShWt4X7+dZf37lJx6vjv0bsP+rb/x287DBN59iMfIucS8i6FJu0af3EdXV5fpyyayeu46nj4K0djm7ObIvTv3uXbei6vnPAnwvY+zW/If3U792uF12Zs73n6Z2qe0yKnnW97f2fN8x8TGcvz0OYb2706FMiVxdLCjf/eOODrYsXPfIQCsLC00HifPXqJSuVLkt7f9ZLs1qlRkYC936tZMPeEIfPSYQq7OVC5fhq8qlKWQWwECHz0BkkcsypcpScmihTO+w//gux5NOLnjGKd/+ZOn956wduxKYt/FUrP1N6nWj4p8S2T4K/WjZI3SxL6LVScTdq72BPk+5M6FW/icv0WQ7yPsXB0A+L53M/wu3+HBzYAs6582JKlUn+3DwMAAU1NTjUdqU5waNmxIq1atKFWqFN9++y2HDx/m1atX7Nq1K0N/VpJMfEShp8C+RAECzr//Y6BSqbh3/jZO5VIfMlToK0mIjdcoi4+Jx7li8i+U54HP0Mulj11xZwzzGONQyoUQvyAMTY2pP7QV+yeuz7wOpZGenh5lypbg5Mnz6jKVSsWpk+epVKns3+z5affvP8TQMBelShfD3DwP5cqXwue2H2ZmpoyfMIThQydnTPD/gZ6eHqXKFOPsqYvqMpVKxbnTlyhfsfTf7PmeoVEulHpKXr2KBMD3zj0KuDlj52CLfX5bXNyc8PMNwMk5P23aN2fOjMWZ0pd/I6eeb6WekiKlCnH5rKe6TKVSceXsNUqVL/7J/XoM7ULEi5f8uv1Qim0Bfg9wdMlPXnsb8jnkxdElP/f9A7F3sqNxm+9YMevnTOnLv5FTz7e8v7Pv+U5MSCQxMQkDfT2NcgMDfbxu+qSo/zziJWcuXKHF99/+p+MWdHXm4eOnhDwLI/hZKI8eP8XNxYmgJ8HsP3yMgT07/6f200Ohp6RASVdun/NWl6lUKm6fu0nBcmlLbGq1qcul384R+y55Hv5j/yBsXeywtLPCyt4aWxc7Ht8NwsYxHzVbfcOuuVszpS8ic5mZmVGoUCECAjI2EZQLsD9ibG6KQqngzfNIjfK34ZHYuNqlus/dMzep0aMRgVf8ePEoFLdqJSjRoCK6usm52rvXUewcvoI28/qil0sfr71nuXvmJi1n9+LCpqNY5Lehy5oRKJQKji3cza3fr2R6Pz9maWmOUqkkPOy5RnlY2HMKFfr09SJ/59Wr1/TpNYJVP8/DMJcBO7bt48TxsyxdPovVqzbj5OzAjl9Wo6enxGPGYn7d/3tGdOVfsbA0Q6lU8jz8hUZ5ePgLXP/6tvGfjJs8jNBnYeoPLAF3HzB72kJ27E3+EDlr6kIC7j5gx741TJ80j1p1qjN0dD8S4hOYOMaDyxc8/675TJFTz7eZRR6USiUR4REa5RHhL3F2c0p1n9KVStK0XSPa1+uW6vaH9x6xfNZqlu9YAMAyj1U8vPeIZTsXsHj6CqrUqkyv4V1JiE9g7sTFXL/knWo7mSmnnm95f2ff821sbETpEkVZuWE7Lk6OWFqYcfj4abxv++GYysjDgd+PY2Rk+MkRh7RydXZkUO8u9Bw8FoBBvbvg6uxIj0FjGNqvG+eveLJ87VaUSgWjB/ehQplPX5+TUUzMTVAoFUR+9Lkl8vkr7Fzt/3F/19IFcSzixM8jl6nLggOesHPOVsZsmQzAjtlbCA54wtitk9nusZFSNcvyw+C2JCYksGnyWvyu3MnQPonM8fbtW+7fv0+nTp0ytF1JJjLAgSkb+WFWT4afmIdKpSLiUSjXfjmtMS3K58g1fI5cUz93qVwU2yKO/DppA6NOL2TbwCW8CX/FgP3TeXDFj6gXr7XQk4x38LejHPztqPp5teqVKFGiCCOGTebGrZN06zKI0NBwTp7ez/nzV1L80f/c9R/cgyYtGtKqcReNqQGb1+9i8/r3w4it2jbl7dsoPK96c+bqQRrVaYOtXT6Wr5lLlTL1iYuLT635L052O99GxoZMXTKeGSPmEBkR+cl6ezb9yp5Nv6qfN2rVgOioaG5du82ec1vp3LAXNrbWzFwxmSaVWxMv5/uLIO9vTZ/b+faYMJyJHguo06wjCoUuRQu50bBuTe74p/zWdd/Bo3xfvzYGBvr/+bhtmjeiTfP30yJ/PXwMIyNDSpcoSuN2PdmxZhGhYc8ZMXEWR3avR1//vx8zM9Vq8w1Bvg+5731Po/zE1iOc2Pp+6lqNH2rz7u077nr5M+/PZUxoMgILW0t+XDqMQdV7kxCXkNWhZ6rPdy2ntBs+fDiNGzfGycmJ4OBgJk2ahEKhoF27dhl6HEkmPhL18jWJCYmYWGletJTbOg9vwl+lvk/EGzb1mo/SQA8js9y8Dn1Jw9HteBGU8iI2SJ4W1WxaN3YOWYalcz50Fbo8uOwLwPPAEBzLuOF7witD+/VPXrx4SUJCAtY2VhrlNjZWhIaGZ8gx9PX1mb9gKr16DsPF1RmlUsH5c8mjMPcDAqlQoTR//P5nhhwrrSJevCIhISHFRYnW1pYpvtX7WO8BXeg/uDttm/XA1+fuJ+uZW5gxZFRffmjkTtkKpXgQ8IjAB0EEPghCT0+Ji5szfnfufXL/zJBTz/eriEgSEhKwsNa8+NbC2pwXYSk/+Dg422PvaMf8jbPUZf8fcbz0+CQ/VO/A00fBGvvkschDz2Fd6dV8ACXKFSPowWMeBz7hceATlHrK5GlQfg8yoXefllPPt7y/s/f5dnSwY8Oyn4h+F0NUVDTWVhYMm+CBg53mMpieN24TGPSEn6amvED1v3r5KpIV67exYdkcbvn445TfXv1ISEzg4eOnFHJN2yhYer15+YbEhETyfPS5JY+VGa8+8bnl/wwMDajSuDq75+/423om5ib8MLg1U1uNx61MIZ4FBvPsYQjPHoagUCqwLWDHY/+MXyVI/DdPnjyhXbt2vHjxAmtra6pXr86lS5ewtrbO0OPINRMfSYxP5OntQNyqllCX6ejo4Fa1OI+8/v4PQkJsPK9DX6KrVFCyQSXuHLuWar1vBjTn7mlvnvo8RFehi+4Hqz4o9BRaWWotPj6eG9dvU6tWVXWZjo4ONWtV5cqV6xlyjJGj+nP8+Bm8b/igUOiiVLzPZZV6Sq0spRgfH8/NG3eoXvMrdZmOjg7Vv66M59VPT0fpO7Abg0f0oWPL3ty8kXJ+7oemzBzFz8s3ERIcikJXFz299/1WKBUodLXT75x4vhPiE/C7eZdK1cury3R0dKhYvTw3PVOex4cBQbSp1ZkOdbupH2eOnufa+et0qNuN0OCUXxgMm/Ij21fvIiwkHF2FrsYNghQKBQp5f2cZeX/njPNtZJgLaysLIl+/4cIVT+rU+Epj+96DRyhWuCBFCrpk+LFnL15Np9bNyGdjTWJSIgkJ77+dT0xMypLVjhLjEwi8dZ/i1d4v/aujo0PxaiW55+X/N3tC5UZVUerrcW7f6b+t13FiNw6v/Y2IZy/QVeii0Pvgc4tSO59bxD/bsWMHwcHBxMbG8uTJE3bs2IGra/qmOv4dGZlIxdk1h2g9ry9Pbj3g8Y0AqndviL6RAdd+SX6ztZnXl8jQl/wxJzmTz1/GlTx5LQi+8wjTfObUG9wSHV0dTq36LUXbNm72lP6+CgsbJX9DEhbwFFWSioqta/EmPBJrVzsee9/Pus5+YOmStaxcPZfr129x7Zo3/fp3xcjIiC2bk9fkXvXzXIKDQ5ky6Scg+SK/IkXdANDX18PWLi8lSxUl6m00Dx480mi7cBE3WvzwPdWrfg/AXf/7JCUl0alza8JCwylUyBUvz5tZ2Nv3fl6+kQXLZ3Lzug/XvW7Rs28nDI0N2bl1HwCLVswkJCSMWVMXAtBvUHeGjxnAgJ4jeRwUrP72LyoqmuioaI22a9SqQgFXZwb1TZ5f6339Nq4FC1C7bnXs7G1JSkzifkBg1nX2Azn1fG9dtZPJi8Zyx9sPnxu+tO/ZCkMjQ37bcRiAKYvHEfbsOctmriIuNo77/prn501k8tKXH5cDVP66Ao4u+Zk0cAYAd2744eTmRNU6lclrZ0NSUiKP7mvn27ucer7l/Z19z/f5y56oVCqcHR0IehLMvGVrKeDoQLNG9dV13kZFcfTkWYYP6JlqG90Hjuabr6vSvmXyfRSio98R9OT9aOPT4FD87t4nj6kJtvlsNPa9cMWLR4+fMnP8MABKFC1E4KMnnL14lWdh4ejq6uLs5JDR3U7V4TUH6DNvIA9u3ue+9z0advueXEa5OP3LCQD6zh9IxLMIds7ZorFfrTZ18Tx6mbevPr1UaInqpbEtYMfKocmLCzzwDsDO1Z7StcphaWtJUmISwfeDP7n/lyopW0x0yhqSTKTC++AljC1MqT+kJSbWZgT7PmKt+yze/nVxk5m9FSrV+xeZnoE+3w5vjYWjDXFRsfidvM7OIcuJeR2dou0fPHpwcPpm4v9aMSEhNp5dw1fQbGpXlAZ6/DpxA69DX2ZNRz+yd88hrKwsGDt+CHnzWnHrpi8/NOuing7g4GBHUtL7b1lsbW04f/H96jaDBvdi0OBenD1ziUYN22u0vXjJTMaOnkF0dPK9NGJiYunbeyRzF0zBwECf4UMnERISmgW9TOnAvj+wsLJg+NgBWNtY4XPLj44te6vn+9o52JKU9P58d+7WBgMDfX7etFCjnXmzljF/9nL181y5DJgxZxx9uw1Xv15CgkOZMGom85fOIC4ujsH9xhITo3kXy6ySU8/3sQN/Ym5pRp+R3bG0tuCuTwA/th9OxPPk910++7wa5zutDHLpM3LGEMb0maQ+32Eh4fw0fiETF4whPi6eSQNnEhuTctnNrJBTz7e8v7Pv+X7zNoqFK9cTGv6cPKYm1KtZnYG93dH7YDTw9+OnUangu3q1Um3j8dMQXka+v0bxtt89uv04Sv18zpLVADRtWJcZfyUNkLw07cz5y5k7dYx66mM+G2vGDOnL+JkL0NfTY8b4YeRKZbnOzHDp4HlMLU1pObQtZtbmPLoTyKzOU3n91+cWSzvrFL/XbF3sKFKpGDM7TP5ku3oG+nSZ2pMlA+aqX+cRz16wYdIaev80gPi4eFYMW0x8KssJi5xDR/Xhp+JsYqRzxl5Y8qVYGX5Z2yFohYm+9u8crg1v4rR7k0NtKWT6z6uTZEd3Xz/VdghaIe/vnOXFo+PaDkEr3MsP++dK2dC2R/u0HcInVbOv88+VtOT806y9/uyfyMiEEEIIIYQQH5BpTmmn9Stmli5dSufOndmxI/n6g82bN1OsWDGKFCnC2LFjNS5mSk1sbCyvX7/WeCSoErMidCGEEEIIIXI0rSYT06dPZ+zYsURHRzNkyBBmz57NkCFD6NChA+7u7qxZs4Zp06b9bRseHh7kyZNH43E5Um6eIoQQQgghRGbT6jSnDRs2sGHDBlq0aIG3tzfly5dn48aNdOjQAYAiRYowcuRIpkyZ8sk2xowZw9ChQzXKJpfskalxCyGEEEKI7CsbXlKcabSaTAQHB1OhQgUASpcuja6uLmXKlFFvL1euHMHBf7/cmIGBAQYfrZag1Mn6db2FEEIIIYTIabQ6zSlfvnzcuZM8JenevXskJiaqnwP4+PhgY2Pzqd0/KwbGuWg8sTNjzi1mht9G+u2ZgkOpjL9BzuekarWK7PzlZ/wDLvI66gGNvq+n7ZCyxIAhPTh0Yif+QVfwvnuGtVsW4+rmrO2wMl1OPd8fcx/QgWshZxk69Udth5Kpcur5lvf353W+o6KimbVwJfVauFO+dlM69B7KLd/Ub8Q2Zc4SSlRryOadKVcIOn3hCu16DqZ87aZUbdCKgaOnpqgT/CyU8rWbEh39jviEBFas20qDVl0pV7sJLdz7ce6S5o1o6//gTolqDVM8ps9blqJtlUpFn2ETKFGtISfOXEjnTyPjLDq3im2P9qV4dJnWS9uhiS+QVkcmOnToQOfOnWnatCknTpxg5MiRDB8+nBcvXqCjo8OMGTNo2bKlNkNMs5aze5G3UH52DF3O69CXlGtenZ5bxjGv3nCt3TcisxkbG3H7li+bN/3Cth0rtR1OlvmqakU2rtnOjeu3UCqVjJ4wiG17f6bWV014F519l3PMqef7Q8VKF6FFpybc9QnQdiiZLqeeb3l/f17ne+KsRQQ8eIjHxOHYWFny25E/6TloLL9uXUVeayt1veOnz3PTxw8bK8sUbRw7eY5JsxcxqHcXKpcvTWJiIvc+uhEfwJ9nL1GpXCmMjAyZv3wtB4+cZPKogRRwys/5K54MGjONLavmUbRQ8s39dqxZpHGvjnsPHtFz8Fjq166Rou3NO/ejkxE/kAwyvskIjbtW5y/kyNhtU7h86LwWo/q8yGpOaafVZGLKlCkYGhpy8eJFevbsyejRoyldujQjR44kOjqaxo0b/+MF2J8DpYEeJRpUYmPPeQRe8QPg2MI9FP2mHFU61uPIvF1ajjBzHDt6mmNHT2s7jCzXsVVvjeeD+43jVsA5SpUpxuULnlqKKvPl1PP9f4ZGhkxbNpEZw+fQfbC7tsPJdDn1fMv7+/MRExvL8dPnWDxrEhXKlASgf/eOnD5/mZ37DjGwV/L7MDT8OR4LVrBq/gz6jZio0UZCQiKzFq1kWP8e/ND4W3W5awGnFMc7efaiOhH47Y8/6eXelq+rVgKgbfPvuXT1Bhu272X2pJEAWJibaey/ZvMu8tvbUrFsSY1yv7v32bhjDzvXLqZWkw7/4SeScd5EvNZ43qRvC549DMH3ko+WIhJfMq0mE7q6uowdO1ajrG3btrRt21ZLEaWPQqlAoVSQ8NEdIONj4nCuWFhLUYmsYmpqAsCrl5FajkRkplEeQzh/4iJXznrmiGRCJJP3t/YkJiSSmJiEgb6eRrmBgT5eN5M/9CYlJTFm6ly6tG+Jm0vKBMH3bgCh4S/Q1dWhZZf+PI94SZGCrgzr352CLs7qeq/fvMXrpg8eE0YAEBcfj76+forjXr+Z+oft+Ph4Dh49Sec2zdHReT8G8S4mhpFTZjNuWH+sLC3S9XPIbAo9JdWb1+TwmgPaDkV8obR+n4nsIDYqhoeed/lmYAtMbczR0dWhbLPqOJUrhKm1mbbDE5lIR0eHKR6juHLJC3/f7D/1Jaeq3/QbipQsxNKZq7QdishC8v7WLmNjI0qXKMrKDdsJC39BYmIivx35E+/bfjx/HgHA2i2/oFDo0rFV01TbeBwcAsDytVvp7d6OZXOmYGqSm64DRhH5+o263tmLVynkWgAb6+RpUtUql2fTjr08evyUpKQkLlzx4sTpC4S/iEj1OCfOXOTN27c0+07zWpM5i1dTpkQx6tSo8p9/HpmlQv1KGJkac/qXz+uuytqm+oz/+9xIMpFBdgxZho6ODuOvLGfm3c1U6/ItNw5cIEmWFsvWZs4dT+GiBenXfbi2QxGZJK+dDcOmDWR8/2nEfTT6KLI3eX9rn8eE4aBSUadZR8rVbsLWX36lYd2a6Ojq4uN3jy2//MqMccM0RgM+pEpK/hvcy70N9WpXp3iRgkwfOwQdHTjy51l1vT/PXqJ29a/Uz0cP6o1Tfnsat+9F2VqNmTl/Oc0a1UNXJ/WPTXsPHqH6VxXUyQjAybOXuOzpzehBvVPd53NRu01dvE958Sose17fKTKfVqc5ZScRQWGsbDMVPUMDcuU25E34KzosHUhEUJi2QxOZZPqccdT9tiYtvnMnJDhU2+GITFKkVGEsrS3YcnSNukypVFL2q9K07tqCqk7faFyEKbIHeX9/Hhwd7Niw7Cei38UQFRWNtZUFwyZ44GCXDy/v20S8fEW9Hzqr6ycmJvHT0jVs3rWfo3s2Yv3X1CJXZ0d1HX19fRzsbAkJTf77HB8fz/nL1+jZuY26joW5GYtnTSQ2No5Xr19jY2XJghXrcLDLlyLG4GehXLp2g4Uzx2uUX/a8weOnIVRpoLmQzJBxMyhXujgbls757z+g/8jK3poS1UuxoLf2YxFfLkkmMlj8u1ji38ViaGpMoa9Lcdhjm7ZDEplg+pxxNGj0Da0ad+Fx0FNthyMy0dWz12hTq7NG2cSFY3gUEMTGpVslkciG5P39+TEyzIWRYS4iX7/hwhVPhvbrRr1a1fmqYlmNer2HjKdxgzo0+64+AMWKuKGvr0dg0FPKlS4BQHxCAk9DQrHLl7z0/BWvm5ia5KZIwZTLuRsY6JPX2or4hASOnTrPt3W+TlFn36FjWJjn4esqlTTKe3RqzQ9NGmiUNe/Ul5EDe1GrWuX0/zAyUM1WdYh8Ecn1P6/9c+UcRm5al3aSTGSQQl+XAh0dwu8HY+Wcj0Zj2xN2P5irv3xeq2NkJGNjI1xc31/w5uycn5KlivIyIpInT/7+ZoNfsplzJ9Cs5Xd0a/8jb99GY22TvDzhm9dviImJ1XJ0mSennu/oqHfc9w/UKIuJjuHVy8gU5dlJTj3f8v5O9rmc7/OXPVGpVDg7OhD0JJh5y9ZSwNGBZo3qo6dUYpbHVKO+UqnAysKcAk4OAOQ2NqZ10+9YvnYz+WyssMuXl/XbdgOoV246de4ytT6Y4gRw08eP0PAXFCnoQlj4C5av24JKpaJbB81RhqSkJPYfOkbThnVRKjVvmGtlaZHqRde2ea1THeHIajo6Onzdqg5nd58iKVG+FBHpJ8lEBsllYkTDkW3Jk8+C6Mi33Pr9Ckfm7iQpIVHboWWasuVKcviP7ernHrOTh3i3btlN394jtRVWpnPvnrza2J5DGzXKh/Qbx67t+7UQUdbIqec7p8qp51ve38k+l/P95m0UC1euJzT8OXlMTahXszoDe7ujp0z7x5dhA3qgUCoYM20usbGxlCxWhHWLZ5Hnr5W6Tp6/xLQxQzT2iY2LY8nPG3kS/AwjQ0NqVKmIx4QRmJrk1qh38ep1QkLDaN6o/n/vbBYrUb0U1g42nNp1QtuhiC+cjiobjuOMdG6n7RC0YmX4ZW2HoBUm+obaDkEr3sRl3xto/Z1CpvbaDkEr7r7OmdNt5P2ds7x4dDxLj3fHP4DuA0dz5tCOf5WgZDT38sO0dmxt2vYo5d3KPxflbKtrO4RP8go5p+0QNMhqTkIIIYTIkRITExkzpK9WEwkhvnTy7hFCCCFEjlSyWGFKFpObywrxX0gyIYQQQgghxAey4VUAmUamOQkhhBBCCCHSRZIJIYQQQgghRLrINCchhBBCCCE+kIRMc0orGZkQQgghhBBCpIskE0IIIYQQQoh0kWlOQgghhBBCfEAl05zSTEYmhBBCCCGEEOkiyYQQQgghhBAiXWSakxBCCCGEEB9IkpvWpZmMTAghhBBCCCHSRZIJIYQQQgghRLrINCchhBBCCCE+IKs5pZ2MTAghhBBCCCHSRZIJIYQQQgghRLpIMiGEEEIIIYRIF7lmQgghhBBCiA/I0rBpJyMTQgghhBBCiHSRZEIIIYQQQgiRLjLNSQghhBBCiA/I0rBpJyMTQgghhBBCiHSRZEIIIYQQQgiRLjLNSQghhBBCiA/Iak5ply2TiSsJ4doOQSui42O1HYJW5NR+5zU203YIWjFQ10nbIWhFt/gH2g5BiExXpaS7tkPQiou3Nmo7BCHSTaY5CSGEEEIIIdIlW45MCCGEEEIIkV6ymlPayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gOymlPayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gOymlPayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gMqVZK2Q/hiyMiEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gNJsppTmsnIhBBCCCGEECJdJJkQQgghhBBCpItMcxJCCCGEEOIDKpVMc0orGZkQQgghhBBCpIskE0IIIYQQQoh0kWlOQgghhBBCfEBWc0o7GZkQQgghhBBCpIskE0IIIYQQQoh0kWlOQgghhBBCfEBWc0o7GZkQQgghhBBCpIskE5/QzL0JOy5u4WjAYZb/toQiZQp/sm6DVvU59eS4xuNowGGNOm16t2LfjV/Yd+MXWvdqqbGtaNkirDq8HIVCTofIWu492nHJ+yj3Q7z47dh2ypQr+cm67Tu3ZO/hTfgEXsAn8AI79q1JUb/3gC543z2D990z9O7vrrGtbPmS/H5yFwqFIlP6khY2lQtTe8NQWnouofPTLeT/tvzf1ndsWIG620fR+uZy2vr9TMMDk7CrqdnnAs2r8sPVRbTxWUWFSR00thk7WNHs7E/o5TbM8L6ItOvZqxO37pwh7IUvf57aS/nypT5Zt0jRgmzeupxbd87wOuoB/fp3TVGndZum3PE/x6Mn15k5a5zGNkdHe7xunMDEJHeG9+Pfyqn9btWlOQeu7OJ84HE2HFpF8TJF07Rf/abfcC3kLHPXz9Qo79inLUdvHeDorQN06N1GY1vxssXYfGRNlv5ei4qKZtbCldRr4U752k3p0Hsot3z91dtLVGuY6mPd1t2fbHPZ2i0p6jdu11OjzpzFq6naoBXfNO/EwSN/amw78udZ+o+clLEdFV8MmeaUitqNa9FvYh/mj1mE73VfWvb4gZ+2zKJTza68evEq1X3evo6ic80u6ucfDo+5FC1A1+HujHEfj46ODh4bp3P1jCeBfoEoFLoM9RjM3FELSExMyuSeCfFek+YNmDR9JKOHTuG65y169OnE1j2r+Lri97x4HpGifpXqFfl1z2GuXb5BTGws/Qd1Z9ve1dSp0pRnIWEULV6IEWMG4N62Pzo6sGHHck6fvIDfnXsoFApmzZ/EyMGTSUxM1EJvkymNDHh5J4iAHWeovXbwP9a3+aoIIWduc33WL8S9jsKtTU1qbxjG799PIsLnEQbmuanyUw8uDF3Fm0fh1Nk0jJDzPjw9fgOAyjO74DVzJ/Fv32Vux8QntfihETNnjWXwoAlcu3qDfv27svfXjZQvW5fn4S9S1DcyNOThwyD27zuMx+zxKbZbWJqzZJkHfXuP4GHgY37Zu4Yzpy7yxx/JH67mL5zGpIlzePPmbab37e/k1H7Xa1KHIZMH4DFqHrev36Fdz1Ys2T6PH6q35+Un/n4D2DrkY9DEfnhduqFR7lbUlT4juzO40yh0dHRYsGk2l05f5b7fAxQKBWNnD2PGiJ+y9PfaxFmLCHjwEI+Jw7GxsuS3I3/Sc9BYft26irzWVpw6sFWj/tlL15josZB6tar9bbtuBZxYs+h9IvVhgnTq3CUOHTvF6gUzCHoSzISZC6hWuTzmZnl48zaKxas3smbhzNSa/WIlyTSnNJOvwlPRqtcPHNp+mD92HeHRvSDmj15ITEws37Vt8OmdVCoiwl+qHy+fv1JvcnR15IFvINcv3MDr/HXu+z7A0TU/AG36tMH78k38vf0/0bAQmaNnP3e2bdrNrm37ued/n9FDp/AuOoa2HVukWv/HXqPYuHYHPrf9uH8vkOEDJ6Kro0v1r78CwK1gAXx97nL+7GXOnbmMr89d3AoWAKDvwK5cunAN7+u3s6x/qQk+eZMbc3bz+I9raap/bdIWfFYc4oX3A94EhnJ91i7eBD7DoV5ZAHI72RD/JpqHBy7zwvsBoRd8MXOzB8C5aRVUCYkE/Z62Y4nMMeDH7mxcv5Otm3fj7xfA4IHjeffuHZ06t0q1vpfXTSaMm8We3QeJjY1Lsb2Ac35ev37D3j2H8PK6yZnTlyhUxBWAlq0aEx8fz28HjmRqn9Iip/a7Q+827N/6G7/tPEzg3Yd4jJxLzLsYmrRr9Ml9dHV1mb5sIqvnruPpoxCNbc5ujty7c59r5724es6TAN/7OLs5AtCpXzu8Lntzx9svU/v0oZjYWI6fPsfQ/t2pUKYkjg529O/eEUcHO3buOwSAlaWFxuPk2UtUKleK/Pa2f9u2QqHQ2M/cLI9624NHj6lYtiQlihbiu3q1MDY24knIMwDmL19Lm2aNsM1nk3kdF581SSY+otRTUrhkITzPeqnLVCoVnme9KFau2Cf3MzQ2ZMelrey6so3pa6fiXMhJve2BXyAOLvbY2NmQ196G/AUcCPR/iJ2TLQ3bfMvaOesztU9CfExPT49SZYpx9tRFdZlKpeLc6UuUr1g6TW0YGuVCqafk1atIAHzv3KOAmzN2DrbY57fFxc0JP98AnJzz06Z9c+bMWJwpfclSOjro5c5F7KsoAN4EPkNhaIBFcSf0zYyxLO3CS98g9PMYUWZESy6P36jlgHM2PT09ypQtwcmT59VlKpWKUyfPU6lS2XS1ef/+QwwNc1GqdDHMzfNQrnwpfG77YWZmyvgJQxg+dHLGBP8f5NR+K/WUFClViMtnPdVlKpWKK2evUap88U/u12NoFyJevOTX7YdSbAvwe4CjS37y2tuQzyEvji75ue8fiL2THY3bfMeKWT9nSl8+JTEhkcTEJAz09TTKDQz08brpk6L+84iXnLlwhRbff/uPbQc9eUrtJh1o0KoroybPJuRZmHpbYTcXfPzuEfn6DT5+94iNjcXR3g4v79vc8Q+gQ6sm/71z4osl05w+ksciDwqlgojwlxrlL5+/xNEtf6r7BN1/zOxhc3ng+wBjU2Pa9G7F0v2L6fpNd8JDnhMUEMSaWeuYu302AD/PWktQQBDzts9h1YzVVKpVgS5DOpOQkMiSScu4eflWpvdT5GwWlmYolcoU0x3Cw1/g+tdowj8ZN3kYoc/C1AlJwN0HzJ62kB17k/+4zpq6kIC7D9ixbw3TJ82jVp3qDB3dj4T4BCaO8eDyBc+/a/6zVLzPdyiNcvHot8sAxEVGc37wKqot6oMilz4Pdp8j+PQtqsztgf+Go+TOb02d9UPRUSrwnr+XoENXtdyDnMXS0hylUkl42HON8rCw5xQq5JquNl+9ek2fXiNY9fM8DHMZsGPbPk4cP8vS5bNYvWozTs4O7PhlNXp6SjxmLObX/b9nRFf+lZzabzOLPCiVSiLCNadpRoS/xNnNKdV9SlcqSdN2jWhfr1uq2x/ee8TyWatZvmMBAMs8VvHw3iOW7VzA4ukrqFKrMr2GdyUhPoG5Exdz/ZJ3xnbqI8bGRpQuUZSVG7bj4uSIpYUZh4+fxvu2H46pjDwc+P04RkaG1K3591OcShUrzPRxw3B2dOD5iwiWr9tK534j2L95BcbGRlSrXJ7vv61D2x6DyGVgwIzxwzAyzMW0ucuYPm4oO/cdYtvuA5iZ5WHyyIG4uaT+8/6SqOSmdWkmyUQGuOPlyx0vX/Xz29d82HRqHY07fM+6uRsAOLDlIAe2HFTX+bZlPaKjovHxvMPm0xvo/X1/rG2tmLhsHO2qdiI+Lj6ruyFEmvUf3IMmLRrSqnEXjSkRm9fvYvP6Xernrdo25e3bKDyvenPm6kEa1WmDrV0+lq+ZS5Uy9Yn7gl7nBZpVodTQ5pzqtoCYF6/V5Y//uKYxbSrvV0UwL+rIlfGbaH5+Hmf7L+NdeCTfHZxC2CV/jX3Fl+ngb0c5+NtR9fNq1StRokQRRgybzI1bJ+nWZRChoeGcPL2f8+evpHqNwpcou/XbyNiQqUvGM2PEHCIjIj9Zb8+mX9mz6Vf180atGhAdFc2ta7fZc24rnRv2wsbWmpkrJtOkcutM//vtMWE4Ez0WUKdZRxQKXYoWcqNh3Zrc8Q9IUXffwaN8X782Bgb6f9tmjSoV1f8u7FaAksUKU/8Hd/748yw/NE4e1ejfvSP9u3dU11u+bitfVSiDUqlk1cYd7Nu0nNMXrjB2+lx2rVuSQb0VXwJJJj4SGRFJYkIiFtbmGuXmVuZEhL38xF6aEhMSuXc7AHtnu1S35zE3xX1IZwa1HELRskV5HPiEp4FPeRr4FKWeEgcXBwL9Av9zX4T4lIgXr0hISMDK2lKj3NraMsW3mR/rPaAL/Qd3p22zHvj63P1kPXMLM4aM6ssPjdwpW6EUDwIeEfggiMAHQejpKXFxc8bvzr0M6U9mc27yFVXm9uB07yWEnE05leD/dPWVVJ7ZhXMDV2JSIC86Sl1CLyXPp3794BlW5Vx5cux6VoWd47148ZKEhASsbaw0ym1srAgNDc+QY+jr6zN/wVR69RyGi6szSqWC8+euAHA/IJAKFUrzx+9//kMrGSun9vtVRCQJCQlYWFtolFtYm/MiLGVi4+Bsj72jHfM3zlKX6eomz/6+9PgkP1TvwNNHwRr75LHIQ89hXenVfAAlyhUj6MFjHgc+4XHgE5R6yuRpUH4PMqF37zk62LFh2U9Ev4shKioaaysLhk3wwMEun0Y9zxu3CQx6wk9Tx/zrY5ia5MYpvz1BT4JT3f7g0WMOHvmT3euXsvfQUSqUKYGFuRnf1vmaCTMXEBUVjbGxUbr6J748cs3ERxLiE/C/dZdy1cupy3R0dChfvSx3vO6kqQ1dXV1cihTgRVjKFXEA+k/uyy9r9hAe8hxdhS5K5fucTqFQoNCV0yIyV3x8PDdv3KF6za/UZTo6OlT/ujKeVz89TN93YDcGj+hDx5a9uXnj0x+qAabMHMXPyzcREhyKQlcXPb0PXudKBQpd7S0R+284N61C1fm9ONtvGU9P3PjbuqUGNePpqZtE3H6Irq4uuh+shqKrp0BH3ttZKj4+nhvXb1OrVlV1mY6ODjVrVeXKlYxJ6kaO6s/x42fwvuGDQqGLUvH+da7UU2plKeSc2u+E+AT8bt6lUvX3Sz7r6OhQsXp5bnqm/H31MCCINrU606FuN/XjzNHzXDt/nQ51uxEaHJZin2FTfmT76l2EhYSn/vc7C5d4NzLMhbWVBZGv33Dhiid1anylsX3vwSMUK1yQIgVd/nXb0dHvePw0BGsrixTbVCoVU+csZuSPPTEyMiQpMYn4hAQAEv76f2LSl786pUql+mwfnxsZmUjFL6v3MGbBSPy9/fG94U/LHi3IZZiL33f+AcCYhaN4/uw5P89aC0DnwR254+XL04fB5DY1pm2f1uR1yMuh7YdTtF2+RjkcXBzwGDwHAH9vfxzd8lOpdkVs7GxISkoi6MHjrOusyLF+Xr6RBctncvO6D9e9btGzbycMjQ3ZuXUfAItWzCQkJIxZUxcC0G9Qd4aPGcCAniN5HBSs/tYzKiqa6KhojbZr1KpCAVdnBvUdC4D39du4FixA7brVsbO3JSkxifsBWT/6pjQywKRAXvXz3I7WmBd3JO5lFFHBLyg7ujVGtuacH7QKSJ7aVG1hb65O2kL49fvksk5e3SQxJo74N5rLveYpaIdzk8ocrJ+8rGbk/WBUKhVubWvyLjySPK62PPfO3G8sRUpLl6xl5eq5XL9+i2vXvOnXvytGRkZs2Zy85v6qn+cSHBzKlEk/AckXLxcp6gaAvr4etnZ5KVmqKFFvo3nw4JFG24WLuNHih++pXvV7AO763ycpKYlOnVsTFhpOoUKueHnezMLevpdT+7111U4mLxrLHW8/fG740r5nKwyNDPltR/Lf4ymLxxH27DnLZq4iLjaO+/6av4feRCYvbftxOUDlryvg6JKfSQNnAHDnhh9Obk5UrVOZvHY2JCUl8uh+UCb3EM5f9kSlUuHs6EDQk2DmLVtLAUcHmjWqr67zNiqKoyfPMnxAz1Tb6D5wNN98XZX2LZMvnP5p6c/UqlYZu3x5CXv+gmVrtqBQ6PJd3Zop9t3z2x+Ym+WhVvXk5KVsqWIsX7cF79u+nL10DVdnR0w/g/uNiKwjyUQqTv52CjPLPHQd3gULa3MC7txnZKcx6uVe89rboPog6zbJY8LwOUOxsDbnbeRb/G/do3/TQTy6p/lLRT+XPoOm/8jUvtPVmWV4yHMWT1jK6HkjiIuLx2PwHOJiUi7LJ0RGO7DvDyysLBg+dgDWNlb43PKjY8ve6nnOdg62JCW9/wakc7c2GBjo8/OmhRrtzJu1jPmzl6uf58plwIw54+jbbbj6dR4SHMqEUTOZv3QGcXFxDO43lpiY2Mzv5EcsS7vw7e73N9uqODl5/m/ArjNcGLIaw7xmGNu9nxpSsEMddPWSpy5VntlFXf7/+h+qMqc7V6dsJeFdcr8SY+I5P2QVlWd0QaGv5PL4Tbx7lrapkiLj7N1zCCsrC8aOH0LevFbcuunLD826qKfzOTjYkfTB73NbWxvOX3y/qs+gwb0YNLgXZ89colHD9hptL14yk7GjZxAdnZxYxsTE0rf3SOYumIKBgT7Dh04iJCQ0C3qZUk7t97EDf2JuaUafkd2xtLbgrk8AP7YfTsTz5PdePvu8Gr/X0soglz4jZwxhTJ9J6t9rYSHh/DR+IRMXjCE+Lp5JA2cSmwV/v9+8jWLhyvWEhj8nj6kJ9WpWZ2Bvd/Q+GCX5/fhpVCr4rl6tVNt4/DSEl5Hvr98KDXvOyEmzefX6NRZmeShbqjhbVy3AwtxMY7/nES9ZvXEHW1bOV5eVLFYY97Yt6DdiEhbmZswcPyxD+ys+fzqqz3G85D+q5VBX2yFoxbkw33+uJLKNvMZm2g5BKzyM0re05ZeuW/hJbYegFUZ6BtoOQWShQqb22g5BKy7eypnLSOtZ/fspWFnFOk9hbYfwSeGRn9e9ybQ6MhESEsKKFSs4d+4cISEhydcauLjQrFkzunTpopU5l0IIIYQQQoi00drVgNeuXaNo0aIcPnyY+Ph47t27R/ny5TE2Nmb48OF8/fXXvHnz5h/biY2N5fXr1xqPJNWXf+GPEEIIIYQQnzutJRODBw9myJAhXLt2jbNnz7Jhwwbu3r3Ljh07ePDgAdHR0YwfP/4f2/Hw8CBPnjwaj6A3DzO/A0IIIYQQIlvS9opNX9JqTlpLJry8vOjUqZP6efv27fHy8iI0NBRzc3PmzJnD7t27/7GdMWPGEBkZqfFwNHHOxMiFEEIIIYQQoMVrJmxsbAgJCcHFJfnim9DQUBISEjA1NQWgYMGCRESkfp+GDxkYGGBgoHmBnq6OrOUuhBBCCCFEZtPap+5mzZrRp08f/vjjD06ePEmHDh2oWbMmhoaGAPj7+2Nv/2Ws6tBlaGdOPTmu8dh0ap22wxIiQw0Y0oNDJ3biH3QF77tnWLtlMa5uztoOK8PZVC5M7Q1Daem5hM5Pt5D/2w9ugKVUUG5sGxof96DdvTW09FxCtUW9Mcxrpr2ARYaqWq0iO3/5Gf+Ai7yOekCj7+tpO6QskVP7/TH3AR24FnKWoVN/zNLjRkVFM2vhSuq1cKd87aZ06D2UW77vV+yJjn7HjHnL+aZZR8rXbkqTDr3Yue9Qqm2pVCr6DJtAiWoNOXHmQortwc9CKV+7KdHR7wh48IjBY6dT/wd3SlRryOad+1Jtc/ue36j/gzvlajehXc/B3LqjuZpQbGwc0+cto1rD1lSs25zBY6fzPEJzKexL167TofdQKtVtQc3G7Zm/fK36JnefoySV6rN9fG60lkxMnz6dYsWK0bhxY7755htiY2NZt+79B3AdHR08PDy0Fd6/FugXSIuyrdSPH5sP1nZIQmSor6pWZOOa7TSu3452LXqip6dk296fMTQy1HZoGUppZMDLO0FcHpdyqUaloT4WJZ25uWg/hxpM4FTPhZi62FJ7/VAtRCoyg7GxEbdv+TJsyCRth5Klcmq/P1SsdBFadGrCXZ+ALD/2xFmLuHj1Oh4Th7Nv8wqqVipHz0FjCQ1Pvi/InCWrOXf5Gh4TR3Jg22o6tW7GzAXLOXn2Uoq2Nu/cj87fHOvPs5eoVK4URkaGvIuNwcEuH4P7dsXK0jzV+r8fP82cJavp260Dv6xbQmG3AvQeOp4XL1+p68xevIpT5y8zf/pYNiydQ/jzFwweO1293e/eA/oOn0j1yuXZvWEpc6eO5uS5y8ybNy9dPy/xedHaNKfcuXOzc+dOYmJiSEhIIHduzbsl1q9f/xN7fp4SExOJCJcbUonsq2Or3hrPB/cbx62Ac5QqU4zLFzy1FFXGCz55k+CTqd+9N/7NO463m61RdmX8JhodnoqxnSVRwS+yIkSRiY4dPc2xo6e1HUaWy6n9/j9DI0OmLZvIjOFz6D7YPUuPrULF8dPnWDxrEhXKlASgf/eOnD5/mZ37DjGwlzs3bvnStGFdKpUrBUCrpt/xy6+/c8vXn9o1vlK35Xf3Pht37GHn2sXUatIh1eOdPHuR+rVrAFCyaGFKFk2+n8LCFetTrb9p5z5aNm5I87/usD1xxI+cuXCVfQeP0qNTa968jWLvwaPMmTySyuXLADBt3FCatO+F921fSpcoyh8nzlDItQB9uyXH5Ohgx7B+3Rg2cRb9+/dP8RlQfFm0fnFBrly5ssWLyL6APbuv7WDb+c2MWzIGGzsbbYckRKYyNTUB4NXLSC1Hol36poaokpKIex2t7VCEEOk0ymMI509c5MpZbXwxoiIxMQkDfT2NUgMDfbxu+gBQpmRRTp67RGj4c1QqFVc8vXkY9JSqlcqp67+LiWHklNmMG9YfK0uLVI/0+s1bvG76ULv6V6lu/1h8fDx3/O/xVcUy6jJdXV2+qlAG79vJN8q943+PhIQEvqrw/oaiLk75sc1rg/dtP3U7Bvr6H/XPgNjYWHx8fNIUS1bT9opNsppTDnPnui+zhvzEyE5jWDB2Ebb587F47wIMjbPX9A8h/k9HR4cpHqO4cskLf9+snxLwudA10KPc2LYE7r9I/Nt32g5HCJEO9Zt+Q5GShVg6c5VWjq+DLqVLFGXlhu2Ehb8gMTGR3478ifdtP54/T16IZuyQvrg6O/JNs06UrdmY3sPGM25YP/VIBsCcxaspU6IYdWpU+eSxzl68SiHXAthYW6YptpevXpOYmISlheYUKEsLc/U1Ec9fvERPT4mpSe6P6pjx/K+FdKpWKseN274cPnaKxMREQsOfs3L9NgDCw8PTFIv4fGn1DtjZxZWTV9X/fuAbiO91X3Zc2kbtxjU5vOMPLUYmROaYOXc8hYsWpHnDTv9cOZvSUSqoufJH0NHh8pgN2g5HCJEOee1sGDZtIP3bDCUuNk5rcXhMGM5EjwXUadYRhUKXooXcaFi3Jnf8k7+s2br7ADd9/Fg6exK2+fLieeMWM+Ytx8bKkioVy3Ly7CUue3qze/3Svz3On2cvpXlUIiNVq1yeYf27M/WnJYyZ9hP6enr07tIeT+/b6OrK99pfOkkmMsHb11E8efAEe+cvYzUqIf6N6XPGUffbmrT4zp2Q4FBth6MV/08kjB0sOdbaQ0YlhPhCFSlVGEtrC7YcXaMuUyqVlP2qNK27tqCq0zckJSVlehyODnZsWPYT0e9iiIqKxtrKgmETPHCwy0dMbCyLVm1kkccEalatBEBhtwL43XvAhu17qFKxLJc9b/D4aQhVGrTUaHfIuBmUK12cDUvnEB8fz/nL1+jZuU2a4zI3M0Wh0OXFRyszvYh4idVfoxVWlubExyfw+s1bjdGJFxGvsLJ4P93KvW0LOrdpTvjzCExNc/M0JJSFK9fj4ODwr39eWSGJz2860edKkolMYGiUCztnW47ulYsxRfYyfc44GjT6hlaNu/A46Km2w9GK/ycSJgXycrTVTGJfvtV2SEKIdLp69hptanXWKJu4cAyPAoLYuHRrliQSHzIyzIWRYS4iX7/hwhVPhvbrRkJCAgkJCejqaK7RpFDoquPr0ak1PzRpoLG9eae+jBzYi1rVKgNwxesmpia5KVLQJc3x6OnpUaxwQS5fu8E3X1cFICkpicueN2j3QxMAihUuiFKp5PK1G9SrXR2AwEdPCAkNo3SJIhrt6ejoqKdY/X7sFLa2thQvXjzN8YjPkyQTGaDv+F5cOH6J0CehWOa1pOswd5ISkzix/6S2QxMiw8ycO4FmLb+jW/sfefs2GmsbKwDevH5DTEyslqPLOEojA0wK5FU/z+1ojXlxR+JeRhEd9opaqwdiUdKZP93noaPQJZd1HgDiXr0lKT5RW2GLDGJsbISLq5P6ubNzfkqWKsrLiEiePAnWYmSZK6f2OzrqHff9AzXKYqJjePUyMkV5Zjp/2ROVSoWzowNBT4KZt2wtBRwdaNaoPnpKJRXKlmTesrUYGBhgl8+Ga9dvceD3E4wY2BMAK0uLVC+6ts1rjYNdPgBOnbtMrY+mOMXHx3M/MOivfycQGv4Cv7v3MTIyxNHBDoDObZozbsY8ihcpSIlihdmyaz/vYmJp1ij5XiQmuY1p8X195iz5mTymJhgbGzFzwQpKlyhK6RJF1cdat3U31b8qj66OLsdPn2fNll9YtGgRCoUi43+gIktJMpEBrG2tmbB0LKbmpkRGRHLrym36NfmRyIicvcqNyF7cu7cFYM8hzfsvDOk3jl3b92shosxhWdqFb3ePUz+vOLkjAAG7zuA9b6/6JnaNj83U2O9IyxmEXvTNukBFpihbriSH/9iufu4xezwAW7fspm/vkdoKK9Pl1H5/Lt68jWLhyvWEhj8nj6kJ9WpWZ2Bvd/SUyR/T5k4ZzcKVGxg9ZQ6Rr99gl8+Ggb3dadOsUZqPcfL8JaaNGaJRFvY8gpZdB6ifb9i+hw3b91ChbEk2LJ0DQMO6NXn5KpKla7bwPCKCIgVdWTlvmnqaE8Cogb3R1dVl8LjpxMfHU7VSeSYM769xrHOXrvHzph3ExcVT2K0AS2ZNpE7duv/6Z5VVPsdVkz5XOqps+NOq5fD5vjgz07kw+SCTk+Q1NtN2CFrhYVT2nytlQ93Cc+ZIp5GegbZDEFmokGnOvNbw4q2UN8nMSHf8A+g+cDRnDu1QJyifAz2rtE+5ymqmxp9vbK+jHmg7BA1yCb0QQgghRDaWmJjImCF9P6tEQmQf8qoSQgghhMjGShYrTMlihbUdxhclKftN3Mk0MjIhhBBCCCGESBdJJoQQQgghhBDpItOchBBCCCGE+IBKblqXZjIyIYQQQgghhEgXSSaEEEIIIYQQ6SLTnIQQQgghhPiArOaUdjIyIYQQQgghhEgXSSaEEEIIIYQQ6SLTnIQQQgghhPiASqY5pZmMTAghhBBCCCHSRZIJIYQQQgghRLrINCchhBBCCCE+IDetSzsZmRBCCCGEEEKkiyQTQgghhBBCiHSRaU5CCCGEEEJ8QFZzSjsZmRBCCCGEEEKkiyQTQgghhBBCiHSRaU5CCCGEEEJ8QKY5pZ2MTAghhBBCCCHSRZIJIYQQQgghsqlly5bh7OxMrly5qFy5MleuXMnQ9iWZEEIIIYQQ4gOqz/jxb+zcuZOhQ4cyadIkvLy8KF26NN9++y1hYWH/sqVPk2RCCCGEEEKIbGj+/Pn07NmTrl27UqxYMVauXImRkRHr1q3LsGNIMiGEEEIIIcQXIjY2ltevX2s8YmNjU9SLi4vD09OTunXrqst0dXWpW7cuFy9ezLiAVCLDxMTEqCZNmqSKiYnRdihZSvot/c4JpN/S75xA+i39Fp+/SZMmpZj9NGnSpBT1nj59qgJUFy5c0CgfMWKEqlKlShkWj45KJWtfZZTXr1+TJ08eIiMjMTU11XY4WUb6Lf3OCaTf0u+cQPot/Rafv9jY2BQjEQYGBhgYGGiUBQcHY29vz4ULF6hSpYq6fOTIkZw+fZrLly9nSDxynwkhhBBCCCG+EKklDqmxsrJCoVAQGhqqUR4aGkq+fPkyLB65ZkIIIYQQQohsRl9fn/Lly3PixAl1WVJSEidOnNAYqfivZGRCCCGEEEKIbGjo0KG4u7tToUIFKlWqxMKFC4mKiqJr164ZdgxJJjKQgYEBkyZNStPQU3Yi/ZZ+5wTSb+l3TiD9ln6L7KVNmzaEh4czceJEnj17RpkyZfjjjz/Imzdvhh1DLsAWQgghhBBCpItcMyGEEEIIIYRIF0kmhBBCCCGEEOkiyYQQQgghhBAiXSSZEEIIIYQQQqSLJBMZaNmyZTg7O5MrVy4qV67MlStXtB1Spjpz5gyNGzfGzs4OHR0d9u/fr+2QsoSHhwcVK1bExMQEGxsbmjVrhr+/v7bDynQrVqygVKlSmJqaYmpqSpUqVfj999+1HVaWmzVrFjo6OgwePFjboWSqyZMno6Ojo/EoUqSItsPKEk+fPqVjx45YWlpiaGhIyZIluXbtmrbDylTOzs4pzreOjg79+/fXdmiZKjExkQkTJlCgQAEMDQ1xdXVl2rRp5IS1ad68ecPgwYNxcnLC0NCQqlWrcvXqVW2HJb5AkkxkkJ07dzJ06FAmTZqEl5cXpUuX5ttvvyUsLEzboWWaqKgoSpcuzbJly7QdSpY6ffo0/fv359KlSxw7doz4+Hjq169PVFSUtkPLVA4ODsyaNQtPT0+uXbtGnTp1aNq0KT4+PtoOLctcvXqVVatWUapUKW2HkiWKFy9OSEiI+nHu3Dlth5TpXr58SbVq1dDT0+P333/nzp07zJs3D3Nzc22HlqmuXr2qca6PHTsGQKtWrbQcWeaaPXs2K1asYOnSpfj6+jJ79mzmzJnDkiVLtB1apuvRowfHjh1j8+bN3Lp1i/r161O3bl2ePn2q7dDEl0YlMkSlSpVU/fv3Vz9PTExU2dnZqTw8PLQYVdYBVPv27dN2GFoRFhamAlSnT5/WdihZztzcXLVmzRpth5El3rx5oypYsKDq2LFjqpo1a6oGDRqk7ZAy1aRJk1SlS5fWdhhZbtSoUarq1atrOwytGzRokMrV1VWVlJSk7VAyVaNGjVTdunXTKGvRooWqQ4cOWoooa0RHR6sUCoXq4MGDGuXlypVTjRs3TktRiS+VjExkgLi4ODw9Palbt666TFdXl7p163Lx4kUtRiayQmRkJAAWFhZajiTrJCYmsmPHDqKioqhSpYq2w8kS/fv3p1GjRhrv8+zu3r172NnZ4eLiQocOHQgKCtJ2SJnuwIEDVKhQgVatWmFjY0PZsmX5+eeftR1WloqLi2PLli1069YNHR0dbYeTqapWrcqJEye4e/cuAN7e3pw7d46GDRtqObLMlZCQQGJiIrly5dIoNzQ0zBEjkCJjyR2wM8Dz589JTExMcTfBvHnz4ufnp6WoRFZISkpi8ODBVKtWjRIlSmg7nEx369YtqlSpQkxMDLlz52bfvn0UK1ZM22Fluh07duDl5ZWj5hNXrlyZDRs2ULhwYUJCQpgyZQo1atTg9u3bmJiYaDu8TPPgwQNWrFjB0KFDGTt2LFevXmXgwIHo6+vj7u6u7fCyxP79+3n16hVdunTRdiiZbvTo0bx+/ZoiRYqgUChITExkxowZdOjQQduhZSoTExOqVKnCtGnTKFq0KHnz5mX79u1cvHgRNzc3bYcnvjCSTAjxH/Tv35/bt2/nmG9yChcuzI0bN4iMjGT37t24u7tz+vTpbJ1QPH78mEGDBnHs2LEU3+JlZx9+M1uqVCkqV66Mk5MTu3btonv37lqMLHMlJSVRoUIFZs6cCUDZsmW5ffs2K1euzDHJxNq1a2nYsCF2dnbaDiXT7dq1i61bt7Jt2zaKFy/OjRs3GDx4MHZ2dtn+fG/evJlu3bphb2+PQqGgXLlytGvXDk9PT22HJr4wkkxkACsrKxQKBaGhoRrloaGh5MuXT0tRicw2YMAADh48yJkzZ3BwcNB2OFlCX19f/a1V+fLluXr1KosWLWLVqlVajizzeHp6EhYWRrly5dRliYmJnDlzhqVLlxIbG4tCodBihFnDzMyMQoUKERAQoO1QMpWtrW2K5Lho0aLs2bNHSxFlrUePHnH8+HH27t2r7VCyxIgRIxg9ejRt27YFoGTJkjx69AgPD49sn0y4urpy+vRpoqKieP36Nba2trRp0wYXFxdthya+MHLNRAbQ19enfPnynDhxQl2WlJTEiRMncsx88pxEpVIxYMAA9u3bx59//kmBAgW0HZLWJCUlERsbq+0wMtU333zDrVu3uHHjhvpRoUIFOnTowI0bN3JEIgHw9u1b7t+/j62trbZDyVTVqlVLsdTz3bt3cXJy0lJEWWv9+vXY2NjQqFEjbYeSJaKjo9HV1fwopFAoSEpK0lJEWc/Y2BhbW1tevnzJkSNHaNq0qbZDEl8YGZnIIEOHDsXd3Z0KFSpQqVIlFi5cSFRUFF27dtV2aJnm7du3Gt9SBgYGcuPGDSwsLHB0dNRiZJmrf//+bNu2jV9//RUTExOePXsGQJ48eTA0NNRydJlnzJgxNGzYEEdHR968ecO2bds4deoUR44c0XZomcrExCTF9TDGxsZYWlpm6+tkhg8fTuPGjXFyciI4OJhJkyahUCho166dtkPLVEOGDKFq1arMnDmT1q1bc+XKFVavXs3q1au1HVqmS0pKYv369bi7u6NU5oyPB40bN2bGjBk4OjpSvHhxrl+/zvz58+nWrZu2Q8t0R44cQaVSUbhwYQICAhgxYgRFihTJ1p9bRCbR9nJS2cmSJUtUjo6OKn19fVWlSpVUly5d0nZImerkyZMqIMXD3d1d26FlqtT6DKjWr1+v7dAyVbdu3VROTk4qfX19lbW1teqbb75RHT16VNthaUVOWBq2TZs2KltbW5W+vr7K3t5e1aZNG1VAQIC2w8oSv/32m6pEiRIqAwMDVZEiRVSrV6/WdkhZ4siRIypA5e/vr+1Qsszr169VgwYNUjk6Oqpy5cqlcnFxUY0bN04VGxur7dAy3c6dO1UuLi4qfX19Vb58+VT9+/dXvXr1StthiS+QjkqVA27zKIQQQgghhMhwcs2EEEIIIYQQIl0kmRBCCCGEEEKkiyQTQgghhBBCiHSRZEIIIYQQQgiRLpJMCCGEEEIIIdJFkgkhhBBCCCFEukgyIYQQQgghhEgXSSaEEEIIIYQQ6SLJhBBCfGa6dOlCs2bN1M9r1arF4MGDszyOU6dOoaOjw6tXr7L82EIIIb4MkkwIIUQadenSBR0dHXR0dNDX18fNzY2pU6eSkJCQqcfdu3cv06ZNS1NdSQCEEEJkJaW2AxBCiC9JgwYNWL9+PbGxsRw+fJj+/fujp6fHmDFjNOrFxcWhr6+fIce0sLDIkHaEEEKIjCYjE0II8S8YGBiQL18+nJyc6Nu3L3Xr1uXAgQPqqUkzZszAzs6OwoULA/D48WNat26NmZkZFhYWNG3alIcPH6rbS0xMZOjQoZiZmWFpacnIkSNRqVQax/x4mlNsbCyjRo0if/78GBgY4Obmxtq1a3n48CG1a9cGwNzcHB0dHbp06QJAUlISHh4eFChQAENDQ0qXLs3u3bs1jnP48GEKFSqEoaEhtWvX1ohTCCGESI0kE0II8R8YGhoSFxcHwIkTJ/D39+fYsWMcPHiQ+Ph4vv32W0xMTDh79iznz58nd+7cNGjQQL3PvHnz2LBhA+vWrePcuXNERESwb9++vz1m586d2b59O4sXL8bX15dVq1aRO3du8ufPz549ewDw9/cnJCSERYsWAeDh4cGmTZtYuXIlPj4+DBkyhI4dO3L69GkgOelp0aIFjRs35saNG/To0YPRo0dn1o9NCCFENiHTnIQQIh1UKhUnTpzgyJEj/Pjjj4SHh2NsbMyaNWvU05u2bNlCUlISa9asQUdHB4D169djZmbGqVOnqF+/PgsXLmTMmDG0aNECgJUrV3LkyJFPHvfu3bvs2rWLY8eOUbduXQBcXFzU2/8/JcrGxgYzMzMgeSRj5syZHD9+nCpVqqj3OXfuHKtWraJmzZqsWLECV1dX5s2bB0DhwoW5desWs2fPzsCfmhBCiOxGkgkhhPgXDh48SO7cuYmPjycpKYn27dszefJk+vfvT8mSJTWuk/D29iYgIAATExONNmJiYrh//z6RkZGEhIRQuXJl9TalUkmFChVSTHX6vxs3bqBQKKhZs2aaYw4ICCA6Opp69epplMfFxVG2bFkAfH19NeIA1ImHEEII8SmSTAghxL9Qu3ZtVqxYgb6+PnZ2diiV73+NGhsba9R9+/Yt5cuXZ+vWrSnasba2TtfxDQ0N//U+b9++BeDQoUPY29trbDMwMEhXHEIIIQRIMiGEEP+KsbExbm5uaapbrlw5du7ciY2NDaampqnWsbW15fLly3z99dcAJCQk4OnpSbly5VKtX7JkSZKSkjh9+rR6mtOH/j8ykpiYqC4rVqwYBgYGBAUFfXJEo2jRohw4cECj7NKlS//cSSGEEDmaXIAthBCZpEOHDlhZWdG0aVPOnj1LYGAgp06dYuDAgTx58gSAQYMGMWvWLPbv34+fnx/9+vX723tEODs74+7uTrdu3di/f7+6zV27dgHg5OSEjo4OBw8eJDw8nLdv32JiYsLw4cMZMmQIGzdu5P79+3h5ebFkyRI2btwIQJ8+fbh37x4jRozA39+fbdu2sWHDhsz+EQkhhPjCSTIhhBCZxMjIiDNnzuDo6EiLFi0oWrQo3bt3JyYmRj1SMWzYMDp16oS7uztVqlTBxMSE5s2b/227K1asoGXLlvTr148iRYrQs2dPoqKiALC3t2fKlCmMHj2avHnzMmDAAACmTZvGhAkT8PDwoGjRojRo0IBDhw5RoEABABwdHdmzZw/79++ndOnSrFy5kpkzZ2biT0cIIUR2oKP61FV+QgghhBBCCPE3ZGRCCCGEEEIIkS6STAghhBBCCCHSRZIJIYQQQgghRLpIMiGEEEIIIYRIF0kmhBBCCCGEEOkiyYQQQgghhBAiXSSZEEIIIYQQQqSLJBNCCCGEEEKIdJFkQgghhBBCCJEukkwIIYQQQggh0kWSCSGEEEIIIUS6/A8jv+jawj5/GAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -1103,7 +1101,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1113,7 +1111,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1123,7 +1121,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1332,7 +1330,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "tags": [] }, @@ -1375,7 +1373,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -1424,12 +1422,12 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1439,7 +1437,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1499,14 +1497,14 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1516,7 +1514,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1579,12 +1577,12 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1594,7 +1592,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1604,7 +1602,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABH8klEQVR4nO2dd3xUZdbHf5M2k2Qy6RVSIRAIJRA6SAApLtUFF0QWxVcBEXVhFftSlF0FCyoKllVQigJKsyAiAtIJEEjoLaEngUB6n3neP2CGTJ5zw9yQZAJ7vp9lnZw589znPs+9c+be59zf0QghBBiGYRjGRhzs3QGGYRjm7oIDB8MwDKMKDhwMwzCMKjhwMAzDMKrgwMEwDMOoggMHwzAMowoOHAzDMIwqOHAwDMMwquDAwTAMw6iCA8ddTo8ePdCjRw97d0NCo9Fg+vTp9u6GIncybhERERgzZkyN9sfeTJ8+HRqNxt7dkKivx/f/Ohw47IBGo7Hp3+bNm2u1H0uXLsUHH3xQq9uoirS0NMu+zpw5k/QZNWoUNBoN9Hp9Hfeu/tOjRw+bjqPaDuA7duzA9OnTkZ2dXavbsZXs7GwEBARAo9Hg+++/t3d37kmc7N2B/0UWLVpk9fc333yDDRs2SPZmzZrdtq3ffvut2v1YunQpDh06hEmTJlW7jZpAp9Ph22+/xeuvv25lLygowJo1a6DT6ezUs/rNa6+9hieffNLyd2JiIj766CO8+uqrVsdOq1atbtvW66+/jpdffrla/dixYwdmzJiBMWPGwMvLq1pt1CRTp05FYWGhvbtxT8OBww78/e9/t/p7165d2LBhg2S3BRcXl5rqlt3o378/Vq5ciYMHD6J169YW+5o1a1BaWooHHngAf/zxhx17WD/p06eP1d86nQ4fffQR+vTpo/r2jpOTE5yc7v6vg0OHDmH+/PmYOnUqpk6dau/u3LPwrap6yoIFC9CrVy8EBARAq9WiefPmmD9/vuRX+R7w5s2bodFosHz5cvz73/9Gw4YNodPpcP/99+PUqVNWn/v5559x9uxZyy2NiIgIy/slJSWYNm0aGjduDK1Wi9DQULz44osoKSmx2n5JSQkmT54Mf39/eHh4YPDgwbhw4YKqfe3cuTMiIyOxdOlSK/uSJUvwwAMPwMfHh/zcvHnzEBsbC61Wi5CQEEycOJG8XfL555+jUaNGcHV1RYcOHbB161ayPVv32VYKCgrw/PPPIzQ0FFqtFk2bNsW7776LyoLUGo0GzzzzDFavXo0WLVpAq9UiNjYWv/76a7W2W5GtW7fib3/7G8LCwiz7NHnyZBQVFVn5UWsctvRr+vTpmDJlCgAgMjLSciylpaVZfBYvXoz4+Hi4urrCx8cHDz/8MM6fPy/11dZ5qop//OMf+Otf/4r77rtP9WcZ27n7f2Lco8yfPx+xsbEYPHgwnJyc8OOPP+Lpp5+GyWTCxIkTb/v5t99+Gw4ODnjhhReQk5OD2bNnY9SoUdi9ezeAG7c5cnJycOHCBcyZMwcALOsIJpMJgwcPxrZt2zBu3Dg0a9YMKSkpmDNnDk6cOIHVq1dbtvPkk09i8eLFeOSRR9ClSxf88ccfGDBggOr9HTlyJBYvXoy3334bGo0GV69exW+//YZFixaRX6DTp0/HjBkz0Lt3b0yYMAHHjx/H/PnzkZiYiO3bt8PZ2RkA8OWXX2L8+PHo0qULJk2ahDNnzmDw4MHw8fFBaGiopT01+2wLQggMHjwYmzZtwhNPPIG4uDisX78eU6ZMwcWLFy1jbmbbtm1YuXIlnn76aXh4eOCjjz7CsGHDcO7cOfj6+qoeTzMrVqxAYWEhJkyYAF9fX+zZswdz587FhQsXsGLFitt+/nb9Gjp0KE6cOIFvv/0Wc+bMgZ+fHwDA398fAPDvf/8b//rXvzB8+HA8+eSTuHLlCubOnYvu3bsjKSnJcmvL1nm63b7u2LEDR48etQpcTC0gGLszceJEUXkqCgsLJb9+/fqJqKgoK1tCQoJISEiw/L1p0yYBQDRr1kyUlJRY7B9++KEAIFJSUiy2AQMGiPDwcGk7ixYtEg4ODmLr1q1W9k8//VQAENu3bxdCCHHgwAEBQDz99NNWfo888ogAIKZNm1blfqempgoA4p133hGHDh0SACzb/OSTT4RerxcFBQXiscceE+7u7pbPZWZmChcXF9G3b19hNBot9o8//lgAEF999ZUQQojS0lIREBAg4uLirMbi888/FwCsxs3WfRZCiPDwcPHYY49VuW+rV68WAMTMmTOt7A899JDQaDTi1KlTFhsA4eLiYmU7ePCgACDmzp1b5XYqsmLFCgFAbNq0yWKjjqO33npLaDQacfbsWYtt2rRp0jFoa7/eeecdAUCkpqZafT4tLU04OjqKf//731b2lJQU4eTkZLGrmSclCgsLRVhYmHjllVeEELfOgxUrVtz2s4x6+FZVPcXV1dXyOicnB1evXkVCQgLOnDmDnJyc237+8ccft1r/MF+6nzlz5rafXbFiBZo1a4aYmBhcvXrV8q9Xr14AgE2bNgEAfvnlFwDAc889Z/X56iy2x8bGolWrVvj2228B3Fi4HzJkCNzc3CTf33//HaWlpZg0aRIcHG4dwmPHjoXBYMDPP/8MANi7dy8yMzPx1FNPWY3FmDFj4OnpWa19tpVffvkFjo6O0tg8//zzEEJg3bp1VvbevXujUaNGlr9btWoFg8Fg03xVRcXjqKCgAFevXkWXLl0ghEBSUtJtP38n/Vq5ciVMJhOGDx9uNaZBQUGIjo62jKmaeVLi7bffRllZGV599VWb/Jk7g29V1VO2b9+OadOmYefOnVKGSE5Ozm1PqLCwMKu/vb29AQDXr1+/7bZPnjyJo0ePWm43VCYzMxMAcPbsWTg4OFh9sQBA06ZNb7sNikceeQTvvfceJk+ejB07dih+CZw9e5bcjouLC6Kioizvm/8bHR1t5efs7IyoqCgrm637bCtnz55FSEgIPDw8rOzmbCdz38xUni/gxpzZMl9Vce7cOUydOhVr166V2rLlB8id9OvkyZMQQkjjb8Z8O1HNPFGkpaXhnXfewSeffMJp23UEB456yOnTp3H//fcjJiYG77//PkJDQ+Hi4oJffvkFc+bMgclkum0bjo6OpF3YUCnYZDKhZcuWeP/998n3bb3nrJaRI0filVdewdixY+Hr64u+ffvWynYo7LXPZu5kvpQwGo3o06cPrl27hpdeegkxMTFwd3fHxYsXMWbMmDo5jjQaDdatW0e2U1Nf8lOnTkWDBg3Qo0cPy9pGeno6AODKlStIS0tDWFiY1dUpc2dw4KiH/PjjjygpKcHatWutfvGpvV1yO5SeFG7UqBEOHjyI+++/v8qnicPDw2EymXD69GmrX//Hjx+vVn/CwsLQtWtXbN68GRMmTFBMDw0PD7dsp+Iv0tLSUqSmpqJ3795WfidPnrTccgKAsrIypKamWqX+2rrPthIeHo7ff/8deXl5Vlcdx44ds+pbbZKSkoITJ07g66+/xqOPPmqxb9iwoUa3U9VxJIRAZGQkmjRpovh5NfNEce7cOZw6dYq8Onn66acB3LjSrg/PmNwrcAiuh5h/nVX8VZeTk4MFCxbU6Hbc3d3J2xXDhw/HxYsX8cUXX0jvFRUVoaCgAADwl7/8BQDw0UcfWfncydPoM2fOxLRp0/Dss88q+vTu3RsuLi746KOPrMboyy+/RE5OjiWrq127dvD398enn36K0tJSi9/ChQultF1b99lW+vfvD6PRiI8//tjKPmfOHGg0GsvY1SbUcSSEwIcfflij23F3dwcAaUyHDh0KR0dHzJgxQ7pCEUIgKysLgLp5opg5cyZWrVpl9e/NN98EALz44otYtWqVpY9MzcBXHPWQvn37wsXFBYMGDcL48eORn5+PL774AgEBAbh8+XKNbSc+Ph7Lli3DP//5T7Rv3x56vR6DBg3C6NGjsXz5cjz11FPYtGkTunbtCqPRiGPHjmH58uVYv3492rVrh7i4OIwcORLz5s1DTk4OunTpgo0bN1o9L6KWhIQEJCQkVOnj7++PV155BTNmzMADDzyAwYMH4/jx45g3bx7at29veZDS2dkZM2fOxPjx49GrVy+MGDECqampWLBggfTr1NZ9tpVBgwahZ8+eeO2115CWlobWrVvjt99+w5o1azBp0iRpXag2iImJQaNGjfDCCy/g4sWLMBgM+OGHH+543aQy8fHxAG6keD/88MNwdnbGoEGD0KhRI8ycOROvvPIK0tLS8OCDD8LDwwOpqalYtWoVxo0bhxdeeEHVPFF069ZNspmvLtq3b48HH3ywJneXATgdtz5ApeOuXbtWtGrVSuh0OhERESFmzZolvvrqKyntUSkdt3Iaojn1dcGCBRZbfn6+eOSRR4SXl5cAYJWaW1paKmbNmiViY2OFVqsV3t7eIj4+XsyYMUPk5ORY/IqKisRzzz0nfH19hbu7uxg0aJA4f/686nTcqqicjmvm448/FjExMcLZ2VkEBgaKCRMmiOvXr0t+8+bNE5GRkUKr1Yp27dqJP//8Uxo3NftsSzquEELk5eWJyZMni5CQEOHs7Cyio6PFO++8I0wmk5UfADFx4kTp87ZuxwyVjnvkyBHRu3dvodfrhZ+fnxg7dqwlpbbisaCUjmtrv958803RoEED4eDgIB2jP/zwg+jWrZtwd3cX7u7uIiYmRkycOFEcP37cqg1b58kWOB23dtEIcQerbwzDMMz/HLzGwTAMw6iCAwfDMAyjCg4cDMMwjCo4cDAMwzCqsGvguJNylQsXLpTkm2sac4W6hQsX1to21HI3lNKsXFrVPFd79+6tk+3fDWN0t0GdbxERERg4cGCdbN9cLqC2q2LWNXfrflUrcBw+fBh///vf0aBBA0sthFGjRuHw4cM13T/mDjEajQgJCbFIP1DMmzePDI5HjhzB9OnT66VEdX3uW10wb948aDQadOzYkXy/qvFRmu/6QH3tmxACixYtQvfu3eHl5QU3Nze0bNkSb7zxhuqHQ+8J1Obv/vDDD8LFxUUEBQWJ1157Tfz3v/8Vr7/+uggODhYuLi5i5cqVNrdVVlYmioqK1HZBCCFEeXm5KCoqknLiaxLq2Qd7ozav/bfffhMAREREhBg1ahTpExsbS7ZJPRdgC8XFxaK0tNTy94IFCwQAkZiYqKqdqqiqbyUlJVby3PciXbp0EREREQKAOHnypPR+VeOjNN9VQZ1v4eHhYsCAAWq7XiVKfTMajaKoqMhKRr+uKC8vF8OHDxcAxH333SfmzJkjPvvsM/H3v/9dODg4iBYtWoj09PRqtW1+3kTtOWZvVF1xnD59GqNHj0ZUVBSSk5Mxc+ZMPPHEE3jzzTeRnJyMqKgojB49+raSy+YI7eTkVO160o6OjtDpdDWiK3Qvs3jxYrRt2xaTJ0/G6tWra+3XkRDCUlVOq9ValE/tgYuLyz1RUleJ1NRU7NixA++//z78/f2xZMmSWtuW+Xix9/nm4OAAnU5nF6HC2bNnY/ny5XjhhRfw559/YtKkSRg3bhwWLVqE1atX48iRI1a3Zv8nUBNlxo8fLwCIP//8k3x/y5YtAoAYP368xWZ+IvXw4cNi5MiRwsvLS8TFxVm9V5HCwkLx7LPPCl9fX6HX68WgQYPEhQsXpCeRzb9iKz6hav4FtHXrVtG+fXuh1WpFZGSk+Prrr622kZWVJZ5//nnRokUL4e7uLjw8PMQDDzwgDhw4YOVn6xWHre2Zf10sW7ZMzJw5UzRo0EBotVrRq1cv8lfjZ599JqKiooROpxPt27dX/SRtYWGh8PDwELNnzxaXL18WDg4OYsmSJVY+4eHhAoDVv4SEBMv4Vv5n/mVkHutff/1VxMfHC61WK+bMmWN5r+KTxea2tmzZIsaNGyd8fHyEh4eHGD16tLh27ZpVfyrPc8V+mtu8Xd+oMcrIyBD/93//JwICAoRWqxWtWrUSCxcutPKp+CS7eexdXFxEu3btxJ49e2wa87rgzTffFN7e3qKkpERMmDBBREdHW71f1fgozXfFz23evFlMmDBB+Pv7Cy8vL6v3qPNt/fr1onXr1kKr1YpmzZqJH374wao/1HlOtVlV35R+mS9fvly0bdtW6HQ64evrK0aNGiUuXLhg5WNWHrhw4YIYMmSIcHd3F35+fuL5558X5eXlVY51YWGh8Pb2Fk2aNBFlZWWkz+OPPy4AiJ07d0pjc7vvosr7NXXqVOHk5CQyMzOl7YwdO1Z4enpW+y5NTaIqfP/444+IiIhQrOfbvXt3REREWArpVORvf/sbCgsL8Z///Adjx45V3MaYMWMwd+5c9O/fH7NmzYKrq6uqUqSnTp3CQw89hD59+uC9996Dt7c3xowZY7X+cubMGaxevRoDBw7E+++/jylTpiAlJQUJCQm4dOmSzduqbntvv/02Vq1ahRdeeAGvvPIKdu3ahVGjRln5mEtpBgUFYfbs2ejatSsGDx5M1mpWYu3atcjPz8fDDz+MoKAg9OjRQ/p1+sEHH6Bhw4aIiYnBokWLsGjRIrz22mvo3r27pQjRq6++annPXE8CuKFOO3LkSPTp0wcffvgh4uLiquzPM888g6NHj2L69Ol49NFHsWTJEjz44IOqpcNt6VtFioqK0KNHDyxatAijRo3CO++8A09PT4wZM4YU/Fu6dCneeecdjB8/HjNnzkRaWhqGDh2KsrIyVf2sLZYsWYKhQ4fCxcUFI0eOxMmTJ5GYmGh5v6rxUZrvijz99NM4cuQIpk6dipdffrnKvpw8eRIjRozAX/7yF7z11ltwcnLC3/72t2op8NrSt4osXLgQw4cPh6OjI9566y2MHTsWK1euRLdu3SRxRKPRiH79+sHX1xfvvvsuEhIS8N577+Hzzz+vsk/btm3D9evX8cgjjyiqNZuVh3/66Scruy3fRZUZPXo0ysvLsWzZMit7aWkpvv/+ewwbNqzad2lqFFsjTHZ2tgAghgwZUqXf4MGDBQCRm5srhLj1a2PkyJGSb+VfIvv27RMAxKRJk6z8xowZY/MVBypdEWVmZgqtViuef/55i624uFi6V5qamiq0Wq144403rGyw4YrD1vZsLetaE6U0hRBi4MCBomvXrlafp37NVGeNwzzWv/76K/kedcURHx9vtfYxe/ZsAUCsWbPGYqs8z0ptVtW3ylccH3zwgQAgFi9ebLGVlpaKzp07C71ebzlWzfPt6+trdSW0Zs0aAUD8+OOP0rbqmr179woAYsOGDUIIIUwmk2jYsKH4xz/+YeVXnTUO8zx169ZN+iVe1flW8QojJydHBAcHizZt2lhstl5xVNW3yr/MzedIixYtrH6B//TTTwKAmDp1qsX22GOPCQBW56IQQrRp00bEx8dL26qI+dhZtWqVos+1a9cEADF06FCLzdbvIupKqnPnzqJjx45W21i5cmW9Wgux+YojLy8PAKSKZpUxv5+bm2tlf+qpp267jV9//RXALQ19M1VJbFemefPmVldE/v7+aNq0qdW6i1artdwrNRqNyMrKgl6vR9OmTbF//36bt1Xd9m5X1rUmSmlmZWVh/fr1GDlypMU2bNgwaDQaLF++XPU+UkRGRqJfv342+48bN85q7cNcc8Ncgra2+OWXXxAUFGQ1Fs7OznjuueeQn5+PLVu2WPmPGDHCUjERUFd2t7ZZsmQJAgMD0bNnTwA3amGMGDEC3333HYxGY41sY+zYsYoFnCoTEhKCv/71r5a/DQYDHn30USQlJVmKKdUG5nPk6aeftvoFPmDAAMTExJB3PSp/B9133323nVNbvveUvvNs+S6iePTRR7F7926cPn3aYluyZAlCQ0NvqxxdV9gcOMyDYx5IJZQGOjIy8rbbMJcirezbuHFjW7tpU6lLk8mEOXPmIDo6GlqtFn5+fvD390dycrJN5TQro7a925V1vdNSmgCwbNkylJWVoU2bNjh16hROnTqFa9euoWPHjjW2mGrLnFak8v7o9XoEBwfXekrt2bNnER0dLS2s2lrGVU3Z3drEaDTiu+++Q8+ePZGammqZ144dOyIjIwMbN26ske2omdfGjRtLC+bmok21Oa9K5YOBG3LyledUp9NJZYFtKYFry/ee0ndedcvujhgxAlqt1nKe5uTk4KeffsKoUaPqTTKQzYHD09MTwcHBSE5OrtIvOTkZDRo0gMFgsLK7urpWr4cqsaXU5X/+8x/885//RPfu3bF48WKsX78eGzZsQGxsrE3lNCujtr3aKBNaGfNB17VrV0RHR1v+bdu2DTt37qyRX891NacAauzXtC3UxfxUhz/++AOXL1/Gd999ZzWnw4cPB4Aa+0FQ0/Oq9GVXH+b0dph/XFT1vWd+r3nz5jZt83bHkbe3NwYOHGiZz++//x4lJSWWOjP1AVWFnAYOHIgvvvgC27ZtI4unbN26FWlpaRg/fny1OmMuRZqammr16/ROCgNRfP/99+jZsye+/PJLK3t2djb8/Pzs3t6dltI0p2s+88wz0qWtyWTC6NGjsXTpUrz++usAlE/smv51c/LkScstFgDIz8/H5cuX0b9/f4vN29tbWtgsLS2VClip6Vt4eDiSk5NhMpmsrjrqsoxrTbBkyRIEBATgk08+kd5buXIlVq1ahU8//RSurq5Vjk9NzuupU6cghLBq88SJEwBuPFkO3Lpiy87OtirfWvmqQE3fKpYPrniOmG01NafdunWDl5cXli5ditdee40MBt988w0A1OhT9I8++iiGDBmCxMRELFmyBG3atEFsbGyNtX+nqMqqmjJlClxdXTF+/HhL2Ucz165dw1NPPQU3NzdMmTKlWp0x3y+fN2+elX3u3LnVak8JR0dHKeqvWLECFy9erBft3WkpTfMvlRdffBEPPfSQ1b/hw4cjISHB6tepu7s72a5SSdDq8vnnn1tlJs2fPx/l5eVWZVQbNWqEP//8U/pc5V+navrWv39/pKenW2WqlJeXY+7cudDr9fXmvnFVFBUVYeXKlRg4cKA0pw899BCeeeYZ5OXlYe3atQCqHh+l+a4Oly5dwqpVqyx/5+bm4ptvvkFcXByCgoIAwFLtsOK8FhQU4Ouvv65239q1a4eAgAB8+umnKCkpsdjXrVuHo0ePqsrErAo3Nze88MILOH78OJnh9fPPP2PhwoXo168fOnXqVCPbBG6UZfbz88OsWbOwZcuWenW1Aai84oiOjsbXX3+NUaNGoWXLlnjiiScQGRmJtLQ0fPnll7h69Sq+/fbbapfFjI+Px7Bhw/DBBx8gKysLnTp1wpYtWyy/YGrql9LAgQPxxhtv4PHHH0eXLl2QkpKCJUuW2Lx+UNvt3WkpzSVLliAuLg6hoaHk+4MHD8azzz6L/fv3o23btoiPj8f8+fMxc+ZMNG7cGAEBAejVqxfi4uLg6OiIWbNmIScnB1qtFr169UJAQEC19qu0tBT3338/hg8fbin12q1bNwwePNji8+STT+Kpp57CsGHD0KdPHxw8eBDr16+XrtzU9G3cuHH47LPPMGbMGOzbtw8RERH4/vvvsX37dnzwwQe3TfioD6xduxZ5eXlWY1WRTp06WR4GHDFiRJXjozTf1aFJkyZ44oknkJiYiMDAQHz11VfIyMjAggULLD59+/ZFWFgYnnjiCUyZMgWOjo746quv4O/vj3Pnzlm1Z2vfnJ2dMWvWLDz++ONISEjAyJEjkZGRgQ8//BARERGYPHlytfaH4uWXX0ZSUhJmzZqFnTt3YtiwYXB1dcW2bduwePFiNGvWjAyCd4KzszMefvhhfPzxx3B0dLRK7KgXVCcVKzk5WYwcOVIEBwcLZ2dnERQUJEaOHGlJJ62IORXvypUriu9VpKCgQEycOFH4+PgIvV4vHnzwQXH8+HEBQLz99tsWv6oeSKpM5fTM4uJi8fzzz4vg4GDh6uoqunbtKnbu3Cn5qUnHtaU9NWVdhaheKU1zSvO//vUvRZ+0tDQBQEyePFkIIUR6eroYMGCA8PDwkNJ9v/jiCxEVFSUcHR3JBwApbvcAoLe3t9Dr9WLUqFEiKyvL6rNGo1G89NJLws/PT7i5uYl+/fqJU6dOkeVKlfqm9ADg448/Lvz8/ISLi4to2bKlNN5VlbKFDaVwa5NBgwYJnU4nCgoKFH3GjBkjnJ2dxdWrV4UQyuOjNN9VScPc7gHAVq1aCa1WK2JiYshyrfv27RMdO3YULi4uIiwsTLz//vtkm0p9U3oAcNmyZaJNmzZCq9UKHx+fKh8ArIxSmjCF0WgUCxYsEF27dhUGg0HodDoRGxsrZsyYIfLz8yV/W7+LqpIc2bNnjwAg+vbta1Mf65K7onTsgQMH0KZNGyxevFh6UI5hGOZe5ODBg4iLi8M333yD0aNH27s7VtS7ehxmvaOKfPDBB3BwcED37t3t0COGYZi654svvoBer8fQoUPt3RUJVWscdcHs2bOxb98+9OzZE05OTli3bh3WrVuHcePGKd6zZxiGuVf48ccfceTIEXz++ed45plnLIkO9Yl6d6tqw4YNmDFjBo4cOYL8/HyEhYVh9OjReO211xS1YhiGYe4VIiIikJGRgX79+mHRokX1Mnmj3gUOhmEYpn5T79Y4GIZhmPoNBw6GYRhGFXZZNDCZTLh06RI8PDzqjWgXc28ihEBeXh5CQkLsUj2Ogo9/pi6pjXPALoHj0qVLnCHF1Cnnz59Hw4YN7d0NAHz8M/ahJs8BuwQOc5bA3E/mS0qcLePiJf/NG38j2+nTR64FseG39aRv3wcekGzrf11H+nbr2Ye0b9/8u2S7r2dv0nfrJtm3XdeehCewd/smydanL13nQmn/OnW/X7Lt3CL3AQB6E+O2cYPCGBP1NpT60KUHPRY7iHHrdX9f0nfj73Lb9/Wi52PrH3KVOZPJWtOquLgYb0yfVq8yU8x9OXHmHDw8rFWkswvlKoM+erp+emFJuWTTOtOKrCaTnAOjdLGTkVNM2hv4uEm2y9nyc1cAEOwlK+weuUCXLGjWwCDZSstplWql/TuTkS/Zwvzk/gJAcamsyuuqpb8KqX7onOlf7Reu0WMR6iv3I6eglPAE3HVyPzJySwhPINCglWyODvKk5uXlIjoyrEbPAbsEDvPluaurK9zcrAdVT+yckswz5atT8KUGTclXr6cHmOpHbfkqTbLiWBBtK+6fmrFQMx9qxkJh/6h+KLVL+ZoUpLrr0y0hc188PAxS+QGjkxw4DAqBw6mWAkeBid6ewSB/AeYbnQlPwGCg5pxO4Kw8BoD6wKEvlL/Mqf4CgDMRONxqIHDoy5TGQu6HyZEOHHoicBQKOnAYbAwcZmryHKgfN30ZhmGYuwYOHAzDMIwq7Poodlh4JNz1eivbtayrkl9kFC3Tfv16lmRTKjN75coVol3aNy/nGmmn2s7Jpn0bhsvy56UF9D3e4FC5VOel9EzSN4TwBYDyQrnt8Ah63M5fypBsSuOWkSmPW1Qj2jdfYSxCI+SxSCfaBYDoxtGS7VqWPM8A0Ijox8kTx0nf+khxqVG6beJE3GooKaNvv1G3bZSe5zUR9rJyhVtHrvQtF+p2l7vCLZ5r+fKtmIY+9C3OjBz5VoyzI31bJYdYAwKACH/iNlqxfCsPoNeRXF3oW2DUrSql20GervRYUH0uLqNvxel1so06JgDASMxHVbeqahK+4mAYhmFUwYGDYRiGUQUHDoZhGEYVHDgYhmEYVdh1cTxp/14px59aCN+zezf5+Y5Ecfjdu3bZ7Ju423ZfpX6069CR9N2bKPu2bNOe9D18IFGyde7c2eZ2AaC0rdx28n65XQDo2FHev6R9e2z23aMwbm3adSDtSXvltuPb0+OWuEduu4vCWCTukcfCy8uL9K2PuOmcpAe+qIVwZ0f6952axVETYdY6KfiqEMx2UljE1hLPOlCL4ADQwFteEVZ65qCIeAYDAM5lyQ/fBRDPOQCAl5u8+K80bu5aedHcSWE+ikrpNgzEornSuFEEetL7YetzGbXxDBNfcTAMwzCq4MDBMAzDqIIDB8MwDKMKDhwMwzCMKjhwMAzDMKqwS83x3NxceHp64o/Nf0JfSXKEyhS5fo2WnPD19ZNslzJoqQ4PTx/JVpKfTbfrJ7cLACfPXpJsPkQfAKCsQG47MMCf9KVkPZR8laQ6Avxl/6yrsnwLALgZvCVbUd510tfVQ/ZNVxjj6PAQ0n6WkDgJDQ4gfa8SfVYaiytXZN/jx49Z/V1cXIRXX34JOTk5pAqrPTAf/5evZEt9KjPKUhRKWVVU9lNBCZ11RMlehBDZTACg9I1wOrNAslHnKwCE+sryIi5O9H5Qsh5aBV8lqQ5KlkMpmSiLkEPxV8jAyiQywYoVJGCiAtxJ+5U8eXveRGYXQPdZadyosacyvnJzcxHo61mj5wBfcTAMwzCq4MDBMAzDqIIDB8MwDKMKDhwMwzCMKuwqOZKYmChJjlC1KVKSaOmMtoTExV5ChgIAunaRZSt27tpJ+lIyGwBw8tB+yRYXT8tsUHIm3e/rSvsSfVaSJ1Eai+gWbSXb8ZR9pG/TlnJd92PJtG9bQhrkBDEOAOChUMfhENFnBw29f5ScSdcuXUjffYT8yt0kOeLgoIFDpUXd67nyInaQF72InV8k15tQqivhQZQkVZIWUVrwjgmRS/hSdTcAwJFY5dUplH11IHzTs+m650pjcexSnmRrHEgvVmcXyGNMyZAAgDOxMK1Uy1yp/kcw0edMhTriLoQUSbmRng+qPnldwVccDMMwjCo4cDAMwzCq4MDBMAzDqIIDB8MwDKMKDhwMwzCMKuwqOfLbxi1wryQ5QmUmFOTSchghQbJsxcXLsrwFAHj5+Eq2orxs0tfTS5YnAWjpE513EOnr4NdAsjXxobMx9u7dK9mEI52BoimWs0cAQKf3kmw52ddI3+N58u8FJV8fX3ncGrnS2SPe/vRYBPh4SrarWfScFuTIY6wkOULN9YW0U1Z/12fJkTMXs+BRqU8ZOXI2kY/ehWzHXStn1eQVyRlDAFBESHUoFToqLKHnl5K+SLmQS/r+dkaWgxnQmJ5HiiIjLevRPJiew8vX5XFTyjp6e9Mpyeauo7OqygkJmOe6RJC+V/LoTKlAYpyVpFOook1KkjO5xFyHeMtSLyw5wjAMw9gdDhwMwzCMKjhwMAzDMKrgwMEwDMOowq6SI0n790qSI9HR0bLf3j3k503xsmzFAQXfFoSEx+ED8qI0AHQh5EkAICXloGRr1r816dtAK8fk9EJ68Sxx+x+STUnK5FAS3eeGTeV+HFeQEfFs1EKyOaYfJ30jQ+RxO33sMOnbvjndZy+i7kPudXox/g9CcoSSlgHosfD29iJ96yNuWke4a62TIBoF6iU/JQkQqq6EUp2HwlJ58ZiqYQEAXu70YjzVj6/2XSB924fL8iQHruSQvg+3bijZrhOyIADgqSBrc/iSvEjvrZBUEBsij/HDreRkFoCWVAn1kRegAeDLvedJ+5AYOYkn0o+WQ3Ek5iSbqKUC0FImdQVfcTAMwzCq4MDBMAzDqIIDB8MwDKMKDhwMwzCMKjhwMAzDMKqwa1ZV81Zt4O5uneFQRhQt6dyZLqyk95SlQajCQwAtW6HX0e0afGnpjJYDH5Ns90XS8iR7zmdLNq88Ouuieet2stFVzkoBgNZEJhkAFDjKciYt4oh2AexJlyUlYpvT2WEXy2UJhDHjnyN9nYkiNABgKsmXbNkK0hjtiPmLaEjPh85Z9j19ks4Oq4+k5xSjwGSd+VNUKkttRAXQGThUVlS+glyID5EpVa6QrXX5WhFpf39rqmR7o18T0nfujjTJNr0v7Xs6o0CyXcgtJH2pwkoAkF4oZ425Xadle5ZukfvWmJDqAICtaXIm2PBY+nh8rA2dmRXpL8/fvrO05A6VbdVQIYuLkmfS11FxJ77iYBiGYVTBgYNhGIZRBQcOhmEYRhUcOBiGYRhVcOBgGIZhVGHXrKojB5Ogq6RVFdWokeS3Z/du8vPx7WUNo8Q9stYRALRuK/seOUjrPvXoP5S0lxFFXRZuOU36lhz6SbK1bNWK9D2Rsl/2bUNnRB1ISiTtMa1k/2SF/fMNay7Zzhw6QvoWBMjZVtvTaJ0pXwVtoJ3ffynZ4uLakL679shzfSU/jvS9dFzWDvPx8SZ96yOBBh0MBmu9IeoYUyq15kRksVFaR4CC5pIvXVjscg6dVUUVeOo+YwPpe+y9gZJNIYkL0UGydpSHK/3V5ONOa1W1DvSSbJ4KbQzuGCrZWgXLnweA15alSLYzmXKWIAA0DaYzIV+9X9bfa9VQLm4G0Fmlm45nkr7dGvmR9rqArzgYhmEYVXDgYBiGYVTBgYNhGIZRBQcOhmEYRhV2XRxv2aatJDmSXyJLLlCL4ADg7SsvDnXoqCBPYpAXTVu060b6Zmt9SXu0v7yYmBBF+24qi5VsLm70gliHjrJ0RrmzvGAIALGUPAkADy9Z+qRNO1p+pVwnyxqc9aAXlX3z5QXRU/sVCjkN6ULac1vFSTY90V8AMETJC/dhwYGkb7iPXHDr2LFjVn8rLSzXB7ILSmF0tF60Ts+Ri32F+dKSE9RCqtL+UkWYDp7NJn2/2ksXZ+rfXD7Wp/aRF34BIIPYj+Iy+dwG6IJE567RkiOl5XLyAAAUE1ItSjTylbf35u8nSd8zv6yVbVo6qeAfX79E2vMIaRCl/fj5+GXJ1jGYPlc0RB6EiZhnynan8BUHwzAMowoOHAzDMIwqOHAwDMMwquDAwTAMw6iCAwfDMAyjCrtmVaUc2A/XSpIjjRs3lvz2791Dfr5zZzmrZi8hWQEAnTrJ2VY+3vQj+1cVMh7Kc7Il245kWtZjf6Lcj05EfwFgz25ZJoXqLwAcOkBvrwvR9vHkfaRvVHNZ7sPbKGfBAEBMzwTJ5pV/ke5b4nbSvo+YE6XiXFdPHpJsed50IaOUJHks/Hyts8OozJP6go+HFgYP60JZPgqyLRQaYueUsnW0TnImEVU0CqALBAFAIy9ZUsPVhS6W5Oos25VkRCjiwrxIu4PChDoQiUfU+ABAAbF/vi3lgmUA4P/ms5Lt1fvl7yiAzlwD6D7rtfS49W8iF4lSmtNyIqtO6yxvqzbOAb7iYBiGYVTBgYNhGIZRBQcOhmEYRhUcOBiGYRhV2HVxvG3bdnDXW0tr5BSVSX5t4mnJEQMhW9GyTXvS15eQJ/EOp+USGpBWoJGfLAOyMeUU6RvePE6ylTnTi7yxcbKMyOlCevHMK0qWMgGAC6XyVLaMpyVHBj3QW7IpLSRm5cmL5usPnCd9w0JoaZC2hGSM3pOWUYgj5trbh5Z16dqFSAg4fozwrJ8UlpTDqVKNi/NZci2MQE964dbZSf7dR9XdAOhaKWdzCkjfR9uHkPaWoQbJ9vq646Rvv8bynCkt0jbwlCU8Vhy6RPpGeNNjkUtIFfWK9Cd9YxrIi/xKi+4B7vL2jl7MI339POjEBi2RKCAUtGGuF8jff85E3RWArsdCncdK5/adwFccDMMwjCo4cDAMwzCq4MDBMAzDqIIDB8MwDKMKDhwMwzCMKuyaVbV//15JciQ0Ikry20vIdwB00abDCpIcJhEv2a4VKUgueNB5VVtPZEm2sMYxpK9/qex7vYyWcsg+d0ay6cOakb6FWXSRnfAm3SVb2gVaGoRSRsjOpyVH9l/OlWynDu8nfT10dPbbwf2yZEz7DrTkyGmibR2RdQbQc+3l5UX61kfctE5w01qfgkFEUSOdM/37rpyYyBBvuujT2atyYSQvLZ0F9NG2NNL+n5/kDKqwIDlDCQA8msvSGUev5ZC+0f5yG6WEnAYAdGxIZ9j9d6+c6TfnUhrp+3Z/+ZxNu5JPt7tPPt/eHkCf89lERhQA+Lg7S7YSBRmRAIOcxXXpejHp6+Rov9/9fMXBMAzDqIIDB8MwDKMKDhwMwzCMKjhwMAzDMKqwr+RIvCw5UkzUCKCkJQDAi5CiaNmGXkgNbygv1mkc6N3vGSv7AoCjg/zo/oKtqaSvs68sd9CjBb2wd7xhhGQLNdCLnNt9aTkIN6IuQmyjMNI3j6hHsO5wOunrBXlBM6alnGgAAAVOdJ8pyZgAf7oWSkci4UGr9yJ923eQJVVOnqAlMOojRaVGOFc63gtK5LkxuMoL5gBgKpMXWDNy6IXUcD9Z1oNaiAWAL0a0Ju0uhMRJt7c2kb7zd5+VbNP6NCF9Vx6W5UUGNwkgfV/5+Shpbx/pJdn89fKiNABczpbH6NnlB0jf0feFS7bUTFqq5dAVevG/VyN5X9y19HcPVdNDqc5HSZn8XUnNkZK8yZ3AVxwMwzCMKjhwMAzDMKrgwMEwDMOoggMHwzAMowoOHAzDMIwq7Cs5sncvdJUkR5o0kYsr7dq1i/x867Zy0aaUJFpyxMlRzuw5sE+WwgCAixlXSXt2pizh8cjwkaTvD0my7/wfk0nflj5ylkYYUfwIALRX6MJRDuVykalDhd6kb4C7LDURWH6F9D17Ud6Pc0cPkL7x7enCUQcJaRCjQsGtlP2Jkq1DR7rdxD2yFM3dJDmidXKAtlIWjJJkCAWVgRXoSWdg5RTKchg+RHEnAEi7QmcNRfjLhch+mXwf6TvyK/ncajFuEemb+PEjkq2IyK4EgGl9m5J2qthV/w+2kb4t/OVz5T9DWpC++YRMECULAwAGVzqLy9dD7huV2QUAgUSmm1IhLyqDqq7gKw6GYRhGFRw4GIZhGFVw4GAYhmFUwYGDYRiGUQUHDoZhGEYVGlEbQia3ITc3F56enti0ZSv0lbSqqOyP0oJssh29p49kS7tAay7lOhLZKoVykSIACAsKJO3lRbJ/SBCtqZOVJWdmObl6kr5lhbLGjaOrgW73Kp3x1SEuVrJ5BdC6VpROzrrft5C+Ghc5o6Mo5zrpG6wwFiX52XK7Onr/yomxoOYZAHKuy8Wyzpw6YfV3cXERXn35JeTk5MBgoLdZ15iP/4wsuU/ns+SCSw0UMq2yiXMlXSFbZ0OqnDXX3E/OLgIAXx2dbUVlVXno6MRMB0LXTSlbK9RX1tFS0oPSyM0CAKIC5L6dyyoifSmNrnNEoSsAuF5cKtn83eksp8pFucyEEFlYJ9LpwlERhKZYThFdIMqV0KejMrtyc3MR6OtZo+cAX3EwDMMwquDAwTAMw6iCAwfDMAyjCg4cDMMwjCrsKjmye/duSXKkYXiU5JdMyFAAQNt2sizHkYO05EhTovjQUQXpjIyC5qS9+OwRydaKkD0BgJOH9ku2OKKgEQAk7ZXlGTp3lgsaAcCx5H2kffCAByTb2pTLpG8jZ3lhLjmRlmfo3FkuorVfoQ96HS0NsjdRlgZRKgZ1lGi7Uyd6LPYT43Y3SY6UG00oN1oXY9I5ywue1EIzADg5yvZQX3ohPaFcLiIW7i8vxALAl4nnSPvjxOL4aYVF7JgQD8nmTUjdAIATsX/RQfTCvVJRo9wiWRrk+TWHSN/Zg+REkuYNbV80pgooAUBpuVxYCwBMRP6RwpSSi/+eClImOmJxvK7gKw6GYRhGFRw4GIZhGFVw4GAYhmFUwYGDYRiGUQUHDoZhGEYVdpUc+W3jFrhXkhxxJNINLqVnku34+/tJttTztOSIl4+cVUJJVgDA1nMlpD3CS86aiAwJIn1dyuRsk+AAf9I3PVOWgzB40TIbRjc5WwUAGoY0kGwRPnIWDABkZmRItuSUFNK30FHOvHEz0vIMTgoyKZRUy3XQsg0BjrLEg86DLkhFSZkcPXrU6u/6LDmSejELHpX6RBXnySuWM4YA+ly5eI2W2SghMn4oyQoAePS/chYcADz1QGPJ1kBPFzVqFyYfv67O9O/U4jK5b/kK+7z30jXSrnWU96VHY/p8oxKalL4Et52WJX66RcnfOwCQqqIA1rpjdMbjsFYNJVtGLv19FExImVBf57m5uQjy82LJEYZhGMZ+cOBgGIZhVMGBg2EYhlEFBw6GYRhGFXaVHNm/N1GSHGnatAnhRy/WtWsvS1wcS6HlMNp3kH0PH6DlSVrGtCbt548mSzaTJy3bkERInwhCIgWgJUeiW7QlfUOCaa2Chl5yP/YfpBe8M9LlhTmqDwA9bnsTad82CvtHzV90C1pyZDsxf0pSLZQUjbe3F+lbH3F2cpAWw52JxXGDK32aFpXK0hdRgXRCRAmxAK0ke/HmQy1Ie8dwecH7ap6czAAABqJOx3WifggAeLnJkhpKi/zN/eiaNv5EjY1r+XTfKFkXpTHuHCkn1SglFYQo1E3REUkBSvtRZrR9nij5FSXfmoavOBiGYRhVcOBgGIZhVMGBg2EYhlEFBw6GYRhGFRw4GIZhGFXYNasqNq4t3N2tJUeoR/87d5KLCQFAACHh0bEjXfQnvVzO3Gjeuh3pKxRkPajsHh9CygSgM4z0nrSMCFUMyt+flkto2bIVaacybM5n09Ig3gZZwoPKngJoqZaOCoWVAggJGAAwEeOWJWjJkSZEgSed3ov0jW8vt3vm1AnStz5yNb8EJRprOQlKACjQkx4rD6LAj5JUx/LkC5Kta0P62M0ro9u4XiBnRVFFigAgp0j2zSNsAFBGyKH4EVlSgHIRJSqD6mBGNunb0l/OaNKqkEPROdP77O1OF1y6QmSe7bxIyx1RVC72ZYbK7vIgstlqA77iYBiGYVTBgYNhGIZRBQcOhmEYRhUcOBiGYRhV2HVx/EhyElwrSY40bixr/m/fsZP8PLWofISQ+gAA/8YtJdvFU7QkR0wrWg7jWLIshxFPyJ4AwEFCDqODwsL9oSS5z+MnPE36agm5BAA4nZUvt7ttA+nbhlisTkmS+wsAbYlF/r17aAkYpbGg5Ewax9KSKpRkTCsFyZEjhGTM3SQ5EuzlCoPB+vin6ilQciEAcJlIfmjoQ8tehBlke/OGdG0GJUmNyABZzqRAYTHeTUvJetCLx1RdkYISul0tIckCABtOynV4hrSQa9QAQDaxyK+8qCz3Q0nVI0dBUsWTkDNpF0jXmInwk6WDripIp+i1crsajdw7ynan8BUHwzAMowoOHAzDMIwqOHAwDMMwquDAwTAMw6iCAwfDMAyjCrtmVUXHxkmSI1RRl3YKchgu7rJ0gJLkCCVxYWjehvQNbxBE2oWQs63cCPkOgM4w8vWlJR5atpGlT3x96HazFDIsIn3kjBelAkiOBln65L6evUnfa8WyxEPzOFqqpcCJLmpFZWYpSar46mV5mUBCWgYADK7yXB8/doz0rY+kZuZDX2T92y2cyKopUpDZoLKDgr10pG9BuZwddOh8Dukb4U8XgzqVLmfuUYWnAMAXLpLNSaHK0NW8Esnm4y5/HgDSrsh9AIBejQIlGyWRAgApl7MlWxsH+nxLviT7RvnoZUcAhzLp8ewSLp/34f70uUIlQDXwpueUEj6hsvIo253CVxwMwzCMKjhwMAzDMKrgwMEwDMOoggMHwzAMowoOHAzDMIwq7JpVdeJQEnSVtKqiG0dLfvsTaW2k9kQG1a6dtK5VGyLLaR+hPQUA/gpFZCitKo+OdMZX4p5dkq1LZ7og1SFCc6lHr/tJ31SF4kydwuVMKU25nK0CAJ3iWku2k8ePkL7OuZmS7dBBetyUikEl7pN1sFrHyzpjAHBQhe+BfbIGlo83nR1THwn1dYPBQGfXVITSJAKAqEA5+0lJ16pzmFxky53QkwIANwWtqihCq6qEKMIEAM6OcnoQpUkFACHeso7WmcwC0vePtKukfVL3RpLNaKKziUIL5DEvVshcaxsqH0+eCppbSgW3KH05pexIg6vtvj5E4SiNg3wtwFpVDMMwjN3hwMEwDMOoggMHwzAMowoOHAzDMIwqNKI2nke/Dbm5ufD09MTGTX/CXW/9+D7VnXOXMsh2okKDJVvaBbmgCwB4eMmLx6I4l/QVLh6kvSQ/W7KZdLQviuS2g4MCSNesq/KCX9++fUjfzBx6wVvrLP8G0CkUfcorkqUYkg/QC94mEG2U5JG+vn7yAiwAXLwsz5+TmywXA9Bz4u1Lt5uffU2yHT9uLTlSXFyEV19+CTk5OTAY6MJFdY35+D+fcV3qk4lY0FUq5EMVbUrPLiZ984iCS9FBtHTG0Yv0eUHJmRy+TPvGBMrnhZvCIj+1duvsSP+mVZJJoYpEeRGLxwBw8VqRZPMkpI4AujhTTAh9ziusxSOXON/OXqWTXKg5KTPSDVMFoqgEhNzcXAT5edXoOcBXHAzDMIwqOHAwDMMwquDAwTAMw6iCAwfDMAyjCg4cDMMwjCrsKjmyd28iXCtJjjRu3FjyO0xIcgCAm4sscUHJUABAly6y3MdOBXmS5q3pQkVHCamN5q3l4k4AcHC/LJ3RqRNdZGrPbllSJTIigvR1cqFlDbK0crbE+u8WkL5RTVtItuR9tKwLVUSLklMBgM6daEkVaiwU5Un2yvPXWUGqZecuef7uJskRFycHuFQqhERlVSkV8ikhZDK8FTKJKBmdciMtF0JJZAB05lIDTzmzS6kNpe05KWRQUTQKpDPBNp6UM/cGtwghffOJDDNK9gQAvBUKSlEoKKrAz0MeeyUZGZ2C3AsFNZ6UvAhLjjAMwzB2hwMHwzAMowoOHAzDMIwqOHAwDMMwqrCv5MjmP6GvJDlSTNQTyCOkJQDAw1NeCM1R8HXVe0m2zCu0tn9woD9pv0JIg4SGBJK+FwiZFC8fX9I3l+izgZBIAYDsa1mk3Y+Q+yjMyyZ9dcRYKI2b0UVejNSW07USqD4AQHrmFcnm66swFtflfnzzI50cMWaIXKfjxF0kOXLpSrbUp2xC4sKgoxdScwgpC3eFRdeMHFmKpFxBysJNoU4HJanhq6cXj68XyDIpSrVC9MT+URIpAKAjpHWU8CcWpQEgnRgLJTmU5IvZkq1DBH1uQuGbtJioWUIlQQB0jZQG3SaRvpk7P5Jszk7y+OTm5iLQ15MlRxiGYRj7wYGDYRiGUQUHDoZhGEYVHDgYhmEYVXDgYBiGYVRhX8mRPYnQVZIciYhqJPkl7qYlLig5jP2EZAUAdOgoy30cS6aLF7m170DaKemTsvK2pO+JQ/slm5KUCdVuTCtaykRJUoUaCyWpFkru46BCu23byWOxN5H2bdVWznICgIP7Zf/2HWj5FWqu/+9BWnJkxw5CcsTn7pEc0dz8VxEdkRWjRGW5EgBwVZCsoCQ1nBQ0MpQymqhiRycu00W9mgTLxY7OZ9HFi6jMLKqAEgBoFcaniMjYcnKk94/KtqIKoQFAuzD5eHJVkGS5kkcXWaP2r4TItALoAlZZu+eSvkalylF1AF9xMAzDMKrgwMEwDMOoggMHwzAMowoOHAzDMIwq7Lo4bjSVw2i0XojLuS5LaigteF4n5De8vLxI3ytXZNkLb2/aN19BfoNqu6Qg23bf/Os2+5YX0u0GB9BSHYW5cttKY5GVJUunKPlS86E0boW59LhRNTKodm+0LfumZ2TS7RLHxeV0a9+SEnrBsj6g0dz4VxFqcdtBYRHbpEItiPJ1cKB/N1KL4Eo08KHrWFBKRsFedF0Righ/N9KuVLujuFSuTaJUh8JRqXAGATUfSuUtlORXqD47qKiRUUzUXQFomZQCIrGhUCHZ4U7gKw6GYRhGFRw4GIZhGFVw4GAYhmFUwYGDYRiGUYVdFsfNC2fFxbIuflGh/HRpcXER2U5RUS35En1Q8nch2lXypfpQE75K/vXBV8lfzRirabfyYrj5bzuUnVHE3Je8vFziPdlfaXG8hFg01So81UwtsJYq+KqhsIReeC0nFpWVnnSmFoqVFv7VLI6XKjxFX0Y8ta30lDnVZ6XFdaX9o/qsVI+DQmlxvJxYHKcWws3HWU2eA3Yp5HThwgWEhobW9WaZ/2HOnz+Phg0b2rsbAPj4Z+xDTZ4DdgkcJpMJly5dgoeHh2LKHMPUBEII5OXlISQkRDH9tK7h45+pS2rjHLBL4GAYhmHuXurHTzCGYRjmroEDB8MwDKMKDhwMwzCMKjhwMAzDMKrgwMEwDMOoggMHwzAMowq7yaoXFxejtLTUXptn/odwcXGBTme7pHddwMc/U5fU9Dlgl8BRXFyMyMhIpKen22PzzP8YQUFBSE1NrTfBg49/pq6p6XPALoGjtLQU6enpOJ16DgaDAQICN/9n0eoRELde33wPN23ixsub/uZ3zP9nbRMVbOYnHW+0cWubVrYKnxM3LebPVv6cWU/HdLMBK5vV52/YzX0xiZttCrPfrX20fE7caFdU8LX0Rch9quxnuvnCJCqOmZD3S5jHqFIbouL4K7xXcX7MYy6E/FpUbSdt4qaekDBVmETza3HrtdlXUO8DJUUFePfVx1BaWlpvAof5+D9x5hw8PAy3jgdUmC+r+RQw3dwtk7j5+qbNBPM8VzwmKrVBtGt1nFnG/Za/EcKyLbOvUQiYTOb+3Pjb/Hmj+XNCWHSYjBV8jOLmZ0y39sFoEjCabr6++Z4QgNF00x+49b7pRrsm3NB5MppuHC833heW/bfYb/ZD3Pys2SZMN/bHZDL37Wa7JuvXuOljsZv31WS61a5RQJjMdvNrAZMw3Xp9Y8Bufu7Wa1Rst4Kv+bUwmQCT8cZxbDLenBzjrdcm4633jZV9K/gIE1BWjPQjX9foOWDXCoAGg6HGA0dlm9WXHyq2d2ublE36gr1pM1XwqU7gEKhwkltOyooneIX3zP2wnOh3FjgqfhFZB4IKY1s5OFTeZqX/okIfbxcgqh84lAKD+dvuNu/XUzwMBhiqCBy35q6KwGGZZ+UgQdmowFGxDfMXvXkbFQOHyYbAYX5tCRymW4HDKJQDh8XHJAcOs00pcJhMAg437Q7iVuCobDP7aioFC+vXgKaCj8ZiM1lew3jrc6gQOFAhANyMtDf+W+G1uDHY0NwMIpVfQwocpgrBQlgHDo2R9tHcsAmTLOp4p/DiOMMwDKMKDhwMwzCMKjhwMAzDMKrgwMEwDMOowq6L47m5NytT1eDiOCrZrBZ4UbG9W9u0slX4HLU4XvFznFVVYewqL3JXfC2qtpO2msqqKqarB9YH8nJzb7+wLW6zOA4htcFZVXdPVtWNDCrzf2spq8pY888L2a10rF6vR6PIMHtsnvkfQ6/XWwJUfcB8/DeJ4uOfqRtq+hywS+DQaDTIz8/H+fPnYTAY7NGFu47c3FyEhobymKnEPG71qdIeH//Vg8+B6lEb50C9eI6DsR0es3sHnsvqweNmf3hxnGEYhlEFBw6GYRhGFXYJHFqtFtOmTYNWq7XH5u9KeMyqR30ct/rYp7sBHrfqURvjphH1Kd2EYRiGqffwrSqGYRhGFRw4GIZhGFVw4GAYhmFUwYGDYRiGUQUHDoZhGEYVtRY4PvnkE0RERECn06Fjx47Ys2dPlf4rVqxATEwMdDodWrZsiV9++aW2ulZvUTNmCxcuhEajsfpXX0qj1iV//vknBg0ahJCQEGg0Gqxevfq2n9m8eTPatm0LrVaLxo0bY+HChTXeLz7+qwefA+qw1/FfK4Fj2bJl+Oc//4lp06Zh//79aN26Nfr164fMzEzSf8eOHRg5ciSeeOIJJCUl4cEHH8SDDz6IQ4cO1Ub36iVqxwy4Ib1w+fJly7+zZ8/WYY/rBwUFBWjdujU++eQTm/xTU1MxYMAA9OzZEwcOHMCkSZPw5JNPYv369TXWJz7+qwefA+qx2/EvaoEOHTqIiRMnWv42Go0iJCREvPXWW6T/8OHDxYABA6xsHTt2FOPHj6+N7tVL1I7ZggULhKenZx317u4AgFi1alWVPi+++KKIjY21so0YMUL069evxvrBx3/14HPgzqjL47/GrzhKS0uxb98+9O7d22JzcHBA7969sXPnTvIzO3futPIHgH79+in632tUZ8wAID8/H+Hh4QgNDcWQIUNw+PDhuujuXU1tH2t8/FcPPgfqhpo61mo8cFy9ehVGoxGBgYFW9sDAQKSnp5OfSU9PV+V/r1GdMWvatCm++uorrFmzBosXL4bJZEKXLl1w4cKFuujyXYvSsZabm4uioqI7bp+P/+rB50DdUFPHv11l1Znq07lzZ3Tu3Nnyd5cuXdCsWTN89tlnePPNN+3YM4apG/gcsB81fsXh5+cHR0dHZGRkWNkzMjIQFBREfiYoKEiV/71GdcasMs7OzmjTpg1OnTpVG128Z1A61gwGA1xdXe+4fT7+qwefA3VDTR3/NR44XFxcEB8fj40bN1psJpMJGzdutPp1UJHOnTtb+QPAhg0bFP3vNaozZpUxGo1ISUlBcHBwbXXznqC2jzU+/qsHnwN1Q40da2pX7m3hu+++E1qtVixcuFAcOXJEjBs3Tnh5eYn09HQhhBCjR48WL7/8ssV/+/btwsnJSbz77rvi6NGjYtq0acLZ2VmkpKTURvfqJWrHbMaMGWL9+vXi9OnTYt++feLhhx8WOp1OHD582F67YBfy8vJEUlKSSEpKEgDE+++/L5KSksTZs2eFEEK8/PLLYvTo0Rb/M2fOCDc3NzFlyhRx9OhR8cknnwhHR0fx66+/1lif+PivHnwOqMdex3+tBA4hhJg7d64ICwsTLi4uokOHDmLXrl2W9xISEsRjjz1m5b98+XLRpEkT4eLiImJjY8XPP/9cW12rt6gZs0mTJll8AwMDRf/+/cX+/fvt0Gv7smnTJgFA+mceq8cee0wkJCRIn4mLixMuLi4iKipKLFiwoMb7xcd/9eBzQB32Ov65HgfDMAyjCtaqYhiGYVTBgYNhGIZRBQcOhmEYRhUcOBiGYRhVcOBgGIZhVMGBg2EYhlEFBw6GYRhGFRw4GIZhGFVw4GAYhmFUwYGDYRiGUQUHDoZhGEYV/w/bniwQQ+uOcQAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -1614,7 +1612,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1754,7 +1752,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -1775,7 +1773,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -1893,139 +1891,6 @@ "Let's try denoising with a UNet, \"CARE-style\". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. " ] }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "# Adapted from https://discuss.pytorch.org/t/unet-implementation/426\n", - "\n", - "import torch\n", - "from torch import nn\n", - "import torch.nn.functional as F\n", - "\n", - "\n", - "class UNet(nn.Module):\n", - " def __init__(\n", - " self,\n", - " in_channels=1,\n", - " n_classes=1,\n", - " depth=3,\n", - " wf=4,\n", - " padding=True,\n", - " batch_norm=False,\n", - " up_mode='upsample',\n", - " ):\n", - " \"\"\"\n", - " Implementation of\n", - " U-Net: Convolutional Networks for Biomedical Image Segmentation\n", - " (Ronneberger et al., 2015)\n", - " https://arxiv.org/abs/1505.04597\n", - " Using the default arguments will yield the exact version used\n", - " in the original paper\n", - " Args:\n", - " in_channels (int): number of input channels\n", - " n_classes (int): number of output channels\n", - " depth (int): depth of the network\n", - " wf (int): number of filters in the first layer is 2**wf\n", - " padding (bool): if True, apply padding such that the input shape\n", - " is the same as the output.\n", - " This may introduce artifacts\n", - " batch_norm (bool): Use BatchNorm after layers with an\n", - " activation function\n", - " up_mode (str): one of 'upconv' or 'upsample'.\n", - " 'upconv' will use transposed convolutions for\n", - " learned upsampling.\n", - " 'upsample' will use bilinear upsampling.\n", - " \"\"\"\n", - " super(UNet, self).__init__()\n", - " assert up_mode in ('upconv', 'upsample')\n", - " self.padding = padding\n", - " self.depth = depth\n", - " prev_channels = in_channels\n", - " self.down_path = nn.ModuleList()\n", - " for i in range(depth):\n", - " self.down_path.append(\n", - " UNetConvBlock(prev_channels, 2 ** (wf + i), padding, batch_norm)\n", - " )\n", - " prev_channels = 2 ** (wf + i)\n", - "\n", - " self.up_path = nn.ModuleList()\n", - " for i in reversed(range(depth - 1)):\n", - " self.up_path.append(\n", - " UNetUpBlock(prev_channels, 2 ** (wf + i), up_mode, padding, batch_norm)\n", - " )\n", - " prev_channels = 2 ** (wf + i)\n", - "\n", - " self.last = nn.Conv2d(prev_channels, n_classes, kernel_size=1)\n", - "\n", - " def forward(self, x):\n", - " blocks = []\n", - " for i, down in enumerate(self.down_path):\n", - " x = down(x)\n", - " if i != len(self.down_path) - 1:\n", - " blocks.append(x)\n", - " x = F.max_pool2d(x, 2)\n", - "\n", - " for i, up in enumerate(self.up_path):\n", - " x = up(x, blocks[-i - 1])\n", - "\n", - " return self.last(x)\n", - "\n", - "\n", - "class UNetConvBlock(nn.Module):\n", - " def __init__(self, in_size, out_size, padding, batch_norm):\n", - " super(UNetConvBlock, self).__init__()\n", - " block = []\n", - "\n", - " block.append(nn.Conv2d(in_size, out_size, kernel_size=3, padding=int(padding)))\n", - " block.append(nn.ReLU())\n", - " if batch_norm:\n", - " block.append(nn.BatchNorm2d(out_size))\n", - "\n", - " block.append(nn.Conv2d(out_size, out_size, kernel_size=3, padding=int(padding)))\n", - " block.append(nn.ReLU())\n", - " if batch_norm:\n", - " block.append(nn.BatchNorm2d(out_size))\n", - "\n", - " self.block = nn.Sequential(*block)\n", - "\n", - " def forward(self, x):\n", - " out = self.block(x)\n", - " return out\n", - "\n", - "\n", - "class UNetUpBlock(nn.Module):\n", - " def __init__(self, in_size, out_size, up_mode, padding, batch_norm):\n", - " super(UNetUpBlock, self).__init__()\n", - " if up_mode == 'upconv':\n", - " self.up = nn.ConvTranspose2d(in_size, out_size, kernel_size=2, stride=2)\n", - " elif up_mode == 'upsample':\n", - " self.up = nn.Sequential(\n", - " nn.Upsample(mode='bilinear', scale_factor=2),\n", - " nn.Conv2d(in_size, out_size, kernel_size=1),\n", - " )\n", - "\n", - " self.conv_block = UNetConvBlock(in_size, out_size, padding, batch_norm)\n", - "\n", - " def center_crop(self, layer, target_size):\n", - " _, _, layer_height, layer_width = layer.size()\n", - " diff_y = (layer_height - target_size[0]) // 2\n", - " diff_x = (layer_width - target_size[1]) // 2\n", - " return layer[\n", - " :, :, diff_y : (diff_y + target_size[0]), diff_x : (diff_x + target_size[1])\n", - " ]\n", - "\n", - " def forward(self, x, bridge):\n", - " up = self.up(x)\n", - " crop1 = self.center_crop(bridge, up.shape[2:])\n", - " out = torch.cat([up, crop1], 1)\n", - " out = self.conv_block(out)\n", - "\n", - " return out" - ] - }, { "attachments": {}, "cell_type": "markdown", @@ -2036,7 +1901,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -2092,10 +1957,11 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ + "from dlmbl_unet import UNet\n", "import torch.optim as optim\n", "import torch\n", "\n", @@ -2108,8 +1974,8 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet().cuda()\n", - "\n", + "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = unet_model.to(device)\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", "\n", @@ -2135,18 +2001,18 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "938it [00:12, 74.28it/s] \n", - "938it [00:12, 74.39it/s] \n", - "938it [00:12, 74.28it/s] \n", - "938it [00:12, 74.36it/s] \n", - "938it [00:12, 74.30it/s] \n" + "938it [00:19, 48.99it/s] \n", + "938it [00:18, 49.39it/s] \n", + "938it [00:19, 49.23it/s] \n", + "938it [00:19, 49.10it/s] \n", + "938it [00:19, 49.15it/s] \n" ] } ], @@ -2166,7 +2032,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -2175,13 +2041,13 @@ "Text(0, 0.5, 'mean squared error loss')" ] }, - "execution_count": 38, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2211,7 +2077,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -2225,12 +2091,12 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 37, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2240,7 +2106,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2250,7 +2116,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2260,7 +2126,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAARDklEQVR4nO3deVDVVR8G8KOZhLigKS6AC2YqRLmhAZUtlqRASmFTU1NpMzRaplZTzthM41hNY2XLQDVOTalli6lZYoG4kApZQpkkIGpaiqlYrrll73+/9zwPyr0aV7me5/PXeebo5QfdON6zfE+jf//9918jIiLOanyhH0BERC4sDQQiIo7TQCAi4jgNBCIijtNAICLiOA0EIiKO00AgIuI4DQQiIo5r4u8fbNSoUSCfQ+pZIM4Jjh49GnKvXr0gd+nSBfLKlSu99vbt26Hv1KlTkP/880/IXbt2hczfD3+tW265xWtnZWVBX+/evSFHR0dD7t+/P+STJ09CXrRoEeT27dt77bS0NOibNWsWZP4+IyIiIB86dAhydXU15CZN/v+/6G233QZ9n376KeTExETIOTk5JhD0uyC4+PO7QJ8IREQcp4FARMRxGghERBzn9xqBSE1NDeSSkhLIf/31F+T58+d77dTUVOjbuHEj5Hbt2kGOi4uDHBISAnnJkiWQd+zY4bV5zp+fu7Cw0NTl8OHDkHlOfMOGDV6b5/Svu+46yOvXr4d8xRVXQD5y5Ahk/rnEx8d77bKyMuhr2bIl5O+//96InAt9IhARcZwGAhERx2kgEBFxnNYIxG+7d++GnJKSApnn1tPT0712RUUF9FVWVkJOTk6GvGLFCsjDhg2D3L17d8irVq3y2mFhYdDH6wtRUVGQ+TzEG2+8Ablv376QY2JivHZSUhL0FRUVQb7++ushl5eXQ16zZg3k5s2bQz5+/LjX7tevH/QlJCRA5vUFEX/pE4GIiOM0EIiIOE4DgYiI4xr5e3m96osEl0DUGuJaNsXFxZAHDx4MuVOnTl47NjYW+niu/LfffqvztXiPfKtWrSCPHDnSa+fm5kJf48b4750//vgDMj8br4VwHSR7TeHAgQPQ16xZM8j2WQpjjMnMzITMZy+OHTsG2T4fMWDAAOjr2LEj5PDwcMgPPfSQCQT9LgguqjUkIiI+aSAQEXGcto/KORs4cCBk3ippl0netWsX9N19992QeYvn6tWrIdulFoypXbrBns7haSZ+LrtExOmebc+ePZB79uxpzmTr1q2QeesqT9/Y20GNMeaff/6BzOW6IyMjvTaX1eBy2vx9B2pqSC4++kQgIuI4DQQiIo7TQCAi4riLYo3APuY/d+5c6OP5359//hkyb4XjrVYFBQWQ7VIJXIb5Yrdz507IgwYNgszz+PZcO8+V21cwGlO7NPScOXMgjxgxAjKXW7DLW3Dpi4MHD0LmuXX7mkt+LWNqz+uvXbvWa/N2Ty59wddm7t27F/Jbb70F+YYbboC8dOlSr80/A956ymU4RPylTwQiIo7TQCAi4jgNBCIijgvKEhOXXnopZHtfeOvWraGPSxPwGgHvMe/Ro0edX9suE5yfnw99zz//PGR7Lvl8C0SJiRdffBHyli1bIHPZh5UrV3ptvsKR999fffXVkA8dOlTns/A8fp8+fbw2vz+qqqog87WYdhmH0712ixYtIHfu3Nlrz549G/q4hAT/TLjsNF83yc9ul7W2v8fTvbb9XMYYM3bsWBMIDel3gfimEhMiIuKTBgIREcdpIBARcVxQniPgGjd2qd/JkycH9GvbNXKys7Ohj2vBTJo0CfIHH3wQuAc7D3h+m/fyx8XFQf7ll1+89rfffgt9PBceGhoKmc8sNG3aFHKHDh0g23V2Nm3aBH1cO4ivpiwrK4PM38e+ffsgnzp1ymvPnDkT+uwrM42pvb7A87Xcz++hjIwMr80lrYcOHQqZ10JE/KVPBCIijtNAICLiOA0EIiKOuyjOEdhztlzfPZD46sAPP/wQ8u+//w6Za9oEUiDOEfCcNF/TyHWd7Fo4DzzwQJ1/NyYmBrJd08kYvPbSGGNKS0vP+Hp8FSXfJ8BrG/ws/F7nqyrt2kNt27aFPj4f0a1bN8h8roWv0Rw+fDhk+ywKryf4umchJyfHBEJD+l0gvukcgYiI+KSBQETEcRoIREQcF5TnCE6cOHGhH8EY47tOkX2P7sWAa+0vWLAAcnp6OuTy8nKvbZ8pMKb2GoBdU8cYY3r37g2Z7xTgNQJ7/YJrIHHdIj4XsHnzZshpaWmQi4uLIdt3EPBdy++//z7kvLw8yLyGwD8zXmcZNWqU116+fDn0zZs3DzKvo4j4S58IREQcp4FARMRxGghERBwXlGsEgcRnFLiu0YwZM7x2QkIC9HGdmYkTJ9bz011YfGfA9u3bIUdEREC+5JJLvPbff/8NfXwPMNfS57l3vjOA58Ptuv5Tp06Fvtdffx0yry/wf+PPPvsM8u233w7ZPh/Caxl83wXfoc1nGnje377DwRhjEhMTvTbfR8D7+flOYxF/6ROBiIjjNBCIiDguKEtMsGbNmp227Y8xY8ZAvuuuuyD3798fsn2N4QsvvAB9fKR///79Z/Us9SkQJSYmTJgAmaeG7JISxuCWz2effRb61q1bB5lLg9hbT42pPX3D2yzDwsK8Nr9Xf/jhB8hJSUmQeWvrvffeCzk8PBzyF1984bV5O+i2bdsg87TSjz/+CJmnyGJjYyHn5uZ6bZ6K5K/N/fY0Zn1qyL8LpDaVmBAREZ80EIiIOE4DgYiI44Jy+2hKSgrk6dOne22+ZrC+/frrr167pKQE+i7kmsD58N1330HmEsu8nmJv+Vy8eDH08XWSXK7D3g5qTO1tl/bVlMZgiQm+UpPn/OPj4yEfOXIEMped5u2kw4YN89r2+8EYY6699lrIfPUkbwFdtmwZ5JqaGsj2e52v++TtonY5dpGzoU8EIiKO00AgIuI4DQQiIo4LyjUC3sds7+3n/ecfffQRZLuEsDHGvPfee3V+rSFDhkDOysry2lyG+amnnoKcnZ1d52sHm1atWkH2dY7AXjPh8hRcMoJLUERFRUGuqqqCfPTo0TO+Hl+pySUm+KwJr/UwvvrSLmt9zz33QB+fE7jssssg81qIr2exr9HkMhy8lsE/UxF/6ROBiIjjNBCIiDhOA4GIiOMuilpD59M111zjtb/++mvo43lsng8+nwJRa4hrK3HZbZ4Pt2sNcdlont/mnxXvr8/IyIDMpaTtcwW8VsHnBHiuPTk5GTKfDeBrMu1S5fb7wZja12JyWerGjfHfXnzuhdcjNmzY4LV5DWDcuHGQuf7StGnTTCDod0FwUa0hERHxSQOBiIjjNBCIiDguKM8RXEg//fST154yZQr0Pf7445BDQ0Mh8175YMNz5/b8tTHGREdHQ7bn0vl779WrF2Sed+Z5+8rKSsg8H15cXOy1X331Vejjej+8PsG1ibgeUJMmTc6YP/nkE+i78cYbIfN5B15D4PULXiOIiYnx2nxnA68/2FeDipwNfSIQEXGcBgIREcdpIBARcZzWCOoRz3tHRkZC5nMGwSYkJARy3759IXfv3h2yfY9wXl4e9G3cuBEy/+x47zPXHuL5cHs//qRJk6CP7wi44447IK9duxZymzZtIBcWFkK25/H79esHfffddx9kvg+Zc0VFBWS+m3nLli1e+/LLL4e+hQsXQuazFiL+0icCERHHaSAQEXGcBgIREcdpjeAstWjRwmtnZmZCH9/pG+xrAozPCfD9ugUFBZBHjx7ttfnuAq5bNH/+fMh79+6FzHcY33rrrZCLioq8dmxsLPR9/PHHkKurqyE/+OCDkHm/Pt/FbO/f79ixI/Tx/QR8roDvFd6zZw/kLl26QN65c6fXHjBgAPTdeeedkE+ePGlEzoU+EYiIOE4DgYiI44KyDDVPC+Tn55+3r21fe/jYY49B39SpUyE/99xz5+ORTisQZajbtm0L+YknnoDMU2N2iQm7VMLp/izr2rUr5NTUVMivvPIKZLvkRNOmTaGPy1VwuWwuncHlMOzpQGPwys7Zs2dD32uvvQZ53759kN9++23I6enpkLlMtX2VJV+DmZiYCHndunWQectufWlIvwvEN5WhFhERnzQQiIg4TgOBiIjjGuQaQXh4OOR3330X8v79+yHb2xTr25gxYyDn5OR47W+++Qb6eL73QgrEGsH48eMhc0llviLSvsaR/+yBAwcgc7lmvgb0mWeegcxbQO33DM/Lc6lnXhPgMtNXXXUVZC6Bbc/bM97SaZctNwav1DTGmB49ekDmeX172yxf3/noo49C5rWzwYMHn/E5/wutEQQXrRGIiIhPGghERByngUBExHENco2Aywtw+d20tDTIX331Vb197ZdffhkylzTOzs722tOmTYM+vmbwQgrEGgHPZ/Pefi5DbZdc5rMeCQkJkHnufNCgQZBXrVoFOSkpCfLu3bu9Npe+4DLU/LUOHz5c52tzuW27xIR9RaYxeMbAmNplH/iKzc2bN0O+6aabIK9fv96cyahRoyDzOYKZM2ee8e/+F1ojCC5aIxAREZ80EIiIOE4DgYiI4xrkGgGX5uU1Aq7H8l/wmsDYsWMh27WFjDFmypQpXpvLFTckgVgjuPnmmyHzeQ6eax83bpzXLi0thT7eE5+VlQWZr648ceIE5EWLFkG2zzDw3+U1Jy71XFJSAnn48OGQy8rKILdv395r8/kILj3OV3J26tQJMq+78M/QPm8RGhoKfe3atYPM5yW0RiDGaI1ARET8oIFARMRxGghERBx30V9VybXkuY79ww8/DPmll16CPHny5MA8WBDiuXM+N8H3FXz55Zdem/fT8/0E9pWMxtTeTz9hwgTIdh0jY3C9Yu7cudDHNaB47z/fEcDXaNr3KhiDtYY+//xz6ON7FHgNYMSIEZDfeecdyN26dYMcFhbmtSMiIqCPzxjw2QwRf+kTgYiI4zQQiIg4TgOBiIjjGuQawcSJEyHPmjULMs/5xsfHe22uJT906FDIvu46mD59+lk9q8v4HEFhYSHk6OjoM/5d3tvMr8V75O3zG8ZgvR9jjOnZs6fX5juHed87rzfwWRE+x3L8+HHI9nuI1wBWr14N+f7774f85JNPQs7IyIDM9zCEhIR4bT7HwWcO+J4FEX/pE4GIiOM0EIiIOE4DgYiI4xpkrSGuqcL7vu01AbZt2zbIS5cuhZybmwt5wYIF5/KIDV4gag3xmYo5c+ZA5vly+z4CX/V/WrduDZn/G/MdATNmzIBsrwVxLSGuCcXnH7h/zZo1kDMzMyHv2LHDay9cuBD6UlJSIBcVFUHm9S2+55nvSujcubPXLigogD4+V9C8eXPIfJ6ivqjWUHBRrSEREfFJA4GIiOMa5NSQ/HeBmBoaMmQI5MTERMj2VkdjjKmsrPTa9lWSxhjTpk0byFu3boXMU0UHDx6EbJe4NsaYvLw8r83bKnkKZd68eZAfeeQRyHFxcZC5BIX9/wKXx7ZLVBtTu4R1nz59IEdGRkK2S0oYY0x5ebnX5q2p/FrHjh2DzFtR64t+FwQXTQ2JiIhPGghERByngUBExHENssSENExXXnklZN6qW11dDdme7x45ciT0LVmyBDKXBmE1NTWQuTSIXb6Z50R37doFmctpV1RUQO7QoQNknhO3t3wePXoU+tLS0iAPHDgQ8ooVKyC3bNmyzq9tl7t4+umnoe/NN9+EzGshIv7SJwIREcdpIBARcZwGAhERx2mNQPxmlzswxpjFixdD5j30ycnJXnvTpk3QZ1/3aEztcwMdO3aEnJ+fD5lLVDRp8v+3clRUFPSlpqZCXr58OWTeu89lSbictp25pASXQ+HXruu5jTGmtLQUsr2GUFVVBX3jx4+HvGzZMiNyLvSJQETEcRoIREQcp4FARMRxftcaEhGRi5M+EYiIOE4DgYiI4zQQiIg4TgOBiIjjNBCIiDhOA4GIiOM0EIiIOE4DgYiI4zQQiIg47n/9qxsbmBe5GAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -2270,7 +2136,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2280,7 +2146,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2290,7 +2156,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2300,7 +2166,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAQmElEQVR4nO3da0zWVRwH8ANoCnkFL6FcioyLKYoKKmUXMyQVWnO9aLW0Oa1lNdfarKZbpa+6vWmp06arVi1vJehgpYUpplPUvIQSZlQSaYrX1BTpRdt/5/t95HkeiAd5ON/Pq/PdIZ6Hi5z+5/I7EY2NjY1GREScFXmj34CIiNxYGghERByngUBExHEaCEREHKeBQETEcRoIREQcp4FARMRxGghERBzXKdgPjIiICOX7kFYWinOCeXl5kMeMGQP5n3/+gbx3716vnZWVBX1r166FPGzYMMj8+3bt2jXIN998M+TY2FivfeDAAejr1Al/zQcMGOD3tWJiYvy+Vn19vdc+dOgQ9OXn50NesmQJ5NGjR0M+ffo05OTkZMjl5eVee9asWdBXVlZm/OHvcWvR34LwEszfAj0RiIg4TgOBiIjjNBCIiDguItiic5oXDC+hWCMYOnQoZJ4P5znrrl27eu20tDTou3z5MuTs7Gy/n+umm26CHB8fD7mmpsZrjx8/HvreeOONJt+XMcbMmTMHcmlpKeTISPz/JXsePyoqCvq6dOkCua6uDnJcXBzkS5cuQa6trYV85513em3+mfLXwa89f/58Ewr6WxBetEYgIiIBaSAQEXGcBgIREccFfY6go0hNTYW8adMmyPv374c8adKkkL+ncMHz+IMGDYLM8+H23KQ9h2+MMb169YK8dOlSyBkZGZDtMwnGGHPbbbdBvv322702nznIycmBPGLECMj3338/5MzMTMgbNmyAbK8LHDt2DPrsMwbG+K5tnDlzBjKvs3Tr1g3y2bNnr9s2xpjo6GjI/P0XCZaeCEREHKeBQETEcRoIREQc59wawbJlyyBz3ZnZs2e35dsJK6dOnYJcXFwMmWv62Pvx3333Xejj+WxeAzh//jzkBQsWQF68eDHkkSNHNvm5eH2CayTxXPvGjRshNzQ0QLbPAvC5gD///NP4w7WJqqqqIPMe/SFDhnhtPmPA76tv375+X1ukKXoiEBFxnAYCERHHdfipocceewzyqFGjIC9cuBByUVFRyN9TuOKph61bt0LmbZeFhYVee+fOndDXs2dPyPxz4WmoQK9lT/9wH5fHTk9Ph3z8+HHI/fr1g7x582bIP//8s9fu0aMH9PGU16233ur3ffPXyWUj7O8bT2Pyf5uQkGBEWkJPBCIijtNAICLiOA0EIiKO63BlqJOSkiDz3DRv33v44Ych89WB4SoUZaiffPJJyP3794f8119/Qba3UvI8/LRp0yBzyQn7ikZjjBk7dizkXbt2QbZLTPCWTt4eum/fPsjbtm2DzNtLz507B/m7777z2hMnToQ+3vaamJgIeceOHX4/N1/ZuWXLFq/90EMP+X0tXjNYvny5CYVw+Vsg/1EZahERCUgDgYiI4zQQiIg4rsOdI3jvvfcg9+nTB/KiRYsgd5Q1gbZw9epVyFwKunfv3pDtksu8n/7gwYOQea8/l2PmcuF79uyBbK8L8F78iooKyHY5CmN8z0dUVlZCvnDhAmT7LACfMeDzEFzegq+m5Os/uWy1Pe//66+/+n3fAwcONCItoScCERHHaSAQEXGcBgIREcd1iDUCe391Xl4e9PFcMs81S/AOHz4MOTc3FzJf82nvc586dSr0LVmyBPK4ceP8vhZfP5mcnAzZrl3ENXkuXrwI2T4HYIwxnTt3hnzlyhXIvH9/9erVXjs+Ph76eA2A16B4zSomJgZySUkJZHsdJtBZi5SUFCPSEnoiEBFxnAYCERHHaSAQEXFch1gjeP75570270efO3cuZK6HI8GbPHky5PXr10Pu3r075LS0NK/Ne/l5r//Zs2ch85553vvPNaPsvf7Hjh2DPp6nz8rKgmyfd7jee33//fchFxQUeG2uJWTXBjLG996Fv//+GzLXYJo+fTpkez3j6NGj0JeRkQGZaySJBEtPBCIijtNAICLiOA0EIiKOC8s1gnnz5kHOz8/32suWLYM+nRtoPbyXPzU1FTLXqV+1apXX5jl+xms7XMeI1xQeeOAByPaawYwZM6DPvmPYGGO++uoryDxvb9+1bIxvnf+9e/det22MMcOHD2/yY43xPedSVlYGme8r6NKli9fmdRM+k1BaWgqZvw8iTdETgYiI4zQQiIg4TgOBiIjjwmKNIDISx6t77rkHsj2//NZbb7XJe3IR18pPT0+HfPLkSchRUVFem+f4+X4CPoPAH8+/A/za9l0IX3zxBfRNmDAB8pEjRyDHxsZC5nn+Z555BrJ9DoHvaOD7Ye27lI3xrXPEtYn467LXJ6ZMmQJ9fPZi9+7dRqQl9EQgIuI4DQQiIo4Li6mhF198ETJvHXz55Ze9dnV1dZu8Jxd9/vnnkO3SHsb4bn187rnnmuzjaxbr6uogDxo0CHKnTvirylNJv//+u9fm7aJffvkl5EceeQQyb0fmshD82nYJi8GDB0MfX9dZX18PmaeduBwGl7uwS6L88ccf0MfTZ9wvEiw9EYiIOE4DgYiI4zQQiIg4LqKR97s19YFUPqAtbd++HfLAgQMh29cc/vLLL23xltq9IH+szcJrAg0NDZD5WlC7JMWkSZOgb/PmzZCTkpIgf/LJJ5AXLVoEmbdS2utE/L74c/O8PZd35nl/3hbbr18/r80lrvnaS/7c9vWdxvhubeUrOu2rK/nKTN7OGx0dDXnx4sUmFG7k3wJpvmD+FuiJQETEcRoIREQcp4FARMRx7fIcQUpKCmS+WpD3s2tdoG2sW7cOMpf6mDVrFmT77IC9z98YYxISEiDb6zzG+J4T4JIUH3zwAWR7/z6Xa+Yy0vzafO5gyJAhkIuKiiD36tXLa991111+3xdf73nu3DnIW7duhcxrDPZ74T4uO83rMCLB0hOBiIjjNBCIiDhOA4GIiOPa5RoBlxzmWi9tKScnB7K9N7tbt27Qx2sVjz76KGQuGxxu7L36xvjO+/P8+IMPPui1q6qqoG/nzp2QucYOl2/mef8xY8ZArqmp8dq8d5+vweT6PjyPz6Wi+ZrN5ORkr801khj/7tpXTxrju/efr5+85ZZbvDZfqcl1i9LS0vy+F5Gm6IlARMRxGghERByngUBExHHtco0gEJ5vbk2fffYZ5MLCQsj2PC3XXOEa+sXFxZAnTpwIma8pbO927doFmc97jB49GvKmTZu8Nq+P2HvxjTHm+PHjkHkunetL8f772tparx0fHw99dm0gY7AGkjHGrFq1CjLflRATEwPZXhviqyrvuOMOyHwmobKyEnJmZibkH3/8EXJeXp7XXrFiBfQVFBRAtu8uEGkOPRGIiDhOA4GIiOM0EIiIOC4s1wh4//7/wTVs7r77bsj+6uhzPfiPP/4YMp8jmD17NuR33nmnWe/1RuO5dt7bz/v3n332Wa/90ksvQR/XKeJzA7xnntcUevToAdmuTcS/H7GxsZA//PBDyFFRUZC3bNkCmWsolZeXe+3ExETo43UjPlvC9wr/9NNPkPl8xMqVK70239W9ceNGyPb5BpHm0BOBiIjjNBCIiDhOA4GIiOPa5Z3FPP9bUVEBmWsR2fPNXEcmkCeeeAIyrxksXLiwWZ/Pxt9avnt57NixLf7czX3t1sB35vKctD13bgzOd6empkLft99+6/e1eF6f11v452zffcBrGTyXzucMeA1g//79kPkeYbu+EL8WnyPgsyInTpyAzF9HRkYGZHs944UXXoA+vtuA/128/fbbJhR0Z3F40Z3FIiISkAYCERHHtcupIfbaa69Bnj9/PmT78fnVV1+FvkBlgrmUAbt8+XIQ7/D6uJQBTw3l5ua2+HMHEoqpoQULFkBeunQp5PT0dMh22YinnnoK+rg8M5d54CkW/l7y1JF93SSXo+CfMU/1cPmLwYMHQ75y5Qpk+98Cb1Xlz83TnHzdJF/J+cMPP0Du37+/187OzoY+LsvRs2dPyPzvprVoaii8aGpIREQC0kAgIuI4DQQiIo4LixITPDfN88fTp0/32lwKed68eZBLSkog/59S0FyaYMaMGX4//tNPP23xa7UHp06dgsxbbePi4iDbZbk3bNgAfVxSguf1eW3m/PnzkHnb5YgRI7y2Pa9+vffN8/IXL16EfPLkScj2dZHG4PpGoOsj+feRvw/8WlzK3F6fKCoqgj7eBjt+/Hgj0hJ6IhARcZwGAhERx2kgEBFxXFisETQ0NEB+/PHHIdtXKM6dOxf6Vq9eDfngwYOQL1y4AJnLBHMphKFDh3rtrKws6LPnqY3xLVWwfPlyE862bdsGmffbc0ll++fGc+l2OW9jjBk5ciRkLjvNPxdmrynwXDqfLeHPHR0d7fdz8zz+fffd57XXrVsHfVyanMtA8HWSvH7B61/2fz9hwgTo4zMHfK5AJFh6IhARcZwGAhERx2kgEBFxXFjUGmoOnv/lEsNTp06FPGrUKMj8dfr79pSWlkLm9YgVK1b4fa+hFIpaQ3wV55o1ayDzXLs9b+9vL74xvvPbM2fOhMylyKurqyHX1NR4ba4NxKXGeV2IzxXwz5XLb9sltb///nvoKysrg5yQkAC5vr4ect++fSHbNZOMwVpGvFbB30M+17J+/XoTCuHyt0D+o1pDIiISkAYCERHHaSAQEXFcWJwjaI7Tp09DfvPNN/1mCR7Ph585cwYy75EvLCz02oHm3fnKx/z8fMjTpk2DzOcS7DMNXMdo9+7dkNeuXQuZr9Hkr4vvK7DPR3Bdo99++w0yrxHw+YnJkydDTklJgWz/PvOVm3l5eZD5mkuRYOmJQETEcRoIREQcp4FARMRxHW6NQEKHz2hwHR3er2/X/ImMxP/n4HuEuU7/K6+8ArmqqgpyYmIiZHuP/Y4dO6CP99PPmTMHMp8ruHr1KuSuXbtCttcMamtroY/38vO5gYKCAshca6h3796Q7bWP119/HfoqKysh853FIsHSE4GIiOM0EIiIOE4DgYiI47RGIEHr3Lkz5JycHMjl5eWQs7OzvXZMTAz08d5+vquX9/Zz/aADBw5Atu+G2L59O/Q9/fTTkPlehSlTpkD+5ptvIPMZB3sen9+X/TUb41t/ic9a8H9/9OhRyPaZhiNHjkBfZmYm5EOHDhmRltATgYiI4zQQiIg4TlNDEjS+ArJPnz6Q09LSINtTFVy24d5774XM13ryNEddXR3kYcOGQS4uLvbaw4cPhz6e2klKSoK8cuVKyLw1lUto21tEY2Njoe/rr7+GPG7cOMhc/oK3m/IU2kcffeS1ucwGl7PgazJFgqUnAhERx2kgEBFxnAYCERHHaY1AgsZbOvlaxUuXLkG2S1BwOWbewmlfyWiMb3lnnv8uKSmBbM/r8xZNfi3e4rlnzx7IXAqa5+Lt0tC8/sCfm/sPHz4M+dq1a5B5jSA3N9dr81oGX3PJ5bJFgqUnAhERx2kgEBFxnAYCERHHRTQ2NjYG9YEREaF+L9KKgvyxNsvMmTMhDxgwAHJFRQXkEydOeG1eX+Byy1yu2b4O0hjf8hbdu3eHbJehZnztJV9VyfP6+/btg8zz/DU1NV6bv8/874RLd1dXV0PmEhRxcXGQ7RLY/D3hdZM1a9ZA5jLhrUV/C8JLMH8L9EQgIuI4DQQiIo7TQCAi4rig1whERKRj0hOBiIjjNBCIiDhOA4GIiOM0EIiIOE4DgYiI4zQQiIg4TgOBiIjjNBCIiDhOA4GIiOP+BdqLl9ubVSYrAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -2388,7 +2254,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ @@ -2417,14 +2283,14 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 39, "metadata": { "tags": [] }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2434,7 +2300,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAUTElEQVR4nO2de5CO5RvHLx0cthCym2xOEWodQs5EbFJSabMIoZASScfppGkaxTSjmjIyYaiJnIacclqHWG1ZZ1aOOZ9WtCkq+f33zP39vr99393Nu7vm/n7+ur9z7/u8z/O8z7g913Xd36vIpUuXLpkQQghvuaqgT0AIIUTBooVACCE8RwuBEEJ4jhYCIYTwHC0EQgjhOVoIhBDCc7QQCCGE52ghEEIIz7kmp39YpEiRaJ5HrihTpgzo2NjYYNynTx+YO3r0KOgtW7aEPXbFihVBt2vXDvSyZcuC8VdffQVzhWlvXjTOpUePHqCbNWsGesOGDaDLli0bjJOSkmAuLS0N9MKFC0Hzb/zzzz+DbtmyJejDhw8H49atW8NcXFwc6Fq1aoHOzMwE/e6774Lme9mxY8dg/Ouvv8Kc+yyamU2YMAH0Aw88ADo9PR30I488ku25XX/99TDHz/bevXtBT58+3aJBYfq3QEQmJ/8W6I1ACCE8RwuBEEJ4jhYCIYTwnBznCKIJx4MbNGgAukKFCqA5RunGaTdt2gRzXbp0CauzsrJAly5dGvT69etBu7FoPlbx4sVB//LLL6A5hn7u3Dm7kuDfZdu2baD5Xrmx+q1bt8Kcm2sxM6tXrx7oEiVKgL722mtBc3zcpWrVqqDPnDkDeu7cuaATEhJA161bF/Q///wD+tixY8F43759MJeSkgK6SZMmYTXnRnbt2gXavcecf8jIyAD922+/mRB5QW8EQgjhOVoIhBDCc7QQCCGE5xRIjuDGG28EzbXTp0+fBn38+HHQHFsvVqxYMD5y5AjMvfDCC6CvuQYvuWjRoqA5zvrvv/+Cvummm4Ix5xf4WHydnFOYPXs26N9//90KM3PmzAHt3nez0H0Gp06dCsbufTMzO3/+PGjON9SpUwc054k4Xj5r1qxgzDF93u/x/PPPg+Zafz63kiVLgm7fvr1lB9+D/fv3g05NTQVdqlQp0Hyd7jOxefNmmIuJiQF93333ZXteQoRDbwRCCOE5WgiEEMJztBAIIYTnFMlp8/rL6S/COQGG4/wcC+VTduP4V199ddi/5fgvx5P581y//vfff2d32iHf9ddff4Fmrxjm+++/DzufG6LhNdSvXz/QV12F/4/ge+k+M6tWrYK55s2bg3b3Z5iF7itgf6CxY8eCdn+nAQMGwBzfC47b83eNHDky7Lm2adMmGLMH0tq1a0Gz79H48eNBd+3aFTTfQ3e/BN8Dzp3t3r0bNO9RuFzIa+jKQl5DQgghIqKFQAghPCdfykc5tMNllRwK4hDKhQsXQIcL31y8eBHm+LWINb+Ksx0Bl5u658ahES415c9yWIlLILn8lENLBU3t2rVBs2UGhy7cUNcbb7wBc1yyyc8Eh2s45MLPhFvied1118Fco0aNQA8dOhQ0P2+9e/cGvXTpUtBu2S+HSRo2bAh63rx5oEeMGAGaS0I51OTaoE+ePBnm+PmpXLmyCZEX9EYghBCeo4VACCE8RwuBEEJ4Tr6Uj1apUgU0l8wdPHgQNFsMR/pu9xI45v/HH3+A5pK7W265BTRbGyxevBi0m4/g2HKkGD/HwdnymstH+VxzQzTKR5OTk0HfeuutoJcsWQI6MTExGO/Zswfm2Eph3bp1oOPj40EvX74cNLcQdbXbItPM7MsvvwTN1hg1a9YEzZ93rTLMzNasWROMI9mj8LPM+Qu2NOHSVtdOhXMAfF6cs+LcxuVC5aNXFiofFUIIEREtBEII4TlaCIQQwnPyZR8Bx8YPHDgAulKlSqDdVoBmoTFdriF38wAco+U9DNwC8eGHHwb98ssvg3bjwWZmw4YNC8a85+CGG24AzfsIbr/9dtBcQ16+fHnQ/yVHEA3KlSsHmvd/1KhRAzTH/V3c9qJmZjt37gTNttU333wzaI7jf/rpp8E4MzMT5l588UXQHFtPT08H7eY2zEKtGxo3bhyM2Tqc/5ZzUJwD4GemV69eoBctWhSM4+LiYI5za0lJSSZEXtAbgRBCeI4WAiGE8BwtBEII4Tn5so+AW+jxsTi2zJbE3JqScwQnT57M9rvefvtt0Jyf4L0AbBPcuXNn0G7cfvDgwWGPxbkPjnvv2LEDNHsVpaWlWV6Jxj4CjrWzzTH77Lg18ytWrIA5/s379+8P2v1Nzcy2b98OmuvvXR8njtOzZfXrr78O+q233gLNuR2O40+ZMiXb82KvoBYtWoB+/PHHQc+cORM0x/3d49WtWzfseXGug+/55UL7CK4stI9ACCFERLQQCCGE52ghEEIIz8mXfQSuV7xZaIw/KysL9NmzZ0Gzhwp7+HTq1CkYv/feezC3YMGCbP/WzOyhhx4C/eCDD4Lmtodu3J5rxE+cOAGar4s15xS4Jr2wwbFzjtPz9bu+T+xDNHr0aNAzZswAzb0PMjIyQLu1/Gb4jAwfPhzmOOfEexI4Z/Dss8+C/uKLL0C7+0c4R8C1/u4+ALPQvSG8x2bIkCGg33///WDM+yOaNWsG+u677zYh8oLeCIQQwnO0EAghhOdoIRBCCM/JlxwBw/sCuNaacwDsZc89i/v27RuMp02bBnNcU75y5UrQqampoLnmdtCgQaBdf3n2QGL4WGXKlAHNXkWRjlfQcIyafZo4Fu/2K+DfkGvgOW7Pvv2tWrUCzTXy99xzTzDmXAvH7evXrw+6WrVqoPnznMtp2bJlMOa9Ifxsun9rFpobeeedd0C/9tproN1nhntt8D4O7r3B+S8hskNvBEII4TlaCIQQwnO0EAghhOfkS46AY5ucI+B6dI67bt26FTTHk2+77bZgzN5CXOu/adMm0CNGjAD93XffgebeuW69Osf4I3mwcA6A48luP+TCCPdTWLZsGWj2SnJ9nbZs2QJzfK/4dylVqhRo7v3bsWNH0G69PucfuD8y+/lwbwPee8L7DNze0pyD2rVrF+jq1auD7tmzJ2jORwwdOhS022eBr4uPPXHiRBMiL+iNQAghPEcLgRBCeE6+hIbYIoJDJNxe8uLFi6A5jOBaDjPulnwzsypVqoDmEAWXBvJ3cymrG1bgdot8ncWLFwfNoSAOmXF5aWFjwoQJoJs2bQqar6d06dLBmNuPtmvXDvS+ffvCam6Tye0mExISgjGXsXIbzOTkZND8PHHIzw3PmGH4h58nDllxWGrjxo2g2ZaDn7eqVasGYw5DHTp0CHT37t1NiLygNwIhhPAcLQRCCOE5WgiEEMJz8iVHwLFxjp1zCR3bHfPfc3zY3VrPMdtx48aB5nJS/ntuJciW2K5FcYkSJWCO8wtc7se2CWxBXNiJVL7IVtOTJk0KxsOGDYO5lJQU0H/++Sforl27gv7hhx9AuyWcZmZdunQJxvy8cZ6I7S74d2A7Zz439xniHEDRokVBc1lsYmIiaLbX3r9/P2i3tJrLrjm/wOW9QuQUvREIIYTnaCEQQgjP0UIghBCeky85Am5NyfYBbNfMMVmOxZ8/fx70Bx98EIy7desGcxzv5XNhOwHOGUydOhW022qwfPnyMMe18jzP18HxZI4Xx8TEBGO2GC4I2AJj+fLloJ966inQ7vVv3rwZ5nj/Bn92+vTpoHmPBtuMuLF03gcwatQo0E8//TRobovJuRzOSbk2JFz3z5YlHPPnZ9216jYLte1wcx/cxnLw4MGgX3nlFdD9+/c3IXKC3giEEMJztBAIIYTnaCEQQgjPiVqOwN0LwPbEvE/A9aQxMzty5EjYY7Mnz9y5c4Mx+8Zwu74mTZqATktLAz158mTQHOd3PW8ieSjt3bsXNNd58+c5f+EerzDkCNgefPXq1aDXr18P2r33WVlZMMe+RGPGjAHt5mLMQttL8rm4/j+8b4D3jrRv3x407xXh53Xt2rWgK1Wq9H/HZqFW0Py7cRz/k08+Ad2hQwfQ7j11c0Zmofs2OnfubELkBb0RCCGE52ghEEIIz9FCIIQQnhO1HEE4b3328XdbTZqZnTx5MuyxORbvehHNnj0b5tatWwea67YZ9o5hfx03B8ExfvYaYg/9kiVLgo6UCylsrSs5B8B7NDgPMH/+/GDMcXjeC3L//feD/uyzz0C7vvxmof5U7p4MjvHfeeedoDMzM0Hz/g7OM7F30TPPPBOMFy9eDHP33nsvaPZEevPNN0Hzfgjet9KjR49gzJ5bfL/Zj0mInKI3AiGE8BwtBEII4TlaCIQQwnOiliPgOL4L11ZzTTnHTQ8cOACaY7audxHvUeB8xE8//QSaPW84Dsu4cXs+b/ad4RpzzhFwLoS9hzgHUdBwfoU9ozhG7Xr4xMfHw1zNmjVBc2x8wIABoDk/wc+Xm5PiPQZ8rGnTpoHmZ4T3LHDu58cffwzGvAdmx44dYT/LuQ1+/mJjY0G7PbIHDhwIc/w8bd261YTIC4XrXxohhBD5jhYCIYTwHC0EQgjhOVHLEbi+6+zBzrF0jrVz/JfnOe7qHp9r7yP1BQ53LDOzIkWKgHZr1HmO4Xmunee+CxwvLmxw3TrX0HN+xb0ezi/MmTMHdJs2bUC73kFmZo0bNwbN/Q3cvQHcP4A9eRo0aACavYROnz4N2vWyMsO9Jvx8cS+D5s2bg969ezfoVatWge7Xrx/oDRs2BOOKFSvC3NGjR0FzzkaInKI3AiGE8BwtBEII4TlRCw25JZ68ZZ/DL4zbdtAsNDTEJaI8H26OwzVcisrnGsluwIXDUmxl8F/PraBhG20+/169eoGeN29eMGbLkUjhGS6l5RDeXXfdle3n+by4JJNLUdmmmsNO586dA+22gHTLO81Cn4E77rgDNFuYcKkrl+C698m17DAzi4uLA3348GETIi/ojUAIITxHC4EQQniOFgIhhPCcfGlVyfFd1mylcObMGdAcK2eb4dyQ27h7uHJSnuPySbYTYEtrhq+rsNlQV69eHfSKFStAp6eng27dunUwZqvnWbNmgW7VqhXosmXLgubPs724WzqZkZEBc3379gX90Ucfga5Xrx7olJQU0FzS6cbiOZ+1f/9+0KmpqaA7deoEevz48aA5D+M+b2zXznmXcLkyIcKhNwIhhPAcLQRCCOE5WgiEEMJzopYjcOPdnBPgfQBsS8310Bwr51i6G6uPZPvA+Qg+Fn+etXstPMdxbG5FyXYEXCvP51LY9hFw/T1bGnB8e+nSpcG4Ro0aMJeYmBj2u/iZKF++PGi2sXbj4z179oS5V199FXSjRo1As7UHfxdbTX/44YfBuFatWjDHeyn27t0Levny5aB5n0pMTAxoNw/DOQLXDtss1AJEiJyiNwIhhPAcLQRCCOE5WgiEEMJzopYjcOF6e46lc6vAY8eOgWYvmNzsI+DvjuRzFOnzLpFyBJzr4OuIlPuIlO/Ib7p27Qr6ueeeA805ENdamvcY8G/ObT05Vj5lyhTQbO/s5lPYr4dzAvxZ9hZq27Yt6OPHj4Nes2ZNMH7yySdhbty4caD79OkDmttJ8n4JtrF27yl7C3FLV+UIRF7RG4EQQniOFgIhhPAcLQRCCOE5UcsRuL47HPvm+nn2FuJWlhxL55aP4chtnJ1zArzvIBzsNcTXwd5DfGyuKc/Nd+cHH3/8MejevXuDXr16NWh3zwW3VXzppZdAcz8CvndNmjQBzfkY9/PswcPPz9SpU0FzT4CdO3eCrlKlCuhvv/02GPOzm5aWBnrgwIGgH3vsMdCjRo0Czb0P3BwCt++sVq0aaPY9EiKnFK5/aYQQQuQ7WgiEEMJztBAIIYTnRC1HUKxYsWDMPukc3+X6Z84BcNyej+fWkHM+IpLHP8fh+bv4865P0oULF7KdMwv1y8lNbuP/nWtBw/si2HufcxyNGzcOxuznc+jQIdCnT58GHemZ4Vh8y5Ytg3Ht2rVhbtOmTdmel5nZnj17QH/99degOedQv379YNyiRQuYGzZsGOhvvvkG9JIlS0CPHTsW9Ny5c0F36NAh2/Pk/hZ83ULkFL0RCCGE52ghEEIIz9FCIIQQnhO1HIFbQ879CCJ58rDfCsdCOdbu7kuI1LeV49gch+ceAPz37nfxZ3kfAecbIn03184XNq8h9sXhHAlfr+snxL0Mzp49C9rNKZmFPhNDhw4FzfX2bo09ezrxPgD2DmL/n+7du4PmngJuPmP79u0wx/2PuUcD+zPNmTMHdIUKFUBv27YtGJ88eRLmXC8nM7MZM2aAfvTRR02InKA3AiGE8BwtBEII4Tn5YkPNIQ4OA3DZ5alTp0BzS8RwJZ25hUNBHFri73LLTTnUw6ETPi/WHCJji4BIYa78pl27dqBdqwUzszp16oCOjY0NxmPGjIE5t42lWagFBVtaz58/HzRbMrvhnIkTJ8LcwoULQXPpakZGBuiOHTuCfuKJJ0CfOHEiGPM1c3gsPj4etNvm0iw0zNmgQQPQbgkyh0i59DQ1NRX0559/bkLkBL0RCCGE52ghEEIIz9FCIIQQnhO1HIEb345kp8zx4I0bN4KeOXNmtsc2w9g75yMifXdu7CsYLovlv83MzASdkJAAOlLuJLdtNaMNn1/Dhg1B8/W4MesVK1bA3PDhw0GvXLkS9KRJk0BXrFgRNOdb3FJWtiwZOXJktudlZjZ69GjQlStXBs25G/fzycnJMMdlsqVLlwbN7SX5Hg4ZMgT0oEGDgnG5cuVgjstJu3XrZkLkBb0RCCGE52ghEEIIz9FCIIQQnhO1HIG7DT8mJgbm2D6AWziGO9aVDMd0GW57yDYMBQ23dGzatCnoBQsWgHbj4xw757aXXD+flJSU7bHMQveaHDx4MNvzdG0azELv6+bNm0FzjqF58+ag27Ztm+13LVq0CDS32GT7C95HUL16ddDu3hTOwfD93717twmRF/RGIIQQnqOFQAghPEcLgRBCeE6RS4WtWF0IIUS+ojcCIYTwHC0EQgjhOVoIhBDCc7QQCCGE52ghEEIIz9FCIIQQnqOFQAghPEcLgRBCeI4WAiGE8Jz/ARgm1+1VeVPEAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -2444,7 +2310,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2454,7 +2320,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2464,7 +2330,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2474,7 +2340,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2484,7 +2350,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2494,7 +2360,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2589,18 +2455,18 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 74.10it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 74.16it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 74.19it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 74.04it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 74.19it/s]\n" + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:38<00:00, 48.91it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:38<00:00, 48.67it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.84it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.62it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.60it/s]\n" ] } ], @@ -2617,7 +2483,8 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet().cuda()\n", + "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", @@ -2636,12 +2503,12 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 42, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2651,7 +2518,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2661,7 +2528,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2671,7 +2538,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAV5ElEQVR4nO2de7BW0xvHVz8hSqebbnSfbpRuQ+l+kwwlKXTMMCoyGZMaZkRmjMlMSmXQISZ3kSZhhKNEKt1LKadS5HSVCl0l9Ptvz3o+57T3eXXe0zmt7+ev9Z31vu/e7353Z7Wf51nfp9TJkydPOiGEEMHyvzN9AkIIIc4sWgiEECJwtBAIIUTgaCEQQojA0UIghBCBo4VACCECRwuBEEIEjhYCIYQInNIFfWGpUqXSeR6ikEnHPsHMzEyjjx49anT9+vWN3rdvXzResmSJmevfv7/R69atM7ps2bJGd+zY0eipU6canZGREY0bNmxo5i6//HKjFy9ebHT16tWNbtSokdHTpk0zukWLFtH4l19+MXM///yz0YMGDTJ6y5YtRm/fvt3o//3P/t9s4MCB0ZjXe8WKFUb718A551577TWXDsqVKxc7z3vP1+ecc07sa/l3hvP//vtv7Py55557ytf+888/sbp06fg/h/y8VOBnJ33PuOvC9/7999+xxzp06FDi+emJQAghAkcLgRBCBI4WAiGECJwC5wiEYEy1UqVKRv/4449GHzt2LBpfeeWVZo6xdcY1+fp33nkn9th+XL9ixYpm7q+//jL60ksvNfq3334zev/+/UZ36dLFaD9G+8cff5i5888/3+itW7ca3aBBA6OZvzh8+LDRubm50fjPP/80c8wvUKeLEydOGM24fxy8h5JyBMyZEB7bj+On+t6k1zNH4J9r3Nx/IS6HwGvG8+Y1Lgh6IhBCiMDRQiCEEIGjhUAIIQJHOQJRYDZs2GD0bbfdZjRj7d26dYvGOTk5Zq5ChQpG79ixw+hFixYZ3bhxY6OZIzh48GA0njFjhpm7++67jZ43b57RN9xwg9Hvvvuui+Piiy+Oxl27djVzS5cuNfrGG280+ocffjC6adOmRnMfgl8jXrt2bTPXuXNno7lHIV0k7QUoTJLq6+Nez7h90j6BpD0LSa+Pe2+q+wbiPjvps/5LfkJPBEIIEThaCIQQInC0EAghROAoRyAKzK233mo069rp2eP7B7G2ecGCBUa3bNnS6PXr1xvNHMGBAweM9vMXF154oZk7fvy40e3atTN6+fLlRlepUsXo1q1bG71w4cJo7PspOedctWrVYj+LPkdffvml0bfccovRO3fujMasF2cug9+rOML4NeP2/I7UST47frycr/V9iPL77KT9EIzFHzlyJBqnmhNI+mzif14qry0oeiIQQojA0UIghBCBo9CQKDC0hWB4hvYK/qM4y0VbtWpldPfu3Y2+//77jR47dqzRtELu06dPNGYZ5cqVK41m+KZnz55G06KCoSPfJuLXX381c506dTJ6zZo1RvM6XHXVVUbXqFHD6N27d0djWnPXqlXLaNpVpItULQ38UAXfy9AQy4J5vWijwXCOf8/FWVQ751z58uWN5n3BkCJLnH1b8KTS06TS1aRwTlw4KNWy1/zQE4EQQgSOFgIhhAgcLQRCCBE4Z0WOoH379tGYdsV79uwx+rvvvjM6qczriy++MHrTpk3RePXq1amfbAmG9sO0d2Zs0rd7Ziy9cuXKRvN3mTNnjtF+GaVzeeO7fhnnddddZ+aSygRpjUE7bVpi+zYRbLHJuDK/N9t5stR1165dRvvWGRs3bjRzPXr0MJoW1umiMC2X+Vm09abmPci4v69Z9kv7cV77pNwH73f/92Duws/tOJfcYjOpJDQuD1MYFh96IhBCiMDRQiCEEIGjhUAIIQKn1MkCBphOt/VaYcK4oG9HwBrwFStWGM1YNOu+GzZsGHtsv3597ty5Zu7JJ580mvXnRUk6rIEnTZpk9MyZM42uV6+e0RdddFE0btu2rZnj/ZSdnW009wL4ltbO5Y2H+zXdjMMz9nvo0CGjmzRpYnTz5s2NZpz/vffei8a03fDtJ5xzbtWqVUb718S5vLHkFi1aGO3Hhhnjfv31142m3cK2bdtcOuAejqR4t/8dzjvvPDPHf8v8DoytUzPO79ucXH311WaONiW+nXh+89zTwDi9n1vy27I6l9f+g/dFUu6D19Cf53kk5R9oBZMfeiIQQojA0UIghBCBo4VACCECp0TmCDp06GC032pw9OjRaT22HxOeMmWKmeM1GjVqlNGM6aaTdOQIhg8fbjQtlOkftHfv3mjMuHLdunWN9uvlnXOuZs2aRs+aNcvoOnXqGO3H9RlnZo03Wz5yr8lll11mNPMV/jzfy5g39yRkZGQYfcEFFxhNW2u/9WWbNm3MHK8Z82HcH1FY0POIxHndMF9DUr1v6W/l7y/hXhPeg2XKlDGa+RtaiFetWvWUmhbsvAYvvvii0WxJyhwB72E/zp/qngPlCIQQQiSihUAIIQJHC4EQQgROifQaYn2+H0dNNzNmzIjGW7duNXNvv/220XfccYfRRZkjKArowcN4tx9DpU8O4+6NGjUymh5PAwYMMJqeUn7MtV+/fmaOsWJ6xtDfh/kL5gH82DLrwTMzM2M/m7DHA/H3ZjD2yzwKexucKZgri2uzmGrbReYYGFv394gwNs7+GUk+/ryfmQfw9yE0a9bMzF1zzTVGsx9B0n4J/tZx1zDVtpj5oScCIYQIHC0EQggROFoIhBAicEpkjoBxwTNFkk+RX0d/NrBkyRKjWVf9+eefG92uXbto3LdvXzPne/o7lzfvM2zYMKMXLVpk9NChQ40+cuRINKavC38X+v/06tXL6NzcXKPp/7Ns2bJozDj9q6++GvvZ77//vtH03mHfYd9Lh3Xw7H1w8803u6KA8Wz2d0jHHpZTfTZzBv658e8EY+mM23NPAvslM67v//bck8A9HMxXMAeQdK5xFMb11xOBEEIEjhYCIYQIHC0EQggROCUyR5BO6BXD2uzJkydHY9bRM449cuTIQj67Mwv93RnnZK2/H2Nl3J49AFiH/cEHHxhNvyD2FNi8eXM0vuSSS8wcf1PWeDM+y54V3OMwfvz4aPzNN9+YOfrVvPzyy0Yzzs+9KDyW32uDfZ79vEh+x04XSXXrcfHtpNcmeeszJxD3eUm1+vR9Yh8KelKx38bAgQOjcU5OjpljDoz7RbiXhf+WeM/GXdOkvRUFQU8EQggROFoIhBAicM6K0JBfYsfWdUkMGTLEaIY3aP3rP44/8sgjZi4rK8to2g+UdGjV8OGHHxrN8I5/rdjusWfPnkZPmzbNaD6G87GeNtR+OGj//v1mbu3atUaznPT22283miEDWkn7ViL8jRmu4SM/200yHEErDt/ugt9r3LhxRk+fPt0VBfwtkmwg/PmkskiWQibNs/zW//fPclCG5dj+lG1HWV7K6++XhzM0xHvu999/N5rhGx4rLuTF19IKQ6EhIYQQKaOFQAghAkcLgRBCBE6JzBH07t3b6AkTJkRjbtEvbLZt2xaNV69ebebOtpwA2blzp9EPPPCA0Q8++KDRffr0icb+dXMubwy1S5cuRrOskhYVLB+tVatWNK5fv76Zu+mmm4xu0KCB0W+++abRR48eNbp79+5G+2WaH330kZmjtYBvVeycc7t37zaaFhWtW7c2eseOHdGYLTRZnsx4ebqIs5nOjzjLA76X34HWDcwNsdy2ffv20ZjXy79HnMubM2A+59ixY0azdaX/vfi7MZ/A78E8S1KOIO4a8jzjWoWeCj0RCCFE4GghEEKIwNFCIIQQgVMicwSMK/q126zDZm01rXtfeeWV2GOx3t23R549e7aZe+ihh4yeMmVK7GeXNGhx4LeHdM65O++802g/1s49CL51gnN54/jVqlUzmrX9jLX79fjz5883c7S3GDx4cOxn8Vi0C8jOzo7GzEnxfpk6darRbIP59ddfG02bCP86MZ9QtmxZozt27OiKglRtj+Pmk+LZjOOzXST3Zfj7T5ivYd6J87wnDx48aDRtqVu2bBmNmUeiNc2kSZOMpsUE9wLEtdFMarGpHIEQQoiU0UIghBCBo4VACCECp9TJAvY1S6V12tmM37bws88+M3Nbtmwxmq0si5J0tAukDTXjoLNmzTLazymwdp8xUu7BYCyd8Vz6Gvnx3SR/H9qFc56xd9pS33XXXdGYcXvuLaHHDHNYPBZj4P78pk2bzByv/759+4zm/ojCIlU/r1RyBPQpombOgPsO2BIy7lisv6dtNfNazN/49+gLL7xg5rgXhTkwf3+Ic3l9kWhD7Z9bktcT4bnkh54IhBAicLQQCCFE4GghEEKIwCmR+wjOJL5HzpgxY8zciBEjjGZtMGOSJQ365tCnny0iMzMzo/Fjjz1m5tq2bWt0q1atjGa+hbX8n376qdF++0nG/BmXZ+6GOYCmTZsazZi4f+xHH33UzLFHwMSJE41OakHIFp7+seiVw3p++tsUF/zvmGruivmew4cPGx2XU0g6FvMLSS0fmcfy71HG7elz1KNHD6O5t4V/G5jrYP6isNETgRBCBI4WAiGECBwtBEIIETjKERQijO8yZs64d0mDNdz8frt27TJ6wYIF0dj3iXcub900Y6Tbt2832s8BOJe3Pt+v+U6KlbOumrHixYsXG00fGT83smLFCjOXm5trNOvFuW+gYsWKRq9cudLoxo0bn/Kz9+zZYzT3WqQL5jVSifun0t84PxiLT/LdiYP5B76XcXmem5/v4f3MHt3sn8H7gPmI/9J3+FTnWRD0RCCEEIGjhUAIIQJHC4EQQgSOcgQp4vuNDBw40MwtW7bM6JKeEyA5OTlGs18s+w5v2LAhGjO+7Xs2OZe3t0GbNm2MXr58udGsy/bzEfTcqVGjhtH0kGHvA2r/ezjnXNWqVaMxY9TMCbAenLmQvXv3Gh137owbc29Fuvt1FwWn65Hlvz/ps5LyCYy1s6+wv1+F+QTud2CvA/7ufD/zF/53SYfvm54IhBAicLQQCCFE4JTI0BBLCefOnVtkxx47dmw07tWrl5l74okniuw8zgTXX3+90UuXLjWaVgy+JQUtrCdPnmw0Q0EMobAklPYW/uPyvffea+a++uoro1l6ykftMmXKGO2XcDrn3Lx586Lx448/buaef/55oxlWYplh7dq1jaY9hh9aYmiCthws500XqbZCjAtlJIVvWF5KGEJJen3csWnZQav0vn37nlLzHqEFCu0peJ48l7gy26RrpvJRIYQQKaOFQAghAkcLgRBCBE6xbFVZoUIFo6dNm2Y0422DBw9O27kMGTLE6KysrGicnZ1t5hhDPJOko1Xl6NGjjT5+/LjRzBH4JXOM8Xft2tVobslneR1LOmnxvWTJkmjMFo6My7Osl5bYtG5gm02f+fPnG01rDJYF0uKaFti0+u7YsWM0ZotNlpPSpnr69OmnOu3TgteefxviWikyDp9kV8F7irmjpGP78NhJluDNmzc3mu0o/ev/008/mbmHH37YaLYZpcVEUt4llXafRK0qhRBCJKKFQAghAkcLgRBCBE6x3EfAGG7lypWN7tOnT9qO/fTTTxs9atQoo6dMmRKN/T0FIcCad9pCfPvtt0b7vxvr41n/vW3bNqPZ6o/2Hc2aNTO6Xr160di3AXEubyy9Z8+eRq9bt87oOnXqGN2yZUujn3322WjcunVrM8c9CMx17Ny50+iRI0caTdsI36qA/w54jWrWrOmKAsbW+VvG1cAzX8O9EbQE5/4TWo0w/u3/1oyd8zwrVapkNPdl3HfffUbzvvL3p8ycOdPM8Xfm9+K5MH8RlxNI2nOQ6j4P5/REIIQQwaOFQAghAkcLgRBCBE6xzBEwBkb98ccfF9qxmBMYPny40U899ZTRY8aMicaM853tsGaeMVPmAfy9A2yjyPgsY+sDBgwwevPmzUYzP+HvM2D7SFpBJ7XBpA8M20dWqVIlGh84cMDMNWzY0GjGsLlH4a233jKaseL69etHY9aeMw69ceNGo4cNG+bSQar2zf53YqycOQO2NL3nnnuMpr0zf+u4PQtsF3nFFVcYPWLECKOrV69uNO+b5557Lhozr5nkY5TUYjOVHEGSLgh6IhBCiMDRQiCEEIGjhUAIIQKnWOYIChPGsSdOnGj00KFDjWZOgP46IcM4J2Pvvt+Pc87VrVs3GtOvh3F4er/zs3v37m30M888Y/SaNWuiMVs2stcB+0hwDwNr1eN8/hcuXGh0kyZNjGbvg86dOxtNLyJ6MlH7MEfFmHa6YA4gyS/I18wRsI0o96owL9KtWzejv//+e6P9XBTzUNw/wl4SzFfQP+ill14yeu3atdGYvlvMeSXV/p8Ocfs2CoqeCIQQInC0EAghROBoIRBCiMApljkC+q+88cYbRtP33/cNpwfNtddea3RSr4MJEyakdK4hwRpuxqTpte/Hv1njvnv37tj38vXM9TC349frV6xY0czNmTPHaPoD7dixw+iqVasa7ecfnLPXgfmHVatWGc19A/S4p98+e234OYJy5cq5OI4cORI7X1iw5p3eQ9Tly5ePxuy3wL0n/I7MFTHHwt4Tubm50Zj5B3o1sa8C92WMGzfOaPpd+b0RmF9I2heQFNdPysPEoZ7FQgghUkYLgRBCBI4WAiGECJxi2bOYsbulS5cazTirDz1o5s2bZ/Qnn3xi9OzZs//LKRZ70tGzmL78LVq0MJq10/49Q+989i5gXJn146wJ79Chg9H+PTF+/Hgzx9wGP4t+QdxXwDh23L8F1pMz9st9B/379zeaOavMzMxozFwG811+LN65vHstCgvmNfi7M0fj7yHhPgF+FnMEvG+4H4U9GPy/Hcwv8HdmHorXfvHixUan4vOftLci1RyBP59q/oH3f37oiUAIIQJHC4EQQgROsSwf9cuynMsbghBnBpbuMVTB8kX/EZZWCrReYEiAYY6srCyjWcrnl6MyNOFbOTuXN0TAR23Os3TVL0tkqIcWCgxPDBo0yOikcI8f6qCNMkMy1OmCoQjagxw8eNDonJycaMxWnHwvbbt53yTZO/shxYyMjNhj8X5lW1H+lqlYOSSFa5I+i98rLhyZioX1qdATgRBCBI4WAiGECBwtBEIIETjFMkcgiie7du0yetOmTUbH2XlkZ2ebOZb9scSN8V3GSFlC7OccOnXqZObYYpBx+9WrVxvNMlnO+3YCfttK5/LaGrCcdP369UYzH9avXz+j/bg1La6ZC6E9RbpgDJpxfOYy4qwvkmLlSe1gGff3rzfzUIyl872lS9s/h6dj+5BUbs/PTjq2D78Hj5VKmWt0vJTfIYQQ4qxCC4EQQgSOFgIhhAgc5QhEgeF+DtZZs/7et29m3JItGFk3zdg69zAw/utbD/jtCvODtfq002ZMm7F4f88DP4txZ+ZVuD+COYV9+/YZXadOnWi8detWM8e4Mq0w0gWPy5xBXAw7Kc5OzfuC0JrEf/2JEyfMXCo2Ds7l/R5Jsfk4kuL4SbmQuOuQdJ4FQU8EQggROFoIhBAicLQQCCFE4BTYhloIIcTZiZ4IhBAicLQQCCFE4GghEEKIwNFCIIQQgaOFQAghAkcLgRBCBI4WAiGECBwtBEIIEThaCIQQInD+D4jmbk/mPBEsAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -2681,7 +2548,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2691,7 +2558,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2701,7 +2568,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2711,7 +2578,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2727,12 +2594,12 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 43, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2742,7 +2609,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2752,7 +2619,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2762,7 +2629,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2772,7 +2639,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2782,7 +2649,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAYtUlEQVR4nO2debCO5RvHb78WlRCikooSsnfi2ImaokEkM5aINpFqSgv1h2kaY5omkTZaJppCI/ueJTKhENmXY19CtkTaf/89c1+fw3Of93Dec6bn+/nr+c79vu+zvM/93PN8r+u+7kL//vvvv04IIURi+V9+H4AQQoj8RQOBEEIkHA0EQgiRcDQQCCFEwtFAIIQQCUcDgRBCJBwNBEIIkXA0EAghRMK5MKcfLFSoUF4eh+F//7Pj0z///JPr3+ratavRLVu2NHrRokVGZ2ZmGj1//nyjx4wZk+tj4XlxLt/5nNuXF/MEn376aaN5Pj///LPRF1xwQbS9evVq01alShWjL730UqMvvNDemmXKlDH6999/N3rGjBnRNv/Dv//+2+hOnToZ/cILLxj9xBNPGL1mzRqjf/jhh2i7Xbt2pm337t1G//XXX0Zv3brV6L179xrdpEkTo/37jW1NmzY1etiwYUbv37/f5QWlSpUyOtQ//WdHqA+QP//802j/nnLOuYsuuuis+7r++utNW0ZGhtHVq1eP/e1Tp04Zzft7586d0fbatWtN2549e4w+ffq00TzvYsWKGf3HH3+4s8FnceiaHjly5Ky/Ff1G8BNCCCH+02ggEEKIhKOBQAghEk6OYwTnAj2tkC+YakygVatW0Xbfvn1NW6NGjYymF02/mN4027t16xZtDx061LTNmTMn9jjPJdZREKAvf/DgQaPpHU+ePDnavuOOO0zbyZMnjb799tuN/vjjj40uX7680UWKFDH65ptvjrb5H/fv39/owYMHG71gwQKjv/rqK6ObNWtmdJcuXc56nBs2bDC6cePGRh84cMDo3r17G71q1Sqjfe+Y9+a8efOM5jXMKxj3oEcdF0/kd/ksoE8f0iVKlDDav8/at29v2ho0aGA07xP+NuMTjBkcP3482l64cKFpmzBhgtErV640+tChQ7G/XbhwYaP9Z0foecr/IyfojUAIIRKOBgIhhEg4GgiEECLhFMrpwjTnMo8g1XkBderUMXrgwIFGM/+3bNmy0TZ9bHrRzAXmsRQvXtzoSy65xGjfm7744otNG3OHN2/ebPTLL79sNH3D80lezCPo2LGj0ceOHTO6dOnSRvt+ec+ePU3brFmzjOY9UrduXaPp3zLP2v8vOGeB+6b3S9/6yiuvNNr3gp1zrlq1atF2v379TBt9aObylyxZ0mh6wcuWLTPav7evvvpq0zZ79uzY4544caLLC+jLk7i8ds7pYB9ifytXrpzRjLnUq1fPaD9WxL7MfaU6r4fPCr+d9xSfMz/99JPRWVlZRjOmsG7dOqP952+qscajR48GP6M3AiGESDgaCIQQIuFoIBBCiISTL/MISI8ePYz+8MMPjf7tt9+MZs6tn5tNX4+1SG644Qaj9+3bZzS9aMYc4mqAXH755UbTz6T/y/P+7LPPjPavW154/qni+6/OObdlyxaj6f/6/xNjAldccYXR9DHp59J7Z82eX3/9Ndp++OGHTdu0adOMbtu2rdGcN9C8eXOj/Zoyzjm3bdu2aJtxkmuuucboTZs2Gf3II48Y/eWXXxrtn4dzztWsWTPaXrJkiWljHGXXrl2uIOLfu+xf/J9r1Khh9AMPPGA06yuxX/j3INtY74fw/uX3GUvyP8/z4rOgcuXKRletWtVoPxbkXPa6Xv6zgPGI8zE/SW8EQgiRcDQQCCFEwkmLNcRXLsJp9kzD5GsX4eulD1+jqHls1Ezvi7No+OpI24C//dRTTxlNa6gg2EE+LLHMUtKHDx82+qabboq2mRZIq4fXZvHixUa3adMm9lj8VN3ly5ebtvr16xvN0gy0pXgstGQaNmwYbbPUMUv+0k5jSQpaQbzXf/zxx2j7xIkTpu3aa681mqmWeUWopEHcfcv+x3Po3r270UwPJbRu/f+OlknIok61JLb/eVrGoWvE8ha8TypWrGj0xo0bz/rbPE+VmBBCCJEyGgiEECLhaCAQQoiEk5YYAencubPRRYsWNZrTs1mCmH5cXAyC/hl9fE6XD6WM+dDPpQdJX5xpiDxvls3NqxIBuYXXiuU7uNxe7dq1o22W0+C1Y0onl6b0Uzady17210/b5HVkOjJLZfDYWCqapTN86HEzVZUxBKYRDhkyxOjWrVsb7ccFGHPiccfFys4nIS+d7X6/YH/i9WPKNT8f0nHLYoZiBqFYZlwJ7dB3ue/QUqwsn79+/frY34/bV07QG4EQQiQcDQRCCJFwNBAIIUTCyZcYgZ+H7Vx2L4/+MctEMEbgfz/V3GHmBvPzccvC0RfkeXAOAs+Ln2/RooXRBS1GQJ+eviZjBP7SifzPtm/fbjSXj2RJZZZgZtzIn3vCkhEsK3LjjTcaPW7cOKOZ480lOf3yGJyDwPkOvL9YjpgxBd4DflkSlvTg/Ju9e/e6dMD7OFS+2b/P2Zd5z7A91D95LH7/D80RSjUfn9+Pe7YwBkAYb2AZHS7tOnr06Gg7rsyNc4oRCCGEyAUaCIQQIuFoIBBCiISTLzEC1tWg5xXyIInv1cV5+s5l9/no1dHbS2WJTnpz3BfPi/5npUqVcryv/IA58bxWpUqVMvr111+PtpnjnpmZaTTnKLA+EMuFs7yzP2eB8QV+dsyYMUaz9HFGRobR/B/9OjC8BocOHTKa5YXp448fP95ozrHx4zJdunQxbTt27DB65syZRg8fPtzlBanWGkqlDDVjBHExgDPtyyf0LGD/C32f2v/vQ9eE9wnPk/cY41h+3+I8l1CMJifojUAIIRKOBgIhhEg4GgiEECLh5EuMoEKFCkb/8ssvRtM/C/n8ofUKfOjzMWc8VDPEP5ZQ/IDtPC/WoucyhwWNrKwso/15As5lr/9TsmTJaNuvq+9cds/0zjvvNJr59lzab9WqVUb78wqmT59u2hjbCC0r+M0337g4/GO79dZbTRtrCU2ZMsVo1tvn8qWcq+EvRzl//nzTxvUJmHueLuJqC4U+e9lllxkdqt8Vao+bU5TqcyTUf/19MSYQmlPE2AjnEXBf/loTnNdyPtYt0RuBEEIkHA0EQgiRcDQQCCFEwsmXGAF9QXqdIT+N2vcC4zzDM7WHfMRQLnHcvkLzIfh55tIXNDhPgF4lYxx+DIQ1ZYoUKWI016blmsWsTzVo0CCj33zzzWj7xRdfNG1cB+KNN94wulatWkbT5+/WrZvRQ4cOjba5/jFrDb3//vtGsz4T76fixYsb7dci4nwb+sica5FXpDqPwF9XmH2X6yzznBhLCs0r8OcF8TkSmiMU6r+8/v7v8bucn8Tzoubay9y3H28LxQRUa0gIIUTKaCAQQoiEo4FACCESTr7ECOiDco1i5tfT8wr5hHGkGgMIrXsa913CXGF6lrwuBQ3m28+YMcNov2a6c84NHDgw2uYarMyXX716tdHffvut0YxPcF6CPzdl1qxZpu26664zmmsZcM4C/+OPPvrIaL9e0Nq1a00bYwSca8HzXLp0qdEDBgww2p+bwVga1zDu1KmTSweprgXs9zl649WrV4/9rVD8Ie7ZQJ8+9Nuh9UKofV+f65Ozr1911VWxv8XYCeOo/vdZIykUB80JeiMQQoiEo4FACCESTlqsIaZxFS1a1Gi+7jHFLlQ6Oo5USljnpj3uszxOlkc+fPiw0bwu/mt0qGRuOjh16pTRLGmwaNEio0+ePBlt81X5vvvuM5rppY8//rjRXH7SXy7SOZu62rx5c9P2+eefG80SJ9WqVTN67ty5RvO1f8WKFdF2u3btTBuXvZw0aZLRLJXBJTgfeugho/3r8MEHH5g22iqjRo0yukePHi4vCNmptGB8C5SWB5cRDZVvZn+m1RT3XaZopmoLsw/650lrh/cMjztUYoKpqn4581AZHFlDQgghUkYDgRBCJBwNBEIIkXDSEiOoUqVKbHvISw+VgYgrPRu3vNyZPp8KofLX3Jc/Tdy57EvOEX9Jz/Xr16d4dOcf/k9+DMC57OWbfZ/0tttuM230xunH0sdnWuWwYcOM9pdpZKkFpnR27drVaPr6XF7SL/PgnHNbt26NttesWWPaWJaaZTd4Hbi8JM97xIgR0XYo7Zr9Jq8IpWHGaXrn7BOh3z4XQiUmQmWo6dv7x0bPn/GEUNp6qByN3864CPtlbq6Z3giEECLhaCAQQoiEo4FACCESTlpiBCHv8ujRo0Zz6UrmjMflKafq+ac6z8D330J5yvT9WCKAHi/xp5UXhBhB6dKljeZykVz20/e7mSfNkhHU9N5ZBoJ+uZ9Tz/kO48ePN3rkyJFGv/3220bTc+Xv+fn5XGKTZTfogU+YMMHoLl26GP3aa68Z7efdb9y40bRx7sX+/ftdOgj1sTiPOlSOOZWS1mf6fFy8kPn37L/837lv+v5+/+ZzgrEQxhcYUyA8Fv/3Q/MfNI9ACCFEymggEEKIhKOBQAghEk5aYgTMpSaMCTA/neWPjx8/bjRLvMYRKmNLQkvQ+dBLpj/M8to8T8Jc+/ymadOmRrNODGvdVKxYMdpmbv/EiRONDsVbGGdijMD3a+vXr2/aWGvIL499pt9+8MEHjZ4yZYrR/j3Etl69ehnt1yVyzrnGjRsbPXXq1Nhj85fVXLdunWnjEpv+vJO8JFT/J27eD7/L2kOMq1Gz7zO2FFeHJ5W+fKZjZQwsLhYSqiVEeNw8bz+WEnpmKUYghBAiZTQQCCFEwtFAIIQQCSctMYKQhx/ywkO1hnLadibOZT2CkDdK3495yKHzLmgxAvr69EhvueUWo/2YCPOouYQjfX3m9o8dO9ZoxiNWrlwZbX/33XemLSsry2jm7mdkZBhdpEgRo48cOXLWY12wYIFpYxzo9OnTRnN9Avr+3Je/zOa9994b+91y5cq5dBCqmxPXL5hfTx+e8wpCc2/YR/x9hfp23FoGzoVr9vi/z/MgjBGE4hN8VvhzqUJzLVJ9BjqnNwIhhEg8GgiEECLhaCAQQoiEky8xAvp+fr65c9m9duaUM0fX98Ton9GnP9d1Sv383tD6qvSHuSZxiRIljOZ1YW2f/IZ+rF+X37ns/q/v52ZmZpo2/oeDBg0yumbNmka/9NJLRnPuif/5GjVqmLY5c+YYzTUB6NuzZg+9d39eAtc22LlzZ+y+6fPzt1ljyWfv3r1Gcy4F6zHlFal61H4f5HrkvA8YS2L/DNUm8nXoWUDo24fWG4nz4nncGzZsMJprXoTijf4cBl6DUIwmJ+iNQAghEo4GAiGESDgaCIQQIuGkJUZAL5xeJmvyFC5c2GiuV0B8Py3V9QXot4XWPPZ/P27tZOfCtYcYf+B14XXLb1izp23btkYz1uPn2E+fPt20dezY0ehmzZoZvW3bNqO57vWSJUuM9q/tokWLTNvBgweNZk0e7uvw4cNGV65c2Wg/FtSpUyfT9umnnxrNvHfmk/O69OzZ02jfW2YMijW8GIPKK0J9LC5GwD4Qgv2PcbO4uTvsX9S8nuy/oXhiXGyS14D3QWhuFLX/LGDNI8ZQGWfJCXojEEKIhKOBQAghEk5arCGWkT5w4IDRTEtkaVpOu49L0wxNf2e6GtP9+Hodl6rKV7LQvkPltA8dOmR0aInPdEPLjmnBtI4aNGgQbdNG6tChg9Gvvvqq0UwB5bV+7rnnjB4wYEC03blzZ9PG68jyFVWrVjWalguPpU6dOtE2l6bkcbJU944dO4zu16+f0fPmzTPaL3dRt25d08bU09DSp+kiLqWT9wz7CFM8mdIZSrH2nw20fWmZhEo/sz3OEuNnQzZx6FlB68h/doSW2FQZaiGEECmjgUAIIRKOBgIhhEg4aYkR0MdjeYBQGmZcOppz1jML+WP00/zyrmcilWnqoVK0oXQ0xkLSlQ6YU5j6t3jxYqPvueceo/0yybt37zZtS5cuNZrppI0aNTL6lVdeMZpxJj/9dP78+aaNpaFZrqJPnz5Gv/vuu0az/HaLFi2i7T179pg2vxy2c9k9caayTp482WjeX/5ylF988YVpY1o1S3zkFedS6p3PAqbTMjWSfYAxlrhj4W+nGhMg9O39Z0Oq1yRUvoLPHf/zjDUy9hEqn33G/aX8DSGEEP8pNBAIIUTC0UAghBAJJy0xAk7tZowg5GnRE4vLyQ3FCOjzcZ4A2+m/xZWhpsfI4yY8Vuag58bry0v8ZROds/n0zmUv7eCXauA8gbfeesvoFStWGL1582ajGzZsaHTfvn2N9ucObN++3bS1atXKaC5lyXkEFSpUMJr3m1+mmiUiuATn8OHDjR42bJjR48ePN5plqv0YAucRsDQGy1TnFXFe+Zm0D+d0hOKD9NJDcbY4752fDZViYMwvLobAaxL6Lo+Tmr/n62LFipk2zh9RiQkhhBApo4FACCESjgYCIYRIOGmJEdCHZ64w/TF65SwLXKpUKaP9PPGQr859MX5Bz5L1SvzP0/ejd8faQayhxGNlLZ+CFiNgmWl65/RF69evH21///33pu355583miW4ly1bZjSXcGR8okmTJtH2o48+atrGjh1rdEZGhtFcuvK9995zcUybNi3a5hKcrBXE+RCMXzCORL+3UqVK0XZWVpZpO3nypNFcGjVdpJJDz7kOoe+yf3JuQFwZee6L1ydUs4c6rvZQqJw9S8qH5izEzaUK1UzKDQXrSSOEECLtaCAQQoiEo4FACCESTlpiBIReOb3x9evXG8368YMHDzbazw9mrjA9RvprrO9Dry/Otw/lOA8ZMsRo+uKsVe/Xnncu/zzfs7F27VqjGTOg9+77/qtWrTJtjAM1btzYaM414b64vsGIESOi7Xbt2pk2rnfB/5xLUY4ZM8Zof96Ac85Vr179rMfBWjj0tNl+//33G03PfMuWLdE2YwQ8L17/dBGqre9r9q+QL0/Yn+nF++2h+Q6Ex0bizotxUO6LNaeOHTtmNOOLfE75mt8lqjUkhBAiZTQQCCFEwtFAIIQQCSctMQL6fowR7Nu3z+jixYsbzVxs5uT68xLoj3HfzC1mLjG/HzfngT4ez4vHTR+ROeOh+iP5Db135vbzfxk3bly0PXDgQNP2ySefGM1r1b9/f6O5xgCvjT+vgOtQV6lSxeipU6cazfkQXFeB/9vy5cuj7V69epm2UaNGGc01G+hx0+9lXMm/X2vWrGnaeF6cw5BXsI+EvHi/j/FahnLiOc+CzwpeT/++CMUuCD/PY42Lb/Aa8DnDGEFojgLPy79HGXfivlNdG8E5vREIIUTi0UAghBAJRwOBEEIknLTECMqUKWM0c8TpcXFt3N69exs9cuRIo/368YwvcB4Aa+qHaoRwTVrfq6O/u2HDBqPpoXONWa67S2+V55LfPPvss0azdj5r3/jrzfK6t27d2miuEcBru2nTJqPnzJljdO3ataNt1njicTVo0MDorVu3Gs3/nDne/u+x7tUzzzxjNL1hziO46667jOYavW3atIm2OX9m165dRi9ZssSlA/YReu9sj4t10YenV845HzNnzjSaa0T7MT2uR871ktn3eZz02unN+zXQWA+N8TKuVc2+w1gkYwj+vJu4OQbO5a72kN4IhBAi4WggEEKIhJMWa4iv/U2bNjWaqVZ8LeKrPVPyqAsqfGXj6yAtsa+//jqvDykluIQjj5/WV9myZaNtLulIS4D2zN1332306NGjjeZrvZ/SyfuJdgvtBpaQoHVJK8kva80yD+3btzd61qxZRj/22GNG815v2bKl0f514fVmSeuuXbu6/CCUlum3839mCXBeD9qttL/ibKpQmXjCfdMKiitvwWtQvnx5o2nzshwIrVPuy7eGQst1Kn1UCCFEymggEEKIhKOBQAghEk5aYgQs60ufNPR5EpeOFvIrCX1BpnDGLRkX8uboUc6ePdvoDh06GM1Uwz59+pztsPMFf+lJ57IvL8lr6Zd3Zqpsw4YNjWaZB5aUYPkOlrWuW7dutM0SEyzlwRRO+rGMhdDn9+MAvAZz5841ul69ekbTI2fJBJa38GMhvAYsj8LfzivY/0Lpin4/Ycor/3fGZ5gmzP+O8R//GvG4uK+4UhjOZe/PvE/88+JnGXdinJPnwfIhjH34KdGMrzGWoTLUQgghUkYDgRBCJBwNBEIIkXDSEiNgPvyTTz5pdK1atYxmKV+SmynUOYXeHPW58M477xjNaelconPhwoXnbd/nA3qo9HO55OO2bduibeb2c/o/fXxei86dOxvNZT1PnDgRbXfv3p2HbvCXf3Qu+7wWesFVq1Y12r8n6Nu3aNHCaM6hoafNfXFZVn+JTt4vmZmZRqerJAn98FDeuh9T4D3Nsg/8bziPgGWpuW9/eVfer6FSGFw+lb8d573zt1gi5fjx40ZPmjTJaN7vfMb5sRXO1zkf6I1ACCESjgYCIYRIOBoIhBAi4RT6NzeFKYQQQvxn0BuBEEIkHA0EQgiRcDQQCCFEwtFAIIQQCUcDgRBCJBwNBEIIkXA0EAghRMLRQCCEEAlHA4EQQiSc/wMsT1NcZqa11gAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -2792,7 +2659,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2802,7 +2669,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAU+UlEQVR4nO2defDNZRvGH21SSlEh+75FdkOIIVtkyYwyNdkyklG0lzL8oWlaRmNSTJNqKrLUkCgRWbNv2bOXIiK0ann/eOf9zn1/Ts7v0O+g97k+fz3XPD/nfM8533rme933cz15/vrrr7+CEEKIaDnvbF+AEEKIs4sWAiGEiBwtBEIIETlaCIQQInK0EAghRORoIRBCiMjRQiCEEJGjhUAIISLngkz/ME+ePLn2pnytU93TVrVqVadvvPHGZPzKK6/8o9fOiREjRiTj0aNHu7mvvvrqlF7rvPP8Ovznn3+e/oWBbOwTnDFjhtOLFy92evr06U7/8ccfybhmzZpurkyZMk4fPXrU6aVLlzo9aNAgp1977TWnu3TpkoztbxRCCA888IDTO3fudPr77793+pdffnH6t99+c9p+lvfff9/N/f77706XKFEipKNy5cpOX3TRRU7v3r07GfP+OHz4sNNXXHGF0xMnTkz73qdLbv6/QGSfTP5foCcCIYSIHC0EQggROVoIhBAicjKuEfwTTrUm0KlTJ6d79erl9Ndff+209WUXLlzo5uhjb9++3emff/7Z6fz58zvdt29fp62X/d1337m5yy+/3OklS5Y4PWvWLKdzsyZwJqD3fskllzh96623Or1y5cpk/Pnnn7u5Fi1anPRvQ0j1zmfOnOl02bJlnT548GAyrlSpkptjDYC/S5EiRZyuV6+e05deeqnTmzdvTsY33XSTm2Pt47LLLnOa9x/rTHXq1HHa1iMWLVrk5goVKnTSvxXiVNATgRBCRI4WAiGEiBwtBEIIETl5Mj2Y5lR7h22PfE5e+PDhw53mPoEffvjB6Z9++slp6/OzD7tAgQJO81ro4V511VVOszd7+fLlyTinegNf6/jx406//vrrTrPmcCrfIcnGPoLOnTs7Te+9fv36TttaDnveixYt6nTJkiWdZu/+hRde6DS/K1sX+PXXX90c93dwz0KbNm2cXrZsmdO333670/YeOP/8890cPf8+ffo4zT0KrFfUrl3bafs7rl+/3s01atTI6TFjxji9adOmkA20j+DfhfYRCCGEyBEtBEIIETlaCIQQInKyViOwXj39Xvab9+jRw+k9e/akfW/2+lvvne9FD5avxRpCtWrVnGavvPWft27d6ubo/9KLLliwoNPcd/D000+nvVZLTj9bNmoE3M/BPvYff/zR6SpVqiTj+fPnuzmbQxRC6n6Pli1bOt24cWOn+d3bmsGuXbvcHOtAFSpUcJr3gM2uCiGE8ePHO71v375kXLFiRTfHPS41atRwmn/Pe4Lfw+zZs5NxuXLlQjoOHDjgNLOhcgvVCP5dqEYghBAiR7QQCCFE5GQtYoKP/pYbbrjBacYx0zI5cuSI099++63TNgKgWLFibq5Zs2Yn/dsQUu2NY8eOOb1jxw6n7aM/rSBaVnxUZ1vjBRek//rtI9258DjOKAZGHtBy2bt3bzLOly9f2tfq3r270zbGIYTU9lNagPfee28y7tevn5tjHIW1W0II4cEHH3SaEdi8P21LMa1Etmzyflu7dq3T5cuXd5pW5sUXX5yMJ0yY4OYeeeSRtNcpRKbozhFCiMjRQiCEEJGjhUAIISLnrNQISpcu7fSJEyecZqwDvXT6wzbqgL489TXXXOM0fX76wzxq0NYvWF9g7AHh56Jvzs9p47X/6fGeucG6deuctv51CKnXv3r16mTMuA3GhEyZMsXp/fv3Oz1gwACn2WZpY66bNGni5tjS2bZtW6dXrVrlNI+bZDSIvf8YX8GaAGsba9ascZr3EOtntqbASIlDhw45Xbdu3SDE6aAnAiGEiBwtBEIIETlaCIQQInJyrUZwKh52Tv309NJZQ6CHmzdv3mRM75mvzThj+seMUmbUsvWuWX9gxAJ7zPnerKPwiMUNGzYkY8Ydn41jLnkNjGJgjcR+P7w/7B6DEEIYNWqU0zy6kt9t9erVnS5evHgynjZtmptjXAX15MmTnWbECfc42LjxkSNHujnGWfB+Yq//li1bnOa+FRtRwf8u5syZ4zQ/R//+/YMQmaAnAiGEiBwtBEIIETlaCIQQInLOSI2AMb/0OhnXzOMm2YNOb93qnKKgeewlfXteK2sOtu+bccfs4y5VqpTT9IN5rcxJsjWCcwH2yI8dO9Zp9rV36tQpGbPOwzjmnj17Ot2tWzeneXwp48GtP87aBbOr0u1x+bv5efPmOW2zrnjkJjOU6OPzc/Nad+/e7fRLL72UjHl/cb9Eto6mFP//6IlACCEiRwuBEEJEjhYCIYSInFyrEbA/2va50yu3ff8hpO45YC82PVvWEGy/Oj199ttfffXVTjMrhu/NzBvrg3OPAnOJmMWT7jsKITUHyXI2soUIPy9z/1kjsL/zwoUL3Vzr1q2dfvnll51+/vnnnWbODn8nux+ENSibQxRC6n4H/g48PpK/o51n/YH3Jr8T1ko4zyM47Xvx3ub5F6x3CZEpeiIQQojI0UIghBCRo4VACCEiJ9dqBOmyb5i5zj0H1OxXpz/OrCHrXdscmL+7Lp5fu3PnTqfps9LztfP8XLxOZg0x9541A9YYLDn1vp8JuAfjrbfecpo1hFq1aiXjjh07ujl64+zVf+GFF5y2/fQhpO7hGDRoUDKeOHGim2M9gWde81wI5kuRhx9+OBkPGzbMzfH+u/76653m/cTcLe4t+eSTT5Jx79693RzPP+YeGCEyRU8EQggROVoIhBAicrQQCCFE5GTtzGILzygmOdUM6KXTV7W+PT1/9oSXKVPGaZ5/zPdmzcBm8rMnnF4zM5JYr+B78Vot58I+AtZE6HezjrFgwYJkzH0APNuA9YXOnTun1VWqVHF60qRJydh6+CGEMGLECKeHDx/u9DPPPOM0zzRm//7y5cuTMe/tzZs3O71ixQqn0+1JCCH1nIVmzZol42PHjrk5fv/p7h8h0qEnAiGEiBwtBEIIETlnpH2Uj6y0Ofi4TBg5TFvBvh4jI9guyutkKyHtDcYV2PY+XveRI0dCOmgd0XZiXIHlVI4CzRa06BjXwdZHq2fPnu3mBg8e7DRbU3k0JY8FveOOO5y2rbqvvvqqm+NvymMxGXnCCApGVBQuXDgZM/q5Xbt2TtMqYrTGzJkzneZ3bONZ+N8RvyNetxCZoicCIYSIHC0EQggROVoIhBAics5I+yh9erZd0mtnWxy9T0ZQ2LgC+tQ84pCe/7XXXus0WwXpH1udk7dMTY+XcQT0h+3fM/bgbNQMjh8/7vS2bducpv/dtWvXZFy/fn0398477zh99913O127dm2nWcvZvn270za+mS2Y7du3d9rGNoQQQo0aNZxetGiR0/xc9v5t06aNm5s/f77T/Ny8P3l8aePGjZ0uWbJkMl63bp2bq1y5stP8fYTIFD0RCCFE5GghEEKIyNFCIIQQkXNGagSMWqAPf+WVVzpN337IkCFOP/fcc05b75S9+jz+kb37rE/Qe+fr2X53xhywJ7xBgwZOs1ayfv16p7kPwV47awSsJ5yJmGrGd/DzNWzY0GlbIzl69Kibs9EJIYRQrFgxp+nj26MoQ0jdL2JjIVavXu3mWDOoU6eO02PGjHG6SZMmTi9btszpunXrJmNGonPfAGHvf4UKFZy28RUh+O+ccdqMnGDdRIhM0ROBEEJEjhYCIYSIHC0EQggROVmrEdh8IMYXM1emXLlyTk+ePNnpN954w2l6utZ3peefP39+p9nHzfhjZhEx/8fuYaBHW6lSJafvu+8+p3kcI/NzeHyj9dzpPZ+NrCEepcmsobFjxzptr9H2w4cQQo8ePZyeO3eu07t373Z6w4YNTu/fv/+k18a60IwZM5xmFDmPk+Q+F2Zb7dmzJxkzxrxIkSJO2+M6Q0i9l1kjeOyxx5weOnRoMj548GDa6+rSpUsQ4nTQE4EQQkSOFgIhhIgcLQRCCBE5WasR2MyUdNlAIaT68PSDb7755rTvtW/fvmTMnKKiRYs6vXTpUqfZj0/NPRC2X5+eLf1e+t7shWdfOGsG7H+3pDv/IVswy2bv3r1OM2enb9++yZi/6a5du5xm5r895jKEEAYNGuQ09zB07949GTdt2tTNPfroo07PmjXLadY+uGejePHiTts6APeOcG8J9zRwH0H58uWd7tChg9P9+/dPxnPmzHFzrEnxCFchMkVPBEIIETlaCIQQInK0EAghRORkrUZgzwFgzzt7921fdgghdOzY0Wn6wcymt94oPX1mC+WU2c7ebO55sLCewJoB9xHQU+e/57Uxb/5sw++SPn/Pnj2dtuct8DekV87zB3gPMINn48aNTtszi7m/4/7773eaNSpbXwghNV+K2tYQmjdv7ub43rxXhw0bdtLXCiGEgQMHOm3/22EWFe9VfkdCZIqeCIQQInK0EAghRORoIRBCiMjJWo3Aerb0Mpn5z3meK8w8F/qq1otm1gtfm34v4XvZzCRCj59+cMWKFZ1mnzdzkJhtb/cZsPbBesSZgDUBZvRMnDjR6QEDBiTjzp07u7mRI0c6zV7+0qVLO83Pa88oDsHvueD90bt3b6e5p+HTTz91mnlU99xzj9PvvvtuMp46daqbu/POO51mbhH3HbBuxN/ZfhbuG+D5A9yvI0Sm6IlACCEiRwuBEEJETtasIdv6SMuDbYh8pGULHh/V+e/t6/PYS3tcYgipVhFfm7ZCOmuIcRY8jpHQlqJtwGhlayUxhuNsWEOM+OY19evXz+k1a9YkY7Y+8rPz+EhaRzVr1nR63LhxTi9evDgZW0sqhNRYc1p6jMa46667nGb7c6lSpZJx69at3RyPYWX7MaO7W7Zs6TSP4LRHVdIKKlCggNP8fYTIFD0RCCFE5GghEEKIyNFCIIQQkZO1GoE9mpDHDtLLZOQEPVl6uvT17evxmELWE4htPQ0h1eNlHcC+Hq+b9Qf6vYxRWL9+vdP03K2/zHjjHTt2hDNNTvUX1i2s/81/u2LFCqfZmvrUU085PW3aNKd59KWtGSxcuNDNMcKEPn3Xrl2dZl1o7dq1TtuWT7a5UjP2nPdMo0aNnGb7so3aYIQE25VbtWoVhDgd9EQghBCRo4VACCEiRwuBEEJETtZqBNaH3bZtm5uj50/flBEUPJaR2nrzjKfge/G17dGTIYSQN2/etNdm9zywVkFvmR46fX5GMjAew8ZS16tXz819+OGH4UzDGsfYsWOdtseThhDCkiVLkvHQoUPdHOtE/N5ZA6CPz1qQjX3gvhS+1uHDh9NeC+tCbdu2dXrTpk3J2O5fCCH1ONKGDRs6zWNXueeBexjs/ct9A/Xr13f6xRdfdJrx20KcDD0RCCFE5GghEEKIyNFCIIQQkZNrNQJ66QcOHEjGzBoqVKiQ09w3QB+fvf18LxvnTB+V0B9m7C/fi9dSsGDBZMzed34OZibRi+Zr05u231uxYsXC2Wbu3LlO099mpLLNSrKZOSGkxjHzdxs/frzT1113ndO8B957771kfNttt7k55hSxLsR9AtyjYWsCIYRQtGjRZMy9H7yfuIfm448/dpq1Hx7hafdfcI/BvHnznObvIUSm6IlACCEiRwuBEEJEjhYCIYSInFyrEdDDtb397Ptnbz99+XTnDfzd39s9C/Z4xxBSfXieN2BrGSGkery8dutl8zr4uZjBz/0U7AOnF23rAsyVYZ3l0KFDIdt0797daZ6/QG+9adOmyZief+HChZ3mngzOs8ZQtmxZp+1RmE8++aSbe+ihh5xmbad8+fJOr1y50mnuS7Df/fTp091c+/btneZ+h3Xr1jnNvSW8Nvu5WT9grtHGjRuDEKeDngiEECJytBAIIUTkaCEQQojIybUaQe/evZ22Pip9enrp9OHZj094Dqztr+b5Ajav5+/+Lc+Mpe9K397WENjXzX0A9HR5bcWLF3eaOTU2u4h/27x5c6d5Lm82mDp1qtOVKlVyukOHDk7bfn367MwWsmdchxDCZ5995rTN5Q8hdU9D9erVk/FHH32Ucu0n+9sQQpg0aZLT/B25h8PugejWrZubmz17ttPt2rVzuk+fPk5PmDDBaXsecgj+nqhbt66b473J+0eITNETgRBCRI4WAiGEiBwtBEIIETl5/srJkP/fH8LnJ8zSHzhwYDJmTj1fi2fInjhxwuktW7Y4zbOA7XvTz50yZYrT7E/v1auX0+xnf/PNN522ewN49gH3P9AHz5cvn9M2tyiEEL788kunbU7NmjVr3Bwzk7Zu3ep0hj/rKcHMHu7Z4Oe32Tf8TdkvzzONN2/e7DTPQ+Z3ae8RZg3xDGPu/7D3agip+xB4/9apUycZz5gxw83Z3KsQUnOMWINixhJ/V5tNxH0n3Etis51CSK0/5BY5/b9AnFtk8v8CPREIIUTkaCEQQojIybX2UUYgPP7448mYrX6M7s0JPm43atTIaRvvzNhfto/aCOEQUttJbTRGCKn2x6pVq5IxowloWXXp0uWk/zaE1LZZ2gJjxowJ5xK0NdjCOnr0aKdHjRqVjFu0aOHmaHVVq1bN6R49ejj9xBNPON23b1+nS5QokYw3bNjg5th2ybZfxlXQhmKcuG2jrVq1qpvbvn27002aNHGa8du8X1u1auW0tddoaTFWhPe2EJmiJwIhhIgcLQRCCBE5WgiEECJycq1GkI5bbrnFabbBMa6Z9QZunec2/DZt2iTjIUOGuDn6qGxV5Txb8lgjsFEJNWrUcHNsaWT7KHn77bedXrRo0Un/lq/FdkzWG7IBazW8XsZEWN+ebbysn9CXf/bZZ51mmyWjHezRlfTZ2ebL4yEZ3zx48GCnGUMybty4ZMya0hdffOF0p06dnObnZCsmo0RsWy3/O/jmm2+cZkuuEJmiJwIhhIgcLQRCCBE5WgiEECJyci1i4lyBURc2DiCEEGbNmuU0vXZGEPOIRdtDvmLFCjf3T48K5Hdsf5qcortJNiIm2BPP73bPnj1O2/0drMXQz2Z9hf35CxYscLpChQpO2xoC45lbt27tNGMfGPXBmgLrSrZuxNoF98gsX77c6QYNGjjN+4vHf9o9EbVq1XJzjPzgUagffPBByAb/lv8XiP+iiAkhhBA5ooVACCEiRwuBEEJETsY1AiGEEP+f6IlACCEiRwuBEEJEjhYCIYSIHC0EQggROVoIhBAicrQQCCFE5GghEEKIyNFCIIQQkaOFQAghIuc/Ogw5jttBx+gAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -2855,11 +2722,11 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 73.34it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 73.31it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 73.30it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:25<00:00, 73.27it/s]\n", - " 85%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉ | 1592/1875 [00:21<00:03, 73.91it/s]" + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:38<00:00, 48.63it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.76it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.43it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.59it/s]\n", + " 73%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍ | 1360/1875 [00:28<00:10, 48.00it/s]" ] } ], @@ -2876,7 +2743,8 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet().cuda()\n", + "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", @@ -2900,7 +2768,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2910,7 +2778,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2920,7 +2788,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2930,7 +2798,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAV7klEQVR4nO2dZ5AU1dvFL6IgIgKSFJCkwJJEEAQlrBJWkKyCBaKlBLGkFFlTIUgJhVqKFoVVYAJBVLAKgZLoIkFyFCRnJUoSUJKIIu+nf7/3nNntnmZmdne45/fpnroz0z09zV76eZ57njyXL1++bIQQQjjLNTl9AkIIIXIWLQRCCOE4WgiEEMJxtBAIIYTjaCEQQgjH0UIghBCOo4VACCEcRwuBEEI4zrXRvjBPnjyJPA8RZxKxT/C1114DXaJECdAHDhwAvXr1am88bNgwmFu8eDHoVatWgb7mGvw/Sr9+/UDv27cP9B9//OGN165d6/vaYsWKga5Vqxboo0ePgj558iToChUqeONrr8V/Qvny5fM9VpkyZUAPHz4cdO/evUHv3r3bG+/cudP3WDfeeCPoCRMmmERQoEAB0Py3we9vxaVLl0K9N5b7OMx5ZXasMOfGc//991+oYwV9T/vzg75H3rx5QZ85c8b39cboiUAIIZxHC4EQQjiOFgIhhHCcPNGazilHkFwkIkfwzDPPgN60aRPo1q1bg54xY4Y3Llq0KMylpKSA/vvvv0EXLFgQNMfDN2/eDLp69ere+MKFCzDXrFkz0N27dwc9ZMgQ0Py9ihQpAvr06dPeeM+ePTDXvHlz0Nu3bwddvHhx0KVLlwZ93XXXgT5y5Ig3/uuvv2CubNmyoBctWgR6zpw5JhHccMMNoDkm7XfvhYmFx0rQscL+G/E7t7C5jbDXwS8fwfk0zk+cO3fO91jG6IlACCGcRwuBEEI4jhYCIYRwnKj3EQhRrVo10Fy3fv78edD169f3xkuWLIE5jpXXq1cPNO9J+Pfff0FzLN0+Nr922bJloD/++GPQnG/gc+P3P/74496Y91L88ssvoLt16waacwa8R4Hn09LSvPGYMWNgjvdm8D6DRBG2Zt6PoHr6WHIGYeP0QccOc25hr0mYYyUiX6snAiGEcBwtBEII4ThaCIQQwnGUIxBRs3HjRtDLly8HXbVqVdC33HKLN7br/I2JjOPbtfnGRPr9cMw1f/78oO34ONfbt2nTBvT8+fNBnzp1CrTt72OMMS1atAA9cuRIb/zyyy/DHNfUc65j//79oHl/xbZt27L8PPZ6ysjIAN2uXTuT2wnr9xP2/X7wXpQg+J7z07HsC4jm9bZOxDXSE4EQQjiOFgIhhHAchYZE1Bw+fBh03bp1Qd96662gL1686I05JHL27FnQbDFx9913g+bHXbZ2sG0juByUw0gdO3YEzWGouXPnguZQ08CBA73x+vXrYa5QoUKgeXv/9OnTQaempoJmu+2tW7d648GDB8NcuXLlQNv22NlJPMsZw34Wh2uuv/56b8wW4ZUqVQLNoUz7fjUm8r7g+9+2PufwIts+hLXEjgU+dlTvScB5CCGESCK0EAghhONoIRBCCMe5KnIE9913nzeeNGkSzNk2vsZEWgwHlXVxqeGOHTu88bp168KfbBLTuHFj0HYrysy0XTpZo0YNmOvUqRNo27LamEhLioMHD4LmuH3hwoW9Mcd677nnHtC///476GPHjoHu0aMHaG59aX8+nweX1DZq1Aj0q6++CnrmzJmg2c5izZo13pivGcel7fh4TuJnjxBrmSVbi7Altn2fPfzwwzDXoEED0GwBHmSvbecEjEHb79GjR8MclwFzuTTrMHYYQfmFK7H80BOBEEI4jhYCIYRwHC0EQgjhOEmZI+A44bhx47xxgQIFYI7jwaybNGkCunLlyqDbt28P2rZe/uGHH2DurbfeAs0x82Rn3759oNkW4pVXXgFt2z1z3J5j/hzX5Phs3759QVepUgW0Hefnem+OqU6ePBn0O++8A5pbPnKOoU6dOt74jjvugDm+f/h+5JwAW16XL18e9Pfff2+yYsuWLaA5ht2nT58s3xsL8W7L6AfXxN90002gn3zySdAtW7b0xnxt//nnH9C8T4D3HfD+EzsPZYwxXbt2zfS4xhjz4osvgl6xYgVozl2GIRFtaPVEIIQQjqOFQAghHEcLgRBCOE5S5gg4Zjt16lRvPGDAgIQe+7HHHvPGo0aNgrk5c+aATk9PB/3FF18k7sSygePHj4Nma+kNGzaAfvrpp70xWzvzazkey3XWCxYsAM3xXrsG3PbnMSbSg4f3Q7z33nugOVbMeSX79Z999hnMcfvIhg0b+p4Lt6bkWLJ9HTgHwHXyhw4dMtlBLDHqsPmFoGNzrsnO77AfFd+D/Luy/xXnIkuWLAn6kUce8cbPP/88zHXu3Bk031PsOcVeW/Fs2RkNeiIQQgjH0UIghBCOo4VACCEcJ8/lKIN0iY5RhYFjd3YN+qVLl7LtPOrVqwf666+/Bs3xy+bNmyf8nP5HImqNW7VqBZrj3VxDP2vWLG9cq1YtmOOa7CJFioDmWn6uH7/ttttA220IeR8B5zbatm3rO8/15TyflpbmjVetWgVzdntOYyLbXM6bNw/0lClTQLM3ke25xD0a2OeIvXS4lj1eFCxYEHRQ3N/vb0fYWDjvK+D2k3Ysnq8P71WJtX2k/VuxhxT/2+A9R4MGDQLN+Yl4/r3lnhiZoScCIYRwHC0EQgjhOFoIhBDCcZJyHwHXkOcUQT5F7HOf7HTp0gU0e/YsXLgQdNOmTb0xx/y5vzHH9U+cOAG6devWoNlnp1ixYt6YfVxSUlJAs28/+/ovXrwYNPvZZGRkeOOnnnoK5r799lvQnCdiD6WyZcv6vt7et8JxY65F52uWqBxBLDmBIPizguL258+fj/rYQX2DWXNOgfMRFStW9Ma1a9eGOb6n+H7lXGZO52D1RCCEEI6jhUAIIRxHC4EQQjhOUuYIEgnvUWBfoxEjRnjj+vXrw9zSpUtB9+/fP85nl7Owl9Jdd90FmnsE2DX1qampMNevXz/Q3bt3B82xdrt235jI+LgNe/BwfoK9iHgvQM2aNUFzTsG+J9gjqU2bNqCHDh0KulKlSqA5Nsy5E7seffDgwTBXtGhR3/POLhIZ3w7KR/C+AnsfAfv7cMyfNe+P4L0AvG+oV69eWX7WtGnTQHMfCu7Pkd3eQoyeCIQQwnG0EAghhOMkpcUEY1sQ2+No6NmzJ+hHH30UNG/rt7drv/322zA3evRo0H/++Weoc4knibCYsFtPGhMZRuOyS/txmUNDY8eOBc2P5WzVwLbU/NhutxD9+eefYY5DJnxtuOyXQ0ncgnP8+PHeeN26db7H4u39bDfMNghnzpwBbbdb5O+8ceNG0ByqTJQlu32tjQl3r8VqKcHltxyas61IOAzHoUtuM1q3bl3febZBsW2suaUo282sWbPG+BG2lNUPvsZcYpsZeiIQQgjH0UIghBCOo4VACCEcJynLR9kOefjw4d64Ro0aCT323r17vTHHh3MyJ5AdcLtItn2oWrUqaNty2bZTNsaYdu3ageb46+nTp0Fzm0bm5ptv9sZc1srHKlWqFOhJkyaB5pwBx/Xt771r1y6Y49zGjBkzQJcrVw40l6Zyq8oCBQp4Y87JsBU3n2eiCGsDYce7g3ICPM/f2bYSMSbS5qV9+/bemO9H/m34nmM4v+MXx+dcBv/Oa9euBR10zfzmY3lvVuiJQAghHEcLgRBCOI4WAiGEcJykzBFwrM6O5W3fvh3mJk6cCJrjqJ9//rnvsbjVYJ8+fbwxbyPnevNRo0b5fnayceedd4JetmwZaK7btuvNuU0nt+5jOwA+Ftfn79ixI8vXszU053I4R8D3E1sE2y03jTGmcePG3viJJ56AOa5r5/fy/cn7VKpXrw66TJky3pjj4Ww50bBhQ5MbiKcNNVs/B7VHtVs+sk06W3zzng3OCfA9yTkG2yK8U6dOMFeyZEnQbDGRXfmcaNETgRBCOI4WAiGEcBwtBEII4ThXhddQdmK3pGN/kd27d4PmmG52kgivoWHDhoHmVpxcO23H8bnmnS2UOX7L3izp6emgOfZu35/cypRrvAsXLgya93/s378fNHvO7Ny50xtz+04+Fu8j4Hti9uzZoHkfjO2xxHXxfI3s1onGGDNkyBCTCNgXKsw+grDwPgKu/eeczIULF7yxnS8wJjL3E7Qfgv2t+Fzs/M6gQYNgjn+Lbt26gV6/fj3oIMtsv2sYtp1nZuiJQAghHEcLgRBCOI4WAiGEcJyk3EeQk2zYsMEbc1yQ2y/aPjHGRHrPJxurV68GzZ5PHPc8dOhQlu+1vYGMiYzbc4tQ7oXANeC//vqrN+aeEgcOHADN7SDZB+bUqVOgeU+DHWteuXIlzD300EOg69SpA3rq1KmgH3jgAdB8HX766SeTFfy9gvyY4kUicwIM53vsHgDRnIsfQW0wGY7bb9myxRsH9YbgnAHfN5x/8Du3sH5N0aAnAiGEcBwtBEII4ThaCIQQwnGUI4gjKSkpoG2fGGMi9xkkG2XLlgV99OhR0Bz3L1++fJaf9c0334Dm2Ljd9yGzz65WrRrozp07e2O7zt8YY7p27Qqa9w1w7T7Hb9kD384TsTcQ3wO8J6FEiRKg2UuHe27bfk2cq2CvK45L50aC4tdhY/5+PQLi7dvPx7JzfrwPhn9Hu5dyNPjtcQjqb6wcgRBCiNBoIRBCCMfRQiCEEI6jHEFIChUq5I3tuLQxxqxatQp0sucEGK6v//TTT0Hb/WKNQY8e9sW5/fbbQbOvPMfxOUfA/j92vT37xh8/fhw0e8PbMX9jgj1m7J7ItreNMZHfc8yYMaA5b2T3dTYmMuewaNEib8z5BPY5Yu+rnMIv9s5eTPzaoHnWefPmBe2XI4il13Jm2P2m2UuL97mcPHkSNN9TYbyFglDPYiGEEKHRQiCEEI6TlKGhli1bgua2h4nEtmJOS0uDuaFDh2bbeeQEbM3w3HPPgT59+jRo2zK4ePHiMMdWxrZFhDGR1rlsUcFlmLb1wP333w9zHBriR+fU1FTQ9iO/McZMnz4dtG0bwdbG3IKwXbt2oLnkk68DhxM7duzojdlugdte9urVy+QEYcIYfO35vXztOVTEIRSev3jxojfm3ybsuTF87AYNGnhjtgg/fPgwaLbGYNvpeKLQkBBCiNBoIRBCCMfRQiCEEI6TK3ME3I5u7NixoLm0MJE5gp49e4J+9tlnvTGXIb755psJO4/cANtM8+/EcVLbJplLTznezTYQo0ePBs1x/w4dOoAeMWKEN+Zy0CpVqoDmMtfNmzeDZjtntnbo06ePN54zZw7McekqlxSzXcW9994LulKlSqDtstk9e/bA3KZNm0B/8sknoNu2bWtyGxy/5pwAf3/OSzFs7W7/lpxn4lLToPwDay797dGjhzcuWbIkzPFvxeWkfC5hS1uv9LVZoScCIYRwHC0EQgjhOFoIhBDCcXJljoBrqTmuyrXZ8eT9998HnZ6eDnrUqFHe2N5T4AK8jZ5rpbdt2wba/t2aNm0Kc9yK0o7xG2PMyJEjQe/atQv0uHHjsjxWqVKlYI5bUXbq1Ak0x5kzMjJAs532lClTvDHHfrm1JMdveQ/M2bNnQX/33XegS5cu7Y1te5PMdHbZUAfZQDD2XgHeN8DfoUmTJqB79+4Nevny5aBnzZoF2s6pcIyf8xFsfc6wDQTnc+xWtJxnWrZsGWi2IuEcQdg9D37IhloIIURotBAIIYTjaCEQQgjHyZU5gqCaWq7fjwXOCbB/zrvvvgt60KBB3jiecb1kwG6baExkzJTb8dnxXI6hTp48GfRHH30E2rZ6NsaY8ePHg27UqBFo22OGc0xc/8319uyDxLFhbjt47tw5b8wtN+2YvjHoR2OMMVu3bgXN9zYfe8WKFd64Zs2aMBfk05Nd8Hn4/fvl2DhbfnN+h387vi/mz5+f5efx78a5DYZ/uwoVKoAuV64caDtvxeexb98+0OwtxL8V56nC/G0Juv7RoCcCIYRwHC0EQgjhOFoIhBDCcXJljiCecJ3yBx98AJo93DknMGDAgMScWBIS1AJyxowZWb6e9w2wN8vw4cNB//jjj6DbtGnjeyw7R8B9EbhenH2O+Ny4R8CHH34IumHDht74jTfegLmlS5eCzp8/P2i+3xYuXAh6yZIloO09DwcPHoS5Y8eOgeZWlZzvihdBPQX84Np+/i3snIgxxrRq1Qp00aJFQXNOxc7f8LXnnAH7GPEeBs4Z7NixA7T9e5w4cQLmOBfC+TO+R7mPBedO7GsedL21j0AIIURotBAIIYTjaCEQQgjHyZU5gv79+4OeMGECaPaTr1WrljfmWusHH3wQdFCvA45Vi/+H46DcY4D1Sy+95I3ZI4bhfQEch+bYMe9hmDt3rjfmfQG8r4B7H0yaNAk0x3ebN28O+tChQ96YezRwHN++N40x5oUXXgBdrVo10M2aNQNtx7mDvPvr1atncoJYvPPZg4fr7/n6cp6Kf2s7h3DkyBGYY18nzlcsWrQINOcYuA+KvS+BP5t7IXAug7930L6BWPpCR4OeCIQQwnG0EAghhONoIRBCCMfJcznKgNKV1KZeKbbPtzHGrFy5EjTHXW04xjhv3jzQs2fPBj1t2rQrOcVcTzz6mDIcz2adL18+0PbvaMfVjTGmdu3aoPn+4r7DAwcOBL1//37QCxYs8MZ2vsAYY9LS0kBzfwHes8C9Ezjey72CbSpXrgyaY78VK1YEzT0c7D7PxhjTokULb8we95wP4/PmGvx4wfssYtlXwB48/G+f8x68/4T7VGzZssUbB8Xd2XuIz4XziYxd62/vXzAmMifA5817QDjHwPsIbML+2+b7NzP0RCCEEI6jhUAIIRwnV4aGROwkIjTEbRa5nJFDRSkpKd6YS/PYKmDv3r2gu3TpAvrLL78EzSWhdrjQDqcYExnKYOtoLhe1LSSMiWyVaodoOJTBliYcllq8eDHokydPgubyU/vzuHyRw1Bc3vvVV1+ZRMBWDWHgcExQeIZDLBzu4ffbZZlhrRi4nJRDnYxtj8Hnyfc3W0xwm1cOLflZTDD8PVhz2Ckz9EQghBCOo4VACCEcRwuBEEI4jnIEVymJyBFw/DY9PR002zW//vrr3phbVXLbPy7V4xaFXH7aoUMH0D169PDGbCHBcXuOK2dkZIBmS2C2Sk5NTfXG3Fpx586dvufNvwvnJ9atWwfazk90794d5rhUmi3TE9W6knMEsbSqDNIcew9qN2m3fOSYPxN03mH+5vF58rXnz+acAJ+r37kHnSfrM2fOZPlZ/0NPBEII4ThaCIQQwnG0EAghhOMoR3CVkogcAVt72G0UjTFmzZo1oO2abq6n523vvAWf22ByTTfnEOy6a273yDYOvE+AcwicC2Gbg4kTJ3pjjvXOnDkTdN++fUH/9ttvoLm+nK+D/Xo+Fv/G3P7Qtt2IJ5wj4Lg91/rbfzv47wi/N+w8Y8fW/XIV0XxW0Lxf+8ggzdco6Fz95vizg+6TzNATgRBCOI4WAiGEcBwtBEII4ThR5wiEEEJcneiJQAghHEcLgRBCOI4WAiGEcBwtBEII4ThaCIQQwnG0EAghhONoIRBCCMfRQiCEEI6jhUAIIRzn/wB6dc1jJr3khwAAAABJRU5ErkJggg==", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAQtklEQVR4nO3de0zVZRwG8C8mlpC3xLuEYiIaThE0JTVvKDabrbzMWVtbNcuttVytbNWaq7bstrbon+41y7WmecmleZl4zVIULyBpihgmmiJYYKb2V7+9z0Oec0SPcnyfz1/vs9c4Pw6Mt/Nevm/chQsXLpiIiHirybV+ABERubY0EIiIeE4DgYiI5zQQiIh4TgOBiIjnNBCIiHhOA4GIiOc0EIiIeK5ppP8wLi4ums8hV1g0zgnOnDkTcocOHSAfPHgQ8pkzZ4J2VVUV9D300EOQt2/fDrlZs2aQ16xZA3ny5MmQN2/eHLRvuukm6Gvfvj3kkpISyMnJyZD5dz0+Ph5yeXl50O7atSv0JSQkQP76668hT5w4EfItt9xioSxfvjxojxkzBvr4Pdq9ezfkTz75JOTXbij9LYgtkfwt0CcCERHPaSAQEfGcBgIREc9FvEYgUldXB/no0aOQ3TUBM7PRo0cH7eLiYuh7++23IR85cgRybm4u5MTERMg8Hz58+PCgXV1dDX08p33zzTdDPnv2LGSet6+pqYE8YMCAoN28eXPo++mnnyCPGjUKcpcuXSDz/O3OnTshZ2RkBO127dpBX1FRUcivLRIpfSIQEfGcBgIREc9pIBAR8ZzWCCRiPM8/ZMgQyE2b4q+T++95nj47Oxtyeno65JUrV0IeNGgQZP567jkCnvOvra2FnJqaCvmff/6B/N1330Fu2bIlZPdMxL59+6AvKSkJcps2bSDz3n9+bXdNwMxs2bJlQds9v2BmdurUKcj8HopESp8IREQ8p4FARMRzGghERDynNQKJGNfV4Zo+vEbg5tatW0Pf3r17IfNe/SZN8P9ReJ7++PHjkN39+qtWrYK+6dOnQ96yZQtkrj3knn8wq39moVu3bkGb1yM6d+4Mmb+vDRs2QO7evTvktLQ0yO77NnLkyJBf+/z58ybSEPpEICLiOQ0EIiKe09SQRKxTp06QT548GfLf33jjjUGbp4Z4GolLWHfs2BFyaWkpZN6W6ZZmuP/++6Hv1VdfhZyXlwc5KysL8rp16yCfO3cO8h9//BG0ubw2f199+/aFzFNi/L48+OCDkN1prYqKios+h5nZr7/+Cvm5554zkUjoE4GIiOc0EIiIeE4DgYiI566LNYKcnJyg/dVXX0Hf77//DpnL/HKpAi4LzFsR3Tnebdu2XfrDxjAuQ+2uAZiZtWrVCrJbNpm3e3JJZf458Xw4r0/wz83dAsrrC48//jjkw4cPQ+ZnmzBhAuSCggLIY8eODdoLFiyAvl69ekHmrae8xZPLb8+dOxeyW2pjypQp0OeW1TCrv+1VJFL6RCAi4jkNBCIintNAICLiubgLPCl+sX9Ic7LXUnx8PORdu3YFbd5fzlcH8hrBsGHDIPfs2TPka7vXHP7www/Qx/vVuZTB1RThj/WSzJkzBzKXOOB97e68P7/P/HPh9Qa+9pJfi39OQ4cODdoDBw6Evg8//BBySkpKyK/NZwG43Pann34atPlay7///hvyb7/9BpnPFbRt2xYyl5Z212W4PPb48eMh87WZs2fPtmhoTH8LJLxI/hboE4GIiOc0EIiIeE4DgYiI52JyjeDOO++E7O77jta86H+mTp0atPPz86GP36NZs2ZB/uyzz6L3YCQaawT8/fAaCc9/u+spXEaar2hs0aIF5MLCQsg8F8/lnt11I15vOHToEGR+b5KTkyFzCWxeV8rMzAza7vdoZvbtt99CHjFiBOQ9e/ZA7tGjR8hnTUxMDNpc8prXUXjd5MUXX7RoaEx/CyQ8rRGIiEhYGghERDyngUBExHMxuUbA5wjc+i1cOz6asrOzIc+bNw8y17S5mrVgorFG8NRTT0Hm95rn5t3fmWPHjkFfRkYGZN5vX15eDpnf67KyMsju3PukSZOgj+v0cy2i7du3Q+YrOXkdIDU1NWjz2sU333wDmd8j/r7S09Mh8/Wf7lkMfi4+78BrCG+88YZFQ2P6WyDhaY1ARETC0kAgIuI5DQQiIp6LyfsIeC70WglXp6iysvJqPk7UuXPjZmZFRUWQu3TpAtk9ZzBo0CDo45/hrbfeGvJr8d2+XJPH/VnwPREDBgyAzGsZ06ZNg7xp0ybIf/75J+RFixYFbb7rgL+PPn36QOb1iJ9//hkyv0/t27cP2lzHqLa2NuRzi0RKnwhERDyngUBExHMaCEREPBeTawTRxGcUeM72nXfeCdpc9379+vWQed99rOM1Ad7XvnbtWsjuHvqtW7dCH++/53l83k/PawIHDhyA7P4s+P5jPkeQkJAQ8rn5TMNrr70G2b2H+IYbboC+fv36QeY7Gjp06AA5NzcX8o4dOyC7NZX4++JzKv379zeRhtAnAhERz2kgEBHx3HUxNeR+1OeP/eE8/PDDkLk8QVZWFmR3K+Hzzz8Pfe+//z5kns6IdVwuoaqqCjJPe/zyyy9Bm6975BITS5YsgczXLvJU0unTpyG7U3pcypnLlp84cQKye82lWf2rLfnZ9+/fH7SXLl0KfSUlJZD595G/r3HjxkHmqSG3XPdff/0FfSdPnoTcu3dvE2kIfSIQEfGcBgIREc9pIBAR8VxMlqHOy8uD7Jbbvf3226P62u7Wwaeffhr6li9fHtXXvhTRKEP9zDPPQHbnys3qz9u7awb8+8Olnd31BDOzO+64A3JNTQ3ku+++G7J7ReTw4cOhLy0tDTI/y8aNGyEfPHgQcq9evSCnpKQEbS5n0bZt25Bfu02bNpB5nYXLlBQXFwdtfs848zZZLol9pTSmvwUSnspQi4hIWBoIREQ8p4FARMRzMXmOgOco3b39vI/7yy+/hHzmzBnIH3/8ccjXGjNmDOQZM2YE7YULF0Ifz6Hn5+eH/NqxhktDcxkILsHslljmKxr5zMHYsWMhr1mzBvKoUaMg83qMuzbE5x14rpxLMfB+/CZN8P+PWrZsCdmdi+/evTv0uaW3zcxKS0sh83oDW7x4MeTMzMyg3aJFC+jjMht8nadIpPSJQETEcxoIREQ8p4FARMRzMXmO4Fpyywx///330Ldv3z7IfJXl1RSNcwTz58+HzPPZXKepoKAgaPP1kFxSmWs6VVRUQO7YsSNkrsnjXgHJpZ/5Osnq6mrIZWVlIfsHDx4M2a35w+cG3Kslzcx+/PFHyLz+wNdPhnqf3PMLZliHyKz+WsbLL79s0aC/BbFF5whERCQsDQQiIp7TQCAi4jmtEVwGvsvgySefhMz1cmpra6P+TP+JxhoB7/XnOv91dXWQ3Ssfud4Pr6fw3DmvIXANKa7ZU1lZGbT57gI+J5CYmAiZz0Nw/aCmTfG4jXtFJ78W1/9xawWZ1b/a8rbbboPM9Zrcr8/PxesRhYWFkKNV+0p/C2KL1ghERCQsDQQiIp7TQCAi4rmYrDXUWKWnp0Pm2jw8Lx5rcnJyIPOed75T110zWL16NfRNmDAB8tmzZyHz/npeX+F5e7fuDq8JcD0gvtOY5/H5PMSKFSsgJyUl/W/bDGsDmWG9pf/791u2bIHMdxy776m7NmFWf+6X3zORSOkTgYiI5zQQiIh4TgOBiIjntEZwidya8JMnT4Y+risT62sCzD0XYIZ1l8zM4uPjIbvvFdfB2bp1K+SJEydC5vsLkpOTIfN727lz56C9d+9e6GvdujVkvhOAaxPx98HnDNwzD7we8cEHH0DmWkS8jsT3Y/B5CXdthc8/uPdwmJlNmzbNRBpCnwhERDyngUBExHMxOTWUm5sLma8HjKZXXnklaHPJhTlz5ly157gWeEqlqqoKMpdb2LlzZ9DmrY9caoFLenPZ6WPHjkHmkhT79+8P2jy14/aZmfXo0QNy3759IX/xxReQp06dCtn9fXOnpMzMunXrBtktfWFmtnTpUshDhw4N+azue3r48GHo4/eIp5lEIqVPBCIintNAICLiOQ0EIiKea5RrBLzd76OPPoJ86tQpyNFcI+BS04899ljQ5vneaF0N2FisXLkSMpdB5nl7t3QDb//kEt28DZO3qvJWSZ4fd0szbN68Gfq41Mfx48chnz9/HvKjjz4KmctbuFtd+YpN98pMs/plqbksxJ49eyDz+kVNTU3QbteuHfRxqYzevXubSEPoE4GIiOc0EIiIeE4DgYiI5xrlGgGXD+Bj+vfcc0/UXvvNN9+EPGvWLMj5+flB2z1T4IPBgwdDLikpgcxrBG4558WLF0Mfz5XzfvqRI0dC5nLNBQUFkN3yCyNGjLhon1n9MwxczoLXJ7jktbvm8O6770IfnysIdc2lWf31B15jcF+L1yP4bIW7niByKfSJQETEcxoIREQ8p4FARMRzjXKNgOePOfP+/cvBawIzZ86E/Prrr0N+4YUXgva5c+eu2HPEAj6/waWk3fUTM5zH79OnD/RxWWo+R8Dz3/feey9kPjvi/ty4bPS6detCvhafhxg/fjzkRYsWQV6wYEHQ5msw+UwC12Piktd8ZoZrFbnrY27tJn4OM7O8vDwTaQh9IhAR8ZwGAhERz2kgEBHxXKNcI7iS3OsSzczeeustyI888ghkXhOYPXt2dB4sBnXq1Aky1+RZsWIFZLduDs+Vp6amQuZ5fJ5L51r7mZmZkNevXx+0+T6C3bt3Q+Z7E/j7mjdvXshncesHcf0fXp/gukdcI4lzXV0d5A0bNtjF3HfffZD5+xaJlD4RiIh4TgOBiIjnNBCIiHgu7gJv0r/YP4yLi/azBB544AHIn3/+OWTeU+7eOZuRkQF948aNgxzuroNnn30W8okTJ8I+b2MU4Y/1krh1+M3Mjh49CjktLQ2yW/umefPm0Md1+g8cOAB54MCBkHl//rZt2yCPHj06aPOZBZ7H5/pAvHefz4dw/aAjR44E7X79+kEf3y/A9wyfPn0aMtc14q/nvhbf6cDPyecj5s+fb9FwNf8WyOWL5G+BPhGIiHhOA4GIiOc0EIiIeK5RrhHwfDLvxXbXBFhZWRlkvmd32bJlkBcuXNiQR2z0orFG8N5770HetWsXZN7H7t4NPGzYMOhz9/2b1Z87v+uuuyDzHRW89uOuMfDvC9cD4vUJntfnNYWePXtCds9ENGvWDPr4foEdO3ZYKHwXM9/D4D5rZWUl9PE9C7z+NWPGjJCv3VBaI4gtWiMQEZGwNBCIiHiuUU4NyeW7GttHc3JyIPN2RXd6JyEhAfrcaSOz+tM1fMUjT4ukpKRAdrf5JiUlQV9hYWHI/5ZLYnM5DHcLpxluk121ahX0cQnr0tJSyHxNJpfaKC4uhpydnR20eQstvyc8NfTSSy9ZNOhvQWzR1JCIiISlgUBExHMaCEREPKc1gutUNNYInnjiCch8nSRvhRwyZEjQLi8vhz4uj8BrBLxdtLq6GjKXU5g0aVLQ5i3CXEKioqICMpel5u3JvAW0qKgoaPN2Ty5ZzWWpeRstl8jm96FVq1ZBe+3atdDHP2NeQ1i9erVFg/4WxBatEYiISFgaCEREPKeBQETEc9f9VZVy5fB1kTxvz/PhGzduDNpZWVnQ564fmJnNnTsXMp876N+/P2ReIzh06FDQnj59OvQtWbIEMl9zya/Fax+5ubmQ3XMHvHefr0bl+XQua85XVXbt2hXypk2bgvaUKVOgj8t0pKenm0hD6BOBiIjnNBCIiHhOA4GIiOciPkcgIiLXJ30iEBHxnAYCERHPaSAQEfGcBgIREc9pIBAR8ZwGAhERz2kgEBHxnAYCERHPaSAQEfHcv5LNvf1ZY5U7AAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -2940,7 +2808,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2950,7 +2818,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2960,7 +2828,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -2970,7 +2838,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] From 58924132d34231aa6fc45a99060f333a23c67e3f Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 16:13:33 +0100 Subject: [PATCH 14/51] updated the exercise --- exercise.ipynb | 182 ++++++------------------------------------------- 1 file changed, 22 insertions(+), 160 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 628f49e..218a870 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -417,25 +417,12 @@ }, "outputs": [], "source": [ - "import torch.nn as nn\n", - "import torch.nn.functional as F\n", - " \n", - "# Dense model:\n", - "class DenseModel(nn.Module):\n", - " def __init__(self):\n", - " super().__init__()\n", - " self.fc0 = nn.Linear(784, 256)\n", - " self.fc1 = nn.Linear(256, 120)\n", - " self.fc2 = nn.Linear(120, 84)\n", - " self.fc3 = nn.Linear(84, 10)\n", + "import torch\n", + "from classifier.model import DenseModel\n", + "\n", + "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", "\n", - " def forward(self, x):\n", - " x = torch.flatten(x, 1) # flatten all dimensions except batch\n", - " x = F.relu(self.fc0(x))\n", - " x = F.relu(self.fc1(x))\n", - " x = F.relu(self.fc2(x))\n", - " x = self.fc3(x)\n", - " return x" + "print(f'selected torch device: {device}')" ] }, { @@ -452,7 +439,7 @@ "metadata": {}, "outputs": [], "source": [ - "from tqdm.notebook import tqdm\n", + "from tqdm import tqdm\n", "\n", "# Training function:\n", "def train_mnist(model, train_loader, batch_size, criterion, optimizer, history):\n", @@ -487,6 +474,7 @@ "source": [ "import torch.optim as optim\n", "import torch\n", + "import torch.nn as nn\n", "\n", "# Let's set some hyperparameters:\n", "n_epochs = 2\n", @@ -512,8 +500,11 @@ "outputs": [], "source": [ "# Initialize the clean and tainted models\n", - "model_clean = DenseModel().cuda()\n", - "model_tainted = DenseModel().cuda()\n", + "model_clean = DenseModel(input_shape=(28, 28), num_classes=10)\n", + "model_clean = model_clean.to(device)\n", + "\n", + "model_tainted = DenseModel(input_shape=(28, 28), num_classes=10)\n", + "model_tainted = model_tainted.to(device)\n", "\n", "# Weight initialisation:\n", "def init_weights(m):\n", @@ -1293,139 +1284,6 @@ "Let's try denoising with a UNet, \"CARE-style\". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. " ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Adapted from https://discuss.pytorch.org/t/unet-implementation/426\n", - "\n", - "import torch\n", - "from torch import nn\n", - "import torch.nn.functional as F\n", - "\n", - "\n", - "class UNet(nn.Module):\n", - " def __init__(\n", - " self,\n", - " in_channels=1,\n", - " n_classes=1,\n", - " depth=3,\n", - " wf=4,\n", - " padding=True,\n", - " batch_norm=False,\n", - " up_mode='upsample',\n", - " ):\n", - " \"\"\"\n", - " Implementation of\n", - " U-Net: Convolutional Networks for Biomedical Image Segmentation\n", - " (Ronneberger et al., 2015)\n", - " https://arxiv.org/abs/1505.04597\n", - " Using the default arguments will yield the exact version used\n", - " in the original paper\n", - " Args:\n", - " in_channels (int): number of input channels\n", - " n_classes (int): number of output channels\n", - " depth (int): depth of the network\n", - " wf (int): number of filters in the first layer is 2**wf\n", - " padding (bool): if True, apply padding such that the input shape\n", - " is the same as the output.\n", - " This may introduce artifacts\n", - " batch_norm (bool): Use BatchNorm after layers with an\n", - " activation function\n", - " up_mode (str): one of 'upconv' or 'upsample'.\n", - " 'upconv' will use transposed convolutions for\n", - " learned upsampling.\n", - " 'upsample' will use bilinear upsampling.\n", - " \"\"\"\n", - " super(UNet, self).__init__()\n", - " assert up_mode in ('upconv', 'upsample')\n", - " self.padding = padding\n", - " self.depth = depth\n", - " prev_channels = in_channels\n", - " self.down_path = nn.ModuleList()\n", - " for i in range(depth):\n", - " self.down_path.append(\n", - " UNetConvBlock(prev_channels, 2 ** (wf + i), padding, batch_norm)\n", - " )\n", - " prev_channels = 2 ** (wf + i)\n", - "\n", - " self.up_path = nn.ModuleList()\n", - " for i in reversed(range(depth - 1)):\n", - " self.up_path.append(\n", - " UNetUpBlock(prev_channels, 2 ** (wf + i), up_mode, padding, batch_norm)\n", - " )\n", - " prev_channels = 2 ** (wf + i)\n", - "\n", - " self.last = nn.Conv2d(prev_channels, n_classes, kernel_size=1)\n", - "\n", - " def forward(self, x):\n", - " blocks = []\n", - " for i, down in enumerate(self.down_path):\n", - " x = down(x)\n", - " if i != len(self.down_path) - 1:\n", - " blocks.append(x)\n", - " x = F.max_pool2d(x, 2)\n", - "\n", - " for i, up in enumerate(self.up_path):\n", - " x = up(x, blocks[-i - 1])\n", - "\n", - " return self.last(x)\n", - "\n", - "\n", - "class UNetConvBlock(nn.Module):\n", - " def __init__(self, in_size, out_size, padding, batch_norm):\n", - " super(UNetConvBlock, self).__init__()\n", - " block = []\n", - "\n", - " block.append(nn.Conv2d(in_size, out_size, kernel_size=3, padding=int(padding)))\n", - " block.append(nn.ReLU())\n", - " if batch_norm:\n", - " block.append(nn.BatchNorm2d(out_size))\n", - "\n", - " block.append(nn.Conv2d(out_size, out_size, kernel_size=3, padding=int(padding)))\n", - " block.append(nn.ReLU())\n", - " if batch_norm:\n", - " block.append(nn.BatchNorm2d(out_size))\n", - "\n", - " self.block = nn.Sequential(*block)\n", - "\n", - " def forward(self, x):\n", - " out = self.block(x)\n", - " return out\n", - "\n", - "\n", - "class UNetUpBlock(nn.Module):\n", - " def __init__(self, in_size, out_size, up_mode, padding, batch_norm):\n", - " super(UNetUpBlock, self).__init__()\n", - " if up_mode == 'upconv':\n", - " self.up = nn.ConvTranspose2d(in_size, out_size, kernel_size=2, stride=2)\n", - " elif up_mode == 'upsample':\n", - " self.up = nn.Sequential(\n", - " nn.Upsample(mode='bilinear', scale_factor=2),\n", - " nn.Conv2d(in_size, out_size, kernel_size=1),\n", - " )\n", - "\n", - " self.conv_block = UNetConvBlock(in_size, out_size, padding, batch_norm)\n", - "\n", - " def center_crop(self, layer, target_size):\n", - " _, _, layer_height, layer_width = layer.size()\n", - " diff_y = (layer_height - target_size[0]) // 2\n", - " diff_x = (layer_width - target_size[1]) // 2\n", - " return layer[\n", - " :, :, diff_y : (diff_y + target_size[0]), diff_x : (diff_x + target_size[1])\n", - " ]\n", - "\n", - " def forward(self, x, bridge):\n", - " up = self.up(x)\n", - " crop1 = self.center_crop(bridge, up.shape[2:])\n", - " out = torch.cat([up, crop1], 1)\n", - " out = self.conv_block(out)\n", - "\n", - " return out" - ] - }, { "attachments": {}, "cell_type": "markdown", @@ -1440,7 +1298,7 @@ "metadata": {}, "outputs": [], "source": [ - "from tqdm.notebook import tqdm\n", + "from tqdm import tqdm\n", "\n", "def train_denoising_model(train_loader, model, criterion, optimizer, history):\n", " \n", @@ -1496,6 +1354,7 @@ "metadata": {}, "outputs": [], "source": [ + "from dlmbl_unet import UNet\n", "import torch.optim as optim\n", "import torch\n", "\n", @@ -1508,7 +1367,8 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet().cuda()\n", + "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", @@ -1766,7 +1626,8 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet().cuda()\n", + "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", @@ -1850,7 +1711,8 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet().cuda()\n", + "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", @@ -1937,7 +1799,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python [conda env:07-failure-modes] *", + "display_name": "Python [conda env:07-failure-modes]", "language": "python", "name": "conda-env-07-failure-modes-py" }, @@ -1951,7 +1813,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.12.5" } }, "nbformat": 4, From f42e77926a07493cbe3ba7938ed91c5a859a6685 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 16:32:42 +0100 Subject: [PATCH 15/51] Added missing import to exercise --- exercise.ipynb | 1 + 1 file changed, 1 insertion(+) diff --git a/exercise.ipynb b/exercise.ipynb index 218a870..7bdc825 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -1357,6 +1357,7 @@ "from dlmbl_unet import UNet\n", "import torch.optim as optim\n", "import torch\n", + "import torch.nn.functional as F\n", "\n", "# Some hyper-parameters:\n", "n_epochs = 5\n", From f384125f609316152adba40cbb4fe97707377932 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 16:33:42 +0100 Subject: [PATCH 16/51] added missing import to solution --- solution.ipynb | 1055 ++++-------------------------------------------- 1 file changed, 85 insertions(+), 970 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index 7b98abd..5f6fbd7 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "tags": [] }, @@ -146,20 +146,9 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAK9ElEQVR4nO3dW4iU5R8H8Gc9YWtalpSW0oFAS4kKCi/sAK6RnSiKAi0U66IDorHVFtTSokYlFGlqKCIEYTdGetFJKoU0bwrs6KZFbse1IouiDHP/V/9hfk/t7Kw7M7uzfj5Xz5d5Z/dX+870632e93kburq6uhIAcEwb0t8FAAD9T0MAAGgIAAANAQCQNAQAQNIQAABJQwAAJA0BAJBSGlbugQ0NDdWsgwqrxn5TzoH6Uq09x5wH9cV3AeWeA64QAAAaAgBAQwAAJA0BAJA0BABA0hAAAElDAAAkDQEAkDQEAEDSEAAASUMAACQNAQCQNAQAQNIQAABJQwAAJA0BAJA0BABA0hAAACmlYf1dQD175JFHQm5rawt5yJDYb11xxRUhb9++vSp1UTsPP/xwyMuWLQv5qaeeCvmhhx6qek0AR8MVAgBAQwAAaAgAgGQNQa/Nnz+/MG5paQmvHTlypOR7u7q6qlESNTZ69OjCeOHCheG1/G+8ePHikPfu3Rvy+vXrK1scwFFyhQAA0BAAABoCACBZQ9BrZ5xxRmE8cuTIfqyEWhk2LH5M7r777sL41FNPLfnezs7OkN97773KFUZVNTc3hzxixIiQzz333MJ47ty5JX/Wnj17Qp46dWofq4PKc4UAANAQAAAaAgAgpdTQVebN8Q0NDdWuZUBqamoK+aWXXiqMTzjhhPBaPk947bXXhpzPJ//111+VKPE/VWPPg2P1HJgxY0bIvXkGRX4OvPbaaxWpqRzV2veiXs+Dyy+/PORp06aVfP3GG28MuS//3PkeJfv27Qv5vPPOO+qf3RPfBZUzdOjQkM8666yy3/v111+HfOjQoYrUVI5yzwFXCAAADQEAoCEAAJJ9CP4lny/esGFDyPm6gWLLly8Pef/+/ZUrjJo588wzQ16xYkXZ733rrbdC3rZtWwUq4v8mTJgQ8saNG0M+++yzu31v/tkdNWpUyPm8+Pvvvx/yRRddVHaduSFD4v975b+73l1//fUhb9mypZ8qKW3MmDEhX3nllSEvWLAg5HzvieHDh4d86aWXlv27W1tbQ166dGnZ760VVwgAAA0BAKAhAACSfQj+Zd26dSHnc0rF8vnhmTNnVqOko+Le46P30UcfhVzqHvHffvst5FtuuSXkrVu3Vq6wXhoM+xDk+4Dkn89JkyZV7Hflzxf46aefQh43blzIp512WmGcrzWaOHFiyd+VnxezZ88uu87eqsV3wXHHHRfyn3/+WfHf2Z1TTjkl5FmzZhXGkydPDq/le030tAbggw8+CHnz5s0hF+8zcvHFF5f8Wfm+M42NjSWPryT7EAAAZdMQAABuO8wvA+ZTBPmWowcPHiyMB+JtI/Rdfum41OW21atXh9yfUwSD0YMPPhhyb6YI8q1hW1paQt61a1fI7e3tJX/ezz//HPKiRYsK456mCL766quQb7/99pLH15taThHk8qnbKVOmFMb51Eb+Wc5ff/nll0MuftR5SikdOHAg5G+++aYwzqcM8p/9wgsv5KUPOK4QAAAaAgBAQwAApGNwDUG+Le2mTZt69f6VK1cWxu+8804lSqKfPf300yH3NO9YvD3xkiVLqlfYMSjfSnb69Om9en9HR0dhnM/T79ix4+gL+w89rRsolt+ult/SyNHLP5/F6xl2794dXlu2bFnIH3/8ccj5I4rzNWQPPPBAyI899li3dX355Zcht7W1dXvsQOEKAQCgIQAANAQAQDoG1xBcddVVIZ9//vklj88fZ/vss89WvCZqa9WqVSHfcMMNIedzkh9++GHIc+fOLYzz7Ujpm+bm5pB72t51586dIRfP0/Z1zcDYsWNDzr87LrvssrLrevXVV/tUC93Lz5l9+/b95/ho5I91ztcBjBw5sjDO95rIt7L//vvv+1RLLbhCAABoCAAADQEAkI6BNQT5/PATTzxR8vh333035Hnz5oX866+/VqQuaueSSy4JOT8nxo8fX/L9a9euDfnHH3+sSF38W/7vOn/WSP75mzNnTsg//PBDxWq56667Qi6158Qnn3wScv4Y7ErWRfT6669X7Gfl+wy0traGXLxmIKW4b0G+h0a+pqAeuEIAAGgIAAANAQCQBuEagr4+qyDff7qzs7OvJdHPFixYEPKECRNKHv/ZZ5+FnO9DT/Xkn9fefn774rrrrgs5nz/OHT58uDB+/vnnw2vWDNSH/G++dOnSkIcPHx5y/t+HhQsXFsZ93fNgIHCFAADQEAAAGgIAIKXU0JVv3N7dgdkz4geqNWvWhHznnXf26v3Tpk0Lub29vc819Ycy/6y9Ui/nwOLFi0Nevnx5yEOGlO6DJ02aFPJ3331XkbpqrRrnQEr1cx701j///BNyT//+7rnnnsI43z9hIDmWvwty11xzTcgbN24M+fjjjw+5o6Mj5KamppDrZd1AueeAKwQAgIYAANAQAABpkOxDcMEFFxTG+X7SPcnvMa/XNQPHuuJ5/zvuuCO8lq8ZyOeK161bF3K9rhmgdx5//PGQ8/PkyJEjJd+/ffv2itdEZeVrBl555ZWQhw4dGvIXX3wR8qxZs0Kux+cT9IYrBACAhgAAGCRTBm+++WZhPHbs2JLH7tq1K+T58+dXoySq7Jxzzgl5y5YthfHkyZNLvveZZ54JuaWlpXKFMWCNGDEi5AsvvDDkfIogv1Vr0aJFIe/du7eC1VEpxdsRv/jii+G1fIqg1HtTGvxTBDlXCAAADQEAoCEAANIgWUNw8sknF8Y93Sq0evXqkH///feq1ER15esEelo3UKx4vQGDV2NjY8i33XZbyPktZbl8W9t8Prqn7xpqI99qvPgRxvlWxAcOHAj53nvvDflYv+3cFQIAQEMAAGgIAIBUp2sINmzYEHJPj7MttnPnzkqXQz846aSTyj5227ZtIX/66acVroaBYvTo0YVxviX1zTffXPK99913X8jPPfdcyNYMDAzjxo0LeceOHSFPnDixMM4fXzxv3ryQbT8duUIAAGgIAAANAQCQ6mQNQfHjjVNKqampKeTiub2///47vLZq1aqQOzs7K1sc/WLJkiVlH7tmzZqQf/nll0qXwwBx+umnF8Y9rRnIH3W7YsWKqtREZU2dOjXk4jUDKaV0+PDhwnjOnDnhNWvISnOFAADQEAAAGgIAINXJGoITTzwx5PHjx3d77Lfffhvy/fffX42SqLF83nDUqFHdHtvW1hbypk2bqlIT/W/KlCkhNzc3d3vs559/HvLs2bOrUhPVdfDgwZD/+OOPkLdu3VoYWzPQO64QAAAaAgBAQwAApDpZQwDTp08PuXjP+tyhQ4dC7urqqkpN9L9HH3005FtvvbXbY1euXBny/v37q1IT1bV79+6Q8/VF+RoDyucKAQCgIQAANAQAQKqTNQR79uwJOb+3dMaMGbUsh36wfv36kFtbW0NubGwsjN94442a1ETt5fPFY8aM6fbYtWvXhvz2229XpSb6V0dHR3+XMGi4QgAAaAgAgJQausq8J6uhoaHatVBB1bjVzjlQX6p1u2V/ngdPPvlkyPlWxcW3El599dXhtfb29uoVVkP537Wnv4fvgsGnWueAKwQAgIYAANAQAADJGoJBy7whg3ENwcyZM0PObzG96aabCuPNmzfXpKaBzncB1hAAAGXTEAAAGgIAwBqCQcu8IYNxDQG957sAawgAgLJpCAAADQEA0Is1BADA4OUKAQCgIQAANAQAQNIQAABJQwAAJA0BAJA0BABA0hAAAElDAACklP4H+tT1YwpD3CAAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -277,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -296,30 +285,9 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Create grid texture\n", "texture = numpy.zeros(tainted_test_dataset.data.shape[1:])\n", @@ -341,7 +309,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "tags": [] }, @@ -363,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -378,20 +346,9 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# visualize example 4s\n", "plt.subplot(1,4,1)\n", @@ -537,19 +494,11 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "selected torch device: cuda\n" - ] - } - ], + "outputs": [], "source": [ "import torch\n", "from classifier.model import DenseModel\n", @@ -569,7 +518,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -602,12 +551,13 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import torch.optim as optim\n", "import torch\n", + "import torch.nn as nn\n", "\n", "# Let's set some hyperparameters:\n", "n_epochs = 2\n", @@ -628,25 +578,9 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DenseModel(\n", - " (fc0): Linear(in_features=784, out_features=256, bias=True)\n", - " (fc1): Linear(in_features=256, out_features=120, bias=True)\n", - " (fc2): Linear(in_features=120, out_features=84, bias=True)\n", - " (fc3): Linear(in_features=84, out_features=10, bias=True)\n", - ")" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Initialize the clean and tainted models\n", "model_clean = DenseModel(input_shape=(28, 28), num_classes=10)\n", @@ -680,7 +614,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -702,49 +636,11 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "938it [00:08, 114.99it/s] \n", - "938it [00:08, 116.51it/s] \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "model clean trained\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "938it [00:08, 116.86it/s] \n", - "938it [00:08, 117.20it/s] " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "model tainted trained\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], + "outputs": [], "source": [ "# We store history here:\n", "history = {\"loss_tainted\": [],\n", @@ -759,7 +655,7 @@ " optim.Adam(model_clean.parameters(), lr=0.001),\n", " history[\"loss_clean\"])\n", "\n", - "print('model clean trained')\n", + "print('model_clean trained')\n", "\n", "# Training loop for tainted model:\n", "for epoch in range(n_epochs):\n", @@ -770,7 +666,7 @@ " optim.Adam(model_tainted.parameters(), lr=0.001),\n", " history[\"loss_tainted\"])\n", "\n", - "print('model tainted trained')" + "print('model_tainted trained')" ] }, { @@ -783,30 +679,9 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'negative log likelihood loss')" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Visualise the loss history:\n", "fig = plt.figure()\n", @@ -959,7 +834,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -989,7 +864,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": { "tags": [] }, @@ -1011,7 +886,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1072,64 +947,9 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2494075/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", @@ -1330,7 +1150,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": { "tags": [] }, @@ -1373,7 +1193,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1422,30 +1242,9 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABDBklEQVR4nO2deXxTZdbHf2mapPvC2patFBCwrBbZocIgKJu+gCAii69CUdHBQVDEV0RwHFARRBBxEBQKssjiCuMCAsqMyi4oawERyt59SZuc94+S0OSep+R2S2DOd4aP6cnJc5/7LPfk5px7joGICIIgCILgIX7e7oAgCIJwcyGGQxAEQdCFGA5BEARBF2I4BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXYjgEQRAEXYjhEARBEHQhhuMWJjY2FqNGjfJ2N3ySu+66C3fddVepPnszj+uoUaMQGxvr7W4INzliOG5Cjh8/jqSkJMTFxSEgIABhYWHo1KkT5s6di9zcXG93z2NOnjwJg8EAg8GAGTNmsDrDhg2DwWBASEhIJffu5iIjIwPTpk1Dy5YtERISgsDAQDRr1gzPPfcczp496+3ueUzxNcH9Gz16tLe7KADw93YHBH188cUXeOCBB2CxWDBixAg0a9YMVqsVO3bswMSJE3Hw4EEsWrTI293URUBAAFauXIkXX3zRRZ6dnY2NGzciICDASz27OThx4gR69OiB06dP44EHHsCYMWNgNpuxf/9+LF68GOvXr8eRI0e83U2PqF69OpYtW6aRb9q0CcnJyejZs6cXeiW4I4bjJiIlJQUPPvgg6tWrh++++w7R0dHO95588kkcO3YMX3zxhRd7WDp69+6NdevWYd++fWjZsqVTvnHjRlitVtxzzz347rvvvNhD36WwsBADBgzA+fPnsXXrVnTu3Nnl/VdffRUzZ870Uu/0ExwcjIcfflgjX7p0KcLCwtCvXz8v9EpwR36quomYNWsWsrKysHjxYhej4aBhw4b461//WmIbaWlpGD9+POrUqQOLxYKGDRti5syZsNvtLnpvvPEGOnbsiKpVqyIwMBAJCQlYu3atpj2DwYBx48Zhw4YNaNasGSwWC+Lj47Fp0yaPz6tDhw6oX78+VqxY4SJPTk7GPffcgypVqrCfW7BgAeLj42GxWBATE4Mnn3wSaWlpGr1FixahQYMGCAwMRNu2bbF9+3a2vfz8fEydOhUNGzaExWJBnTp1MGnSJOTn53t8LsXJzs7GhAkTnGPduHFjvPHGG3BPSF2WMfzkk0+wb98+TJkyRWM0ACAsLAyvvvpqiW3Y7XbMmTMH8fHxCAgIQM2aNZGUlISrV6+66G3cuBF9+vRBTEwMLBYLGjRogOnTp8Nms7no3XXXXWjWrBkOHTqEbt26ISgoCLVq1cKsWbNueD4c586dw5YtWzBgwAC5+/QVSLhpqFWrFsXFxXmsX69ePRo5cqTz7+zsbGrRogVVrVqVXnjhBVq4cCGNGDGCDAYD/fWvf3X5bO3atemJJ56gd955h2bPnk1t27YlAPT555+76AGgli1bUnR0NE2fPp3mzJlDcXFxFBQURJcuXSqxfykpKQSAXn/9dXrhhReobt26ZLfbiYjo4sWL5O/vTytXrqSRI0dScHCwy2enTp1KAKhHjx40b948GjduHBmNRrrzzjvJarU69f75z38SAOrYsSO9/fbbNH78eIqIiKC4uDhKTEx06tlsNurZsycFBQXR+PHj6b333qNx48aRv78/3XfffSWOK4fdbqfu3buTwWCgxx57jN555x3q168fAaDx48eX2xg+9NBDBIBOnz5dop6DkSNHUr169Vxkjz32GPn7+9Po0aNp4cKF9Nxzz1FwcLBmLO+//34aPHgwvf766/Tuu+/SAw88QADo2WefdWkvMTGRYmJiqE6dOvTXv/6VFixYQN27dycA9OWXX3rUz+LMnj2bANDXX3+t+7NCxSCG4yYhPT2dAGguYiXhfoGbPn06BQcH05EjR1z0nn/+eTIajS4Xn5ycHBcdq9VKzZo1o+7du7vIAZDZbKZjx445Zfv27SMANG/evBL7V9xw/PrrrwSAtm/fTkRE8+fPp5CQEMrOztYYjgsXLpDZbKaePXuSzWZzyt955x0CQB988IGzzzVq1KBWrVpRfn6+U2/RokUEwMVwLFu2jPz8/JzHd7Bw4UICQD/88INT5onh2LBhAwGgGTNmuMgHDRpEBoPBZbzKMoatW7em8PDwEnWK4244tm/fTgAoOTnZRW/Tpk0aufuaICJKSkqioKAgysvLc8oSExMJAH300UdOWX5+PkVFRdHAgQM97quDhIQEio6OdplrwbvIT1U3CRkZGQCA0NDQUrexZs0adOnSBZGRkbh06ZLzX48ePWCz2bBt2zanbmBgoPP11atXkZ6eji5dumD37t2adnv06IEGDRo4/27RogXCwsJw4sQJj/sWHx+PFi1aYOXKlQCAFStW4L777kNQUJBG95tvvoHVasX48ePh53d9CY8ePRphYWFOP88vv/yCCxcuYOzYsTCbzU69UaNGITw8XDM2TZs2RZMmTVzGpnv37gCALVu2eHwuAPDll1/CaDTi6aefdpFPmDABRISvvvrKRV7aMczIyCjzmggPD8fdd9/tct4JCQkICQlxOe/iayIzMxOXLl1Cly5dkJOTg99//92l3ZCQEBdfhdlsRtu2bXWtCQA4cuQIdu3ahQcffNBlrgXvIs7xm4SwsDAARRu2tBw9ehT79+9H9erV2fcvXLjgfP35559jxowZ2Lt3r8tv/AaDQfO5unXramSRkZGa38hvxEMPPYQ333wTzzzzDH788Ue88MILrN6pU6cAAI0bN3aRm81mxMXFOd93/LdRo0YueiaTCXFxcS6yo0eP4rfffvNobDzh1KlTiImJ0VzUmzZt6tI3B6UdQ70G2p2jR48iPT0dNWrUYN8vft4HDx7Eiy++iO+++875RcZBenq6y9+1a9fWrJXIyEjs379fV/+Sk5MBFIVlC76DGI6bhLCwMMTExODXX38tdRt2ux133303Jk2axL5/2223AQC2b9+O/v37o2vXrliwYAGio6NhMpmwZMkSjQMbAIxGI9se6axKPHToUEyePBmjR49G1apVKzX00m63o3nz5pg9ezb7fp06dSr0+KUdwyZNmmDPnj34448/StVHu92OGjVqOC/Q7jgMaVpaGhITExEWFoZXXnkFDRo0QEBAAHbv3o3nnntOE1xRXmtixYoVaNy4MRISEnR9TqhYxHDcRPTt2xeLFi3Czp070aFDB92fb9CgAbKystCjR48S9T755BMEBARg8+bNsFgsTvmSJUt0H1MPdevWRadOnbB161Y8/vjj8Pfnl2e9evUAAIcPH3a5c7BarUhJSXGen0Pv6NGjzp+cAKCgoAApKSkuob8NGjTAvn378Je//IW9q9JLvXr18M033yAzM9PlrsPxk46jb2WlX79+WLlyJZYvX47Jkyfr/nyDBg3wzTffoFOnTi4/RbmzdetWXL58GevWrUPXrl2d8pSUlFL12xP+85//4NixY3jllVcq7BhC6ZAfDW8iJk2ahODgYDz22GM4f/685v3jx49j7ty5ys8PHjwYO3fuxObNmzXvpaWlobCwEEDRt0WDweASZnny5Els2LCh7CdxA2bMmIGpU6fiqaeeUur06NEDZrMZb7/9tss32MWLFyM9PR19+vQBALRp0wbVq1fHwoULYbVanXpLly7VhO0OHjwYf/75J95//33N8XJzc5Gdna3rPHr37g2bzYZ33nnHRf7WW2/BYDDg3nvv1dWeikGDBqF58+Z49dVXsXPnTs37mZmZmDJlivLzgwcPhs1mw/Tp0zXvFRYWOsfJcQdRfLytVisWLFhQxjNQ47i7feihhyrsGELpkDuOm4gGDRpgxYoVGDJkCJo2bery5PiPP/6INWvWlJhDaeLEifj000/Rt29fjBo1CgkJCcjOzsaBAwewdu1anDx5EtWqVUOfPn0we/Zs3HPPPXjooYdw4cIFzJ8/Hw0bNtT9G7VeEhMTkZiYWKJO9erVMXnyZEybNg333HMP+vfvj8OHD2PBggW48847nU5Zk8mEGTNmICkpCd27d8eQIUOQkpKCJUuWaHwcw4cPx+rVqzF27Fhs2bIFnTp1gs1mw++//47Vq1dj8+bNaNOmjcfn0a9fP3Tr1g1TpkzByZMn0bJlS/zrX//Cxo0bMX78eBdHeFkwmUxYt24devToga5du2Lw4MHo1KkTTCYTDh48iBUrViAyMlL5LEdiYiKSkpLw2muvYe/evejZsydMJhOOHj2KNWvWYO7cuRg0aBA6duyIyMhIjBw5Ek8//TQMBgOWLVum+6cnT7HZbFi1ahXat29fbmMllCNejOgSSsmRI0do9OjRFBsbS2azmUJDQ6lTp040b948l7BILmw0MzOTJk+eTA0bNiSz2UzVqlWjjh070htvvOESs7948WJq1KgRWSwWatKkCS1ZssT57ERxANCTTz6p6aMnIavFw3FLgnuOg6go/LZJkyZkMpmoZs2a9Pjjj9PVq1c1egsWLKD69euTxWKhNm3a0LZt2ygxMdElHJeoKHx35syZFB8fTxaLhSIjIykhIYGmTZtG6enpus6NqGisn3nmGYqJiSGTyUSNGjWi119/3fmsioOyjKGDq1ev0ksvvUTNmzenoKAgCggIoGbNmtHkyZPp3LlzTj3uOQ6iohDlhIQECgwMpNDQUGrevDlNmjSJzp4969T54YcfqH379hQYGEgxMTE0adIk2rx5MwGgLVu2OPUSExMpPj5ecwzVsTkc4cBvv/22R/pC5WIgqqCvDIIgCMItifg4BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXXjUcL7/8cqkftlq6dCkMBgNOnjxZvp0qhqMa2dKlSyvsGHopS8nTysK9tKpjrn755ZdKOf7NMEY3G9x+i42NRd++fSvl+Fu3boXBYMDWrVsr5XiVxc16XqUyHAcPHsTDDz+MWrVqOWshDBs2DAcPHizv/gllxGazISYmBgaDQZNYz8GCBQtY43jo0CG8/PLLFWqcS4sv960yWLBgAQwGA9q1a8e+X9L4qObbF/DVvhERli1bhq5duyIiIgJBQUFo3rw5XnnlFd0Ph94S6I3f/eSTT8hsNlNUVBRNmTKF/vnPf9KLL75I0dHRZDabad26dR63VVBQQLm5uXq7QEREhYWFlJubq4mJL08czxksWbKkwo6hF+75g5L417/+RQAoNjaWhg0bxurEx8ezba5Zs0YTo+8JeXl5Ls+ELFmyhADQzz//rKudkiipb/n5+S5p1G9FOnbsSLGxsQSAjh49qnm/pPFRzXdJcPutXr161KdPH71dLxFV32w2G+Xm5noltXphYSENHjyYAFCXLl3orbfeovfee48efvhh8vPzo2bNmlFqamqp2t6yZUup9pi30XXHcfz4cQwfPhxxcXHYv38/ZsyYgUcffRTTp0/H/v37ERcXh+HDh98wW6fDQvv7+5e6opfRaERAQEC55BW6lVm+fDnuuOMOPPPMM9iwYUOFfTsiIuTm5gIALBYLTCZThRzHE8xms0sa9VuNlJQU/Pjjj5g9ezaqV6+uTFBYHjjWi7f3m5+fHwICArySWn3WrFlYvXo1nn32WWzbtg3jx4/HmDFjsGzZMmzYsAGHDh0qMWPDLYkeK5OUlEQAaNu2bez733//PQGgpKQkp8zxtPHBgwdp6NChFBERQa1atXJ5rzg5OTn01FNPUdWqVSkkJIT69etHZ86cIQA0depUp57jW2xKSopT5vgGtH37drrzzjvJYrFQ/fr16cMPP3Q5xuXLl2nChAnUrFkzCg4OptDQULrnnnto7969Lnqe3nF42p7j28WqVatoxowZVKtWLbJYLNS9e3f2W+N7771HcXFxFBAQQHfeeafyiWcVOTk5FBoaSrNmzaJz586Rn5+fpmBPvXr1CIDLv8TEROf4uv9zfDNyjPWmTZsoISGBLBYLvfXWW873ij/x7Gjr+++/pzFjxlCVKlUoNDSUhg8fTleuXHHpj/s8F++no80b9Y0bo/Pnz9P//u//Uo0aNchisVCLFi1o6dKlLjrFn2R3jL3ZbKY2bdrQTz/95NGYVwbTp0+nyMhIys/Pp8cff5waNWrk8n5J46Oa7+Kf27p1Kz3++ONUvXp1ioiIcHmP22+bN2+mli1bksVioaZNm9Inn3zi0h9un3NtltQ31Tfz1atX0x133EEBAQFUtWpVGjZsGJ05c8ZFx5F54MyZM3TfffdRcHAwVatWjSZMmECFhYUljnVOTg5FRkbSbbfdRgUFBazOI488QgBo586dmrG50bXI/bxeeukl8vf3pwsXLmiOM3r0aAoPDy/1rzTliS7z/dlnnyE2NhZdunRh3+/atStiY2OdhXSK88ADDyAnJwd///vfMXr0aOUxRo0ahXnz5qF3796YOXMmAgMDnUnrPOHYsWMYNGgQ7r77brz55puIjIzEqFGjXPwvJ06cwIYNG9C3b1/Mnj0bEydOxIEDB5CYmIizZ896fKzStvePf/wD69evx7PPPovJkyfj3//+t6bewOLFi5GUlISoqCjMmjULnTp1Qv/+/fHHH3943K9PP/0UWVlZePDBBxEVFYW77rpL8+10zpw5qF27Npo0aYJly5Zh2bJlmDJlCrp27eosQvTCCy8433PUkwCKstMOHToUd999N+bOnYtWrVqV2J9x48bht99+w8svv4wRI0YgOTkZ999/v+58R570rTi5ubm46667sGzZMgwbNgyvv/46wsPDMWrUKDYp5IoVK/D6668jKSkJM2bMwMmTJzFgwAAUFBTo6mdFkZycjAEDBsBsNmPo0KE4evQofv75Z+f7JY2Par6L88QTT+DQoUN46aWX8Pzzz5fYl6NHj2LIkCG499578dprr8Hf3x8PPPAAvv76a93n5UnfirN06VIMHjwYRqMRr732GkaPHo1169ahc+fOmiSWNpsNvXr1QtWqVfHGG28gMTERb775JhYtWlRin3bs2IGrV6/ioYceUmZrHjFiBICiGjbF8eRa5M7w4cNRWFiIVatWucitVivWrl2LgQMH+kbddU8tTFpamkelS/v3708AKCMjg4iuf9sYOnSoRtf9m8iuXbvYmsyjRo3y+I4DbndEFy5cIIvFQhMmTHDK8vLyNL+VpqSkkMVioVdeecVFBg/uODxtz/HtomnTpi6/wc+dO5cA0IEDB4hIX8nTkujbty916tTJ5fPct5nS+DgcY71p0yb2Pe6OIyEhwcX3MWvWLAJAGzdudMrc51nVZkl9c7/jmDNnDgGg5cuXO2VWq5U6dOhAISEhzrXqmO+qVau63Alt3LiRANBnn32mOVZl88svv7jU37bb7VS7dm1NzfjS+Dgc89S5c2fNN/GS9lvxO4z09HSKjo6m1q1bO2We3nGU1Df3b+aOPdKsWTOXb+Cff/45AaCXXnrJKRs5ciQBcNmLREVldxMSEjTHKo5j7axfv16pc+XKFQJAAwYMcMo8vRZxd1IdOnSgdu3auRxj3bp1PuUL8fiOw1F57kZlKh3vu1cIGzt27A2PsWnTJgBF33iKU1KKbXduv/12lzui6tWro3Hjxi5+F4vF4vyt1Gaz4fLlywgJCUHjxo3Z0qg3Qm97jzzyiMtv8I7+Ovqop+SpisuXL2Pz5s0YOnSoUzZw4EAYDAasXr1a9zly1K9fH7169fJYf8yYMS6+D0fNjS+//LJc+qPiyy+/RFRUlMtYmEwmPP3008jKysL333/voj9kyBBERkY6/3afH2+SnJyMmjVrolu3bgCKKjIOGTIEH3/8sUsa/LIwevRoZSEmd2JiYvA///M/zr/DwsIwYsQI7NmzB6mpqeXSHw7HHnniiSdcvoH36dMHTZo0YX/1cL8GdenS5YZz6sl1T3XN8+RaxDFixAj85z//wfHjx52y5ORk1KlT54aZoysLjw2HY3BuVLpUNdD169e/4TFOnToFPz8/jW7Dhg097aZHJTjtdjveeustNGrUCBaLBdWqVUP16tWxf/9+TQlMT9DbnnsfHRcpRx/1lDxVsWrVKhQUFKB169Y4duwYjh07hitXrqBdu3bl5kz1ZE6L434+ISEhiI6OrvCQ2lOnTqFRo0Yax6qnZVzd58db2Gw2fPzxx+jWrRtSUlKc89quXTucP38e3377bbkcR8+8NmzYUOMwd1SSrMh5VZUPBoqqIrrPaUBAgKYssCeleT257qmueaUtBzxkyBBYLBbnPk1PT8fnn3+OYcOG+UwwkMeGIzw8HNHR0Tesx7B//37UqlXLWSPbQUnVxcoTT0pW/v3vf8ff/vY3dO3aFcuXL8fmzZvx9ddfIz4+XlMC0xP0tldeZTVLwrHoOnXqhEaNGjn/7dixAzt37iyXb8+VNacAyu3btCdUxvyUhu+++w7nzp3Dxx9/7DKngwcPBoBy+0JQ3vOqutj5wpzeCMeXi5Kue473br/9do+OeaN1FBkZib59+zrnc+3atcjPz3fWmfEFdBVy6tu3L95//33s2LEDnTt31ry/fft2nDx5EklJSaXqTL169WC325GSkuLy7fTYsWOlak/F2rVr0a1bNyxevNhFnpaWhmrVqnm9PT0lTzkc4Zrjxo3T3Nra7XYMHz4cK1aswIsvvghAvbHL+9vN0aNHnT+xAEBWVhbOnTuH3r17O2WRkZEax6bVasW5c+dK3bd69eph//79sNvtLncd5V3GtaJJTk5GjRo1MH/+fM1769atw/r167Fw4UIEBgaWOD7lOa/Hjh0DEbm0eeTIEQBFT5YD1+/Y0tLSEBER4dRzvyvQ07fi5YOL7xGHrLzmtHPnzoiIiMCKFSswZcoU1hh89NFHAFCuT9GPGDEC9913H37++WckJyejdevWiI+PL7f2y4quqKqJEyciMDAQSUlJuHz5sst7V65cwdixYxEUFISJEyeWqjOO38vdy1HOmzevVO2pMBqNGqu/Zs0a/Pnnnz7Rnp6SpxyObyqTJk3CoEGDXP4NHjwYiYmJLt9Og4OD2XaDg4MBwKNjesKiRYtcIpPeffddFBYWupRRbdCgAbZt26b5nPu3Uz196927N1JTU10iVQoLCzFv3jyEhIT4zO/GJZGbm4t169ahb9++mjkdNGgQxo0bh8zMTHz66acASh4f1XyXhrNnz2L9+vXOvzMyMvDRRx+hVatWiIqKAgBnBb/i85qdnY0PP/yw1H1r06YNatSogYULFyI/P98p/+qrr/Dbb7/pisQsiaCgIDz77LM4fPgwG+H1xRdfYOnSpejVqxfat29fLscEgHvvvRfVqlXDzJkz8f333/vU3Qag846jUaNG+PDDDzFs2DA0b94cjz76KOrXr4+TJ09i8eLFuHTpElauXFnqUo8JCQkYOHAg5syZg8uXL6N9+/b4/vvvnd9gyuubUt++ffHKK6/gkUceQceOHXHgwAEkJyd77D+o6Pb0lDzlSE5ORqtWrVCnTh32/f79++Opp57C7t27cccddyAhIQHvvvsuZsyYgYYNG6JGjRro3r07WrVqBaPRiJkzZyI9PR0WiwXdu3dHjRo1SnVeVqsVf/nLXzB48GBnqdfOnTujf//+Tp3HHnsMY8eOxcCBA3H33Xdj37592Lx5s+bOTU/fxowZg/feew+jRo3Crl27EBsbi7Vr1+KHH37AnDlzbhjw4Qt8+umnyMzMdBmr4rRv3975MOCQIUNKHB/VfJeG2267DY8++ih+/vln1KxZEx988AHOnz+PJUuWOHV69uyJunXr4tFHH8XEiRNhNBrxwQcfoHr16jh9+rRLe572zWQyYebMmXjkkUeQmJiIoUOH4vz585g7dy5iY2PxzDPPlOp8OJ5//nns2bMHM2fOxM6dOzFw4EAEBgZix44dWL58OZo2bcoawbJgMpnw4IMP4p133oHRaHQJ7PAJShOKtX//fho6dChFR0eTyWSiqKgoGjp0qDOctDiOULyLFy8q3ytOdnY2Pfnkk1SlShUKCQmh+++/nw4fPkwA6B//+IdTr6QHktxxD8/My8ujCRMmUHR0NAUGBlKnTp1o586dGj094bietOcIvVuzZo3L51XH8bTkaXEcIc3/93//p9Q5efIkAaBnnnmGiIhSU1OpT58+FBoaqgn3ff/99ykuLo6MRiP7ACDHjR4AjIyMpJCQEBo2bBhdvnzZ5bM2m42ee+45qlatGgUFBVGvXr3o2LFjbBlVVd9UDwA+8sgjVK1aNTKbzdS8eXPNeJdUyhaKMOHKol+/fhQQEEDZ2dlKnVGjRpHJZKJLly4RkXp8VPNdUmqYGz0A2KJFC2eZYff1TVS0Ltu1a0dms5nq1q1Ls2fPZttU9U31AOCqVauodevWZLFYqEqVKiU+AOiOKkyYw2az0ZIlS6hTp04UFhZGAQEBFB8fT9OmTaOsrCyNvqfXopJSjvz0008EgHr27OlRHyuTm6J07N69e9G6dWssX75c86CcIAjCrci+ffvQqlUrfPTRRxg+fLi3u+OCz9XjcOQ7Ks6cOXPg5+eHrl27eqFHgiAIlc/777+PkJAQDBgwwNtd0aDLx1EZzJo1C7t27UK3bt3g7++Pr776Cl999RXGjBmj/M1eEAThVuGzzz7DoUOHsGjRIowbN84Z6OBL+NxPVV9//TWmTZuGQ4cOISsrC3Xr1sXw4cMxZcoUZa4YQRCEW4XY2FicP38evXr1wrJly3wyeMPnDIcgCILg2/icj0MQBEHwbcRwCIIgCLrwitPAbrfj7NmzCA0N9ZmkXcKtCREhMzMTMTExXqkexyHrX6hMKmIPeMVwnD17ViKkhErljz/+QO3atb3dDQCy/gXvUJ57wCuGwxElkPTk07BYLC7vmYxai2iz8/577suaQhV25g1/o75ve37MAQttnvfN6Of58eyKmAWb4njceavOjzsPayGfFdjEtKHMdqoYfIJWzs0zABQybRTa+L75M9+e3GM98vPz8d6Ct30qMsXRl/2HUxAa6ppFOsii3ZKqueGWEzd+AFDItBFg1pcx1p+Zszwrn+HWj+mc2d/zb7uqObcW8HLuvFXnx+3D7LxCVjeQaYM7NwAoUMwTt5e5dgEgn2lDNcYBJm0b3HUuMzMDLZrUL9c94BXD4bjwWCyWm95wGG8Rw2Ew+obhMDJtGMtgOBz40k9Cjr6EhoYh1K38QHAFGQ7uoqa6eKngDIe5kg1Hvg7DoTo/bh/6mXnDEVQOhsPGrEmuXYA3HCbFGAcyhkO1B4Hy3QO+8aOvIAiCcNMghkMQBEHQhVcfxTZc+19xuFst5Q0W9/OM4jbSWsItnDvcTzkAkJ2vvZ21+PO3nAXMrbZBYae5W8icfP721KK43Tf5e+5/sTEDp/oZgf05UDGWql/iuG6ofnLgfqJT/eTGyfMLXD+vY9orHYPBoFlr3M9SqvXP/SqnWh+qn1E4uJ+kAOBCep5GFhZoYjSBHGavGBSXG+6no0uZVkYTCA3g2wi2aPdhruInHm6/hSja5fqmGkvVT9F2ZgNk5PI/jbG+GhM/HxZGzrWr+vmyLMgdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDowrvOcYPW+co5tLgHXYoa0IrydTwsowprVjl/ubhwVdw05zRXPWPAPeegdgjztp7rh+pZCS6uXBU3b2KcrSpXmyqogJ09P4WDnZlUVfw556R0DxKw23zn+Q13/AzagILLWVqncEQQ74DmhiUzm3e6cm3ofR6hSohZI1M9Y8I5zVV7hQuIUDmEVQ/1cX3mnokBACuz1lUP2QUxTnfVM1aqvWliv58rnk1i9r3K6c4F0HBBAjZGVlbkjkMQBEHQhRgOQRAEQRdiOARBEARdiOEQBEEQdCGGQxAEQdCFV6OqbHbSRFpwkRBc+g4AMDHZUe2qSBGmDVVUiSp1Bhc1xEUoAXzEi+I02JQSqnQJKjkXsaKKcuLSK+QpUoBwkSKqqLN8O9+GmWtDEZrFRZ6pot+MHqSHV0X9+AIFhXZN/2qEWTR6XPoOgN8rhf78wHLpcriIOUCdtoeL7lEsf3bOVKkvuHa56LKS5Nw8q6KcosK1Y5yuSAHCRXGpUvlk5vF9Y+dJFWHGyG2K+eD2VSaTHj5LkTK+LMgdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDowqvOcT8/g8ZBzaXfUME5vFWOPa5VVeqAAt7/DItJ27bKwcjVm9DjEFM59lSOOS7VAFeGUiXnSsQCiqAChbfaz6BII8Kcih+pys9qZapx42qQuDta9ZTrrWz8/f0064cPDvC8PowqPQ+31lUpQLIVgRJhgdrLRbCijkV6ToFGplqPesraqoI4aoQHaGSZudo+ALwDWVXKlQtGUa0plZzbW/5+/PE4J3+e4oLElY7l6rHk6yjZ6ylyxyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOjCq1FVZCeQW2QHMZEJelIVqNKIcG2o0iVYFEVkuEf3ufQdqjYKmcIrAB/dwhWQKdLl2+DORRU1ww1RVh7fbigTSaNKe8LpAnykiIFNtAKYmQgQpiZWURtME+R2KFUEmC9gtxFsblFyXG9VUTXcWKmi/Lg2VGlfuOgpAEhNz9fIuPQdqjYuZnqeLqRaqLZoVJEu3wYXmahKN8NdN1LT8ljd6EhttNblLD6FRy1GF+CvG6pIuVDmeqIqXsXtYzsTrVgRkYVyxyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuvCqcxwGaLyBnJNX5drh8tGrHLf+zGP/qpQjOQonNtcGl1oE4B23gQqne6BZK89W9IFzngH8eavST3DpFUxG1Tlr+6Zytqkc0dw8qdJPFDI5RwyK4/kzx3Pvgy87x8u6/kOYOg+XM7UObIB3sKrq3FzKVKW40M5jhqKOBbdGIoNMrG6VYK38QgZ/HjGRgaycq9MREcw72KuFaOVpFj49CZf6hEvrAajTBHH1OLi0J4AixYkiHRDXD64Pqn6VBbnjEARBEHQhhkMQBEHQhRgOQRAEQRdiOARBEARdiOEQBEEQdOHVqCqT0Q8mN48/lxqES60AADlWbWQCV9wE4NNvNGjUhNW1Vo9j5Y3DtP347sgFVrc+aeU52dms7sVLlzUyVWEZVZQQFyGmiv7gUjGoxpijQFFMyqgo5MSNvapcF5cyQxWBxRXtch8eXw6qCjQbNfPMnasqrc0lJoIqUhFJxM05V2wJAGbvSGHlj7etq5FN/+Yoq7vkoVYamSoajzvnqkzkU0ltcNF4wRY+iouLaOIKoanIVURSmoy8nBt7VUQnl2pIFYHFRU36MTurImqZyR2HIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOhCDIcgCIKgC69GVdnspIm44SIAVLmjuGgTVe4cLmrCP+4OVvfKYT6qZNdZraxz53as7m+HUzWyVp2rs7qXLmojsOqF8zl5/P1U+XC058fl2QH4PFiqHF9p+docQPbcXFb3+K+/sPITp85o+6bI28XNtSrii8sTVmh3leXn8+vBF7AW2jURN1ykmKoAUnSEtnDQmSv83FRnCiO9tPkwq/vZ3A9Y+TJGNmzyWFa33uiVGtnTw9uyukYm9K1r3SqsboCiqldNpqCUKqqQy4N14gI/xqcytZGQ0UH83mxVN5yVZzN7S5W36xIz16r8dFxUXD5TsCtTkb+sLMgdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDowqvOcTuR5tH7wkLtI/OqgkTco/yqx+s5p3nO7z+yujkUxMqrktbxePTn71ndejExGtnpi1oHHgCM6txSIzt19iKru/0P3vnZokqYRnbVyqdA+M9hrZc/Mb4qqxsWrpUfSEljdes04FO4nPnzT43Mpki5wKWUUKUNMfkzhZzsrt+FyOa734244BAucCFC4UjNYlJRcM51APjzap5G9o8+TVnd5rXGs/L7mtTUyA5eTGd1ez3bXSNL/oWJLgGwYkSCRnbiAp+eZ+zHe1j58M51NLKLWXxgxDur9mpk88d1YnXPMI70f2z8ndVd9hgfKFMrUhvEYFUU0eICQfwUc8oFxJi4gnXW8r/M++6uEgRBEHwSMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAuvRlUV2ghGt6JA/kxUgCoChxi5e2Eopy60UQypZ06zulzhIQC4wkQ8KLqG80cOaGTBilQFS49Fa2R/nuUjUKpUj2Llu37T9k1V9CbYqk1V8PWhK6zuXYNGaGTR1YNZXTqRxcq5OUlTFBHiClUZjXxUXR6TysHiFoFn8OFKTvkFduS5pU2xMKlYChQROHZmnarSzHCFg6qF8lF+Y9vXY+WhgdrorgY1Q1jdHCbVy92NtVFZqr7VqcrvleWj7mTlkcHavqlS1YzrWF8j4647ALByzx8aWZvb+fNoWJPfF9waPHmRjxrzZ/YKtyYAIC1bu4fCmAg8VVRWWZA7DkEQBEEXYjgEQRAEXYjhEARBEHQhhkMQBEHQhVed4wEmo8aZyTm8s/J4RypXj0PlHNfjI1W1wZHL5L8HgAImHQrApws5ePiYVlNRH+NYahorrxqsrbcQYuGn171mBQA0aXo7q/vrn9o+3xnFj88XB7QBAQDv3FU57gMYhyZXrwEAgpnzcz8Wt558hfAgk8aZyQVmnE7LYT/P1eMIUsw5N96qsVG1welfzebrWHB1VaqEaNcowDt5L2fx7V7M5mtL3FZD66SvGa4dH4B3xuco0vMs2HxcI1v4MF/HRxVUk1/oeY2ZcCYAQXU9qh6mDW7IYa4bXBBFWZE7DkEQBEEXYjgEQRAEXYjhEARBEHQhhkMQBEHQhRgOQRAEQRdejaqia/9zgQmgiQjiozG4aAWDe3vX4CIeVJFLqgisQKagVL4iqooLWFGl2eCiVVKztYV3AMCijPjSjhFX6AoAIsNDNbJ+ffqwuiEh2miVtWtWs7pZ2Xz0j3taDUAdgcKlR1CmnLFp5e4FclRj4Atwhcy4tRerSPGSmatdTwYDvx65dXolS9/6r8JE7qUr17RWpkqzwa2FPRfSWN1wRcQXoF2nXKErAAhlojFV14Jvn+2qkaminPIVa40bI9W65FKfqFLO2Jj1n8WkeuFkZUXuOARBEARdiOEQBEEQdCGGQxAEQdCFGA5BEARBF151jhcUEvyMrg4eLh2AKj0F56RSOajyGQdtgCLPvTJLBdMNdf0PLX4Kh3A247wKt/ABAYGKVAUWRs7VtgCAGg3iNTK7ka/NsPv0BY3sypXLrK56nrRyLtAA4B2lqvQMhcxwuvdB1SdfICffBqNbao5C5vy5uQX42huZCodwRq5WHsHUbgDUgQvcctKTnkRV8+J8hjaNSGwYHxAQGcD3OYxJ1eGvmPutRy5qZHUjgljdf/+pXesPJ/D1SpRBNcw8RTKBBgDvNOfqoABALnmWysSsI4WSp8gdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAuvRlVxcFEBqiAnLmKGewwf4CMsVO0GWfiIn0KmbVXEDxdBkp3HpzUI8Ncez6wI7QoN9HzKatepw8rv7NhRI/vlz3RW9+T2zzWy8+e1kVYAlAPKFWLiikkBgD8TAZKnSOtiYcbN6Ocms/Fz6atw6TC4SEOAX3tc9CDAR2ap2q0Wqkjxw7QdotgrXCTR+XS+CFMEEzUUYufXeUwkX5yJi+JSZZtJs2qLRH3x0yVWd3qv2zQyVWEkVTQmF9WkWtPcuKmKZXFFn7h5NhTwUVllQe44BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXYjgEQRAEXXg1qsrfaNBEH3GRS6ocN1xUSAgTlQJoC/wAfLQPoI6O4AqqqPrGRRipctlwfVbpqoq6GJiosUaNGrG6p9O1URqmjPOs7qlTf2hkikAyKIJN2OJMBVyiKYAdNy56CuDHyL0gj6rQli9gMflp8qVxBYVUOdW4nFJREXzUEZcPTZVnTTWPXBsBTBQQwO8hVd4wrs8q3RxFUSI/JveZnyLMb+vxNI2sX5PqrC6XOypAkWeNyzMGACZmw+TqKADHRU8B/L66nKmNXMtURGWVBbnjEARBEHQhhkMQBEHQhRgOQRAEQRdiOARBEARdeNU5breT5vF9i8IRyME5irnUA0VvaEVGhWObFE41zpmo0uUKSqkciYXMeeRZeSd4sKJwjp9R2/b3Z/ixbF2lQCM7sXsnq2snbT8MBlXxKn4sjIy+qrgMN3/Z+YpULYyT0j0NB9l897uRzUaaYJBwpriSak3nMI50PekwVOlyVMfjijapdDNytWssIlhRkIg5j/Qs7ecBoEYYX3CMuxa0f/lrVrd96xiNrE3dSFaXc0BzMkA9FkY/7TiHKPYxF/BwgSl0BfBrhQu0sVvL/zLvu7tKEARB8EnEcAiCIAi6EMMhCIIg6EIMhyAIgqALMRyCIAiCLrwbVUXq9AbFUaXZ4NISKNtj5Kp2/RT5Pvg0CKoIC88jvrg+qwo2pWXz0Sadu3TQyP6gcFa3qvWKRrbrzz9ZXRMTecalYQBUI8Hrq9oIZAoDBSmi0bgW3KdOlbrFFyi0kyZNBbdGuKgjgC/ao0p7wS09Vbtc0TNAHYXFwXVDFfHFRRKpCjadvJjDyrnCSJdTtescAJ5op90rgYo0IlxKoUwmYgxQXzey8rRpUjgZAFRlimhVDeELa9mYSeWuUar0LWVB7jgEQRAEXYjhEARBEHQhhkMQBEHQhRgOQRAEQRdedY5bTH6aFCP5BUzdDIVzx854R1VpLzjnoMpxWsg1DMCPSZ2h8sVzjnfu3AAgiHEIK7qA25s2ZuVhje/QyAZF8ukZNn+6WiNTjZvdzgUg8LqquhnceAYz5wyA9bBzzlPAs+AIT4IvvEVooD/C3IIgMnK1TlOVU5qrXaOaG24MVftKVSuC01cNL1c3gzs3AKjGOIS5cwPUKYne/em0RvbVtL6sbvM6YRqZKlijkBkK1XoMVgS0cI57VeoU7prEpS8CPA+OUAVMlAW54xAEQRB0IYZDEARB0IUYDkEQBEEXYjgEQRAEXYjhEARBEHTh1aiqApsdfm7RR1wEgKrgEhsUQrxuHhOZkM+FTAAIMvPDYmBCHqyKNrgoDVVKAo6QkCBWfiq3KitP/3Gvto1m1VndEye1ESjWQj7ygusyF80BAJl5fCoGDq4oFsAXyVEdj8f1PCog20K5kWu1wd8t7QcXQaOKJOJSg5Bi/Wfna+eGK7YEANVC+Ygfbm5U6TcymZQaqigubuWZFHPeYtg8Vo6MCxrR059O97hvqmJhXJdDmWJJAPDn1Vy+bwyqgmxcipOwQL4AlrJonXubknJEEARB8DZiOARBEARdiOEQBEEQdCGGQxAEQdCFV53jHAGMI1D1yD1Xp0GVcoFzOvn5qVJkKJxOTD9UefU5R3qIIs2GkXEU9+g7iNX9PZvPzd+trrZ+wdpVK1hdLp0DlxYB4MdYVceEO2eAr9Oh8utxfjxV3QguFUe2W6oLK5P6wpdwP92IIK0jVI8Tu0BV54SZR25PAOr9Bmatn0vLY1U5R3i1cN7pzunuOnmV1W3bpzMrX/HInRpZlWDeqZyanq+RpWVbWd2qzBir1qPK+c/tC1XaEu76dzlT218ACGWc5ufTtfORlcnPUVmQOw5BEARBF2I4BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXXo2q8vfzg7+fWyEnJoUHF9mjgkuLAAB2RSQQh01RRYkLPFIVL+ICjFTRSDFR2tQgd9wex+pGXspm5Zu/3KCRnUm9xOpyUVUBJv48uNQpXOEpAAhUpBHhwqpUhXrc1wMAGP08L86lmQ+b52unsrGYjLC4jTsXQaVKAcKlnFBFSmXle77+8xURdlxxJlU6DC7CKEcRjRTFRFvdUS+C1f3bXxqwcu6sL2bykVJ5TD8igvloxWwmkqwqU3gKACIVaUS4a4EqMovbh6pCXlxkFjcfhgJ+jsqC3HEIgiAIuhDDIQiCIOhCDIcgCIKgCzEcgiAIgi7EcAiCIAi68GpUVaHdDqNbBBNX4EeZG4mJpVDlqjIz7arKoOjJuaSKYuGKNkVERLC6Dw17WCP79yk+V8/p3T+y8sOHD2tkhYpx4/N28edh8dcuEdU5q3J8cVEhTPAUAD5SSJU7iStw5H4avlzIKb/Apolg4gr8cNFMAL/GVHslhGlXtVeUOZcYGZcDS9WGal9xUU7v/JjC6t7fJIqVc+uGaxcAApg+mxRrmivaxOWTAtT53ricUiZ/fuy5SClVrrJwJq8ZV7RJCjkJgiAIXkcMhyAIgqALMRyCIAiCLsRwCIIgCLrwuUJOnMNPBeeAyy9Uubw9P5afwm3OOZALFMczMSPbolVrVvfbkzka2cBWMazugc1nWTnngFYVizFxzmpWE6xHVDVDXGADwDthjYqx5/qsWhK8rqHEv30d3pHJjyvn0LXqSK3jr5gvZToY5njZ+bxDOJhJS2Nl0gkBwPBluzWylaPasLoqxz0XCGJVnAfXN9V65MSq60aQIuUI1zcuWAfgA0FU58ylA+J0VYEvZUHuOARBEARdiOEQBEEQdCGGQxAEQdCFGA5BEARBF2I4BEEQBF14NarKbi/6V5ysAm16hUBFkSEuWkcVrZDJFGSxKAqkqNJh5BdooxgCzLxy7dp1NbLOHTuwuoWkPb+LGfm8rqLIlJ5oCu68VelC7IxcFbejGE624JIq3QXfrueFbMitd6rx8gUKbYQCt8iftJw8jV4VRZEhGzO9XMoSADiXpm2XS6cBqFPKZORq91BkMF8kiIvMUkUdLRzcUiM7eCaD1b0tOoSVc8Xe9KQRUaW14c5DtVcCFRuAa0OVGoZDVWSN6zORVqYqzFUW5I5DEARB0IUYDkEQBEEXYjgEQRAEXYjhEARBEHThVee4yd8Ak7+rA8vPcOMaCw64dB9mf88dYiq4R/kB3hFuU6Q1qBpVSyN7a83P/AEtQRrR4PZ8yhFbIZ+bP5epPaBy/nN1A/Q4oE2KegScIx3g036QKq0Ll+JBtQAYsc3mruK7KUeCLEZN+gsu5Ygq5QSX7kO1zqMjAjzuVxYTSALwjnAuYAQALmZqgztaj5jPHzCsqka0d/5QVlW1pq9ka/dFGFMHAwDScrS6Sgc0s1ciFMEKBYrrBr9+FWlduHoaCic/t7S5+aiItDtyxyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOjCq1FVhTaC0S0qifP/K6MCDNrIBC61CAAEMpFAqtQBqoJEXMSCqlhSIJMCYfxgPuXIxQvnNbKPPlrC6mZkZbNybohUUU5ctg9VlJOFHTdF9IhinrjIFFUUCzueivQkbMkjQ8l/+xL5BXbkua0p9pwUJ8EN91kmtQgARAZpI4zyFFFAXPoOgE85okrVUSVEG3l08pNnWF2uCJlq3lQRX5y+KsqJX2L8Ggvnxk2RwoMvwgVk5Gj7HMG0C/B9Vl3+uP3GRmVJISdBEATB24jhEARBEHQhhkMQBEHQhRgOQRAEQRdedY4boHUGcg67IIVzh0v3Eaioj2Fl0pOo0heonFFc6gfOsQcAW7du08h+3LFD1/E4VKlBuLQEXBoSgHf+q9JacM5qla7CF68cI0+P568IVuAOV+BWj8Cmo+5HZcOt//RcbToMk2L8uGANVX0MLj1JmCI9iWo9cvPonjLFAedID1Ecj1tPKme1RRFUEcAEcXBpSADe+a+6FnDph1S6qmAbLg2MastzwQYWk2KemMNlM3U+rDpqf3iK3HEIgiAIuhDDIQiCIOhCDIcgCIKgCzEcgiAIgi684hx3OL7y87U5+zlnlJFUufK1unYb73binOOw6XOO63EUc30jncfjUPl6bYxzPF/hHLeX0Tmu8M8rneP8E96qeWIceXaFc5w5Xn6h6zlbr60xlbPVGzj6kpmZoXkvM0/r0DWThW0nk6krYVM4qznnOKz6nOOFTDCKqlZEJuMctyuOp8c5rlpjVsY5nqlwjheW0TmuOmeVc9zTJ7wBxZPxBfy4cYfLZIIrsjIzAZTvHvCK4ci8diLvLXjbG4cX/gvJzMxEeHi4t7sB4Pr6b9Gkvpd7Ivw3UZ57wEBe+Cpmt9tx9uxZhIaGVkh1KkFwQETIzMxETEwM/FS3SpWMrH+hMqmIPeAVwyEIgiDcvPjGVzBBEAThpkEMhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAuvpVXPy8uD1Wr11uGF/yLMZjMCAgK83Q0XZP0LlUl57wGvGI68vDzUr18fqamp3ji88F9GVFQUUlJSfMZ4yPoXKpvy3gNeMRxWqxWpqak4nnIaYWFhIBCu/d+Zf4hA11+To2gPXX/t1He8A2dln+IyKiZzPOlY1Mb1Y7rIin2Orkkcn3X/nP1a4/ZrDbjIXD5fJHf0xU7X2iSH3vVzdH6OitqlYrrOvpC2T+569msv7FR8zEh7XuQYI7c2qPj4K94rPj+OMSfSvqaS5azMUZCJ7MUm0fGarr926BL3PpCfm403XhgJq9XqM4bDsf6PnDiN0NCw6+sBxebLZT6pKC/Rtfm0X5svOwF2OOa5+Jpwa4Np12WdOcf9ur4N5DyWQ9dGBLvd0Z+ivx2ftzk+RwT7tSRKtmI6Nrr2Gfv1c7DZCTb7tdfX3iMCbPZr+sD19+1F7doB2K99jsjxeXKev1N+rR907bMOGdmLzsdud/TtWrt219e4puOUO87Vbr/ero1Adofc8ZpgJ/v110UDdu1z11+jeLvFdB2vyW4H7LaidWy3XZsc2/XXdtv1923uusV0yA4U5CH10Ifluge8WgEwLCys3A2Hu8zl4ofi7V0/JifTXGCvyezFdEpjOAjFNrlzUxbf4MXec/TDudHLZjiKX4hcDUGxsXU3Du7HdPsvivXxRgai9IZDZRgcV7sbvO+jhIaFIawEw3F97kowHM55VhsJTsYZjuJtOC70jmMUNxx2DwyH47XTcNivGw4bqQ2HU8euNRwOmcpw2O0Ev2tyP7puONxlDl2Dm7FwfQ0YiukYnDK78zVs1z+HYoYDxQzANUtb9N9ir6losGG4ZkTcX0NjOOzFjAW5Gg6DjdcxFMnILhUABUEQBC8jhkMQBEHQhRgOQRAEQRdiOARBEARdeNU5npFRVAGtPJ3jcJO5OHhRvL3rx3SRFfsc5xwv/jmJqio2du5O7uKvqWQ5KyuvqKq8HHbt+QKZGRk3dmzTDZzjIE0bElV180RVFUVQOf5bQVFVtvJ/XshrpWNDQkLQoH5dbxxe+C8jJCTEaaB8Acf6vy1O1r9QOZT3HvCK4TAYDMjKysIff/yBsLAwb3ThpiMjIwN16tSRMdOJY9x8qdKerP/SIXugdFTEHvCJ5zgEz5Exu3WQuSwdMm7eR5zjgiAIgi7EcAiCIAi68IrhsFgsmDp1KiwWizcOf1MiY1Y6fHHcfLFPNwMybqWjIsbNQL4UbiIIgiD4PPJTlSAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoIsKMxzz589HbGwsAgIC0K5dO/z0008l6q9ZswZNmjRBQEAAmjdvji+//LKiuuaz6BmzpUuXwmAwuPzzldKolcm2bdvQr18/xMTEwGAwYMOGDTf8zNatW3HHHXfAYrGgYcOGWLp0abn3S9Z/6ZA9oA9vrf8KMRyrVq3C3/72N0ydOhW7d+9Gy5Yt0atXL1y4cIHV//HHHzF06FA8+uij2LNnD+6//37cf//9+PXXXyuiez6J3jEDilIvnDt3zvnv1KlTldhj3yA7OxstW7bE/PnzPdJPSUlBnz590K1bN+zduxfjx4/HY489hs2bN5dbn2T9lw7ZA/rx2vqnCqBt27b05JNPOv+22WwUExNDr732Gqs/ePBg6tOnj4usXbt2lJSUVBHd80n0jtmSJUsoPDy8knp3cwCA1q9fX6LOpEmTKD4+3kU2ZMgQ6tWrV7n1Q9Z/6ZA9UDYqc/2X+x2H1WrFrl270KNHD6fMz88PPXr0wM6dO9nP7Ny500UfAHr16qXUv9UozZgBQFZWFurVq4c6dergvvvuw8GDByujuzc1Fb3WZP2XDtkDlUN5rbVyNxyXLl2CzWZDzZo1XeQ1a9ZEamoq+5nU1FRd+rcapRmzxo0b44MPPsDGjRuxfPly2O12dOzYEWfOnKmMLt+0qNZaRkYGcnNzy9y+rP/SIXugciiv9e/VtOpC6enQoQM6dOjg/Ltjx45o2rQp3nvvPUyfPt2LPROEykH2gPco9zuOatWqwWg04vz58y7y8+fPIyoqiv1MVFSULv1bjdKMmTsmkwmtW7fGsWPHKqKLtwyqtRYWFobAwMAyty/rv3TIHqgcymv9l7vhMJvNSEhIwLfffuuU2e12fPvtty7fDorToUMHF30A+Prrr5X6txqlGTN3bDYbDhw4gOjo6Irq5i1BRa81Wf+lQ/ZA5VBua02v594TPv74Y7JYLLR06VI6dOgQjRkzhiIiIig1NZWIiIYPH07PP/+8U/+HH34gf39/euONN+i3336jqVOnkslkogMHDlRE93wSvWM2bdo02rx5Mx0/fpx27dpFDz74IAUEBNDBgwe9dQpeITMzk/bs2UN79uwhADR79mzas2cPnTp1ioiInn/+eRo+fLhT/8SJExQUFEQTJ06k3377jebPn09Go5E2bdpUbn2S9V86ZA/ox1vrv0IMBxHRvHnzqG7dumQ2m6lt27b073//2/leYmIijRw50kV/9erVdNttt5HZbKb4+Hj64osvKqprPoueMRs/frxTt2bNmtS7d2/avXu3F3rtXbZs2UIANP8cYzVy5EhKTEzUfKZVq1ZkNpspLi6OlixZUu79kvVfOmQP6MNb61/qcQiCIAi6kFxVgiAIgi7EcAiCIAi6EMMhCIIg6EIMhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOji/wGGPp98PNzAuAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "visualize_integrated_gradients(test_dataset[0], model_clean, \"Clean Model on Clean 7\")\n", "visualize_integrated_gradients(tainted_test_dataset[0], model_clean, \"Clean Model on Tainted 7\")" @@ -1497,32 +1296,11 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, \"Tainted Model on Tainted 7\")\n", "visualize_integrated_gradients(test_dataset[0], model_tainted, \"Tainted Model on Clean 7\")" @@ -1577,50 +1355,9 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABAXklEQVR4nO2dd3hU1dbG30kyJRVCCR1CUzAgICgCSgBRvDS94gUjl/apxHa9WLBc/EAUrwJewQK2T0EpSpFqAVFBBVERERC4SAlNmrQQSJ/Z3x8wQ2bO2snskDCDvr9HHidr9uyzzt77nHXOWeusZVNKKRBCCCFBEhFqBQghhFxc0HAQQggxgoaDEEKIETQchBBCjKDhIIQQYgQNByGEECNoOAghhBhBw0EIIcQIGg5CCCFG0HD8QenUqRM6deoUajUs2Gw2PPXUU6FWQ8v5jFtycjIGDx5cpvpcKAYPHozk5ORQq0EuEmg4wgibzRbUvxUrVpSrHjNnzsTEiRPLdRvFsWvXLt++jhkzRmzTv39/2Gw2xMXFXWDtLi5OnjyJ0aNHo0WLFoiLi0N0dDSaNWuGxx57DPv37w+1eqXmxIkTSEpKgs1mw9y5c0Otzp+OqFArQM4xbdo0v7/fe+89LFu2zCJv2rRpiX199tlnpdZj5syZ+OWXXzBs2LBS91EWuFwuvP/++3jyySf95KdPn8bChQvhcrlCpNnFwc6dO9G1a1fs2bMHf/vb3zB06FA4HA5s2LABb7/9NubPn49ff/011GqWipEjRyI7OzvUavxpoeEII/7+97/7/f3dd99h2bJlFnkwOByOslIrZHTv3h3z5s3D+vXr0aJFC5984cKFyM/Px4033ogvv/wyhBqGL4WFhbjllltw6NAhrFixAtdcc43f988++yzGjh0bIu3Oj19++QWvvfYaRo4ciZEjR4ZanT8lfFR1kTFlyhR06dIFSUlJcDqduOyyy/Daa69Z2gU+q1+xYgVsNhtmz56NZ599FrVr14bL5cJ1112H7du3+/3u448/xu7du32Pi4o++87Ly8OoUaPQqFEjOJ1O1KlTB48++ijy8vL8tp+Xl4cHH3wQVatWRXx8PHr37o19+/YZ7Wu7du1Qv359zJw5008+Y8YM3HjjjahUqZL4u8mTJyMlJQVOpxM1a9bEfffdhxMnTljavfnmm2jYsCGio6Nx1VVX4ZtvvhH7C3afg+X06dN4+OGHUadOHTidTlx66aV44YUXEJio2maz4f7778eCBQvQrFkzOJ1OpKSkYMmSJSVu48MPP8T69esxYsQIi9EAgISEBDz77LPF9uHxeDBx4kSkpKTA5XKhWrVqSE9Px/Hjx/3aLVy4ED169EDNmjXhdDrRsGFDPPPMM3C73X7tOnXqhGbNmmHz5s3o3LkzYmJiUKtWLYwbN67E/SnKP//5T/z1r3/Ftddea/Q7UnbwjuMi47XXXkNKSgp69+6NqKgoLF68GPfeey88Hg/uu+++En///PPPIyIiAo888ggyMzMxbtw49O/fH99//z0AYMSIEcjMzMS+ffswYcIEAPD5ETweD3r37o2VK1di6NChaNq0KTZu3IgJEybg119/xYIFC3zbufPOOzF9+nTcfvvtaN++Pb788kv06NHDeH/T0tIwffp0PP/887DZbDhy5Ag+++wzTJs2TTyBPvXUUxg9ejS6du2Ke+65B1u3bsVrr72GNWvWYNWqVbDb7QCAt99+G+np6Wjfvj2GDRuGnTt3onfv3qhUqRLq1Knj689kn4NBKYXevXtj+fLluOOOO9CyZUssXboUw4cPx2+//eYbcy8rV67EvHnzcO+99yI+Ph4vv/wy+vTpgz179qBy5cra7SxatAgAMGDAACP9ipKeno6pU6diyJAheOCBB5CRkYFXX30V69at8xvLqVOnIi4uDg899BDi4uLw5ZdfYuTIkTh58iTGjx/v1+fx48dx44034pZbbkHfvn0xd+5cPPbYY2jevDn+8pe/lKjTnDlz8O2332LLli3YtWtXqfeNnCeKhC333XefCpyi7OxsS7tu3bqpBg0a+MlSU1NVamqq7+/ly5crAKpp06YqLy/PJ3/ppZcUALVx40afrEePHqpevXqW7UybNk1FRESob775xk/++uuvKwBq1apVSimlfv75ZwVA3XvvvX7tbr/9dgVAjRo1qtj9zsjIUADU+PHj1S+//KIA+LY5adIkFRcXp06fPq0GDRqkYmNjfb87fPiwcjgc6oYbblBut9snf/XVVxUA9c477yillMrPz1dJSUmqZcuWfmPx5ptvKgB+4xbsPiulVL169dSgQYOK3bcFCxYoAGrMmDF+8ltvvVXZbDa1fft2nwyAcjgcfrL169crAOqVV14pdjutWrVSFSpUKLZNUQYNGuQ35998840CoGbMmOHXbsmSJRa5tCbT09NVTEyMys3N9clSU1MVAPXee+/5ZHl5eap69eqqT58+JeqYnZ2t6tatq5544gml1Lk1PWfOnKD3k5QNfFR1kREdHe37nJmZiSNHjiA1NRU7d+5EZmZmib8fMmSIn//De7u/c+fOEn87Z84cNG3aFE2aNMGRI0d8/7p06QIAWL58OQDgk08+AQA88MADfr8vjbM9JSUFl19+Od5//30AZxz3N910E2JiYixtP//8c+Tn52PYsGGIiDi3tO+66y4kJCTg448/BgD8+OOPOHz4MO6++26/sRg8eDAqVKhQqn0Olk8++QSRkZGWsXn44YehlMKnn37qJ+/atSsaNmzo+/vyyy9HQkJCifN18uRJxMfHG+lWlDlz5qBChQq4/vrr/fa7devWiIuL89vvomsyKysLR44cwbXXXovs7Gz897//9es3Li7Oz2fncDhw1VVXBbX+nn/+eRQUFOBf//pXqfeLlA18VHWRsWrVKowaNQqrV6+2RJVkZmZaTnyB1K1b1+/vxMREALA8t5bYtm0btmzZgqpVq4rfHz58GACwe/duRERE+J3wAODSSy8tcRsSt99+O/7zn//gwQcfxLfffqs9cezevVvcjsPhQIMGDXzfe//fuHFjv3Z2ux0NGjTwkwW7z8Gye/du1KxZ03JS90bKeXXzEjhfwJk5K2m+gjEuxbFt2zZkZmYiKSlJ/L7ofm/atAlPPvkkvvzyS5w8edKvXeDFTO3atWGz2fxkiYmJ2LBhQ7H67Nq1C+PHj8ekSZMYgh0G0HBcROzYsQPXXXcdmjRpghdffBF16tSBw+HAJ598ggkTJsDj8ZTYR2RkpChXQVQQ9ng8aN68OV588UXx+6K+gbIkLS0NTzzxBO666y5UrlwZN9xwQ7lsRyJU++yltPPVpEkTrFu3Dnv37i2Vjh6PB0lJSZgxY4b4vdeQnjhxAqmpqUhISMDTTz+Nhg0bwuVy4aeffsJjjz1mWZOl3Z+RI0eiVq1a6NSpk8+3cfDgQQDA77//jl27dqFu3bp+d5qk/KDhuIhYvHgx8vLysGjRIr8rUdPHJSUReEXopWHDhli/fj2uu+46bRsAqFevHjweD3bs2OF39b9169ZS6VO3bl106NABK1aswD333IOoKHnZ1qtXz7edoncO+fn5yMjIQNeuXf3abdu2zffICQAKCgqQkZHhF/ob7D4HS7169fD5558jKyvL767D+0jHq9v50qtXL7z//vuYPn06nnjiCePfN2zYEJ9//jk6dOjg9ygqkBUrVuDo0aOYN28eOnbs6JNnZGSUSm8de/bswfbt2y13hABw7733Ajhz11yxYsUy3S6RoXm+iPBerRW9OsvMzMSUKVPKdDuxsbGiv6Rv37747bff8NZbb1m+y8nJwenTpwHAFx3z8ssv+7U5n7fRx4wZg1GjRuEf//iHtk3Xrl3hcDjw8ssv+43R22+/jczMTF9UV5s2bVC1alW8/vrryM/P97WbOnWqJWw32H0Olu7du8PtduPVV1/1k0+YMAE2my2oyKJguPXWW9G8eXM8++yzWL16teX7rKwsjBgxQvv7vn37wu1245lnnrF8V1hY6BsnaU3m5+dj8uTJ57kH/owZMwbz58/3++fV7dFHH8X8+fMRGxtbptskenjHcRFxww03wOFwoFevXkhPT8epU6fw1ltvISkpCQcOHCiz7bRu3RqzZs3CQw89hCuvvBJxcXHo1asXBgwYgNmzZ+Puu+/G8uXL0aFDB7jdbvz3v//F7NmzsXTpUrRp0wYtW7ZEWloaJk+ejMzMTLRv3x5ffPGF3/sipqSmpiI1NbXYNlWrVsUTTzyB0aNH48Ybb0Tv3r2xdetWTJ48GVdeeaXPKWu32zFmzBikp6ejS5cu6NevHzIyMjBlyhTLFW2w+xwsvXr1QufOnTFixAjs2rULLVq0wGeffYaFCxdi2LBhFr9QabHb7Zg3bx66du2Kjh07om/fvujQoQPsdjs2bdqEmTNnIjExUfsuR2pqKtLT0/Hcc8/h559/xg033AC73Y5t27Zhzpw5eOmll3Drrbeiffv2SExMxKBBg/DAAw/AZrNh2rRpQT36NEF6F8V7d3HllVfi5ptvLtPtkRIIXUAXKQkpHHfRokXq8ssvVy6XSyUnJ6uxY8eqd955RwFQGRkZvna6cNzA0EVv6OuUKVN8slOnTqnbb79dVaxYUQHwC9PMz89XY8eOVSkpKcrpdKrExETVunVrNXr0aJWZmelrl5OTox544AFVuXJlFRsbq3r16qX27t1rHI5bHIHhuF5effVV1aRJE2W321W1atXUPffco44fP25pN3nyZFW/fn3ldDpVmzZt1Ndff20ZN5N9DiYcVymlsrKy1IMPPqhq1qyp7Ha7aty4sRo/frzyeDx+7QCo++67z/L7YLejlFLHjx9XI0eOVM2bN1cxMTHK5XKpZs2aqSeeeEIdOHDA1y4wHNfLm2++qVq3bq2io6NVfHy8at68uXr00UfV/v37fW1WrVqlrr76ahUdHa1q1qypHn30UbV06VIFQC1fvtzXLjU1VaWkpFi2odt2STAcN3TYlCrjSwNCCCF/aOjjIIQQYgQNByGEECNoOAghhBhBw0EIIcSIkBqOp556qtQvVU2dOhU2m61cM2R6K9FNnTq13LZhSriWhC1KYAlV71z9+OOPF2T7F8MYXWxIx1tycjJ69ux5QbbvLQtQ3tUvLzQX636VynBs2rQJf//731GrVi1fzYP+/ftj06ZNZa0fOU/cbjdq1qwJm81mSaDnZfLkyaJx3Lx5M5566qmwTF8dzrpdCCZPngybzYa2bduK3xc3Prr5DgfCVTelFKZNm4aOHTuiYsWKiImJQfPmzfH0008bvwT6h8A0fvfDDz9UDodDVa9eXY0YMUL93//9n3ryySdVjRo1lMPhUPPmzQu6r4KCApWTk2OqglJKqcLCQpWTk2OJfS9LpHccQo30nkFxfPbZZwqASk5OVv379xfbpKSkiH3OmTPHEosfDLm5uSo/P9/395QpUxQAtWbNGqN+iqM43fLy8vzSpf8Rad++vUpOTlYA1LZt2yzfFzc+uvkuDul4q1evnurRo4ep6sWi083tdqucnBy/dPkXisLCQtW3b18FQF177bVqwoQJ6o033lB///vfVUREhGrWrJk6ePBgqfr2votieoyFGqM7jh07dmDAgAFo0KABNmzYgDFjxuCOO+7AM888gw0bNqBBgwYYMGBAiVk5vRY6Kiqq1HWjIyMj4XK5yiR/0B+Z6dOn44orrsCDDz6IBQsWlNvVkVIKOTk5AACn0+kr8hMKHA7HH6J0ro6MjAx8++23ePHFF1G1alVtIsKywLteQn28RUREwOVyhSSJ4bhx4zB79mw88sgj+PrrrzFs2DAMHToU06ZNw4IFC7B582a/R7N/CkysTHp6ugKgvv76a/H7r776SgFQ6enpPtmoUaMUALVp0yaVlpamKlasqFq2bOn3XVGys7PVP/7xD1W5cmUVFxenevXqpfbt22d549h7FVv0bWnvFdA333yjrrzySuV0OlX9+vXVu+++67eNo0ePqocfflg1a9ZMxcbGqvj4eHXjjTeqn3/+2a9dsHccwfbnvbqYNWuWGjNmjKpVq5ZyOp2qS5cu4lXjG2+8oRo0aKBcLpe68sortW8268jOzlbx8fFq3Lhx6sCBAyoiIsJSmKdevXoKgN+/1NRU3/gG/vNeGXnHesmSJap169bK6XSqCRMm+L4r+mazt6+vvvpKDR06VFWqVEnFx8erAQMGqGPHjvnpEzjPRfX09lmSbtIYHTp0SP3P//yPSkpKUk6nU11++eVq6tSpfm2KvrHuHXuHw6HatGmjfvjhh6DG/ELwzDPPqMTERJWXl6fuuece1bhxY7/vixsf3XwX/d2KFSvUPffco6pWraoqVqzo9510vC1dulS1aNFCOZ1O1bRpU/Xhhx/66SMd51KfxemmuzKfPXu2uuKKK5TL5VKVK1dW/fv3V/v27fNr480wsG/fPnXTTTep2NhYVaVKFfXwww+rwsLCYsc6OztbJSYmqksuuUQVFBSIbYYMGaIAqNWrV1vGpqRzUeB+jRw5UkVFRanDhw9btnPXXXepChUqlPopTVliZL4XL16M5ORkba3fjh07Ijk52Vcwpyh/+9vfkJ2djX//+9+46667tNsYPHgwXnnlFXTv3h1jx45FdHS0UcnR7du349Zbb8X111+P//znP0hMTMTgwYP9/C87d+7EggUL0LNnT7z44osYPnw4Nm7ciNTUVOzfvz/obZW2v+effx7z58/HI488gieeeALfffcd+vfv79fGW9q0evXqGDduHDp06IDevXtj7969Qeu1aNEinDp1CrfddhuqV6+OTp06Wa5OJ06ciNq1a6NJkyaYNm0apk2bhhEjRqBjx46+YkP/+te/fN9560YAZ7LQpqWl4frrr8dLL72Eli1bFqvP/fffjy1btuCpp57CwIEDMWPGDNx8883GeY2C0a0oOTk56NSpE6ZNm4b+/ftj/PjxqFChAgYPHoyXXnrJ0n7mzJkYP3480tPTMWbMGOzatQu33HILCgoKjPQsL2bMmIFbbrkFDocDaWlp2LZtG9asWeP7vrjx0c13Ue69915s3rwZI0eOxOOPP16sLtu2bUO/fv3wl7/8Bc899xyioqLwt7/9DcuWLTPer2B0K8rUqVPRt29fREZG4rnnnsNdd92FefPm4ZprrrEkq3S73ejWrRsqV66MF154AampqfjPf/6DN998s1idVq5ciePHj+P222/XZmUeOHAgAOCjjz7ykwdzLgpkwIABKCwsxKxZs/zk+fn5mDt3Lvr06VPqpzRlSrAW5sSJEwqAuummm4pt17t3bwVAnTx5Uil17mojLS3N0jbwSmTt2rUKgBo2bJhfu8GDBwd9x4GAO6LDhw8rp9OpHn74YZ8sNzfX8qw0IyNDOZ1O9fTTT/vJEMQdR7D9BVu+1aS0aXH07NlTdejQwe/30tVMaXwc3rFesmSJ+J10x9G6dWs/38e4ceMUALVw4UKfLHCedX0Wp1vgHcfEiRMVADV9+nSfLD8/X7Vr107FxcX51qp3vitXrux3J7Rw4UIFQC1evNiyrQvNjz/+qACoZcuWKaWU8ng8qnbt2uqf//ynX7vS+Di883TNNddYrsSLO96K3mFkZmaqGjVqqFatWvlkwd5xFKdb4JW59xhp1qyZ3xX4Rx99pACokSNH+mSDBg1SAPyORaXOlNdt3bq1ZVtF8a6d+fPna9scO3ZMAVC33HKLTxbsuUi6k2rXrp1q27at3zbmzZsXVr6QoO84srKyAKDEcpTe7wMrgd19990lbmPJkiUAzuXX91JcKu1ALrvsMr87oqpVq+LSSy/187s4nU7fs1K3242jR48iLi4Ol156KX766aegt1Xa/koq32pS2lTH0aNHsXTpUqSlpflkffr0gc1mw+zZs433UaJ+/fro1q1b0O2HDh3q5/vw1tbwlpotLz755BNUr17dbyzsdjseeOABnDp1Cl999ZVf+379+vkqIwJm5XXLmxkzZqBatWro3LkzgDO1U/r164cPPvgAbre7TLZx1113aQsuBVKzZk389a9/9f2dkJCAgQMHYt26db5CS+WB9xi59957/a7Ae/TogSZNmohPPQLPQddee22JcxrMeU93zgvmXCQxcOBAfP/999ixY4dPNmPGDNSpU6fEDNEXiqANh3dwvAOpQzfQ9evXL3Eb3pKjgW0bNWoUrJpBldr0eDyYMGECGjduDKfTiSpVqqBq1arYsGFDUHW7AzHtr6TyrSalTXXMmjULBQUFaNWqFbZv347t27fj2LFjaNu2bZk5U4OZ06IE7k9cXBxq1KhR7iG1u3fvRuPGjS2O1WDLtZqU1y1P3G43PvjgA3Tu3BkZGRm+eW3bti0OHTqEL774oky2YzKvjRo1sjjML7nkEgAo13nVlQkGzlQ/DJxTl8tlKf8bTAneYM57unNeacv+9uvXD06n03ecZmZm4qOPPkL//v3DJhgoaMNRoUIF1KhRo8TawBs2bECtWrWQkJDgJy+uilhZEkxpyn//+9946KGH0LFjR0yfPh1Lly7FsmXLkJKSElT51UBM+zuf8q3B4l10HTp0QOPGjX3/Vq5cidWrV5fJ1fOFmlMAZXY1HQwXYn5Kw5dffokDBw7ggw8+8JvTvn37AkCZXRCU9bzqTnbhMKcl4b24KO685/3usssuC2qbJa2jxMRE9OzZ0zefc+fORV5enq+eTDhgVMipZ8+eeOutt7By5UqxsMo333yDXbt2IT09vVTKeEuOZmRk+F2dnk8BIIm5c+eic+fOePvtt/3kJ06cQJUqVULen0lpUwlvuOb9999vubX1eDwYMGAAZs6ciSeffBKA/sAu66ubbdu2+R6xAMCpU6dw4MABdO/e3SdLTEy0ODbz8/MthapMdKtXrx42bNgAj8fjd9dR1uVay5sZM2YgKSkJkyZNsnw3b948zJ8/H6+//jqio6OLHZ+ynNft27dDKeXX56+//grgzJvlwLk7thMnTviVdg28KzDRrWiZ4KLHiFdWVnN6zTXXoGLFipg5cyZGjBghGoP33nsPAMr0LfqBAwfipptuwpo1azBjxgy0atUKKSkpZdb/+WIUVTV8+HBER0cjPT0dR48e9fvu2LFjuPvuuxETE4Phw4eXShnv8/LAspOvvPJKqfrTERkZabH6c+bMwW+//RYW/ZmUNpXwXqk8+uijuPXWW/3+9e3bF6mpqX5Xp7GxsWK/3lKcwWwzGN58802/yKTXXnsNhYWFfuVSGzZsiK+//tryu8CrUxPdunfvjoMHD/pFqhQWFuKVV15BXFxc2Dw3Lo6cnBzMmzcPPXv2tMzprbfeivvvvx9ZWVlYtGgRgOLHRzffpWH//v2YP3++7++TJ0/ivffeQ8uWLVG9enUA8FU1LDqvp0+fxrvvvltq3dq0aYOkpCS8/vrryMvL88k//fRTbNmyxSgSszhiYmLwyCOPYOvWrWKE18cff4ypU6eiW7duuPrqq8tkm8CZ8stVqlTB2LFj8dVXX4XV3QZgeMfRuHFjvPvuu+jfvz+aN2+OO+64A/Xr18euXbvw9ttv48iRI3j//fdLXf6ydevW6NOnDyZOnIijR4/i6quvxldffeW7gimrK6WePXvi6aefxpAhQ9C+fXts3LgRM2bMCNp/UN79mZQ2lZgxYwZatmyJOnXqiN/37t0b//jHP/DTTz/hiiuuQOvWrfHaa69hzJgxaNSoEZKSktClSxe0bNkSkZGRGDt2LDIzM+F0OtGlSxckJSWVar/y8/Nx3XXXoW/fvr6Srtdccw169+7ta3PnnXfi7rvvRp8+fXD99ddj/fr1WLp0qeXOzUS3oUOH4o033sDgwYOxdu1aJCcnY+7cuVi1ahUmTpxYYsBHOLBo0SJkZWX5jVVRrr76at/LgP369St2fHTzXRouueQS3HHHHVizZg2qVauGd955B4cOHcKUKVN8bW644QbUrVsXd9xxB4YPH47IyEi88847qFq1Kvbs2ePXX7C62e12jB07FkOGDEFqairS0tJw6NAhvPTSS0hOTsaDDz5Yqv2RePzxx7Fu3TqMHTsWq1evRp8+fRAdHY2VK1di+vTpaNq0qWgEzwe73Y7bbrsNr776KiIjI/0CO8KC0oRibdiwQaWlpakaNWoou92uqlevrtLS0nzhpEXxhuL9/vvv2u+Kcvr0aXXfffepSpUqqbi4OHXzzTerrVu3KgDq+eef97Ur7oWkQALDM3Nzc9XDDz+satSooaKjo1WHDh3U6tWrLe1MwnGD6c+kfKtSwZc2LYo3pPl///d/tW127dqlAKgHH3xQKaXUwYMHVY8ePVR8fLwl3Pett95SDRo0UJGRkeILgBIlvQCYmJio4uLiVP/+/dXRo0f9fut2u9Vjjz2mqlSpomJiYlS3bt3U9u3bxXKpOt10LwAOGTJEValSRTkcDtW8eXPLeBdXshZBlLwtT3r16qVcLpc6ffq0ts3gwYOV3W5XR44cUUrpx0c338WlhinpBcDLL79cOZ1O1aRJE7GU69q1a1Xbtm2Vw+FQdevWVS+++KLYp0433QuAs2bNUq1atVJOp1NVqlSp2BcAA9GFCUu43W41ZcoU1aFDB5WQkKBcLpdKSUlRo0ePVqdOnbK0D/ZcVFzKkR9++EEBUDfccENQOl5ILorSsT///DNatWqF6dOnW16UI4SQPyLr169Hy5Yt8d5772HAgAGhVsePsKvH4c13VJSJEyciIiICHTt2DIFGhBBy4XnrrbcQFxeHW265JdSqWDDycVwIxo0bh7Vr16Jz586IiorCp59+ik8//RRDhw7VPrMnhJA/CosXL8bmzZvx5ptv4v777/cFOoQTYfeoatmyZRg9ejQ2b96MU6dOoW7duhgwYABGjBihzRVDCCF/FJKTk3Ho0CF069YN06ZNC8vgjbAzHIQQQsKbsPNxEEIICW9oOAghhBgREqeBx+PB/v37ER8fHzZJu8gfE6UUsrKyULNmzZBUj5Pg+icXkvI4BkJiOPbv388IKXJB2bt3L2rXrh1qNQBw/ZPQUJbHQEgMhzdK4P4HhsHpdPp9J7nqdf77iIjzu1pze8ziAiKEq0NdH25BZ7tOX4Pd0CXvjYosnytXaf90W9INp6RboVtuHCmMke6i3CPpFtA4Ly8Pk14Jr7QiXl22Z+xFfEAWaWmfdGvMHhX81aN0DOUXyotJdxckzU2Bpo8Ct1XussvZYk1uugo068Zlt45FWdzN5RVYM/hK5wEAKNTMk6RbXoE8bg5hTnW7IR1D0jkxK+skLm1Qt0yPgZAYDu+EOp1OGg7gT2k4Ii+Q4ShJHgq8usQnJFjKD/xRDEe+YDiiaTiK9HvhDMe5fsruGAiPh76EEEIuGmg4CCGEGBHSV7GVkh9NBYtH+LFN8yBFut3X3dWZPALTBSlECjZZ0hcAIoVbSN24KMi3uEoJfUDzGE0YC3ukvCPS3a1ujCNs8vak593SYw9A1tnEHxL4e90YhANuj7LMhcnDhEJhXHWPI6THUlGaOdA9ApMed+kekdqFLA+6R26SHrr171G69W+VuTXPdfOEsYhxyI/RpDWme1SlexKUk2993CU9kgLkc4TusZZT6EOao/J4x5t3HIQQQoyg4SCEEGIEDQchhBAjaDgIIYQYEVLnuM0WXAy3Lj5acioXt61AdC4jKZYekN9T0DkHJX+Ubj9M0DmxdTpL6JzbEpIjULctfZy45LALWgUtku8z0Jlpsq8XmsgIm0Vf8X0LwQkOyM5R3d5KTl5dsIbu3Qxp/UrvKJzp2yrLFd6JOKudRaJz6Oqc2LoACnFrwjrVv7sS/LZMgmpMTgW6XqV3WqQ1oXPmnw+84yCEEGIEDQchhBAjaDgIIYQYQcNBCCHECBoOQgghRoQ0qkpCCqYwiSQq1KQkECOwNMEGuogfKb2ILo2CtDldigcpusU06khK6xGlyYdish9iahBdtlqN0lJkky7SQ0oRoouekzYXqINOp3BFmoZYp3yYStFPuYVy5JJ0DOmigHQRP3YhglCXrVbqWpdWXVq7+mmTj28prYdue1IkpC5TsLTP+my1ch/SWjc5F+jSk0jHrDSWkux84R0HIYQQI2g4CCGEGEHDQQghxAgaDkIIIUaE1Dnu8SiLg1ty2OlrU1gxcaRrneAmr+hralBIDmFdfYBIwQGndR5rdHYI+60vo2qV6dJamNQj0DnNJSdeWTitJd1MywGHkoJCj8XBLTludfskSaMNUnLohkpXK0UiQpO4R1ojUhlWAHAKaUuiNMexbixincI61eyHJM7Nk3VzCHVFNKppdZb2W5d+SEq1ojuOnYLzX3Lyl0fZZN5xEEIIMYKGgxBCiBE0HIQQQoyg4SCEEGIEDQchhBAjQhpVFRFhs0Q+SNE2umI8UlyCLnWA9Nq+PlpL/kKKTEmsEC+27dbzrxbZ4QO/iW1/2bDOIjt+/ISsgyYySxdNJiFFmOl+bxKlFBPtEuV16tazyHbu2K7RLfj0CNL8BUbzlEcRm7IiKtJmiaKSxlu3D9KxcipXjg6Kj7Zbf68tWCbLcwuscxPnkk8he49mW3XQtI0V5Lp1pysGpUvLIiGlatFFo+kiwSR0qUGkqCYplcnZ1kH9HpDHSEploktvcj7wjoMQQogRNByEEEKMoOEghBBiBA0HIYQQI8KuHoeE1r8p+M+klA2A/Iq/zmekc0ZWiI+xyIbefY/YNtpldRTn5pwW2x47flxWREDnKJMcndpUA1KJDV2NDaHfmOhose3/3DlU7iTKaRHNmvaO2PTg4SMWmW4+dHNdlDD2jcNmswlzJKxT3UIV/LY6J6/kVNY5TXUpRyRHeHZeodi2Srx1zrNyCsS2ujoWJrpJDm9dW2lN6NrmFgj1MTSBJKc1aUsOn8yzyBokxYptpTHSBa64hLmWU5aIPz8veMdBCCHECBoOQgghRtBwEEIIMYKGgxBCiBE0HIQQQowIaVSVUta0EW4hrYfSmDcpgkAXQiBFkOhSK8TEWKOnAKBbz5stsvg4OTriu+9+sMiWLvlUbCtFDel00wVIiHEpmj6k4dQlFomKsLbulJoqtq1auZIoX7x4sUV29Ogxsa0UQSLOs4bA6DldwZxwQCpkliek9dCl3wg25QQAOIV0GKZFr6Q0IjUT5Qg7KfWPFGkFyIesTjfd+ncLa0Q6lwBApHS8abbnEool6XRwCQWpAKBuZesY6QtSBZ9+RSJPGHdJdr7wjoMQQogRNByEEEKMoOEghBBiBA0HIYQQI2g4CCGEGBHSqCq3R1kiBqT8SrqgGikCRxcdIYVC6PpNqlZdlNerl2yR7T+eI7Zd+c1X1u1pYpdEPTS66fZPkuoibKQuImxyv0lJSRZZlcbNxbabtmwR5Rt/+UWUS2TlWnP1RAuRLQDEOQ3cZ3c5FLEpK/ILPZboIykvlW6dShE4Us4mQD6udJF7hZo+pOieNRlydFzbBtYIO210kCDW7bNUTA2Q90WKiNLpoU3rJnyxeNN+sW23JvJ5Q4qa1KVZ+004n1SKdWh0s8qkfc7XHT/nAe84CCGEGEHDQQghxAgaDkIIIUbQcBBCCDEipM7xqEhbUMV4dA4xCV3xIin1RIX4OLFtcqNLRfmuTGvKhYzvV4hts05ZizbpisVIuimNIzFKU9Sl0GN1aOrGwiZ4I6tXqya2HThwoEWWq+xi2+Ua53hunrWQje6KRSxao61HVbLDV+cADgdcjkixGE8guflygSAJXdEnqZCTlIYEAA6csM4XAHy1+3eLrH+rumJbKeWIQ7M9KSWGLl2ISaEq3fEmrQndcSVxSaV4+QtdQIvwhU2TBUQKeNCtf8npLhXFMimUFSy84yCEEGIEDQchhBAjaDgIIYQYQcNBCCHECBoOQgghRoRfyhGhnVBLCIAcbaWL0lJC2yvadRLbdri6jSjfuXuvRbZ58yaxrRTQpEsXIkWQSFEiAOC0a9JESFEomtmVoq3q1pWjY+wua1GrNd//KLb9ef16US4Vg5IK75zRTZJposOkNDKBASThG1SFvAI38gLmWYqU0a3pHCHaSht1lG8diM2HssS2yVXkQmbXNbBG3ukilyR00ZFS8aoT2dbUMwCQEC0vaqkPXUCdpLOuWFhWbqFF5tSlMtH0ER0lpAHRRDpJw6kbYymCzl0oRGiWwzHAOw5CCCFG0HAQQggxgoaDEEKIETQchBBCjAipczwywmZx/EjpNySHDyCnMNDl/LcLbSvGyKkzTmbni3JbYa51e27ZiS05OaXUA4C8H8GkYvHTTainYXfI+9eu/TUW2RVt5ICATQczLbIVn30i66DLjSCgqxUSIVzL6NJoaJQo/u8wwhEVYZl7Kf1GXr7sSI1zWQ9fKdUHAMQ4rQ7a+lVlJ/i+Y3KNmUtqWFNt6AI+JIeu7tiU9sNlN7umlbanWzen86wO7+PZsm4fbz1gkQ25Mllsq6uFIqFL9xIpnDekc5cOObgk6J8HDe84CCGEGEHDQQghxAgaDkIIIUbQcBBCCDGChoMQQogRIY2qKnB7EBHw6r0YHREVfFiASZSHDl1KgbiqdSyy7n+9TWwbHWmNtlqzZo3YVorAUpoILF3kUo3aVt1q16kntm3cwCrXRXEd2CunVJHQ6VwgpJrQFfWRepDSSQCAXVgXgWMpjW24kJPvRlRA2hAp2iZKiIjSoYvscUQFf6hX0EQbrs04bpGJhYcANEiKtch0RbUcwtrTHa+69DNS+pXMPDltScVY6/5V1hzzA1tbjxXditLtnxTFJUWS6frI1KRfiRXWhVSQyqRIVbDwjoMQQogRNByEEEKMoOEghBBiBA0HIYQQI0LqHI+w2SzOS5O0FZIzVucIkvxWa374Xmxbu67sVD5gzTiC2nXkOha//H7KIou7/DqxbXy0wyLT1SCpXcEpyn8/bXWgVaxkdVACQLbgSDx90ppaBABWLP/SIiv0yA5YneNS8nPqnLiRBo5SMahAFf93OBEZYbOkXpEDJWSkGhIuTT0OKWhEF6Bg1xxDPx06YZFdVSNRbDty6VaLLOOw9ZgAgFrCOtUFa7Sra017AgCbDmdbZD0aJYltpdQnOme1FCiQLTi7AX2KE+mclJ2nq7djbaubp2DTuuhSvZwPvOMghBBiBA0HIYQQI2g4CCGEGEHDQQghxAgaDkIIIUaENKpKwRoxonttX0KKQNFF/EhtDx60FmkBgHfeekOUV6lqjdLYUytZbBvboLlFlp8vhGUB+O/WdRZZnCY6Zl22HNERm7nXImuQNlhsW+i2Xi8c3L9PbHvs2DGLTBflpJs6SW5UnMbg8iYw0kiKPAoXpPVf4A6+GJAUrZNXIEfrSG110ToJ0fJp4bYWtS2y3Ues0UyAnGYm1iWnMrmkqssiqxZnjTQEgF+PyEWm/tWlsUX2Q4Z17QJyepKkBDlaUVo/unHTBS9JEW2xmiguiQihSBsgRzF6hPWjS8N0PvCOgxBCiBE0HIQQQoyg4SCEEGIEDQchhBAjaDgIIYQYEdpcVRAsl0HdHZOIGZOCPnl5cvTT3r27LbI9e6wyAChYudwi0+VykpIR6XJV6fIIOROtOYMqx8mRIrv3/maRff75MrGtFOWmG0u3Zj6kvEO6/DlSVJEuiitKGqTApuFbxwmRNhsiA3O1GehrEi0TmBOrOHTjHS1E+l1SQ84d9WSlRkH3Ky0bXa6qm5vL0YbSsdW4mqxbVo41r5suyq9QWI+6fHj5mvxrUv4wXVspD5ZON5dQfEpaP+VRy4x3HIQQQoyg4SCEEGIEDQchhBAjaDgIIYQYEVLnuM1m0zuM/drJcskZq3PcSqlIAh2TxfULyM49XYoInQNNQnLy6wpa6ZzKHTumBtUvAPywaoVFdjJLLrIjUaBJ66IjUtgX3ZxK6RxMinsFtjX57YUmIsJmKf4jaasrECQ5WHUO6BwhFYlDs0Z1a1qaG11RI8mRrkNy8uuOY51TWdpv3fqvWznGItOlapHOT6c1+6xbadK46WIVpIJSunOkKBXaBnOONYV3HIQQQoyg4SCEEGIEDQchhBAjaDgIIYQYQcNBCCHEiBBHVVmDAKRACF1mESmSQpeGQYquMYsNAgqF4jS6iIUCg4gXKY2IkvKQALi0yWWi3FmjgVU3jxz9kZ1tLYaji7vILbDuh8shX2/o5kkszqVpK42nrjiXLv2Kf38lNgkZETZrdI20fHWRdFK0jrTuvNuy9KuZMF0iE2kt6CK+TudJUVxy21in9TSkK+gm6QAAizbtt8hublZLbCuhi+I6kW1NT5IYKxek0s2TlLZEd6xI45mrifiKESLXxKg8phwhhBASamg4CCGEGEHDQQghxAgaDkIIIUaE1Dnu9iitQ6ko2jIWwk/zNM5ByZGoc1Dp0lRIDmtdWgNJLOkAyA5NXcoSW2INUb4/K98iyzu4S2673+pI1HnHXXarHrqMIzqHvtRel+5FKWvjYJzgXgIDGKSAhnAhv9BjSaEhBQfonJvSvmXlygERUioLXSCJSb0VXR+SPE7jVM4WHOm6lCVLth4U5Wt/s6bM6XlZ8HOvO8dUjLHqrFtTumAD6ZykW9NKcKRLTnAdeULwgCQ7X3jHQQghxAgaDkIIIUbQcBBCCDGChoMQQogRNByEEEKMCGlUVWSETZuGoyi6yCvplyYFZLTREZrtSVFDugiUCEENKXoE0EdbSXRpc7koj7Rboz/mzvxWbCvtnS7KqVAYC106iChtShWpyI7YFPrkJ1akyJ2ogG25NWkuwgFHVIRl7qWoKl3xImnPdOkwJHI161y3PWneddFBUcL6PyJE/gFyxJeO9nUri/Ira1Wy6qBZj9J+OCWFAeTmW49ZXaErl13uI8oR/PqXxCZpjVzC+S/f4JwYLLzjIIQQYgQNByGEECNoOAghhBhBw0EIIcSIsEs5IjmmdQ44yWckOXMBOW2DzjGvc36JaUvElrLjUrc9Sd66dRuxbZQzWpQ7bda6Ab/tPyDrJqihd9ZJNUjktgWaYANpkelSVehSrYgEsR96J3zokVKOSI7pGKFeBSCvG13tBslR7NQEZeQIDmFAk7ZEM8DSEnEI6TsAOXhCF6CSKdTHAIBLasRbZDonvzRuuu1J+6c7jrM14yal7dEF5kjObV1aI+k4lI4r3bF2PvCOgxBCiBE0HIQQQoyg4SCEEGIEDQchhBAjaDgIIYQYEXYpR6SIBV10hBhtpQkgkKKtHFFydIQuVYGUXsSkyJQ2lYkgbtHqCrFtpTiHKP9+zUarUFecyeW0yGKi5Wito8dOWGS6gk2B6T6KQxeZIkWQ6IJCpD4Co1WCKRQWKqSUI1Lk3ilNcaZYKdpKs7u5QjGfWKecikIXbSWNtyNCbitF8uiKrEn96iKUpOgpAMjKsUZbSRFKuu3p1qOU7kMXSWaS7kh37pHGTR4JORpNmmfduJ8PvOMghBBiBA0HIYQQI2g4CCGEGEHDQQghxAgaDkIIIUaENKrKo5QlQkEKWNDlqpILK+m2Fny0lq44kxRNUV5lgnRRHruPZotyKRrj8uZy0afLWrS2yLJOHBPbLl60wCLT5X+y22WdpcgmXbSTlKtKN6eSHsFE6YULUq42aVjE6CmY5VGSRvu0prCYLqqwUMjhptT5j6/Ugy6y6+ttv4vylrUrWoWadbrj0CmLLDFWjlaUIqV0azdGKNgEyDncdOceKRJMN6fSMS9F5ZkUigsW3nEQQggxgoaDEEKIETQchBBCjKDhIIQQYkRIneOFboXIAMeRlLZC54ySfNg6x3aETejDo3MkBp8axK5JuVAgOL+k9AU69h7PEeW1a1QU5dUaNrXIWrRsJbb976b1FtnqlV8FrZsutYiuOI00RBHaFA9WmXb+gxDq5jIcyCvwWFJESEV/dI5Uaax0hbCkuAXdatSl1JCG0mmX02ycFtKk6OZc2tqqHUfFtrF2+ZT1/W5r+5Y1E8W2DavFWXXTDIYUQKBLLZInpPsA5OPFbpDWRTv/kkwsbsZCToQQQkIMDQchhBAjaDgIIYQYQcNBCCHECBoOQgghRoQ0qkoqZCMRoamPIhZLMogI0QREwaaxp1J0ghQ9BcgRVLoIH6n4yi+rl4ttEzp2EuV7du+2yOb/vFZsm5OTa5F5PHL6CSnKQxccpi/OZJXpxl6KoNJtTxdBZ9omVMQ4Iy3FlKR1ExkRfJRfvpAWRNdWKgQEABE2eXKkuZGipwB5LeiOzcxsaxGmaxtVEdue1GwvwmaNlKoYYxfbSkF6uohH6fyki8CyCxFxuu05NGMvRVDptidF0EnnqPJIu8M7DkIIIUbQcBBCCDGChoMQQogRNByEEEKMCKlzXEJKd+CR/X3iq/xRBs5QXSoLrdNc6FujmuyM1+jmFPJBZOyyOrsBYM/e93RbtCDVAQBkZ5muBoOks26IdakqbEJyhELd2At9j/+/JWLb4XfeKCsShE7hgM1ms6wpqeaFbh6l9CS6OhbS2s0r0NTj0Dh5xXQwmnoc0rDr1pgz2noa0qXvqCC01ZGlcaRLDu9ITQSOdKzofM361EjWH+Tqxl7ovOrVD4htf//uZVmRIPU6H3jHQQghxAgaDkIIIUbQcBBCCDGChoMQQogRNByEEEKMCLtCTrqIJgkpWsAk7UVZxBroIiykojUmAT66Ykm6oixiygRNWylywyT6KL9AbmuPCr4wli7CRlJDFz11saccyc13w5HvH10jzbtuD6RoK10KH49wrJTF+tfNo3Qcmqx/l6ZYkrQfgNnxJkWeSdFsOk7myhFRgeljzulhVcSlKYAl7Z8uekpXtKu07UzgHQchhBAjaDgIIYQYQcNBCCHECBoOQgghRoTUOR4REZwzXOcoltA5zyTnsc6xrXMUS2ITZ7wJOp+url/Juad1lAqduDVpLSTHWpRBfRRAnhObwZzqHNxywIO/MJxTjkRF2oJa2zpHsUl9GJM0MzpHsXRo6Wp6mAy71FR3XOmO79x8q8M6ziWf3qSgGl2KE2nspVQvgDw+gDwnuvofEjrntrQf0powcfwHC+84CCGEGEHDQQghxAgaDkIIIUbQcBBCCDEiJM5xrwMnLy8vqPYmb/+aOMelN5qLIxyc47r9kxxlbo1TTdpvnXNc6sPU4SzprNNNwiRQIHDfvGtM98Z9KPDqkpV1Mqj2Oueo7AgNvgaL8TyGgXNc5/yX5PkGQQX5Gue41IfO2axzeBca6CahG4tgnePedVaWx0BIDEdWVhYAYPIrL4Vi8+RPSFZWFipUqBBqNQCcW/9NGtYLsSbkz0RZHgM2FYJLMY/Hg/379yM+Pt4oLI0QU5RSyMrKQs2aNRFhkgitHOH6JxeS8jgGQmI4CCGEXLyExyUYIYSQiwYaDkIIIUbQcBBCCDGChoMQQogRNByEEEKMoOEghBBiRMjSqufm5iI/Pz9Umyd/IhwOB1wuV6jV8IPrn1xIyvoYCInhyM3NRf369XHw4MFQbJ78yahevToyMjLCxnhw/ZMLTVkfAyExHPn5+Th48CB2ZOxBQkLCmfxCZ/7z5bhRUOc+K28+G3Xus6+99xv4kt4UlakiMu+bjmf6OLdNP1mR36mzEu9vA3/nzfXjOduBn8zv92fkXl086myfytvu3D76fqfO9KuKtPXpoqw6BbbznP3gUUXHTFn3S3nHKKAPVXT8Nd8VnR/vmCtl/ayKl4sydTa/j/IUmUTvZ3Xus7etkr4H8nJO44V/DUJ+fn7YGA7v+v915x7ExyecWw8oMl9+86nO5Ik6O5+es/PlUYAH3nkuuiYC+hD69VtnvnE/194N5duWt61bKXg8Xn3O/O39vdv7O6V8ucncRdq41dnfeM7tg9uj4Pac/Xz2O6UAt+dse+Dc954z/XpwJveZ23NmvZz5Xvn23yc/q4c6+1uvTHnO7I/H49XtbL8e/88428Yn9+6rx3OuX7eC8njl3s8KHuU59/nMgJ393bnPKNpvkbbez8rjATzuM+vY4z47Oe5znz3uc9+7A9sWaaM8QEEuDm5+t0yPgZBWAExISChzwxEo8zv5oWh/57YpySwn2LMyT5E2pTEcCkUOct9BWfQAL/KdVw/fgX5+hqPoicjfEBQZ20DjELjNgP+jiI4lGYjSGw6dYfCe7Ur4PkyJT0hAQjGG49zcFWM4fPOsNxKSTDIcRfvwnui92yhqODxBGA7vZ5/h8JwzHG6lNxy+Nh6r4fDKdIbD41GIOCuPUOcMR6DM29YWYCz8PwO2Im1sPpnH9xnuc79DEcOBIgbgrKU98/8in9WZwYbtrBEJ/AyL4fAUMRbK33DY3HIb2xmZ8rACICGEkBBDw0EIIcQIGg5CCCFG0HAQQggxIqTO8ZMnz1amKkPnOAJkfg5eFO3v3Db9ZEV+JznHi/6OUVVFxi7QyV30sypeLsrKKqoqN1tce+FA1smTJTu2VQnOcShLH4yquniiqs5EUHn/X05RVe6yf18oZKVj4+Li0LB+3VBsnvzJiIuL8xmocMC7/i9pwPVPLgxlfQyExHDYbDacOnUKe/fuRUJCQihUuOg4efIk6tSpwzEzxDtu4VRpj+u/dPAYKB3lcQyExXscJHg4Zn8cOJelg+MWeugcJ4QQYgQNByGEECNCYjicTidGjRoFp9MZis1flHDMSkc4jls46nQxwHErHeUxbjYVTuEmhBBCwh4+qiKEEGIEDQchhBAjaDgIIYQYQcNBCCHECBoOQgghRpSb4Zg0aRKSk5PhcrnQtm1b/PDDD8W2nzNnDpo0aQKXy4XmzZvjk08+KS/VwhaTMZs6dSpsNpvfv3ApjXoh+frrr9GrVy/UrFkTNpsNCxYsKPE3K1aswBVXXAGn04lGjRph6tSpZa4X13/p4DFgRqjWf7kYjlmzZuGhhx7CqFGj8NNPP6FFixbo1q0bDh8+LLb/9ttvkZaWhjvuuAPr1q3DzTffjJtvvhm//PJLeagXlpiOGXAm9cKBAwd8/3bv3n0BNQ4PTp8+jRYtWmDSpElBtc/IyECPHj3QuXNn/Pzzzxg2bBjuvPNOLF26tMx04vovHTwGzAnZ+lflwFVXXaXuu+8+399ut1vVrFlTPffcc2L7vn37qh49evjJ2rZtq9LT08tDvbDEdMymTJmiKlSocIG0uzgAoObPn19sm0cffVSlpKT4yfr166e6detWZnpw/ZcOHgPnx4Vc/2V+x5Gfn4+1a9eia9euPllERAS6du2K1atXi79ZvXq1X3sA6Natm7b9H43SjBkAnDp1CvXq1UOdOnVw0003YdOmTRdC3Yua8l5rXP+lg8fAhaGs1lqZG44jR47A7XajWrVqfvJq1arh4MGD4m8OHjxo1P6PRmnG7NJLL8U777yDhQsXYvr06fB4PGjfvj327dt3IVS+aNGttZMnTyInJ+e8++f6Lx08Bi4MZbX+Q5pWnZSedu3aoV27dr6/27dvj6ZNm+KNN97AM888E0LNCLkw8BgIHWV+x1GlShVERkbi0KFDfvJDhw6hevXq4m+qV69u1P6PRmnGLBC73Y5WrVph+/bt5aHiHwbdWktISEB0dPR598/1Xzp4DFwYymr9l7nhcDgcaN26Nb744gufzOPx4IsvvvC7OihKu3bt/NoDwLJly7Tt/2iUZswCcbvd2LhxI2rUqFFeav4hKO+1xvVfOngMXBjKbK2Zeu6D4YMPPlBOp1NNnTpVbd68WQ0dOlRVrFhRHTx4UCml1IABA9Tjjz/ua79q1SoVFRWlXnjhBbVlyxY1atQoZbfb1caNG8tDvbDEdMxGjx6tli5dqnbs2KHWrl2rbrvtNuVyudSmTZtCtQshISsrS61bt06tW7dOAVAvvviiWrdundq9e7dSSqnHH39cDRgwwNd+586dKiYmRg0fPlxt2bJFTZo0SUVGRqolS5aUmU5c/6WDx4A5oVr/5WI4lFLqlVdeUXXr1lUOh0NdddVV6rvvvvN9l5qaqgYNGuTXfvbs2eqSSy5RDodDpaSkqI8//ri8VAtbTMZs2LBhvrbVqlVT3bt3Vz/99FMItA4ty5cvVwAs/7xjNWjQIJWammr5TcuWLZXD4VANGjRQU6ZMKXO9uP5LB48BM0K1/lmPgxBCiBHMVUUIIcQIGg5CCCFG0HAQQggxgoaDEEKIETQchBBCjKDhIIQQYgQNByGEECNoOAghhBhBw0EIIcQIGg5CCCFG0HAQQggx4v8Bq5T5j+w8diEAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "visualize_integrated_gradients(test_dataset[6], model_clean, \"Clean Model on Clean 4\")\n", "visualize_integrated_gradients(tainted_test_dataset[6], model_clean, \"Clean Model on Tainted 4\")\n", @@ -1752,7 +1489,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1773,90 +1510,9 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAadUlEQVR4nO2dfbCVVRWHNyAgIhIfGibgRyAqICIC8iVoIIKSAVOWlahZ6agzUpSpNU1WjjWZqTmZg5lChWIiYAqiSCIgqCBeFVKQwK8AxRQVBD/6722v53iPlwtX7+U+z1/7N/tw3vece97tdq+1fqvBhx9++GESERGRek3DT/sGRERE5NPHDYGIiIi4IRARERE3BCIiIpLcEIiIiEhyQyAiIiLJDYGIiIgkNwQiIiKSUtqjqi9s0KBBTd6H7GJqwm/qggsuCPq5554L+ogjjgj6scceK8ZDhw4Nc3Pnzg26T58+QS9atCjoNm3aBH3wwQcH/eKLL37k+KPue926dUGvX78+6GnTpgU9YMCAoN9///1i/NZbb6VyvPHGG0G3atUq6M2bNwd9yCGHBH300UcXY34n++yzT9Bt27YN+he/+EXZe6surgV1i5pYCy6++OKg+Zt4/PHHg86fmRNOOCHM/eUvfwm6ffv2QXOdOeqoo4Lea6+9gv7c5z5XjP/73/+GuUcffTToww8/POjFixcHPWLEiKC3bt0adEVFRTE+7LDDwlyLFi2Cfuedd1I5GjaM/3/Ov9vbb79djPms77///kE//PDDQc+ePbvstYt7qNKrREREZLfGDYGIiIi4IRAREZEdyCEQ6d69e9AbN24MmvHy4cOHF2PGsBgrz2NxKaXUrFmzoD/72c8GvW3btqA7duxYjF966aUwd/XVVwd9xhlnlL0WcyH23HPPoPO8gf79+4e5//znP2V1586dg165cmXZe8njp4wptm7dOmjmTojUFL/+9a+DHj16dNBNmzYNOs93Wbp0aZg788wzK31tSimtXbs26JYtWwbN2Hz+HLz77rth7qCDDgq6W7duQXNdYc4A163Vq1cX4wMPPLDsezEXgnH/du3aBc38pA4dOhTjhQsXln1t3759U3XwhEBERETcEIiIiIgbAhEREUnmEMgOMGXKlKBZn8/Y34YNG4oxa3I/+OCDoBk7p77vvvuCHjNmTNDvvfdeZbcd6pJTKs1nYIyyS5cuQdMrIP+cL7/8cphjngXj+sxvYH4C46N53fTTTz8d5hg7HTZsWBL5JGAeDvNbWCef/475fNEHZNWqVUG/+uqrQdPHgHH+/HlmXJ75QTfeeGPQ3/nOd8pe+7XXXgu6cePGxTj3XUmp1FeA3ikrVqwIetOmTUHvvffeQec+BPxcvM/t27en6uAJgYiIiLghEBERETcEIiIiklJq8GEVja71L69b1IR/+e9///ugP/OZzwQ9f/78oJcvX16Mjz/++DBHr/N+/foFndf3plQai2csMK8BZg008w/IHnvEVJpjjjkmaHoFvPnmm8WYz8W+++4bNOuDmzdvHjS9G/j6PFbImCLzF5iXMWPGjFQTuBbULWpiLbj00kuDZp7NvHnzgmZuTTnob8Icgfz5Syml3r17B53nDDF/iH1K2BeBcf977703aPY+yPuisG/CKaecEjTXtLxPSUopLVmyJGj2aNiyZUsx5jrCfCLOT5o0KVUFTwhERETEDYGIiIhYdig7AG14Wb7HI7P99tuvGNO2k2Uxzz//fNAMR9Dmk0eS//znP4sxbTtpKcrPwSNJzvOY8K677irGbOvM9sa33XZb0F27dg2apUcMV+TzY8eODXN5S9mUSsMwIjUFy2cHDhwYNI+s8xLkJk2ahDmGAGhTzpAdy52XLVsWdL4O5etCStHiPKXSNuxsYczyPq5L+bV431yjGA4cMmRI0AyDzpkzJ+g8vMH2xrSO5lpcVTwhEBERETcEIiIi4oZAREREkjkENcr48eODvvzyy4N+4okngh40aFBN39JOwbKZvAwmpVI74T/96U/FmPExxtPatGkTNK04GfujTW9uJ8zynTyXIaXSnICJEycG3bNnz6BZSpi3VGV71cGDBwedx05TSum3v/1t0N/73veCppVxbvlMi1fmcIwcOTKJfBLkNroppXT77bcHzee3T58+xZjldMwPmjlzZtDt27cPmmsFLYHzZ45xfVqon3POOUEzN4LllOTQQw8txswH4n1RM8eAZcUsW8xzhNjG+cEHHwy6UaNGld90GTwhEBERETcEIiIi4oZAREREkjkEOwXrab/85S8Hfdlll5V9/RVXXFEzN1ZDMLZeUVERNHMM8jgX6/WfeuqpoGmHy/di/S9te2fNmlWMr7/++jDH2B7rnk888cSg2caU1sZ5G2LGPydMmBA0cx0Y66Pd8COPPBL01772tWL85z//OczRX4H3WR/g7yZ/xlhD/q1vfavse40bNy5o5q2U49Zbby37XrsbrHNn6/NyFtz0HGHbX/oMMB6etxxOqbw3AK2L85h/SqVrAa/FvyPvPc854PrIZ5n5QcwJYv4C//2oUaOKMVu2066d9s9VxRMCERERcUMgIiIibghEREQk7YY5BN26dQuasepdCX3rb7nllrKvv/HGG4Nma83aDlsQsz6fOQWdO3eu9N8yds42pM2aNQuasb62bdsGffbZZxfjZ599Nsz1798/6NwfIaXSeBt9Chg3POuss4ox26Wed955QbP18nXXXRc0W9PSr2HNmjXFuEuXLmGO7VNrqt1xbebcc88Nmi26y8GWsYS/UfLee+8VY/rO7+6w58aqVauCZr1/vjbwWWc+AuPhzOl5/fXXg/7Sl74UdP7fAPYlYY7A9OnTg77wwguDpt8CvWNyf4VnnnkmzPF55eccPnx40PwN8fl+7bXXijFzlxYsWBA0PWGqiicEIiIi4oZARERE3BCIiIhI2k1yCHr06FGMWedNj23GHHcG+tAT+tyzl0Fdg73Dv/jFLwadx1RTirFA1hrzu5k/f37Q9CtnLJD1xHmOAnuas0acHuH3339/0Ox9wPyF/HPRZ53X+uUvfxk0PRLeeOONoJmHkXsosNcF44asc64P5M8+Yd4K+0hMmzYtaMZ8c2+Lj+Lvf/97MZ48eXLZ1+5u0GeAOQWMl+fP77p168IcfQX4d2M/Al575cqVQb/wwgvFmD4gzNnJ4/IpxX4BKaX03HPPBf3jH/846JtuuqkY0xuFHhm89r///e+g+Z3RR+Okk04qxg888ECYowfCokWLUnXwhEBERETcEIiIiIgbAhEREUm7SQ7B+PHjizE9tY899thdeq3jjz++GF900UVlX8t8BcbB6xpdu3YNesmSJUHnHv8ppXTJJZcUY8ZjX3nllaBZm8w4Y4cOHYKmz3fu609P8E6dOgVNn4LmzZsHzXsdOXJk0Hm98Kmnnlr2Ptl/4O677670vlNK6bjjjqt0np+D3z/7rdcHfvSjHwXdq1evYswY7jXXXFP2vZhDIJXDWDvj3fT6+PznP1+M6TOQ+5WklNKTTz4Z9MCBA4Pm2sH8hTyHiP096NUxYsSIoJmf0K9fv6BvvvnmoHPfEPqVbNu2LehvfOMbQbPHCtcOfqe5B8LChQvL3vdpp52WqoMnBCIiIuKGQERERNwQiIiISKqjOQTsVzB69OhKX3vbbbft0mvntaD0xWYMnXXOdR32HSenn3560HmckT7f7FN+0EEHBc3XU5988slBn3POOcU4z11IKaUmTZoEzRwCzjOngB4JY8eOLcaMf9LDYN68eUGzFpme41OmTAk673fBngy8T/4e6wOs3f7hD39YjJn78XG0bNmy7Dx7H9x111079P67EwcccEDQq1evDpqx+dx7nx4j9AFhrJ3z3bt3D5o+Bbm3x/vvvx/mli1bFnSec5JSSgMGDAiaf3PmqG3YsKEY77XXXpXeR0opzZw5M2g+r+eff37Z1+e+I1yLeW368VQVTwhERETEDYGIiIjUkZABj3RpR5kfnW7fvj3M7eq2pHnIgMe/vBZLQeo6LGtbu3Zt0DwuX7p0aTGmnTC/Ox7j8xgwtyNNqfS4PD9O+93vfhfmGEKgXenWrVuDZqkSy57y47n169eHOV6bLU7z8quUUrrhhhvKXjs/xuZzQKvo/Puur+RHpR93bMrfJFtTk9mzZwdNW/T6BC19GQLkWpGH1mj5Pm7cuKDvuOOOoFnaS8tfluDlawttkXv37h00j+1Z0sgSSIan89Jfhq8YjmB55EMPPRQ0Szn5fnlpNsuuGXIdNWpUqg6eEIiIiIgbAhEREXFDICIiIqmO5BDQcvTb3/52pa+dNGlS0I899thOXZtxxrzcZuPGjWFuwoQJO3Wt2g5jeyzpYTwuL/FhCQ7LkhgX/Mc//hE0Wxbn5XgpxVIkxvWbNWsWNEsFGzaM++K+ffsGzVajeQkV8w8Yy2PcmfkILVq0CJp2p61bty7Gbdu2DXMdO3YMetWqVUmqDq3FmQND+LzXZ1jS+a9//StolsXlFt5nn312mOPzmdsBp1Qax2fZ+ebNm4POn0nm2dAinTbnzG1iCeQf/vCHoPOWx61atQpzLFnkGrj33nsHPXHixKAvvfTSoLds2VKMmV9AC/Tq2uR7QiAiIiJuCERERMQNgYiIiKRamkPAeMgZZ5xR5X972WWX7dJ7oZ1kHhvLbSvrA8wZyFtBp1Ram5zH2nP/hpRKW4Wy3fFXvvKVoNlq+tprrw06zwO48847wxw9Dq688sqgb7rppqDXrFlTVue2yfSaoIUrcx/oFUBPBNqy5r+xQYMGhTnmUdC+VMrDWPXH8cc//rGG7qTuwdp/xs9pGZ+v6XxG6GdC++AjjzwyaOYF0E44zxFibhJ9BvhMMaeHzzfn8+eV3ih87aOPPho07435amzVnOe40NOAuXK0eq9qfpsnBCIiIuKGQERERNwQiIiISKqlOQSTJ08OumnTplX+t7m3dEqlcW/Gl1mHmtfLppTScccdV+m1+NrdnaFDhwZ9+OGHB83Woh06dCjGjJcxjsjeBT169Aia3tz0oshzEuhf/pOf/CToTZs2lb02P8d5550XdF6Pzv4CjIey1Svj/LNmzQqasdjca2Dq1KlhjjFH+smL1BRcV5kL89Of/jToJ554ohi3a9cuzNEHhHF75mqtXLmy7L3kzz9r/+nVweeNngbsXcBeJPm90HeAOVX5evhR137xxReD/uCDD4LOv+NOnTqFOfq2sD9EVfGEQERERNwQiIiIiBsCERERSbUkh4CxlUMOOSToBg0aVPm96O9Ovv/975edZz97xnGqe1+7A2+//XbQ7Mn96quvBp37FDDWzl71rNnNPQxSKvUlWL58edB5z3R6pc+fPz/oQw89NOi8P0VKpX3K2fvgzTffLMa/+tWvwhxrppnPwDro3NMgpdI8gDzHhd8v8xPsZSCfFPT8Zw8Pxs8rKiqKMZ9Hem+wDwLzE9jTgzkGuY8/85yYL0QPA65T/O8J89vydYjrDvOF+OwzV4Kfm14tef8C9o7gd8Q+CVXFEwIRERFxQyAiIiJuCERERCTVkhyCF154Iegrrrgi6H333Tfoxx9/vNL32mOP+JFYQ/5xfOELXwiasbKcE044YYfeu67DeBvj/Izt5T0CvvnNb5Z9Lb2358yZEzTzF9jvIq9zpmc4+60vXrw4aPqAjxkzJmj+pvK4Pr3QmVfCPgqM7fH39cADDwQ9duzYYkwvB+Y6yK6FORuM+dZnmIdDb4+5c+dW+m8HDx4cNP1Nfv7znwfN9Z89KFi/n3sPsJfI7Nmzgz733HODpkfCb37zm6DZR+GrX/1qMWZcn78XriP8fY0cOTJo+u/kOULMGeB/t6666qqgzzzzzFQVPCEQERERNwQiIiLihkBERERSLckhINdff/0ue69p06bt0Ovpi03yXgjnn39+te6prpLX36eU0vr164NmTKxr167FePr06WFu2LBhQbOnBOuF2Yuecce8/8DBBx8c5ugxzr7l/Jsz1rdixYqgn3zyyWLMWCo/B/sNMBcir89OqTRemudDcO6oo44Kurq1x/WFbt26Bd27d++yr2dfFH0e/g97BDC/qHXr1kHnnhlLly4Nc8wXog8N82zWrVsXNH1s8muz3wzzF9jbhjDXac899ww6713Cz8E1jrlM9Djg+sl1a/v27cV4y5YtYY5rc3X7mnhCICIiIm4IREREpJaGDD5JaC9J8mOalFK6/PLLi3HeBrc+wFbQLNdjGeLf/va3YszjbB6t33vvvUHzWJ/HgizByy1K99tvvzA3Y8aMoHNL5ZRKrVQZMuCxf6NGjYoxywxff/31oHO70ZRKQ1g9e/YMOrdgTinanfLImt//kCFDklQOj7lZusVjb6mcPn36BH3//fcHzd9qbutLi17aw9NumCWNbDGeP48pxVAPj+1zW+OUSp9PWqQvXLgwaIYM8pJHhvS4HrJcvmXLlkHTQr19+/ZB56FQrlm0Mee1q4onBCIiIuKGQERERNwQiIiISDKHIN1xxx1l56dOnRr0U089VZO3U6uZOHFi0Cx7YwvU3BaUVqYsi8ktej8Kxh1Z7peXAjIHgHkgLCO8+uqrg2a5D1st5/kPbL26evXqoBkHZIyS3wPj2nnckXHCk046KWitjMvDGC3LU6XqsCSTJXTMx8jbnXOdYB7Nyy+/HDSfP647LEvMc4RoJ8wcH5ae8tos5+MzmL9+4MCBYW7mzJlB07591qxZQbMscc2aNUHna9zo0aPDHHOZ+vXrl6qDJwQiIiLihkBERETcEIiIiEiqhzkEjCMyfkWYQ1CfoXdA//79g6Y3QF4r26VLlzDH2uJ33303aPpD0MqYMcsmTZoUY9abs96X12bOwYIFC4Jm7XGez3DkkUeGOdqP8r3Z6puaOQk/+MEPivFf//rXMJe3fE4ppcaNGyeRTwJ6fWzbti1oPnMNG/7//z35fE6ePDlo5tWceOKJQdNqnC3D82eOHgdsE8x2xvfcc0/Qxx57bNB8XvN7yT9jSqW+LcwP4udgntTWrVuDzr0fmOtAu+dJkyYFnftAlMMTAhEREXFDICIiIm4IREREJNXDHIJevXoFTf9p1rQyxlSfYd02W3CyH8HRRx9djOkhzrg826Xye+e16QeRvx9rh9lHge/FWF337t3LXiv3Y2AeBWOprLnO2xmnVJrTwu/phhtuKMaMhzJng3kYsnNcd911n/Yt1Fr4W1y0aFHQzBnKvT2GDx8e5k4++eSg6dNPb48WLVoEzZr7xYsXF2PmHvG9W7VqVfZabFf+7LPPBv3d7363GLMd/NNPP132WszDYH4C1468bTRzIdgS+pJLLknVwRMCERERcUMgIiIibghEREQk1cMcgo+DPasZF6/P9OjRI2j2gTj99NOD3rhxYzGmr8Ds2bODpg/4K6+8EjQ9ENjL4K233irGjG+yvpf1wJs3bw6a/ueMz51yyinFmN8JfQiWLVsWdOfOnYNmHgbjih06dKj0Pg877LCgKyoqkuw66DFx3333fUp3UvtYuHBh0MwJyvOHUkpp5cqVxZjPPp9XrhV8/uhTwP4EuT/HxRdfXOl9pJTSqlWrgh41alTQef+AlEo9EX72s58VY+Y28Dtgjg+9GrjGca3IfQ2Yn8B14/bbby9735XhCYGIiIi4IRARERE3BCIiIpLMISiBfvHyf+bMmRM06/uff/75oPP6/k6dOoU5xryGDBkS9N133x0064EffvjhoAcPHlyMGcdnHJA90Bs1ahQ0vQSeeeaZoA888MBiTE/xU089NWh+R7mvQEopXXjhhUEz5yD3xWAMkh7uude57Dz8Hcj/of8GfUOWLFkSdP68f5wPCL93+vAzp+DBBx8M+qKLLirGzHWgRwnzFfJnO6WU5s2bFzRzJcaNG1eMuc7wczzyyCNBX3nllUHPmjUraK55+b0z74J5FOwXUVU8IRARERE3BCIiIuKGQERERJI5BCXcfPPNn/Yt1FpGjBgRdO4zkFJpbeyECROKMf0cGLtj7T97TDAWT6/uqVOnFuPly5eXvRZr/1mbTD/zBg0aBJ33MWfuQ+43nlKpB8IxxxwTND937juQUkpz584txvRlZ14G/x6ycwwbNizoa6+99lO6k9rH2rVrg27SpEnQrHvfvn17Mc59AlIq9RVgfT7j/rnnSEqlniT5c8CcAPYlmT59etDjx48P+utf/3rQzKPasGFDMebvZc2aNUGPHDky6GnTpgXdrFmzoJmvkPc5adeuXaX3kVJp34Sq4gmBiIiIuCEQERGRehgymDFjRtB77FHvvoJqw/acPJbiMf8999xTjHmkxWNAHq+NGTMmaB6v8e+Y3xvvg5a/tCtlm1GWQfEoMG87zLIkljQy3MB7IywlzMMXPErltVh6JBGWwuXhmJRKy+EuuOCCGr+nugqPrNnumG28c33EEUeEOZYGsnyZx/5Dhw4NmiHBPGRw6623hjmG3W655ZagGZpk+JHhxLxV+pQpU8JcXgqdUmkpYJs2bYJmKITfQ35vvXr1CnP8vll6XVU8IRARERE3BCIiIuKGQERERFJKDT7MvVHLvRCxUKndVPHPukMwxsp4W7du3YLOS3xYvrNixYqgGU9jvkLTpk2DZqvRffbZpxjvv//+YY5lTvy3BxxwQNBszzpgwICg81JC2qgyTshcCcb6+vbtG/SmTZsqfT/GThkfZcninXfemWoC14K6RU2sBSy3ZV4An7E8/+Whhx4Kc1xH+F6LFy8O+p133gmauTR563Q+b3y+mH/QtWvXoFlK3bNnz6DzfCKWCTIXid9J8+bNg+aayPU2X3fy3IWUUmrYMP6/Pe3Wr7nmmlQVPCEQERERNwQiIiLihkBERERSPfQhkOozduzYoNn6l1a6eeydr2XOAGN7jP2x3SpbjeaxvNNOOy3MsaXwWWedVXaeOQes/8/bEDdu3DjMMfeB7ZA7d+4cNK1UGcPM/RuuuuqqMDdo0KCg2RJapKag7wBzZVivnz/vbOvLHJ2KioqgaW1M6/EFCxYE3bFjx2LMfCLW53Oe6w7zovJ1JqVo2UyvlX79+gXN55O5D/QW4PvlXi0vvfRSmGNrZfq4VBVPCERERMQNgYiIiLghEBERkbQDPgQiIiKy++IJgYiIiLghEBERETcEIiIiktwQiIiISHJDICIiIskNgYiIiCQ3BCIiIpLcEIiIiEhyQyAiIiIppf8B8WyHX16lX3QAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -1901,7 +1557,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1957,13 +1613,14 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from dlmbl_unet import UNet\n", "import torch.optim as optim\n", "import torch\n", + "import torch.nn.functional as F\n", "\n", "# Some hyper-parameters:\n", "n_epochs = 5\n", @@ -1976,6 +1633,7 @@ "# Model:\n", "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", "unet_model = unet_model.to(device)\n", + "\n", "# Loss function:\n", "criterion = F.mse_loss #mse_loss\n", "\n", @@ -2001,21 +1659,9 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "938it [00:19, 48.99it/s] \n", - "938it [00:18, 49.39it/s] \n", - "938it [00:19, 49.23it/s] \n", - "938it [00:19, 49.10it/s] \n", - "938it [00:19, 49.15it/s] \n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Training loop:\n", "for epoch in range(n_epochs):\n", @@ -2032,30 +1678,9 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'mean squared error loss')" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Loss Visualization\n", "fig = plt.figure()\n", @@ -2077,7 +1702,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2091,90 +1716,9 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Displays: ground truth, noisy, and denoised images\n", "def visualize_denoising(model, dataset, index):\n", @@ -2254,7 +1798,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2283,92 +1827,11 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" @@ -2455,21 +1918,9 @@ }, { "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:38<00:00, 48.91it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:38<00:00, 48.67it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.84it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.62it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.60it/s]\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import torch.optim as optim\n", "import torch\n", @@ -2503,90 +1954,9 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAQ2ElEQVR4nO3dW1DVVf8G8KWoiKSQ5gm0FBBFTVMjUJxB1ByVxswRw2rULLNmUrMaqptO3tiUdtE02ZQ5TVZTaqVYWTaoqeMJ7KBCqICclADJMgMr9X/1/816nv3uzX5J3tys53O1nlnE3rAZV791+K52V65cuWJERMRZ7f/tNyAiIv8uDQQiIo7TQCAi4jgNBCIijtNAICLiOA0EIiKO00AgIuI4DQQiIo7rEOwXtmvXrjXfh1xlrXFOcOXKlZBjY2Mhf/nll37/28GDB0M+ceIE5A4d8E/xp59+gjxu3DjIkZGRft/L5s2boW/IkCGQCwsLIcfHx0MeP3485KqqKsgXL1702uXl5dB3+vRpyPxzR0REQK6oqIB83XXX+X1vv/zyC/Tt378fMv9OcnNzTWvQvwWhJZh/C/REICLiOA0EIiKO00AgIuK4oNcIRHh++8yZMwHzoEGDvHZSUhL0PfTQQ5DXr18PecCAAZD//vtvyH/++aff10pISIC+MWPGQOafo2fPnpB5TaCpqQny9ddf7/dro6KiAv639fX1kFNTUyHzGsPnn3/utRMTE6Fv+PDhkHl9QSRYeiIQEXGcBgIREcdpIBARcZzWCJrB+9ntedp+/fpBH8/vtjVdunSBfPLkSciLFi2CXFxc7LW3bt0KfcePH4f8xx9/QK6pqYFcWVkJOTMzE3JZWZnXvvXWW6EvLy8Pcl1dHeSUlBTI586dg3z58mXI9jmDw4cPQ9+lS5cg2+sJxhjTqVMnyHx+oqioCPLkyZO99s6dO6FvwoQJkH/77Tcj0hJ6IhARcZwGAhERx2kgEBFxnPNrBH379oX84osvQrb3pxtjTE5OjtfmffNtHdcSmjhxIuSDBw9Ctue/58+fD30bNmyAzHviw8LCIPPcOc/NNzQ0eO17770X+rjeD59R4HWg5ORkyNnZ2ZCffvppr93Y2Ah9N998M2Q+s8DnCt577z3IvF5h12SaM2cO9J06dQpy9+7djUhL6IlARMRxGghERBzn3NQQb9/bsWMHZD7Gz9auXeu1W6PU87WMSxjwVJC9hdMYnDp6//33A34ve2rHGN/pmujoaMhcCtnetslbUX/99VfIXHaaS1xzyQl7Kohfe9iwYdDH20WPHj0KuVu3bpCHDh0K+dixY5DtqcvS0lLo4zIbcXFxRqQl9EQgIuI4DQQiIo7TQCAi4jjn1gh4eyivCXB5gZkzZ0Lm+WaX8Pz31KlTIa9atQry999/77V5ayP/Hu1yFMb4zr3HxMRAPnv2LGR7yyeXhuay1LyGwFdA8pbOSZMmQbbXL6qrq00gXEKia9eukNPS0iB/9dVXkO11KC4hMXfuXMivvvoq5AcffDDgexP5f3oiEBFxnAYCERHHaSAQEXFcm18jmDJlCuTZs2dD5jWBadOmQT5w4ECrvK9QxNdN8lz69OnTIX/zzTdeOzY2Fvq4hDWXuOY1AS7B3L9/f8h2yQq+mpKvuWzfHv//JysrC3JJSQnkbdu2Qbb37/N5CH7td955B/LIkSMh83oFl7HOyMjw2nv27IE+PnPA5bdFgqUnAhERx2kgEBFxnAYCERHHtbk1Ai4rvWbNGsg33ngj5Lvvvhuy1gT84/32HTt2hMzXSdrnDMLDw6GP1wDsMwfG+J4r4BLMBQUFkG+//XavzecduBR0ZGQk5OXLl0Pmv5HOnTtDtmsq8Wvl5uZC5rLUfJ5i3759kLkct712wu+jtrYWMp9REAmWnghERByngUBExHEaCEREHNfm1gjWrVsHma8lfOmllyBv2rSptd9Sm8FXU3777beQe/ToAdm+r4DvD+BzBbxmwHV1uKYP1/W3aw8tWLAg4Pfmz5z37vPefjZ27Fiv3adPH+jjdRO+72LLli2QeV1lxYoVfjNfoXnx4kXIFRUVgd62iF96IhARcZwGAhERx2kgEBFxXJtYI7DrCdnzt8YY09TUBPndd9/9n7yntqiwsBAy13HicwanTp3y2ry+wPft8n28nBsbGyHz3Lz9Wrw3n2sLHTp0CDL/zfBrc60i+5xBeXk59BUVFUHm2kJ33XUXZF7r4DpHqampXpvPyHCdo9OnTxuRltATgYiI4zQQiIg4TgOBiIjjQnKNgOu7rF271mtzvZVly5ZBtu+bbYmwsDCv3alTJ+jjueS//vrrH73WtYbXW/je4fr6esgjRozw2ocPH4a+W265BfKuXbsC9vPveuDAgZBHjRrltfnuAr5zguv/8LkB/tz4c7XPR/AdDb169YLM8/Zca4jXVXgdwP5Z7PuLjfG9+4DPFYgES08EIiKO00AgIuK4kJwaysnJgWyXK/juu++g74MPPvhHr/Xyyy9DTklJ8drjx4+HPt46uHjxYsh81WCoWb16NeRHH30U8t69eyHbWyO5hLJdEsIYY+bOnQuZp2d46ypPudjfj8s8xMXFBfxe6enpkPPz8yEnJCRAtks9HDlyBPqys7Mh87TUmTNnIHOJCd5WGx8f77Wrqqqgz56mNMZ3qkgkWHoiEBFxnAYCERHHaSAQEXFcSK4RZGVl+e3jeXmei27O7t27Iaelpfn9Wi6tzFsJFy5cCDnU1wjuvPNOyD///DPk0aNHQ7a36vL1j1xmmufx+cpQ/hz5+9mlGTIyMqDvxx9/hMzbXvlzGTZsGGT+HO0SFlFRUQHfJ/fzvH5NTQ1ke8utMcYMHTrUay9ZsgT6eKspX/c5b948IxIMPRGIiDhOA4GIiOM0EIiIOC4k1wj4qP0/wecEAq0JGIMlATIzM6Fv6dKlkOfPnw/59ddfh1xQUBD0+7wWREdHQ75w4QJk3vs/ZMgQr93Q0AB9PBdul5E2xpjBgwdD5tIhvP/eLjvCZah5TSAxMREyl2bgtZ+PPvoIsl3+mdcy7J/ZGGP69esHmctO81oHv3d7HYD/Nvl7N3fFpog/eiIQEXGcBgIREcdpIBARcVxIrBEMGDAA8g033AC5rKzMa/Neasb7uO3aQf8Jl0devny539fiNQOea+YcamJiYiDzNY08R23PvfN1kbyewNcu8jqQXU/KGN/fvX0lJJ9R6NKlS8DvxXv/ef3hzTffhPzcc895bS47zdde8ve6fPlywP6bbroJsv33yn/358+fh8xnMUSCpScCERHHaSAQEXGcBgIREceFxBoB783m+i3FxcVem68VZHzlId8pwPP49pqAMYHXIPh6Rd4bzzVvQs1rr70GeerUqZBra2sh23Vy7HUcY4yJjIwM+FqHDh2CzPvvp0+fDtk+d7BmzRro4zUAnofnz23RokWQn332Wcj2PD+freB5e2b/rRrje21mY2MjZHu9g+8q4N8J39EgEiw9EYiIOE4DgYiI4zQQiIg4LiTWCCZPnhywf+PGjVfttbZv3w450Lw+ry9MmTIFMtcW4jneUMN1/rnWENfxt+vk8F299l0FxhhTXV0Nmc8kzJgxAzKvR9TX13vtDh3wz5rPKPA91nz38gsvvAC5d+/ekO16U3w/8ocffgiZz8DwWQz+nW3evBmy/TfD9w/wGhSfkREJlp4IREQcp4FARMRxGghERBwXEmsEzamoqLhq34trD9l17o3BuWveX27PHRvju5891PHP17NnT8h5eXmQ7TUUns+eNm0aZD4XsH79esh1dXWQea//ww8/7LWbqy10//33Q+a9/FVVVZD5PoP4+HivzbWDunfvDplrKvHfE6+NzJo1C7K95pCcnAx9/Hd/6dIlI9ISeiIQEXGcBgIREceFxNTQ0aNHIXMZiZycHK/92WefQR9v2eRrCbnMdHp6OuR58+ZB7t+/v9fmba2rV6+GfPz4cdOW8NRDamoqZL52cdu2bV67c+fO0FdUVAS5tLQUcnh4OGTeZnnu3DnICxcu9NpcNpq3k/L20MWLF0NOSkqCHBERAdmezuH3tW7dOshcOprLdDz55JOQebrHLonCZTfsv0VjjPn999+NSEvoiUBExHEaCEREHKeBQETEce2u8J2A/r7wGrpm8cSJE5Dt7Xw8//vKK69A5rIIvI3x008/hcxlqwN56qmnIB88eBAyz/FyGYWrKciP9b9iz8Mb41vSgNdM8vPzvTZv0eS5cJ7v5nLOvA2TP0e7lPSBAwegj+fOueQE93M5C34v9mvPnj0b+lasWAF50KBBkL/++mvIdqluY3zXsOztplymY8SIEZC5/4knnjCt4Vr6t0CaF8y/BXoiEBFxnAYCERHHaSAQEXFcSK4RvPHGG5DtcgPt2+PYVllZCZn3rzOed+UyCoFKSXMpglWrVkHeunUrZL628GpqjTWClStXQravUfxP2V4D4asp9+3bB9le5zHGmMzMTMh2mWljfK9ltD+nBx54APpOnjwJmT9DLonNnyOfFbBf274i0xjf3zt/5lymg6/N5Pdmf/2oUaOgj0ukDxw4EPKyZctMa7iW/i2Q5mmNQEREmqWBQETEcRoIREQcFxK1htgjjzwC+dixY177+eefhz7en86Z8dz1nDlzIO/ZsyfYt9nmDB8+HHJBQUHAr+/Tp4/X5vMYXA+I1x/sz9QY37l1/hzPnj3rtfm8RklJCeTs7GzIXLeI1yu2bNkC2V7b4asoR44cCfnIkSOQb7vtNsh8bqBbt26Q7TpJGzZsgL7o6GjIKkMtLaUnAhERx2kgEBFxnAYCERHHheQ5Amlea5wjePzxxyH36tULMl9Had9BEBMTA308v81rAB07doTMe/vLysogNzQ0eG2+FyExMREynzXZvXs35KioKMh8zmDBggVee/v27dDH5xvS0tIgZ2RkQF66dCnk++67D7Jdi2jv3r3Qx+cI7rjjDsiPPfaYaQ36tyC06ByBiIg0SwOBiIjjNBCIiDguJM8RyL+D99vzHnqee7dr6fO901zTqampCTLfP1BXVwc5ISEBsn0/NN83UFtbC5nXALi+D9+dYJ9RMAbPKfB6RI8ePSDn5uZC7t27N+Tk5GTIPJ/79ttve+177rkH+vh3wucdWmuNQNoePRGIiDhOA4GIiOM0EIiIOE5rBBI03o/ft29fyDt37oRs73PPysqCvurqash2TR1jjKmpqYGcmpoK2V5/MAbvsea7C/h7zZw5EzKvEXzxxReQZ82aBbmxsdFr79q1C/qqqqog830F4eHhkHmthO+xTk9P99o//PAD9I0ZMwYy35sgEiw9EYiIOE4DgYiI4zQ1JEHjbZkbN26E3LVrV8j21sqPP/4Y+mJjYyFzmWou12xP/RjjO5VkT7GEhYVBH29N3b9/P2SetrK3ohrjWxp606ZNXpuny3jbK0/X8NSQXarbGGMqKiogFxYWem0uKTFu3DjIPK0kEiw9EYiIOE4DgYiI4zQQiIg4TmsEErS33noL8qRJkyDz/LddGnrGjBnQl5SUBHnHjh2QuaQ1l1OIiIiAbF+bGRcXB31cAnvs2LGQuQQ2rxGkpKRAnjhxotcuLy+HviVLlkCOjIyEzGWqP/nkE8h22Wlj8Pdw/vx56LPLfBtjzIQJE4xIS+iJQETEcRoIREQcp4FARMRxWiOQoPHVlFwymcs123P1fE6guLgYMs+ll5SUQOZSDDw3P3r0aK/NJSNKS0shcz+vbfDZgMrKSsjPPPOM17ZLQBjju3bB6xX5+fmQL1y4ADkvLw+yvR7BPwevZfAaAq/LiPijJwIREcdpIBARcZwGAhERx7W7whO9IiLiFD0RiIg4TgOBiIjjNBCIiDhOA4GIiOM0EIiIOE4DgYiI4zQQiIg4TgOBiIjjNBCIiDju/wCH8L7b5W1DrAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, test_dataset, 123*i)" @@ -2594,90 +1964,9 @@ }, { "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAATRUlEQVR4nO2dZ4xVVReGN2JBlDKINEEcpEoR6W1EGI0QBKSJEIxAQKKSEKORaGKM8YeCjSiExGBJUAiQUNQAiqBGKVJUYOggTYoUKYJd+f6db63nOvdekIsO+31+7Tf7eu455x5me9Za+12lzpw5cyYIIYSIlkv+7RMQQgjx76KFQAghIkcLgRBCRI4WAiGEiBwtBEIIETlaCIQQInK0EAghRORoIRBCiMi5NNsPlipVKpfnIc4zudgn2LJlS6dHjhzp9IIFC5z+4YcfknGPHj3c3Jo1a5yuXLmy09ddd53TpUuXdvrw4cNOFxUVJeMuXbq4uVWrVjl94MABp9u1a+f0kSNHnP7111+d3rt3bzKuXr26m2vYsKHTe/bscfq3335z+pJL/P+LrV271ulOnTol47y8PDd39dVXOz1//nynV6xYEXKB/haULLL5W6A3AiGEiBwtBEIIETlaCIQQInKyzhEI0aRJE6enTp3qdEFBgdNXXXXV345DCOHaa691mvHu77//3uly5co5/fPPPzu9ZcuWYo9Vv359p2vUqOH0iRMnnGZcf9u2bU736tUrGe/bt8/NLVq0yOn27ds7/csvvzi9e/dup5lzOHToUDJmfqF8+fJO8x4JkS16IxBCiMjRQiCEEJGjhUAIISJHOQKRNazlLywsdPqrr75y2ta916xZM+2xy5Qp4/QNN9zg9KlTp5w+duyY0zfffHMy7tq1q5ubMWOG061atXL6+uuvd5rXUbVqVadt3J419XbvRAipuY5M+wi4p2HatGnJeMiQIW7u6NGjTh8/fjwIcS7ojUAIISJHC4EQQkSOFgIhhIiciz5HwBhuJt8N1mJbr5cQUv100n0XY+p//PFH2u9ORyZ/l1x4CxFee79+/ZwuW7as05de+v/Hq0KFCm6O9fOMw8+cOdNpevh8+eWXTt92223J2PoOhRDC77//7vQXX3zh9C233OJ0fn6+082aNXPa7gXYvHmzm2vbtm1IB/cs0GPpyiuvdNrmTpYtW+bmbr/99mI/K8TZoDcCIYSIHC0EQggRORd9aIjleX/++afTdevWdXrEiBFO08rg9OnTyZh2AStXrnQ6UyiI4R6eq53PdCyGoXIBQ0H79+93ulKlSk5b++e//vrLzTFUtH37dqcZkmNp5Hfffef0hAkTknHPnj3dHG2kGUJhaIilrpMnT3balpvSOqNWrVpOX3HFFU7TWoOhJRtO4/H4fLz00ktpz1uIbNEbgRBCRI4WAiGEiBwtBEIIETkXfY6AsXPmCGhHwJI8xqJtzJflknfccYfTU6ZMcZp2Ayz55LlZaK3MmPtPP/1U7H97vmCegjYQbPFoW1syls5WlEuXLnWaJZxVqlRxunXr1k5fc801yZi5imrVqjlNm+n169c7zRLibt26OW1LWdlacvbs2U7TVvqyyy5zms/nvHnznO7QoUMybtGihZujxTVLcoXIFr0RCCFE5GghEEKIyNFCIIQQkXPR5who+0sYa2bcmzFcW8v94YcfujnWo48fP97p1atXO83Y9KZNm5xu06ZNsedJu4Hly5eHXLNhwwane/fu7fSOHTucvvzyy5Ox3VMQQgijRo1y+uDBg06zZp4tIZs2ber0yZMnkzFtpJmPIPfee6/TderUcXr69OlOL168OBmzfeejjz7qNO0tiD3vEEJ45513nLbPL++RPY8QUu+JENmiNwIhhIgcLQRCCBE5WgiEECJyLrocQSbbadb6s23hjz/+6DTr3+vXr/+34xBS4+D0z+FeANaB9+3b12kbX+ax6YlEP51c0KVLF6cZt2fNvG2lWK9ePTe3bds2p9ni0eYXeKwQUvMA9rtpWW3bWIaQei/5eVpgM/dhf0c+b+vWrXO6c+fOTr/xxhtOMx/Rv39/p+0+FuZNuOeF90SIbNEbgRBCRI4WAiGEiBwtBEIIETmlzmTZ4zBTq8QLydmcCy9vxYoVTnPfQKbvsn47mfYosF8B/YEY02VOwX4X/W4YW2atfC5aVw4dOtRpeudzn4HNKWzdutXN7dq1y2l68PDYffr0cXrv3r3Fnic9dw4fPuw0/YBmzZrl9MaNG52mR5TtKcB78u677zrduHFjp20vgxBS8xH0E6pRo0YyZv6BbS15XWzneb74L/0tEJnJ5m+B3giEECJytBAIIUTkaCEQQojIKZH7CP5J/PvYsWNOs/adPYrZc9bGrrkvgDkBxnCZIygoKHDaes+H4OvG6ce/cOHCcKFhrDwvL89p9uO1ewO454AePNyvwXxDYWGh07yXNrbOGDbj8vQD4m/MfAzj/tYDin5T3LPAPhGPPPKI06+88kpabXMMjRo1cnN8vjL1tRaiOPRGIIQQkaOFQAghIkcLgRBCRE6JzBH8E9hnmP4t1IzxnjhxIhnT/4Z7EpjLYOya38Vzsz2MGROvVatWuND06NHDafrmPPzww06///77yZhxet4b1ryztwO9iLiHY8aMGcnY9i8OIfU+MxfDfAX7EPPz1v+HPkRjx451esmSJU4/9NBDTjOu/9Zbbzk9ceLEZLxgwQI3N3z4cKd5nUJki54cIYSIHC0EQggROSUyNJQuxGLDKSGklnjaLfshpNo3U7O00IYkGDaqWLGi0wwdMfRDq2VaYFeoUCEZ016A10U77VxgQz0hhDBgwACnp02b5rS9d7z25s2bO81QT/fu3dN+N58BW9Z75MgRN8cyXRveCyE1LEWrcv6O9hlhOGbu3LlOjxs3zml+fsyYMU7bEFcIPqRGS5KnnnrK6WbNmgUhzgW9EQghRORoIRBCiMjRQiCEEJFTInMELD0sXbp0MmaOYODAgU5Xq1bNaVoUZ7KFsFYILOFknJv5BZYp0mqZ323LICdNmuTmGGPnsXJBx44dnW7SpInTzJnYc6K185w5c5ymPcXixYudpgUFbbftd9MKg/Yc+/fvd5o5gMqVKzvNclQbt6dlCUs8e/bs6fSpU6ec/uCDD5zmfbAWE127dnVztEPJZKkuRHHojUAIISJHC4EQQkSOFgIhhIicEpkjYDw8XcvIoqIip7lPgC0Sbb4hhNScg40303aasWYeu0yZMk4z7s14s7UyGDx4sJt74YUXnGYLzlzwzTffOM2a+KpVqzptY/XMHzCezVp+5iP4uzE+PmXKlGRMK2jaSDN3M2jQIKft/o0QUltA2nr9/v37u7nPP//cabbNHDlypNN8vsaPH++0zStt2rTJzXEfB+2177///iBENuiNQAghIkcLgRBCRI4WAiGEiJzzliOg94uNtTOWzM+yvp61++RsWvLNnz/f6dOnTzvNWDP9f7hnwe47YD6BOQBeF8l03fb49JGhX86FoHbt2k7TYpk+TtY6mnsOWOvfoEEDp5lT+Pbbb51mfNzmW06ePOnmuC+AzyOfJ7YBpYW2bdFJa25eh21rGUIIe/fudfrgwYNOt27d2unjx48nY+YuVq5c6bTdcyDE2aA3AiGEiBwtBEIIETlaCIQQInLOOUeQqd7+bOL4Z8utt97qdL9+/ZIx688Za2atP3MC3KPA67LH4z1gfTpzBsw38NyIPTd61PTt29dp+vXnAvoyMcexZcsWp/Pz85NxuXLl3Bz3ftBniXmkQ4cOOU0vIusfNGTIEDdHj3/uYVizZo3TDzzwgNPMK23YsCEZ33TTTW6OfRf47+D55593uk+fPk6zJ4V9pnr37u3m+Czz34UQ2aI3AiGEiBwtBEIIETlaCIQQInLOOUfA2Hk6KlWq5DTrzevVq5d2nvHw+vXrO52uhyzj8PSWpzc9/YOYQ7BeQ4xzMz68bNkyp9lnmDFd7iOwewUYj2/Xrl240LCePlPPZuuVZOPqIYSwa9cupxlr573q1q2b03aPAv97ejZ9/fXXTnfu3NnpiRMnOl2nTh2nmQuyHlLM+zRs2NBpPm9vvvlm2nNjjuuTTz5Jxm3btnVz9Jfivo4RI0YEIbJBbwRCCBE5WgiEECJytBAIIUTknHOOgDHqZ5991mnbe5WxY+YXGIO1/iohpNZis9baxupZf04vIcbt77nnHqdXr17tNOvfbT4iU4/Ypk2bpj0WfWcYc7e19YyZ0/fnQkC/H14/z79ly5bJmL8xvfOPHDniNH83+v/cddddTlvvourVq7u5119/3enNmzc7zXvJPhGM49vn7cknn3Rz3O/AuH3dunWdZj7jo48+cvq9995LxuxvPGzYMKe530GIbNEbgRBCRI4WAiGEiJysQ0N8tX/11Ved5uu4Df+ks2n4O1iyyf+eYQMLrXr52s8t/jzWgw8+6HS68lLaHDB0wrJYlhKy/JStLW0pLMtHafdwIdi2bZvTtEdgqMuWN9Ii+eOPP3aa5aMMsfBesnWltVtgiSbPc+vWrU6PGTPG6dGjRzu9du3aYjVtRNhyc/369U7z+WT7z8LCwmLPjeXFDKGma9kqRDr0RiCEEJGjhUAIISJHC4EQQkROqTPcI18Mw4cPd5qx9h07djhtyx1Z+ki7ZsJYOeOqjEXbOL4tWw0h1XKiWrVqTt99991OM+bLEkl7LbY88u80v5sxXM4zN2JhWSzvEct59+zZU+yxzpXnnnvOabab5PVYaxFaTJQvX95p5phYertz506nmTOw+Zru3bu7OeY2aCNibRxCSC1X7tKli9O29SVzFbTiZskwbUg6derkNJ/P7du3J+PXXnvNzU2aNMnpyZMnO/3yyy+HXMBnUfy3yeZPvN4IhBAicrQQCCFE5GghEEKIyMl6HwHruhmnT2fFwM8yZ8DYOOPHtBzevXt3scfjvgDGgxn/nTNnjtOs+2aOwMa9GfNnXTdr//ndrAtn3N/OMy7Le0Zr7lzANp4nT550uqCgwGlreUBrhUWLFjndqFEjp1nrX7NmTadpBWL3aLA2n78Lz7NBgwZO33jjjU5zX8LKlSuTMfNC/A2Z23jiiSecfuaZZ5zu0KGD0/YZ4t6dadOmOZ2XlxeEOBf0RiCEEJGjhUAIISJHC4EQQkRO1jmCffv2Oc3aVNuWMARv5WvrrkNIjdnSgpg+OoxNcx+CjctyHwBzF6x153czVk1rX5vvoIUwz4vHzpQz4Ly1oWZ9uW1jGUIIzZs3D7nmwIEDTg8ePNjpmTNnOt2iRYtk/Pjjj7u5O++802nWxDPWztg5PX1sG0faRnNfAZ/VVatWOb1u3TqnT5065bRtMcpcDduycp/BjBkznG7fvr3TzKfZfTHLly93c2+//bbTo0aNCkKcC3ojEEKIyNFCIIQQkaOFQAghIifrHAFrs2fPnu00vYis/w99+lnbz30FjA/bWHkIqXFZ2yuBMVn2MmBug70RGAfn5+3xmLvIdF2Z9h2k24fAfEJ+fr7T9P3JBezNwH0QvPcHDx5MxtyHMn/+fKe5/4PeQ/TwobeSbTnK3M2mTZucbtOmjdP8Hdkbgc+j9TVij4mBAwc6zbaYrP3v1atX2nOdNWtWMra5iRBS92YwJyVEtuiNQAghIkcLgRBCRI4WAiGEiJys+xFk8iBnrfZjjz2WjKtUqeLmGMtkbJxxffZLZo7Axnj5WZ43L5fxX2p+l53PdE84nymOz++yMXjuI2Ctu42Rh5CdB/nZwh4AderUcZq/m92Twf0crVq1cnru3LlO0zuJ+Yhly5Y5bWv9bVw9hFRfIuas6F3FPTPMKdi4P/sh0ydr3rx5TjOPwv0gPNfOnTsnY+6R4b8rm5MJIYQJEyaEXKB+BCUL9SMQQgiRES0EQggROVoIhBAicrLOETD2zphtOtjzlb1vGetkj2L6A/FcbI6AcWrCenZePuPDvE4bi+Z5EB6bXkLcw8DrtJ79rC9njDzTd58P7rvvPqdZ+8/rsedQtWpVN8ffgfsCateu7fTChQud7tixo9N2H8vTTz/t5kaPHu30uHHjQjp47+iVZX9H/mZTp051euzYsU5Pnz7daf7bYI8He4/5bBYVFTnNPNGLL74YcoFyBCUL5QiEEEJkRAuBEEJEznkrHz2fNGzY0OlMNta2jeGuXbvcHMMxO3bs+OcnWALIRWiINscbN250mlbY1hqEVs8sH92zZ4/TfN7Kli2b9txsqSqtPmglzjaYLFWl5cTSpUudts8bLdNpIz1o0CCnec+sfXYIqc+rvW/9+/d3cwxD0YaENh7nC4WGShYKDQkhhMiIFgIhhIgcLQRCCBE5/8kcgfjn5CJH0LJlS6cbN27sNGPrNh5u21aGkGrF0KRJE6eXLFniNGPvLN21eSXaUB89etRp5okGDBjg9Nq1a52mBYW1nKCtg7WECCG1vSTvEUun2YLT5j7y8vLcXMWKFZ3+7LPPnOY9PF/ob0HJQjkCIYQQGdFCIIQQkaOFQAghIifrVpVC0HaaduINGjRwulmzZsmY9t60Z2ZLR2vlEUJqS0fuO/j000+TMe2yaQPB2PrOnTudZmvUoUOHOm33KXDPAvMRtN2gBTbj/sOGDXN6+/btyZg25rzfvCdCZIveCIQQInK0EAghRORoIRBCiMjJeh+BEEKIixO9EQghRORoIRBCiMjRQiCEEJGjhUAIISJHC4EQQkSOFgIhhIgcLQRCCBE5WgiEECJytBAIIUTk/A8FKX1vACgLSQAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" @@ -2717,19 +2006,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:38<00:00, 48.63it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.76it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.43it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:39<00:00, 47.59it/s]\n", - " 73%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍ | 1360/1875 [00:28<00:10, 48.00it/s]" - ] - } - ], + "outputs": [], "source": [ "import torch.optim as optim\n", "import torch\n", @@ -2763,90 +2040,9 @@ }, { "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, test_dataset, 123*i)" @@ -2854,90 +2050,9 @@ }, { "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAVOklEQVR4nO2dZ6xVRduGR0VRilIU6SAivRpAQUURT2g2LARIRI2xxKCGgAqiUaMxJoIafhiiRoPEXiAgoAYpUkWqoIAi/YAg56A0Bdv761vfPNc5rNnLzcb3Ze7r19yZvVdjzh7W/TzzzEl///33304IIUS0nPxvX4AQQoh/F00EQggROZoIhBAicjQRCCFE5GgiEEKIyNFEIIQQkaOJQAghIkcTgRBCRE6FXD940kknFfI6xDGmEOsEx48fb/Thw4eN3rRp01GvYceOHaavdevWRpeUlBhdVFRk9MSJE40eNGiQ0Rs3bkzay5YtM33NmjUz+s8//zR6+fLlRp999tlG33bbbUb//PPPSZvPoGLFikZPmDDB6M6dOxvdr18/o5955hmjzzvvvKQ9ZMgQ0zdu3Dij+/fvb3SfPn1cIahQoUKqJnzeWeA4Dv0O+f38bJbvOufcX3/9lfPnTz7Z/p+az+TIkSNG//7775muzX+Goc+Gzl0eeiMQQojI0UQghBCRo4lACCEi56Rci84pRvC/RSFiBI888ojRw4cPN3rkyJFGd+/ePWnPmjXL9NWuXdvoOnXqGE1fmZq+53fffZe0mzZtavpKS0uN7tSpk9F79uwxesmSJanXesoppyTttm3bmr5atWoZzbjJ+vXrjWbMgJ/3n+Hq1atTz7Vo0SKjx4wZ4wpBpUqVUvvprfuavyOhGEDWGEGWY9HXD8UU+Hn/vtjHc/3xxx+p/aF4hP/50HWG/nbKQ28EQggROZoIhBAicjQRCCFE5OS8jkCIGjVqGP3tt98aTe/49NNPT9rVq1c3fb169TJ61KhRRt98881G79692+jmzZsb3a1bt6Q9adIk09e+fXuj6cfSv+3YsaPRbdq0MdqPISxcuND0+Xn/zjm3f//+1OvevHlz6vf9NRErV640fTVr1jS6bt267nhAzzlL/n0WLzxfssYXQudOO17W7xbyPk899dTMx9AbgRBCRI4mAiGEiBxNBEIIETlaR3CCUoh1BA899JDRp512mtG//PKL0QcOHEjafu69c85t2bLF6K5duxrNeAPPxXpAvm/ft29f08f8+uLiYqPr1atndOXKlY0+dOiQ0V26dDlq365du4yuX7++0axF9Omnnxq9bds2o6tVq5a0q1atavpYW8ivgeScc9dff70rBH7sx7lsY40xgnx/V9LiE6F1AKFjZdGhOAnjKlljCmmEniHrYZWH3giEECJyNBEIIUTkKH1U5Ixv9ThXtiwELYN9+/YlbVo/F110kdG0a/hqTWtp586dRvulptesWWP6aKn41o5zZW2oefPmGX3++ecb7dtQLK/dsGFDo1lumOUvmE568OBBo30LjM+Maa9nnHGG+zcIlXJI+2yIUOmGtHOFyjhwTIU+z2vx9bG0eso7V9qxspbPLvd8mb8hhBDihEITgRBCRI4mAiGEiBzFCETOnHXWWUa3aNHC6Ndff93oq666KmnPnDnT9LF8M+ML9NYZQ2Aapl9GYu/evaZvypQpRl977bVG+yWsnSvr87N09DXXXJO06eVeeumlRjN17/333zea93nOOecYvX379qTNUhe8Lvb/W2Tx7fMt+0CylH3I6q2nxRCylrTOmkab1h8qr50LeiMQQojI0UQghBCRo4lACCEiRyUmTlAKUWKidevWRg8ZMsToNB+U18PcfMYA6HMyv55rGHzv/brrrjN99OFD5S54bJZ92LBhQ9IeOHCg6eP2kTNmzDCaJSd4LsYr/DUO33//velj2Y3LL7/c6BtuuMEVAsZnsvjf+Xj+uZDm87M8M9dd/PrrrzkfyznnKlT4/xArxxTHXNr2nc5lK2cRui5+97fffkv9vHN6IxBCiOjRRCCEEJGjiUAIISJH6whEzgwdOtRo5uszhvD5558nbcYE5syZY/SZZ55p9MUXX2w0t8XcunWr0XfccUfS5roBv6+879K3Xrx4sdHTpk0zesGCBUmbpbeHDRtmdFFRkdH0b9966y2jua2mH7/gtpbcUpPbXBaKfOKFWdcNZF134MeWGGdiTSmWH//xxx+N5jajWWIfoe08Q5pkia2wBlUu6I1ACCEiRxOBEEJEjiYCIYSIHK0jOEEpxDoC1hKqUaOG0azj72+d2KpVK9NHb501do4cOXLUYznnXO3atY324xOlpaWm79133zV63LhxRk+dOtXoFStWGM34he8dczvIn376yWjWA2rUqJHRXDfA+/Tvhesj/BiMc2X3Ohg5cqQrBKwLRfLZZjHfdQb+2gquE+D2pozfcM0H95rIUtMntI6AZPl9Da1ByHpu5/RGIIQQ0aOJQAghIkcTgRBCRI7WEYicoa9fuXJlo1lnp3Hjxkl7/vz5po/773KdAGMKjCGwzs6iRYuOel2sBzR58mSjly5davS5555rdJUqVYzeuHFj0v7www9NX48ePYymX/vZZ58ZPWDAAKMZM/D3Wz506JDp4zMaNGiQOx6EfP2suf8+oT2KeSzW+PHHBWsLsa5T1rr9/2ac1D936PnzmeSC3giEECJyNBEIIUTkaCIQQojIOeFiBFn3CqXX3KRJE6PXrVt3DK8uG2m+YC65wccarhvYvXu30e3atTPa98eZH09fkznyX375pdHcL9n36Qk9feby9+7d2+ivvvrKaNaJoTffpUuXpM1nwjULjFdw/cPChQuNPnDggNH+ugTGaLi+Yfbs2UYPHjzYFYJ8xh7HMX36UIyA/Wl+OL/LGjxc88F/9yzn4n3xWFn3Q84SjzgWa4b0RiCEEJGjiUAIISLnf9IaSkufCqWyEZYy4HZ/x9Iayvpa7FsrhSgZkRVu5cetE7mdpP/qTcuN5RBYeuHw4cNGM02zZcuWRvs2FW0olsB+8MEHjb7nnnuM/uCDD4z2rSDn7NZ/THtt1qyZ0Uxh5DOjTcXx6FtgTEX1U0udc66kpMT9N5Bma4SsHpaK5rH87SHL+74PrTMem+OV9iPHIO0eX4csaR6LNlWobIRPyD77J9ad3giEECJyNBEIIUTkaCIQQojIOS5lqLOWms2nNC3T+bh9H0vR1q1bN7V/27ZtRvtbLHJrO6aX0VPMBy6P37lzZ+rnCxFTuO+++4y+7LLLjH777beNvvvuu5P2yy+/bPpYHoEpmm3atDGaz7ZBgwZGL1myJGnTf2VqKv9N9+zZY3RxcbHRHI/+8bm15KZNm4xeu3at0X369DGaPjXHlD+G2Ne2bdvU7z788MOuELAMdZaSE/wsj8XUX8ZYmI7Lfj8OwLIkDRs2NLp69epGs3z59u3bjWb6ru/F8z7498mS1vxtYPyHpKWucrwzHhE6tnN6IxBCiOjRRCCEEJGjiUAIISLnuKwjyOpXhz5fv359o/2cdG5Pt2/fPqPp4a5atcro7t27G80cdD+G8M4775g+es2kYsWKRrNkMeMZLIfs88QTTxidtaTuP4G+PLdKZHzFX0fA/Hj6tczx5rqBxx57zOhXX33V6BYtWiTtrl27mr7XXnvN6J49expND5XrJR599NGjXhvHz9VXX200fejHH3/caH+LTefK5oBfeOGFSZtbT95///1GM2ZQKOhvh3Lo/bHJccoSL/T8uW6gWrVqqdfirwXgs+dvAf8eGYfr1q2b0Syd7pcUpy/P3zCWH1+zZo3R/tqU8vCfA+MFLEvyT2KTeiMQQojI0UQghBCRo4lACCEiJ+d1BKH6Flm+G6qFwRxylu5lvrS/vR+96KzQ3xw9erTRvp9Mb4707dvXaOb7MreY+evPP/980maePTkeZaqnTJliNHPkP/roI6P9dQfcqpJ+LdcksMw068B06NDB6JUrVyZtxnU++eQTo5nzzVhMvXr1jPZ9euecmzBhQtKmb79r1y6j+e+2efNmo+fNm2f07bffbrT/zFlbiF4w1yh06tTJFQLG4ejjc5z7181nz2MxZkA/nOuEOM79ZxJa18Pr5LVwTHbu3Nlo/75ZM4p/2yxPPmvWLKNZgyrtt4XxBGr+Fuzfv/+ox/o/9EYghBCRo4lACCEiRxOBEEJETs7rCEJ56mn1RejjsZ7IFVdcYTRzbOmjMmc37Tqz1EEpT9P39nO3mTfP3HfmlOdT/4f51cx9Px77FdBTpZc+bNgwozds2JC0x4wZY/qmT59uNLeTrFmzptGsTcStLH1/fOrUqaaPXjmfHfecYGxn2rRpRvtbQHJNy9ixY41mvIK6Vq1aRrMOkl+LiPVrWEuHsbNCwTr/9P25JsT39Znbz9pBIT+bY5DavxbuSxGql8b4BGMf/F1q3LjxUY81c+ZMo7ds2WI0/56piR/75O9p1j1YykNvBEIIETmaCIQQInI0EQghROTkHCPIp7Y+fUDfY3WubK36EMwPzmfP4lA/96R98cUXk/aIESNMH71S+sf0f7OQS03xQsM866VLlxpND/uSSy5J2m+88YbpY213rhVhzvw333xjND3VuXPnJm367ow3+DWQnHPuyiuvNJoeOMeA7/dy3Qr3ZuZ6CY4R1qfi/gR+HID3xe8yNsIY1bGCfzMcm7wu/xkxvhfajyBUa5/rNHyfn2OEaxD4O8L4Dcf7ggULjPbHAZ/BF198YTTHL+sc8Vp4bj++we8ylsFaWbmgNwIhhIgcTQRCCBE5mgiEECJyco4RMGeevj9zdn0PeMCAAaYvl9oXaRzLvYAJ/Td6fx07dkza9C/pF2/dutXoZ5991mi/RpJzZfOS/Zr99Ddbtmxp9L333usKje/DO2f3gXCubIzA93vZx5z3oqIio7l2hDEF1qWfPXt20uaahRdeeMFof+8C5+x6B+fKrkXh/gb9+vVL2hwvy5YtSz0X97DgHgL82/D3qOCxWM+GulBwnIfqkGWpe8UYAL3z0N+cfy6uWQitvWGdKMI9NPxxwHUuvA+uUWBtIcZ/GCvx12bw2Kxf9fXXX/PSg+iNQAghIkcTgRBCRE7OZahpRbRr185opoH5r3R8neOrJFMF+TqYpcRyaPk1UwPTytg6V7YcrG9RcCk9bQFubccytqWlpUbTFvDT8JgmR6tk8uTJRhei5AS3WWS58LRtQps1a2b6fvjhB6NZMoKvyn4qqnPpqbjbt28/ap9zZf+NaRnQBqUlsHfv3qTNscmyG0wnHT58uNG33HKL0SxF0KhRo6S9evVq00d7lmmur7zyiisEHPe06Yhf5pt2DVM8Q+XWCT/v2yahstNMu+TzpB3LdHBfc8wwDXj37t1G89/SH1PlXZv/O8X03JKSktRz52Kl641ACCEiRxOBEEJEjiYCIYSInJxjBKESruK/i0LECJiWyTgRveOJEycmbS7fZ+nxFStWGE2/m7EcxpV8r5gpmW+++abRftqfc2VjM4wLMfWvbt26SZvlKujHcstNxkpYgoJ+rx9X4pabLK/tX5dzzt11112uEDAWxH93PgM/5pcWS3Su7L8zt2HkuOa5smxVSR8+629cWml+xi543Tw3r41pyf65WEKCMS7eN59heeiNQAghIkcTgRBCRI4mAiGEiBzFCE5QChEj+Pjjj40uLi42mvn7vjfJz9K3ZClo+vTUzNf3y1zTO+d6Dp6bvjTzzevUqWO0XyaC8Qgem+fm+gnmhDPu4q8rYAkSlingGpmhQ4e6QkD/mnDs+b8doS1vCb1zfp86LWc+tI0tScvl57lCxwqthcqyxS7HZ2g73rStfZPzBz8hhBDihEYTgRBCRI4mAiGEiJycy1ALsXLlSqPnz59vNH1+35ukf00fn7n8c+bMMZrbLrZu3dro0aNHJ+1Ro0aZPtazYU0Zxh+aN29uNOv/9O/fP2mvWbPG9NHzD5Xf5roC3rf/nFjziMf26xIVkqzbwfoedpaS1OURqg3me+0h7zzrNrZpsY/QdYZiBKFjp11r1vsqD70RCCFE5GgiEEKIyNFEIIQQkaN1BCcohVhHMGjQIKNvuukmoxkH8HPmuW1n7dq1jeb+CqynwvopzGX3673TS2fdF3/7R+ecmzRpktGMEXDNgl9Lnrn9a9euNdqvxe9c2XxxXtsFF1xgNGvi+4wdO9Zobld65513HvW7+cDaS/nAcRra9jL0fR+OGR6bsSPW7CFpPj/7mOsfgt9PixGEngnvU7WGhBBCBNFEIIQQkaOJQAghIkfrCETOdOjQwWjuIcB1BDNmzEjaDzzwgOljTXvu99y+fXujN2zYYDT9Xz8fn54/r6tHjx5GM17BmkrE31uBfjnzwxctWpR6bu5ly3UGfoyAz2zAgAGp5ypUjCBfXz8LIe88y7oEjhnui80YAfeaSLs23nPourKsEwidK/SMckFvBEIIETmaCIQQInI0EQghRORoHcEJSiHWEcybN8/ol156yWh62N27d0/a27ZtM33Lly83mnsYt2jRIvXz3NPYP/6NN95o+pjbf+TIEaNZt6hJkyZGr1u3zmh/jUNpaanpq1atmtFcg0DfuVWrVkYzPjFkyJCk/fTTT5s+xjZ4X++9954rBMy/Z4wgzR8PeeP5/s6kjXseO7Q3QmiPAP8+WfMoVGsoRD73wVgI16qUh94IhBAicjQRCCFE5MgaOkEphDXEFFDaHkwvLSkpSdrcopH2Are57Nmzp9G0lubOnWv04MGDkzbLY1etWtXo9evXG80yEEw3Xbx4sdH+3wLvg1bRwYMHje7Vq5fRLL3h22nOObd58+akzfvwn69zZS2xSpUquULALRxD1lDab8extoryGffH0qbKkg6a9fNZ03VpGZaH3giEECJyNBEIIUTkaCIQQojIUYzgBKUQMYInn3zS6CpVqhg9YsQIo5966qmkPXDgQNN36623Gk2fnimcbdu2Tb224uLipM1y2Ew1ZSzD31LTubKeKrVfYpjXXadOHaNXrVqVeiymm7LstH+uHTt2mD6WF2aJhOeee84Vgqzpo/5YzFJuubxjH+t003xIO3c+5bPL6/efQ+gZ8fkrRiCEECKIJgIhhIgcTQRCCBE5KkMtcmbXrl1GczvJPn36GO373+PHjzd93JKxX79+RtPvZpkI4q9pmD59uulr2rSp0VOnTjW6qKjIaN4XfXw/t79Ro0amj8+od+/eRvPaqlevbjTLWjdo0CBpb9y40fS1adPGaMZGCkXIl0/z/UNrDFgegX541vz8fD6bj8+f73XmU247tOVmeeiNQAghIkcTgRBCRI4mAiGEiJyc1xEIIYQ4MdEbgRBCRI4mAiGEiBxNBEIIETmaCIQQInI0EQghRORoIhBCiMjRRCCEEJGjiUAIISJHE4EQQkTOfwArmpDn6d3zGgAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" From 76eaa2afc84859f6384c547c412c118689745d52 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 17:24:50 +0100 Subject: [PATCH 17/51] use bilinear upsampling in the unet --- exercise.ipynb | 6 +- solution.ipynb | 1058 ++++++++++++++++++++++++++++++++++++++++++++---- 2 files changed, 976 insertions(+), 88 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 7bdc825..3072a8a 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -1368,7 +1368,7 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear')\n", "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", @@ -1627,7 +1627,7 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear')\n", "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", @@ -1712,7 +1712,7 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear')\n", "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", diff --git a/solution.ipynb b/solution.ipynb index 5f6fbd7..18178f2 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "tags": [] }, @@ -146,9 +146,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -266,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -285,9 +296,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAGFCAYAAAASI+9IAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAJzklEQVR4nO3csXHsuBZFUfQvJUOb9oTCHMhI6DOd55LxPBPjHbcbUukO6tdaNtBHsHbR0av33hsAtNb+91//AQDMQxQACFEAIEQBgBAFAEIUAAhRACBEAYD4+vTgcRzDP36e5/Cdf/75Z/hOa639+fOnZGvmncotb6rdqdyaeadya/Y3/f37d/jOfd9vz/hSACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAIhX771/cvB5nt/+W360s65rydbMO5Vb3lS7U7k1807l1uxvuq5r+I5/iAfAEFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUA4uvTg/u+D//4tm3Dd47jGL7TWmvneZZszbxTueVNtTuVWzPvVG7N/qZlWb619Y4vBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQDi1Xvvnxx8nue3/5Yf7azrWrI1807lljfV7lRuzbxTuTX7m67rGr5z3/fbM74UAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAOLr04P7vg//+LZtw3eO4xi+01pr53mWbM28U7nlTbU7lVsz71Ruzf6mZVm+tfWOLwUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAePXe+ycHn+f57b/lRzvrupZszbxTueVNtTuVWzPvVG7N/qbruobv3Pf99owvBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYD4+vTgvu/DP75t2/Cd4ziG77TW2nmeJVsz71RueVPtTuXWzDuVW7O/aVmWb22940sBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIF699/7Jwed5fvtv+dHOuq4lWzPvVG55U+1O5dbMO5Vbs7/puq7hO/d9vz3jSwGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGA+Pr04L7vwz++bdvwneM4hu+01tp5niVbM+9UbnlT7U7l1sw7lVuzv2lZlm9tveNLAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBevff+ycHneX77b/nRzrquJVsz71RueVPtTuXWzDuVW7O/6bqu4Tv3fb8940sBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIL4+Pbjv+/CPb9s2fOc4juE7rbV2nmfJ1sw7lVveVLtTuTXzTuXW7G9aluVbW+/4UgAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFACIV++9f3LweZ7f/lt+tLOua8nWzDuVW95Uu1O5NfNO5dbsb7qua/jOfd9vz/hSACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACC+Pj247/vwj2/bNnznOI7hO621dp5nydbMO5Vb3lS7U7k1807l1uxvWpblW1vv+FIAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQAiFfvvX9y8Hme3/5bfrSzrmvJ1sw7lVveVLtTuTXzTuXW7G+6rmv4zn3fb8/4UgAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFACIr08P7vs+/OPbtg3fOY5j+E5rrZ3nWbI1807lljfV7lRuzbxTuTX7m5Zl+dbWO74UAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAOLVe++fHHye57f/lh/trOtasjXzTuWWN9XuVG7NvFO5NfubrusavnPf99szvhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUA4uvTg/u+D//4tm3Dd47jGL7TWmvneZZszbxTueVNtTuVWzPvVG7N/qZlWb619Y4vBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQDi1Xvvnxx8nue3/5Yf7azrWrI1807lljfV7lRuzbxTuTX7m67rGr5z3/fbM74UAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAOLr04P7vg//+LZtw3eO4xi+01pr53mWbM28U7nlTbU7lVsz71Ruzf6mZVm+tfWOLwUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAePXe+ycHn+f57b/lRzvrupZszbxTueVNtTuVWzPvVG7N/qbruobv3Pf99owvBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYD4+vTgvu/DP75t2/Cd4ziG77TW2nmeJVsz71RueVPtTuXWzDuVW7O/aVmWb22940sBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIF699/7Jwed5fvtv+dHOuq4lWzPvVG55U+1O5dbMO5Vbs7/puq7hO/d9vz3jSwGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGA+Pr04L7vwz++bdvwneM4hu+01tp5niVbM+9UbnlT7U7l1sw7lVuzv2lZlm9tveNLAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBevff+ycHneX77b/nRzrquJVsz71RueVPtTuXWzDuVW7O/6bqu4Tv3fb8940sBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIL4+Pbjv+/CPb9s2fOc4juE7rbV2nmfJ1sw7lVveVLtTuTXzTuXW7G9aluVbW+/4UgAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACBEAYAQBQBCFACIV++9f3LweZ7f/lt+tLOua8nWzDuVW95Uu1O5NfNO5dbsb7qua/jOfd9vz/hSACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgBAFAEIUAAhRACC+Pj247/vwj2/bNnznOI7hO621dp5nydbMO5Vb3lS7U7k1807l1uxvWpblW1vv+FIAIEQBgBAFAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQAiI//Id7fv3+Hf/x5nuE73/0nT1VbM+9UbnlT7U7l1sw7lVv/j2/6hC8FAEIUAAhRACBEAYAQBQBCFAAIUQAgRAGAEAUAQhQACFEAIEQBgHj13vt//UcAMAdfCgCEKAAQogBAiAIAIQoAhCgAEKIAQIgCACEKAMS/PPHqkSaRY7MAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Create grid texture\n", "texture = numpy.zeros(tainted_test_dataset.data.shape[1:])\n", @@ -309,7 +341,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "tags": [] }, @@ -331,7 +363,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -346,9 +378,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# visualize example 4s\n", "plt.subplot(1,4,1)\n", @@ -494,11 +537,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "selected torch device: cuda\n" + ] + } + ], "source": [ "import torch\n", "from classifier.model import DenseModel\n", @@ -518,7 +569,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -551,7 +602,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -578,9 +629,25 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DenseModel(\n", + " (fc0): Linear(in_features=784, out_features=256, bias=True)\n", + " (fc1): Linear(in_features=256, out_features=120, bias=True)\n", + " (fc2): Linear(in_features=120, out_features=84, bias=True)\n", + " (fc3): Linear(in_features=84, out_features=10, bias=True)\n", + ")" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Initialize the clean and tainted models\n", "model_clean = DenseModel(input_shape=(28, 28), num_classes=10)\n", @@ -614,7 +681,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -636,11 +703,49 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "938it [00:07, 117.64it/s] \n", + "938it [00:07, 119.34it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "model_clean trained\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "938it [00:07, 119.67it/s] \n", + "938it [00:07, 120.21it/s] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "model_tainted trained\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], "source": [ "# We store history here:\n", "history = {\"loss_tainted\": [],\n", @@ -679,9 +784,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'negative log likelihood loss')" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Visualise the loss history:\n", "fig = plt.figure()\n", @@ -834,7 +960,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -864,7 +990,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": { "tags": [] }, @@ -886,7 +1012,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -947,9 +1073,64 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", + "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", + "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", + "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", + " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", @@ -1150,7 +1331,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": { "tags": [] }, @@ -1193,7 +1374,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -1242,9 +1423,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABDBklEQVR4nO2deXxTZdbHf2mapPvC2patFBCwrBbZocIgKJu+gCAii69CUdHBQVDEV0RwHFARRBBxEBQKssjiCuMCAsqMyi4oawERyt59SZuc94+S0OSep+R2S2DOd4aP6cnJc5/7LPfk5px7joGICIIgCILgIX7e7oAgCIJwcyGGQxAEQdCFGA5BEARBF2I4BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXYjgEQRAEXYjhEARBEHQhhuMWJjY2FqNGjfJ2N3ySu+66C3fddVepPnszj+uoUaMQGxvr7W4INzliOG5Cjh8/jqSkJMTFxSEgIABhYWHo1KkT5s6di9zcXG93z2NOnjwJg8EAg8GAGTNmsDrDhg2DwWBASEhIJffu5iIjIwPTpk1Dy5YtERISgsDAQDRr1gzPPfcczp496+3ueUzxNcH9Gz16tLe7KADw93YHBH188cUXeOCBB2CxWDBixAg0a9YMVqsVO3bswMSJE3Hw4EEsWrTI293URUBAAFauXIkXX3zRRZ6dnY2NGzciICDASz27OThx4gR69OiB06dP44EHHsCYMWNgNpuxf/9+LF68GOvXr8eRI0e83U2PqF69OpYtW6aRb9q0CcnJyejZs6cXeiW4I4bjJiIlJQUPPvgg6tWrh++++w7R0dHO95588kkcO3YMX3zxhRd7WDp69+6NdevWYd++fWjZsqVTvnHjRlitVtxzzz347rvvvNhD36WwsBADBgzA+fPnsXXrVnTu3Nnl/VdffRUzZ870Uu/0ExwcjIcfflgjX7p0KcLCwtCvXz8v9EpwR36quomYNWsWsrKysHjxYhej4aBhw4b461//WmIbaWlpGD9+POrUqQOLxYKGDRti5syZsNvtLnpvvPEGOnbsiKpVqyIwMBAJCQlYu3atpj2DwYBx48Zhw4YNaNasGSwWC+Lj47Fp0yaPz6tDhw6oX78+VqxY4SJPTk7GPffcgypVqrCfW7BgAeLj42GxWBATE4Mnn3wSaWlpGr1FixahQYMGCAwMRNu2bbF9+3a2vfz8fEydOhUNGzaExWJBnTp1MGnSJOTn53t8LsXJzs7GhAkTnGPduHFjvPHGG3BPSF2WMfzkk0+wb98+TJkyRWM0ACAsLAyvvvpqiW3Y7XbMmTMH8fHxCAgIQM2aNZGUlISrV6+66G3cuBF9+vRBTEwMLBYLGjRogOnTp8Nms7no3XXXXWjWrBkOHTqEbt26ISgoCLVq1cKsWbNueD4c586dw5YtWzBgwAC5+/QVSLhpqFWrFsXFxXmsX69ePRo5cqTz7+zsbGrRogVVrVqVXnjhBVq4cCGNGDGCDAYD/fWvf3X5bO3atemJJ56gd955h2bPnk1t27YlAPT555+76AGgli1bUnR0NE2fPp3mzJlDcXFxFBQURJcuXSqxfykpKQSAXn/9dXrhhReobt26ZLfbiYjo4sWL5O/vTytXrqSRI0dScHCwy2enTp1KAKhHjx40b948GjduHBmNRrrzzjvJarU69f75z38SAOrYsSO9/fbbNH78eIqIiKC4uDhKTEx06tlsNurZsycFBQXR+PHj6b333qNx48aRv78/3XfffSWOK4fdbqfu3buTwWCgxx57jN555x3q168fAaDx48eX2xg+9NBDBIBOnz5dop6DkSNHUr169Vxkjz32GPn7+9Po0aNp4cKF9Nxzz1FwcLBmLO+//34aPHgwvf766/Tuu+/SAw88QADo2WefdWkvMTGRYmJiqE6dOvTXv/6VFixYQN27dycA9OWXX3rUz+LMnj2bANDXX3+t+7NCxSCG4yYhPT2dAGguYiXhfoGbPn06BQcH05EjR1z0nn/+eTIajS4Xn5ycHBcdq9VKzZo1o+7du7vIAZDZbKZjx445Zfv27SMANG/evBL7V9xw/PrrrwSAtm/fTkRE8+fPp5CQEMrOztYYjgsXLpDZbKaePXuSzWZzyt955x0CQB988IGzzzVq1KBWrVpRfn6+U2/RokUEwMVwLFu2jPz8/JzHd7Bw4UICQD/88INT5onh2LBhAwGgGTNmuMgHDRpEBoPBZbzKMoatW7em8PDwEnWK4244tm/fTgAoOTnZRW/Tpk0aufuaICJKSkqioKAgysvLc8oSExMJAH300UdOWX5+PkVFRdHAgQM97quDhIQEio6OdplrwbvIT1U3CRkZGQCA0NDQUrexZs0adOnSBZGRkbh06ZLzX48ePWCz2bBt2zanbmBgoPP11atXkZ6eji5dumD37t2adnv06IEGDRo4/27RogXCwsJw4sQJj/sWHx+PFi1aYOXKlQCAFStW4L777kNQUJBG95tvvoHVasX48ePh53d9CY8ePRphYWFOP88vv/yCCxcuYOzYsTCbzU69UaNGITw8XDM2TZs2RZMmTVzGpnv37gCALVu2eHwuAPDll1/CaDTi6aefdpFPmDABRISvvvrKRV7aMczIyCjzmggPD8fdd9/tct4JCQkICQlxOe/iayIzMxOXLl1Cly5dkJOTg99//92l3ZCQEBdfhdlsRtu2bXWtCQA4cuQIdu3ahQcffNBlrgXvIs7xm4SwsDAARRu2tBw9ehT79+9H9erV2fcvXLjgfP35559jxowZ2Lt3r8tv/AaDQfO5unXramSRkZGa38hvxEMPPYQ333wTzzzzDH788Ue88MILrN6pU6cAAI0bN3aRm81mxMXFOd93/LdRo0YueiaTCXFxcS6yo0eP4rfffvNobDzh1KlTiImJ0VzUmzZt6tI3B6UdQ70G2p2jR48iPT0dNWrUYN8vft4HDx7Eiy++iO+++875RcZBenq6y9+1a9fWrJXIyEjs379fV/+Sk5MBFIVlC76DGI6bhLCwMMTExODXX38tdRt2ux133303Jk2axL5/2223AQC2b9+O/v37o2vXrliwYAGio6NhMpmwZMkSjQMbAIxGI9se6axKPHToUEyePBmjR49G1apVKzX00m63o3nz5pg9ezb7fp06dSr0+KUdwyZNmmDPnj34448/StVHu92OGjVqOC/Q7jgMaVpaGhITExEWFoZXXnkFDRo0QEBAAHbv3o3nnntOE1xRXmtixYoVaNy4MRISEnR9TqhYxHDcRPTt2xeLFi3Czp070aFDB92fb9CgAbKystCjR48S9T755BMEBARg8+bNsFgsTvmSJUt0H1MPdevWRadOnbB161Y8/vjj8Pfnl2e9evUAAIcPH3a5c7BarUhJSXGen0Pv6NGjzp+cAKCgoAApKSkuob8NGjTAvn378Je//IW9q9JLvXr18M033yAzM9PlrsPxk46jb2WlX79+WLlyJZYvX47Jkyfr/nyDBg3wzTffoFOnTi4/RbmzdetWXL58GevWrUPXrl2d8pSUlFL12xP+85//4NixY3jllVcq7BhC6ZAfDW8iJk2ahODgYDz22GM4f/685v3jx49j7ty5ys8PHjwYO3fuxObNmzXvpaWlobCwEEDRt0WDweASZnny5Els2LCh7CdxA2bMmIGpU6fiqaeeUur06NEDZrMZb7/9tss32MWLFyM9PR19+vQBALRp0wbVq1fHwoULYbVanXpLly7VhO0OHjwYf/75J95//33N8XJzc5Gdna3rPHr37g2bzYZ33nnHRf7WW2/BYDDg3nvv1dWeikGDBqF58+Z49dVXsXPnTs37mZmZmDJlivLzgwcPhs1mw/Tp0zXvFRYWOsfJcQdRfLytVisWLFhQxjNQ47i7feihhyrsGELpkDuOm4gGDRpgxYoVGDJkCJo2bery5PiPP/6INWvWlJhDaeLEifj000/Rt29fjBo1CgkJCcjOzsaBAwewdu1anDx5EtWqVUOfPn0we/Zs3HPPPXjooYdw4cIFzJ8/Hw0bNtT9G7VeEhMTkZiYWKJO9erVMXnyZEybNg333HMP+vfvj8OHD2PBggW48847nU5Zk8mEGTNmICkpCd27d8eQIUOQkpKCJUuWaHwcw4cPx+rVqzF27Fhs2bIFnTp1gs1mw++//47Vq1dj8+bNaNOmjcfn0a9fP3Tr1g1TpkzByZMn0bJlS/zrX//Cxo0bMX78eBdHeFkwmUxYt24devToga5du2Lw4MHo1KkTTCYTDh48iBUrViAyMlL5LEdiYiKSkpLw2muvYe/evejZsydMJhOOHj2KNWvWYO7cuRg0aBA6duyIyMhIjBw5Ek8//TQMBgOWLVum+6cnT7HZbFi1ahXat29fbmMllCNejOgSSsmRI0do9OjRFBsbS2azmUJDQ6lTp040b948l7BILmw0MzOTJk+eTA0bNiSz2UzVqlWjjh070htvvOESs7948WJq1KgRWSwWatKkCS1ZssT57ERxANCTTz6p6aMnIavFw3FLgnuOg6go/LZJkyZkMpmoZs2a9Pjjj9PVq1c1egsWLKD69euTxWKhNm3a0LZt2ygxMdElHJeoKHx35syZFB8fTxaLhSIjIykhIYGmTZtG6enpus6NqGisn3nmGYqJiSGTyUSNGjWi119/3fmsioOyjKGDq1ev0ksvvUTNmzenoKAgCggIoGbNmtHkyZPp3LlzTj3uOQ6iohDlhIQECgwMpNDQUGrevDlNmjSJzp4969T54YcfqH379hQYGEgxMTE0adIk2rx5MwGgLVu2OPUSExMpPj5ecwzVsTkc4cBvv/22R/pC5WIgqqCvDIIgCMItifg4BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXXjUcL7/8cqkftlq6dCkMBgNOnjxZvp0qhqMa2dKlSyvsGHopS8nTysK9tKpjrn755ZdKOf7NMEY3G9x+i42NRd++fSvl+Fu3boXBYMDWrVsr5XiVxc16XqUyHAcPHsTDDz+MWrVqOWshDBs2DAcPHizv/gllxGazISYmBgaDQZNYz8GCBQtY43jo0CG8/PLLFWqcS4sv960yWLBgAQwGA9q1a8e+X9L4qObbF/DVvhERli1bhq5duyIiIgJBQUFo3rw5XnnlFd0Ph94S6I3f/eSTT8hsNlNUVBRNmTKF/vnPf9KLL75I0dHRZDabad26dR63VVBQQLm5uXq7QEREhYWFlJubq4mJL08czxksWbKkwo6hF+75g5L417/+RQAoNjaWhg0bxurEx8ezba5Zs0YTo+8JeXl5Ls+ELFmyhADQzz//rKudkiipb/n5+S5p1G9FOnbsSLGxsQSAjh49qnm/pPFRzXdJcPutXr161KdPH71dLxFV32w2G+Xm5noltXphYSENHjyYAFCXLl3orbfeovfee48efvhh8vPzo2bNmlFqamqp2t6yZUup9pi30XXHcfz4cQwfPhxxcXHYv38/ZsyYgUcffRTTp0/H/v37ERcXh+HDh98wW6fDQvv7+5e6opfRaERAQEC55BW6lVm+fDnuuOMOPPPMM9iwYUOFfTsiIuTm5gIALBYLTCZThRzHE8xms0sa9VuNlJQU/Pjjj5g9ezaqV6+uTFBYHjjWi7f3m5+fHwICArySWn3WrFlYvXo1nn32WWzbtg3jx4/HmDFjsGzZMmzYsAGHDh0qMWPDLYkeK5OUlEQAaNu2bez733//PQGgpKQkp8zxtPHBgwdp6NChFBERQa1atXJ5rzg5OTn01FNPUdWqVSkkJIT69etHZ86cIQA0depUp57jW2xKSopT5vgGtH37drrzzjvJYrFQ/fr16cMPP3Q5xuXLl2nChAnUrFkzCg4OptDQULrnnnto7969Lnqe3nF42p7j28WqVatoxowZVKtWLbJYLNS9e3f2W+N7771HcXFxFBAQQHfeeafyiWcVOTk5FBoaSrNmzaJz586Rn5+fpmBPvXr1CIDLv8TEROf4uv9zfDNyjPWmTZsoISGBLBYLvfXWW873ij/x7Gjr+++/pzFjxlCVKlUoNDSUhg8fTleuXHHpj/s8F++no80b9Y0bo/Pnz9P//u//Uo0aNchisVCLFi1o6dKlLjrFn2R3jL3ZbKY2bdrQTz/95NGYVwbTp0+nyMhIys/Pp8cff5waNWrk8n5J46Oa7+Kf27p1Kz3++ONUvXp1ioiIcHmP22+bN2+mli1bksVioaZNm9Inn3zi0h9un3NtltQ31Tfz1atX0x133EEBAQFUtWpVGjZsGJ05c8ZFx5F54MyZM3TfffdRcHAwVatWjSZMmECFhYUljnVOTg5FRkbSbbfdRgUFBazOI488QgBo586dmrG50bXI/bxeeukl8vf3pwsXLmiOM3r0aAoPDy/1rzTliS7z/dlnnyE2NhZdunRh3+/atStiY2OdhXSK88ADDyAnJwd///vfMXr0aOUxRo0ahXnz5qF3796YOXMmAgMDnUnrPOHYsWMYNGgQ7r77brz55puIjIzEqFGjXPwvJ06cwIYNG9C3b1/Mnj0bEydOxIEDB5CYmIizZ896fKzStvePf/wD69evx7PPPovJkyfj3//+t6bewOLFi5GUlISoqCjMmjULnTp1Qv/+/fHHH3943K9PP/0UWVlZePDBBxEVFYW77rpL8+10zpw5qF27Npo0aYJly5Zh2bJlmDJlCrp27eosQvTCCy8433PUkwCKstMOHToUd999N+bOnYtWrVqV2J9x48bht99+w8svv4wRI0YgOTkZ999/v+58R570rTi5ubm46667sGzZMgwbNgyvv/46wsPDMWrUKDYp5IoVK/D6668jKSkJM2bMwMmTJzFgwAAUFBTo6mdFkZycjAEDBsBsNmPo0KE4evQofv75Z+f7JY2Par6L88QTT+DQoUN46aWX8Pzzz5fYl6NHj2LIkCG499578dprr8Hf3x8PPPAAvv76a93n5UnfirN06VIMHjwYRqMRr732GkaPHo1169ahc+fOmiSWNpsNvXr1QtWqVfHGG28gMTERb775JhYtWlRin3bs2IGrV6/ioYceUmZrHjFiBICiGjbF8eRa5M7w4cNRWFiIVatWucitVivWrl2LgQMH+kbddU8tTFpamkelS/v3708AKCMjg4iuf9sYOnSoRtf9m8iuXbvYmsyjRo3y+I4DbndEFy5cIIvFQhMmTHDK8vLyNL+VpqSkkMVioVdeecVFBg/uODxtz/HtomnTpi6/wc+dO5cA0IEDB4hIX8nTkujbty916tTJ5fPct5nS+DgcY71p0yb2Pe6OIyEhwcX3MWvWLAJAGzdudMrc51nVZkl9c7/jmDNnDgGg5cuXO2VWq5U6dOhAISEhzrXqmO+qVau63Alt3LiRANBnn32mOVZl88svv7jU37bb7VS7dm1NzfjS+Dgc89S5c2fNN/GS9lvxO4z09HSKjo6m1q1bO2We3nGU1Df3b+aOPdKsWTOXb+Cff/45AaCXXnrJKRs5ciQBcNmLREVldxMSEjTHKo5j7axfv16pc+XKFQJAAwYMcMo8vRZxd1IdOnSgdu3auRxj3bp1PuUL8fiOw1F57kZlKh3vu1cIGzt27A2PsWnTJgBF33iKU1KKbXduv/12lzui6tWro3Hjxi5+F4vF4vyt1Gaz4fLlywgJCUHjxo3Z0qg3Qm97jzzyiMtv8I7+Ovqop+SpisuXL2Pz5s0YOnSoUzZw4EAYDAasXr1a9zly1K9fH7169fJYf8yYMS6+D0fNjS+//LJc+qPiyy+/RFRUlMtYmEwmPP3008jKysL333/voj9kyBBERkY6/3afH2+SnJyMmjVrolu3bgCKKjIOGTIEH3/8sUsa/LIwevRoZSEmd2JiYvA///M/zr/DwsIwYsQI7NmzB6mpqeXSHw7HHnniiSdcvoH36dMHTZo0YX/1cL8GdenS5YZz6sl1T3XN8+RaxDFixAj85z//wfHjx52y5ORk1KlT54aZoysLjw2HY3BuVLpUNdD169e/4TFOnToFPz8/jW7Dhg097aZHJTjtdjveeustNGrUCBaLBdWqVUP16tWxf/9+TQlMT9DbnnsfHRcpRx/1lDxVsWrVKhQUFKB169Y4duwYjh07hitXrqBdu3bl5kz1ZE6L434+ISEhiI6OrvCQ2lOnTqFRo0Yax6qnZVzd58db2Gw2fPzxx+jWrRtSUlKc89quXTucP38e3377bbkcR8+8NmzYUOMwd1SSrMh5VZUPBoqqIrrPaUBAgKYssCeleT257qmueaUtBzxkyBBYLBbnPk1PT8fnn3+OYcOG+UwwkMeGIzw8HNHR0Tesx7B//37UqlXLWSPbQUnVxcoTT0pW/v3vf8ff/vY3dO3aFcuXL8fmzZvx9ddfIz4+XlMC0xP0tldeZTVLwrHoOnXqhEaNGjn/7dixAzt37iyXb8+VNacAyu3btCdUxvyUhu+++w7nzp3Dxx9/7DKngwcPBoBy+0JQ3vOqutj5wpzeCMeXi5Kue473br/9do+OeaN1FBkZib59+zrnc+3atcjPz3fWmfEFdBVy6tu3L95//33s2LEDnTt31ry/fft2nDx5EklJSaXqTL169WC325GSkuLy7fTYsWOlak/F2rVr0a1bNyxevNhFnpaWhmrVqnm9PT0lTzkc4Zrjxo3T3Nra7XYMHz4cK1aswIsvvghAvbHL+9vN0aNHnT+xAEBWVhbOnTuH3r17O2WRkZEax6bVasW5c+dK3bd69eph//79sNvtLncd5V3GtaJJTk5GjRo1MH/+fM1769atw/r167Fw4UIEBgaWOD7lOa/Hjh0DEbm0eeTIEQBFT5YD1+/Y0tLSEBER4dRzvyvQ07fi5YOL7xGHrLzmtHPnzoiIiMCKFSswZcoU1hh89NFHAFCuT9GPGDEC9913H37++WckJyejdevWiI+PL7f2y4quqKqJEyciMDAQSUlJuHz5sst7V65cwdixYxEUFISJEyeWqjOO38vdy1HOmzevVO2pMBqNGqu/Zs0a/Pnnnz7Rnp6SpxyObyqTJk3CoEGDXP4NHjwYiYmJLt9Og4OD2XaDg4MBwKNjesKiRYtcIpPeffddFBYWupRRbdCgAbZt26b5nPu3Uz196927N1JTU10iVQoLCzFv3jyEhIT4zO/GJZGbm4t169ahb9++mjkdNGgQxo0bh8zMTHz66acASh4f1XyXhrNnz2L9+vXOvzMyMvDRRx+hVatWiIqKAgBnBb/i85qdnY0PP/yw1H1r06YNatSogYULFyI/P98p/+qrr/Dbb7/pisQsiaCgIDz77LM4fPgwG+H1xRdfYOnSpejVqxfat29fLscEgHvvvRfVqlXDzJkz8f333/vU3Qag846jUaNG+PDDDzFs2DA0b94cjz76KOrXr4+TJ09i8eLFuHTpElauXFnqUo8JCQkYOHAg5syZg8uXL6N9+/b4/vvvnd9gyuubUt++ffHKK6/gkUceQceOHXHgwAEkJyd77D+o6Pb0lDzlSE5ORqtWrVCnTh32/f79++Opp57C7t27cccddyAhIQHvvvsuZsyYgYYNG6JGjRro3r07WrVqBaPRiJkzZyI9PR0WiwXdu3dHjRo1SnVeVqsVf/nLXzB48GBnqdfOnTujf//+Tp3HHnsMY8eOxcCBA3H33Xdj37592Lx5s+bOTU/fxowZg/feew+jRo3Crl27EBsbi7Vr1+KHH37AnDlzbhjw4Qt8+umnyMzMdBmr4rRv3975MOCQIUNKHB/VfJeG2267DY8++ih+/vln1KxZEx988AHOnz+PJUuWOHV69uyJunXr4tFHH8XEiRNhNBrxwQcfoHr16jh9+rRLe572zWQyYebMmXjkkUeQmJiIoUOH4vz585g7dy5iY2PxzDPPlOp8OJ5//nns2bMHM2fOxM6dOzFw4EAEBgZix44dWL58OZo2bcoawbJgMpnw4IMP4p133oHRaHQJ7PAJShOKtX//fho6dChFR0eTyWSiqKgoGjp0qDOctDiOULyLFy8q3ytOdnY2Pfnkk1SlShUKCQmh+++/nw4fPkwA6B//+IdTr6QHktxxD8/My8ujCRMmUHR0NAUGBlKnTp1o586dGj094bietOcIvVuzZo3L51XH8bTkaXEcIc3/93//p9Q5efIkAaBnnnmGiIhSU1OpT58+FBoaqgn3ff/99ykuLo6MRiP7ACDHjR4AjIyMpJCQEBo2bBhdvnzZ5bM2m42ee+45qlatGgUFBVGvXr3o2LFjbBlVVd9UDwA+8sgjVK1aNTKbzdS8eXPNeJdUyhaKMOHKol+/fhQQEEDZ2dlKnVGjRpHJZKJLly4RkXp8VPNdUmqYGz0A2KJFC2eZYff1TVS0Ltu1a0dms5nq1q1Ls2fPZttU9U31AOCqVauodevWZLFYqEqVKiU+AOiOKkyYw2az0ZIlS6hTp04UFhZGAQEBFB8fT9OmTaOsrCyNvqfXopJSjvz0008EgHr27OlRHyuTm6J07N69e9G6dWssX75c86CcIAjCrci+ffvQqlUrfPTRRxg+fLi3u+OCz9XjcOQ7Ks6cOXPg5+eHrl27eqFHgiAIlc/777+PkJAQDBgwwNtd0aDLx1EZzJo1C7t27UK3bt3g7++Pr776Cl999RXGjBmj/M1eEAThVuGzzz7DoUOHsGjRIowbN84Z6OBL+NxPVV9//TWmTZuGQ4cOISsrC3Xr1sXw4cMxZcoUZa4YQRCEW4XY2FicP38evXr1wrJly3wyeMPnDIcgCILg2/icj0MQBEHwbcRwCIIgCLrwitPAbrfj7NmzCA0N9ZmkXcKtCREhMzMTMTExXqkexyHrX6hMKmIPeMVwnD17ViKkhErljz/+QO3atb3dDQCy/gXvUJ57wCuGwxElkPTk07BYLC7vmYxai2iz8/577suaQhV25g1/o75ve37MAQttnvfN6Of58eyKmAWb4njceavOjzsPayGfFdjEtKHMdqoYfIJWzs0zABQybRTa+L75M9+e3GM98vPz8d6Ct30qMsXRl/2HUxAa6ppFOsii3ZKqueGWEzd+AFDItBFg1pcx1p+Zszwrn+HWj+mc2d/zb7uqObcW8HLuvFXnx+3D7LxCVjeQaYM7NwAoUMwTt5e5dgEgn2lDNcYBJm0b3HUuMzMDLZrUL9c94BXD4bjwWCyWm95wGG8Rw2Ew+obhMDJtGMtgOBz40k9Cjr6EhoYh1K38QHAFGQ7uoqa6eKngDIe5kg1Hvg7DoTo/bh/6mXnDEVQOhsPGrEmuXYA3HCbFGAcyhkO1B4Hy3QO+8aOvIAiCcNMghkMQBEHQhVcfxTZc+19xuFst5Q0W9/OM4jbSWsItnDvcTzkAkJ2vvZ21+PO3nAXMrbZBYae5W8icfP721KK43Tf5e+5/sTEDp/oZgf05UDGWql/iuG6ofnLgfqJT/eTGyfMLXD+vY9orHYPBoFlr3M9SqvXP/SqnWh+qn1E4uJ+kAOBCep5GFhZoYjSBHGavGBSXG+6no0uZVkYTCA3g2wi2aPdhruInHm6/hSja5fqmGkvVT9F2ZgNk5PI/jbG+GhM/HxZGzrWr+vmyLMgdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDowrvOcYPW+co5tLgHXYoa0IrydTwsowprVjl/ubhwVdw05zRXPWPAPeegdgjztp7rh+pZCS6uXBU3b2KcrSpXmyqogJ09P4WDnZlUVfw556R0DxKw23zn+Q13/AzagILLWVqncEQQ74DmhiUzm3e6cm3ofR6hSohZI1M9Y8I5zVV7hQuIUDmEVQ/1cX3mnokBACuz1lUP2QUxTnfVM1aqvWliv58rnk1i9r3K6c4F0HBBAjZGVlbkjkMQBEHQhRgOQRAEQRdiOARBEARdiOEQBEEQdCGGQxAEQdCFV6OqbHbSRFpwkRBc+g4AMDHZUe2qSBGmDVVUiSp1Bhc1xEUoAXzEi+I02JQSqnQJKjkXsaKKcuLSK+QpUoBwkSKqqLN8O9+GmWtDEZrFRZ6pot+MHqSHV0X9+AIFhXZN/2qEWTR6XPoOgN8rhf78wHLpcriIOUCdtoeL7lEsf3bOVKkvuHa56LKS5Nw8q6KcosK1Y5yuSAHCRXGpUvlk5vF9Y+dJFWHGyG2K+eD2VSaTHj5LkTK+LMgdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDowqvOcT8/g8ZBzaXfUME5vFWOPa5VVeqAAt7/DItJ27bKwcjVm9DjEFM59lSOOS7VAFeGUiXnSsQCiqAChbfaz6BII8Kcih+pys9qZapx42qQuDta9ZTrrWz8/f0064cPDvC8PowqPQ+31lUpQLIVgRJhgdrLRbCijkV6ToFGplqPesraqoI4aoQHaGSZudo+ALwDWVXKlQtGUa0plZzbW/5+/PE4J3+e4oLElY7l6rHk6yjZ6ylyxyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOjCq1FVZCeQW2QHMZEJelIVqNKIcG2o0iVYFEVkuEf3ufQdqjYKmcIrAB/dwhWQKdLl2+DORRU1ww1RVh7fbigTSaNKe8LpAnykiIFNtAKYmQgQpiZWURtME+R2KFUEmC9gtxFsblFyXG9VUTXcWKmi/Lg2VGlfuOgpAEhNz9fIuPQdqjYuZnqeLqRaqLZoVJEu3wYXmahKN8NdN1LT8ljd6EhttNblLD6FRy1GF+CvG6pIuVDmeqIqXsXtYzsTrVgRkYVyxyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuvCqcxwGaLyBnJNX5drh8tGrHLf+zGP/qpQjOQonNtcGl1oE4B23gQqne6BZK89W9IFzngH8eavST3DpFUxG1Tlr+6Zytqkc0dw8qdJPFDI5RwyK4/kzx3Pvgy87x8u6/kOYOg+XM7UObIB3sKrq3FzKVKW40M5jhqKOBbdGIoNMrG6VYK38QgZ/HjGRgaycq9MREcw72KuFaOVpFj49CZf6hEvrAajTBHH1OLi0J4AixYkiHRDXD64Pqn6VBbnjEARBEHQhhkMQBEHQhRgOQRAEQRdiOARBEARdiOEQBEEQdOHVqCqT0Q8mN48/lxqES60AADlWbWQCV9wE4NNvNGjUhNW1Vo9j5Y3DtP347sgFVrc+aeU52dms7sVLlzUyVWEZVZQQFyGmiv7gUjGoxpijQFFMyqgo5MSNvapcF5cyQxWBxRXtch8eXw6qCjQbNfPMnasqrc0lJoIqUhFJxM05V2wJAGbvSGHlj7etq5FN/+Yoq7vkoVYamSoajzvnqkzkU0ltcNF4wRY+iouLaOIKoanIVURSmoy8nBt7VUQnl2pIFYHFRU36MTurImqZyR2HIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOhCDIcgCIKgC69GVdnspIm44SIAVLmjuGgTVe4cLmrCP+4OVvfKYT6qZNdZraxz53as7m+HUzWyVp2rs7qXLmojsOqF8zl5/P1U+XC058fl2QH4PFiqHF9p+docQPbcXFb3+K+/sPITp85o+6bI28XNtSrii8sTVmh3leXn8+vBF7AW2jURN1ykmKoAUnSEtnDQmSv83FRnCiO9tPkwq/vZ3A9Y+TJGNmzyWFa33uiVGtnTw9uyukYm9K1r3SqsboCiqldNpqCUKqqQy4N14gI/xqcytZGQ0UH83mxVN5yVZzN7S5W36xIz16r8dFxUXD5TsCtTkb+sLMgdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDowqvOcTuR5tH7wkLtI/OqgkTco/yqx+s5p3nO7z+yujkUxMqrktbxePTn71ndejExGtnpi1oHHgCM6txSIzt19iKru/0P3vnZokqYRnbVyqdA+M9hrZc/Mb4qqxsWrpUfSEljdes04FO4nPnzT43Mpki5wKWUUKUNMfkzhZzsrt+FyOa734244BAucCFC4UjNYlJRcM51APjzap5G9o8+TVnd5rXGs/L7mtTUyA5eTGd1ez3bXSNL/oWJLgGwYkSCRnbiAp+eZ+zHe1j58M51NLKLWXxgxDur9mpk88d1YnXPMI70f2z8ndVd9hgfKFMrUhvEYFUU0eICQfwUc8oFxJi4gnXW8r/M++6uEgRBEHwSMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAuvRlUV2ghGt6JA/kxUgCoChxi5e2Eopy60UQypZ06zulzhIQC4wkQ8KLqG80cOaGTBilQFS49Fa2R/nuUjUKpUj2Llu37T9k1V9CbYqk1V8PWhK6zuXYNGaGTR1YNZXTqRxcq5OUlTFBHiClUZjXxUXR6TysHiFoFn8OFKTvkFduS5pU2xMKlYChQROHZmnarSzHCFg6qF8lF+Y9vXY+WhgdrorgY1Q1jdHCbVy92NtVFZqr7VqcrvleWj7mTlkcHavqlS1YzrWF8j4647ALByzx8aWZvb+fNoWJPfF9waPHmRjxrzZ/YKtyYAIC1bu4fCmAg8VVRWWZA7DkEQBEEXYjgEQRAEXYjhEARBEHQhhkMQBEHQhVed4wEmo8aZyTm8s/J4RypXj0PlHNfjI1W1wZHL5L8HgAImHQrApws5ePiYVlNRH+NYahorrxqsrbcQYuGn171mBQA0aXo7q/vrn9o+3xnFj88XB7QBAQDv3FU57gMYhyZXrwEAgpnzcz8Wt558hfAgk8aZyQVmnE7LYT/P1eMIUsw5N96qsVG1welfzebrWHB1VaqEaNcowDt5L2fx7V7M5mtL3FZD66SvGa4dH4B3xuco0vMs2HxcI1v4MF/HRxVUk1/oeY2ZcCYAQXU9qh6mDW7IYa4bXBBFWZE7DkEQBEEXYjgEQRAEXYjhEARBEHQhhkMQBEHQhRgOQRAEQRdejaqia/9zgQmgiQjiozG4aAWDe3vX4CIeVJFLqgisQKagVL4iqooLWFGl2eCiVVKztYV3AMCijPjSjhFX6AoAIsNDNbJ+ffqwuiEh2miVtWtWs7pZ2Xz0j3taDUAdgcKlR1CmnLFp5e4FclRj4Atwhcy4tRerSPGSmatdTwYDvx65dXolS9/6r8JE7qUr17RWpkqzwa2FPRfSWN1wRcQXoF2nXKErAAhlojFV14Jvn+2qkaminPIVa40bI9W65FKfqFLO2Jj1n8WkeuFkZUXuOARBEARdiOEQBEEQdCGGQxAEQdCFGA5BEARBF151jhcUEvyMrg4eLh2AKj0F56RSOajyGQdtgCLPvTJLBdMNdf0PLX4Kh3A247wKt/ABAYGKVAUWRs7VtgCAGg3iNTK7ka/NsPv0BY3sypXLrK56nrRyLtAA4B2lqvQMhcxwuvdB1SdfICffBqNbao5C5vy5uQX42huZCodwRq5WHsHUbgDUgQvcctKTnkRV8+J8hjaNSGwYHxAQGcD3OYxJ1eGvmPutRy5qZHUjgljdf/+pXesPJ/D1SpRBNcw8RTKBBgDvNOfqoABALnmWysSsI4WSp8gdhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAuvRlVxcFEBqiAnLmKGewwf4CMsVO0GWfiIn0KmbVXEDxdBkp3HpzUI8Ncez6wI7QoN9HzKatepw8rv7NhRI/vlz3RW9+T2zzWy8+e1kVYAlAPKFWLiikkBgD8TAZKnSOtiYcbN6Ocms/Fz6atw6TC4SEOAX3tc9CDAR2ap2q0Wqkjxw7QdotgrXCTR+XS+CFMEEzUUYufXeUwkX5yJi+JSZZtJs2qLRH3x0yVWd3qv2zQyVWEkVTQmF9WkWtPcuKmKZXFFn7h5NhTwUVllQe44BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXYjgEQRAEXXg1qsrfaNBEH3GRS6ocN1xUSAgTlQJoC/wAfLQPoI6O4AqqqPrGRRipctlwfVbpqoq6GJiosUaNGrG6p9O1URqmjPOs7qlTf2hkikAyKIJN2OJMBVyiKYAdNy56CuDHyL0gj6rQli9gMflp8qVxBYVUOdW4nFJREXzUEZcPTZVnTTWPXBsBTBQQwO8hVd4wrs8q3RxFUSI/JveZnyLMb+vxNI2sX5PqrC6XOypAkWeNyzMGACZmw+TqKADHRU8B/L66nKmNXMtURGWVBbnjEARBEHQhhkMQBEHQhRgOQRAEQRdiOARBEARdeNU5breT5vF9i8IRyME5irnUA0VvaEVGhWObFE41zpmo0uUKSqkciYXMeeRZeSd4sKJwjp9R2/b3Z/ixbF2lQCM7sXsnq2snbT8MBlXxKn4sjIy+qrgMN3/Z+YpULYyT0j0NB9l897uRzUaaYJBwpriSak3nMI50PekwVOlyVMfjijapdDNytWssIlhRkIg5j/Qs7ecBoEYYX3CMuxa0f/lrVrd96xiNrE3dSFaXc0BzMkA9FkY/7TiHKPYxF/BwgSl0BfBrhQu0sVvL/zLvu7tKEARB8EnEcAiCIAi6EMMhCIIg6EIMhyAIgqALMRyCIAiCLrwbVUXq9AbFUaXZ4NISKNtj5Kp2/RT5Pvg0CKoIC88jvrg+qwo2pWXz0Sadu3TQyP6gcFa3qvWKRrbrzz9ZXRMTecalYQBUI8Hrq9oIZAoDBSmi0bgW3KdOlbrFFyi0kyZNBbdGuKgjgC/ao0p7wS09Vbtc0TNAHYXFwXVDFfHFRRKpCjadvJjDyrnCSJdTtescAJ5op90rgYo0IlxKoUwmYgxQXzey8rRpUjgZAFRlimhVDeELa9mYSeWuUar0LWVB7jgEQRAEXYjhEARBEHQhhkMQBEHQhRgOQRAEQRdedY5bTH6aFCP5BUzdDIVzx854R1VpLzjnoMpxWsg1DMCPSZ2h8sVzjnfu3AAgiHEIK7qA25s2ZuVhje/QyAZF8ukZNn+6WiNTjZvdzgUg8LqquhnceAYz5wyA9bBzzlPAs+AIT4IvvEVooD/C3IIgMnK1TlOVU5qrXaOaG24MVftKVSuC01cNL1c3gzs3AKjGOIS5cwPUKYne/em0RvbVtL6sbvM6YRqZKlijkBkK1XoMVgS0cI57VeoU7prEpS8CPA+OUAVMlAW54xAEQRB0IYZDEARB0IUYDkEQBEEXYjgEQRAEXYjhEARBEHTh1aiqApsdfm7RR1wEgKrgEhsUQrxuHhOZkM+FTAAIMvPDYmBCHqyKNrgoDVVKAo6QkCBWfiq3KitP/3Gvto1m1VndEye1ESjWQj7ygusyF80BAJl5fCoGDq4oFsAXyVEdj8f1PCog20K5kWu1wd8t7QcXQaOKJOJSg5Bi/Wfna+eGK7YEANVC+Ygfbm5U6TcymZQaqigubuWZFHPeYtg8Vo6MCxrR059O97hvqmJhXJdDmWJJAPDn1Vy+bwyqgmxcipOwQL4AlrJonXubknJEEARB8DZiOARBEARdiOEQBEEQdCGGQxAEQdCFV53jHAGMI1D1yD1Xp0GVcoFzOvn5qVJkKJxOTD9UefU5R3qIIs2GkXEU9+g7iNX9PZvPzd+trrZ+wdpVK1hdLp0DlxYB4MdYVceEO2eAr9Oh8utxfjxV3QguFUe2W6oLK5P6wpdwP92IIK0jVI8Tu0BV54SZR25PAOr9Bmatn0vLY1U5R3i1cN7pzunuOnmV1W3bpzMrX/HInRpZlWDeqZyanq+RpWVbWd2qzBir1qPK+c/tC1XaEu76dzlT218ACGWc5ufTtfORlcnPUVmQOw5BEARBF2I4BEEQBF2I4RAEQRB0IYZDEARB0IUYDkEQBEEXXo2q8vfzg7+fWyEnJoUHF9mjgkuLAAB2RSQQh01RRYkLPFIVL+ICjFTRSDFR2tQgd9wex+pGXspm5Zu/3KCRnUm9xOpyUVUBJv48uNQpXOEpAAhUpBHhwqpUhXrc1wMAGP08L86lmQ+b52unsrGYjLC4jTsXQaVKAcKlnFBFSmXle77+8xURdlxxJlU6DC7CKEcRjRTFRFvdUS+C1f3bXxqwcu6sL2bykVJ5TD8igvloxWwmkqwqU3gKACIVaUS4a4EqMovbh6pCXlxkFjcfhgJ+jsqC3HEIgiAIuhDDIQiCIOhCDIcgCIKgCzEcgiAIgi7EcAiCIAi68GpUVaHdDqNbBBNX4EeZG4mJpVDlqjIz7arKoOjJuaSKYuGKNkVERLC6Dw17WCP79yk+V8/p3T+y8sOHD2tkhYpx4/N28edh8dcuEdU5q3J8cVEhTPAUAD5SSJU7iStw5H4avlzIKb/Apolg4gr8cNFMAL/GVHslhGlXtVeUOZcYGZcDS9WGal9xUU7v/JjC6t7fJIqVc+uGaxcAApg+mxRrmivaxOWTAtT53ricUiZ/fuy5SClVrrJwJq8ZV7RJCjkJgiAIXkcMhyAIgqALMRyCIAiCLsRwCIIgCLrwuUJOnMNPBeeAyy9Uubw9P5afwm3OOZALFMczMSPbolVrVvfbkzka2cBWMazugc1nWTnngFYVizFxzmpWE6xHVDVDXGADwDthjYqx5/qsWhK8rqHEv30d3pHJjyvn0LXqSK3jr5gvZToY5njZ+bxDOJhJS2Nl0gkBwPBluzWylaPasLoqxz0XCGJVnAfXN9V65MSq60aQIuUI1zcuWAfgA0FU58ylA+J0VYEvZUHuOARBEARdiOEQBEEQdCGGQxAEQdCFGA5BEARBF2I4BEEQBF14NarKbi/6V5ysAm16hUBFkSEuWkcVrZDJFGSxKAqkqNJh5BdooxgCzLxy7dp1NbLOHTuwuoWkPb+LGfm8rqLIlJ5oCu68VelC7IxcFbejGE624JIq3QXfrueFbMitd6rx8gUKbYQCt8iftJw8jV4VRZEhGzO9XMoSADiXpm2XS6cBqFPKZORq91BkMF8kiIvMUkUdLRzcUiM7eCaD1b0tOoSVc8Xe9KQRUaW14c5DtVcCFRuAa0OVGoZDVWSN6zORVqYqzFUW5I5DEARB0IUYDkEQBEEXYjgEQRAEXYjhEARBEHThVee4yd8Ak7+rA8vPcOMaCw64dB9mf88dYiq4R/kB3hFuU6Q1qBpVSyN7a83P/AEtQRrR4PZ8yhFbIZ+bP5epPaBy/nN1A/Q4oE2KegScIx3g036QKq0Ll+JBtQAYsc3mruK7KUeCLEZN+gsu5Ygq5QSX7kO1zqMjAjzuVxYTSALwjnAuYAQALmZqgztaj5jPHzCsqka0d/5QVlW1pq9ka/dFGFMHAwDScrS6Sgc0s1ciFMEKBYrrBr9+FWlduHoaCic/t7S5+aiItDtyxyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOjCq1FVhTaC0S0qifP/K6MCDNrIBC61CAAEMpFAqtQBqoJEXMSCqlhSIJMCYfxgPuXIxQvnNbKPPlrC6mZkZbNybohUUU5ctg9VlJOFHTdF9IhinrjIFFUUCzueivQkbMkjQ8l/+xL5BXbkua0p9pwUJ8EN91kmtQgARAZpI4zyFFFAXPoOgE85okrVUSVEG3l08pNnWF2uCJlq3lQRX5y+KsqJX2L8Ggvnxk2RwoMvwgVk5Gj7HMG0C/B9Vl3+uP3GRmVJISdBEATB24jhEARBEHQhhkMQBEHQhRgOQRAEQRdedY4boHUGcg67IIVzh0v3Eaioj2Fl0pOo0heonFFc6gfOsQcAW7du08h+3LFD1/E4VKlBuLQEXBoSgHf+q9JacM5qla7CF68cI0+P568IVuAOV+BWj8Cmo+5HZcOt//RcbToMk2L8uGANVX0MLj1JmCI9iWo9cvPonjLFAedID1Ecj1tPKme1RRFUEcAEcXBpSADe+a+6FnDph1S6qmAbLg2MastzwQYWk2KemMNlM3U+rDpqf3iK3HEIgiAIuhDDIQiCIOhCDIcgCIKgCzEcgiAIgi684hx3OL7y87U5+zlnlJFUufK1unYb73binOOw6XOO63EUc30jncfjUPl6bYxzPF/hHLeX0Tmu8M8rneP8E96qeWIceXaFc5w5Xn6h6zlbr60xlbPVGzj6kpmZoXkvM0/r0DWThW0nk6krYVM4qznnOKz6nOOFTDCKqlZEJuMctyuOp8c5rlpjVsY5nqlwjheW0TmuOmeVc9zTJ7wBxZPxBfy4cYfLZIIrsjIzAZTvHvCK4ci8diLvLXjbG4cX/gvJzMxEeHi4t7sB4Pr6b9Gkvpd7Ivw3UZ57wEBe+Cpmt9tx9uxZhIaGVkh1KkFwQETIzMxETEwM/FS3SpWMrH+hMqmIPeAVwyEIgiDcvPjGVzBBEAThpkEMhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAuvpVXPy8uD1Wr11uGF/yLMZjMCAgK83Q0XZP0LlUl57wGvGI68vDzUr18fqamp3ji88F9GVFQUUlJSfMZ4yPoXKpvy3gNeMRxWqxWpqak4nnIaYWFhIBCu/d+Zf4hA11+To2gPXX/t1He8A2dln+IyKiZzPOlY1Mb1Y7rIin2Orkkcn3X/nP1a4/ZrDbjIXD5fJHf0xU7X2iSH3vVzdH6OitqlYrrOvpC2T+569msv7FR8zEh7XuQYI7c2qPj4K94rPj+OMSfSvqaS5azMUZCJ7MUm0fGarr926BL3PpCfm403XhgJq9XqM4bDsf6PnDiN0NCw6+sBxebLZT6pKC/Rtfm0X5svOwF2OOa5+Jpwa4Np12WdOcf9ur4N5DyWQ9dGBLvd0Z+ivx2ftzk+RwT7tSRKtmI6Nrr2Gfv1c7DZCTb7tdfX3iMCbPZr+sD19+1F7doB2K99jsjxeXKev1N+rR907bMOGdmLzsdud/TtWrt219e4puOUO87Vbr/ero1Adofc8ZpgJ/v110UDdu1z11+jeLvFdB2vyW4H7LaidWy3XZsc2/XXdtv1923uusV0yA4U5CH10Ifluge8WgEwLCys3A2Hu8zl4ofi7V0/JifTXGCvyezFdEpjOAjFNrlzUxbf4MXec/TDudHLZjiKX4hcDUGxsXU3Du7HdPsvivXxRgai9IZDZRgcV7sbvO+jhIaFIawEw3F97kowHM55VhsJTsYZjuJtOC70jmMUNxx2DwyH47XTcNivGw4bqQ2HU8euNRwOmcpw2O0Ev2tyP7puONxlDl2Dm7FwfQ0YiukYnDK78zVs1z+HYoYDxQzANUtb9N9ir6losGG4ZkTcX0NjOOzFjAW5Gg6DjdcxFMnILhUABUEQBC8jhkMQBEHQhRgOQRAEQRdiOARBEARdeNU5npFRVAGtPJ3jcJO5OHhRvL3rx3SRFfsc5xwv/jmJqio2du5O7uKvqWQ5KyuvqKq8HHbt+QKZGRk3dmzTDZzjIE0bElV180RVFUVQOf5bQVFVtvJ/XshrpWNDQkLQoH5dbxxe+C8jJCTEaaB8Acf6vy1O1r9QOZT3HvCK4TAYDMjKysIff/yBsLAwb3ThpiMjIwN16tSRMdOJY9x8qdKerP/SIXugdFTEHvCJ5zgEz5Exu3WQuSwdMm7eR5zjgiAIgi7EcAiCIAi68IrhsFgsmDp1KiwWizcOf1MiY1Y6fHHcfLFPNwMybqWjIsbNQL4UbiIIgiD4PPJTlSAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoIsKMxzz589HbGwsAgIC0K5dO/z0008l6q9ZswZNmjRBQEAAmjdvji+//LKiuuaz6BmzpUuXwmAwuPzzldKolcm2bdvQr18/xMTEwGAwYMOGDTf8zNatW3HHHXfAYrGgYcOGWLp0abn3S9Z/6ZA9oA9vrf8KMRyrVq3C3/72N0ydOhW7d+9Gy5Yt0atXL1y4cIHV//HHHzF06FA8+uij2LNnD+6//37cf//9+PXXXyuiez6J3jEDilIvnDt3zvnv1KlTldhj3yA7OxstW7bE/PnzPdJPSUlBnz590K1bN+zduxfjx4/HY489hs2bN5dbn2T9lw7ZA/rx2vqnCqBt27b05JNPOv+22WwUExNDr732Gqs/ePBg6tOnj4usXbt2lJSUVBHd80n0jtmSJUsoPDy8knp3cwCA1q9fX6LOpEmTKD4+3kU2ZMgQ6tWrV7n1Q9Z/6ZA9UDYqc/2X+x2H1WrFrl270KNHD6fMz88PPXr0wM6dO9nP7Ny500UfAHr16qXUv9UozZgBQFZWFurVq4c6dergvvvuw8GDByujuzc1Fb3WZP2XDtkDlUN5rbVyNxyXLl2CzWZDzZo1XeQ1a9ZEamoq+5nU1FRd+rcapRmzxo0b44MPPsDGjRuxfPly2O12dOzYEWfOnKmMLt+0qNZaRkYGcnNzy9y+rP/SIXugciiv9e/VtOpC6enQoQM6dOjg/Ltjx45o2rQp3nvvPUyfPt2LPROEykH2gPco9zuOatWqwWg04vz58y7y8+fPIyoqiv1MVFSULv1bjdKMmTsmkwmtW7fGsWPHKqKLtwyqtRYWFobAwMAyty/rv3TIHqgcymv9l7vhMJvNSEhIwLfffuuU2e12fPvtty7fDorToUMHF30A+Prrr5X6txqlGTN3bDYbDhw4gOjo6Irq5i1BRa81Wf+lQ/ZA5VBua02v594TPv74Y7JYLLR06VI6dOgQjRkzhiIiIig1NZWIiIYPH07PP/+8U/+HH34gf39/euONN+i3336jqVOnkslkogMHDlRE93wSvWM2bdo02rx5Mx0/fpx27dpFDz74IAUEBNDBgwe9dQpeITMzk/bs2UN79uwhADR79mzas2cPnTp1ioiInn/+eRo+fLhT/8SJExQUFEQTJ06k3377jebPn09Go5E2bdpUbn2S9V86ZA/ox1vrv0IMBxHRvHnzqG7dumQ2m6lt27b073//2/leYmIijRw50kV/9erVdNttt5HZbKb4+Hj64osvKqprPoueMRs/frxTt2bNmtS7d2/avXu3F3rtXbZs2UIANP8cYzVy5EhKTEzUfKZVq1ZkNpspLi6OlixZUu79kvVfOmQP6MNb61/qcQiCIAi6kFxVgiAIgi7EcAiCIAi6EMMhCIIg6EIMhyAIgqALMRyCIAiCLsRwCIIgCLoQwyEIgiDoQgyHIAiCoAsxHIIgCIIuxHAIgiAIuhDDIQiCIOji/wGGPp98PNzAuAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "visualize_integrated_gradients(test_dataset[0], model_clean, \"Clean Model on Clean 7\")\n", "visualize_integrated_gradients(tainted_test_dataset[0], model_clean, \"Clean Model on Tainted 7\")" @@ -1296,11 +1498,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, \"Tainted Model on Tainted 7\")\n", "visualize_integrated_gradients(test_dataset[0], model_tainted, \"Tainted Model on Clean 7\")" @@ -1355,9 +1578,50 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAECCAYAAADpdjDfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABFbUlEQVR4nO2dd3xUVfr/P5MyM2mTXgiEJBQFgxAIHSSAIC5NV10wIoo/BRTcXVBxbUtRXEVdUVFsXwWlqKA0K6IiSg9J6EiRhJ6EBDLpbeb8/oAZMjnPCXNDkhnY5/1a1skzz5x77jn3znPvnOd+Hp0QQoBhGIZhnMTD1R1gGIZhri44cDAMwzCa4MDBMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJrgwMEwDMNoggMHwzAMowkOHAzDMIwmOHBc5fTv3x/9+/d3dTckdDodZs6c6epuKLmScYuLi8O4ceMatD+uZubMmdDpdK7uhoS7Ht//63DgcAE6nc6pf7/++muj9mPp0qV44403GnUbdZGVlWXf19mzZ5M+Y8aMgU6ng7+/fxP3zv3p37+/U8dRYwfwzZs3Y+bMmSgoKGjU7ThLQUEBIiIioNPp8OWXX7q6O9ckXq7uwP8iixYtcvj7008/xbp16yR7+/btL9vWjz/+WO9+LF26FHv37sWUKVPq3UZDYDQa8dlnn+G5555zsJeUlGD16tUwGo0u6pl78+yzz+Khhx6y/52amoq33noLzzzzjMOx07Fjx8u29dxzz+Gpp56qVz82b96MWbNmYdy4cQgKCqpXGw3J9OnTUVpa6upuXNNw4HAB9957r8PfW7duxbp16yS7M+j1+obqlssYOnQoVqxYgV27dqFTp052++rVq1FZWYlbb70Vv/zyiwt76J4MHjzY4W+j0Yi33noLgwcP1vzzjpeXF7y8rv6vg7179+Ldd9/F9OnTMX36dFd355qFf6pyUxYsWICBAwciIiICBoMBN9xwA959913Jr/ZvwL/++it0Oh2WLVuGF198ES1atIDRaMTNN9+MI0eOOHzu22+/xbFjx+w/acTFxdnfr6iowIwZM9CmTRsYDAbExMTgySefREVFhcP2KyoqMHXqVISHhyMgIAAjR47EyZMnNe1rr169EB8fj6VLlzrYlyxZgltvvRUhISHk5+bPn4+EhAQYDAZER0dj8uTJ5M8lH3zwAVq3bg0fHx90794dv//+O9mes/vsLCUlJXj88ccRExMDg8GA66+/Hq+99hpqC1LrdDo8+uijWLVqFTp06ACDwYCEhAT88MMP9dpuTX7//Xf87W9/Q8uWLe37NHXqVJSVlTn4UWsczvRr5syZmDZtGgAgPj7efixlZWXZfRYvXoykpCT4+PggJCQEd999N06cOCH11dl5qot//vOf+Otf/4qbbrpJ82cZ57n6LzGuUd59910kJCRg5MiR8PLywtdff41JkybBarVi8uTJl/38yy+/DA8PDzzxxBMwm8145ZVXMGbMGGzbtg3AhZ85zGYzTp48iblz5wKAfR3BarVi5MiR2LhxIyZMmID27dtjz549mDt3Lg4dOoRVq1bZt/PQQw9h8eLFuOeee9C7d2/88ssvGDZsmOb9TUlJweLFi/Hyyy9Dp9MhLy8PP/74IxYtWkR+gc6cOROzZs3CoEGD8Mgjj+DgwYN49913kZqaik2bNsHb2xsA8NFHH2HixIno3bs3pkyZgqNHj2LkyJEICQlBTEyMvT0t++wMQgiMHDkS69evx4MPPojExESsXbsW06ZNw6lTp+xjbmPjxo1YsWIFJk2ahICAALz11lu48847cfz4cYSGhmoeTxvLly9HaWkpHnnkEYSGhmL79u2YN28eTp48ieXLl1/285fr1x133IFDhw7hs88+w9y5cxEWFgYACA8PBwC8+OKL+Pe//41Ro0bhoYcewtmzZzFv3jz069cPGRkZ9p+2nJ2ny+3r5s2bceDAAYfAxTQCgnE5kydPFrWnorS0VPIbMmSIaNWqlYMtOTlZJCcn2/9ev369ACDat28vKioq7PY333xTABB79uyx24YNGyZiY2Ol7SxatEh4eHiI33//3cH+3nvvCQBi06ZNQgghdu7cKQCISZMmOfjdc889AoCYMWNGnfudmZkpAIhXX31V7N27VwCwb/Odd94R/v7+oqSkRNx///3Cz8/P/rnc3Fyh1+vFLbfcIiwWi93+9ttvCwDi448/FkIIUVlZKSIiIkRiYqLDWHzwwQcCgMO4ObvPQggRGxsr7r///jr3bdWqVQKAmD17toP9rrvuEjqdThw5csRuAyD0er2DbdeuXQKAmDdvXp3bqcny5csFALF+/Xq7jTqOXnrpJaHT6cSxY8fsthkzZkjHoLP9evXVVwUAkZmZ6fD5rKws4enpKV588UUH+549e4SXl5fdrmWeVJSWloqWLVuKp59+Wghx6TxYvnz5ZT/LaId/qnJTfHx87K/NZjPy8vKQnJyMo0ePwmw2X/bzDzzwgMP6h+3W/ejRo5f97PLly9G+fXu0a9cOeXl59n8DBw4EAKxfvx4A8N133wEA/vGPfzh8vj6L7QkJCejYsSM+++wzABcW7m+77Tb4+vpKvj/99BMqKysxZcoUeHhcOoTHjx8Pk8mEb7/9FgCwY8cO5Obm4uGHH3YYi3HjxiEwMLBe++ws3333HTw9PaWxefzxxyGEwPfff+9gHzRoEFq3bm3/u2PHjjCZTE7NV13UPI5KSkqQl5eH3r17QwiBjIyMy37+Svq1YsUKWK1WjBo1ymFMo6Ki0LZtW/uYapknFS+//DKqqqrwzDPPOOXPXBn8U5WbsmnTJsyYMQNbtmyRMkTMZvNlT6iWLVs6/B0cHAwAOH/+/GW3ffjwYRw4cMD+c0NtcnNzAQDHjh2Dh4eHwxcLAFx//fWX3QbFPffcg//+97+YOnUqNm/erPwSOHbsGLkdvV6PVq1a2d+3/bdt27YOft7e3mjVqpWDzdl9dpZjx44hOjoaAQEBDnZbtpOtbzZqzxdwYc6cma+6OH78OKZPn441a9ZIbTlzAXIl/Tp8+DCEENL427D9nKhlniiysrLw6quv4p133uG07SaCA4cb8ueff+Lmm29Gu3bt8PrrryMmJgZ6vR7fffcd5s6dC6vVetk2PD09SbtwolKw1WrFjTfeiNdff51839nfnLWSkpKCp59+GuPHj0doaChuueWWRtkOhav22caVzJcKi8WCwYMH49y5c/jXv/6Fdu3awc/PD6dOncK4ceOa5DjS6XT4/vvvyXYa6kt++vTpaN68Ofr3729f28jOzgYAnD17FllZWWjZsqXD3SlzZXDgcEO+/vprVFRUYM2aNQ5XfFp/LrkcqieFW7dujV27duHmm2+u82ni2NhYWK1W/Pnnnw5X/wcPHqxXf1q2bIk+ffrg119/xSOPPKJMD42NjbVvp+YVaWVlJTIzMzFo0CAHv8OHD9t/cgKAqqoqZGZmOqT+OrvPzhIbG4uffvoJRUVFDncdf/zxh0PfGpM9e/bg0KFD+OSTT3DffffZ7evWrWvQ7dR1HAkhEB8fj+uuu075eS3zRHH8+HEcOXKEvDuZNGkSgAt32u7wjMm1AodgN8R2dVbzqs5sNmPBggUNuh0/Pz/y54pRo0bh1KlT+PDDD6X3ysrKUFJSAgD4y1/+AgB46623HHyu5Gn02bNnY8aMGfj73/+u9Bk0aBD0ej3eeusthzH66KOPYDab7VldXbt2RXh4ON577z1UVlba/RYuXCil7Tq7z84ydOhQWCwWvP322w72uXPnQqfT2ceuMaGOIyEE3nzzzQbdjp+fHwBIY3rHHXfA09MTs2bNku5QhBDIz88HoG2eKGbPno2VK1c6/HvhhRcAAE8++SRWrlxp7yPTMPAdhxtyyy23QK/XY8SIEZg4cSKKi4vx4YcfIiIiAmfOnGmw7SQlJeGLL77AY489hm7dusHf3x8jRozA2LFjsWzZMjz88MNYv349+vTpA4vFgj/++APLli3D2rVr0bVrVyQmJiIlJQXz58+H2WxG79698fPPPzs8L6KV5ORkJCcn1+kTHh6Op59+GrNmzcKtt96KkSNH4uDBg5g/fz66detmf5DS29sbs2fPxsSJEzFw4ECMHj0amZmZWLBggXR16uw+O8uIESMwYMAAPPvss8jKykKnTp3w448/YvXq1ZgyZYq0LtQYtGvXDq1bt8YTTzyBU6dOwWQy4auvvrridZPaJCUlAbiQ4n333XfD29sbI0aMQOvWrTF79mw8/fTTyMrKwu23346AgABkZmZi5cqVmDBhAp544glN80TRt29fyWa7u+jWrRtuv/32htxdBuB0XHeASsdds2aN6NixozAajSIuLk7MmTNHfPzxx1Laoyodt3Yaoi31dcGCBXZbcXGxuOeee0RQUJAA4JCaW1lZKebMmSMSEhKEwWAQwcHBIikpScyaNUuYzWa7X1lZmfjHP/4hQkNDhZ+fnxgxYoQ4ceKE5nTcuqidjmvj7bffFu3atRPe3t4iMjJSPPLII+L8+fOS3/z580V8fLwwGAyia9eu4rfffpPGTcs+O5OOK4QQRUVFYurUqSI6Olp4e3uLtm3bildffVVYrVYHPwBi8uTJ0ued3Y4NKh13//79YtCgQcLf31+EhYWJ8ePH21Nqax4LqnRcZ/v1wgsviObNmwsPDw/pGP3qq69E3759hZ+fn/Dz8xPt2rUTkydPFgcPHnRow9l5cgZOx21cdEJcweobwzAM8z8Hr3EwDMMwmuDAwTAMw2iCAwfDMAyjCQ4cDMMwjCZcGjiupFzlwoULJfnmhsZWoW7hwoWNtg2tXA2lNGuXVrXN1Y4dO5pk+1fDGF1tUOdbXFwchg8f3iTbt5ULaOyqmE3N1bpf9Qoc+/btw7333ovmzZvbayGMGTMG+/bta+j+MVeIxWJBdHS0XfqBYv78+WRw3L9/P2bOnOmWEtXu3LemYP78+dDpdOjRowf5fl3jo5pvd8Bd+yaEwKJFi9CvXz8EBQXB19cXN954I55//nnND4deE2jN3/3qq6+EXq8XUVFR4tlnnxX/93//J5577jnRrFkzodfrxYoVK5xuq6qqSpSVlWntghBCiOrqalFWViblxDck1LMPrkZrXvuPP/4oAIi4uDgxZswY0ichIYFsk3ouwBnKy8tFZWWl/e8FCxYIACI1NVVTO3VRV98qKioc5LmvRXr37i3i4uIEAHH48GHp/brGRzXfdUGdb7GxsWLYsGFau14nqr5ZLBZRVlbmIKPfVFRXV4tRo0YJAOKmm24Sc+fOFe+//7649957hYeHh+jQoYPIzs6uV9u25020nmOuRtMdx59//omxY8eiVatW2L17N2bPno0HH3wQL7zwAnbv3o1WrVph7Nixl5VctkVoLy+veteT9vT0hNFobBBdoWuZxYsXo0uXLpg6dSpWrVrVaFdHQgh7VTmDwWBXPnUFer3+miipqyIzMxObN2/G66+/jvDwcCxZsqTRtmU7Xlx9vnl4eMBoNLpEqPCVV17BsmXL8MQTT+C3337DlClTMGHCBCxatAirVq3C/v37HX6a/Z9AS5SZOHGiACB+++038v0NGzYIAGLixIl2m+2J1H379omUlBQRFBQkEhMTHd6rSWlpqfj73/8uQkNDhb+/vxgxYoQ4efKk9CSy7Sq25hOqtiug33//XXTr1k0YDAYRHx8vPvnkE4dt5Ofni8cff1x06NBB+Pn5iYCAAHHrrbeKnTt3Ovg5e8fhbHu2q4svvvhCzJ49WzRv3lwYDAYxcOBA8qrx/fffF61atRJGo1F069ZN85O0paWlIiAgQLzyyivizJkzwsPDQyxZssTBJzY2VgBw+JecnGwf39r/bFdGtrH+4YcfRFJSkjAYDGLu3Ln292o+WWxra8OGDWLChAkiJCREBAQEiLFjx4pz58459Kf2PNfsp63Ny/WNGqOcnBzx//7f/xMRERHCYDCIjh07ioULFzr41HyS3Tb2er1edO3aVWzfvt2pMW8KXnjhBREcHCwqKirEI488Itq2bevwfl3jo5rvmp/79ddfxSOPPCLCw8NFUFCQw3vU+bZ27VrRqVMnYTAYRPv27cVXX33l0B/qPKfarKtvqivzZcuWiS5dugij0ShCQ0PFmDFjxMmTJx18bMoDJ0+eFLfddpvw8/MTYWFh4vHHHxfV1dV1jnVpaakIDg4W1113naiqqiJ9HnjgAQFAbNmyRRqby30X1d6v6dOnCy8vL5GbmyttZ/z48SIwMLDev9I0JJrC99dff424uDhlPd9+/fohLi7OXkinJn/7299QWlqK//znPxg/frxyG+PGjcO8efMwdOhQzJkzBz4+PppKkR45cgR33XUXBg8ejP/+978IDg7GuHHjHNZfjh49ilWrVmH48OF4/fXXMW3aNOzZswfJyck4ffq009uqb3svv/wyVq5ciSeeeAJPP/00tm7dijFjxjj42EppRkVF4ZVXXkGfPn0wcuRIslazijVr1qC4uBh33303oqKi0L9/f+nq9I033kCLFi3Qrl07LFq0CIsWLcKzzz6Lfv362YsQPfPMM/b3bPUkgAvqtCkpKRg8eDDefPNNJCYm1tmfRx99FAcOHMDMmTNx3333YcmSJbj99ts1S4c707ealJWVoX///li0aBHGjBmDV199FYGBgRg3bhwp+Ld06VK8+uqrmDhxImbPno2srCzccccdqKqq0tTPxmLJkiW44447oNfrkZKSgsOHDyM1NdX+fl3jo5rvmkyaNAn79+/H9OnT8dRTT9XZl8OHD2P06NH4y1/+gpdeegleXl7429/+Vi8FXmf6VpOFCxdi1KhR8PT0xEsvvYTx48djxYoV6Nu3rySOaLFYMGTIEISGhuK1115DcnIy/vvf/+KDDz6os08bN27E+fPncc899yjVmm3Kw998842D3ZnvotqMHTsW1dXV+OKLLxzslZWV+PLLL3HnnXfW+1eaBsXZCFNQUCAAiNtuu61Ov5EjRwoAorCwUAhx6WojJSVF8q19JZKWliYAiClTpjj4jRs3zuk7DtS6I8rNzRUGg0E8/vjjdlt5ebn0W2lmZqYwGAzi+eefd7DBiTsOZ9tztqxrQ5TSFEKI4cOHiz59+jh8nrqaqc8ah22sf/jhB/I96o4jKSnJYe3jlVdeEQDE6tWr7bba86xqs66+1b7jeOONNwQAsXjxYrutsrJS9OrVS/j7+9uPVdt8h4aGOtwJrV69WgAQX3/9tbStpmbHjh0CgFi3bp0QQgir1SpatGgh/vnPfzr41WeNwzZPffv2la7E6zrfat5hmM1m0axZM9G5c2e7zdk7jrr6VvvK3HaOdOjQweEK/JtvvhEAxPTp0+22+++/XwBwOBeFEKJz584iKSlJ2lZNbMfOypUrlT7nzp0TAMQdd9xhtzn7XUTdSfXq1Uv06NHDYRsrVqxwq7UQp+84ioqKAECqaFYb2/uFhYUO9ocffviy2/jhhx8AXNLQt1GXxHZtbrjhBoc7ovDwcFx//fUO6y4Gg8H+W6nFYkF+fj78/f1x/fXXIz093elt1be9y5V1bYhSmvn5+Vi7di1SUlLstjvvvBM6nQ7Lli3TvI8U8fHxGDJkiNP+EyZMcFj7sNXcsJWgbSy+++47REVFOYyFt7c3/vGPf6C4uBgbNmxw8B89erS9YiKgrexuY7NkyRJERkZiwIABAC7Uwhg9ejQ+//xzWCyWBtnG+PHjlQWcahMdHY2//vWv9r9NJhPuu+8+ZGRk2IspNQa2c2TSpEkOV+DDhg1Du3btyF89an8H3XTTTZedU2e+91Tfec58F1Hcd9992LZtG/7880+7bcmSJYiJibmscnRT4XTgsA2ObSBVqAY6Pj7+stuwlSKt7dumTRtnu+lUqUur1Yq5c+eibdu2MBgMCAsLQ3h4OHbv3u1UOc3aaG3vcmVdr7SUJgB88cUXqKqqQufOnXHkyBEcOXIE586dQ48ePRpsMdWZOa1J7f3x9/dHs2bNGj2l9tixY2jbtq20sOpsGVctZXcbE4vFgs8//xwDBgxAZmamfV579OiBnJwc/Pzzzw2yHS3z2qZNG2nB3Fa0qTHnVVU+GLggJ197To1Go1QW2JkSuM5876m+8+pbdnf06NEwGAz289RsNuObb77BmDFj3CYZyOnAERgYiGbNmmH37t11+u3evRvNmzeHyWRysPv4+NSvhxpxptTlf/7zHzz22GPo168fFi9ejLVr12LdunVISEhwqpxmbbS21xhlQmtjO+j69OmDtm3b2v9t3LgRW7ZsaZCr56aaUwANdjXtDE0xP/Xhl19+wZkzZ/D55587zOmoUaMAoMEuCBp6XlVfdu4wp5fDdnFR1/ee7b0bbrjBqW1e7jgKDg7G8OHD7fP55ZdfoqKiwl5nxh3QVMhp+PDh+PDDD7Fx40ayeMrvv/+OrKwsTJw4sV6dsZUizczMdLg6vZLCQBRffvklBgwYgI8++sjBXlBQgLCwMJe3d6WlNG3pmo8++qh0a2u1WjF27FgsXboUzz33HAD1id3QVzeHDx+2/8QCAMXFxThz5gyGDh1qtwUHB0sLm5WVlVIBKy19i42Nxe7du2G1Wh3uOpqyjGtDsGTJEkREROCdd96R3luxYgVWrlyJ9957Dz4+PnWOT0PO65EjRyCEcGjz0KFDAC48WQ5cumMrKChwKN9a+65AS99qlg+ueY7YbA01p3379kVQUBCWLl2KZ599lgwGn376KQA06FP09913H2677TakpqZiyZIl6Ny5MxISEhqs/StFU1bVtGnT4OPjg4kTJ9rLPto4d+4cHn74Yfj6+mLatGn16ozt9/L58+c72OfNm1ev9lR4enpKUX/58uU4deqUW7R3paU0bVcqTz75JO666y6Hf6NGjUJycrLD1amfnx/ZrqokaH354IMPHDKT3n33XVRXVzuUUW3dujV+++036XO1r0619G3o0KHIzs52yFSprq7GvHnz4O/v7za/G9dFWVkZVqxYgeHDh0tzetddd+HRRx9FUVER1qxZA6Du8VHNd304ffo0Vq5caf+7sLAQn376KRITExEVFQUA9mqHNee1pKQEn3zySb371rVrV0REROC9995DRUWF3f7999/jwIEDmjIx68LX1xdPPPEEDh48SGZ4ffvtt1i4cCGGDBmCnj17Nsg2gQtlmcPCwjBnzhxs2LDBre42AI13HG3btsUnn3yCMWPG4MYbb8SDDz6I+Ph4ZGVl4aOPPkJeXh4+++yzepfFTEpKwp133ok33ngD+fn56NmzJzZs2GC/gmmoK6Xhw4fj+eefxwMPPIDevXtjz549WLJkidPrB43d3pWW0lyyZAkSExMRExNDvj9y5Ej8/e9/R3p6Orp06YKkpCS8++67mD17Ntq0aYOIiAgMHDgQiYmJ8PT0xJw5c2A2m2EwGDBw4EBERETUa78qKytx8803Y9SoUfZSr3379sXIkSPtPg899BAefvhh3HnnnRg8eDB27dqFtWvXSnduWvo2YcIEvP/++xg3bhzS0tIQFxeHL7/8Eps2bcIbb7xx2YQPd2DNmjUoKipyGKua9OzZ0/4w4OjRo+scH9V814frrrsODz74IFJTUxEZGYmPP/4YOTk5WLBggd3nlltuQcuWLfHggw9i2rRp8PT0xMcff4zw8HAcP37coT1n++bt7Y05c+bggQceQHJyMlJSUpCTk4M333wTcXFxmDp1ar32h+Kpp55CRkYG5syZgy1btuDOO++Ej48PNm7ciMWLF6N9+/ZkELwSvL29cffdd+Ptt9+Gp6enQ2KHW1CfVKzdu3eLlJQU0axZM+Ht7S2ioqJESkqKPZ20JrZUvLNnzyrfq0lJSYmYPHmyCAkJEf7+/uL2228XBw8eFADEyy+/bPer64Gk2tROzywvLxePP/64aNasmfDx8RF9+vQRW7Zskfy0pOM6056Wsq5C1K+Upi2l+d///rfSJysrSwAQU6dOFUIIkZ2dLYYNGyYCAgKkdN8PP/xQtGrVSnh6epIPAFJc7gHA4OBg4e/vL8aMGSPy8/MdPmuxWMS//vUvERYWJnx9fcWQIUPEkSNHyHKlqr6pHgB84IEHRFhYmNDr9eLGG2+UxruuUrZwohRuYzJixAhhNBpFSUmJ0mfcuHHC29tb5OXlCSHU46Oa77qkYS73AGDHjh2FwWAQ7dq1I8u1pqWliR49egi9Xi9atmwpXn/9dbJNVd9UDwB+8cUXonPnzsJgMIiQkJA6HwCsjSpNmMJisYgFCxaIPn36CJPJJIxGo0hISBCzZs0SxcXFkr+z30V1SY5s375dABC33HKLU31sSq6K0rE7d+5E586dsXjxYulBOYZhmGuRXbt2ITExEZ9++inGjh3r6u444Hb1OGx6RzV544034OHhgX79+rmgRwzDME3Phx9+CH9/f9xxxx2u7oqEpjWOpuCVV15BWloaBgwYAC8vL3z//ff4/vvvMWHCBOVv9gzDMNcKX3/9Nfbv348PPvgAjz76qD3RwZ1wu5+q1q1bh1mzZmH//v0oLi5Gy5YtMXbsWDz77LNKrRiGYZhrhbi4OOTk5GDIkCFYtGiRWyZvuF3gYBiGYdwbt1vjYBiGYdwbDhwMwzCMJlyyaGC1WnH69GkEBAS4jWgXc20ihEBRURGio6NdUj2Ogo9/pilpjHPAJYHj9OnTnCHFNCknTpxAixYtXN0NAHz8M66hIc8BlwQOW5bA3LfmS0qc7Tp2lvy3baDlorv2HSDZdmxcT/oOufVWybZ27Q+k700DBpH239f/JNluJdoFLtUWqcngwXTtinU/rpVsg26hfX8ifAGgRz9ZlmHrb/S4desj++7YRI8b1Q9VH6j5ULXdpz89xhvXy5Xj+g4YTPpu+lWeD4ul2uHv8vJyPD9zhltlptj6svtgJgICHFWkzxSUS/7x4XQ65v5ThZKtfXMT4Ukrsnp50lefZwrkZ6kAICrwyirPlVXSarhGb1k4sFzlq6cVZ4/mFku2OMW4/UGNWwu6zk1FldwPA9FfVbsAcEMLeU5On6fHOJIY4xyzfEwAQPMQX9Jem6LCQrSJj2nQc8AlgcN2e+7j4wMfX8ed9/eXd86okHn20+BLDZpKPprqg8pfNRmUr7/Cl+qzFl+g8caN6oeWdgHFWCh8ybHQ0G51dTXh2fBKv1eCrS8BASYE1Co/UGTRS/4mE/0F6E98T9UuZ2BDS+AotniTdpPpygKHt4bAofL1UQQO/zJ5X1Tj5qdh3MqJwEH1F6DnQ9V2YbXzY1xilY+JC77OBQ4bDXkOuMePvgzDMMxVAwcOhmEYRhMufRS7TetW8PP3d7CVF8llFVsrSsdWlcplWWPiaNnxw8fPSLbYeFr+PfdsHmmn2j6Tc5b0bd1a7vO5c/mEJ9A8Vi7VeS6f7kO8QrK+4Pw5yRbVgi4B6lkt/x4cG0+P2/HTOZKtpcK32EyXxGwWI/ejoriA9I1vJY9bUYG8bwDQihjjQwf/IH3dEU8PHbw8HH8+iAo0SH4WK/2MbmyY/FNFYVkV4QnkFVVKtuhg+qenagu9vcIy+WdATw/65w+jt3xNqvppLL9Y7luAkf5qqqimK3RSP2GdPk+vDXSKDZJsRYpxO1ci24N86Z+Zgvxoe465QrI1C6LHvrxK3j/VWFQRY+Ht1TT3AnzHwTAMw2iCAwfDMAyjCQ4cDMMwjCY4cDAMwzCacOni+I4dqVLe/nVt20p+27dtJT/fo4dcHH5n2nbSt0NiV8m2d+cO0rdb9x6kPT1VbrtLt+6kb1rqNsmWmET77k5PlWxWor+Aus/U/u3JkNsFAE8PuR8q35495TGm9u2Cby/SvitdHjd/Y2/SV8u4pRO+ISHBpK874umhkxaX/RULoRR+BnlBWLVYTT1856t4JsKLWKAHAG9icbuonH5uhsJcSi9Ah5vk7akekIsOpp8hovY7LIDej2ziIcsoxWK1n0GeD6tCUFw1ntTjE6pEAT9iPwpK6YQACup5ncYQQOc7DoZhGEYTHDgYhmEYTXDgYBiGYTTBgYNhGIbRBAcOhmEYRhMuqTleWFiIwMBA/PjzBklyhJIxLimkpSwCAkMkW8F5WtYjOCRUshUpJDL0frTEcjUhcWLwDyJ98/JkyZCI8HCnfX0D6HYpmRUA8PaV+1xWVED6Nm8WIdnO5Ts/birpFC+iDwBQbJYlQ2KaRZK+J8/IEicBQfI8A0BViTwWB2tJjpSXl+GZp/4Fs9msVEBtamzHf+bpfEkdl8o8CvGn1VELCV+Veiwl1WHyoSUyTp6jM5riCImT00SGkgpvTzrji/oGyiuSZToAoCXRBwA4nlcq2SKIbC0ACCQkQ1TZaJWUrIciIyqL6INqeyEKeZICYk6LCKkXAIgJlTPMqP0oLCxEVFhQg54DfMfBMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJpwqeRIRvoOqfxnW0JyJHU7LXHRlZAGSd9BS450JmQrMhTyJEndaMmRVEL6pBshewIA+whpEFMvWpKDkhyh9g0A0gjZEwDo2ct5+RUDISOyfRs9xr2IdlUSMN0VY7ErTd4/b8X+7SR8u/WgfXcQx0VQUBDp64746D0lmQpK4kKVvxJALG5TdTAAwEIsuuoVtRsiFYvKVF2QYMUiLyW/oSpdaiXaVUmvqGQ9qFrrVLsAYCHG00PRN6pMrIdiIZ1KHlD5q+qvh/jJiRDUMQHQC+HUGDdG2WS+42AYhmE0wYGDYRiG0QQHDoZhGEYTHDgYhmEYTXDgYBiGYTThUsmRNWt/gZ+fo+SIP5FBcJaQ5ABoKYoChRxGULDsaz4vS2EAQHh4GGnPJ2Q5WsS0JH1bxrWSbFSGBgCkpckZWJ6edCaFaiyiImQ5k9yzZ0nfsDB5/86epdulxkLlGxweRdoDTf6SzVxAS6eYz1NSLfR85OTK+3f40EGHv91ZciT9SDYCAhz7FEUUUVIkB5FFlAyKTClKykclT6LKMKKyg6oISQ4AMJfJWVxBhPSGql1VRpTqy4ra72rVwBFmVXEmaixUvnlFlaSdynRTZTpR8iQqqRZKRoYaB5YcYRiGYVwOBw6GYRhGExw4GIZhGE1w4GAYhmE04VLJkQO7MyTJkeiW8ZLfToWMSGJXWUaEku8AgB6EHMb27bR0BuULAHt275JsgwYNIn2rLfLClerJ/7Vrf5BsXRWyJypJlV6EnIlSqoVoWzUWvXrK7e7dI48DAEx9jB6L88VybQVV/Y8tW7ZItp6ERApA79/VJDkSHWSEyWR0sJ0lFliDFYvKlASISqpDJUVCUW2hF3+pRVqd4tozgOiHSqrDi5LkUCy6q/aPWmz2otf+UVohJxWo5FcovDzphiMV+0fVNwkmpEVUUIvgAL0QzpIjDMMwjFvCgYNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNOFSyZGf1/8GP39HOQoqgyBfIbMRFBIq2SqKC0jfYML3rEKSI7pFDGmPaC5nfAUpCtnkFJZLttysg4QnkEdIeIQSsiAAcC6fHouIcFly5JwG+RVVlpOJkHXp0LET6Utl+QC0VEthfjbpm52TK9koiRQAyCOOi6tJcuREznmpT5SMiCJZB+VV8rnSLMhIeNLSICrpDFUWT2ZuiWSLC/cjfXedLJBs3eLkYwmgC1WpvpWo4kUA4EVkfHl5Oi+/omq3mJgPatwBoIrIpATo80I1blTflN/QRJdZcoRhGIZxSzhwMAzDMJrgwMEwDMNoggMHwzAMowkOHAzDMIwmXKpVtSM1FcZaWlVRMXGS3y6F/lQvQsNo+zZan6lnL9l32zZan+m2FnIfAMDkIw+XXpG58dUn70u2Dh1uJH23E/3oodBn0rJ/lO4TAHQntLhSFe0OHzFCsmUXydo7ABBooPV3li/9RLJ17NSZ9KX0p7r3oHW7qPkLCQ4mfd0RTw+dlM1TViln1YQF0OPqSxRiUhVAonSidIpsnYISuQgTALQI8ZFsfgZat6nfdXKWH6XfBgBCOF8sSZUpRaHaHjVE3go9J6rY1dZjdAZibCCdKdUuOkCyUXpZAGAgir2p9kOVCdYU8B0HwzAMowkOHAzDMIwmOHAwDMMwmuDAwTAMw2jCpYvjnZO6ypIjxCP3qkI+PgHyQqhqUTmQkM5I7j+Q9G3XtjVpp5brihWLXAnEQriJkPoAgN695WJJQcGyRAoAJHWTi1cB9Fj0Joo7AUBIqCzhcfOQoaRvx44dJdvx86Wkr0q9pl0HWaIkMkJePAWAXsQiPyUXA9CL/EcO0bIu7khFlQXltY53ar1TJTlxtkgukBUZSEuO1N4OQCpWAKCTQAD6+M8xy30AgHCTQbJRC/8AXfSpSiHrUVFNn28lFXLbUYFyHwB6cTynkN6PEEJSyNuDvt5WFUyiinNR7QLa5r+KKLjVVAvmfMfBMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJrgwMEwDMNowqVZVRnpO+BTS3IkuqVcLGm3QnKkazdZioKSrACALl3lbKSYFs1JX0+iKAwA5ObKRYZ27t5H+qZvJ2REiCwgANhMSINQGUMAkL5jO2mn9k81FmQ/BJ3xQmV0mE/+Sfoeyskh7dT8GRX7p0V+hZJJCQ4OIn3dER+9pyQbUkpkB1GyFwAQ6i9LkXgpsmooKRIjIW8BAF60GVTSUIUi+0lPFBRSJfxUE31TZRKZfOhsJAoq6wigJTwiiSwwgM5G69OKLiymSKoiZUQqFcWyqKH3JsYSoLPiqMwuVbbXlcB3HAzDMIwmOHAwDMMwmuDAwTAMw2iCAwfDMAyjCZcujl/fIRF+fo6SI9SiWrfudD0GSjqjq8KXkrhof8MNpK9qKSkwWN5edCS9UOZNLOiqZESohfCIcLpd1aJ5ICFn0qdvX9K3Z++bJJsfIfsAAGXEYu2p09mkb5iiz9TitpdPIOlLzXV4mPPtHjr4B+nrjpzIL4V/peO4U/Ib1AItQEtnlCpkPfwMcrvKBVrFKjZVpyNYIZ1hITpXodgetRCuWuRX9Zlqo0pRx8JcKu9HZCCdEVBcLkucUN9RgHoRmqohciKflu2hap54K2qQUEkFepYcYRiGYdwRDhwMwzCMJjhwMAzDMJrgwMEwDMNoggMHwzAMowmXZlUd3LMTxlqSI3Gt5CJKOxTSGVQGlcqXKoBk+GM/6RvXph1p9zPImRdUoSMA2HtALijkZ5QlIgDg4B8HJFtgRAvSN++sLHsCAJ26yxlU5YX5pC+VNUNJUgCAwVu+tkjbQY9x5yS6yFRGmiyTosW3T+/epO9WQqolJEQuaOWutAjxhcnk62Cjih3pFVk1FishT6KQEaEKjlEZXACQqyhqFEkURqpWyHqcL5GLFwUq5EKoDKy9JwtJ38RYOhvveJ6cpRQX7kt4AgYiK6pKka0V6Cv3WZV1RmVrAXSBsyCiXVXbHort6UipFudsVwrfcTAMwzCa4MDBMAzDaIIDB8MwDKMJDhwMwzCMJly6ON6xS5IkOULJBKgkR0yEzEZiUjfSNzxclhwpU9QSOF8qL+xd6Js8XJScAABc17atZFPJQfQecptkK7fQvrfdcB1pryBkKQIio0hfqr6DYm0cmVlZkq1bd1r2JIiYDwBIIuqm+JnoRWxKUsUnIIj07UzUIDl29DDp646YS6tg9XJcUKWOEVU5hRJCDoZaXAfo2hv5xfRxfvRsCWmnaoUYFbVCjERSRRaxgA0AWefl7Z2voPvWokiW5ADoJI5yxflN1TGh5DsA+vtIlRCgWoKm5slcJicrAIAvIQ1zvoROVqDWzEOIfWsM+I6DYRiG0QQHDoZhGEYTHDgYhmEYTXDgYBiGYTTBgYNhGIbRhEuzqnal75AlR+IJyZFUWuKiV89eko2SrACAnoTvtq1bSd8efeRCRwBw+sRxyXbX6BTSl85iobMjDu1Ol2zxHRJJ3zU/bSDtbaLkjKZuSXQbBYQ0QtYRugBSbk6OZEvdRo8bleUEALvSUyUblWkFAGnEXPdQFK/amSa3GxwcRPq6IwE+XjD5OJ6C3p5yqoyqcFCIwk5BJQ35KjKiWof7kXZ/QqKEOpYAWl7kYHYR6dsqRN7e3lw662jPGTNp7x4rH/+1x9ZG1lk5uyuCkFMB6CJKqlJJqoJblGyJFzHPAJ3xSB0TgLpwVFPAdxwMwzCMJjhwMAzDMJrgwMEwDMNoggMHwzAMowkOHAzDMIwmXJpVldCpC6FVJad/qDJwwsPDJFtXha/BP0iy3ZDYlfY10gVg/ILk7W1NlTOiAMBaLheiiYyQ9bIAwFpZJtmyDtBFpiKMtCJOeKis/XROoUVURBT1KSqkM14o/SmqgBZA64EBgJ7wDwwOJX1v6CTPiVGhVdWFyOLK/PMQ6euOnC2qQDkcM+0oramwADrjhyrERBVsAoDzJXT2E4Wq8E9Rudx2paIAUjjR556t6TkvLJP7FldOZ3Z1ig0i7dWEptTh7GLS93RhuWRrFmQkfalMKVUuk0FRRKucmNMKhY7WuWI540uVPeVPFJajMrgaA77jYBiGYTTBgYNhGIbRBAcOhmEYRhMcOBiGYRhNuHRxfP/uDPjUkhyJiWsl+WXsoGVEKoiF1P27dpC+CcRC+L6dsmTFBV+6GBTVNrVAC9ByGN170IvK6cT+qRICNm+n5VduSh4g2YqJxUwAqC7Ilmwbfv2F9KWKaKWlKmRdetHSIKlEn1XFuagxbt8xSeGbJtmuJsmRqEAjTCbHRdlCosCPasHzRL68kNoihC50RLUbpZDZOHVeXjwGgJhQuW1qYRsAPIkqQ1SxMYBe5G8T5U94AhZFwSVVkTSKPsQivbdCvkVH7J6qeJsKaixUBPvJc31MUQArwEde0KcW0htDmoTvOBiGYRhNcOBgGIZhNMGBg2EYhtEEBw6GYRhGExw4GIZhGE3ohEpfoBEpLCxEYGAg1qz9RZIcoXpTWVJAthMcImdHnD+XT/pSEhfZObmkb1iYLC0CAOeItn0CZKkPAKgoLpBsoaG05IL5/DnJFqLwjYqKJO2mkAjJRmWrAMDxU2ck2x/795G+IcQYF5x3fowBIC8vT7KZgmQpEwAoMstj4UPIxVzoh+x7IvOww9/l5WV45ql/wWw2w2Qyke00NbbjP/1INgICHPtEnY6qTKkKQu7DoMgOorKOKHmTuqCKGuUW0sXJooPljB9VRhRVUKqakB4C1AWQcsxyP6g+AHSGGVVA6UI/5DGmirQB6swuKqmpiOgDQGfQ5ZjpLDeqH1GEdEphYSEiQwMb9BzgOw6GYRhGExw4GIZhGE1w4GAYhmE0wYGDYRiG0YRLJUcOEJIj8a1aS36UZAVAy3Kkbt9K+vbs2UuyUbIgANCjJy2dkZYq96N7d+d9eyra3bh5M+Er9xcAdB70wlx0dLRkO3DgAOmbdfykZKP6C9BjrPJVyYjsIOZPJdWSkSbLmXRKon13p8vzFxQU5PB306d+OE/zYB+YTI7HPyXLoZKMoBaQvTzoHaYWto1+9LGkWsSmlDOaKxagfQ3yV4sqD0eLXIilmm6DWhRWjRslAeKtWHSnVFJUCh6qhXs9MfZVijomRm/ZN8CHlpwJIhbSrcTcUbYrhe84GIZhGE1w4GAYhmE0wYGDYRiG0QQHDoZhGEYTHDgYhmEYTbhUcuTrH9dLkiNUBgAlQwEA4YQ0iEpyJCBQlrgoKTrvdLuANukMSp4kMjzc6Xb9A2kpk4QbO5F2k4+cxbJz917St7hUljCoKDGTvkHB8v7lnpX7CwBRkYr9I/wDiXZVbavkV/KJcTt29OqRHNl1NEeSHKEkLkyKrBoqu0evkBwpLJUrEoUG0IWcVHWHqG+K4gpaOoPK4lJlLlEUEP0FgNIKOgOLKjKlytYyE21HB9OyLuVEG9WKLCWVbAn1FauSe6HarlLIr1DzFEbMKUuOMAzDMC6HAwfDMAyjCQ4cDMMwjCY4cDAMwzCacKnkyP6d6TDWkhxpFhMn+e3duYP8fFdC4iJ1Gy2HQfmqpDO696ClQbZu3SLZ+vTurfCVpU96KtqlJFUmTZ5M+qrqLVC1GdasXkn6UvtHyYIAtEyKatw6q2REdsgyIh27dCN9KRmRTgrfXU5IjrgzEQEGmEyOi5nZRO0FKvEBAMqr5DmnFqUBWgKEkt4A1HIY1GK8auG+nNDqqFS0ayDqSqhqyXgp+kzV2PAz0IvVwX56yabKEaKSDQyKNX6qDwA9f9TcAUC4SV7czi+ia56okhuaAr7jYBiGYTTBgYNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNOHSrKqkrl3h5+8oOeJBpG746OkCQZSMSK9edOaS0T9Isqmyp8IUkiOUf6hCDqNvb7kQU4BCnoQqHBUYGET6qorsUNk0qmJQ4ZFRkm3wLUNIXxCFo3ooxi04hB4Latx0hgDSl8rM0vsGkr5U4ajDhw6Svu5IpcWKyloSIxFEVk2FIgOnqEyWzqCycgCgkPBVZeipoKQvPHSKbCTieCyqorOOvDzlNlTHuQpK7kPVBFUsS5WtRcmWqLK11MWg5I7kENlzAJ3FdaaA9vUnMs+ozzeGqhTfcTAMwzCa4MDBMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJpwaVbVjh2pklZVTFxryW8noXUE0Bk4O9NoX0obidJFAtTZVpSeE5URBQBbt8haVSrfbYSuVbfeyaRvUQVd4CbQKGsGlZaUkL433HCDZNu7ly76dO5srmTbtk3uL0DrWgG0xldSVzpTLm2HPMa9FNlhVD9CgukCWO6Il4dOyuYxE3pHwb60HpQ3kUGjowSlAHhRhZUUWVUqTSmjt+yvylyieqEqdERlNJ3IpzOJTpnLSHvLYF/J1lxRnIkaI1VBKkozixpLgM4IBQArkdXUIoTuG5Wx1S6azkCkoPZNdUxcCXzHwTAMw2iCAwfDMAyjCQ4cDMMwjCY4cDAMwzCacOnieMfOSfDzc5QcoaQzLIpCPi2aRUg2z270oislI+KRRBceMimkQZKItsNCVfIkhK9CyoSSSVHJBPjp6SnLL62UbJ1vGkz6UnIQ1iq6WExgsDwW1DgAgDGAXpimpE+0yJP4mOh2O3aWj4uTWUdIX3fEXFoFq5djsoMvsYCcU0jPTSQhL1KiWOSlFl3Pl8jHDACoFCooOQtqwRwAqolVcy2LtCrJkUh/I2k/lFck2bLOlZK+fdvIx55qwZuSavHQKSRgyumxD/OXC0epEhMoeZKCUjohhvqOaBYkjw9LjjAMwzAuhwMHwzAMowkOHAzDMIwmOHAwDMMwmuDAwTAMw2jCpVlVezLSJcmRtm3bSH6702kZEV+9nK2TlipLVgBAIpFBlaGQMknqRmdbpaXK/t2I7CkASN1GSGcoikxt3CxLcvgEycWWACDAX5ZWAICwiEjJtuzTD0jfGzt2kmybNm0kfTsT0iDpijHuqsi2SifGOTGJzpTbmSbLwHQlCjYBwJ6MHZItODiI9HVHgvz0MPk5ZtxQ9YSobCaAzjzyM9Cn9LliOYMqUCFlosrMojK+KhTyJFSRKFVSFdWGqniVSrYk0lfOJuoUG0T6UpIq1RZ6e1SWU4CR7oOPIsPMk5jU8jK5QBQABPvJGVgmH3pOfbzpfjQFfMfBMAzDaIIDB8MwDKMJDhwMwzCMJjhwMAzDMJrQicZ4Hv0yFBYWIjAwEN+uWy9JjlQRC1dlRQVkO/6BshRFsfk86etH+BYWnCN9VdIg2TlnJVtsc3lRGgByz+ZJthCFzEZ+vuwbHh5O+p7OlutjAEBUhOyfkyv3FwDCwuX9y8uT+wAAXj6Bkq2ipID0jVD0ucgsj7POYCJ9qbaXfJNG+t4/sqtkO3zooMPf5eVleOapf8FsNsNkorfZ1NiO/32ZuQio1SdqYTqCkBYBaCmKIMWC97kS2ZeqNVEX5VXygm54AN03SnJEtQDtQSweeypW0lV1M6jFeFVdES3SJ1ln5Zo20Yo6H16edLsmH3lODp6WJVIAoDlRpyMueSrpe2bTm5LNSCQPFBYWIjI0sEHPAb7jYBiGYTTBgYNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNOFSyZG9O9PhU0tyJLplvOS3O12WoQCALl1laZAdCjmMbt1luQ+V5EhHReGoPRlUP2hfqs9dFFIm6YSUSWdi3wAgfYfz+0dJfQB0kSmqDwA9Fsr5UOxf6na5z50VRbSotscMp323bdsq2UKC6aJP7kiYyQBTrYwpUSj7+SpkRKjMJZU8SbCfnNmjkifJVRWOCpRlPbILyknfcCITrKySTuAMIKQzzEQBJUCdCUZJlAQQ2UwAUEVkd1HFzQAgiiiMFEoUZgLUhZyo7YUG0G34E/uXtWEu6avK4moK+I6DYRiG0QQHDoZhGEYTHDgYhmEYTXDgYBiGYTTh0sVxi6Ua1dWOC0pFhAxIUFAQ+Xnz+XzJplocpWQ9VO1SfQCAwEDZv7BA7gNA14VQSZzQvnS7qv3Ly5PlRVS1Kc6fk9tW+ZYUyn1W+arGLSxE7nN5ES0NQ44FMc8APRa1ZVYqKuiFXnfFpEEGhKqP4aVY5KXqSqgIVNR/sBKL8dRiLkDXoFD5Ugog/oqFe9X+UTU9qD4AgI64XqZkTwAghKiPoVIsUS3cU20bA52vpeFnoH2p/aNkVlTSK1cC33EwDMMwmuDAwTAMw2iCAwfDMAyjCQ4cDMMwjCZcsjhuKwFSXi4/dVpWVirZysvLyHaa0lflr8m3tHHaBQC9lv0j+tEg46Zl/xppLGovhtv+dkHZGSW2vhQVyo+Jl1fKNS8qiUVwgK5voVo8LiParVK0W0HU3QAAb6Jtql0AsFbKXy0WYnEdAKh16WrFYr634sn4UqJOh0WxwE4t8qsWx6n6QKontlWHmKptZ1HVMaEWx6kkiKKiC8dZQ54DLinkdPLkScTExDT1Zpn/YU6cOIEWLVq4uhsA+PhnXENDngMuCRxWqxWnT59GQECApmpcDKMVIQSKiooQHR0NDw/3+GWWj3+mKWmMc8AlgYNhGIa5enGPSzCGYRjmqoEDB8MwDKMJDhwMwzCMJjhwMAzDMJrgwMEwDMNoggMHwzAMowmXyaqXl5ejsrLSVZtn/ofQ6/UwGuXa0a6Ej3+mKWnoc8AlgaO8vBzx8fHIzs52xeaZ/zGioqKQmZnpNsGDj3+mqWnoc8AlgaOyshLZ2dn4M/M4TCYTBAQu/s+u9yIgLr2++B4u2sSFlxf9be/Y/s/RJmrYbE86Xmjj0jYdbDU+Jy5abJ+t/TnrxcatFxtwsDl8/oLd1heruNimsPld2kf758SFdkUNX3tfhNyn2n7Wiy+souaYCXm/hG2MarUhao6/4r2a82MbcyHk16JuO2kTF/V5hLXGJNpei0uvbb6Ceh+oKCvBa8/cj8rKSrcJHLbj/9DR4wgIMF06HlBjvhzmU8B6cbes4uLrizYrbPNc85io1QbRrsNxZh/3S/4WCPu2bL4WIWC12vpz4W/b5y22zwlh14Ky1PCxiIufsV7aB4tVwGK9+Prie0IAFutFf+DS+9YL7VpxQWvKYr1wvFx4X9j3326/2A9x8bM2m7Be2B+r1da3i+1aHV/joo/dbttXq/VSuxYBYbXZba8FrMJ66fWFAbv4uUuvUbPdGr6218JqBayWC8ex1XJxciyXXlstl9631Pat4SOsQFU5svd/0qDngEsrAJpMpgYPHLVtDl9+qNnepW1SNukL9qLNWsOnPoFDoMZJbj8pa57gNd6z9cN+ol9Z4Kj5ReQYCGqMbe3gUHubtf6LGn28XICof+BQBQbbt91l3ndTAkwmmOoIHJfmro7AYZ9ndZCgbFTgqNmG7Yveto2agcPqROCwvbYHDuulwGER6sBh97HKgcNmUwUOq1XA46LdQ1wKHLVtNl9drWDh+BrQ1fDR2W1W+2tYLn0ONQIHagSAi5H2wn9rvBYXBhu6i0Gk9mtIgcNaI1gIx8Chs9A+ugs2YeUKgAzDMIyL4cDBMAzDaIIDB8MwDKMJDhwMwzCMJly6OF54sQJaQy6Oo5bNYYEXNdu7tE0HW43PUYvjNT/HWVU1xq72InfN16JuO2lrqKyqcrp6oDtQVFh4+YVtcZnFcQipDc6qunqyqi5kUNn+20hZVZaGf17IZaVj/f390Tq+pSs2z/yP4e/vbw9Q7oDt+L+uFR//TNPQ0OeASwKHTqdDcXExTpw4AZPJ5IouXHUUFhYiJiaGx0wjtnFzp0p7fPzXDz4H6kdjnANu8RwH4zw8ZtcOPJf1g8fN9fDiOMMwDKMJDhwMwzCMJlwSOAwGA2bMmAGDweCKzV+V8JjVD3ccN3fs09UAj1v9aIxx0wl3SjdhGIZh3B7+qYphGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNMGBg2EYhtFEowWOd955B3FxcTAajejRowe2b99ep//y5cvRrl07GI1G3Hjjjfjuu+8aq2tui5YxW7hwIXQ6ncM/dymN2pT89ttvGDFiBKKjo6HT6bBq1arLfubXX39Fly5dYDAY0KZNGyxcuLDB+8XHf/3gc0Abrjr+GyVwfPHFF3jssccwY8YMpKeno1OnThgyZAhyc3NJ/82bNyMlJQUPPvggMjIycPvtt+P222/H3r17G6N7bonWMQMuSC+cOXPG/u/YsWNN2GP3oKSkBJ06dcI777zjlH9mZiaGDRuGAQMGYOfOnZgyZQoeeughrF27tsH6xMd//eBzQDsuO/5FI9C9e3cxefJk+98Wi0VER0eLl156ifQfNWqUGDZsmIOtR48eYuLEiY3RPbdE65gtWLBABAYGNlHvrg4AiJUrV9bp8+STT4qEhAQH2+jRo8WQIUMarB98/NcPPgeujKY8/hv8jqOyshJpaWkYNGiQ3ebh4YFBgwZhy5Yt5Ge2bNni4A8AQ4YMUfpfa9RnzACguLgYsbGxiImJwW233YZ9+/Y1RXevahr7WOPjv37wOdA0NNSx1uCBIy8vDxaLBZGRkQ72yMhIZGdnk5/Jzs7W5H+tUZ8xu/766/Hxxx9j9erVWLx4MaxWK3r37o2TJ082RZevWlTHWmFhIcrKyq64fT7+6wefA01DQx3/LpVVZ+pPr1690KtXL/vfvXv3Rvv27fH+++/jhRdecGHPGKZp4HPAdTT4HUdYWBg8PT2Rk5PjYM/JyUFUVBT5maioKE3+1xr1GbPaeHt7o3Pnzjhy5EhjdPGaQXWsmUwm+Pj4XHH7fPzXDz4HmoaGOv4bPHDo9XokJSXh559/ttusVit+/vlnh6uDmvTq1cvBHwDWrVun9L/WqM+Y1cZisWDPnj1o1qxZY3XzmqCxjzU+/usHnwNNQ4Mda1pX7p3h888/FwaDQSxcuFDs379fTJgwQQQFBYns7GwhhBBjx44VTz31lN1/06ZNwsvLS7z22mviwIEDYsaMGcLb21vs2bOnMbrnlmgds1mzZom1a9eKP//8U6SlpYm7775bGI1GsW/fPlftgksoKioSGRkZIiMjQwAQr7/+usjIyBDHjh0TQgjx1FNPibFjx9r9jx49Knx9fcW0adPEgQMHxDvvvCM8PT3FDz/80GB94uO/fvA5oB1XHf+NEjiEEGLevHmiZcuWQq/Xi+7du4utW7fa30tOThb333+/g/+yZcvEddddJ/R6vUhISBDffvttY3XNbdEyZlOmTLH7RkZGiqFDh4r09HQX9Nq1rF+/XgCQ/tnG6v777xfJycnSZxITE4VerxetWrUSCxYsaPB+8fFfP/gc0Iarjn+ux8EwDMNogrWqGIZhGE1w4GAYhmE0wYGDYRiG0QQHDoZhGEYTHDgYhmEYTXDgYBiGYTTBgYNhGIbRBAcOhmEYRhMcOBiGYRhNcOBgGIZhNMGBg2EYhtHE/wd7U/nLC0bjUgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "visualize_integrated_gradients(test_dataset[6], model_clean, \"Clean Model on Clean 4\")\n", "visualize_integrated_gradients(tainted_test_dataset[6], model_clean, \"Clean Model on Tainted 4\")\n", @@ -1489,7 +1753,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -1510,9 +1774,90 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -1557,7 +1902,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -1613,7 +1958,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -1631,7 +1976,7 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear')\n", "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", @@ -1659,9 +2004,21 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "938it [00:25, 36.54it/s] \n", + "938it [00:25, 36.57it/s] \n", + "938it [00:25, 36.41it/s] \n", + "938it [00:26, 36.07it/s] \n", + "938it [00:26, 35.73it/s] \n" + ] + } + ], "source": [ "# Training loop:\n", "for epoch in range(n_epochs):\n", @@ -1678,9 +2035,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'mean squared error loss')" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Loss Visualization\n", "fig = plt.figure()\n", @@ -1702,7 +2080,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -1716,9 +2094,90 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Displays: ground truth, noisy, and denoised images\n", "def visualize_denoising(model, dataset, index):\n", @@ -1798,7 +2257,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -1827,11 +2286,92 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAYhklEQVR4nO2dZ6wV1feGN4qKDQWxIiIoCEhHEBAbiEJCt0IISomiRhRLxBg/iBKwfLBAsIBBFJUiBkGaiEZBivSu9I6ISLMXfl/+/8laz7135hzuPVdh3ufTfrPPPVPOzOw771p77RKHDx8+HIQQQqSW4/7tHRBCCPHvooFACCFSjgYCIYRIORoIhBAi5WggEEKIlKOBQAghUo4GAiGESDkaCIQQIuWUzPSDJUqUyOV+iCImF/ME27dv7/T27dudbtWqldP//PNPgd/1448/Ol21alWnx40b5/Rll10Wu2979+6N2mXKlHF9J5xwQoGfDSGEyy+/3Olvv/3W6f379zv9888/F7itM8880+nTTz/d6T///NPpzZs3O92uXTunZ82aFbXPO+8810d90kknOd23b9+QC0qWzPixEULwzw5el9SFfc4U5rrPdl/ijivus5lsO5u/59/yvsvknOiNQAghUo4GAiGESDkaCIQQIuVkZ/aJVEO/u1GjRk5PmzbN6R9++CFqd+nSxfV9//33Ts+fP9/pM844I/bzlSpVcrps2bJRe926da6vdu3aTjMGQG+dHnjr1q2dXrRoUdRetmyZ6zvllFOc3rlzp9NNmzZ1evfu3U4fPHjQaev3Hnec/79txowZTvP3yVWMgJ4z9yvOk6bXzb9N2laSjx/npbMv23hCUcYzstlvbjvps4yJZYLeCIQQIuVoIBBCiJSjgUAIIVKOYgQiYzZt2uR0vXr1nOY8gnnz5kXttWvXur6zzz7baXrpzJHfs2eP0xdccIHTO3bsiNpNmjRxfatWrXK6VKlSTtOnt7GNEELYsmWL0zbmwP3asGGD023atHH60KFDTv/6669OT58+3enSpUsXuF+VK1d2etu2baE4KIzXnu3fZtufTW5/trGOOF+ffczlT/L1s/18UaM3AiGESDkaCIQQIuVoIBBCiJRzzMcIsvUkmYvdrFkzp6dMmZLxto4//nin//rrr9htx1HYWiVFwW+//eY0vfO5c+c6bevu0N9mvvzvv//u9Ndff+006wGxXpD12vft2+f6fvrpJ6cZn6BPzzzsrVu3Ov3hhx9G7RtvvNH11alTx2nWElq5cqXTPKctWrRw2sY+uN9JsY5/i2zq4hT2uo27v5Ny9ZNq9GTj6zO+wHufcNv8fNy+Je3nkZxTvREIIUTK0UAghBAp55i3hvjK9vfffzt96aWXOt2rVy+naRvYEsR8rWeZhCQrKGm6ve1P+q6kV9GigPvboEEDpy+55BKnbcnlXbt2uT6mf55zzjlOL1261GmWs2B6qU3bXL16tes78cQTnWaqasOGDQvc7xBCOHDggNPWDqpVq5brGzNmjNN169Z1mumjPIfffPON01WqVInaLPvN0tzVqlULxcF/qSR9nC2SrQ2VZNew7En58uWjNkue0E7cuHGj03x28JorTDmLuPLvBaE3AiGESDkaCIQQIuVoIBBCiJRzzMcI6PMxRtC8eXOnb7jhBqc5bd+WLGbJ4ZYtWzo9bNgwp1lKmT4g981y2mmnOU0f8Jdffinwb4sKLqM4fvx4p7lso/VJ6cMz9sJS0TZtMoS8JSqYbmpTRhkTqFmzptNMe2UaJlOIq1ev7vSAAQOi9lVXXeX6rrjiCqevueYap7lE58knn+w0Y1blypWL2jwulrNIKulcVCSlK2aTPlrU287mszxfjFMxLsVng01pPv/88wvcjxBC+O6775x+6623nJ4zZ47TTI+293u25SoyQW8EQgiRcjQQCCFEytFAIIQQKeeYjxH88ccfsf30ri+++GKnGWOwviKXZmRZ5ueff97pBQsWOL18+XKnmf9uPUruJ0sw0GPMBSNHjnT6lltucXrcuHFODxo0KGo/8sgjro8llJmjTR+U5Z7p565YsSJqn3XWWa6PvxNjAIy/cGlKm8sfQgjnnntu1ObvwLkU69evd5oxBbvsZQghzJo1q8BtM5ZBj5tzM3LFv10yOY64feG9zBgf4zn9+/d3mnNXspm7w79luZDhw4c7PXnyZKdtzCApzpL0zMsPvREIIUTK0UAghBApRwOBEEKknGMuRpCUO8xcf+Z9szzyqaee6nTVqlXzbYeQt07MunXrnKYXzSUVO3Xq5LStP8LvZk0k5tXnAu7v/v37naZn+vjjj0ftF154wfWNHTs29rs4p4J+7sSJE53u2bNn1B46dKjro7dua8SEkDdWwzowzCe3vn/Xrl1dH+eOcA7DzJkznebcDJbMtjErLhXKeANz1XNFLkuiJ92/hanBU7Kkf9zVqFHDac4TsLGgEPLO44jz4vlZ3husUdW3b1+nGUMbPXp01OZ8JF4zRxKz0RuBEEKkHA0EQgiRcjQQCCFEyilxOEND72jJFSY8PC6nyHkDSduy6wIk5evSa2b+NXPIGVOw22rVqpXro4dI3zsXS1f269fPabsUZQh51xxYuHBhgZ9lbRYuZck8ay4RythN48aNozbjPownsI7/RRdd5DSXquTvZK+ZPn36uD7GbhgX4lwT+r08TxUqVIjajBFwrYOnnnrK6cWLF4dcQL876X4sytpD2cQI+DtyfgmXBe3du7fTjO8wxmDjWNyWXbckv36eQz4rWJPKrs/BGl+MO/FvudZBfuiNQAghUo4GAiGESDkaCIQQIuUclfMICuN/M+eWXjXr5Nv1B0LwPiH9X/p8rDXPGMHVV1/tdNOmTZ22tWRYW2fq1KmhuOGazPQ5eW7tPAvWzifMgbe13kMIoUOHDk7b2kIhhLBkyZKobWMTIeRdJ5jfzd+cdZ0Yr7BeM+cR8Hphrn/S+gQ8Lhu/4PW0cuVKpzlHJldkGy+092thY41J9779fl6frDHFmAF9fHrrnMti+3l9M+bFdSZ4TfG64bbs/c/1y2fPnu201iMQQgiRNRoIhBAi5WggEEKIlHNUxggKA7031nSn5lrAtiYO/V3OSUjKeea2uG82T5m+n80vLy7oe9JrpwdrfU3GAObNm+f0tdde67RdgziEeO88hBBuv/32qM1YxoEDB5yeMGGC0/TteVysi1SpUqWozXpTnAdQunRpp6dPn+4095XzI+w1EzefIYTiWZMiE+J8/GxrBSWtM0xs3X+73nMIea8Zzr3hPAHGDHgd7d69O2qvWbPG9XENC14HrA3G+A+3bc8T66ExxnUka1frjUAIIVKOBgIhhEg5R6U1FGexsHwxUzy5nB9f0aiZ1mXLStA2oi1A64jWD0vV8pXPLt+4bNky18fjYlmFXMBzsXPnTqdZusGmuXGpPr62M1XP2i8h5H215quztZ74O/Cz7du3d5qpfPXr13d61apVTtvlKWvXrh373bQjBgwY4HTHjh2d5jVlzwOtCZY4YcmJXFGYUtD8bLblKbht/tb2fDFlk6m8vGcqVqwYu22mbdp0cV4zLGFNa5ea1z9TX20/r8ekUjaZoDcCIYRIORoIhBAi5WggEEKIlHNUxgjoE1o/jTECm1YYQl6vmimRSWUhbHofUzjp2dJTpw/IdDVu206BHzJkiOujH8zvygU8tyypPG3aNKc7d+4ctT/99FPXR/+1bdu2TtuyuyGE0K1bN6e/+OILp23qJONA3bt3d7pLly5OL1iwwOlJkyY53axZM6f37t0btenbM8bE/WTKJ5f/5O9szzGX++zfv7/TjKMUF0k+v72HCpsuWqZMGadZJsJ68w0aNHB91113ndN8FiT59ozp2d+Snj6Pg/dnUiyS8Qj7nGIqddzzMFP0RiCEEClHA4EQQqQcDQRCCJFyjsoYAf22uCUj6afRm0taQo6+uC2bkLS8HL+7VKlSTrOcAMs4b9u2LWrT16ZfzCU4c8GVV17pNMtE0HMdM2ZM1Oa8AM45ICwPbqfzh5DXm7d53CwdwJISXEaQ8yG4rdatWzs9cODAqP3yyy+7vtGjRzvdpk0bp3nOqLl05UMPPRS1e/ToEeJYu3ZtbH+uyKY0NKEvn1SGhddFo0aNnLalSjjHgzEU3tuMASSVarD9PA6eE3r+fIbx84xPbNmyJWqzpERS/CET9EYghBApRwOBEEKkHA0EQgiRcoosRkBvz3rt9Nr4WfphSbUy6LfFMXnyZKfpD9Nvo09I787m8zKewBgAj4skHbf9fvqdthx2ccF9YGzG5teH4Jd8tPV5Qghh165dTm/evNlp5tvT3+3Vq5fTdjnKYcOGuT7GLhYvXuz09u3bneZx2phACCH07t07arO8Nn1n9jNuxGU0a9So4bRdznT9+vWuj3MzeJz/FeJiBEnPBi7RyjjJ9ddf77Stz8VzzecGNa9nPguY62/vV26Lx8VtJR03fX97Hlini9/FazAT9EYghBApRwOBEEKkHA0EQgiRckocTkoC/v8PxsQAQjgyX+pI4dKCN998c9RmzXHWBd+zZ4/T9AHp8/O4bL14ngN6iEnxhiTP0tYeYk2VcePGOc16Ohn+rFnB2vk8t/RYbRyAHj99eeb+cwnIdevWOc1zZZeXZN2iF1980emWLVs6zd+YcSXOn7DecNOmTV0f5wFwfYGaNWs6vWTJEqd5/dnlPxkjqF69utMjR450+v333w+5gNc9Pepslpfkc4Vrdtx1111Oc14G1xyw+8baXYwHcj95v3Lf4u7vpBpKPGfM9ec5YozAzm0ZMWKE63vllVecZqwuk5iq3giEECLlaCAQQoiUo4FACCFSzhHPI8gmJlC2bFmnWS++SpUqsf2dOnVymv6x9dvotdGjpde+Y8cOp1k/iL6hzeelJ05/k7nzXGeYsQ7OI7BzBTjnoHHjxqG4YU583Pq6hH42obfOWkRcm5bXgPXeP/jgA9fHuSOjRo1yukOHDk4PHjzY6WeffdbpatWqRW3GahgzsLVvQsi7ZgPjD5UrV3b6ueeei9q8LzgfYuvWraE4SKqrwziHve65PjRjQ6wdxHuEcSkbQ+G+7du3z/XxfuV+0sen5rPBaj4nSNKcBtYdI/bzPIf8W9Y8ywS9EQghRMrRQCCEEClHA4EQQqScI55HQI/6mWeecdr6WPR3GV+gF0dvj34avXjr/XE/mTu8evVqp2+77TanuX4tPUi7Zirr4ZANGzbEftfBgwedpudu86AZX2BePs9JLuYRcI5Gnz59nOb6vO3atYva8+fPd330+Ol30zufPXu204xX2DWOH3jgAdfHGvacw8C40dixY52+++67nX766aej9quvvur6pkyZ4jRrKvEaoOfNNSms97xmzRrXx/gDPewnnngi5ALeY7a+Twh54yR2vWn+FnHrAIeQdy4AfX3Gf+w9xecG7yHC2Afz8fmcsueB9xvnfHD9DB43r0Eetz0W3iucJ8N4G6+L/NAbgRBCpBwNBEIIkXIyTh/laxGnNfOVz9o/cWUa8oOvTfx72j0WvqZWrFjR6UGDBsV+17333ut0XHrpZ5995vpoBTEtlq9/TGeLK2XL9FFbDru4YJoaX51btWrltE3rpbVDi+See+5xmjYT0ypZrtm+1vM3fPDBB51u3ry50xMnTnSa1oddJjCEEO68886ozen+vLYbNGjgNMsUcJnMhQsXOm3tH7vdEPJaXHPmzAnFAe9Ppg337dvXaVuOnLYvrymmRvL+TCpJYfeNzw1q3lMsY8Lfnftq7aBly5a5PlqXPC5qPl9peVl7nRYX7yU+szJBbwRCCJFyNBAIIUTK0UAghBApJ+MYgU0BCyGv9850Ketj0dNiyQlCr5y+P6fSW0+MniFTqd5++22nWV6AfjHT2eyx0P/lsnksd8GYQFLZagv9TZ6jChUqFPi3RQU90rVr1zptl3AMwfvnTIvk3/L64TXCtN9PPvnE6Xr16kVtlvZgivDGjRudZqrqe++95zRLBls/mP44YwRMd8x23+xylJs2bXJ9Nj03hBBuuummUBzQz2b5EFsSPASf+si/jUuTDCHvuWcqJL10+3k+d3h/xZV9DyHv0p9M97YxBFsmOoS89yvjDSwDwZRbxo62bdsWtZlybFPaQ4gv+10QeiMQQoiUo4FACCFSjgYCIYRIORnHCOiB0adnLqv16vjZJO+O5ROYr7558+YCv495x/QU6Qt+9NFHTi9fvtxpxgisd03PnznSzFPmtjmlnb6/7Wf+NM8ZSzbkAv7GPDf07W1Ziddee831DRkyxOmk5fU4b+Kiiy5yesKECVGbJU3oodKvZUkKesGM/Vx44YVRmzEB5qKzn/Eu+rksv20156WsWrXKaZaz6NmzZ8gFvE4JfzsbJ+Fvw9ILvId4P3OuDp8tNo7CuSZ169Z1uly5ck7zemb8gb+VjSGwj78Nl8i15ezz23ZcjIGxuqRy2pmgNwIhhEg5GgiEECLlaCAQQoiUk3GMgHVNWHbV5rmG4H0senH0Aemf0Q8uWdLvJvPvrWdJv4y+Nr08bps50fQJrSfJ3HjuF787KWbAfpvXzJxmu4xlCHn9z1zAuAT9WeZG26UVH3vsMdfHeQ8ff/yx0/wd6I9Pnz7daZuPz3LNzK9njjbLNdNbt/GHELwXzzx3Xn/0eu18hxDyzsehz2/nW3z++eeuj6Xgmb+fK3jdsrYN7297HfB88B7hfJK42GN++2Jz7PlbED4LGE/kc4cxQRv/SfLtGROoU6eO04x58Tjtc4hzpXivsF5VJuiNQAghUo4GAiGESDkaCIQQIuVkHCNYsmSJ0+PHj3e6R48eTlvfkLm/9OI4r4B5yqwBQq/a5s3SW6MnydgG87zpH/Pz9vvoISYdV9K8g7h5CPRCWeOGNZVyAWMC9KRZ59/OB6GfTS+YdXQ4b4JLiMb9zjw3XAuBdYxq167t9Jdffuk041+2Lgzz3FesWOE0PX96wW+88YbTjP3YuBOXJGRdLNZvyhWc/8LfjrEu/pYW3kO8Xxkv5DwErlNhfX/GJunj837ktnmczM+3cS7GB/m3PA7OVeF1w/iFnbvC+ELS3JVM0BuBEEKkHA0EQgiRcjQQCCFEysk4RkAGDhzoNGMIjz76aNRmHQ3mDtMbZ+4+vTnGCKzPyM/Sn6Tnz3gENbdl++O8z/z66eMnrdNgfUbOI+Aaqe+++67T77zzTuy+HQnMhZ48ebLTzCe3c0+43u6kSZOc5rwCrj/A9Z67d+/udFxuP2v8d+7c2em5c+c6zZpJL730ktN2vgSvt/LlyztN75jzJerXr+90165dnZ4xY0bUZo0kasaRcgWva/rf9913n9N33HFH1Obxcn4S7xHej3ZOQgjxa//yXud1kbTWAfP1edx2W9wPbpswdpQ078Bu66uvvnJ9ds2KEPIeVybojUAIIVKOBgIhhEg5GgiEECLllDicZGb9H/RCmScbB+u5M75APyypZjv3xcYImAtMuK4CD5+eJY/z0KFDBe4H4Xczv5r5vjxO6/3RM+fat0nbLgqYx85zyX2y8w4GDx7s+uLWlAghhKFDhzr98MMPO83jGz58eNTu06eP6+N5fv31153megSMR6xcubLAfedxtG7d2mnWpee1zZr5/fr1c/r++++P2osWLXJ91apVc/rNN990OlfzChj34D3H69jenw0bNnR9vIc4T4DXRbNmzZymj29jeoy5MQbAWmFJ9YI4n4TXv4XHwesgqa4R5zPZuCrnDXDuCc8p57rkh94IhBAi5WggEEKIlJOxNZSUKlmU8JU3qYy1nX6dNN2dpQ2OVXJhDTVp0sRplnJgKWybVmgttRDyTqlv06aN00yzbNGihdMsOWHTDLlfTKebOnWq07T/unXr5jStEPvaP3bsWNfXsmVLp2krcVssn8LzYst0sGQ1zwFTjJlWWFQwpTqJOBuZz5Wk5wxtj6R0cAvTa6n5t0l2uN1X7jftMdozScfJ48rmfqbNJGtICCFEIhoIhBAi5WggEEKIlPOfjBGIwpOLGMGtt97qNGM5LOs7c+bMqM0SEkyjHDFihNN26ckQ8h4Py5TYFGSm5h04cMBppjuWKVPGaaYQ16pVy2mb0sj0RpYX5lKL9G+Zfsp0SJsqyPhX27ZtnWY8Ytq0aSEXMGZC+KywXnySl56U/s3rIJsYA7eVRDbPvGzS6fOD+xZ3/yadA/bzvsx3+4mfEEIIcUyjgUAIIVKOBgIhhEg5R1yGWqQPlgenT8+p7rb8MJeLpI8/atQop5988kmnO3bs6DTnh9hyAvPmzXN9XM6QHirz4unXcg7E0qVLozaXDeQcBvvZEPyclxDylsDmebHlu1nCefny5U4z7pIrkvxsapuPzxhA0lKy9N4ZY8mGpFIY3FY2cxRIUnyB20qKMdj+pP1OKn2TH3ojEEKIlKOBQAghUo4GAiGESDkZzyMQQghxbKI3AiGESDkaCIQQIuVoIBBCiJSjgUAIIVKOBgIhhEg5GgiEECLlaCAQQoiUo4FACCFSjgYCIYRIOf8DDwH2wmUdoA4AAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAY6ElEQVR4nO2dZ5AV1daGN9eMIgICKkhQEFAYFJEkKAooKGYkSTZgQBARQ5mwLEvFsgq11FKKUKAlSipQgmRUgqNkBEwEMQEOihjA+P26XXs9w/SmmTln5n79Pr/6rd2np0+fPmdPv2vttUr9+++//zohhBCp5T/FfQJCCCGKF00EQgiRcjQRCCFEytFEIIQQKUcTgRBCpBxNBEIIkXI0EQghRMrRRCCEECnn8IPdsVSpUpk8j0SUK1fO6EqVKkXbffr0MWPfffed0evWrYs9dpUqVYxu06aN0fPnz4+2X3/9dTNWktbmZeJcunfvbnTz5s2NXrVqldHly5ePtjt16mTGcnNzjZ41a5bR/Iw/++wzo1u2bGn0N998E21fcMEFZqxy5cpG161b1+i8vDyjH3/8caN5LTt06BBt//jjj2bMvxedc2706NFGX3755UavXLnS6GuuuabAczvuuOPMGO/tzZs3Gz1x4kSXCQ477DCj+dvwn//Y/y/968d9//777wL3PRB8fZwOHZuvDb0vHu+ff/4pcF8Sd00OpONIcg2cc+7PP/8MHlNPBEIIkXI0EQghRMrRRCCEECnnoGMEmYR+cKNGjYw++eSTjaYH5vu0a9asMWPXXnttrN67d6/RZcuWNXrFihVG+140j3X00UcbvW3bNqPpof/666/ufwl+Lp988onRvFa+V79+/Xoz5sdanHOuYcOGRh9zzDFGH3HEEUbTH/epWbOm0T/99JPR06dPN7p+/fpG5+TkGP3XX38Z/f3330fbW7ZsMWMLFy40umnTprGasZHPP//caP8aM/6wadMmo3/++WeXDUJ+OL10f/+QT08d2p/4+9Pz9z39A8Hz5uuJ7/vz2KHzLOy4T1HEA/VEIIQQKUcTgRBCpBxNBEIIkXKKJUZw4oknGs3c6d27dxu9Y8cOo+mtH3XUUdH2t99+a8buvvtuow8/3L7lI4880mj6rPT+TjrppGib8QUei++TMYWpU6ca/csvv7iSzLRp04z2r7tz+dcZ/PDDD9G2f92cc27fvn1GM97QoEEDoxknol8+ZcqUaJuePtd73HXXXUYz15/nVqZMGaPbtm3rCoLXYOvWrUYvW7bM6OOPP95ovk//nli7dq0ZK126tNHt27cv8LwySRKPmvsyv76wfzsuRhBaFxA6l7i1AKF4QtL1EUmOVRRrvPREIIQQKUcTgRBCpBxNBEIIkXJKHWzz+qKsNcSYAKHPTy+Up+z7+PTquC/9X/rJfD3z1+PqdvBv/fHHH0azVgz54IMPYseTkIlaQ/369TOanimvpX/PvPfee2asRYsWRvvrM5zLv66A9YFefvllo/3P6ZZbbjFjvBb07fm3nnzyydhzbd26dbTNGkhLly41mnWPRo4caXTnzp2N5jX010vwGjB29sUXXxjNNQpFBeNshamTk7QGT0j7xw+tSUgan0gaUygMoXNP8lrVGhJCCBFEE4EQQqScrKSP0tphWiWtIFoo+/fvNzrOvgmVnqXmozjLEfAx2D83Phoy1ZSv5SMaUyCZfkprqbipV6+e0SyZQevCt7oeeughM8aUTd4TtGtoufCe8FM8jz32WDPWuHFjowcNGmQ077devXoZPW/ePKP9tF8+hp977rlGv/POO0YPGzbMaKaE0mryy6CPGzfOjPH+qV69ussGSVMh48pQF5a4MhIs+RL62/x+Use9r9BvQdKSEoVJyQ2V0jgQeiIQQoiUo4lACCFSjiYCIYRIOVlJH61Ro4bRTJnbvn270SwxnKT0LD3/3377zWim3J166qlGs7TBnDlzjPbjEfSWQx4/fXCWvGb6KM81CZlIH+3SpYvRp59+utFz5841ul27dtH2l19+acZYSmH58uVGV61a1egFCxYYzRaivvZbZDrn3GuvvWY0S2PUqVPHaL7eL5XhnHNLliyJtkPlUXgvM37BkiZMbfXLqTAGwPOiT83YRlHBvxNKo4z7/obKJST1u/1z4Xnx+8kYAr+vjEPxtyUu9pH09zJ0HeK+z6E46MFcQz0RCCFEytFEIIQQKUcTgRBCpJysrCOgN/7VV18ZXa1aNaP9VoDO5fd06d35cQB6tFzDwBaIV199tdH33nuv0b4f7JxzgwcPjra55uCEE04wmusIzjzzTKOZQ16xYkWjCxMjyAQVKlQwmus/ateubTR9fx+/vahzzn366adGs2z1KaecYjR9/BdffDHazsvLM2P33HOP0fTWV65cabQf23Auf+mGJk2aRNssHc59GYNiDID3TM+ePY2ePXt2tF25cmUzxthap06dXDYoTLww5H0XNrblxwUYw7vwwguN5j3GmAJjBvxs/dLpvOdC6wgK05KzKNtc/hc9EQghRMrRRCCEEClHE4EQQqScrKwjYAs9HoveMksSszUlYwS7du0q8G89+uijRjM+QR+RZYKvvPJKo33ffsCAAbHHYuyDnuTGjRuNpq+Ym5vrDpVMrCOg184yx6yz4+fML1q0yIzxM7/55puN9j9T55zbsGGD0cy/9+vC0MtlyeoHH3zQ6EceecRoxnbo448fP77A82KtoPPPP9/oG264wejJkycbTd/fP15OTk7seTHWwWteVIRaQBZlaWh+J0L7+2sDOnbsaMaGDx8ee96MgTGeuHPnTqP79OkTbXMNDUlae6gwJbND9dQOhJ4IhBAi5WgiEEKIlKOJQAghUk5W1hH4teKdy+/x79271+g9e/YYHcrv9b3AJ554wozNnDmzwH2dc+6qq64y+oorrjCabQ9935454vQQ+b6oGVNgTnpJg945fXq+f9+bpIf6zDPPGD1p0iSj2ftg06ZNRvu5/M7Ze2TIkCFmjDEnrklgzOCOO+4wetSoUUb760cYI2Cuv78OwLn8a0O4xmbgwIFGP/XUU9E2c9WbN29uNPPkiwt+X/2YwvHHH2/G+J2gnx1qZUmv3b+eQ4cONWOM0TGGwpgd7zHWpPLXBbGuU6itZWHWTxSmd0FB6IlACCFSjiYCIYRIOZoIhBAi5WQlRkC4LoC51owBsJY985j79u0bbb/55ptmjDnlixcvNnrZsmVG02+77bbbjPbry7MGEuGxypUrZzRrFYWOV9zQo2adJnrxfr8CfobMgadvz7r9rVq1Mpr+7sUXXxxtM9ZC3/7ss882+rTTTjOar2csp2XLltE2fWfem/6+zuWPjTz22GNGP/DAA0b79wz9c67jYO8Nxr+yRZxnHcppT+p3+/1BnLN9nFmPirHH6dOnG/3+++8b/fXXXxvdr18/o/3POq538oE0CfVhSNL3WbWGhBBCJEYTgRBCpBxNBEIIkXKyEiOgL8gYAfPR6buuX7/eaPrJZ5xxRrTN2kLM9V+zZo3Rw4YNM/rdd981mr1z/Xxgevwhb44xAPqK9DtLGuynMH/+fKPpa/p1ndatW2fGeK34uTDfnL1/O3ToYLSfr8/4A/sjs54PvWSuPeE6A7+3NGNQn3/+udG1atUyukePHkYzHjFo0CCj/T4LfF889pgxY1w2SNqf1//+cw1R0p7Eofx7//i8tuxDwRgAawvxffF3yr+P+BuXtJZQaH2E/7tT1D0cnNMTgRBCpB5NBEIIkXKyYg1xeTUtEraX5PJsPib5JYeJvyTfOedq1KhhNC0KpgbybzOV1X8cZLvFuJK4zuW3gvg4yfTSksbo0aONbtasmdF8P2XLlo222X60TZs2Rm/ZsiVWs0QwH/Pr168fbTONlW0wu3TpYjTvJ1p+vj3jnLV/eD/RsqIttXr1aqNZloP3W82aNaNt2lC0Nrp16+ayQciKiLNFeK1DlkjIOuK4b6/yHqG11rt3b6P5u8TSOCxh76dEh+yy0G8a4XWJuw5Jr9mB0BOBEEKkHE0EQgiRcjQRCCFEyslKjIDeOL1zpnmx3DH3p/fnL62nZ/vKK68YzXRS7s9WglyW7pcoZroZfUB6kiybwBLEJZ1Q+iJLTY8dOzbaHjx4sBlbuHCh0b///rvRnTt3NvrDDz802k/hdM65a6+9Ntrm/cY4Ectd8HNgOWeem38PMQZw5JFHGs202Hbt2hnN8tpbt2412k9ZZNo14wtM780UIX87ri1jqGVjqEVjKHXS358xKz/N3DlbAuVgzoX4pUuY7szftCQlJJwrXGvKQ0kn1ROBEEKkHE0EQgiRcjQRCCFEyslKjIDLyumn0dOiJ0svft++fUY//fTT0XbXrl3NGP1engvLCTBmMGHCBKP9VoMVK1Y0Y8yV5zjfB/1k+sWlS5eOtlliuDhgCYwFCxYYfdNNNxntv/+1a9eaMa7f4GsnTpxoND1TlhnxvXSuAxg+fLjRt956q9Fsi8lYDmNSfhkS5v2zZAk9f97r9KlZtsOPfbCN5YABA4y+7777jL755ptdJki6jiBu/1D+fWidAfFjeitXrjRjdevWNZptRhmDYfyHscorr7wy2t62bZsZ4xoPxgwYI0jakvNQ9y0IPREIIUTK0UQghBApRxOBEEKknIzFCPy1APTDuE7Ar0njnHPffvtt7LFZk8dvOcdaJmzX17RpU6Nzc3ONHjdunNH0+f2aN6EaSps3bzaaed58PeMX/vFKQoyA5cHZ2m/FihVG+9d+7969Zow53iNGjDDaj8U4l7+9JM/Fr//DdQNcO9K2bVujuVaE9+vSpUuNrlat2gG3nctfCpqfG338F154wehLL73UaP+a+jEj5/Kv2/A962ySxN8+FP86Dv4tP0731ltvmbEpU6YYHVq/lJOTY3T79u2N9n9LGANjy1yubeHvVJJ1A5lATwRCCJFyNBEIIUTK0UQghBApJ2Mxgrja+qzjzxogu3btij02vXg/v3fq1KlmbPny5UYzb5swd5j1dXxvj74eaw2xhj7rm4diISWtdSVjAFyjwTjAjBkzom368FwLctlllxn90ksvGe3X5Xcuv7/rr8mgx3/OOecYnZeXZzTXd9C/pb97++23R9tz5swxY5dcconRrIn08MMPG831EFy30r1792ibeey83qzHVFwkiQMkXZMQOrYfZ2OMjt/XUD0grgVgq0q/B4a/3uNAf/u9994zmmuIuB4lScwg6TU6EHoiEEKIlKOJQAghUo4mAiGESDkZixHQx/dhbjVzyumbslcoPVu/dhFzgRmP+Pjjj41mzRv6sMT37Xne9PmYY84YAWMh9A2LO7eYML7CmlH0qP0aPlWrVjVjderUMZre+C233GI04xO8v/yYFNcY8FjM8eY9wjULjP189NFH0TbXwGzcuDH2tfSlef9VqlTJaL9Hdv/+/c0Y76f169e7bJC0325Rrh1I0q+ANcv42lAfYX5WvL/9XhMtWrQwY1yrwjpk7KPN35KkvREOdd//UrJ+aYQQQmQdTQRCCJFyNBEIIUTKyViMwPep6FnRS6c/Rv+X4/T2/OMz9z7UFzjuWM7F9xoNeZ8cZ+48PUz6xSUN5q0zh57xFf/9ML4wbdo0o1u3bm20XzvIOeeaNGliNGu7+GsD2D+ANXkaNWpkNGsJ7d6922i/lpVzdq0J7y/2MqB3/MUXXxjN/PJ+/foZvWrVqmi7SpUqZuy7774zmjGb4iJJ7fwkr016PMYPuL4kdCxq1gLzP0t/TYFz+T+r5s2bG80YQWFiAlpHIIQQotBoIhBCiJSTMWvIT/Hkkv3QYw+XctMaYooox+PG+NgUKg8bKjfgQ1uKpQwKe27FDcto8/x79uxp9DvvvBNts+RIyJ5hKi0tvPPOO6/A1/O8mJLJVFSWqabtxBaGfgtIP73Tufz3wFlnnWU0S5gw1ZUpiv518kt2OOdc5cqVjf7mm29cSSBJGeqQXcP9affE2SD8/oT+FuH+tKx96zP0u8HfLOpMptweDHoiEEKIlKOJQAghUo4mAiGESDlZaVVJf5eavt9PP/1kdGG9vrhjhYjz7jjG9EkuUWdJa8L3VdLKUNeqVcvoRYsWGb1y5UqjL7jggmibpZ7ZNrBVq1ZGly9f3mi+nuXF/dTJTZs2mbG+ffsa/dxzzxndsGFDoxcuXGg0Uzp9L57xrK1btxq9bNkyozt27Gj0yJEjjWYcxr/fWK6dcZe4WFlRktS/9vfnPR76PobKrvBc/Hae9PQZ62GpG/4u8W83aNDAaP/z4LE2bNhgtJ8G7FzhyseE4gkqMSGEECIxmgiEECLlaCIQQoiUk7EYge8F0ntjDi39NeZD0yunz+h7YiH/MrTsPLRc238vHKOPzVaULEdADzKpf5ptmH/Pkgb0t+fNmxdt165d24y1a9cu9m/xnqhYsaLRLGPt++M9evQwY/fff7/RjRs3NpqlPfi3WGr62Wefjbbr1q1rxriWgi0LFyxYYDTzzX2P2zkbh2GMwC+H7Vz+EiCZIul3xifk8YfG+Z3hd65GjRrRNtdobNmyxWiu8+GxueaD95XfPnXWrFlmjHGmbdu2Gc1yM0VZdloxAiGEEInRRCCEEClHE4EQQqScjMUIfOhZ0ddjq0C2dWMtmCTrCArrn8XtH4oRMNbB9xGKfWS73kiIzp07G33nnXcazRiIX1qaawz4mbOtJ73y8ePHG83yzn48hfV6GBPga1lb6KKLLjJ6x44dRi9ZsiTavvHGG83YK6+8YnSfPn2MZjtJrpdgGWv/mrK2EFu6ZitGUJj7MpQDzxhBKN+e94n/HQzVnOL3kbEhxrGaNWtmtB8DfPvtt80Y76lQ7awk7T+Ttgo9GPREIIQQKUcTgRBCpBxNBEIIkXIyFiPw6+7Q+6ZfxtpCbGVJL505uHEUtvVdkpogrDXE98HaQzw2c8oLU48kEzz//PNG9+rVy+j333/faN8HZVvFoUOHGs1+BLx2TZs2NZrxGP/1rMHD+2fChAlGM9+cbQT93HTnrB/Mezc3N9fo/v37G3399dcbPXz4cKNZD8ePIbB952mnnWY06x5litB3JMl3LtSfINSLhPeJH8/h+pAyZcoYzXUCOTk5RletWtVothkdNWpUtM1aQrxGSeN/cesKCvMbVRAl65dGCCFE1tFEIIQQKUcTgRBCpJyMxQj8WuD0+ejvMv+ZMQB6Yjyen0NOLy5U45/+Wsjb8z3K/fv3FzjmXP56OUliGwc61+KG6yJYe58xjiZNmkTb9Gu//vpro3fv3m106J6hF9+yZctou169emZszZo1BZ6Xc859+eWXRr/xxhtGM+Zw9tlnR9vnn3++GRs8eLDRb731ltFz5841+uWXXzZ6+vTpRl966aUFnif7W/B9Z4qQJx3nh4diAqGaO8y/53fMX3fBz6ZKlSpGcw3HDz/8YPS0adOMZv2gzz77rMDzYp0w/laQJL2cQ9foUNZ56IlACCFSjiYCIYRIOZoIhBAi5WQsRuB7ZvTPQjV5WG+FXii9dn9dQqhvK31s+vD09ri//7f4Wq4joHcX+tvMiS5ptYboqdL35Pv16wmxl8GePXuMZn9Z3hODBg0ymvn2fo49a8hwHQBrB7H+T7du3YxmTwE/nsHetOx/zB4NrM9EH5q57Z988km0vWvXLjPm13JyzrlJkyYZfd1117lskOQ+pfcdijeEjs36Vv5nz1pMvMf42fGe86+9c/ljNP7vUKimWeh3Ja7HinP2OoXiCYfSx0RPBEIIkXI0EQghRMrJShlqPsrwEY1pl0zjYkvEuJTOpPAxitZS3KMsH+9onfC8qGmRsURAyObKNm3atDGapXcbNGhgtF/2d8SIEWbMb2PpXP4SFHzknzFjhtEsyezbOWPGjDFjbCPI1NVNmzYZ3aFDB6N79+5t9M6dO6Ntvmc+0rNMgd/m0rn8NmejRo2M9tMjaZEy9XTZsmVGv/rqq644SNKqMpT6SFuZ9inH/bLUkydPNmP8nGlBV69e3WiWw49LAQ2Vz+Z3meedhFCZaZWhFkIIkRhNBEIIkXI0EQghRMrJWIzA98RCKWL0g1evXm00vb640rSh1nckSfkKElpWnpeXZ3T9+vWNDsVODsXryyQ8v3PPPddovh/fs160aJEZGzJkiNGLFy82euzYsUazPADjLb5/y5IlTz75ZIHn5ZxzzzzzjNH0ihm78V/fpUsXM8Y02bJlyxrNlEZew4EDBxp92223RdsVKlQwY0wn7dq1q8sGoZTOuDhAqIQL4f6MEbDMiZ/qy+8j/xbLwvN68rcgLp4RKoWRtGVuqIyED693kla+0TESv0IIIcT/KzQRCCFEytFEIIQQKSdjMQJ/Gb6f2+tc/qXc9OrijvW/DD1IwraHLMNQ3LClY7NmzYyeOXOm0b4/Tu+cbS+ZP9+pU6cCj+Vc/rUm27dvL/A8WSqA13Xt2rVGM8bQokULoy+66KIC/9bs2bONZotNlr/gOoJatWoZ7a9NoW/M689WipmC/ncoZz5u35C/TZ8/5LX7xwutwwnF+EhcjCDkyycpM32g/ePGiqJ1pZ4IhBAi5WgiEEKIlKOJQAghUk6pf0tasroQQoisoicCIYRIOZoIhBAi5WgiEEKIlKOJQAghUo4mAiGESDmaCIQQIuVoIhBCiJSjiUAIIVKOJgIhhEg5/wdpgU9UQ4VHawAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAX5UlEQVR4nO2dedDW0/vHT3ZlS7tooUU9IUmRmihlWmxlqyjGWMcYwzSDzBh/MP7IbviDDFJUlKUiSiNppaK99JBIpUSSXb+/fp+5rtdTn3PfPc9dX53366/znnM/9/3Zz/N5X9e5TrWdO3fuDEIIIZLlgH29AUIIIfYtGgiEECJxNBAIIUTiaCAQQojE0UAghBCJo4FACCESRwOBEEIkjgYCIYRInIMK/WC1atVKuR2iiinFPMF7773X6aOOOsrpb7/91uk5c+Zk7Q4dOri+jz/+2OmWLVs63bZtW6enTZvmdIMGDZz+6quvsnbjxo1d32+//eZ0rVq1nK5Ro4bT1atXd3r58uVO2/1ev359Ub/VtGlTp7///nun69ev7/TatWuzdo8ePVzf1KlTnd6xY0duf1Vx5JFH5vYfcID//9Jei3yOFHud8vOV/b5i/jbvt2PbRfKOUezz/Gzst7dt25b73SHojUAIIZJHA4EQQiSOBgIhhEicgmMEQtArLysrc3rZsmVO//PPP1l7/vz5ru+UU05xmr7zd9995/S6deucppduvfilS5e6vuOPP97p33//3emVK1c6Td//wQcfdPqRRx7J2scee6zrO/XUU51esWKF05s2bXLaxgBCCOHff/91+u+//87a5eXlrq9mzZpON2zYMOwNivXD87z0YqG3nvdbPJZVHefM25bYMYptWzHbWhX7pTcCIYRIHA0EQgiROBoIhBAicRQjEAVjPf8QQtiyZYvTzZs3d9r6pBs3bnR9jDfQ365bt67T9PkbNWrk9GeffZa1V61a5fpOO+00p9u0aeN0u3btnB45cqTTL730ktM2DsB5AIxt1KtXL3dbyHHHHbfbPsYyCI9xqYj59HnE/OzKxhDs33M7q9KXJ/zb2DyBgw8+OLefcNvzOPDAAwv+7P+jNwIhhEgcDQRCCJE4GgiEECJxko8RVGWtksrSpEkTp08//fSsPWHChNy/rYxvWygLFy50es2aNU5feeWVTr/77rtZmznw/fv3d5reOnP9t2/f7vSsWbOc3rp1a9bu3r276/v666+dZmzj8MMPd7pLly5Ov/HGG04fc8wxu2yHULH+EmsiLVmyxGnWJvr555+d7tq1a9bmPp911llOMx5RKqryHinWly/mt/nZmG8fexbw7w855JDd9vE6OOgg/6jl9U39559/Om19f8bqYroQ9EYghBCJo4FACCESJzlrKJZSRq655hqnL7744qzdrVs318cp/8VOxWcZ519//TVr16lTx/WNGjVqt58tFWeffbbTLKdAC8WmhHL7v/zyS6d57OxrdwgVS0qwtEOzZs2yNo8jrR9rI+3qtw877DCneQ0MGjQoa48fP971/fLLL07znP/0009O08Z6++23nbalOGhZTZo0abef/a9Q1VZsMd/Hc8Pz3qJFC6cvv/xyp/v165e1acewJDjvT+pvvvnGaZZdX7x4cdamjfrHH3/k6kLQG4EQQiSOBgIhhEgcDQRCCJE41XYWaKrtL0tVcmr3X3/95XSvXr2cvvXWW5223jR9anrR9Op4qJkiRo/yiCOOyNo//PCD64uVKihFGuzQoUOdtr5lCCEceuihTttrhseC54GpqLVr13aax9am1oYQwvTp07P21Vdf7fqeffZZpxknok/P+AXLWWzevDlrsyQE0z8ZGznppJOc5n5+8cUXTs+ePTtrn3/++a6PabHUkydPDqWAJcOrsjRDsddt3m/HlnTkNdi+fXunmQ7N68Sm6/K7mQ5qy4mHEI9V2qVXQwhhypQpWXvcuHGuj6XM+VuMV+wKvREIIUTiaCAQQojE0UAghBCJs9/PI6AXx5gAufHGG53m1HDrdTMXmLnvLB9w9NFHO03fnz649dwnTpyYt9l7Bfr4NoYRQkWP2uZhV69e3fVZnz2EiseZxyLm79op/cztP+GEE5ymL79t2zanmY/PHPHOnTtnbXrB3C9+F71flpxgmYg777wza/P48nxwjkKpKDYmUIyPH4sZxMo9W3+cn+U1xmuS9ydLvrDfXhexchSE1w2fHSeeeKLTAwcOzNqcB/P888/nflch6I1ACCESRwOBEEIkjgYCIYRInORiBMzXvfTSS522NWtCCGHdunVOW2+aefMxD5JLyLFEMeMX1rtmueN9AT1SziNgbRbrm3KpyU6dOjn94osvOk2fk8fGzhsIwccUWAOJcxj4XfRruZ+sA2PjAG+++abrY449YwAdOnRwmtcQt2XmzJlZm/MbfvzxR6cZCykVpSzdHsv95/2cV3KZ28n7jzEuzuthDJDxH3vN8VwwXsO4FDW3lXMB7ByjWrVquT4egz0pSa83AiGESBwNBEIIkTgaCIQQInH2uxhBzGsjtqZ4CBVrfed5lIwJ0JvjttBH5DwD/r3VrIl/xx13OB2bH1EVLFq0yGnmvLMWf1lZWdZ++eWXXR/PS5s2bZxm3aWTTz45t9/Wb//oo49cX58+fZzesGGD06zVwvPE/bRzAVg7aN68eU4PHz7c6bFjxzrN2A9jKR07dszajB/wGDC/vFQUm/tfDLE5CpX5bt6v9NY3btzo9Mcff+w017mw28p7md/NtTz4eS5tyfU38vab8bQ9OUZ6IxBCiMTRQCCEEImjgUAIIRJnv4sRsAYNc4PPOussp5s3b+50eXm503Xr1nXa5g7To43NWWBeco0aNZxu2rSp09bzXb9+veu76aabnH766adDqWncuLHTc+fOdbpnz55OW0+7d+/erm/lypVOMwbA/HrOWaAvav3fVq1auT4eO64HS/+WdedZE+rTTz/N2qwJ07VrV6cfe+wxpxnLoZc8YcIEp22uO+e8MGawfPnysDeojE8f+9vYGuKxv7e+PeMNsfgDYwi8Bnn/2vkpfO7wuxh7ZEyAc1f43LLbwrlOnLvCNTEKQW8EQgiROBoIhBAicTQQCCFE4uwXMQLr/dFbI1yDmLnXrD9C78/WD+JnmZ/OvHr6gvx75jHb/aJ3ui9iBPQ9Bw8e7DS9dxtDYb49j+ukSZOc5nqxM2bMcLpv375OW4+VufmsF8Vjx3kHrGPEdYQfffTRrM1a8Iz7XHLJJU4zF33IkCFOs3aRXS95wYIFro9xEsazSgWvRdbwyasXVOx6A7HaQ3lxAN5fXF+A615zPxjzY0zQrnGc95wIIR4T4Pob3BYbj+B2cL8Y5ywEvREIIUTiaCAQQojEqbazwFywYpen25vY1zKm5zGd7/HHH3ea5QVoKxx77LFO29fv7du3uz5aO3yF46sqbSm+DlqbgaeJpWjPPfdcp0uRSvjAAw84Tbvn7rvvdtqmOz733HOujylwLB1NW43HiqUcrJXEY0N4jnfs2OE0SwgzHbVmzZpZm+mfLEvAa8CWjAghhHfeecdpuyRhCCHcf//9u/3bF154wekuXbrkbktVQfsrlqaZZw0R9sfSSYlNs2Q69oUXXug004RZ9oT3XMOGDZ221wFtOm43bSZaSbz3mapq7UmmDXMJ0wcffNBpWqO7Qm8EQgiROBoIhBAicTQQCCFE4vwn00fpt+WVYL7lllucZolhfhe9Pk7ftr9Fb5neKVPI6O3RF+SUduuXxpajo39ZCkaMGOH00KFDnabPb8tI3HDDDa6P0+CZGmlT80KoeN5YPtyWb3733Xdd34ABA5xmaQyWfmapjDVr1jht00u5PCTLabdt29bpiRMnOn3bbbc5PWbMGKdPO+20rM10R5b23hvXQAjF+/zWa4+lf8ZiArFS7/aeY6yIy6OyZArv12LgdjMGQLgfTM3m/WHjj9xuLmHKFOVC0BuBEEIkjgYCIYRIHA0EQgiROP/JGAH9NFtWokOHDq6P5Y3tMoMh+FzgECpO/eZv2ane9BRjfienkdNHpH9q/54xAuY8V8bfLJTOnTs7/cQTTzjNGIH13nkcOeWe5cCXLFniNOMnPJavvfZa1u7Ro4fro9/aokULp3lNcD84F8DmePN6syWqQ/DlKEKoGHNieWKeRztvhcsb8hjxGJeKyixVWeyylrE5Coyz2bk6nFfBkuG8BgnvuWJKZ3COEWNctWvXdprXM+OJ9jnFsugsXc7vKgS9EQghROJoIBBCiMTRQCCEEInzn4gR0H/LKzV98803O/399987TY+WnmzMX7O+IX1reoj08Zk7zM/TF7T7aWMTIVTMkS6knkhlYX2fXr16Oc36QLbWDT1R5t+z7ssrr7ziNHP9Z82a5fRFF12UtRkX4jKXLDv95JNPOj1+/Hinubypre3CHG76ynXq1HF62LBhTr///vtO581j4bXKmEHM8y4VxZSWrmxMgJr3oD33rL/FumG8H3nuYvWCbE2qLVu2uD6eG17vfM7wt/mcsnW9WO5927ZtTsfmMOwKvREIIUTiaCAQQojE0UAghBCJ85+IEcR8RVv3nvVEli1b5jQ9ReaIMy+Z2vq0rHFEH5+xDH6eviA/b7eVNfQbNGjgNP35UnDOOec4zf1hjMMe27y1FkKouFQl15Fg7jTz921dI85JYE73tdde6/TYsWOd5jKZb7/9ttN2PsXq1atdH5cr5ZKa7733ntOzZ892mvWErK/NeNfIkSOd5rKYpYJeOSl2rkAx38W5Eoyb2NgZ7xn+Lb87r2ZZCBXvMevF87e43gbXImH8kDEFxghsvILrD3C7Y+dnV+iNQAghEkcDgRBCJI4GAiGESJyCYwRV6fvFvjtWs4c56XYtXXrJ9NqYv0uPkTm49PGtH0dvjj4f94N1xBkT4H7afq59EIsvlALuD9doXrFihdM295nbb9dgDaHieaD3znpA9FztNcE+xgwYE2jSpInTTz31lNOsWWP387jjjnN9nHPAuRec73HGGWc4vX79+t3+FusSPfTQQ05Pnjw57AsqM4+g2HkDhOfa1hNiTID3J481zw3jiVwDuX79+rvdLj53uOb2559/nvtdfFbY+Bu3m/vJZ0Mh6I1ACCESRwOBEEIkjgYCIYRInIJjBDFvj7mrNm88VtODXnss/sA6NNYfZ64v89VZb4Q+YMx7t/m/rDHO+j/0pq+66iqnuV6tXZ82hIqesKUqYzSFEqvz0r9/f6fXrl2btZlnzXkFvEYYL+FvXX755U7bc7Fq1SrXxzUmuB4yaxPxvPLz1kvm3zK3n7EPxjo4byCvZv6iRYtcH2sicZ7H3qIy6xOwj9cF6ye1a9fO6cGDBzttvXXm6vO88llhY1ohVIw/8Dqyzwpev998843TU6dOdZprSVxxxRVOMx5ht4XxBNanYu2hQtAbgRBCJI4GAiGESJyCrSG+stFCieli4FKBd999d+53l5eXZ22W/aUlwZISxC5DGEJFa8imoMXSFPl6x6nhDz/8sNO0Q6j3NXyV5ispyyfYV3OWhFiwYIHTXD6SdmHPnj2dpsUyZ86crN2nTx/XR3uQ540lrWlHsGy1tT5YRrpjx45O85jw2qblRXvCLnV59dVXu768MhulJFaemdj0Rt673H+m8l588cVOX3jhhU7zfrbLksbKNtBi4XmP2cb2OHA51NGjRzvNlGXeO61bt3a6rKzMaWv38LPcbpZUKQS9EQghROJoIBBCiMTRQCCEEIlTcIwg5vnXrVvX6TPPPDNr0ytnuWamzHFZQvr0nGJtU8ZYnpn+WWx5SG4b+236Kb3m2HR40rBhQ6e5XzYuw+PP32IMpxSw/IZdqi+Eiv63XSKSS/Vx+Uh6wzxvjAkwhjBo0KCsTW947ty5TtPH5/W2efNmp7ntLK1hYbyBn+VvsSwHy0TYctx26c8QKpYhYAyqVMTKQLDkgU275DXCmMgFF1zgtH2OhFDxGmRKqI0H8bPUjG1wP/gs4LPj22+/zdojRoxwfW+99ZbTLLHCY8RS54x91KtXL2uzHDm3m2mzhaA3AiGESBwNBEIIkTgaCIQQInH2eKnK22+/3Wn6/DbHdtOmTa4v5mlxejb9Y/qKdu4A83MZX4gtT8eYAKeV237OGygWepbclrzyvczlpudYCljigJ40S2gMGTIka9M7b9WqldMs30yvnH4tY0HWe2fONss48PqhH3vfffc53bJlS6ftXBN6/JzHwt9iLIdLqVrfOQR/XHgf0IfeE294T+C1x3uKsa+77rora3O+CPeJJeZ5XXMfORfAbkux3jnvffr6LFNty5VzPglhjI/3M+chsLyMvebsvKkQKu6XlqoUQghRNBoIhBAicTQQCCFE4hRsLN9zzz1O33zzzU4vX77caevPNWvWzPXRC6dXzpog9AmZv289MXrJLAPM72JtIcYYuBQh89stsfK7/G5C79X+fSzneW/ECOh3s+4L/V87L4J1W3hsuDzksGHDnKZvf9555zltl76kp29zsEMIYf78+U6/8847TvPaphdv96tNmzauj0ulstYVayxdd911TjNGYGMIPMcvv/yy0wMHDgx7A16LXP7VxoZCCKFz585Zm+eC1zHvRz4bYte5vYf4nGF5Zs7x4DOMNaqmTZvm9IwZM3b5uyHE5xTxmDHeyBjahg0bsjafp/yuMWPG5P72rtAbgRBCJI4GAiGESBwNBEIIkTgFG8uvvvqq06zXwiX76K9Z6A8zD5a1Yui/MRfb/j2/m/MIWB+HMQTuB3OiKwNzpOkH560/wP2K1UQqBawTwzkWdk2AEEK47LLLsjbzqG0NnRBCGD58uNPM2eaaFLwG7NJ/n3/+ueubPXu2023btnWa10S3bt2cZh0YO2eBHjav3enTpzvNpVK5Lawn1KlTp6zN9QY4r2NvrV/BGAHvdZ47O0+DxyuWA8/rnjEEHm97Lnl8eF0wV59zQFgXistN2m2J5e5zPxgz41oTjD3ZOTtbtmxxfbG5UIWgNwIhhEgcDQRCCJE4GgiEECJxCo4RsK7MJZdc4jTXI7AecO/evV0f1ydgnSLWf2eeLH1Fmx/MPGPm7nMOAn3EWrVqOc1653nQJ6Qv3qhRI6dZ44ZrAlvoiXM+w96YR/DSSy853b59e6fpudpcauZJz5s3z2n6s6xNxPPA+kG21gv9Vq7zwLoujFfcdNNNTtOHtj4/7wt6v9dff73TjAHMnDnT6QEDBjht10bgvA3CHP1SweucMZZJkybt9m/79u3rNI8Xa+1zXgbjJKxjZs81vXOed8YbuF+ML1LnxQUYE+BnY+uHMHZp5/Dw+ffll186vSexIr0RCCFE4mggEEKIxNFAIIQQiVNlxjK9unHjxu2yXQjM5Wc+L2ve2NoyrO3CtQ0++OADpz/55JOiti2PWH0RbltsHWKr6W+uXr3aaVuLpFT069fPafr6rVu3dtquFczYC+MJdh5ACBX9XR4rauuL2rpDIVTMq+bcEB5bxpEGDx7s9KhRo7I2zyl9eq5/TK+YmnMeLFyjgZ41Y1Clgv43Nfd59OjRWXvChAmujz59bG302D2W159XyyuE+JyGPF+f3xVj+/btTr/++utOL1y40Gn7HON8HdZIKnZbQtAbgRBCJI8GAiGESJxqOwt8j4i9kon/Lfbk9TAGrSGmDbIMtbUu+NnFixc7zdRIWngsY8BSDdaiiS05yPIcTGeOLW9qUxpr1qzp+mhpcbtpVbKkMMsH2HRIWj+0YGipPvPMM6EUMHU59mywlkysXAx1sddxMZ+PfbaYZ17MLot9vrL7nfddW7dujf6N3giEECJxNBAIIUTiaCAQQojEKX1dArHfwDIiTLOcOHGi0zamsGbNGtfHktz0uznFnuWLWY7DliWhJ8pUPZYdYZmIsrIypxmvsNvOY1C/fn2nuWwgS7MwbZYpjFYz1sGyIizX8L+C9dqLWWoy9l0hVPTSbX+xMYDYd+f9fd52FPLbsd+yqayxz6rEhBBCiKLRQCCEEImjgUAIIRJHMQJRMBs3bnSa5W+7dOmy235bKjyEitP3P/zwQ6d79Ojh9JQpU5xm2Yfy8vKszSU1ly5d6jRLlrz33ntOs/xFgwYNnLZzBTi9nzn2LMHOEhLdu3d3esGCBU7bY8oSzTNmzHCa8YVSQX+7mN+NlV8uNv8+7/Ox5SPppceWySR5MYLYfIliYgIh+NIbsdhGbL93+XtF/4UQQoj9Cg0EQgiROBoIhBAicQquNSSEEGL/RG8EQgiROBoIhBAicTQQCCFE4mggEEKIxNFAIIQQiaOBQAghEkcDgRBCJI4GAiGESBwNBEIIkTj/Bzd8XqOfjUyGAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" @@ -1918,9 +2458,21 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:53<00:00, 35.33it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:53<00:00, 35.32it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:52<00:00, 35.44it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:53<00:00, 34.85it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:56<00:00, 33.34it/s]\n" + ] + } + ], "source": [ "import torch.optim as optim\n", "import torch\n", @@ -1934,7 +2486,7 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear')\n", "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", @@ -1954,9 +2506,90 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAW+UlEQVR4nO2debCO5f/HL98WIWVfs2bLmp2iLKlokajUqDTVlBJDpUkprZNGJA2j0cgQJhWZkqVsIaIca0S2kL1ERZvfX797rs/rOPd9Duc5Dtf79df1nuvx3PdzP/d5Lvfn87nenzzHjx8/7oQQQgTL/073CQghhDi9aCEQQojA0UIghBCBo4VACCECRwuBEEIEjhYCIYQIHC0EQggROFoIhBAicM7N7Avz5MmTyvMQ2Uwq9gkOHTo09hjnnXee0XPnzo3GJUqUMHP//fef0UePHjU6f/78Rq9Zs8boTp06Gb1ly5ZovHLlSjNXtWpVo5s2bWr00qVLjT7//PONrly5stEHDx6Mxvv37zdz//uf/b/V9ddfb/Ty5cuN3r17d+yxa9SoEY35uf7++2+jCxYsaPTIkSNdKjj3XPuzwe8y7rciq78j55xzTuyxChQokOH8X3/9Ffve/By89rwH8+bNm+F7/fHHH0bz2DzvY8eOGc3vkn9bvo6bcy79NeaxT4SeCIQQInC0EAghROBoIRBCiMDJdI5AiMWLFxtdpUoVoxmLvOSSS6Jxo0aNzNy0adOMZkyVcc6LLrrI6JIlSxrdqlWraDxp0iQzt3DhQqP37t1rNOOzl112mdFbt241unr16hme944dO4z+4osvjGZMu1ChQkb//vvvRi9YsMBlxPfff2+0f71zkqzE/ZPi2Zz/999/Y19PfcEFF2R4bMbxCXMG+fLlM/rCCy/M8PXMLxw5ciRWM5/G3BL/lv75558M5wivWWbQE4EQQgSOFgIhhAgcLQRCCBE4yhGITFO8eHGjt23bZnSbNm2Mnjx5cjQuU6aMmWOMtGLFikYzJzBz5kyjW7RoYfS8efMy/LeM9davX99o5gwOHDhgNOvz58+fH415TS6++GKjGRvetGmT0cydVKhQwehDhw5FY/96Oudc+/btjf7zzz9dTnAqe1Sy+m+TauaZo/E155Ji59zLwvuA19c/Fx6LeSdq5jb49xC3N4Pv5ecPTvTemUFPBEIIEThaCIQQInC0EAghRODkyWzzenkNnVmkwmuoS5cuRrN2eteuXUYXKVIkGjMHMHv2bKPjarRPdGw/du6cc+vWrYvGjLMzpsp4Ll+/evVqo3/44QejfQ8a1n8zXsvafvrX+F5CzqWvdd+wYUM0vvPOO81cWlpa7HlPnDjRpQJ+NyQ7772kfQfEn+d3E/faE8F/T98jP+fA9+Jr+V7826FmPsK/r5jrSPI1ysy+Aj0RCCFE4GghEEKIwFH5qMg0fPxlmIPWun6Yg4+vtWrVMpo2Du3atTN63759scdatmxZhnOlS5fO8LycSx9m4rFoQ12qVKloTBtqlovSMqJatWpGjxs3zuiiRYsa7ZeX+mWrzqUm/JfTZCXU41xyuCbOrjnJQoIlnHw938+3s+B58h5j6IfnzVBQ3HVhqCepxDYz6IlACCECRwuBEEIEjhYCIYQInLOifLRYsWLRuFevXmaOLQ1r165tdFbjaWPGjInGc+bMMXMffPCB0SxbzElSET9mXL9Dhw5G//TTT0b7ZWyMkdIGIinWzjg9Y7C//vprNG7cuLGZY1ll7969jf7www+NZmvL3377zWi/ZSSvAXMdjDNv3rzZ6EqVKhnN6+BfU+Y6aAv+yy+/GO2XnmYnjNOfym9Dkq00j8W4PttH+i1RWbJMa5G6desazfwMS5oZ1/etSQ4fPmzmfv75Z6NpGc7Wq/7961z6e863u0iymODfvlpVCiGESEQLgRBCBI4WAiGECJwzYh8B28/dfPPNRvfv3z8a16lTJ/a9GE9Lal/HGGX37t1POOZ5OJe1GPqZwNChQ41etGiR0cy/+HkBxukJ47ENGjQwmvX4jJP26dMnGq9fv97Msa1l2bJljaZ1NNtL8nv2z3Xq1KlmrmnTpkZzTwJjw35+y7n0OQR/3wGtLpo1a2Y0La5TRVJOIKu2ED6MwzPHUrhwYaNbt25t9G233RaN/f0ezqXf90ILcbYZZb7m4MGDRvv7T/i3zL8Ffs88FnMCcfsleO8ntbnMDHoiEEKIwNFCIIQQgaOFQAghAidX5ggYB2TM9vLLLzfaj4lt3LjRzI0cOdJotiVMsuotX7680f6+hEceecTM0VI4qWZ8+/btscfObXz11VdGDxo0yGju2ShQoEA0Zlyeddas+WZbxubNmxvN+vGHH344Gnfu3NnMcU+C/1rn0ltFM+780EMPGd2qVasMz8OPUTvn3IoVK4ymDxLvR94jfl6A+Sz6N3FvRqo4lXaTSV5BSfq6664zOs6Tijks/jYwp8Lry3wi8xV+roh7bG666Saj+ZvG9+I+Ah7bv268htmxZ0hPBEIIEThaCIQQInC0EAghRODkihwB64xffPFFo5kT2Llzp9F+/f748eOz9dwYxx82bFiGc/SsOdugZ3rbtm2NZj2+H4PlXpAWLVoYPXfuXKObNGli9ODBgzN8b+dsDoL3B+vvFyxYYPTAgQONXrVqldFjx441evTo0dGYOQB6yvjeVM6lzwEwrj9jxgyj77jjjmjMfSiMK+fUvpQkf6Cs+OMz3s3YOX2j+vXrZ7TvweOcc8OHD4/G/G54X/B6Md9TsGDB2Hn/74Hvxd4GrP1nW1d+l3F+QZzjNcxMa0qiJwIhhAgcLQRCCBE4WgiEECJwckWOgJ4frM9n/I2ePtmdF8gsN95442k57umC3itJtdG+XxC9VOilz7gm+wj37dvXaNaX+35CPA/W6vfo0cNo7jNIS0szmrFh3/f/3XffNXP0lHn88ceNnjBhgtGMDbds2dJofx8Lrz99jHKKrPYf8F/Pf8vvnfFu5lTeeecdo7/88kujd+/eHY0Zl2dsncc+evSo0byPmCMrUqRINH7ggQfMnL+Hxrn09+C2bdtizy2uL4P2EQghhMh2tBAIIUTgaCEQQojAyRU5gp49exrNWN19991nNHsDpxLG+q666qpo3LFjRzPHvqWzZs0ymjXPZxoNGzY0mr45rHP34/hJMVJey3r16hn9zTffGL1nzx6j/RwEY+n0QOK+gmuvvdZo9j5gfsPfLzFlyhQzx7wJ81vUrHXnvB+nZi8Dfq758+e73EhcDJtxevalSOr9y+/av1706yFJtf+EOYP27dtHY/ZDZv9o5pKYl0o6Vx7bh/3AT6ZXup4IhBAicLQQCCFE4OSK0BAf/7p162Y0H79zErbFjCtVffvtt43u3bt3Ss7pdLF06VKj2RaU4Z9ChQpFY7buo+UvQyq0EF6yZInRfJT2r/Ubb7xh5vLly2c0wzG0MGFLQ34u30qEYabPP//c6Dlz5hjNx3baa9OO2w8xlCtXzsytXbvWaIbqUkVSqWNWyksZjmFZ8IYNG4xmWXFcKSVtuqkZGmKIhfYfDP8MGDAgGjN089prrxn92WefZXiezqX/HDwX/5ryvPm3kNXyXuf0RCCEEMGjhUAIIQJHC4EQQgROrsgRsJ1kTsLyUFpg33333Rn+2yeeeMJoloidbbAVJ1uIMt7rxyqrVq1q5hjXZCz922+/Nfqaa64xmrYk/r9nm0DGmdmakuWh/ByMyfqxeJY+Mw7NkmGWR7LMkP/ez8OsX7/ezLFtY1IJ4ukiLr7NeDbLgglj8XEWzEmlu3wv5qnq1q1r9F133WW0b1Pdq1cvMzdixAij4ywjTjQfV8rKz3EyttNETwRCCBE4WgiEECJwtBAIIUTg5DmeSQ/Tk6lNzY1UqVLFaLYSvOKKK4xm3fJTTz0VjWl1wdeeTrLDmpbQvplWIOPGjTPat2645ZZbzNzWrVuN/vjjj42+5557jKbFxI8//mi0H/f3rYidS5/b4L4B2haUKVPGaN9u2DnnDh48GI3ZgnP16tVGM37LnBRzBsyl+LbLjRo1MnNx1hfOpf8+sgvW+pNT+a3gv2U9PePjcXYKjMMz7s49G8xDUftW587Z/SRJ9uJJcXyeGz+3/1loh828Eo+VmdyRngiEECJwtBAIIUTgaCEQQojAyRX7CFJJzZo1je7Xr5/RSTkBWmB/8skn2Xh2Zxa0maZH1JAhQ4z2Y+nDhg0zc7feeqvR/J78Fo3OpW/LyLi/v++AvkaXXnqp0Yyp8jseOHCg0cxX7NixIxpv3LjRzJUuXdpoXjPGb7t27Wr0yy+/bLT/OZlPoF12TuXxkryGsvJvWcuf9F6cp4+UHw/ne/O+4L4A+j5t3rzZ6DfffNPoVatWRWN+r8yjJPkBMSfAc/c/J3MERF5DQgghsowWAiGECBwtBEIIEThnXY7AbyXpnHOTJ082ulixYkanpaUZTa+hkHMCxO8v4Fz6Wn4/Zuqcjc1XrlzZzLFu+uqrrzaa/u1sXblp0yaj/T0NV155pZlj3od7SdatW2c076Hp06cb7dfrM09CGHdmXP+9994zmtfF98Dn5/BzFc4516BBg9hzySnivPaTPHcYW2fsPcmjx9/XwV4izEtVqFDBaO4BoXcY8z1+Tw321+D+Bl4T5gQ47/sYOWf3yXD/yMm0piR6IhBCiMDRQiCEEIGjhUAIIQLnrMgRtGjRIhon5QQYe2aNOD1CTicvvPBCNJ43b56Zmzt3bg6fTfoerox/V69e3Wg/7rllyxYzx9gva6MZ+2Ucnz7+fj6ie/fuZs73h3IufVyfx6JXEf2B/PgufYmYf5gxY4bRTZo0MbpUqVJG0//G319Bb6uGDRsazfh5qshqnbp/H7A+PiknQE2vIcbW/Xuwf//+Zo45FvbgZl8U3gc8F38/CuP03DfA8+R75c2b12j+bvm5IvbJZt7pZNATgRBCBI4WAiGECBwtBEIIEThnZI6AfvLPPfdcND6TcwKMLz/55JPRmB40pwNeK+4r4D4Cvxaa/V/p9c5etdu2bTOaMVfmDHy/IL4X6+u//vpro5lv8D2SnHPu0UcfNfqZZ56JxtzfwNxN2bJljWYNOL2Kbr/9dqP9+nHGgllrztr0nII5gzgvoiSfIuYQko7FnIF/H9CHaPv27UZzDwdzR0l7Afx7kjH/JE8l6qJFixrN3wLfc4q5uv3798ceOzPoiUAIIQJHC4EQQgTOGREaYmnVoEGDjG7btm00Pnz4sJl79dVXjT6doSDaIY8fP95obnn3QxCZaTeXar777jujn3322dh5P+zBFowsu2RIheWmDC3x0dm/tklWGMeOHTOaj9K0mHjrrbeM9u0wGBKgvQVtCdgWk60uGb7wQ518Ld+b1tw5BcM1ceWlnKOlBr8Lhn4Y7mGYuFWrVtGYduP8LVi/fr3RSeEdnosf3kmync6fP7/RtBRnaKh48eJG+/cs74PsQE8EQggROFoIhBAicLQQCCFE4JwROQK2k2TpoV9W161bNzO3ZMmS1J1YAn5Zq3PO9ejRw2iWLb700ktGjxo1KhqfTElYdlOuXDmj/faQzqUvX/RjrkWKFDFzLOGsVq2a0Wz5yPisbyvinHMLFiyIxoMHDzZz999/v9GzZs0yulmzZkazxJM5Bf+zsJSPMX7mRngNffts59LHrXmP+DB3llP3SFbKRZ2z3x3vkSRbatp7tG7d2mj+vft5qREjRpg52kwn2UIQ5gH8fEXJkiXNHGP+nKe1CL/LAwcOGO1bjvs26M5lvd3nidATgRBCBI4WAiGECBwtBEIIETi5MkfAuOCUKVNiX//8889H408//TQl5/T/lC9fPho/9thjZq5Lly5Gs1ae9ezMCUycODE7TjFl7Nq1y2jaTrNGfuXKldGYtfnc78E4PHMCN9xwg9GMpfutAps2bWrmli9fbjTr7TlPe+datWoZvXjx4mh87733mrkHH3zQ6Kefftrojh07Gn3kyBGjuZ/CzzH49gnOOTd27FijT9dekyT7az+2znxCUl6D+wR69+5tNO3LR48eHY15jzAnkGRpTbjPwM8R8Hvt3Lmz0Yz5M1dC+xBaZBcuXDjD88xKXikj9EQghBCBo4VACCECRwuBEEIETq7METDmSLtdPx7sXPp4WnbSp08fo31/HXrakAkTJhjtewc5l77mPLdTp04do2nXTJ8dP5+ycOFCM8d6euZ2uOeCtdP0qClRokQ0ZsyfsV3GZ7mHYfr06UZzz4L/ufz81InOi3kUtlL1z9s55/bt22d05cqVo/Err7xi5phf8C2rUwn/PqlZb+/XtfO19A7i9evUqZPRrMefOnWq0X4snt8z6+2T8lKsx+d35fsa0f5+w4YNRrO95M6dO2Pfm/tLfNasWWM0PZX4OTKDngiEECJwtBAIIUTgaCEQQojAyZU5giRYL01vGB/G7tq1a2c0PUEGDhxoNPMTfpyROYD58+cbPWbMGKMZqz7TYNyyUaNGRrMfgR8HrVmzppljfDbJk4f19fQu8uP6jRs3NnPsA7FixQqjmSNg7qdr165G+/cbW58yZs08CmvZuQ9h6NChRvufk7mx5s2bG839N6mC3vr0W2LM2r/vGbfn98ycAX352aeCHj3+HhDu/0hqg8l+IDw3elL515ttWmfOnGk0cwZ+7se59B5K/l4V52wbTeaRmJM5md8ZPREIIUTgaCEQQojA0UIghBCBk+d4Jk3MT8bj+mRhXD6pz7Afb2b+gOfNfp/8+Iy3xeUBcnMOIBXe9P379ze6UqVKRq9du9Zo/3owDu/7xjuXHL9t0KCB0TNmzDDa9yJiHJ5x5XXr1hnt97x2zrm0tDSja9eubbS/F4Ax7bJlyxrN2n7W0U+bNs1o9k7wcw6Mr/NeZ6x+0qRJLhXQy4n5n7i/OX4G9u5lHopeQ4z7x/VC4HfD96bme/G+YQ8Nf7/Kpk2bzBw/J+8D5nOYd+G5+fsj6FtEbyH6FmVmX4GeCIQQInC0EAghROBoIRBCiMDJlfsI6KHCmvHZs2cb7dcOs66Y7N6922jfv9w5595//32jGfs7GR+PswXGXLdt22Y0/YD8OCdjnvQtYnyW39OePXuMXrRokdG+HxB9jXjePPbWrVuNpu/L66+/brTfQ3vZsmVmjvFZ3svsoc3+Baw/9/tz03ee+Qb25E0V/C4Y7+beHT9HwH07zA1xD8K8efOMplcT80E+/C3gd8N9GYy10w/o0KFDRvvnzvuXnkk8NnORzF3G+SDxbyk7fpP0RCCEEIGjhUAIIQInV5aPilMnFeWjgwcPNpohlCFDhhjtt6ccP368mevbt6/RtOdg+Ma3fnbOuQEDBhjdoUOHaMyyVpYfM4TCkkSWtnbr1s3ojz76KBrTsoTtI2kDwdaKLAHlY75fhphV++dRo0a5VMBSR5ZKsoya5+XD+5ShIcL3jrOOTioNT7KdTjpX//VJ4RmGwPheDF/yu/U/N8NGSdcwM78FeiIQQojA0UIghBCBo4VACCECRzmCs5ScyBHQ5qFNmzZG+/FwluIxTs/yuXr16hm9efNmo2lzUL9+/WhMO2zCtoE8FmPgc+bMMdr/W2DMmrFexnNZskgLBf9zOGdLW1neSGuMKVOmGD1y5EiXClgayXh23L13KnH4pPfm65PeK+nYSZzK3xjPJc7unsdKspBIss44EXoiEEKIwNFCIIQQgaOFQAghAkc5grOUVOQIeA/06NHDaLbQ27t3bzTu1KmTmfMtfJ1L35KQ+wYYl16wYEGGr1+5cqWZa9mypdEVK1Y0mq0raQPBfQh+y8LSpUubuRo1ahg9fPhwoxnX5+dinN9vk8ncB/da8Br27NnTpQKec9JvQ1Z+O041Tn8qv1OnklPga7O6R4F7HOJs2ZmXos0GP0dm7PH1RCCEEIGjhUAIIQJHC4EQQgROpnMEQgghzk70RCCEEIGjhUAIIQJHC4EQQgSOFgIhhAgcLQRCCBE4WgiEECJwtBAIIUTgaCEQQojA0UIghBCB83/E7gir4mqyWQAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAV30lEQVR4nO2dedCN5f/Hr3YSQrZkC0WiLKHwRYpsLaiUIqXV9E9TaRpGM4ySKZomZjJKU5jSaBuiRCX7FhIla2WJiJL2fn/97vl8XodzP4fnyON6v/663nMd59z3fe7zXO7P8r5O+vfff/8NQgghouXk//oAhBBC/LdoIRBCiMjRQiCEEJGjhUAIISJHC4EQQkSOFgIhhIgcLQRCCBE5WgiEECJyTi3oC0866aR8HocoZPLRJzhixAinp0+f7vQ///zjdLdu3ZLxRx995OZq1Kjh9IEDB5w+5ZRTnP7555+d/uGHHw77Wfv27XNzq1evdrpmzZpOf/vtt063atXK6e3btzv922+/JeOSJUu6Of5OTj3V/8QuuOACp2fNmuV05cqVnd65c2cyrlChgptbs2aN082bN3d60KBBIR/wnAjvPXtN0u5LXr+j0aeddpqbK1asmNOVKlVy+uyzz3a6XLlyTvN62/vizz//dHP8LWS7Jofi77//Puy/P/nk3P7/zvc6FHoiEEKIyNFCIIQQkaOFQAghIqfAOQIhbLw6hBB+/fVXp3v06OH0jz/+mIwZl2fc8ptvvnGasfc6deo4fdZZZzk9f/78ZPzTTz+5ubp16zpdv359p1u3bu30pk2bnD7zzDOdXrRoUTJmnLlly5ZOb9myxemtW7c6zbj0woULnR4+fHgyHjlypJvjeXz88cdO5ytHkAbj3za+zVh5rvFu/nvG4i0lSpRwunbt2k736dPHaeatduzY4TSP1eapeM48Lt7vaXH7XHKy2a53QdETgRBCRI4WAiGEiBwtBEIIETnR5QhYx836dtacd+7cOe/HVFRgPLxv375OM2dQtmzZZLxy5Uo3x5r32bNnO33uuec6zXhts2bNnLax91tvvdXNPfvss04z31ClShWnmc/Ytm2b0zY/wXwE+xt4Hsx9fPfdd06z9n3BggXJuFOnTm7O5kVCCKFFixbhWJBrTXw+34txe3v92O/AvBK/d3u/huBzXCFk9hWcfvrpyfivv/7KepzsM+B5Z+sbCMGfJ+cKo2dITwRCCBE5WgiEECJytBAIIUTkRJcjGDdunNOM4Q4YMOBYHk6RYt68eU5Xr17d6S+++MJpm49h7JueOjfddJPTy5cvd7pjx45OP/nkk063bds2GT/yyCNubsiQIU6ztp/xXeaJGIOtV69eMmaOYPLkyU7fd999Tr/11ltOV6xY0WnGoW1PAz9r48aNTtOfKV+kxfGzxazTvIJy/exsnj4HDx50c1WrVnV67969TlsPqRBCWL9+vdOM81erVi0Z87vhPbV//36nmRPgeWTrDciH75ueCIQQInK0EAghROSc8KGhW265xemmTZs6PWzYMKfffffdvB9TUaV48eJO04qB19Y+mtNCgqWPfLT+448/nOZjfa1atZy2ZZk9e/Z0c7/88ovTv//+u9MMBdFKg2WGpUqVOuxxsqx1woQJTl9yySVO01qaJY4bNmxIxgz9tGvXzmmex7EiV2vpo3ltWrmpDcnwnuF3k2b/YctDQ8i8Lyy0CmEpdZrFRJptdTbSwmUFQU8EQggROVoIhBAicrQQCCFE5JxwOQJb0hVCCKNHj3Z66dKlTo8aNSrfh3TC0LBhQ6cZm6R9wrRp05JxkyZN3BxL+7gVJctLBw8e7HS/fv2ctt/rNddc4+ZoFcCSTZa90kqDWxTu2rUrGdOu4tJLL3WauRHmWaht/iEEH5c+77zz3NycOXOcpl32seJoSkLTYv652ifY7SiZRypdurTTX3/9tdO8Dy6++GKnWQJqc03METC/QFheSp1mOZFtTjbUQgghckYLgRBCRI4WAiGEiJwTLkfw/PPPO33OOec4PWbMGKdZvy4Oz9q1a52mpTftO2xOge35tF9mTTzr623sN4TMHIPNQfTv39/NMbY7ffp0p2fMmOE0a/kZt7fWDrTCaN++vdPsG2BOgbXpzEd07do1GX///fdujjHvq6++OhwPFKbFRNrWlvz3NudC+xj+LWD+hn8L2LfBe9JajtOegvcQcwjMCbDXJRuFsTUl0ROBEEJEjhYCIYSIHC0EQggROSdEjsBu4dehQwc3t2LFCqe5NaUoOFdddZXTjLUzRm1jqDVq1HBz9Ohh3fTixYudZrx25syZTnfp0iUZc2vK7t27O82eBW7xeODAAafr16/vtI0H8zwmTZqU9b1pM017bvrd2J6FqVOnurnbb7/d6blz5zp9ImyzmpZDoK+O/a5oXT527FinP/30U6eZc9m8ebPT7G0544wzkjH9q0qUKJH1vZlTYN8Bc2CWwtwq9P/RE4EQQkSOFgIhhIgcLQRCCBE5J0SO4MEHH0zGjNkOHDjQ6d27dx+TYzoRobc+r2U2fxXG/C+66KKsn2Vj4yFk+ujQJ8b2IdSsWdPNsQeBvv3scWDfAGv/t2/fnoz37dvn5vjZr7/+utPMo7CWnXXy1k/osssuc3OMDTMfli9yjVHb+Vy9hTjPnAq/W5sP2rFjh5vj9UnzA9q2bZvT9KCy3lrcf4A5AOYM2EeQtlWlnec9Qo4kZ6AnAiGEiBwtBEIIETlaCIQQInKKZI5g0KBBTlv/efrdqG+g8KC3EP1T6JtjvV24f+yyZcucZuycOQLuddCmTRunGzRokIwfffRRN8c4Mj1o6DvP2DB7GGxsmfsPcN+F3r17O838BK8pr6HNQXA/Ano/Va9ePRyP2Lh/LvmEQ8HYerY9oF944QU3x/4QxtpZu8+8FL2I7H3A3CTfu3bt2k4zt8R8BXMh9rzlNSSEEKLQ0UIghBCRo4VACCEip0jkCBhv+9///ue0jc+NHDnymBxTjLBWukyZMk6zzt3WUqftScy4vfXhDyGEDRs2OH3FFVc4bXMIjNfWq1fP6bp16zr9ySefOP3QQw85zXr0xo0bh8PB3EevXr2c5jUcMWKE0zfeeKPTNhfCmDX33+a+C/kibU+BbL0A2erjQ8jMx6Tti33DDTc4bfsymEMh/CzW+pctW9Zp3sM2H2F9h0LI3Ceb+xOceqr/08u/cTw2myOgLxf/La9pQdATgRBCRI4WAiGEiJwiERriozq3A3zssceSMVv2ReHB8sR58+Y5zfK68uXLJ2OWPnLbP5buzZ8/32mGnViOumfPnmTMkk4+OtvXhpBZBjtlyhSnua1m27Ztk3GfPn3c3Pnnn+80wwv8rBdffNHpTZs2OW1DBNbWO4RMi2uGLv4rGM6x159zaSEShsOaN2/uNG29P/zww2ScFmbKdpwhpIfarDUJy4anTZvmNLcZJdxGk1tXZgv3yIZaCCHEUaOFQAghIkcLgRBCRE6RyBH07NnTaVoAMKYr8sPEiROd5taV3CrRlkKybJK5HJZCPvDAA07zO2fJ5/jx45Mxt4ukzQhzGevWrXPa5jZCyIwVf/nll8mYOQJuD8ktDHketNJgbNhec8ahaY/Nz8oXaXF+YmP1jHWn5QRYVsxcEe+bNWvWJGPaNBAeC3MsaXF6e960RedrixcvnlXnkjspjJwA0ROBEEJEjhYCIYSIHC0EQggROcdljoC12I0aNXKa2/9t3rw534ckQqZVA2uj77zzTqc3btyYjGlHwa0qaRnBGCtfzxZ+a0V+9913uzm7lWkImXF6xqFbt27t9Pr16522lsK0lOB7VaxY0em3337bad7b7HGwdhYXXnihm6MFM22XjxWs12evhK23Zx6DdhS8XrZnI4RMqwb2Xdh+FFox8Dg5z3uO+QpaYNucAu9v5gB4nrwOtLegLbV9PY+b+khsqfVEIIQQkaOFQAghIkcLgRBCRM5xmSNgbXFanXI+adasmdNjx45NxoxXMldBS+FjZROcL5i7oZ0zt120Pju0B+eWjC+//LLTjOdya78tW7Yc9rMqVark5vg9WXvsEDI9lNhXYPMPIYTw2muvJePRo0e7uVdeecVpWljXqFHDaXow8dhq1aqVjPfu3evmFi9e7DT7OvIF69jpp8R4uf3uWJvP33apUqWcrlatmtP05CE2lp5mx8w4PP/u8L5h7qN06dLJmFutsqeG700bdv5t4O/DbrPJXAU5kj4DPREIIUTkaCEQQojI0UIghBCRc1zmCNKgr0dhMnnyZKevvfZap61nDmNxtr48hBDee+89pzt27Og048HHO9wCkrF0zn/wwQfJmLFxbjf6+OOPO82eBMb9mzZt6rT1oWctPvdN4LaCtt8hhMz47cqVKw97bHYryRAyt9Tkez333HNOMz/B67R169ZkbOvxQ8isH6eHUr5gXJ818KyRt78Z+v/wu+B3xxwLrxfzVAsWLEjG7DUpVqyY0zwP5h8aNGjgNHs+7Dz7HXhcjPmvWrXKaV4X5kqsJxXzDewbUB+BEEKInNFCIIQQkaOFQAghIqdI5ghY33s0MCbbqlUrp+kvb33wWYf86quvOs0+ggEDBjj9zDPP5HSs/zXcZ5h6+PDhTts9BejvQ92wYUOnWYfdoUMHpxmXth4/d911l5tjfwfjzLyf+vbt6zT3w7A9DsuXL3dz3HuZ+QXW2HM/5Gz7K997771ubtiwYU7buvZ8klbLz5p4G5tnToB5NuZB7N4PIWTG7dlnYHNHzDew3yHtfmb+h7kmuwfGhAkT3Bz3l6ZXFs+T14F/W6zmvyVp/ROHQk8EQggROVoIhBAicrQQCCFE5Jz0bwGLTvOxT+bhYA0tPd8ZR7U16fTIT+O2225zmjkDxmFzgZd24cKFTl9++eVH/N65fnZh8PTTTzvNa00v/m+//TYZs6569uzZTrNPwHqrhJC5Vy393mfNmpWM27Vr5+bozbJ27Vqn0zxlGMe3vQL0rGdst1y5ck5zrwPGnbP52bzxxhtujn0E/D6Yhyksatas6TRj6+wnsbB3hr9lxrf5WYzbszfA7lnM74LfM2v7Cd97yZIlTts+BR4395fm3hF876+++srp1atXO233+ObeyuRI9ifQE4EQQkSOFgIhhIic47J8lOVnEydOdHrw4MFODx06NBnTqoAt6mTKlClHcogFojBav48naBV9//33O23b4EPwj7+022CoaNGiRU7TUpnhB9pbWAtslnQyjMR2fpYVrlixwmmGkmxIj2FMbidJ22WWXtKWhNbS9jytJXUImVYOtLPIF7QIZwknz9laXzAkwpAKbR+qVKniNMMifL0NxTGkx9DZ7t27neZ9UbJkSaf5+7VhPIYIq1at6jTDpjwP/nZ4bGnW0xbZUAshhMgZLQRCCBE5WgiEECJyjsscAbE5gBBCqFOnjtN33HFHMm7evLmbGzRokNPvv/++00djBc1YKa0NyKRJk474s44HOnXq5DTj27RBtjbU3MqPpY20+G3RooXTtFe45557nO7Tp08yHjJkiJujxUS9evWcph0A4/60NbBlg2+++aabY46K8fNx48Y5zfwFt0a11gQzZ850cyxJtHbP+YS/GdpGMA9gY+/Ma/A3xHwNt/LklqXly5d32t5ntJRnjoA2JYzD07KDcX1rJ8KS2TQrDW61akutQ8i0kbC5FL4Xcxe8pgVBTwRCCBE5WgiEECJytBAIIUTkFIkcAVume/fu7fTSpUuT8cCBA90cY7i2BT2ETCuD7du3Oz1nzhynbbyYce3GjRs7zTbxl156KRRlGDtnTsTG6UPwtdT8Dtnuz9p91o8//PDDTm/atMlpa+lNS2t+5zwPWh1zG01+z59//vlh34vxcdaTM7/F82ac3+YjaJ9Nm46bb745HAu4BaTdJjSEzGtiv2vG5dN6a9avX5/1vdl/Yns+GOO/9NJLnWYPA+1AaG9Bywrbo8T7m30y7FGwlighZOZd2B9hNfMHhdGfpCcCIYSIHC0EQggROVoIhBAicopEjiCNUaNGJWP64bDevEePHk6zbps1utddd91hP3fGjBlO9+/f32keS1Fn1apVTtutKEPItAu38W7WVbPnwFo7h5CZu2FMlfOMxVt43OwjYD0+cx20D7exZ54X+wJ69erldP369Z3u2LGj0yNHjnTabtHJ3gtaczN2ny8Yo+Z3yVp/azXNGnfqbH4+IWTmYBibt5o9HLxH6AvF1zPOz8+y+Qr2orB3ZcGCBU7zfud1yLaVJV/LfELaVpaHQk8EQggROVoIhBAicrQQCCFE5ByXW1WKoycfex/Q/4e+TvRvX7lyZTJmrJf+7YxrMubavn17p7nF42effZaMrT9PCJl+NYwFc5vAMmXKOH399dc7bXtLWNfO4+bWp/SzYf6BvQD2PHmcjGF//fXXTjOHVViwJp5k+1uR5otDzc9K89mxcXy+lu/NfA77DtjrwnnbV8A4PfdkYM8CfYv4enoy2TxMNh+iQ80XZC8DPREIIUTkaCEQQojI0UIghBCRc0L0EYhjAz3TWS/O+Lb1ZWJPRb9+/Zy2/j0hZHoNLVmyJOt8t27dkjH3h2WsmHH8Jk2aOD1+/Hinuc+w7Uto3br1YedCyIzX7tmzx+muXbs6zT0r2rRpk4xZx873Zk9MvmBcPi1unw3Gt7PF/A81T53Nt5+wF4V9GPz39BqyeQG+lprnYXsrDqWznRevGfWRoCcCIYSIHC0EQggROVoIhBAicpQjEAWGsXLuI8zaZxsP537Hae89f/58p1u2bOk093q48sorkzE9/VmjbX3kQ/D9DiFkekZxr2C7p8DixYvd3O7du53msaTVtnfp0sXpXbt2JeMKFSq4Ods7EUKmv02+SOsFyCVmnRbzT4vzZ/sszvG90o4z7fU2rp/reVCzr4afla0XIC3PUhD0RCCEEJGjhUAIISJHoSFRYLhVItv/WRpptxBlez63N6Q9eLYW+xAyLZj379+fjLn9Y/fu3Z3mNpc2rBRCCFu2bHGaJaL2UZzvZcs9Q8gse6UtBMtN+Zi/bt26ZEz7bFpaT506NRwL0kojj6acNNd/m+31aWGltHmWdGYL76QdJ79XlqKmfXY2CsP+R08EQggROVoIhBAicrQQCCFE5MiG+gQlHzbUjKXT5oHli9YCoXLlym6ufPnyTnMLwkqVKjlNW4hatWo5/cQTTyRj2lDv3bvXaeYjuG0gbaoPHjzo9M6dO5Mx7Yd5HrSBaNSokdNz5851mtfUfhZLaCdPnuw0cxlPPfVUyAc856PJART263N5r1zzD+RoykeZI+B9w5yCvQdztd0oyNaVeiIQQojI0UIghBCRo4VACCEiR30EosDQ/mDMmDFON23a1Ol33nknGdMimdYMtE/47rvvnGb9/dChQ53u2bNnMqa9cO/evZ2mZUTNmjWd5vaS3PKxc+fOyZhW3MuWLXOatf/cmrJVq1ZO25xACL6fonHjxm6OPQpFkVzj9rlYN+SaA2Dtfpp1tCVXK2i+nn0zueRG0nIEBUFPBEIIETlaCIQQInK0EAghROQUuI9ACCHEiYmeCIQQInK0EAghRORoIRBCiMjRQiCEEJGjhUAIISJHC4EQQkSOFgIhhIgcLQRCCBE5WgiEECJy/g9HQAXor+p2nAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, test_dataset, 123*i)" @@ -1964,9 +2597,90 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAXxklEQVR4nO2dedBX4/vH7+xrlJKUVtrt2RuRbEVJlDGWSCRGlibbIIxiLGPElIzRRNIgpSylRJQWWVoRJUqLFtmy+/31/fyu6/U8nfs5PX0edL9ff5333J/lnPM553PPeV/XfV2V/v7777+DEEKIZNnmn94BIYQQ/yyaCIQQInE0EQghROJoIhBCiMTRRCCEEImjiUAIIRJHE4EQQiSOJgIhhEic7cr6wkqVKhVzP8QWphjrBM8880ynf//9d6erVq3qdO3atQvblStXdmPz5s1zun79+k5v2LDB6erVqzu9atUqp8eMGVPY7tatmxt76623nL7wwgudnjVrltMNGjRw+quvvnL60EMPLWwvW7bMjc2cOdPpm266yemFCxc6ve222zo9ceLEsCnq1q3r9A477OA0z9ngwYM3+VnlYaeddsr1+qz/Do7FrluOb7PNNpnjm7tfIYTw119/lXk89lmx8dh+2+PkMXM/+V0///xz5meHoCcCIYRIHk0EQgiROJoIhBAiccocIxDixx9/dJq+Pr3Kb775prBNn5I+5/Lly52uVq2a0999953TRx11lNN//PFHYXuPPfZwY7vuuqvTNWrUcHrHHXfMfP3RRx/t9NChQwvbF1xwgRv78ssvnbbnIIQQXnvtNac7d+7sdK1atZz+5ZdfCtt//vmnG6PmOS0WMZ8+6/X0r2P+NilmrDLvcdl94X7xt8l73NTbbff/f9V875b43fVEIIQQiaOJQAghEkcTgRBCJI5iBGKzod/do0cPp5cuXVrYZu55q1atnP7hhx+cpk///vvvO71gwQKnrSfLNQtc38Bcfnqs22+/vdP0a62Pz+9at26d05MmTXLarq0IIYTZs2c7zdiIjTlwvxh/aNmyZagI8ub+29fnXSdQ3vz7PPC7dtllF6erVKnitI17/frrr26MmjED/paxNQv2/dzP2LqCsqAnAiGESBxNBEIIkTiaCIQQInGSjxHk9TuLSb169Zy2NW1eeumlzPdWRA55ixYtnLb7F0LJujvWm2d+/Z577uk06xbts88+TvP46Lnafdlrr73cWKdOnZyePHmy04cddpjTb7/9ttOsB9S0adNN7vdJJ53kNOMRjBF8++23Th9//PFOW9+/d+/ebqxjx45Os/bQv4U891SeeENpr8+KR8TqEvH8HXjggU7z+rfrVX777Tc3tn79+szvsusCQih5PXPNjj2uuXPnujG7hiaEEFavXh3yoicCIYRIHE0EQgiROMlZQ3lTrViy2D6Ot2nTxo0xvSxvKhytlZ9++qmwzTLMw4cP3+Rri8V+++3n9N577+309OnTN/lelmL44IMPMr9ryZIlTrM0NFP7dt9998J2v3793NjFF1/sNEtjvPDCC043atTIaR63tWvq1Knjxh5//PGQxc477+x048aNnV65cqXTNj21ffv2bozX8tdff5353f8UedJH85aQyHOPxawi6rPPPtvp1q1bO21TopkOSsuQ9g3/d2gtZaWfrlixwo0xjXvChAkhL3oiEEKIxNFEIIQQiaOJQAghEqfS32XM7dpaWlXGvLzTTz/d6V69ejltUyJZuoD+L30+nmr6gizDsNtuuxW2mWZ48MEHhyyKkQY7YMAAp1955RWnDzroIKet50qPn+ed8RWmyNlzEULJeIr12lnSmqUYWM6iefPmTl9yySWZ77eloUeOHOnGmKrK1FNef1988YXTLNd9+OGHF7ZtHCSEki00mWI8atSoUAzytqq0lKe1ZGnkSR/lb8FxXoMvv/yy00x53rhx4yY/m5rExvnfYM8bU01Hjx7t9MCBA51mTKE09EQghBCJo4lACCESRxOBEEIkzla/joCeJL1pcvnllzvNpeDW92fuPpeoWw8xhJItFOn7M8ZgWyiOGzcua7crBHrUXbp0cZrL4m2ZCJaY4Lli/jzz81etWuW0LfMQgo9PjBgxwo3Rt7cefwghvPPOO07Tx2ebTBvv4DoAlqWeOHGi0/R3GVdp2LCh0zb/nHESrhtgWY6KIk/8sLwxgTzfFYtH8LN4fVPzt8vzXfzficUI+H677oCtVXnvMDZZFvREIIQQiaOJQAghEkcTgRBCJE5yMQLW+KB/vP/++ztNH9b6x/TqGE9gPRz6gjVr1nSaPuL3339f2GYO8z8ByzszB37x4sVOz5kzp7DN34Hnhrn6zKdneWd68fPmzStsH3fccW6M547HwfFrr73W6f79+zttYwzcT8ZC6DPTz+X19vzzzzt9wAEHFLZZ2pgxmdjaki1F3jVFeWoNkbyvt98V20/+F7DsNGN2PN9Z6ymy4gml7RtjZqxNZD+P+71mzZpc310aeiIQQojE0UQghBCJo4lACCESZ6uLEdB7o9dGWHOcdWqyapgzJkAfnPuybt06p7nOIKs+Ovsi0MeOrY/YEowZM8Zp+tuMgTRr1qywvWDBAje26667Os02nYwBMB7DNRi2flCsTtHrr7/uNFtu3n333U4zhmCvCfYq4H7xu5nr//HHHztNn3/t2rWFbXrDrHXFuEuxyNtnI8vnL2Zr2FhbS56vtm3bOk2vPSu3P9aKMu9x8l6yn8d4Ao9DMQIhhBC50UQghBCJo4lACCESZ6uLEbBODOt6H3300U7bPO0QSubCsy+vzS1mHnFszQJrE9EnZy9dmzfOPPsrrrjC6UcffTQUG55b5uMzn9nmzNPHjNVpyqq7FEII7777rtPW3124cKEb4+9w6qmnZn4Xj/OII45w2h7XZ5995sb69u3rNHs2PPbYY06fd955Tnft2tVpez1yjQLXFcyaNctpxpW2FOXtK1we8sYnLLw/Wa/qyCOPdJrxRV4X9vNiMYJYf2TCGIGtH8R7oW7dupmfVRb0RCCEEImjiUAIIRJHE4EQQiTOVtGzOE8tk2HDhjldvXp1p5mPzx4CNWrUKGzTI2cdGfbGZd0Z5pjzu+1xcYy5wqyTUoz8bPrZjGnwGrGeNev20wPlugF+Fuu8HHvssU4/8cQThW367IsWLcr87BNPPNHpKVOmOL3vvvtu8rvt9RBCdq2gEErm/rPvcIsWLZy+7bbbSt0OIYRXX33VafaunT59eigGjKmQ8qwbKO//TJb3zv2+9dZbne7QoYPTvOcYx7LXMGMCjEtRx2IEPA+2phX/s7gWhcfB/6HS0BOBEEIkjiYCIYRInK0ifdQ+lvFxrnXr1k7TQlm6dKnTLCdQpUqVTY5v2LDBjdmy0SGUTC/loyXbL9IusemlfKTm42GTJk1CsWEq7oQJE5ymTXLHHXcUtm+//XY3xuX8PBfTpk1zmsd3//33O21LhTA1lSnATMMcNGiQ0yyd0ahRI6dtCYvx48e7Mf7mLHdBq5HnlL9ry5YtC9ujRo1yY23atHHalv3+N2Gv3S1tMfPzrAVDO8a2GA2hZGnzrNLPIWSnrsbSWmOlbzieVWKCNinbnTItvSzoiUAIIRJHE4EQQiSOJgIhhEic/2SMgKlXWSWYr7zySqdZCpqfRR+fKZ/2u9imkN4cyyrYFochlPQBuXTc+ob0K7nftWrVCsWGpRZ4vGeccYbTtn1k8+bN3dh3333nNEto8Lt4rq677jqnZ8+eXdhme1G2rrzhhhucHjhwoNNMk33uueectjEEHjPLUDOGMHnyZKcvuugip1mu2543xhfYKpTXarEoT/vI8pLns3g/XX311U4z/Ztploz38Bq09yTHCMezytuXNm7fz/87HgfTusuCngiEECJxNBEIIUTiaCIQQojE+U/GCLic2+Zis5Qs88+XLFniNNcJ0Ifld9lysIwBZOU0hxAvd5zVCo8xAuYhV0SbQvrfK1ascPr999932u5zrB3kww8/7PTjjz/u9CGHHOI0c/9ti0eWmT7//POd7t69u9OM3TAfn21BhwwZUtjm+ohzzz3X6XvuuSfzu3jcbH1pY1osfcH1DlyDUCwqMkYQy8fP8tq5TqBdu3ZOc+0K7/WsXH4SW0fAe52fTd8/6xzz3qfenLLUeiIQQojE0UQghBCJo4lACCES5z8RI6Dfxvoslp49ezpNH5u51vTWYyV2re/NPGX6evTuYrnC9I/tcdrYRAglc4eZO18M6GuyBg9/J3t+Pv/8czdGL92WkQ4hhDp16jjN3401o+yahpkzZ7qx4cOHO12zZk2nuRbg008/zdwX+7uccsopbozn4MEHH3SasR7GIxgjsNcEYwBr1651uizlhrcEeT3/LbmOIFbe2f62V111lRtjTIDE2ksS+1vGWlXy/uV1wOPIWrOQtR+lfXdZ0BOBEEIkjiYCIYRIHE0EQgiROP+JGEEsb7lTp06FbbYwZO0W+vqxeiLUNqbA3F/6gIxlxNpN8vV2X9kngT53RfjD9EwZ02C9IOthb9y40Y2dcMIJTvN3Y58IaraPtPtGn53rCljPnfGVZs2aOc0+ADZP27bjDKFkLwTWTGJrSsYfeE3Y3gnnnHOOG+P1NHLkyPBfI7YuIHbv8/7t2LFjYZvXAX141hVjrj/3jd67HY/FLqgJ9yXrvMTWK8W+qzT0RCCEEImjiUAIIRJHE4EQQiROmWMEMS+vPMTqidDzqlatmtN33nlnYZv1cJh/znUCXEdAn5CerfVl6dHSB+dxsAYIYwI8TjvO3gex+EIxWLlypdOMtxxwwAFO16tXr7DN32Hq1KlOn3zyyU5XrVrV6Y8++sjpE0880emFCxcWtnkNsPfBMccc4/QHH3zgNGMEvXr1cvqRRx4pbLPeT7du3ZxevXq104x1sD4Tz/HFF19c2OaaA64jYJ2sYpHX17evj703Nk6fnrXFOnfuXNiO5ebzXqdPT3i923sutp95axFlxRP5XsbustYcbAo9EQghROJoIhBCiMTRRCCEEIlT5hhBzOOiT2X9uJiHlacWdwghPPPMM05br4759OyrS++Zvl/Me7f1g9j/mPV/6JmzFy57qNqa+iGEsHz58rAptmSMpqxY/zWEkt46f+fFixcXthmLYZ0i5uPTp+f1Nm7cOKdt7SL+LlyjQG/dxphCCGHu3LlOjxkzxmmb+8/j4Gc1bNjQaa4HadmypdOsczRgwIDCNuMR7NHA669Y5O23m/Xa2Gfzd2esiT0HbJyE9y7/C/jZjCHkWRvAsdiaBP7PxI7b7hvjD4xtbM6aIj0RCCFE4mgiEEKIxCmzNRQrixrTeTjooIOcvummmzI/21oQLNXLR3EuSScsEcDHS5siuttuu7kxWkH169d32pYLCCGEe++91+ktsVS8mIwdO9ZpPv6yHaV9ZOV55Hnee++9nebraYOwvMWaNWsK2yz1MXToUKf79+/v9KJFi5zmYznLYdj0VP5G/fr1c/rGG2/M/C62umSq6owZMwrbNm01hJIlFNh2tVjEbGHeY/YcxUop8JpiSizTjJkKbK8L7gctlVhryhhZx0ULa/78+U7Pnj3b6bPOOsvpLLuN54jIGhJCCJEbTQRCCJE4mgiEECJxyhwjiHn+9Hht+V165fRwGzRo4HTt2rWdpl/Mcse2dAPLM1euXNnpWHtI7hvHbfopYwR5W/LVqlXLaR6X9Sx5/mOpb8WAnivjL1OmTHHaxmv69Onjxi677DKnW7Vq5fSGDRucZuokS07Y0gwsQUKPnz7zHXfc4TR9f7bZtDEppqqOGDHC6a5duzo9YcIEp1988UWnp02b5rT1ng877DA3xnRIpvN26NAhFAOeH5ZOadq0qdNHHXVUYZtxtPXr1zvN+433GL+L16RNB+f5Yao4YwRsLcvjZAkZmxLNWAbjUk899VTmd7HlKWMM9v7me/nfwHNYFvREIIQQiaOJQAghEkcTgRBCJM5mt6q85pprnKbPb/01luKlv03Pi+38bDnjEEou27deNPN5GV/gd7O8Bf01en92nH5nXmKlZ+2+MrZB/5J+ZzHIW7K7S5cuhe377rvPjfXu3dtplg1hmelly5Y5vc8++zht4wJcS8KY04UXXug0W1E2b97caR63LX08fPhwN0bP+s0338z8LK6ZseW0uS/8jW2L1hBCmDlzZqgIGBuypbJDKBnLsHE1XuNsOfr99987zfs15vPb88uS84T3EP+H+N/B693GLxhn4vXMMvKMZfI8MEaW9V/A/dY6AiGEELnRRCCEEImjiUAIIRKnzMbyzTff7HTPnj2dprdpPS3mgNMnpPfGHFr6gMwttnU5uA6Aniw/izVvGGOgd8d1CZZYm71YKzx6lvb9rD3C76qIGAHjJczT5loA673T2x0/frzT9J3bt2/v9LPPPus0WzraPOv33nvPjXEdC8/lpZde6vSwYcOcbtOmjdP2WmdeO69NtsnktX7aaac5PX36dKcbN25c2OYaBTsWQslrvVgwhsJ2kSyHbe937mPeGECsVpGN0fC9sfggY1yM9/C4LrjggsI2Y0Fcc8B7m3WhOM5YpR2PtfZlzKAs6IlACCESRxOBEEIkjiYCIYRInDIby/Qnbf2QEEJo0qSJ0/SPLbE82Ji/xro69v38bOYC07OlZ8njYD2g8sAaOMyNz+o/wOOK1UQqBqyDw7afzNu2NWcYX2CedMeOHZ3u27ev0+zdMHHiRKet38v8ep531oLnNXHqqac6PWnSJKdtjIDxg6VLlzr9448/Os06PE8//bTThx9+uNNDhgwpbNeoUcONsc5RRcSJQghhxYoVTs+ZM8dp/jfYOBv3kfEaav43xFpdZtVEi7V3ZXyC8UC2auV1YcmK94VQch0B4xVZ7XtjsY7NQU8EQgiROJoIhBAicTQRCCFE4pTZVGS/XfbYZD+C1q1bF7bbtWvnxpjXzTpF7MVK75m+oa1PEss7Zp4369ozV5g+bBb0L+lX1qlTx2nmKWfVCGFchP5lRfjD9D0ZX2E8xtb4oafPdQK33HKL03fddZfTgwcPdrpHjx5O29ouXJPAWMby5cudPvjgg50eN26c0zxO69UzBrBq1SqnY9cA/V367Xbf2K+Caw4++eSTUBEwtvXAAw84zXVDth9E27ZtM1/L65r3b6zmlh2P5dPznuJxnX/++U6/8847Tmf1Do79F9DnZ4yP+2bjF7Ge0bGexqWhJwIhhEgcTQRCCJE4mgiEECJxKv0dS6793wtz9uMtD8zlZz159iOwNVfoD7O3wRtvvOH01KlTN3c3SxDrgcq6Muxryv6t9pwz7561SlgDfnNqkse4/vrrnaY3SQ/b+ueMAzEnnjGmRYsWOc3flfn4FtYaomfKGAFr4Gd9dgg+DhCL86xdu9bpRo0aOc16QYw52N4JH3/8sRvjehvWu3nooYdK7PuWgLXAYjnz9jqm58/flff2IYcc4nSLFi2cZjzRrl+i7876VFwXM3bsWKezeoiH4I879jfK9zL+wH4GPE92HQ6vZ15jxx13nNO8l0pDTwRCCJE4mgiEECJx/pXWkCg/ZfxZc9GrVy+nBw0a5HSfPn2ctvZV7DH9888/d5opx7ShZsyY4bRNr4uVEmdJCaYNduvWzenRo0c7PWvWrMI2S28z1ZnlLM4991yn2cKQpVxsmjZtk5ityd9nS8FSDLQ9soiVUOZnxVIls0pN07LiuSZ8faysvNWx+42p1Wy1ymuU5fGt5UX7kOVmaIdnla75H3oiEEKIxNFEIIQQiaOJQAghEqdi6taKrQKm+t1+++1Oszyx9T3XrFnjxr799lun69Wr5/QXX3zhNP1dljm340wRPuecc5ymx0q/lp4qU19tyQlbSiWEED788MPM97JM9ZNPPun0jTfe6PT8+fML20w1ZSoqj6tY0KeP+ePWa4+9NlYWgt/N2FPW5/O9Me88T5kIfi/fyzIlTAfn/ZEn7sIyJbFS3aWhJwIhhEgcTQRCCJE4mgiEECJxFCMQZYb59izvzPx9W7qBXjmX7zM3nTEBlqDgd9sSzAMHDnRjLDXevHlzp1evXu00l+RzX6pXr17YZlkC5p6zrPKUKVOcZjl3lj3v3r17YZtlkJk/zuP4pyjPmqNYLn9WK8oQ8vnjsf3ME0PIGzfh63nv8Ditjq3F2Bz0RCCEEImjiUAIIRJHE4EQQiROmWsNCSGE2DrRE4EQQiSOJgIhhEgcTQRCCJE4mgiEECJxNBEIIUTiaCIQQojE0UQghBCJo4lACCESRxOBEEIkzv8BP6T5P9WPEnEAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" @@ -2004,9 +2718,21 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:16<00:00, 24.57it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 23.81it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 24.01it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 23.91it/s]\n", + "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 23.96it/s]\n" + ] + } + ], "source": [ "import torch.optim as optim\n", "import torch\n", @@ -2020,7 +2746,7 @@ "history = {\"loss\": []}\n", "\n", "# Model:\n", - "unet_model = UNet(depth=3, in_channels=1, final_activation=nn.Sigmoid())\n", + "unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear')\n", "unet_model = unet_model.to(device)\n", "\n", "# Loss function:\n", @@ -2040,9 +2766,90 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, test_dataset, 123*i)" @@ -2050,9 +2857,90 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAaAUlEQVR4nO2dZ6wVVReGN/aOgAgIIh3polyKIr0pShEiQQERgUQSIz80JoZEokF+KAqGgEQkSlQUEAUFkSIoFxBQQHqVIkUUxIK9fb++yVrPgZl74J57+b55n1/zZp8zZ87MntmZd629dol///333yCEECK1nFPcByCEEKJ40UAghBApRwOBEEKkHA0EQgiRcjQQCCFEytFAIIQQKUcDgRBCpBwNBEIIkXLOK+gHS5QoUWg/yn1lO6etbt26Trdu3TrafvHFF89o30k8/fTT0faECRNc24EDB7La1znn+HH4n3/+Of0DA7mYJ/jggw86ffjwYaevuuoqp//6669o++jRo66tYcOGTl9xxRVOs4/s3LnT6Zo1azr9ww8/RNvnn3++aytfvrzTy5cvd7pMmTKxv3355Zc7fezYsWi7Tp06pzyOEEL4/vvvnb744oudZp+59tprnd6yZUu0XapUKddWr149p1euXOn0W2+9FXLBueee63RSv417dvAeSGo/7zz/yCpbtqzTt9xyS7R9ySWXuLa9e/c6ffDgQadtfw0hhNKlSztduXJlp3/66ado+6uvvnJthw4dcvrEiRNO83/8/fffTvOcnsn9zH2fDL0RCCFEytFAIIQQKUcDgRBCpJwCxwjOhGxjAj169HB60KBBTsd5e/n5+a5txYoVTu/evdvpX3/91enLLrvM6aFDhzr9448/Rtvffvuta6PPTc92wYIFThdmTKAo2LVrl9P0Oal/+eWXaLt+/fqu7ZprrnF61qxZTnfu3NlpesX05i3bt293mv5t7dq1nWb8gjGBvn37Oj1x4sRomzGBffv2Oc3j/uOPP5xu3Lix0/PmzXP6nnvuibbpcSf5yrmC9y9jBsTe/0n3PvfFftO1a1enW7Vq5bS9f62Hf7J907fntWHsiDGwbdu2Rdu8Nja2E0Lms4B9Mum82Gub9NnTiefqjUAIIVKOBgIhhEg5GgiEECLllCjowjTZ+k7WG03yLp988kmnOU+APqz1nkPwPv8FF1zg2kqWLOk0j4V+MH3AK6+80uk1a9ZE20nxBu6LnuQrr7ziNGMO2ZxDkot5BOPGjXOafvimTZuctv+/ffv2rm3hwoVO058dNmyY0/Rg2QfstcjLy3Ntc+bMcXrgwIFOr1+/3ml674whWK+ZeezMXWfMiXMvfv75Z6eZy27jMpdeeqlrY5yF333uuedCLsgmJpAEYyi8do8++qjTjEN99913p2zns4Caczp43XkP8drZfsFzwrks7EOMBW3dutVpXstsYgR8VhTk2aE3AiGESDkaCIQQIuVoIBBCiJSTs3kE1quj/9urVy+nmUu9f/9+p+k50ve3/hx/a/78+Vnti/Vb6Pla7+733393bfxtm2ccQmbtksGDBzs9evRop60XeKb1mQoD5j6vXr3a6Ro1ajht/fMjR464tjZt2jjNORj0Y219nxAyzzVrD1no365du9bpP//802l6qvSWbeyD1yWpvs1vv/3mdFJdIxt3Ylzk6quvdprX52zB/kf+33Llyjk9ZMgQp+mVM47GmEFcXI2xRjsn6GT7Yr8gvNZxXHTRRU43b97cacYXGX+05OLe1xuBEEKkHA0EQgiRcnJmDcWVPrWlYkPITCGjTcBSvl9//bXTNq2uYsWKro0WBFPwOI2c09K//PJLp215C77mM1Xwm2++cZpWEl9FSZw1VBxUqFDB6QYNGjhNG8ReJ77qduzY0WmeO1o9TPWjXWNtKn63d+/ep/xsCJnlKliigunMdv8vv/yya+M5Suojx48fd3rDhg1ODxgwINr+9NNPXRv76oUXXhj+12jbtq3TPD+0w2id0Saxzx1aQ7Ry+F2mfPJ8UtvUVT6j+PyjrlKlitMsy85yLrkuH6I3AiGESDkaCIQQIuVoIBBCiJRTLDEC+mNM02JZB3rpTB20Xh19eWqm3NHDXbVqldNcOtDGLxhfYGob4f+i783/aVPnzob0UcZmuCyoLc8cQgiTJ0+Otps0aeLamBZIz59T7hs1auQ040q2hMW6detcG9MG2d/oS7N/tmvXzulRo0ZF2/SwK1Wq5DTPGUsN8LdYcmLMmDHRNktKMEZQq1atUBwkxa9sX2Uqb9OmTWO/y+cIffw4n599jL9NzfuR+2aMIO5+Z7oo00P5P9i/WYLClqfhcRXGs0FvBEIIkXI0EAghRMrRQCCEECmn0GIE2fhUSfn09NLp6dL7s94dPVvum94cl72kZ8kyt7ZUAuMP9HdZroK/Tf+TSyhu3rw52qafWRzLXPJcjhw50umZM2c6bZccZYkJ5nQfOHDAaebjs3wC54PYc3vrrbe6NvaXTp06OU2vffHixSGOjRs3RtvsL1WrVnWa15jlU1i6mzEG2/94Tuhps6RJcRHnYbNsd7Vq1ZxmPIdeO68770H7eZ4f3jNJsUd+nj6/fY4xZsXf5jOPzzSW2mAskyXs49BSlUIIIbJGA4EQQqQcDQRCCJFyiiRGwFLPjAGwHGxc2d8Q4ut4cF4A900Pkr49j5UxBzt3gLV1mCt/3XXXOc0aNjxW1kmyMYKzAdZ5oV9Lr90eP/8bS1bzmr/77rtOz5071+nx48c7bb111n1ZsGCB06wtRG+YsRpi6+OwXDZjIZyXwv/ZrVs3p9lfrS/dqlUr18a4SVLZ5KIi7lnAGAjriiU9CxgnYQzP/hafE7zO2c4zYBzA/k8+Rxh/YKyD7XzGUbPmmYUxGc0jEEIIkTUaCIQQIuVoIBBCiJRTaDEC+mc2B5deOWt20NOiF02vj76hzSWmp89cYOYxM3+dv03P1y6ZSJ+PdYnoC8adoxAyc4ctxVFbiCxatMhp+rvDhw93es2aNdE2/2teXp7TNjc/hBCaNWvmNL14+rv2/NBnrly5stP0qdlnGL+g521rzHDeAPO9y5cvH+LYs2eP06yxZD3wadOmxf4Wa9oXFUlziOy157VgH+L8EubjJ625ELcsJmtKkaTnUtxcAfZvxhf4XEmaF1C9enWn7b2kWkNCCCEKHQ0EQgiRcjQQCCFEyim0GEFc7RvW7aenRc38dHpe9IetV896IDwu1jahR8t8YMYjbDv/F4+TtYbWrl3rND1Hxhgsces7FBVcX5b/l//PeunMlx87dqzTrA/E2ivPP/+806zxY68jj+vOO+90esaMGU7Tj+V6scuXLz/lsXLeCfPak9bWYDyDPv+ECROibZ5/9j/25VyRrSdt+zljBHF1w0LIjCEk1R2zzw7eX7y3Oa+Avn3S2gf2WBkP5L75HOH/4HOK627bY2HdosKIH+qNQAghUo4GAiGESDkaCIQQIuXkbM1iC9dlJUkxA3p99Misf0aftHTp0k4z75teHn+bPqHND6bPx5xn1guhD8jf4rFazoZ5BKzTzzkZjO1Y/3zlypWujf+V3jCvy5AhQ5x+7bXXnLY1aLguxEMPPeT0I4884vTUqVOdvuGGG5y26waHEMKGDRuibXr6L730ktNcs9iurRxCCEuWLHGa9YMGDRoUbS9btsy13XjjjU6z1lNRkVT/3t6/nFPE68z8e3rrSc8GC+8Z3q/ZrvHBeIU9tqR1Evgc4XwJxjq4PrX9PJ9/mkcghBDijNFAIIQQKadI0kdpA/DVhalXhK9RfKWz+2PJCKaL8jj56s40Tab/2dLRPG6WPya0jvi6yFdPS2G8/p0pdevWdZqpkHyNt3rHjh2u7fbbb3eaJbe3bNnidJs2bZxmSWb7usySEf3793ea565nz55Of/DBB7HHNm/evGh7586dro19k/1rzpw5TtOqbN26tdPW6uS+7HGEEELz5s3D2YjtB7SJk0pn837k+Y2zX9k/48pIn0yzTDxtLFvSnnYN7UmWt0i6f/ncss+G48ePx343zi475Xey/oYQQoj/KzQQCCFEytFAIIQQKadI0kfpd9EXpNdOr9mWKgghM1XLloamr0dfm54/07ToLzOt0Wq28TipGSthOQx6e/bzLF1QHDEDxl9Yrpn+rT0/HTp0cG1ctpNLEDI1sn79+k5/8cUXTtvrunTpUtfWp08fp5955hmnWa6ia9euTnOZQFsmgd+dPXu200888YTTb7zxhtOlSpVyet++fU7v3r072m7cuHHsd3k9ioqkcs22H7AsBmMAfBawTzGuxribvS8YD+T9yvsvKXU8bn88Dn6WsQz+L6b+smy1jSUxxVjpo0IIIc4YDQRCCJFyNBAIIUTKKZIYAf0x+vD0Ounbjxgxwulnn33WaTvln14dl3+k70dPkn4b92dzh+vUqePamH/O5RYZK+HyjJyHYI+dMQL6sEVRppo+PuEx2Nzqo0ePxu6LU/JZCprzCuiDtmvXLtrmNXz//fedvuOOO5yeMmWK07fddpvT7I+2NDTLUXBpUx438+g5P4KxE1ummn2ZfvuKFSucZlmOooLn3+bAc04Qc+J5P7L0gr3/QsiMCdq5A+yPSUvFMnYZt+QmP8/fSiozzXkFSXHT2rVrR9v5+fmx+z4d9EYghBApRwOBEEKkHA0EQgiRcnIWI7BeIL1M+nxcKnDmzJlOv/rqq05PmjTJaVvXg94avbg4TzGETL+N9X/sHAbm/lofL4QQHn74YaeZ305f3M6HCCGEFi1aRNvbtm1zbcVRa4i5/ZMnT3a6S5cuTh88eDDaZm0hxgA6duzoNJe9ZGxn3bp1TtvzQy+Y8QguCdq5c+cQB/vUsGHDou29e/e6Nvr4rFPEstX9+vVzmn3GzkVh/RrGXQrDKy4M2DftOWF+PO8hxhBY34f7Zr+wXj19+6R5Akllqok9Vh4n46BJ8QjWKuLnbTyS86z43dNBbwRCCJFyNBAIIUTK0UAghBApJ2cxgpYtW0bbcbWBQsj04emrsvYLOXToULRN/4z+8KpVq5ymn0zNORDWd6RHW7NmTae5DKH1zEPI9EsZM2jQoEE4FcXhB3OpynvvvddpXjdbk+fzzz93baytT792/fr1TnNORq9evZy2NX24HKJd7jGETF+f9agOHz7sNPurnVewZs0a18Z6NvyfXEp14MCBTjOmNWDAgGib81T4P1j3qKhIWj7Sxgjo8SfVKaJPTy+e97u9P3ktOCeIcxSSdBxxc2hCSK4HxNgI7+9atWqd8rP8LdUaEkIIkTUaCIQQIuVoIBBCiJSTsxiB9V3pWTF3f//+/U53797dafrD9F2tR0ZPn97ziRMn4g47w5PknAcL/UzGDJgTzjri/D6P7frrr4891qKGHvTy5cudZjzGxm44j6BcuXJO0/9u37690/TtGUPo0aNHtM15KaNGjXK6UaNGTnO9Adb9b9KkidN2ngtrC3EeAdcR5vyJZcuWxf627SP0oVnnKGnN7FyRVJPH1tiiT8/4YZKvz3lA9PHt+eJxcM4C54ckzVGgz895HXGf5XOFsQ3OO6C2zzWua1IY111vBEIIkXI0EAghRMrRQCCEECknZzGCevXqRdv0x5L8M64rzNxh1ua3a4+WL18+dt/0HAl/izm7Fnr8jF3Y3N8QMvN9mTNOv9POM2Dsg/GIooB+Nj1SnttOnTpF24yPME7Ec8W5ADbeEEJmH7Axhw8//NC1cX4HNY+b8znYbmMMH3/8sWvjegKca0EfmteR6xPYuMu4ceNcG+cw8H8VF/yPtrYT75mk9T/opTMmw36UTQ49nw3cFzXjFzaGwOcG7/WktZiT2u2aLVy/m3NTeE4Lgt4IhBAi5WggEEKIlJMza8imPtLyYFoWU8iY5sWUMX7f7p/LXtoyviFkvnJx37Qc4qwhvrbaZQVPBl97WYqWr7329ZJlOIrDGmIaJV9JiS0xwbLSN910k9O0hphKy9RJptbaMtQsaU1bLZvSASFkWk223DgtrLJlyzo9e/Zsp2kftm3b1unVq1c7ba2ODh06uLZ33nnH6Ro1amQce3FAm8OW5GAb7RbapUwB5f1IK8jalSzhwvuVJJVz5rHYZwn3zecM+zP/By0zHou1nlgOfv78+U5n279D0BuBEEKkHg0EQgiRcjQQCCFEyslZjMD6w/v27XNt9AmTUsDon9HXt/vjFH/GE4hNPQ0hc2o3vT+7Px43fcEDBw44TW9v48aNTjMOYMtb2KXqQsgsi1AUcHlImx4aQgiLFi1y2pag6Nu3r2tLit2wXHjPnj2dZp+wsSGeR/4WSzPMnTvX6YoVKzrNPvH6669H2yxx/d577zlNv/bmm292mnEW66eH4Eu1bN261bWxTDnbiwreB7w29h6K89lP1k6vnOUV+Hl7fzL+QHhtGIfi9xnTs/+L54DxQMYP2UeTlsy1KaFcapXlWhiHKgh6IxBCiJSjgUAIIVKOBgIhhEg5OYsR2HzqnTt3ujZ6iPTHOEWaflmcz8jyFElT2pN8QR6bnfPAWAVzg+lN0+efPn260yyPYXOP8/LyXBt97aKgc+fOTtO/5RwM69tzWUVeh/z8fKe5fGSZMmWc3rJli9P2XLZo0cK1zZo1y2mWxGYfYCyH8ZjBgwdH28ePH3dtXJKT5bQ5/2HFihUhDjunhvEulpT45JNPYveVK3hcvD/j8veTlnCk5r7YB21JZsYfkuYJ8F7n/6K2+2eJCcYIeE74v9gH+Xn7LGCMtVKlSk6zREpB0BuBEEKkHA0EQgiRcjQQCCFEyim0GAH9NetTMV+Xfi/9MvqGzOPmb9n6JCVLlow9Tnq6rEPD3+Kx2Dxm+t78H0lL43Hf9D/teWNue3HA/GTOweAx2j7AGjI8d4wJ8Lq8+eabTnNuiq0rs2nTJtfGXH9+l9dhw4YNTrMEto2VcN7AY4895jRLRS9evNhp1iqit2yPhTEBu2RmCCGMHDkyFAX03pNifrYf8x6ht540p4ilz9kH7f4Ys2NNM8Z+OEchLiYQgu839PQZa2Q8MancPZ9D9vvsr/xuUqn9k6E3AiGESDkaCIQQIuVoIBBCiJRTaDECLp9m/TT6Z/QU6YfFrTdwss/bOQusQU4/jbnuzLmlN81jtzEIHgf/l81pDiFzPkXTpk2dZq0Y67nTn2ec5dixYyHXML7Cmj1xy2nS3164cKHTrVu3dpo531wm09b7CcEv48h4xP333+/0fffd5zTjSlx3gX7v6NGjo+1mzZq5thdeeMHpli1bOm3rR4UQQsOGDZ0+ePCg03b/7E93332301w2s1WrVqEoSMq/t/dF0hwD5tMzRkCfnjn0dh4R70fWIUv6bf4Wj8XWHko6btYpYsyA85/4+bglOFm3KJvlOv+L3giEECLlaCAQQoiUo4FACCFSTqHFCB544AGnrYdNn57eXVIdDkKf1ebkMq+Ya4Xyu1wHtkqVKk7Tt7c+OHOB6Tkm5TzT36Q/bPOD+Vmudcuc8lxw+PBhp7k+NK+rjRvNmDHDtdl1f0MIYcGCBU5zTeP+/fs7PWzYMKfHjBkTbS9dutS1sf/RU+W+x44d6zTrv/fr1y/aZq2gbt26xf4W+9f48eOd5trNNobF+BfvG16fXMHfpd/NGI2dP0MvPcmnT1pDnHEr6+uzPybNV2L+PeNU9O15rHHwuPksYByKv22fW3xOcL4S910Q9EYghBApRwOBEEKkHA0EQgiRcgotRjBq1CinrW/FXGr69vTm6MXRL+P6n7aOP2MAU6ZMcZrre7I2Pf3OqVOnOm1zuVlbnvnTzBFnfR3WNmEtFLvm7/r1610bvdGigHNFduzY4TS9YRtD4Fq99Ibr1avn9KRJk5xmDZ/Nmzc7ba/zrl27XBvne1Cz73bs2NFpevM2htC7d2/XxrkU27Ztc3r+/PlOsz4T1yy2/4VeMH1n5r3niqQcecbO7D2ZlNvPa8P7mfcInyX2+4wB8LOcm0OfPqkWmL0e/CznVvC5wjkh7GN85tn6WFwLnXOIGMMpCHojEEKIlKOBQAghUk6hWUN8zXr88cej7SVLlrg2ptQlQcuBNoNNT2OJYb4OVqhQwWm+evL1mq9sa9eujbZr1Kjh2vjKdtddd53yuyFkvsLR7qE9UtzwOtIGadSokdP2VZqloVnW4e2333aaJSeGDx/uNC0UWyqaNhPLiHApS9oRfG1n+qi1Rvbs2RP7W1yulHbh0KFDnWaZCFsquWrVqq6N9gOtx1xBa4j9mGnTdqlQLjFKW8mWJQkh0wamzcx0XNuvaDnzWcAyLbR3+D/4P1n6xsKSEbS0+Jzhc4n2mn1mVq5cOXbftKgLgt4IhBAi5WggEEKIlKOBQAghUk6hxQji4LR7ll+mJ8t4A6dUc3m/Ll26RNsjRoxwbUytsiWrT9ZO35AxAuvH0e+lJ8l0NMJSyjZdlHBf9FZPJ2UsW5gum5eX5zSP35YHoK/JdFimFe7evdtppkpS21Rcerv07dl/WL7jyJEjTtPnr1atWrRdvXp118ZS4yyVsXr1aqefeuopp7mcqY1n8Djy8/Odpq9cVLDvMeZiy58wXZTXnf2a/jdjS/TDbVyKJSD4nKHHzxgBffy40tC8bkwbZnyCy6EyRsb+bc8by94wlVolJoQQQmSNBgIhhEg5GgiEECLllPi3gOua0T87W7HlJkLI9GhZ7pi+H6eRT5s2zenZs2dH25999plrY450tvAc20uTVLqbnM5ydUmwZPJHH33kNP1xO8+A+d6cQk9fnyWuOUeBfrmNK9WpU8e10Z+dPn2603369HGacwO6d+/u9Pbt26Nter30wAmvMa8j5wbY/8Xjol/OeQYTJ06MPZbThX0xqd3+Z/4/no+kMtWM53COkd1/UlkHluwg9Ol5vjnHIe632N8Zn4iLdYTg+wnPWdKyljwPJ0NvBEIIkXI0EAghRMrRQCCEECmnwDECIYQQ/5/ojUAIIVKOBgIhhEg5GgiEECLlaCAQQoiUo4FACCFSjgYCIYRIORoIhBAi5WggEEKIlKOBQAghUs5/AH8g97EIUpi6AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" From 93b46995dad372478fabcf59c05d87c0b90b6dbe Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 17:29:25 +0100 Subject: [PATCH 18/51] Add github action for building notebooks --- .github/workflows/build-notebooks.yaml | 32 ++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) create mode 100644 .github/workflows/build-notebooks.yaml diff --git a/.github/workflows/build-notebooks.yaml b/.github/workflows/build-notebooks.yaml new file mode 100644 index 0000000..c68235e --- /dev/null +++ b/.github/workflows/build-notebooks.yaml @@ -0,0 +1,32 @@ +name: Build Notebooks +on: + push: + +jobs: + run: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v2 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: "3.10" + + - name: Install dependencies + run: | + python -m pip install -U pip + python -m pip install jupytext nbconvert + + + - name: Build notebooks + run: | + jupytext --to ipynb --update-metadata '{"jupytext":{"cell_metadata_filter":"all"}}' solution.py + + jupyter nbconvert solution.ipynb --TagRemovePreprocessor.enabled=True --TagRemovePreprocessor.remove_cell_tags solution --to notebook --output exercise.ipynb + jupyter nbconvert solution.ipynb --TagRemovePreprocessor.enabled=True --TagRemovePreprocessor.remove_cell_tags task --to notebook --output solution.ipynb + + - uses: EndBug/add-and-commit@v9 + with: + add: solution.ipynb exercise.ipynb \ No newline at end of file From e01ec0237b2c72de77c4a240a1e8033276387cc7 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 17:47:08 +0100 Subject: [PATCH 19/51] cleared outputs from solution notebook --- solution.ipynb | 1052 ++++-------------------------------------------- 1 file changed, 82 insertions(+), 970 deletions(-) diff --git a/solution.ipynb b/solution.ipynb index 18178f2..f3b1d9a 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "tags": [] }, @@ -146,20 +146,9 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -277,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -296,30 +285,9 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Create grid texture\n", "texture = numpy.zeros(tainted_test_dataset.data.shape[1:])\n", @@ -341,7 +309,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "tags": [] }, @@ -363,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -378,20 +346,9 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# visualize example 4s\n", "plt.subplot(1,4,1)\n", @@ -537,19 +494,11 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "selected torch device: cuda\n" - ] - } - ], + "outputs": [], "source": [ "import torch\n", "from classifier.model import DenseModel\n", @@ -569,7 +518,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -602,7 +551,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -629,25 +578,9 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DenseModel(\n", - " (fc0): Linear(in_features=784, out_features=256, bias=True)\n", - " (fc1): Linear(in_features=256, out_features=120, bias=True)\n", - " (fc2): Linear(in_features=120, out_features=84, bias=True)\n", - " (fc3): Linear(in_features=84, out_features=10, bias=True)\n", - ")" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Initialize the clean and tainted models\n", "model_clean = DenseModel(input_shape=(28, 28), num_classes=10)\n", @@ -681,7 +614,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -703,49 +636,11 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "938it [00:07, 117.64it/s] \n", - "938it [00:07, 119.34it/s] \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "model_clean trained\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "938it [00:07, 119.67it/s] \n", - "938it [00:07, 120.21it/s] " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "model_tainted trained\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], + "outputs": [], "source": [ "# We store history here:\n", "history = {\"loss_tainted\": [],\n", @@ -784,30 +679,9 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'negative log likelihood loss')" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Visualise the loss history:\n", "fig = plt.figure()\n", @@ -960,7 +834,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -990,7 +864,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": { "tags": [] }, @@ -1012,7 +886,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1073,64 +947,9 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n", - "/tmp/ipykernel_2521962/953204067.py:35: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " annot[i, j] = '%.1f%%\\n%d/%d' % (p, c, s)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxMAAANXCAYAAABOkwIqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd1hURxfA4R9dQEGKKIiIggW7Yom9xmisscfYGyr2jl2jYu8SS4y9xN5ibLH3giLSFEGxIIgFkF72+4N8G1dAkQhL5LzPs4/u3Llzzyx3Yc/O3LkaCoVCgRBCCCGEEEJ8Jk11ByCEEEIIIYT4b5JkQgghhBBCCJEpkkwIIYQQQgghMkWSCSGEEEIIIUSmSDIhhBBCCCGEyBRJJoQQQgghhBCZIsmEEEIIIYQQIlMkmRBCCCGEEEJkiiQTQgghhBBCiEyRZEIIkS5bW1t69eql7jBypAYNGtCgQYNM7ftffl179eqFra2tusMQQgiRQ0gyIUQu9PDhQ5ycnChevDh58uTByMiI2rVrs2zZMmJiYtQdXoY9evQIDQ0NNDQ0mDVrVpp1fvrpJzQ0NMibN282R/ffEhERwYwZM6hYsSJ58+ZFX1+fcuXKMX78eJ4/f67u8D6Lra2t8rzQ1NQkf/78lC9fngEDBnDt2rV/1facOXM4cODAlwlUCCG+AtrqDkAIkb3++OMPOnbsiJ6eHj169KBcuXLEx8dz8eJFxo4di5eXF2vXrlV3mJ8lT5487Nixg8mTJ6uUR0VFcfDgQfLkyaOmyP4bAgICaNKkCUFBQXTs2JEBAwagq6vL3bt3Wb9+Pfv37+f+/fvqDvOzVKpUidGjRwMQGRmJj48Pu3fvZt26dYwcOZLFixdnqt05c+bQoUMH2rZt+wWjFUKI/y5JJoTIRQIDA+nSpQtFixbl9OnTWFpaKrc5Ozvj7+/PH3/8ocYIM+f7779n3759eHh4ULFiRWX5wYMHiY+Pp1mzZpw+fVqNEeZciYmJtGvXjpCQEM6ePUudOnVUts+ePZt58+apKbrMK1y4MN26dVMpmzdvHl27dmXJkiWUKFGCQYMGqSk6IYT4esg0JyFykfnz5/Pu3TvWr1+vkkj8n729PcOHD/9oG2/fvmXEiBEUKVIEPT097O3tmTdvHsnJySr1Fi5cSK1atTAzM0NfXx9HR0f27NmTqj0NDQ2GDBnCgQMHKFeuHHp6epQtW5Zjx45luF81a9akWLFibN++XaV827ZtNGvWDFNT0zT3c3Nzo2zZsujp6WFlZYWzszNv375NVW/t2rXY2dmhr69P9erVuXDhQprtxcXFMW3aNOzt7dHT06NIkSKMGzeOuLi4DPflfVFRUYwePVr5WpcqVYqFCxeiUChU6v2b13Dv3r14eHgwadKkVIkEgJGREbNnz/5oG8nJySxdupSyZcuSJ08eChYsiJOTE2/evFGpd/DgQVq0aIGVlRV6enrY2dnx888/k5SUpFKvQYMGlCtXDm9vbxo2bIiBgQGFCxdm/vz5n+zPx+jr67NlyxZMTU2ZPXu2yuuYkfNVQ0ODqKgoNm3apJxG9f9rXx4/fszgwYMpVaoU+vr6mJmZ0bFjRx49evSvYhZCiJxOkgkhcpHDhw9TvHhxatWqlan9o6OjqV+/Plu3bqVHjx4sX76c2rVr4+LiwqhRo1TqLlu2jMqVKzNz5kzmzJmDtrY2HTt2THPk4+LFiwwePJguXbowf/58YmNjad++Pa9evcpwbD/++CM7d+5UfkAMCwvjxIkTdO3aNc3606dPx9nZGSsrKxYtWkT79u1Zs2YNTZs2JSEhQVlv/fr1ODk5UahQIebPn0/t2rVp3bo1T548UWkvOTmZ1q1bs3DhQlq1asWKFSto27YtS5YsoXPnzhnux/8pFApat27NkiVLaNasGYsXL6ZUqVKMHTs21WsNmX8NDx06BED37t0/O8b/c3JyYuzYscrrbnr37s22bdv47rvvVF7LjRs3kjdvXkaNGsWyZctwdHRk6tSpTJgwIVWbb968oVmzZlSsWJFFixZRunRpxo8fz59//pnpOAHy5s3LDz/8wLNnz/D29laWZ+R83bJlC3p6etStW5ctW7awZcsWnJycALhx4waXL1+mS5cuLF++nIEDB/LXX3/RoEEDoqOj/1XMQgiRoymEELlCeHi4AlC0adMmw/sULVpU0bNnT+Xzn3/+WWFoaKi4f/++Sr0JEyYotLS0FEFBQcqy6OholTrx8fGKcuXKKRo1aqRSDih0dXUV/v7+yjIPDw8FoFixYsVH4wsMDFQAigULFiju3bunABQXLlxQKBQKxapVqxR58+ZVREVFKXr27KkwNDRU7hcaGqrQ1dVVNG3aVJGUlKQsX7lypQJQ/Pbbb8qYLSwsFJUqVVLExcUp661du1YBKOrXr68s27Jli0JTU1N5/P9bvXq1AlBcunRJWfbh65qWAwcOKADFrFmzVMo7dOig0NDQUHm9/s1rWLlyZYWxsfFH67yvZ8+eiqJFiyqfX7hwQQEotm3bplLv2LFjqco/PCcUCoXCyclJYWBgoIiNjVWW1a9fXwEoNm/erCyLi4tTFCpUSNG+fftPxli0aFFFixYt0t2+ZMkSBaA4ePBgurGld74aGhqm+bNLq29XrlxJ1Q8hhPjayMiEELlEREQEAPny5ct0G7t376Zu3bqYmJgQFhamfDRp0oSkpCTOnz+vrKuvr6/8/5s3bwgPD6du3bq4u7unardJkybY2dkpn1eoUAEjIyMCAgIyHFvZsmWpUKECO3bsAGD79u20adMGAwODVHVPnTpFfHw8I0aMQFPzn1+D/fv3x8jISPlt9M2bNwkNDWXgwIHo6uoq6/Xq1QtjY+NUr42DgwOlS5dWeW0aNWoEwJkzZzLcF4CjR4+ipaXFsGHDVMpHjx6NQqFI9Q19Zl/DiIiIf31OGBsb8+2336r029HRkbx586r0+/1zIjIykrCwMOrWrUt0dDS+vr4q7ebNm1flmgddXV2qV6/+WedEev6/sldkZGSasX3qfE3L+/snJCTw6tUr7O3tyZ8/f4bbEEKI/yK5AFuIXMLIyAhQ/QD1uR48eMDdu3cpUKBAmttDQ0OV/z9y5AizZs3izp07KtcMaGhopNrPxsYmVZmJiUmqOfef0rVrVxYtWsTIkSO5fPkyEydOTLPe48ePAShVqpRKua6uLsWLF1du//+/JUqUUKmno6ND8eLFVcoePHiAj49Phl6bjHj8+DFWVlapPug7ODioxPZ/mX0NPzdp+9CDBw8IDw/HwsIize3v99vLy4vJkydz+vRpZXL7f+Hh4SrPra2tU50rJiYm3L17N9Ox/t+7d+8A1cT6c87XtMTExODq6sqGDRt49uyZyvUYH/ZNCCG+JpJMCJFLGBkZYWVlxb179zLdRnJyMt9++y3jxo1Lc3vJkiUBuHDhAq1bt6ZevXq4ublhaWmJjo4OGzZsSHWRNICWllaa7Sk+uND4U3788UdcXFzo378/ZmZmNG3a9LP2/zeSk5MpX758ukuOFilSJEuPn9nXsHTp0ty+fZsnT55kKsbk5GQsLCzYtm1bmtv/n1y9ffuW+vXrY2RkxMyZM7GzsyNPnjy4u7szfvz4VBfwf6lzIi3/fw/Y29sDn3++pmXo0KFs2LCBESNGULNmTYyNjdHQ0KBLly6p+iaEEF8TSSaEyEVatmzJ2rVruXLlCjVr1vzs/e3s7Hj37h1NmjT5aL29e/eSJ08ejh8/jp6enrJ8w4YNn33Mz2FjY0Pt2rU5e/YsgwYNQls77V9xRYsWBcDPz09lhCE+Pp7AwEBl//5f78GDB8rpSpAyjSUwMFBlGVo7Ozs8PDxo3Lhxhr/N/piiRYty6tQpIiMjVb5B//90oP/H9m+1atWKHTt2sHXrVlxcXD57fzs7O06dOkXt2rVVpvp86OzZs7x69Yp9+/ZRr149ZXlgYGCm4s6sd+/esX//fooUKaIc5fmc8zW9n+2ePXvo2bMnixYtUpbFxsamuTqYEEJ8TeSaCSFykXHjxmFoaEi/fv0ICQlJtf3hw4csW7Ys3f07derElStXOH78eKptb9++JTExEUj5VllDQ0Nlyc9Hjx5ly52DZ82axbRp0xg6dGi6dZo0aYKuri7Lly9X+aZ7/fr1hIeH06JFCwCqVq1KgQIFWL16NfHx8cp6GzduTPUhsVOnTjx79ox169alOl5MTAxRUVGf1Y/vv/+epKQkVq5cqVK+ZMkSNDQ0aN68+We1l54OHTpQvnx5Zs+ezZUrV1Jtj4yMZNKkSenu36lTJ5KSkvj5559TbUtMTFS+Tv8faXj/9Y6Pj8fNze1f9iDjYmJi6N69O69fv2bSpEnKxOBzzldDQ8M0EwQtLa1UoyYrVqxIteytEEJ8bWRkQohcxM7Oju3bt9O5c2ccHBxU7oB9+fJldu/erVw3Py1jx47l0KFDtGzZkl69euHo6EhUVBSenp7s2bOHR48eYW5uTosWLVi8eDHNmjWja9euhIaGsmrVKuzt7b/InPePqV+/PvXr1/9onQIFCuDi4sKMGTNo1qwZrVu3xs/PDzc3N6pVq6a88FdHR4dZs2bh5OREo0aN6Ny5M4GBgWzYsCHVNRPdu3dn165dDBw4kDNnzlC7dm2SkpLw9fVl165dHD9+nKpVq2a4H61ataJhw4ZMmjSJR48eUbFiRU6cOMHBgwcZMWKEysXW/4aOjg779u2jSZMm1KtXj06dOlG7dm10dHTw8vJi+/btmJiYpHuvifr16+Pk5ISrqyt37tyhadOm6Ojo8ODBA3bv3s2yZcvo0KEDtWrVwsTEhJ49ezJs2DA0NDTYsmXLF5m2lJZnz56xdetWIGU0wtvbm927d/PixQtGjx6tXNIV+Kzz1dHRkVOnTrF48WKsrKwoVqwYNWrUoGXLlmzZsgVjY2PKlCnDlStXOHXqFGZmZlnSPyGEyDHUto6UEEJt7t+/r+jfv7/C1tZWoaurq8iXL5+idu3aihUrVqgs0ZnWEqaRkZEKFxcXhb29vUJXV1dhbm6uqFWrlmLhwoWK+Ph4Zb3169crSpQoodDT01OULl1asWHDBsW0adMUH/7aARTOzs6pYszI8qnvLw37MR8uDft/K1euVJQuXVqho6OjKFiwoGLQoEGKN2/epKrn5uamKFasmEJPT09RtWpVxfnz5xX169dXWRpWoUhZTnTevHmKsmXLKvT09BQmJiYKR0dHxYwZMxTh4eGf1TeFIuW1HjlypMLKykqho6OjKFGihGLBggWK5ORklXr/5jX8vzdv3iimTp2qKF++vMLAwECRJ08eRbly5RQuLi6K4OBgZb0Pl4b9v7Vr1yocHR0V+vr6inz58inKly+vGDdunOL58+fKOpcuXVJ88803Cn19fYWVlZVi3LhxiuPHjysAxZkzZ5T16tevryhbtmyqY6R37LT6DSgAhYaGhsLIyEhRtmxZRf/+/RXXrl1Lc5+Mnq++vr6KevXqKfT19RWA8vV98+aNonfv3gpzc3NF3rx5Fd99953C19f3s34GQgjxX6ShUGTR10JCCCGEEEKIr5pcMyGEEEIIIYTIFEkmhBBCCCGEEJkiyYQQQgghhBAiUySZEEIIIYQQ4ivzyy+/UKFCBYyMjDAyMqJmzZr8+eefyu2xsbE4OztjZmZG3rx5ad++fZrLxn+KXIAthBBCCCHEV+bw4cNoaWlRokQJFAoFmzZtYsGCBdy+fZuyZcsyaNAg/vjjDzZu3IixsTFDhgxBU1OTS5cufdZxJJkQQgghhBAiFzA1NWXBggV06NCBAgUKsH37djp06ACAr68vDg4OXLlyhW+++SbDbco0JyGEEEIIIf4j4uLiiIiIUHnExcV9dJ+kpCR27txJVFQUNWvW5NatWyQkJNCkSRNlndKlS2NjY8OVK1c+K56v8g7YCWEB6g5BLcyKNvl0pa9QPl19dYegFiFRb9UdglrUsXBQdwhq4f4md/5eK2Rgqu4Q1CIgPFjdIaiFgY6eukMQ2SgiKuf+XsvJnyVdV25mxowZKmXTpk1j+vTpqep6enpSs2ZNYmNjyZs3L/v376dMmTLcuXMHXV1d8ufPr1K/YMGCvHjx4rPi+SqTCSGEEEIIIb5GLi4ujBo1SqVMTy/tRLxUqVLcuXOH8PBw9uzZQ8+ePTl37twXjUeSCSGEEEIIIf4j9PT00k0ePqSrq4u9vT0Ajo6O3Lhxg2XLltG5c2fi4+N5+/atyuhESEgIhQoV+qx45JoJIYQQQggh3peclHMf/6ZbycnExcXh6OiIjo4Of/31l3Kbn58fQUFB1KxZ87PalJEJIYQQQgghvjIuLi40b94cGxsbIiMj2b59O2fPnuX48eMYGxvTt29fRo0ahampKUZGRgwdOpSaNWt+1kpOIMmEEEIIIYQQX53Q0FB69OhBcHAwxsbGVKhQgePHj/Ptt98CsGTJEjQ1NWnfvj1xcXF89913uLm5ffZxvsr7TOTkK/CzkqzmlLvIak65i6zmlLvIak4iN8jRqzmF+Kk7hHTpFCyl7hBUyDUTQgghhBBCiEyRZEIIIYQQQgiRKXLNhBBCCCGEEO9LTlZ3BP8ZMjIhhBBCCCGEyBRJJoQQQgghhBCZItOchBBCCCGEeI9CIdOcMkpGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvS05SdwT/GTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifrOaUYbl+ZCIqKpq5S1fzbbueODZsw09Oo/D08VNuj46OYfYiNxq37YZjwza0/mkAv+//45PtRkS+Y9aiVTRo3ZXKDVrRoks/zl++rtx+5PhpGv/QnVrNOjJ/+VqVfZ8Fh9CiSz/eRUV9uY5mUP8B3fH0Pk/oKx9On92Ho2OFdOuWdijBlm1ueHqfJyIqgMHOvVPV6dS5Dd5+F3n89DZz5k5S2WZjUxj3O3+RL1/eL96Pz9Wz349c9TjBw2B3Dp/cQaUq5dOt27VHB/Yd3YxX4GW8Ai+zc/+vqeo7DemFx/3zeNw/j5NzT5VtlR3L8+eZXWhpaWVJX8Snte3Zmp1XtnLC/yhuh1dQulKpdOs269iUs09PqTxO+B9VqdPZqSP77+xm/53ddBrQQWWbQ+XSrDnqhpaW+n/d5tb39099OnL61iE8n1xi97GNVKhcNt26TVs0ZO/Jzdz0P8OdRxc4eGYbbTp+r1Knz+BuXPE+wRXvE/QZ9JPKtgpVyrLv1BZ5f6tRbj3Pc2u/hfqp/6+bmk2du4wrN27jOnUM+7f8Qq3qVeg/fCIhL8MAmL9iLRev3cR16jgObV9L905tmbPEjTMXrqbbZkJCAv1HTORZcAiLZ03iyI5fmT5+GBYFzAF48zacaXOXMca5H2uWzOLI8dOcvXRNuf+shSsZMbA3eQ0Ns7bzH2jXvgVz5k5kruty6tZuhaenD/sObsK8gFma9Q309Xn0KIjpU+fz4kVoqu2mZiasWOXK5Imu/NC6J527tKFZs0bK7YuX/sy0qfOJjHyXZX3KiNY/NGParHEsnudGswYd8b7nx7a9azAzN02zfs061Ti49yidWvWhddOfeP7sBdv3raWQpQUADmVLMtZlCIP7jsW531jGThpG6TIlANDS0mLu4mlMGDWTpCS5uEsdGrZqwOCpA9m4ZAv9mw/koXcAC7bOJb9Z/nT3eRcRRbvKHZWPzt90VW4r7lCM3mN6MnPwbH52nkPfcb0pVroYAFpamoxyHcFil2UkJan3W67c+v7+vu23uMwcycqF62jbuBu+XvdZv2sFpuYmadZ/+yaC1Ut+o3Pz3rRq0IW9Ow7junwqdRp+A0CpMvYMHz+QkQMmMsppEiNcBlHSwQ5IeX/PXDiRaWNc5f2tJrn1PM+t/RY5Q65OJmLj4jh17iKjnPtStVJ5bKytcO7bDRtrK+Xowx1PH9o0b0L1KhUobFmQjm2+p5R9cZXRiw/tO3KC8IhIls+dSpUKZSlsWZBqlStQukRxAJ4+f0HevIY0b1Kf8g6lqFalIgGPngBw9ORZtLW1+bZB7ax/AT4wZGhfNm34nW1b9uDn68+IYZOJiYmhe4+OadZ3d7/LlElz2bvnCHFx8am2F7MtQkREJPv2/oG7+13On7tKydIpf3Q7dGxFQkIChw8dz9I+ZUT/wT3ZvnkPu7Yf4IHfQyaMmkFMdCxdurVLs/7QAePZtH4nXvd8efggkDHDpqKpoUmdeikfNuxLFMPH6z6XLlzj4vlr+Hjdx75EyofLQcN6c/XyTTxu38u2/glVHQe0548dRzm26ziPHwSxeMJSYmPj+L5Ls/R3Uih4/fKN8vEm7K1yk42dDQE+gdy+fAf3S7d56BOAjV0RADoP7IzHtbv4eaT/+yK75Nb3d++BP7Fr6wH27TjMw/uBTB3jSmxMLB26tk6z/vXLtzh59CwPHzziyaNnbF67Ez9vfxxrVAKgeAlb/LwfcPXiTa5cuIGftz/FS9gC0G9Id25cccfzjnc29U58KLee57m131kqOTnnPnKYXJ1MJCUmkZSUjJ6ujkq5np4u7ne9AKhU3oEzF68S8jIMhULB9VsePAp6Rq3qVdJt9+zFq1Qs58DsRauo1/JH2nYbyNpNO5XfVNlYWxEbG4vPfX/CIyLx8r1PKftihEdEsmLdZiaOGpx1nU6Hjo4OlSqX48yZS8oyhULB2TOXqF69cqbafPjwEfr6eahQsQwmJsZUcayA1z1f8uc3YvKUkYwZNf3LBP8v6OjoUKFSGS6cvaIsUygUXDx3FcdqFTPUhr5BHrR1tHn7NhwAH+8HFLO3xcraksJFLCluXxRfH3+K2hahc9cfmD97eZb0RXyato42pcqX5NYFd2WZQqHg1gV3ylQpk+5++ob67Ly6jV3XtzNr/UxsSxZVbgvwDcS6eGEsrCwoWNiCIsWsCfR7hFVRS5p3/o718zdkaZ8yIve+v7UpW7E0l8/9M/KrUCi4fP46laqmPwXkfTXrVqOYXVFuXLkNwH1vf2ztbLAsXBAr60LY2tnwwOchRWwL0+7HViyd80uW9EV8Wu49z3Nnv0XOkasvwDY0NKBiOQdWb9xB8aI2mJnm5+ipc3jc88WmsCUAE0cOYvq85TRu2x1tLS00NDWYPn44VSulP6f+6fMXPHP3oEXThvyycCZBT58za9EqEpOSGNznJ4yN8jF78mgm/ryI2Lg4WjVrTO0ajkxxXULX9q14FvyCoeOnk5iYxOC+P9G0Yd0sfy3MzEzQ1tbmZWiYSnloaBglS9plqs23byMYOGAsa9YtQj+PHju37+evUxdY6TaXtWu2UNTWmp2716Kjo43r7OUcPPDnl+jKZzE1y4+2tjZhL1+plL98+Qq7v0cTPmXS9NGEvAhVJiT+9wOY9/NSdu5bB8DcmUvxvx/Azv2/MmvaIho0qsOoCYNJTEhkqosr1y7f+rKdEukyNjVGS1uL1y/fqJS/CXuDjX2RNPcJeviEeaMXEuATgKGRIZ2dOrLywHJ6N+7Ly+AwgvyD+HXubyzcMQ+AdXPXE+QfxKId81kzey3VG1Sl18geJCYmsWLaKu5e88zyfn4ot76/TUz///5+rVIeFvqa4va26e6XN58hFzz/RFdXl+SkJKaPn6dMSB4+eMTi2W5s2OMGwKJZq3j44BEb96xiwYzl1GlUk6FjB5CYmMisSQu5+XcSIrJebj3Pc2u/Rc6Rq5MJANcpY5jquoRGbbuhpaWJQ0l7mjepj7efPwDb9hzirpcvK+dNw7JQQW7d8WT2IjcszM2oWS3tjD9ZocDUJD/Txw1DS0uLsqVLEBr2ig3b9zC4T8rFek3q16ZJ/X+mMt24fZf7/oFMHDmI7zv1Zf6M8ZibmvJj/+E4ViqPmUn+LH8tssKRwyc4cviE8nntOtUpV640Y0dP547nGfr0Gk5IyEvOnDvApUvXU32oz+mcR/SjdbvmdGzVS2WoeMuGXWzZsEv5vGOXNrx7F8WtGx6cv3GEFo06Y2lVCLdfF1KzUlPi4xPUEb7IAG93H7zdfZTP7930YvPZ32j1U0t+W7gRgENbj3Bo6xFlne86fEt0VDRet7zZcm4jTi2dKWBpztRVk/ixVncSvpKf99f6/o56F02bhl0xNDSgZt1quMwcyZNHz7j+d+K/c9Nedm7aq6z/Q+cWRL2L5vZNT45f2Uv7pj0oZGnBkrVzaOTY+qv5eedWX+t5/im5td//p5DVnDIs1ycTNtZWbFy1gOiYWKKioilgbsroKa5YWxUiNi6OZWs2scx1CvVrVQeglH0xfB8EsHHH3nSTiQJ/f0vw/moexYsWIezVGxISEtDRUZ1WFR8fz6yFq3CdOpagp8EkJSVRrXLKEHzRIoXx9PKlQZ1vsugVSPHq1RsSExMpYGGuUm5hYU5IyMsvcgxdXV0WL5nJgP6jKW5ni7a2Fpcupqxw9dA/kKpVK3Lsz9Nf5FgZ9frVWxITE1NdpFaggFmqb3k+5DSkF84j+tKlbT98vO6nW8/END8jxw+ifYueVK5agQD/xwQGBBEYEISOjjbF7W3x9X7wRfojPi78dThJiUmYFlC9+NbE3ITXoW/S2UtVUmISD+75U9jWKs3txiZG9BzZg+EdRuJQ2YEngU95FviMZ4HP0NbRxrq4NYG+gf+6L58jt76/37z+//tbdTEFcwtTXoam/8FHoVAQFPgUAJ9797ErWQynEb2UycT7TEyNGTKmP11bD6BilXI8ehjE44AnPA54go62NsXsbLjv8/DLdkykKbee57m13yLnyNXXTLzPQD8PBcxNCY+I5PL1WzSq+w2JiYkkJiaiqaGhUldLS5Pkj1wAU6l8WYKePlep8+jJMwqYmaZKJADWbNxJnW+qUqaUPcnJSSS+twpIYmISSdlwsU1CQgJ3bt+jQYNayjINDQ3qN6jF9etfZph+3HhnTp06j8cdL7S0NNHW+ieX1dbRVstSigkJCdy9402d+v8kaxoaGtSpV4NbNzzS3W/QsD6MGDuQbh2cuHvH66PHmDFnPOvcNhP8PAQtTU10dP7pt5a2FlqasoRkdklMSMTP8z5V6vxzzZOGhgaOdSrj7Z6xi2Y1NTUpXroYr0Jfp7ndefogdv+6l5fBYWhqaaKt/d7PW0sLLc3s/7Wbe9/fiXh5+FKzXnVlmYaGBjXrVuPOzbsZbkdDUxNdXd00t038eTQb1+wgJDg0pd8fvr9lidhsk3vP89zZb5Fz5PqRiUvXbqFQKLC1sSbo6XMWrVpPMRtr2rZoio62NlUrl2fRqvXo6elhVciCm7c9OfTnX4wd1l/ZhsvPC7EwN2PkoJR1mjv/0IIdew8xd+lqunZozeOnz1m3+Xd+6ph69ZCHgY85dvo8uzesBKBY0SJoamqy9/BxzM1MCAx6QjmHktnyWqxcsZ7Vaxdy+7YnN296MNi5NwYGBmzdsgeANesW8vx5CDOmLQBSLvoq7WAPgK6uDpZWBSlfwYGod9EEBDxWabtUaXvatW9JnVotAbjv95Dk5GS69+hEaMhLSpa0w/1Wxv+4f0nr3DaxxG0Od297cdvdk/6DuqNvqM/v2/YDsOyXOQQHhzJ35lIABg/vyxiXIQzpP44nQc+V3wZFRUUTHRWt0nbdBjUpZmfL8EETAfC4fQ+7EsVo2KQOVoUtSU5K5qF/9n5LndvtXrsXlyXj8PPww+eOHx36tSOPfh7+/P0YAC5LxxP2Iox1c9cD0GNEN7zdfXj26Dl5jQzpMrATBa0L8seOo6nadqxbBevi1riOmA+An4cfNvZFqN6wGhZWFiQnJxMU8CT7Ovue3Pr+3rB6G/NWTOfeHW/uunvR06kr+gb67N1xGID5K2cQ8iKURbNWAeA0vBeed3x48ugpuro61G9SmzYdv2f6ONdUbdeqXwNbOxvGDZkGwN3b3hS3L0q9xrWwtCpIclIyAf6PU+0nsk5uPc9za7+zVA5cNSmnyvXJROS7KJau3kDIyzCMjfLxbf06DHPqic7f3yYunDGBpas3MmHGfMIjIrEqZMEwp550bttC2UZwSKjK6IVlwQKsWTKb+cvW0K7nYCzMzejWsQ19u6ku0aZQKJg+fzljh/bHQD8PAHn09Jg1aRSzF7kRn5DAxJGDKVhAdegyq+zb+wfm5qZMnDySggXN8bzrQ/u2vZTTfaytrVRGWywtLbh05Z8b+A0fMYDhIwZw4fxVWjTvqtL28hVzmDhhNtHRMQDExsYxyGkcC5fMQE9PlzGjphEcHJINvUzt0P5jmJqbMmbiEApYmOPl6Uu3Dk7K+Z9W1pYkJyuU9Xv06Yyeni7rNi9VaWfR3FUsnuemfJ4njx6z509iUJ8xKBQp+wc/D2HK+DksXjmb+Ph4RgyeSGxsXNZ3UiidOXyW/GbG9B7TC9MCJvh7P2Rcdxflcq8FC1ugeO88z2ecjzHzR2FawIR34e/w83yAc5vhPH4QpNKubh5dhs8aysxBs5Q/75fBYSyfspIJi8YSH5+A64j5xMemXoYxO+TW9/fRAycxNTNh2PiBFLAww+feffp2Hsqrvy/KtrQuRPJ7c6P1DfSZPn88hSwtiI2NI+DBI8YOnsLRAydV2tXLo8fUueMY2d9F+fMOCQ7l54kLcF0+lfi4BMYPnUacvL+zVW49z3Nrv0XOoKH4/2/Br0hCWIC6Q1ALs6JN1B2CWuTT1Vd3CGoREvVW3SGoRR0LB3WHoBbub3Ln77VCBmnfPPJrFxAerO4Q1MJAR0/dIYhsFBGVc3+vxT24rO4Q0qVXotanK2UjtY5MhIWF8dtvv3HlyhVevHgBQKFChahVqxa9evWiQIEC6gxPCCGEEELkRrKaU4ap7QLsGzduULJkSZYvX46xsTH16tWjXr16GBsbs3z5ckqXLs3Nmzc/2U5cXBwREREqj7g4GVYWQgghhBAiq6ltZGLo0KF07NiR1atXo/HBakkKhYKBAwcydOhQrly5kk4LKVxdXZkxY4ZK2eSxw5g6bvgXj1kIIYQQQgjxD7VdM6Gvr8/t27cpXbp0mtt9fX2pXLkyMTExH20nLi4u1UiEZuQz9PRy37xLuWYid5FrJnIXuWYid5FrJkRukKOvmfA9p+4Q0qVXur66Q1ChtpGJQoUKcf369XSTievXr1OwYMFPtqOnp5cqcUiI//jNxoQQQgghhBD/ntqumRgzZgwDBgxg+PDhHDp0iGvXrnHt2jUOHTrE8OHDGThwIOPGjfsix4qKimbu0tV8264njg3b8JPTKDx9/FTqPHwUxJBx0/mmaXuqNW5L577DCH4RqlLnzj0f+gydQLXGbanxbTt6Dh5L7AejIrFxcVRr3Jagp88B2LH3MK26DsCxYRtadunHwT9PpYpvy+/7admlH44N29D4h+7MW7aGuDjV5SN37D1M0/Y9qdKwNT/2H4Gnt1+qdrJbrdrV+H33Ovz8rxARFUCLlt+qO6RsMWRkP/7463f8gq7jcf8867cux87eVt1hiSzSa1QPzj49pfLYfPY3dYeV5XLr+/vHXu05dHYH7gFncQ84y+9Hf6Ne45y1cor4cnLreZ5b+y2yhtpGJpydnTE3N2fJkiW4ubmR9Pddn7W0tHB0dGTjxo106tTpixxr6txl+Ac8wnXqGCzMzTh8/DT9h0/k4LY1FCxgTtDT5/QYNIZ2Lb/DuV83DA0MeBgYhK7eP3c8vXPPh4GjJtOve2cmjhyElpYWfv4Bqe6OfeX6bSwLWWBjbcXO/UdYunoD08cPp5xDSTx9/Jg+dznG+fLSoE7KHZf/OHGGJas38LPLSCqVL8OjoKdMnr0YDQ0Nxg0bAMCfp84xf8Vapo4dSoUypdiy6wBOoyZzeMc6zEzyf5HXKDMMDQ245+nDls272b5ztdriyG7f1KrGpl93cOe2J9ra2kyYMpzt+9bR4JvWxER/fFqe+G8K9A1k9I//fLmRlJj0kdpfh9z6/n7xPJRFs1byKCAIDTT4oUtL3DYvom2jn/D3y7lTMkTm5NbzPLf2+7PIak4ZptalYTt37kznzp1JSEggLCxlapK5uTk6Ojpf7BixcXGcOneR5XOnUbVSeQCc+3bj3KVr/L7/D4YN6MnytZuoW7Mao537KvezsbZSaWf+sjX81KEN/br/k+AUK2qd6ninL16h4d+JwuFjp+nY5nuaN0mZ21aksCVePg9Yv223Mpm44+lD5fJlaNG0IQCFLQvy/bcNuOvtq2xz8+/76dCqOT+0aArA1LFDOX/5BvuPnFCJJ7udPHGOkydy7pzCrNKto5PK8xGDJ+Hpf5EKlcpw7fItNUUlslJSUhKvX75RdxjZKre+v8+cuKDyfMkcN37s1Z5KVctLMvEVyq3neW7tt8gaapvm9D4dHR0sLS2xtLT8ookEpHyDmJSUjJ6uart6erq43/UiOTmZ85dvYFukMANGTqJeiy782H8Ef53/52Ylr9685a63H6YmxvzkNIp6LX+kl/NY3D3uqbSZnJzMuUvXaVi3JgAJCQno6eqmOq6n930SEhMBqFTeAW8/f+W0pSfPgjl/5QZ1v6mmbMPb7wHfVKukbENTU5NvqlbC457Pl3mRxL9iZJQPgLdvwtUcicgqhYsVZs/NnWy/tIVJK1ywsLJQd0giG2hqatKibVMMDPS5feOuusMRQogcSa0jE9nB0NCAiuUcWL1xB8WL2mBmmp+jp87hcc8Xm8KWvH7zluiYGNZv3cXQ/j0ZNagPF6/dYsTEWfy2Yi7VKlfg6bOUVTXcftvGmCH9KF2iOIf+/Iu+w104sGU1RYsUBsDDK2U0oUKZUgDUqu7I3iPHaFSvJmVK2ePl+4C9h4+TmJjI27cRFDA3pUXThrwJj6D7oDGgUJCYlESntt8zoGcXAN68jSApKRkzUxOVfpmZmhAY9DS7XkaRDg0NDWa4juf6VXf8fPzVHY7IAt63fZg7cgFPAp5gZmFGz5HdWb5vCb0b9yMmSqa1fY1KOtjx+58b0NPTJToqBudeY3l4P1DdYQkhslOyTHPKqK8+mQBwnTKGqa5LaNS2G1pamjiUtKd5k/p4+/mTnJyyMm7DujXp0eUHAEqXtOOOpze7DhylWuUKJP+9em7HNt8rpxo5lLTn6q077DtygpGDegNw5sIV6teujqZmyoDPwN4/Evb6NT8NGIkCBWYmJrRp3pjftu1BQzPlWovr7ndZt/l3Jo92pkLZUgQ9fc7cZWtYvWE7A3t3zdbXSXy+OQsnU8qhBD80767uUEQWuX7mhvL/AT6B+Nz2YefV7TRsVZ+jO4+pMTKRVQL9H9OmYVfy5ctLs9aNmbdiOj+1GSAJhRBCpCFXJBM21lZsXLWA6JhYoqKiKWBuyugprlhbFcIkvxHaWlrY2dqo7FPctgjud70BKGCWss65XbEP6hS14UXIPys+nbl4TZlYAOTR02PWxFFMGzeMV6/fUMDMlN2H/sTQQB/T/MYArFy3mVbfNaJD62YAlLQrRkxsHDPmLWdAzy6Y5DdCS0uTV69V52u/ev0G8w9GK0T2mjV/Ek2+q0+773sS/DxE3eGIbPIuIoqnAU8pbFtY3aGILJKQkEhQYMrIr9ddX8pXKkPPAT8ydcwcNUcmhBA5T464ZiK7GOjnoYC5KeERkVy+fotGdb9BR0eHsg4lU00ZevTkGVaFUuZFF7YsiIW5GY8eq9Z5/OQploUK/v3/ZwS/CKVmtcqpjqujrU0hiwJoaWlx7NQ56teuoRy9iI2LQ1NTdUUorb+3KRQKdHR0KFOqBNdu3lFuT05O5tqtO1Qslztv3pUTzJo/iWYtGtOpdR+eBD1TdzgiG+kb5MHK1pJXoa/UHYrIJhqamujqfdnr+YQQOZwiOec+cphcMTJx6dotFAoFtjbWBD19zqJV6ylmY03bv6cs9e7anjFT51K1UjmqV6nIxas3OXfpGhtWzANS5sX37tqeVeu3UqpEMUqXsOPg0VMEPn7K4lmTADh94QrfVK2Efp48yuM+CnqKp899KpQpRUTkOzbt3MeDgMfMnjxGWad+7Rps3rmP0iXtqFCmNEFPn7Ni3Wbq166BlpYWAD06/8Ck2YsoW7oE5cqUYuuuA8TExtG2hXrXhTY0NKC4XVHlc1vbIpSv4MCb1+E8/fs+G1+jOQun0LbD9/TpOpR376IpYGEOQGREJLGxcZ/YW/zXDJo8gMunrhLyNASzgmb0Ht2T5KRk/jpwRt2hZanc+v4ePdmZc39dJvjpCwzzGtCqfTNq1HakT6eh6g5NZIHcep7n1n6LrKGhUPx9QcBXJCFMdfm+Y3+dZ+nqDYS8DMPYKB/f1q/DMKee5MtrqKyz78hxft2yi5DQMGxtrHHu141Gf6/K9H+/btnFjn2HiYiIpKR9cUYP7kOViuUA6DFoDK2bN1FOV4KUG+GNnz6PR0HP0NbWonqViowc1EdlSdnExCTWbt7J4WN/EfryFSYmxjSoXYNhA3pilC+vst72PYfYsH0vYa9fU7qEHS4jBlKhrOrdw82KNvn3L95nqFO3BkeP7UhVvm3rHgY5fZkbDmZEPl39bDsWwLM3XmmWjxw8iV07DmRbHCFRb7PtWDlJHYvsHZGbumoSFWqUx8jEiPDX4Xhev8ev83/j+ePgbI3D/U32LkuaU97fhQxMs+1YALOXTqFm3WpYFDQnMuIdft4PWLtiM5fPXcvWOALCs/f8yikMdPSy9Xg55TzPbjml3xFROXe55bh7J9UdQrr0yuWsmwzmimQiq715G07D1j9x6sAWtV7HkN3JRE6R3clETiHJRO6S3clETpHdyUROIcmEyA1ydDJx97i6Q0iXXoXv1B2Cilx1zURWCY+IZOzQ/nJBtBBCCCGEyFVyxTUTWc3Wxhpbm9R3wxZCCCGEEOJrJsmEEEIIIYQQ71EoktQdwn+GTHMSQgghhBBCZIokE0IIIYQQQohMkWlOQgghhBBCvC8H3hwup5KRCSGEEEIIIUSmSDIhhBBCCCGEyBSZ5iSEEEIIIcT7kmWaU0bJyIQQQgghhBAiUySZEEIIIYQQQmSKTHMSQgghhBDifbKaU4bJyIQQQgghhBAiUySZEEIIIYQQQmSKTHMSQgghhBDifclJ6o7gP0NGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvS5ZpThklIxNCCCGEEEKITJFkQgghhBBCCJEpMs1JCCGEEEKI98lqThkmIxNCCCGEEEKITPkqRyb0reqqOwS1iHl+Qd0hqEVZh07qDkEtChqqOwL1uBjqo+4Q1MJAR0/dIajFi+jX6g5BZKMqJsXVHYJauL8JUHcIQmTaV5lMCCGEEEIIkWmymlOGyTQnIYQQQgghRKZIMiGEEEIIIYTIFJnmJIQQQgghxPtkmlOGyciEEEIIIYQQIlMkmRBCCCGEEEJkikxzEkIIIYQQ4j0KRZK6Q/jPkJEJIYQQQgghRKZIMiGEEEIIIYTIFJnmJIQQQgghxPtkNacMk5EJIYQQQgghRKZIMiGEEEIIIYTIFJnmJIQQQgghxPsUMs0po2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+Wc0pw2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+Wc0pw2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+Wc0pw2RkQgghhBBCCJEpkkwIIYQQQgghMkWSiVwqKiqauUtX8227njg2bMNPTqPw9PFTbo+OjmH2Ijcat+2GY8M2tP5pAL/v/+OjbSYkJvLLb9to1rE3VRq2pl3PwVy8elOlzpHjp2n8Q3dqNevI/OVrVbY9Cw6hRZd+vIuK+nIdzaCf+nTk9K1DeD65xO5jG6lQuWy6dZu2aMjek5u56X+GO48ucPDMNtp0/F6lTp/B3bjifYIr3ifoM+gnlW0VqpRl36ktaGlpZUlfPkfPfj9y1eMED4PdOXxyB5WqlE+3btceHdh3dDNegZfxCrzMzv2/pqrvNKQXHvfP43H/PE7OPVW2VXYsz59nduWIfudW/Qd0x9P7PKGvfDh9dh+OjhXSrVvaoQRbtrnh6X2eiKgABjv3TlWnU+c2ePtd5PHT28yZO0llm41NYdzv/EW+fHm/eD8+V27td27Vtmdrdl7Zygn/o7gdXkHpSqUytF+j1g04+/QUs36doVLe2akj++/sZv+d3XQa0EFlm0Pl0qw56oaWlvo/Tsl5/oUpknPuI4dR/9kv1GLq3GVcuXEb16lj2L/lF2pVr0L/4RMJeRkGwPwVa7l47SauU8dxaPtaundqy5wlbpy5cDXdNles3cTug38yceQgDm5dQ6e23zPc5Wd87vsD8OZtONPmLmOMcz/WLJnFkeOnOXvpmnL/WQtXMmJgb/IaGmZt5z/wfdtvcZk5kpUL19G2cTd8ve6zftcKTM1N0qz/9k0Eq5f8RufmvWnVoAt7dxzGdflU6jT8BoBSZewZPn4gIwdMZJTTJEa4DKKkgx0AWlpazFw4kWljXElKSsq2Pqal9Q/NmDZrHIvnudGsQUe87/mxbe8azMxN06xfs041Du49SqdWfWjd9CeeP3vB9n1rKWRpAYBD2ZKMdRnC4L5jce43lrGThlG6TAkgpd9zF09jwqiZau93btWufQvmzJ3IXNfl1K3dCk9PH/Yd3IR5AbM06xvo6/PoURDTp87nxYvQVNtNzUxYscqVyRNd+aF1Tzp3aUOzZo2U2xcv/ZlpU+cTGfkuy/qUEbm137lVw1YNGDx1IBuXbKF/84E89A5gwda55DfL/9H9ClkXZNAUJzyu3lUpL+5QjN5jejJz8Gx+dp5D33G9KVa6GABaWpqMch3BYpdlJCWp9wOenOdCnSSZyIVi4+I4de4io5z7UrVSeWysrXDu2w0bayvl6MMdTx/aNG9C9SoVKGxZkI5tvqeUfXGV0YsPHT52mv49OlOvVnWKFLakyw8tqVuzGht37APg6fMX5M1rSPMm9SnvUIpqVSoS8OgJAEdPnkVbW5tvG9TO+hfgA70H/sSurQfYt+MwD+8HMnWMK7ExsXTo2jrN+tcv3+Lk0bM8fPCIJ4+esXntTvy8/XGsUQmA4iVs8fN+wNWLN7ly4QZ+3v4UL2ELQL8h3blxxR3PO97Z1Lv09R/ck+2b97Br+wEe+D1kwqgZxETH0qVbuzTrDx0wnk3rd+J1z5eHDwIZM2wqmhqa1KmXkkTZlyiGj9d9Ll24xsXz1/Dxuo99iZQ/uoOG9ebq5Zt43L6Xbf0TqoYM7cumDb+zbcse/Hz9GTFsMjExMXTv0THN+u7ud5kyaS579xwhLi4+1fZitkWIiIhk394/cHe/y/lzVylZOiVp7tCxFQkJCRw+dDxL+5QRubXfuVXHAe35Y8dRju06zuMHQSyesJTY2Di+79Is3X00NTWZtMKFDYs2ERwUrLLNxs6GAJ9Abl++g/ul2zz0CcDGrggAnQd2xuPaXfw80v+7mF3kPBfqJMlELpSUmERSUjJ6ujoq5Xp6urjf9QKgUnkHzly8SsjLMBQKBddvefAo6Bm1qldJt934hAR0dXVTtXn77zZtrK2IjY3F574/4RGRePnep5R9McIjIlmxbjMTRw3+wj39NB0dbcpWLM3lc/+MkCgUCi6fv06lqukPEb+vZt1qFLMryo0rtwG47+2PrZ0NloULYmVdCFs7Gx74PKSIbWHa/diKpXN+yZK+fA4dHR0qVCrDhbNXlGUKhYKL567iWK1ihtrQN8iDto42b9+GA+Dj/YBi9rZYWVtSuIglxe2L4uvjT1HbInTu+gPzZy/Pkr6IT9PR0aFS5XKcOXNJWaZQKDh75hLVq1fOVJsPHz5CXz8PFSqWwcTEmCqOFfC650v+/EZMnjKSMaOmf5ng/4Xc2u/cSltHm1LlS3LrgruyTKFQcOuCO2WqlEl3vx4ju/H21VuO7jyWaluAbyDWxQtjYWVBwcIWFClmTaDfI6yKWtK883esn78hS/ryOeQ8zyLJyTn3kcPI0rC5kKGhARXLObB64w6KF7XBzDQ/R0+dw+OeLzaFLQGYOHIQ0+ctp3Hb7mhraaGhqcH08cOpWin9OfW1aziyeec+qlYqR5HClly9eYe/zl0mKTllWouxUT5mTx7NxJ8XERsXR6tmjaldw5Eprkvo2r4Vz4JfMHT8dBITkxjc9yeaNqyb5a+FiWl+tLW1CXv5WqU8LPQ1xe1t090vbz5DLnj+ia6uLslJSUwfP0+ZkDx88IjFs93YsMcNgEWzVvHwwSM27lnFghnLqdOoJkPHDiAxMZFZkxZy8+8kJDuZmv2/369Uyl++fIXd36MJnzJp+mhCXoQqExL/+wHM+3kpO/etA2DuzKX43w9g5/5fmTVtEQ0a1WHUhMEkJiQy1cWVa5dvfdlOiXSZmZmgra3Ny9AwlfLQ0DBKlrTLVJtv30YwcMBY1qxbhH4ePXZu389fpy6w0m0ua9dsoaitNTt3r0VHRxvX2cs5eODPL9GVz5Jb+51bGZsao6WtxeuXb1TK34S9wca+SJr7lK9WjhZdmtOvqVOa24P8g/h17m8s3DEPgHVz1xPkH8SiHfNZM3st1RtUpdfIHiQmJrFi2iruXvP8sp3KADnPhbpJMpFLuU4Zw1TXJTRq2w0tLU0cStrTvEl9vP1Srm/YtucQd718WTlvGpaFCnLrjiezF7lhYW5GzWppf9MxYbgT0+ctp1XXAWhoQBErS9q2+Jb9R04o6zSpX5sm9f+ZynTj9l3u+wcyceQgvu/Ul/kzxmNuasqP/YfjWKk8Zib5s/R1yKyod9G0adgVQ0MDatathsvMkTx59Izrf39A3rlpLzs37VXW/6FzC6LeRXP7pifHr+ylfdMeFLK0YMnaOTRybE1CfIK6upIpziP60bpdczq26qUyRL5lwy62bNilfN6xSxvevYvi1g0Pzt84QotGnbG0KoTbrwupWakp8f+xfgtVRw6f4Mjhf97ftetUp1y50owdPZ07nmfo02s4ISEvOXPuAJcuXU+VvP5X5dZ+f230DfWZuGw8C8YtJvxNRLr1Dm09wqGtR5TPv+vwLdFR0Xjd8mbLuY04tXSmgKU5U1dN4sda3f9zv8/TI+e5yChJJnIpG2srNq5aQHRMLFFR0RQwN2X0FFesrQoRGxfHsjWbWOY6hfq1qgNQyr4Yvg8C2Lhjb7rJhKlJfpbPnUpcXDxvIyKwMDdjyS+/YW1VKM368fHxzFq4CtepYwl6GkxSUhLVKqdMLSpapDCeXr40qPNN1rwAf3vz+i2JiYmYF1C96NjcwpSXoen/YlQoFAQFPgXA59597EoWw2lEL2Uy8T4TU2OGjOlP19YDqFilHI8eBvE44AmPA56go61NMTsb7vs8/LId+4TXr/7fb9WL8woUMEv17daHnIb0wnlEX7q07YeP1/1065mY5mfk+EG0b9GTylUrEOD/mMCAIAIDgtDR0aa4vS2+3g++SH/Ex7169YbExEQKWJirlFtYmBMS8vKLHENXV5fFS2YyoP9oitvZoq2txaWL1wF46B9I1aoVOfbn6S9yrIzKrf3OrcJfh5OUmIRpAdXFM0zMTXgd+iZV/cJFrbC0scR1wyxlmYamBgB/PTpO9/q9eP5Y9RoKYxMjeo7swfAOI3Go7MCTwKc8C3zGs8BnaOtoY13cmkDfwCzoXfrkPM8iOXA6UU4l10zkcgb6eShgbkp4RCSXr9+iUd1vSExMJDExEU0NDZW6WlqaJGfgzaWnp0vBAuYkJiVx8uwlGtatmWa9NRt3UuebqpQpZU9ychKJ763yk5iYRFI2vJETEhLx8vClZr3qyjINDQ1q1q3GnZt3P7KnKg1NzVTXi/zfxJ9Hs3HNDkKCQ9HS0kRb558cXktbSy1LpSYkJHD3jjd16v+TrGloaFCnXg1u3fBId79Bw/owYuxAunVw4u4dr48eY8ac8axz20zw8xC0NDXR+bDfmrJEbHZJSEjgzu17NGhQS1mmoaFB/Qa1uH79y0yzGzfemVOnzuNxxyvlPNf65+etraOttvM8N/Y7t0pMSMTP8z5V6vxzbZ+GhgaOdSrj7Z560Yugh0H0btyPft85KR+XT1zh9uU79PvOidDnqT+IO08fxO5f9/IyOAxNLU20td/7vaalhZZm9n+skvNcqJuMTORSl67dQqFQYGtjTdDT5yxatZ5iNta0bdEUHW1tqlYuz6JV69HT08OqkAU3b3ty6M+/GDusv7INl58XYmFuxshBKetT3/XyJeTlK0qXKE7oy1e4/bYVhUJBn586pDr+w8DHHDt9nt0bVgJQrGgRNDU12Xv4OOZmJgQGPaGcQ8lseS02rN7GvBXTuXfHm7vuXvR06oq+gT57dxwGYP7KGYS8CGXRrFUAOA3vhecdH548eoqurg71m9SmTcfvmT7ONVXbterXwNbOhnFDpgFw97Y3xe2LUq9xLSytCpKclEyA/+Ns6eeH1rltYonbHO7e9uK2uyf9B3VH31Cf37ftB2DZL3MIDg5l7sylAAwe3pcxLkMY0n8cT4KeK78Fi4qKJjoqWqXtug1qUszOluGDJgLgcfsediWK0bBJHawKW5KclMxD/+z99i63W7liPavXLuT2bU9u3vRgsHNvDAwM2LplDwBr1i3k+fMQZkxbAKRc1FnawR4AXV0dLK0KUr6CA1HvogkIUD1nS5W2p137ltSp1RKA+34PSU5OpnuPToSGvKRkSTvcb2U8Of+Scmu/c6vda/fismQcfh5++Nzxo0O/duTRz8Ofv6dcXO2ydDxhL8JYN3c98XEJBPo9Utn/XUTKUqcflgM41q2CdXFrXEfMB8DPww8b+yJUb1gNCysLkpOTCQp4kqX9S4+c50KdJJnIpSLfRbF09QZCXoZhbJSPb+vXYZhTT3T+/pZl4YwJLF29kQkz5hMeEYlVIQuGOfWkc9sWyjaCQ0JVRi/i4uNZsW4TT5+/wEBfn7o1q+E6ZSxGH9zURqFQMH3+csYO7Y+Bfh4A8ujpMWvSKGYvciM+IYGJIwdTsIDqkG1WOXrgJKZmJgwbP5ACFmb43LtP385DefX3RdmW1oVIfu8mMfoG+kyfP55ClhbExsYR8OARYwdP4eiBkyrt6uXRY+rccYzs74JCoQAgJDiUnycuwHX5VOLjEhg/dBpxsXHZ0s8PHdp/DFNzU8ZMHEIBC3O8PH3p1sFJOe/VytqS5GSFsn6PPp3R09Nl3ealKu0smruKxfPclM/z5NFj9vxJDOozRtnv4OchTBk/h8UrZxMfH8+IwROJVVO/c6t9e//A3NyUiZNHUrCgOZ53fWjftpdyWpu1tZXKyKOlpQWXrvxzo8rhIwYwfMQALpy/SovmXVXaXr5iDhMnzCY6OgaA2Ng4BjmNY+GSGejp6TJm1DSCg0OyoZep5dZ+51ZnDp8lv5kxvcf0wrSACf7eDxnX3YU3YW8BKFjYAkUmRr118+gyfNZQZg6apfy99jI4jOVTVjJh0Vji4xNwHTGf+NjUy6xmBznPs0AOvDlcTqWh+P+74iuirVtY3SGoRczzC+oOQS3KOnRSdwhqEZUYo+4Q1CIk6q26Q1ALAx09dYcgslF0Qu5MtutYOKg7BLVwfxOg7hDUIiIq5/Y75shidYeQLv2Wo9Qdggq5ZkIIIYQQQgiRKTk6mXjy5Al9+vT5aJ24uDgiIiJUHl/hYIsQQgghhMgu6r4x3X/opnU5Opl4/fo1mzZt+mgdV1dXjI2NVR6K5MhsilAIIYQQQojcS60XYB86dOij2wMCPj2XzsXFhVGjVOeOmZiV/ldxCSGEEEIIIT5NrclE27Zt0dDQ+Oi0JI0P7nXwIT09PfT0VC9M/NQ+QgghhBBCpEtWc8owtU5zsrS0ZN++fSQnJ6f5cHd3V2d4OVqePJoUKpiHokUMsCuWFwMD1RvGnDx7if4jJlK7eSfK1W6O733VOyyHR0QyZ7EbLbv0w7FhG5q068GcJb8Q+S5KWcf3QQBjp82l8Q/dcWzYhlZdB7Bl14E04zl49CTdB43O0LEBdh88Sq8h46jxbTvK1W5OROS7VHWGjJtOk3Y9qNKwNQ1ad2XCzAWEvvznrtTPgkMoV7s5GqaRKg+0klK19SX92Ks9h87uwD3gLO4BZ/n96G/Ua1zr0zv+xw0Z2Y8//vodv6DreNw/z/qty7Gzt1V3WCKL1Kpdjd93r8PP/woRUQG0aPmtukPKFrm137lVr1E9OPv0lMpj89nf1B1WlpPzXHxJak0mHB0duXXrVrrbPzVqkZtpamgQH59M2Ku0lw+MiY2lSoWyjByU9gXsoWGvCA17zZgh/di/5RdmTxrFpWu3mOq6RFnH2+8Bpib5mTt1LAe2rmZAzy4sW72R7XtST087feEqDet8k6FjQ8o61XVqVKV/jy7p1qlepSKLZrpwZMc6lsyezJNnwYycPDtVPUWEPoo3hsoHSVl7Wr94HsqiWSv5oUl32jXpwdWLN3HbvAj7UsWz9Ljq9k2tamz6dQetmv7Ij+36o6OjzfZ969A30Fd3aCILGBoacM/Th9Ejp6k7lGyVW/udmwX6BtKuckflY+gPI9QdUpaT81x8SWqd5jR27FiioqLS3W5vb8+ZM2eyMaL/juiYJKJj0v8GvnWzxkDKt/dpKVHclqVzJiuf21hbMWxATybMnE9iYhLa2lq0a/mdyj5FClvicc+HU+cu07VDa2V5XFw8l2+4M3xgrwwdG6B75x8AuO6e/l0ze3T5Qfl/q0IF6detE8NcZpKQmKi8uR4ACg1QZF9efOaE6v08lsxx48de7alUtTz+fjl3zex/q1tHJ5XnIwZPwtP/IhUqleHa5fS/FBD/TSdPnOPkiXPqDiPb5dZ+52ZJSUm8fvlG3WFkKznPMyAHrpqUU6k1mahbt+5HtxsaGlK/fv1sikZEvosir6EB2tpaH61jbKR6R+urt+5Q0NyM4kWLZFls4RGRHDlxhkrlHVQTCYC8MaBByohErC4kZN9prampSfPWTTAw0Of2jfQTo6+RkVE+AN6+CVdzJEIIkXmFixVmz82dxMcl4OXuzTrX9YQ+D1V3WEL8Z6g1mRA5x5u34azZuIMOrZunW+e2pzfH/zrPqgUzVMrPXLhCg7+nOH1pi93Ws2PvYWJi46hYtrTKsQ308zB2aH/mz9qWUqCbmJJYvNPP8oSipIMdv/+5AT09XaKjYnDuNZaH9wOz9Jg5iYaGBjNcx3P9qjt+Pv7qDkcIITLF+7YPc0cu4EnAE8wszOg5sjvL9y2hd+N+xETFqDs8If4TcvR9JkT2eBcVxeCx07ArZsPgvt3SrPMg4BHDJsxgUJ+fqF3DUVmuUCg4e+ma8nqJL6131w7s3rCStUtmo6mlicvPC5XX0ZjkN6Znl3aQpJXyiNGDeG3IE58lsbwv0P8xbRp2peN3vdixcQ/zVkzHrmSxLD9uTjFn4WRKOZRgcN8x6g5FCCEy7fqZG5z74zwBPoHcOHeTCT0mktcoLw1byayIXE+RnHMfOYwkE7lcVFQ0TqOmYGigz7I5U1JPIQIeBj6m7zAXOrRujlOvH1W2eXr7kZSURKXyDlkSn0l+Y2xtrKlVvQoLZkzgwpUbeHj5pr9DohZoZf0bLSEhkaDAp3jd9WXRrFX4et2n54AfP73jV2DW/Ek0+a4+HVv1Jvh5+tfFCCHEf827iCieBjylsG1hdYcixL/m6upKtWrVyJcvHxYWFrRt2xY/Pz+VOg0aNEBDQ0PlMXDgwM86jiQTudi7qCgGjJyEjo42K+ZNQ09PN1Ud/4DH9B46gTbNmzDcqVeq7acvXKVezepoaaV/ncWXokhOGZGIj09Iv5JWMiRn/31GNDQ10dXTyfbjZrdZ8yfRrEVjOrXuw5OgZ+oORwghvih9gzxY2VryKvTVpysLkcOdO3cOZ2dnrl69ysmTJ0lISKBp06apFj/q378/wcHBysf8+fM/6zhyzcR/lIYG6Oj8kwvqaGvie/8hxkb5sCxkQXhEJMEvQgkNS/mFGBj0FABzMxPMzUxTEokRk4iJi2PZ1LFERUUTFRUNpIwGaGlp8SDgEX2HTqBWDUd6dvmBsFevgZSLjk1N8gNw9uJVnPt1V4ntU8cGCHv1mrBXbwh6+hyABw8fYWigj2UhC4yN8nHXy5d7PvepUqEsRkZ5efIsmBXrtlCksCWVyqXc4fzg0ZPo6OiA5t+rWukmgl4CROX5oq/1h0ZPdubcX5cJfvoCw7wGtGrfjBq1HenTaWiWHlfd5iycQtsO39On61DevYumgIU5AJERkcTGpr1EsfjvMjQ0oLhdUeVzW9silK/gwJvX4Tz9+337Ncqt/c6tBk0ewOVTVwl5GoJZQTN6j+5JclIyfx34uleSlPM8A76C1ZyOHTum8nzjxo1YWFhw69Yt6tWrpyw3MDCgUKFCmT6OhuIrvJGDtu7XPzyZJ48WhS1Tr+/fpnkTZk8ezYE/TjJ5zuJU2wf1+Qnnvt247n6XPkPHp9n28T0bKWxZkFXrt/LLb9tSbbcqZMGJvZsIevqctt0HcvHoLgz0//kA/6ljA+m2PWviKNq2+Jb7DwOZu3QNfv4BxMTGUsDMlNo1HHHq9SMFC6R8iD149CTrt+3mYeATUADJmhCjCwlZO0Iwe+kUatathkVBcyIj3uHn/YC1KzZz+dy1LD3uh6ISs/fiwGdvvNIsHzl4Ert2HMi2OEKi3mbbsXISAx29bD1enbo1OHpsR6rybVv3MMhpXLbGkp1ySr+jE3Jngl7HImumzKZn6qpJVKhRHiMTI8Jfh+N5/R6/zv+N54+DszUO9zfZu6x4TjnPI6Jy7nLqMXtmqTuEdGm2GktcnOrvCD09PfT0Pv53wt/fnxIlSuDp6Um5cuWAlGlOXl5eKBQKChUqRKtWrZgyZQoGBgYZjkeSia9IzPMLn670BW3auY+rN27zy6Kfs/W4Hyrr0Emtx1eX7E4mcgpJJkRuIMlE7pLdyUROIclE5sy7l8iMGaora06bNo3p06enu09ycjKtW7fm7du3XLx4UVm+du1aihYtipWVFXfv3mX8+PFUr16dffv2ZTgemeYkMq1gAXP6de+s7jCEEEIIIb6sHDzNycXFhVGjRqmUfWpUwtnZmXv37qkkEgADBgxQ/r98+fJYWlrSuHFjHj58iJ2dXYbikWRCZFqzxvU+XUkIIYQQQnwxGZnS9L4hQ4Zw5MgRzp8/j7W19Ufr1qhRA0iZEiXJhBBCCCGEELmUQqFg6NCh7N+/n7Nnz1Ks2Kfvh3Xnzh0ALC0tM3wcSSaEEEIIIYR431dwSbGzszPbt2/n4MGD5MuXjxcvXgBgbGyMvr4+Dx8+ZPv27Xz//feYmZlx9+5dRo4cSb169ahQoUKGjyPJhBBCCCGEEF+ZX375BUhZsel9GzZsoFevXujq6nLq1CmWLl1KVFQURYoUoX379kyePPmzjiPJhBBCCCGEEF+ZTy3YWqRIEc6dO/evjyPJhBBCCCGEEO/Lwas55TSan64ihBBCCCGEEKlJMiGEEEIIIYTIFJnmJIQQQgghxPtkmlOGyciEEEIIIYQQIlMkmRBCCCGEEEJkikxzEkIIIYQQ4n0KmeaUUTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifrOaUYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifQqHuCP4zZGRCCCGEEEIIkSmSTAghhBBCCCEyRaY5CSGEEEII8T5ZzSnDZGRCCCGEEEIIkSmSTAghhBBCCCEyRaY5CSGEEEII8T6Z5pRhX2UyUcfCQd0hqIW+VV11h6AWMc8vqDsEtbAt0UrdIahFcWNLdYegFgHhweoOQS0MdPTUHYJadLKsru4QRDZyV3cAQvwLMs1JCCGEEEIIkSlf5ciEEEIIIYQQmaaQaU4ZJSMTQgghhBBCiEyRZEIIIYQQQgiRKTLNSQghhBBCiPcokhXqDuE/Q0YmhBBCCCGEEJkiyYQQQgghhBAiU2SakxBCCCGEEO+Tm9ZlmIxMCCGEEEIIITJFkgkhhBBCCCFEpsg0JyGEEEIIId4nN63LMBmZEEIIIYQQQmSKJBNCCCGEEEKITJFpTkIIIYQQQrxPblqXYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHif3LQuw2RkQgghhBBCCJEpkkwIIYQQQgghMkWmOQkhhBBCCPE+meaUYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifQm5al1EyMiGEEEIIIYTIFEkm0tG2Z2t2XtnKCf+juB1eQelKpdKt26xjU84+PaXyOOF/VKVOZ6eO7L+zm/13dtNpQAeVbQ6VS7PmqBtaWvLjyGpRUdHMXbqab9v1xLFhG35yGoWnj59ye7nazdN8/LZtT7ptrlq/NVX9Vj/2V6kzf/laajXrSOMfunPk+GmVbcdPX8B53LQv29EM6tnvR656nOBhsDuHT+6gUpXy6dbt2qMD+45uxivwMl6Bl9m5/9dU9Z2G9MLj/nk87p/HybmnyrbKjuX588wutLS0sqQvn+OnPh05fesQnk8usfvYRipULptu3aYtGrL35GZu+p/hzqMLHDyzjTYdv1ep02dwN654n+CK9wn6DPpJZVuFKmXZd2pLjuh3btV/QHc8vc8T+sqH02f34ehYId26pR1KsGWbG57e54mICmCwc+9UdTp1boO330UeP73NnLmTVLbZ2BTG/c5f5MuX94v343N926M5yy6uYaPf78w8MA+7iiXSrTt5589sf7w/1WPshn/612JAG365tZFfbm3k+/6tVfa3q1SC2UcWopkD/o7l1n7n1vNcqJ9Mc0pDw1YNGDx1IItdluFz24cO/dqzYOtcutfvzdtXb9Pc511EFD3q91I+V7w3PFbcoRi9x/TEpedkNDQ0cN00ixvnbxHoG4iWliajXEewcPwSkpJk5YCsNnXuMvwDHuE6dQwW5mYcPn6a/sMncnDbGgoWMOfsoW0q9S9cvclU16V826D2R9u1L1aUX5fNUT5//4Pj2YtX+ePkWdYumU3Q0+dMmbOE2jUcMclvTOS7KJav3cSvS+ek1WyWav1DM6bNGseEUTO4fcuTfgO7s23vGupVa8mrsNep6tesU42De49y89odYuPicB7el+371tKoZhteBIfiULYkY12G0LOLMxoasHGnG+fOXMbX+wFaWlrMXTyNcSOmk5SUlO19fd/3bb/FZeZIpo51xePWPXo5/cj6XSv4rmZ7Xoe9SVX/7ZsIVi/5jYAHj4hPSKBh07q4Lp/Kq7DXXDxzlVJl7Bk+fiBOP41AQ0ODNduWcPHsVe77PERLS4uZCycyZdRstfc7t2rXvgVz5k5kxPAp3Lxxh8HOvdl3cBOOlZsQ9vJVqvoG+vo8ehTEgf1HcZ03OdV2UzMTVqxyZZDTWB4FPmH3vl85f/YKx46lfEmweOnPTJs6n8jId1net4/5pmVtuk3uzW+TVuN/5z7N+7RiwpapjG44hIhX4anqL3Gah7buPx8J8ubPx9xjS7j2x2UAipQuSodRP7Kgz2w0NGDsb5PwPH+HJ35BaGpp0nfOQH6d8AvJav47llv7nVvP8ywlqzllmPpT6Ryo44D2/LHjKMd2HefxgyAWT1hKbGwc33dplv5OCgWvX75RPt6EvVVusrGzIcAnkNuX7+B+6TYPfQKwsSsCQOeBnfG4dhc/D790GhZfSmxcHKfOXWSUc1+qViqPjbUVzn27YWNtxe/7/wDA3MxU5XHmwlWqV6lAkcKWH21bS0tLZT+T/MbKbQGPn1CtcnnKOZTk+28bYGhowNPgFwAsdltP57YtsCxkkXUdT0f/wT3ZvnkPu7Yf4IHfQyaMmkFMdCxdurVLs/7QAePZtH4nXvd8efggkDHDpqKpoUmdet8AYF+iGD5e97l04RoXz1/Dx+s+9iWKATBoWG+uXr6Jx+172da/9PQe+BO7th5g347DPLwfyNQxrsTGxNKha+s061+/fIuTR8/y8MEjnjx6xua1O/Hz9sexRiUAipewxc/7AVcv3uTKhRv4eftTvIQtAP2GdOfGFXc873hnU+/Eh4YM7cumDb+zbcse/Hz9GTFsMjExMXTv0THN+u7ud5kyaS579xwhLi4+1fZitkWIiIhk394/cHe/y/lzVylZ2g6ADh1bkZCQwOFDx7O0Txnxfb/WnNl5knO7T/PswVPWT1xNXEwc9Ts1TrN+VPg7wl++VT7K161IXEyc8kO1lV1hgnwe4X3ZE69LngT5PMbKzhqAlk5t8b3mTcBd/2zrX3pya79z63kucgZJJj6graNNqfIluXXBXVmmUCi4dcGdMlXKpLufvqE+O69uY9f17cxaPxPbkkWV2wJ8A7EuXhgLKwsKFragSDFrAv0eYVXUkuadv2P9/A1Z2ieRIikxiaSkZPR0dVTK9fR0cb/rlap+2Os3nL98nXYtv/tk20FPn9Gw9U8069ib8dPnEfwiVLmtlH1xvHwfEB4RiZfvA+Li4rApbIW7xz28/fz5qWPaH2Kzko6ODhUqleHC2SvKMoVCwcVzV3GsVjFDbegb5EFbR5u3b1O+7fPxfkAxe1usrC0pXMSS4vZF8fXxp6htETp3/YH5s5dnSV8+h46ONmUrlubyuWvKMoVCweXz16lUNf0pAe+rWbcaxeyKcuPKbQDue/tja2eDZeGCWFkXwtbOhgc+DyliW5h2P7Zi6ZxfsqQv4tN0dHSoVLkcZ85cUpYpFArOnrlE9eqVM9Xmw4eP0NfPQ4WKZTAxMaaKYwW87vmSP78Rk6eMZMyo6V8m+H9BS0ebYuXtuHfRQ1mmUCi4d/EuJaqkP2X3fQ06N+Hq4YvExcQB8MQvCMviVphZmWNeuACWxa14cj8IC5tC1O/YmF0Lt32ixayXW/udW89zkXPINKcPGJsao6WtxeuXqtMd3oS9wca+SJr7BD18wrzRCwnwCcDQyJDOTh1ZeWA5vRv35WVwGEH+Qfw69zcW7pgHwLq56wnyD2LRjvmsmb2W6g2q0mtkDxITk1gxbRV3r3lmeT9zI0NDAyqWc2D1xh0UL2qDmWl+jp46h8c9X2zSGHk49OcpDAz0aVL/41OcKpQpxaxJo7G1sSbs1WvcfttGj8FjObDlFwwNDahdw5GW3zWiS7/h5NHTY/bk0Rjo5+HnhauYNWkUv+//g+17DpE/vzHTxw3DvnjRjx7vSzA1y4+2tnaq4e+XL19h9/dowqdMmj6akBehyoTE/34A835eys596wCYO3Mp/vcD2Ln/V2ZNW0SDRnUYNWEwiQmJTHVx5drlW1+2UxlgYvr/fqtO4woLfU1xe9t098ubz5ALnn+iq6tLclIS08fPUyYkDx88YvFsNzbscQNg0axVPHzwiI17VrFgxnLqNKrJ0LEDSExMZNakhdz8OwkRWc/MzARtbW1ehoaplIeGhlGypF2m2nz7NoKBA8ayZt0i9PPosXP7fv46dYGVbnNZu2YLRW2t2bl7LTo62rjOXs7BA39+ia58lnwm+dDS1iI8THVaT3jYW6zsCn9yf7uKJbApXZR141Ypy577P+X3+dtw2TodgJ3ztvLc/ykTt01nh+smKtSvTPsRXUhKTGTz9PX4Xs/+0bjc2u/cep5nuWRZzSmjJJn4ArzdffB291E+v3fTi81nf6PVTy35beFGAA5tPcKhrUeUdb7r8C3RUdF43fJmy7mNOLV0poClOVNXTeLHWt1JiE/I7m7kCq5TxjDVdQmN2nZDS0sTh5L2NG9SH2+/1MPU+4+coGXThujp6X60zbo1qyn/X8q+GOXLlKJp+54cO32B9q1SRjWc+3bDuW83ZT2337bxTdVKaGtrs2bTTvZvduPc5etMnLWQXb+t+EK9zTrOI/rRul1zOrbqpTJEvmXDLrZs2KV83rFLG969i+LWDQ/O3zhCi0adsbQqhNuvC6lZqSnx/5HzPOpdNG0adsXQ0ICadavhMnMkTx494/rfCdHOTXvZuWmvsv4PnVsQ9S6a2zc9OX5lL+2b9qCQpQVL1s6hkWNreX//xx05fIIjh08on9euU51y5UozdvR07nieoU+v4YSEvOTMuQNcunQ9zTnrOVmDzo0J8nnEQ48HKuV/bTvOX9v+mdpSt31DYt7FcN/dj0WnVzGl9VhMLc0YunI0w+s4kRifmN2h/yu5td/p+drPc/HlyDSnD4S/DicpMQnTAiYq5SbmJrwOTX1xZlqSEpN4cM+fwrZWaW43NjGi58geLJ+yEofKDjwJfMqzwGfcueyBto421sWt/3U/RNpsrK3YuGoB10/t59S+Lez8dRmJiUlYWxVSqXfrzj0Cg57SrtVHrpNJh1G+vBQtUpigp8/T3B7w+AlHjp9maP8e3Lh9l6qVymFqkp/vGtXD28+fqKjoTPXtc7x+9ZbExETMC5iplBcoYJbq260POQ3phfOIvnRt1x8fr/vp1jMxzc/I8YOYMn4OlatWIMD/MYEBQVy+eB0dHe2PjgRklTev/99vU5VycwtTXoam/4dQoVAQFPgUn3v3+e2XbRw//BdOI3qlWdfE1JghY/oz02UBFauU49HDIB4HPOHapVvoaGtTzM7mS3ZJfMSrV29ITEykgIW5SrmFhTkhIS+/yDF0dXVZvGQmw4dNoridLdraWly6eB3/B4E89A+katWMTRv8kiLfRJKUmISxubFKubF5ft6+fPvRffX09ajZqg5nf//ro/XymeSj/YhObJr2K/aVSvIi8DkvHgXjfeUeWtpaWBZL++9fVsqt/c6t57nIOSSZ+EBiQiJ+nvepUqeKskxDQwPHOpXxds/Y8KWmpibFSxfjVWjqFXEAnKcPYveve3kZHIamliba2v8MEGlpaaGlKT+WrGagn4cC5qaER0Ry+fotGtX9RmX7viPHKVOqBKVLFP/stqOjY3jyLJgC5qaptikUCmbOX864of0xMNAnOSmZhMSUb7ES//43KRtWkEhISODuHW/q1P+n3xoaGtSpV4NbNzzS3W/QsD6MGDuQbh2cuHsn9XUm75sxZzzr3DYT/DwELU1NdHTeO8+1tdDSzP6lUhMSEvHy8KVmverKMg0NDWrWrcadm3cz3I6Gpia6ummPWE38eTQb1+wgJDgULS1NtD/stywRm20SEhK4c/seDRrUUpZpaGhQv0Etrl//MtPNxo135tSp83jc8Ur5eWv98/PW1tFWy887KSGRQM+HlK39z3VAGhoalK1dngfuH1/so0aLWmjr6nBx/7mP1us2tQ9H1x/m9YtXaGppoqXzTz+1tLXUslRqbu13bj3Ps5wiOec+chiZ5pSG3Wv34rJkHH4efvjc8aNDv3bk0c/Dn78fA8Bl6XjCXoSxbu56AHqM6Ia3uw/PHj0nr5EhXQZ2oqB1Qf7YcTRV2451q2Bd3BrXEfMB8PPww8a+CNUbVsPCyoLk5GSCAp5kX2dzmUvXbqFQKLC1sSbo6XMWrVpPMRtr2rZoqqzzLiqKE2cuMGZI/zTb6DtsAo3r1aJrh5QLpxesXEeD2jWwKlSQ0LBXrPp1K1pamnzfpH6qffcePoZJfmMa1En5EF+5QhncftuKxz0fLly9iZ2tDUbZtG73OrdNLHGbw93bXtx296T/oO7oG+rz+7b9ACz7ZQ7BwaHMnbkUgMHD+zLGZQhD+o/jSdBz5bdgUVHRRH8wmlK3QU2K2dkyfNBEADxu38OuRDEaNqmDVWFLkpOSeegfmC39/NCG1duYt2I69+54c9fdi55OXdE30GfvjsMAzF85g5AXoSyalTJv2ml4Lzzv+PDk0VN0dXWo36Q2bTp+z/RxrqnarlW/BrZ2NowbknLfkLu3vSluX5R6jWthaVWQ5KRkAvwfZ19nBStXrGf12oXcvu3JzZseDHbujYGBAVu3pNw7Zs26hTx/HsKMaQuAlItZSzvYA6Crq4OlVUHKV3Ag6l00AQGqP7tSpe1p174ldWq1BOC+30OSk5Pp3qMToSEvKVnSDvdbGU9Sv6Sjvx5i4KJhBNx9yEOPBzTv05I8Bnk4tzvlm/dBi4fx+sVrfp+/VWW/Bp2bcOvENd69jUy37XJ1KmJZzIrVo1IWVQjw8MfKrjAVG1TBzNKM5KRknj9Me2Q2q+XWfufW81zkDJJMpOHM4bPkNzOm95hemBYwwd/7IeO6uyiXey1Y2ALFe98e5zPOx5j5ozAtYMK78Hf4eT7Auc1wHj8IUmlXN48uw2cNZeagWcr7ULwMDmP5lJVMWDSW+PgEXEfMJz429TJt4suIfBfF0tUbCHkZhrFRPr6tX4dhTj3ReW906M9T51Ao4PtvG6TZxpNnwbwJj1A+DwkNY9y0ebyNiMA0vzGVK5Rl25olmJrkV9kv7PUb1m7aydbVi5Vl5cuUomeXdgweOw1Tk/zMmTz6i/b3Yw7tP4apuSljJg6hgIU5Xp6+dOvgpJz3amVtSfJ7F6D16NMZPT1d1m1eqtLOormrWDzPTfk8Tx49Zs+fxKA+Y5TnefDzEKaMn8PilbOJj49nxOCJxMbGZX0n03D0wElMzUwYNn4gBSzM8Ll3n76dh/Lq74uyLa0LkfzeNz/6BvpMnz+eQpYWxMbGEfDgEWMHT+HogZMq7erl0WPq3HGM7O+i7HdIcCg/T1yA6/KpxMclMH7oNOLU1O/cat/ePzA3N2Xi5JEULGiO510f2rftpZzOZ21tRfJ7v88tLS24dOUP5fPhIwYwfMQALpy/SovmXVXaXr5iDhMnzCY6OgaA2Ng4BjmNY+GSGejp6TJm1DSCg0OyoZepXT1yCSMzIzqM6kL+AiY89g5kbo+ZRPx9cbKZVQGV9zeAZXErSlcvw5yfpqfbro6eLr1m9mfFkIXK8/z1i1dsnPYrTguGkBCfwC+jl5OQxnKj2SG39ju3nuciZ9BQvH93ta9EA+sm6g5BLS6G+ny60lco5vkFdYegFrYlWqk7BLUw1NZXdwhqERAerO4Q1MJAR0/dIahFS3OZg56bHAlLf3rp1ywiKkDdIaQrel7qu4LnFAbjc9YtBWRyvhBCCCGEECJT1J5MxMTEcPHiRby9U1/cHBsby+bNmz+6f1xcHBERESqP5Bx4cYoQQgghhBBfG7UmE/fv38fBwYF69epRvnx56tevT3DwP0P54eHh9O798WEmV1dXjI2NVR5BkY+yOHIhhBBCCPG1UiQn59hHTqPWZGL8+PGUK1eO0NBQ/Pz8yJcvH7Vr1yYoKOjTO//NxcWF8PBwlYdNPtusC1oIIYQQQggBqHk1p8uXL3Pq1CnMzc0xNzfn8OHDDB48mLp163LmzBkMDQ0/2Yaenh56eqoX6GlqqH32lhBCCCGEEF89tSYTMTExKjds09DQ4JdffmHIkCHUr1+f7du3qzG6jOs1qge9RvVQKQvyD6JHgz5qiujrlSePJvmNddHT1URbW5PgkBiV7QqFglW/bmHP4WNERkZRuUIZpowZQtEihZV1wiMimbPYjbOXrqGpqUmTBrVxGT4QAwN9lXY27tjLnkPHeP4iBBNjYzq3a4FTzx9Vjnfw6En2HD7Gll8WcfLsJXYd+ANvP3/CIyLZs2ElpUvaqdSPi4tnwcp1/HnqHPEJCdSu7sjkMc6Ym6bccf1teATjZ8znvn9gylKzJvlpVKcmwwf2JO/fyfXJs5f4ff8fGJqn3OQuOQniozRJis/aJHrIyH40b/kt9iWKERsby83rd5gzfTEP/R9l6XHV7cde7fmxVwesbSwBeOAbwKpFv3L+r8tqjkxkhVq1qzF8xAAqVS6HpWVBfuzsxB9HTn56x/+4ZRfXUKCIRaryE5v/ZOOUtWqIKHvk1n7n1vP8syR/dYudZhm1JhOlS5fm5s2bODg4qJSvXLkSgNatW6sjrEwJ9A1k9I/jlM+TEpPUGM3XS1NDg/j4ZCIjEyhUMPUSob9t2822PYeYPXk0hS0LsXLdZpxGTebg1jXo6aXcsXj8jPm8DHvNuqVzSExMZPKcJUyfv5z508cr23Fdupor190Z49yPEna2hEdEEh6R+mZGpy9cpeHfN6CLiY2lSoWyfNeoHtPnLUsz/nnL13D+yg0Wz5pIXkND5ix2Y8TEWWxdvQhISagb1v2Gof17YGpiTNDT58xe5Eb4gkhlfLfueFKremVOn7iLQgE6eZLJY5xMzBsNkhM1/t0L/BHf1KrGpl93cOe2J9ra2kyYMpzt+9bR4JvWxETHfLqB/6gXz0NZNGsljwKC0ECDH7q0xG3zIto2+gl/v5y7rKHIHENDA+55+rBl826271yt7nCyzeTWY1Xu3lykpA0Tt8/g2h+X1BhV1sut/c6t57nIGmpNJn744Qd27NhB9+7dU21buXIlycnJrF793zjJk5KSeP3yjbrD+OpFxyQRHZN2oqZQKNiy6wADenahUd2aAMyZMob6rX7krwuX+b5JAx4+CuLi1Zvs/HUZ5RxKAjBx5CAGjZnKGOd+WBQw4+GjIHbt/4P9W1ZTrKg1ANZWhVIdLy4unss33Bk+sBcArZs1BuBZOjfviXwXxb4jJ5g/fRw1HCsB8POkUbTuOgCPez5ULOeAsVE+uvzQUrmPVaGCdG7Xkg3b9yjLJowYCMDM6SkrncVHaaGll4iWriJLk4luHZ1Uno8YPAlP/4tUqFSGa5dvZdlx1e3MCdX7mCyZ48aPvdpTqWp5SSa+QidPnOPkiXPqDiPbRb6OUHneelA7XjwKxueql5oiyh65td+59TwXWUOtFxe4uLhw9OjRdLe7ubmp3LExJytcrDB7bu5k+6UtTFrhgoVV6mFTkbWePn9B2Ks31KxaWVmWL68hFcqUwuOeLwAe93wwypdXmUgAfFO1MpqaGtz1Tqlz7tI1rK0Kce7yNb7r0Ium7Xsy1XVpqpGJq7fuUNDcjOJFi2QoPm+/ByQmJvLNe/EVL1oEy4IWyvg+FPryFafOXaJqpfIfaVmBhgaQzSOyRkb5AHj7Jjx7D6xGmpqatGjbFAMDfW7fuKvucITIElo62tT5oT7ndv2l7lCyVW7tt0iHIjnnPnIYtY5MfC28b/swd+QCngQ8wczCjJ4ju7N83xJ6N+5HTNTXO/0jpwl7nTIyZPb39Qf/Z2ZqQtirlG1hr95gmt9YZbu2thbG+fIp93/y7AXPQ0I5cfoCcyaPISk5mfnL1zBy0mx+WzFXud+ZC1do8PcUpwzF9+oNOjraGOXL+0F8+Ql7/VqlbOy0uZy5cJXYuDga1K7BzAkj0m1XxyAlmUiMzbpRiQ9paGgww3U816+64+fjn23HVZeSDnb8/ucG9PR0iY6KwbnXWB7eD1R3WEJkiapNq2NgZMi53afVHUq2yq39FuLfkmWPvoDrZ25w7o/zBPgEcuPcTSb0mEheo7w0bFVf3aGJTFAokomPT2DOlDE4VipH9SoVmOkykuvuHgQ+fvp3HQVnL11TXi/xpY0fNoBdG1awYu40njwLZv6KtC8E1NZLRtcwmdhwTRSK7Esm5iycTCmHEgzuOybbjqlOgf6PadOwKx2/68WOjXuYt2I6diWLqTssIbJEw85N8DjrztvQ3DV1N7f2W4h/S5KJLPAuIoqnAU8pbFv405XFF/P/FZFevVb9Q/Dq9RvMzVK2mZuZ8Pqt6rScxMQkwiMjlfubm5miraWFrY21sk5x25SpTMEhoQB4evuRlJREpfKqiwd8ND4zExISEomIfPdBfG8xNzX9oK4pxYsWoWHdb5g2bii/7/+Dl2GqoxfaesnoGaUkEkkJ2fdWnjV/Ek2+q0/HVr0Jfp729SFfm4SERIICn+J115dFs1bh63WfngN+/PSOQvzHmBcuQLk6FTiz85S6Q8lWubXf4iOSFTn3kcNIMpEF9A3yYGVryavQV+oOJVextiqEuZkJV2/dUZa9i4rirrcfFcuVBqBiOQciIt/h5ftAWefarTskJyuoUCalTuXyZUhMSiLo6XNlnUdBzwCwKpRyLczpC1epV7M6WlpaGY6vTKkSaGtrc+3mP/EFPn5KcEioMr60JCtSfnHEJyQoy46ePPtPIpHFS8K+b9b8STRr0ZhOrfvw5O/XJDfS0NREV09H3WEI8cXV79iI8Ffh3D59U92hZKvc2m8hvgS5ZuILGDR5AJdPXSXkaQhmBc3oPbonyUnJ/HXgjLpD++poaICOzj8fnnW0NfG9/xBjo3xYFrKge6e2rN20k6LWhSlsVZCV67ZgYW5G47q1ALCztaHON1WZPm8ZU8cOJSExkTlLfqF5k/pYFDADoGa1ypQpZc9U1yWMH+5EcrKC2YtWUbNaZeVoxdmLV3Hup7oKWXhEJMEvQgkNS0kiA4NSpkSZm5lgbmZKvryGtGvZlPkr1mFslA9DQwPmLPmFiuUcqFguZYTj/OXrvHrzlnIOJTHQ18c/8DGLVv1K5QplKGxZEIA/Tpxh0qxFxL3TJDlRAw3NlGRDoQCycKrTnIVTaNvhe/p0Hcq7d9EUsDAHIDIiktjYuCw7rrqNnuzMub8uE/z0BYZ5DWjVvhk1ajvSp9NQdYcmsoChoQHF7Yoqn9vaFqF8BQfevA7n6XtfMHyNNDQ0qNexERf2nCU5Kedd5JlVcmO/c/N5Lr48SSa+gAKWBZiyciJGJkaEvw7H8/o9BrceSvjr3LPKTXbR09OisOU/95cwN9OjQ+8htGnehNmTR9Pnp47ExMQyff5yIt+9o0qFsqxe9LPyHhMA86aNY/ZiN/oOc0FTU4MmDWozccQg5XZNTU1WzpvOnCW/0HPwOPT181D3m6qMHdofgKCnzwl69pzaNRxVYjtz4SqT5yxWPh87LeVi7UF9fsK5bzcAxg9zQlNTkxGTZpGQkECt6o5MGeOs3CePnh57Dh1j/vK1xMcnUKhgAZrUr0Xfbp2UdXYf+pPEpCTy5APy/XP8hBgN4iIzPlLyuXr27QLA3j82qZSPHDyJXTsOZNlx1c3U3JT5K2dgUdCcyIh3+Hk/oE+noVw+d03doYksULlKeY4e26F87jpvMgDbtu5hkNO49Hb7KpSrU4EC1haczWWrGeXGfufm8zzD/iOrieYEGgqFIudNvvqXGlg3UXcIanEx1EfdIahFzPMLn670BW3auY+rN27zy6Kfs/W4H7It0Uqtx1cXQ+3UNyvMDQLCg9UdgloY6OipOwS1aGleUd0hiGx0JMxD3SGoRURUzr1XT9T0nHtdnOH0HZ+ulI3kmgkhPlPBAub0695Z3WEIIYQQQqidTHMS4jM1a1xP3SEIIYQQIivlwFWTcioZmRBCCCGEEEJkiiQTQgghhBBCiEyRaU5CCCGEEEK8TyGrOWWUjEwIIYQQQgghMkWSCSGEEEIIIUSmyDQnIYQQQggh3ierOWWYjEwIIYQQQgghMkWSCSGEEEIIIUSmyDQnIYQQQggh3qNIltWcMkpGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk9WcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvk2lOGSYjE0IIIYQQQohMkWRCCCGEEEIIkSkyzUkIIYQQQoj3KeSmdRklIxNCCCGEEEKITJFkQgghhBBCCJEpMs1JCCGEEEKI98lqThkmIxNCCCGEEEKITJFkQgghhBBCCJEpX+U0p4uhPuoOQWSjdlWGqTsEtXj04LC6Q1ALfau66g5BLR6Wc1B3CGphdy93/j4/F3Ff3SGoxYS8ldUdglp0yveNukMQH1DINKcMk5EJIYQQQgghRKZIMiGEEEIIIYTIlK9ympMQQgghhBCZJtOcMkxGJoQQQgghhBCZIsmEEEIIIYQQIlNkmpMQQgghhBDvS05WdwT/GTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifrOaUYTIyIYQQQgghhMgUSSaEEEIIIYQQmSLTnIQQQgghhHifTHPKMBmZEEIIIYQQQmSKJBNCCCGEEEKITJFpTkIIIYQQQrxHoZBpThklIxNCCCGEEEKITJFkQgghhBBCCJEpMs1JCCGEEEKI98lqThkmIxNCCCGEEEKITJFkQgghhBBCCJEpkkwIIYQQQgjxvmRFzn1kkKurK9WqVSNfvnxYWFjQtm1b/Pz8VOrExsbi7OyMmZkZefPmpX379oSEhHzWSyXJhBBCCCGEEF+Zc+fO4ezszNWrVzl58iQJCQk0bdqUqKgoZZ2RI0dy+PBhdu/ezblz53j+/Dnt2rX7rOPIBdhCCCGEEEJ8ZY4dO6byfOPGjVhYWHDr1i3q1atHeHg469evZ/v27TRq1AiADRs24ODgwNWrV/nmm28ydBxJJoQQQgghhHiPIgev5hQXF0dcXJxKmZ6eHnp6eh/dLzw8HABTU1MAbt26RUJCAk2aNFHWKV26NDY2Nly5ciXDyYRMcxIC+L5HC369tJ699/ex8OAiSlQs+dH6hkaGDPx5IJtubmbfg/2sPrsGx4ZVldvrt23Ab1c3sMNzJ32n9FPZ18LagtVn16CfVz9L+pKWqKho5i5dzbfteuLYsA0/OY3C0+efeZOTZi2iXO3mKg+nUZM/2ubNO544j5tGw9Y/Ua52c/46fzlVnQ3b91CvRRfqtejCxh17Vbbd9fKlU5+hJCYmfZlOinTpVSlPgaU/U/j4Toq6n0K/Qa2P1jebPpai7qdSPSx3/6qsY9i8EYWPbsf67H5MRg1U2V/LsiBW+zeiYWiQJf0RGdOz349c9TjBw2B3Dp/cQaUq5dOt27VHB/Yd3YxX4GW8Ai+zc/+vqeo7DemFx/3zeNw/j5NzT5VtlR3L8+eZXWhpaWVJXzLCqkYpWv42it43VzD0yVaKf+f40foGFvlpumIw3c4tYMjjzdSd1i1VnSJ1y9Ht3AKcvNfx7dKBaOr80z/dfPp0O7eAfIXNvnhfPofZN6X5ZvMYvruzirYvtmPZrOpH65tWL0XdQ9P43nsNrQI30vjCQuwGNFepY92uNk1vreB733WUm676uhgUMafJpUVoZ+PfMKHK1dUVY2NjlYerq+tH90lOTmbEiBHUrl2bcuXKAfDixQt0dXXJnz+/St2CBQvy4sWLDMcjIxMi16vTqi79pvRj1cRV3L/jR+u+bZi5dSYDGzgR/io8VX1tHW1+3vYzb8PCmTvQlVcvXmFR2IJ3ESlzEI1MjBg6fyhLRy8l5PELpm6cxt3LHtz46wYAg2YNZtPcjcS8i8m2Pk6duwz/gEe4Th2DhbkZh4+fpv/wiRzctoaCBcxTXodvqjJr4kjlPjo6Oh9tMyYmllL2xfmhRVNGTJyVaruffyCrft3KqgXTUSgUOI+dTq3qVShpV4zExCRmLljBtPHD0NZW34eP3EIjTx4S7gfw7uAxLBbN+GT91wvdeLPin8RBQ0sLy51riT51HgDN/EaYThnNq+kLSHwajMXyWcTeuE3MhWsAmLkM482KX1FERWdNh8Qntf6hGdNmjWPCqBncvuVJv4Hd2bZ3DfWqteRV2OtU9WvWqcbBvUe5ee0OsXFxOA/vy/Z9a2lUsw0vgkNxKFuSsS5D6NnFGQ0N2LjTjXNnLuPr/QAtLS3mLp7GuBHTSUpS35cDOvp6hPkE4b3rPC3WjfhkfS1dbWJeRXJz+UEq9WuWuoKGBt+tGMzNVYcJOneX5quHUa5rI+5uOglALZfO3Nt6mshnr75wTz6PloEe4V6PebzjLDU2jPpk/aToWAJ+O0GETxBJ0XGYVi9FpQV9SYyO4/HW0+ia5qPyov64j1hN1ONQam4dy8tLXoScvA1Ahbl98Jq9k8Rs/BsmVLm4uDBqlOrP+lOjEs7Ozty7d4+LFy9+8XgkmRC5Xtt+bTm+4zh/7T4FgJvLKqo1qsa3nb9lj9ueVPWbdP6WvPnzMfaHsST9/a166NNQ5faCNoWIjojm4uELAHheuYu1fRFu/HWDeq3rkZiYyJVjV7KhZyli4+I4de4iy+dOo2qllG8anft249yla/y+/w+GDUj5hlFXRwdzM9MMt1u3ZjXq1qyW7vbAx08oaWdLDcdKAJS0L0bg46eUtCvGhu17cKxUnvIOpTLfMZFhsZdvEHv5RobrK95FoXj3zwV6+g1qoWmUl3eHUubfahe2RPEuiugTZ1Pav+mBTrGixFy4hsF3DVEkJhFz+sv/wRIZ139wT7Zv3sOu7QcAmDBqBo2b1qNLt3asWvprqvpDB4xXeT5m2FS+b/Utdep9w57fD2Ffohg+Xve59HfC6ON1H/sSxfD1fsCgYb25evkmHrfvZXm/Pubx2bs8Pns3w/Ujn4ZxYfoWABw610+1Xd80H/pmRnhuPkVSXAKBJ90xKWEFQCHHElhULM65yZu+TPD/QuhpD0JPe2S4fvi9x4Tfe6x8Hv0kDKvvq2FeoxSPt57GoKgFCZHRPDt4FYCXl7zJV6IwISdvU7htTRQJiQQfzfjvk/+sHDzNKSNTmt43ZMgQjhw5wvnz57G2tlaWFypUiPj4eN6+fasyOhESEkKhQoUy3L5McxK5mraONvbl7fG4eEdZplAouHPxDqWqlE5znxpNauB7y5eBswax+dYWVp5cRUfnjmhqprydnj96hp6+HsXLFievcV5KVCzJI59HGBob8tOYbqyZsjo7uqaUlJhEUlIyerqqIw16erq43/VSPr9x+y71WnShZZd+zFywgrfhEf/quCXsbHn05BnBL0J5/iKEx0+eYV+8KEFPn3Pg6EmG9e/xr9oX2Sdv2+bEXnMnKTglaU4MeoZGHj10StmjaZQP3TKliH8QgGa+vOQf3IvX81aoOeLcTUdHhwqVynDh7D9fWigUCi6eu4pjtYoZakPfIA/aOtq8fZsyOuvj/YBi9rZYWVtSuIglxe2L4uvjT1HbInTu+gPzZy/Pkr6oU8yrCN6FvMGmXnm08+hiVb0UYT5P0NTWouGcXpyZ8FuOnlefUcblimJarSRhV3wAiAp4gZa+LsbliqKT3xCTSnZEeAehY2yIw/iO3J24Ub0BiwxTKBQMGTKE/fv3c/r0aYoVK6ay3dHRER0dHf766y9lmZ+fH0FBQdSsWTPDx5GRCZGrGZkaoaWtxZuwtyrlb8PeYm1nneY+hWwKUqFWBc4eOMuMXtOxtLVi0KxBaOlos3PpDqLCo1gyagkjl4xCN48up/ee5vZ5d4bOH8Yfm45QsEhBJq+fgraONtuXbOfy0UtZ2kdDQwMqlnNg9cYdFC9qg5lpfo6eOofHPV9sClsCUPsbR5rUr01hq4I8eRbMsjUbGTh6CtvWLM70HGg7WxuGO/Wi/4iJAAx36oWdrQ39hrswanAfLl2/hdv6bWhrazFhxEDlqInIWbTMzdCvVZ2wSXOUZcmR7wibNh/zmePRyKNL1B8nib1yE7Opo4n8/SDahQthseRn0NYifM1mov+6oMYe5D6mZvnR1tYm7KXq9JuXL19hV6JYOnupmjR9NCEvQpUJif/9AOb9vJSd+9YBMHfmUvzvB7Bz/6/MmraIBo3qMGrCYBITEpnq4sq1y7e+bKfU5NigFdSd1o2607vx+IwHPr+fw9G5FU8v+5AUl0D7fVPRN83H3Q0nlNOf/iu+c1+BrpkRmtpa+C7cy+PtZwFICI/CfdhqqqwYhFYeXZ7svkDo2btUXtyfwN9OYGBjQY1NY9DUSdnv+ZHr6u2ISJezszPbt2/n4MGD5MuXT3kdhLGxMfr6+hgbG9O3b19GjRqFqakpRkZGDB06lJo1a2b44muQZEKIz6ahqUn4q7esmrCS5ORkHno+xKygGe0GtmPn0h0AXD1+havH//lWsFyNchRzsGXt1DWsubCWhUMW8OblGxYdWozXtXtpXpvxJblOGcNU1yU0atsNLS1NHEra07xJfbz9/AH4vkkDZd2SdsUoaVeM5p36cOP2Xb6pWjnTx+38Qws6/9BC+fzg0ZMYGOhTsZwDrX7sz85flxESGsbYqXM5vmcDurq6mT6WyBqGrZqSHPmO6DOqSW/MmUvEvFemV6UCOiWK83r+SqwObiLMZQ5Jr15juXkVse6eJL95m82Ri8xyHtGP1u2a07FVL+Li4pXlWzbsYsuGXcrnHbu04d27KG7d8OD8jSO0aNQZS6tCuP26kJqVmhIfn6CO8L+o4Bv32dVyqvJ5/mKFKN2+DjubTaLdnil4/Hacx2c86HrKlWfXfHnl+0SN0X6eC21nom2QBxNHe8pO6sK7wBc8O5Dydyv4z5sE/3lTWdesZmmMythwd9ImmlxZws1BK4gLDaf+nz8TdtWX+LB/N5KdIyWrO4B/75dffgGgQYMGKuUbNmygV69eACxZsgRNTU3at29PXFwc3333HW5ubp91HEkmRK4W8TqCpMQkTMzzq5TnN8/Pm5dv0tznTehrEhOTSE7+5zfNU/8nmFqYoq2jTWJCokp9bV1tBs0exOIRi7G0tURLS4t711LmFj8PfEbJyqW4cSprv9mxsbZi46oFRMfEEhUVTQFzU0ZPccX6f+zdd1hT1xvA8W9IwlTZKEMEwVn3nnVUraOOWme1at1776117133to66qq277r0noAIqDmTJRpCR3x+0aAoq8gOC8n6eJ0+be8899z3kmuTNGdcu5TGRee1tMTfLhc8z3/8rmXhXcEgov677jfVLZ3Hn3n3y5bVPesTFx/H46XMKuqTuV1OReXI0/ZbIA8cgLu79hdRqLEb1J2jcDFR57VAolcRcTxy7HuvzDIPihXl9+mImRSxeBYUQFxeHlbX2KkPW1pYE+Ad+8NgefTvRZ2AX2jTrivu9B+8tZ25hxqARvfihUUdKlyuBt+cTHnn78MjbB7VaRX5XJzzcHqZLe7KSWjM6c/aX30BPD5viTnj+eYm46Dc8v+iBfaXCn1UyEeUTAECYx1MMrE0pPPSHpGTiXXr6KkrO6My1vsswccqNnkqPoAseAER4+2JR2pWXR69nauwidTSajw/DMzQ0ZOnSpSxdujTN55E5EyJbi4uNw/OOJyWqvh1HrFAoKFm1JPeve6R4jNtVd2zz2aJQKJK22eW3J8gvKFkiAdC6XxuunbyO110v9JR6KN9ZvUipUqHUy7x/hsZGhlhbWRAaFs75y9eoXT3lbsyX/gGEhIZj/QkTsj9m5qKV/NSqGXlsrIlPiCfunS+n8fEJJMR/AT8DfWEMypZE7ehAxN6DHyxn2rUd0eev8MbDE/SU8M7QOIVKCZl4jQuIjY3l9k03qtV4++9boVBQ7euKXLvy/om6vfp3ZuCwnrRv0YPbN++9txzApGkjWLVsI74v/FDq6aFWv/1tUqlSotT78lZpK9q6BtEhETw6eh09ZeL7/79LxSrVShTKz/c6V+gpUBqkvIJfoYHf43/iFqF3HqNQ6qF459+3nurzbrdIH9IzIbK9vav3MmjuIDzvPOTBzQc07dIUQ2NDju1IXN1p0PzBBL0MYuPMxFU7Dm46wHcdv6PbxO78uX4/ds52tOzTkj/X7U9Wd94CeaneuDoDGvQH4JnnMzQJCdRtXZfggGAcXBx4cCvjf707d+kaGo0GJ0cHfJ69YO7SNTg7OtCsUT2iol6zbO0W6tasipWlBU+fv2DesrU4OthRtWKZpDq69B/JN19X4ccWTQCIinqNz7MXSfufv/DD44EXprlyYpvHRuv85y9f58nT50wbOwSAYkUK8ujJM85cuMJL/wD09PRwypfyHBXx/1MYGaLKa5/0XGVvi7qgCwlh4cS/9MesbxeUNlYEjZ+pdVyOZvWJueNOrNfj99atdnbEpF5NfNsm3msi7rEPJGjI0bQ+8UHBqJ0ceXPv/nuPFxlj1bINzF82jds37nHj+h269foJIxMjtm/ZA8DCX6fh6+vPjMkLAOg9oAtDR/Wlb7fhPPV5gbVN4pLRkZFRRP1nid/qNSvj7OLEgF6J86Fu3biLSwFnatWphp29LQnxCXh5Psq8xv5DbWyAqVPupOe58lpjVdSR6JBIIl4EUXlEK3LkMefooBVJZayKOiYea2KAkWVOrIo6Eh8bR/DDF1p1G1nmolz/puxqPhmAmNAoXj14Tqku9fE5fQeHql9xZfG+TGhlckpjA3I4v+1lNna0xvSrfLwJieD18yCKjm6Noa0F1/slDnlx/rkur58FEe6Z2EarSoVx7dUI79WHk9Wds6A99k0rcaJu4msd7vkCTYKGfG1rEh0QQg5XO4JvemVCKzPflzC5PrNIMiGyvbP7z2BqYUq7we0xtzbH282bCT+NJ+SfSdnWdtZo3hnSFOgbyPifxtN1fFcWH15CkF8Q+9fuY9evu5LV3XdGX9b8spqY14l3qnwT84YFQxbQ85deqPXVrBi/nFd+Gb9GeXhEJAuWr8MvIBDTXDmpW6Ma/Xt0RK1SER8fzwOvR+w7eIywiEhsrCyoUqEMfbt10JrD8PS5L8HvrPB01+Mhnfu9XU5y1uKVADRtUIep/yQNkLg07bR5y5gzeVTSild5bKwZNagXY6fNR1+tZurYIRh+wjJ34tPoFy1EnlVzk55bDOkFQMS+wwRNnI3SygLVfxJARQ4TjGtXJ3jOh8fOWowdTPC8X9FERwOgiXlD0MRZWIzsj0Kt5tXMxcQH6HYd/uxo355DWFhZMHR0X6xtrLh3x4P2LXokTcq2c7Al4Z0vSx06t8bAQJ9VGxdo1TN3xlLmzXx7DRgaGjB11hh6dR6aNITC94Uf40ZMY96Sqbx584aBvUcTHa19d97MYFMiP81/H5P0/N+b0Ln/fppjg1diktuMHPZWWse0Pfx2YYHcJfJT6PuqhD0NYEOVQVrlvp70EzdXHiTSLyRp27EhK6gzrwclOtfj+vK/8L/lnQGt+jjzUvmptntc0vPik38CwGf7Ka4PWIFhbjOM37mxnkJPQdExrTF2tEYTl0DkYz/uTdnG441/J6u71Oyu3Jm4mfioxNczITqW6wOXU3J6J/T01dwevZ7olykPCRbZh0KTmgFVnxmVvv3HC4kvRoM86TOm/3Oz+/qXtxRjahjZVdd1CDrhVayIrkPQCZe77roOQSdym5jpOgSdGJkje76f543NnsM8m738TdchvFdIu9q6DuG9zLYc13UIWqRnQgghhBBCiHfJMKdU03ky4e7uzsWLF6lcuTKFCxfGw8ODhQsXEhMTQ/v27ald+8OZYUxMDDEx2t2pGo1Ga3KsEEIIIYQQIv3pdAr+oUOHKFWqFEOHDqV06dIcOnSIr7/+Gk9PT548eUK9evU4fvzDXTnTp0/H1NRU66FJCM+kFgghhBBCCJF96TSZmDx5MsOGDSMoKIh169bx448/0q1bN44ePcrff//NsGHDmDFjxgfrGDVqFKGhoVoPhV7OTGqBEEIIIYT44iRk4UcWo9Nk4t69e0l34GvVqhXh4eG0aNEiaX+7du24ffv2B+swMDAgV65cWg8Z4iSEEEIIIUTG0/mciX+/+Ovp6WFoaIipqWnSvpw5cxIaGqqr0IR4L4vclnQa1YmytcpiYGSA72NfFg5dgOdtz0yLITIyisWrNvL36Qu8Cg6hcEEXRg7sQfEihZLKeD32Yf6ytVy9eYf4+HjyOzmyYOrYpPtA/P7HAf46ehL3+55ERr3m/KHfyZUzR7JzRcfEUL1ha3ZtWIaRoSGzl6zinsdDfJ69oF2LJowc2DPZMYePn2HJqo08f+lHPgd7BvX6ma+rVEjaf/TkOXbs/Qu3+56EhoWzc90SChd00aojJuYNs5es4uCxU7yJjaVqhbIo9RTEy8S4dGdQpji5OrRCv0gBVNZW+A8ez+uT55P257t+LMXjghesJGzjjswKU2SQvoO60uC7urgWcCY6Opqrl28ybeI8vDwf6zq0dGVXsRBlejTCuoQzOXKb81fX+Xgfvpa036V+OYr99A3WxZ0wMs/J1m9HE+jmo8OI04dlpcIU6P0dpiWcMcpjzqVO8/A9dDVpf+GhP2DftDJG9hYkvIkn5PYj3KdvJ/jGl3kPCZG+dNoz4eTkxMOHb2/YdeHCBRwdHZOe+/j4YGtrq4vQhHgvE1MTZu2eRXxcHBM7TKTPN71Z+8saIkIjMjWO8TMWcuHKDaaPH8qeTb9SpUIZug0YjV9AIAA+z17QoddQnPPlZd2SmezasIyenX5E3+DtvSOio2OoVrEc3Tq0+eC5Lly+gW0eGxwd7HgTG4u5mSndO7ahkKtziuVv3HFj+MQZfP/dt/y+bgm1q1em/6hfeOj9OKnM6+hoypT4ikG9Or/3vDMXreDkuUvMmzKa9UtmERAYRO7chp/wVxKppTA0JPaBN69mLE5x/9O6LbUegRNno0lIIOrvM5kcqcgIlaqUZ8PqrTSu15a2zbuhVqv4bfcqjIyNdB1aulIbGRDo7sOpsRtS3K8yNuDF5fucn7Y9kyPLWEpjA0LvPeH2qHUp7o/w8uX26PUcrzmSM00nEvU0gCrbR6FvmX2HjWsSNFn2kdXotGeiV69exMfHJz0vVqyY1v6DBw9+dDUnITJbi14tCPQNZOHQhUnb/J76ZWoMCSRw7NRZFs2YQLlSxQHo06U9p85dYvuev+jfvSOLVm6geuXyDOnTJek4Rwc7rXp+av09AJevf3g44fGzF6hVrRIA9ra5GfVPT8Sev46kWH7zjj+oWrEcndslDlvs170DF65c57ed+5kwvB8ATep/A8Bz35T/duERkez+8wizJg6nYtlSAPwyZjBNfuyOgYEeMTFZcODoZyz6/BWiz1957/6EIO0bUxnXqEL01ZvEPffN6NBEJmjfsofW84G9x3DH8ywlShXl0vlr7znq8/Pk5G2enHz/+9393ecAyOlg9d4ynyP/47fwP37rvfuf7Tmv9fzuhM04tatFriKOBJ69l9Hhic+cTnsmevbsSaNGjd67f9q0aaxevToTIxLi4yrUrYjn7YeM+HUkm65vZsGBhdRr+22mxxEfn4CBvlprm4GBPtdv3yMhIYHT56/glNee7oPG8HWjNrTtNpC/T59/T23vl5CQwKlzl6lVvXKqj7l1z53K5UppbatSsSy37qX+BmRu9x8SFxdHpXJvb2KVP19eYuMSMDRQproekf70LMwwqlaRiL2HdB2KyCC5ciX+Ih0SLEONsxuFWonTT7WJDY0k7AsY4iUynk6TCSE+R3ny5qFB+4a8ePSCCT+N5+DmA3Sf1J3aLTKvF00PPUoWK8Ly9VvxDwgiPj6e/YePc+uuB4GBr3gVHELU69es2byDahXLsXL+VL75ugoDR0/hyo0P90L81617HgCUKFroIyXfCgwKxtLCXGublYU5gf/5dftjdajVqmRzOOLjNSiVssiCLuVoXI+EqCiijssQpy+RQqFg0vQRXL54nfvumTcPTOhW7rql+c5rLU2ebMClewPOtZ7Om1fZeKl9Xa/Y9Bmt5qTzCdhCfG4Uego8b3uyadZGALzveZOvUD4atGvI8Z2Zd4v76eOGMn76fGo3a49SqUeRgq40qFMDt/ueJPwzprJW9cp0aJM4lKlwQRdu3nFjx94DlC9dItXnOXHmAjWqVkBPT357EIlyNKlP5MHj8CZW16GIDDBtzlgKFSnA9w1+0nUoIhMFnnPjxDej0LfIiVP7WpRf2Z9TDcfzJjBM16GJLE6+HQjxiYL9g3n6ULvr9+nDp1jbW2dqHI4OdqxfOpvLx/ZwbPcmtq1eSFxcPA52eTA3y4VKqcTFyVHrmPxOefH1C/ik85w4eylpvkRqWVmaE/RKuxci8FUwVpbm7zki5TpiY+MIC9ee2K5UKoiPz3oT0LILg9LFUDs7ErHngK5DERlgyqwx1Pm2Bi0b/4zvi8ydCyZ0Kz4qhsjHfgRf9+TG4FVo4hLI17amrsMSnwFJJoT4RO5X3bB3cdDaZp/fHv9n/jqJx9jIEGsrC0LDwjl/+Rq1q1dCrVbzVZGCPPJ5plX28dPn2P2zLGxqPHn6HN+X/lQuX/rjhd9R8qsiXLx2U2vbhSs3KPlVkVTXUbRQAVQqFZeuvq3n0ZNnqFV6RMfEv/9AkaFyNG1AjNt9Yh966zoUkc6mzBpD/Ubf0KpJZ576PNd1OELHFHoKlAbqjxf8Qul6xSZZzUmIL9gfq/9g1p7ZtOzTkrN/nqVgqYJ8+2N9loxckqlxnLt0DY1Gg5OjAz7PXjB36RqcHR1o1qgeAD//+ANDx8+gXKliVChTkrMXr3Lq3CXWLZ6ZVEdg0CsCg4LxefYCgIdejzExNsI2jw2muXJy/MwFKpUrhZGh9nKsHg8S1x6PioomOCQUjwdeqNUqXJzzAdC+VVN+7jOc9Vt38XWVChw8dop7Hg+ZOKJ/Uh2hYeH4vvTHPzAIICnxsbI0x8rSgpw5TGj+XT1mLV6Faa6cmJgYM23+r0RHx8tKThlAYWSIKq990nOVvS3qgi4khIUT/zIxUVaYGGNc92uC563QVZgig0ybM45mLRrS+cd+REREYW2TuJpReFg40dExOo4u/aiNDTB1yp30PFdea6yKOhIdEknEiyAMzEzIaWeJSe7EXlRzl8Tl6aMCQokK+HwnoyuNDcjhnCfpubGjNaZf5eNNSARvgiMoOKAZLw9fI9o/BH2LnOT/uS6Gecx5vv+iDqMWnwuFRqPJeinO/0mlb//xQuKL0SDPp/1qnh7Kf1OeDiM6Yudkh99TP/au3suRrYczNYbus1uwYPk6/AICMc2Vk7o1qtG/R0dy5jBJKrP7z8Os3rQDP/9AnBwd6NO1PbXfWZVp6ZrN/Lp2S7K6p4weTLNGdenQayhNGtShRZP6WvuLVW2Q7Bi7PDYc2fV27fbDx8+weOWGpJvWDe7dWeumdXv/OsrYafOS1dOrczv6dGkPvL1p3YGjJ4mNjaVKhbKs2Xw0Ww5z8iqW+l6dtDAoW5I8q+Ym2x6x7zBBE2cDkKN5I8yH9OLZt63RRERmaDz/crmb+hXAviS5Tcwy9XzPg1Ne/nNQ7zHs2Lo30+IYmSNj38/tKxWh+e9jkm13//00xwavpHDL6tSd1yPZ/kvzdnN5/u4MiytvbMb+QGJVpQjVdo9Ltt1n+yluDl9LuWV9MC/jir5FTt4ERxBy04v7C/YScjNjeyCbvfwtQ+v/f7z6voauQ3gviz2ndB2CFkkmxGdPF8lEVrD7+qIMrT84JJRaTdpxbO8mrCxSP9choxnZVdd1CDqR0clEViXJRPaS0clEVpXRyURWlaWTiaZZOJn4I2slEzJnQgiRotCwcIb165alEgkhhBBCZC0yZ0IIkSInRwecHB0+XlAIIYQQ2ZYkE0IIIYQQQrxDkz1HnqWJDHMSQgghhBBCpIkkE0IIIYQQQog0kWFOQgghhBBCvEuGOaWa9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iGrOaWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iXDnFJNeiaEEEIIIYQQaSLJhBBCCCGEECJNZJiTEEIIIYQQ75DVnFJPeiaEEEIIIYQQaSLJhBBCCCGEECJNJJkQQgghhBBCpInMmRBCCCGEEOIdMmci9aRnQgghhBBCCJEmkkwIIYQQQggh0kSGOQkhhBBCCPEOGeaUetIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHiXRqHrCD4bkkx8QYzVBroOQSfuv36p6xB0wsiuuq5D0InXL87oOgSdyK6vd3Z9X/OLDNF1CDox5s15XYegE4/r5dV1CEKkmQxzEkIIIYQQQqSJ9EwIIYQQQgjxDlnNKfWkZ0IIIYQQQgiRJpJMCCGEEEIIIdJEhjkJIYQQQgjxDk2CrOaUWtIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHiHrOaUetIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHiHRiOrOaWW9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iGrOaWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3qFJkNWcUkt6JoQQQgghhBBpIsmEEEIIIYQQIk1kmJMQQgghhBDv0Gh0HcHnQ3omhBBCCCGEEGkiyYQQQgghhBAiTWSYkxBCCCGEEO+Q1ZxST3omhBBCCCGEEGkiyYTQ0q37T9xxO41/kDvHT+6mbNkS7y1buEgBNm1Zxh2304RFetO7z8/JyrRq3RS3+2d58uwG02aM0drn6GjP9Zt/kzNnjnRvx6dq17klx6/t487Tc/x+aD0lSn/13rL1GtVi19GNXPU8wc3HZ/jjxBaatmyoVaZz7/ZccDvCBbcjdO7VTmtfiTJfsfvYJpRKZYa0RbwVGRnFjAXLqdu8I2VrNaVdj8Hccb+ftL9Y1QYpPtZu2fneOpeu2ZysfOO23bTKzFq0kir1W/LN9z/x5+HjWvsOHz9Dn+ET0reh4oOy6/tadpXdXm9V0RLkGD0dszW7sNhzCnWFah89xqBBM0wXb8R82xFMl2xCv+a32nWWLIfp0s2YbzmAyYAxoHo7kEVhbILp0s3oWedO97aIz5MMcxJJmv/QiGkzRjNwwDiuXrlJ7z4/s/uPDZQtXYfAgKBk5Y2NjHj82Ie9ew4wfebYZPstLM1ZvHQ6vXoM4/Gjp/y+ezWnT17g0KHEL1fzFvzChPGzCA+PyPC2fUjDZnUZNXkQ44dN59a1u3Tq0ZY1OxbzbeUfeBUYnKx8SHAYy+evxfvhY97ExlKrXnWmLxpPUOArzp64SKGirgwY0ZMe7QaiUChYsWU+Z09e5IG7F0qlkslzRjNu8FTi4+N10NrsZfyMhXh6P2b6+KHYWFmy//Bxug0YzR9bVpDb2oqT+7ZolT9z8Srjpy+gbs2qH6zX1TkfqxdOS3r+bmJ48uxF/jp6kpXzp+Lz7AXjps2nasWymJuZEh4RyaKVG1i9YFpK1YoMkF3f17Kr7Ph6KwyNiH/sSczfB8g5cspHyxt82xTj9t2JXDabOE8PVAWKYNJ7GJqIcGKvngeFghyDxhG9ewuxNy6TY/hkDOo2JubgHgCMfupBzOF9JAT4ZXTTdEqGOaWe9EyIJH37dWHDuu1s2bST+x6eDOw/ltevX/NTh5Yplr9+/Tbjxsxg184/iYl5k2y/s1NewsLC2b3rL65fv83pUxcpWNgFgBYtGxMbG8v+fYcztE2p8XPPduzYvJfdW/fj9eAR44dOJ/p1NC1+bJJi+cvnr3H0wEm8Hj7m6ePnbFy5jftunpStWAqA/AWcuO/2kItnr3LhzBXuu3mSv4ATAF37/sSVC9e5c9Mtk1qXfUXHxHDs1FkG9+lCuVLFcXSwo0+X9jg62LF9z18AWFlaaD1OnLlIhTIlyGtv+8G6lUql1nHmZqZJ+7yfPKV86eIUK1KQhnVrYmJizDPflwDMW7aG1s0aYZvHJuMaLrRk1/e17Co7vt6x1y/x+rc1xF46k6ry+jXrEX1kH2/OnSDBz5c3Z48TfWQ/hs3bAqDIZYqeqRnRB/cS//Qxby6fQ5k3HwCqQl+hci1E9J/v770V2Y8kEwIAtVpNqdLFOHHiXNI2jUbDyRPnqFChdJrq9PJ6jJGRISVKFsXc3JQyZUtw764HZma5GDtuEEMHT0yf4P8ParWKr0oW5vypS0nbNBoN509fplS593eNv6ty9fI4u+TjyoUbADxw88TJxRFb+9zYOeTBycWRh+5e5HWyp3nbxiyY9muGtEVoi4+LJz4+AQN9tdZ2AwN9rt++l6x84KtgTp+/TPPvvk227798nj2nVpN21G/5MyMmzsT3pX/SvkKu+bnn8ZDQsHDueTwkJiYGR3s7rt+6i9t9T9q1TDlJFekvu76vZVfyeqeOQq2GN/9JnN7EoHItAkolmtAQEl4Foi5VDvQNUBUtQfxjL1AqMe4xmMhf50JCgm6CF1mSDHMSAFhamqNSqQjwD9Ta7u8fSMGCLmmqMyQkjJ7dh7Fi1VyMDA3Y9tse/j52hiXLZrByxSbyOTmw7feVqNUqpk9dxB97D6ZHUz6JuYUZKpWKwIBXWtsD/V+R39XpvcflyGnCmTsH0dfXJyE+nokjZiYlJF4PHzNv6jLW7VwGwNwpS/F6+Jj1O5cye9IiqtWuTL9h3YmLi2PKmDlc/ScJEenLxMSYksWKsHz9VvLnc8TSwowDx05x664Hjin0POw7eAxjYyPq1PjwEKcSRQsxZcwQnBwdCAx6xbK1W+jQexh7N/2KiYkxVSuW5btva9Om6wAMDQyYOnYIxkaG/DJnKVPGDGb7nr/4bec+zMxMmTi8P67582XUnyDby67va9mVvN6pE3vjCgZ1vuPNpbPEez9A6VIIgzqNUKjVKHKZogl+RcSciRj/3BfjLv2JvX6RmL8PYNi8HXF3b0DsG3JOW4JeLlOi/9qdNPzpSyM3rUs9SSZEhvpz/xH+3H8k6XnVahUoVqwww4ZM5OadE3TuNAA/vwBOnNrLuXOXUxzTmhVFRkTRtNaPmJgYU7l6eUZNHsTTx8+5fP4aANs27GLbhl1J5b9v3YjIiChuXL3D4Qu7+KFeB/LY2jB/5TRql21C7JtYXTXlizZ93FDGT59P7WbtUSr1KFLQlQZ1auB23zNZ2T1/HuG7erUwMND/YJ3VK5dP+v9Crs4UL1qIej905NDxM/zQOLFXo0+X9vTp0j6p3LK1W6hUrhQqlYoVG7axZ+MyTp2/zOgpc9ixdnE6tVZkli/1fU2k7Et7vV//vgE9cwtyzfwVFKAJCSbmxGGMmv8ICYnfoOPc7xA2vEfSMXp2DhjU/JbQIV3JNWUR0X/tJPb6JUwXrifO7RbxT7x11RyRBcgwJwFAUFAwcXFxWNtYaW23sbHCzy8gXc6hr6/PvPmTGdB/DPldnFCplJw7exnPh4/w8nxEuXIl0+U8nyL4VQhxcXFYWVtobbeysSDA//0fCBqNBp9Hz3C/+4C1v27h8P6/6TGwU4plzS1M6Tu0G5NHzaZkmWI89vLhifdTLp27hlqlwtnFMT2bJN7h6GDH+qWzuXxsD8d2b2Lb6oXExcXjYJdHq9y1m3d55POM5o3rf/I5cuXMQb689vg8e5Hifu8nT/nz8HH6devAlRu3KVeqGBbmZnxb+2vc7nsSGRmVpraJj8uu72vZlbzeqfTmDZFLZhLcph4hPdoQ0r0VCf4v0URFogkLSfEQk55DiVq/FBQKVC4FeXPuJJrQEOLu3UL1ValMDV9kPZJMCABiY2O5eeMuNWtWSdqmUCioUbMKly+nzzCc4SP6cOzYaW7dvIdSqYdK+bZjTKVW6WSp1NjYOO7d8qDy1xWStikUCipXL8/Nq7dTXY9CTw99/ZR/0R79yxDWr9iKn69/YrvVb9utVCllidhMYGxkiLWVBaFh4Zy/fI3a1Stp7d/952GKFipA4QL5P7nuqKjXPH3ui7WVRbJ9Go2GybMWMbxfN4yNjUiITyA2Lg6AuH/+Gy9jjzNMdn1fy67k9f5E8fFoggIgIQH96rV5c/VCimN79L9piCYijNgr51HoJX5tVPy7VKxSCXpf5ldJTYIiyz6yGhnmJJIsWbyG5SvncOPGHa5evUXvPj9jbGzM5k2JqzasWDWHFy/8mDRhNpA42a1wEVcA9PXV2NrlpniJIkRGROHt/USr7kKFXWn+w3dUq/IdAA/ue5GQkMBPHVrh7xdAwYIuXL+W+i/v6Wnd8i3MXDyRuzfduH39Hh17/IiRsRG7tu4HYNaSSfi99GfulKUA9BjQiTs33Xn6+Bn6+mpq1KlK05YNmTh8erK6q9SoiJOLI8P7Jt5X4PYNN/K75uPrb6pga5ebhPgEvD2fJDtOpI9zl66h0WhwcnTA59kL5i5dg7OjA80a1UsqExEZyZETZxjat1uKdXTpP5Jvvq7Cjy0SJ07PXrKKmlUrYpcnN/6BQSxdvRmlUo+GdWokO3bX/kOYm5lSs1pi8lK6RFGWrd3MrbvunLl4FRcnR3LJ/QgyVHZ9X8uusuXrbWiEMo990lO93LYonVzRRISREOiPUftu6FlYE7kocUlqPTsHVAWKEPfADUWOnBg2boXS0ZnIhck/wxSmZhi17EDYqD4AaCIjiH/6GIPvWhB36yrqEmV5vXNz5rRTZFmSTIgku3f9hZWVBaPHDiJ3bivu3Hbnh2adkiazOTjYkfDOr6i2tjacu/BX0vMBA7szYGB3zpy+SKMGP2rVvWjxNEaPnEpU1GsAoqNj6NVjOHPmT8LAQJ+hgyfg66ubNasP7D2KhaU5/Uf0xNrGEve7D+jSuh9B/0zKtnXIQ4LmbbuNjI2YOGsEeWxtiI6OwfvhY4b1HseBvUe16jUwNGD8jOEM6jYKzT+/9vj5+vPL6NlMXzSeNzGxjOg3gZjomMxrbDYTHhHJguXr8AsIxDRXTurWqEb/Hh1Rv3MDpoPHTqHRQMO6NVOs4+lzX4JDw5Ke+/kHMnzCTELCwrAwM6V0ia/YsmI+FuZmWscFvgpm5YZtbF4+L2lb8aKF6NimOb2HTcDC3IxpY4eka3tFctn1fS27yo6vt8qlELmmLEx6btK5LwAxxw8SuXgGeuaW6Fm/sxy1nhLDJq1R2udFExdH3N0bhI3sQ0LAy2R1G3fpT/Qf29EEvx32G7F4Ojn6j8bwux94vXcb8Z4eGdc48VlQaDRZa766RqNBofj/unBU+vYfL/QFMlYb6DoEnchjnHx4SXbgHeqr6xB04vWL1K2l/qUxsquu6xB0Iru+r0XFZs8fGbLr6/24Xl5dh6ATFntO6TqE9/Iq9vFlwnXF5W7WupdNlhvoZmBggLu7u67DEEIIIYQQQnyEzoY5DR48OMXt8fHxzJgxA0tLSwDmzZuXYrl/xcTEEBOj/QtOevRuCCGEEEIIIT5MZ8nEggULKFmyJGZmZlrbNRoN7u7umJiYpCohmD59OpMmTdLaptDLgUKZKz3DFUIIIYQQ2YRGFtpLNZ0lE9OmTWPlypXMnTuX2rVrJ21Xq9WsX7+eokWLpqqeUaNGJevlMLcsnK6xCiGEEEIIIZLT2ZyJkSNHsn37dnr16sXQoUOJjU3bHYANDAzIlSuX1kOGOAkhhBBCCJHxdLo0bPny5bl27Rp9+vShXLlybNmyRRKBz0iVquUZMLA7pUoXw9Y2N21b9+CvP49+/MDPXNtOP9C2UwscHG0BeOjhzdK5qzn993kdR5Y9RUZGsXjVRv4+fYFXwSEULujCyIE9KF6kEABjpszlj4PHtI6pWrEsK+ZNAeDy9dt07jcixbq3rl6QVA/AlRu3GTl5Nn/v2fTR80LiDe3m/7qO42fOExIajr1dbtq1aErr7xsBEBoWztLVmzh/+Tq+fgGYm5tSu3pl+nXrQM4cJun6dxKpk13f17Kr7PJ6q4qWwLBZW1QuBdGzsCJ8+hhiL59N2q8wNce4Qw/UpcqjMMlB7L1bRK1eSILvcx1GrVsJGvk+mlo6v89Ejhw52LBhA9u2baNOnTrEx8frOiSRSiYmxty9486mjb/z27blug4n07x84c/cKUt47O2DAgXft/mOZRvn0qx2Ozzve+s6vGxn/IyFeHo/Zvr4odhYWbL/8HG6DRjNH1tWkNvaCoBqlcoxZfSgpGPUanXS/5cuXoST+7Zo1bl41SYuXbtJscIFtbafOHORmlUrpvq8sxav5NK1W0wfPxx729ycv3yNKXOXYmNlSa3qlfAPDMI/8BVD+3Ylv5Mjvn7+TJ69hIDAIOZPHZshfy/xYdn1fS27yi6vt8LQiPjHnsT8fYCcI6ck259z1FQ0cXGETx+DJioSwyatyDlxHqH9O0JMtA4iFp8TnScT/2rTpg3VqlXj2rVr5MuXT9fhiFQ4euQUR49k3TWiM8qJI9r3OZg/bRltO/1AqXLFJZnIZNExMRw7dZZFMyZQrlRxAPp0ac+pc5fYvucv+nfvCIC+Wo2VZcr3I1H/Z19sXBwnzlzgxxZNkvWUnjh7kTGDe6f6vDfvuNO0QR0qlCkBQMumDfn9j4Pccb9PreqVKJDfiQXT3iYNjg529O/ekZGTZxEXF49KpUynv5RIrez6vpZdZZfXO/b6JWKvX0pxn56dA6pCXxHavyPxTx8DELViHmbr9mBQ/Rtijv2V4nFC/CtL3WfCwcGBpk2bYmIi3fvi86Cnp0ejZvUwNjbixpXbug4n24mPiyc+PgEDfbXWdgMDfa7fvpf0/MqN23zdqA3ftenK5NmLCXnnjtb/dfLMRULCwmnWqK7Wdk/vJ7wKDqFi2ZKpPm+p4kU4cfYifgGBaDQaLl+7xWOf51SpUOa95w+PiCSHibEkEkKITKFQ6QOgiX3zdqNGgyY2FlWR4jqKSvc0GkWWfWQ1WaZnQojPScEiLmw/uA4DA32iIl/Tp9MwvB480nVY2Y6JiTElixVh+fqt5M/niKWFGQeOneLWXQ8c7RPntFStVJY6Napib5ebp899WbhiPT2HjGPLinkolcm/sO/+8zBVK5Qhj4211vbjZy5QtWJZ1Go1arX6o+cFGD2oFxNnLuKbZj+hUipR6CmYOGJAUm/GfwWHhLJi/VZaNGmQjn8lIYR4v/jnT4j3f4lR++5E/ToHTUw0ho1borSyIcHcUtfhic+AJBNCpMEjzyc0rfUjOXPmoH6Tb5i5eCLtmnaXhEIHpo8byvjp86ndrD1KpR5FCrrSoE4N3O57AtCwTs2ksgVdnCno4kyDVp25cuM2lcqV1qrrpX8A5y5fZ+7kUcnOc+LsRdr+0DjV5wXYsnMft+95sGTmBGzz5ObazTtMnbsMGytLKpfXPndEZCS9h03AxdmR3l3ap8efRgghPi4+noiZ4zDpOxzzzX+hiY8j9tY13ly7CLIojkgFSSaESIPY2Dh8Hj0D4N5tD4qXKkrH7m0ZP3SajiPLfhwd7Fi/dDZRr6OJjIzC2sqCIeOm42CXJ8Xyee1tMTfLhc8z32TJxN6/jmKWKyc1q1fS2h4Q+Ar3B17UqFIh1eeNjolh4YoNLJw+Lum4Qq7OeDz0Zv3WXVrJRGRkFD0Gj8PE2IiF08ahVslbsxAi88R7PyBscFcUxiagUqEJCyXXzF+J87qv69B0RpMgiVRqZak5E0J8rhR6eugbqD9eUGQYYyNDrK0sCA0L5/zla9T+T0Lwr5f+AYSEhmP9nwnZGo2GvQeO0rjBN8m+zJ88d5FSxYtgmitnqs8bFxdHXFwcev/5ZU+p1CMh4e2tVSMiI+k+aAxqtYrFMydgYKCfpvYLIcT/SxMViSYsFD1be5QuhXhz6ezHDxLZnvz8JdLMxMSY/C5vV95ycspL8RJFCH4VyrNnL3QYWcYaMrYPp/4+j++zl5jkMKbxD/WpWLUsnVv103Vo2dK5S9fQaDQ4OTrg8+wFc5euwdnRgWaN6hEV9Zpla7dQt2ZVrCwtePr8BfOWrcXRwY6qFbUnQV+6dpNnL17yQ+P6yc5x4uwlalXTTk4+dF6AHCYmlCtdnLlL12BgYIBdHhuu3rjDvoN/M6x/N+CfRGLgGF7HxLBw/DAiI6OIjIwCwNzMNMU5HSJjZdf3tewq27zehkYo89gnPdXLbYvSyRVNRBgJgf6oq9REExpCQqAfynz5Me7Sj9jLZ4m7dVWHQYvPhSQTIs1KlynOgUNbk55Pn5m4xOWWzTvp1WO4rsLKcBZWFsxaMgmb3FaEh0Vw3+0hnVv14/yplJfdExkrPCKSBcvX4RcQiGmunNStUY3+PTqiVqmIj4/ngdcj9h08RlhEJDZWFlSpUIa+3Tqgr6/dA7D7zyOUKl6U/Pnyam2Peh3Npas3GTmgR6rP+685k0ayYPl6Rk6aRWhYOHZ5bOjfoyOtmyXetM7tvhe33RKHETRs3UWr/sM712Nvmzvd/k4idbLr+1p2lV1eb5VLIXJNWZj03KRzXwBijh8kcvEM9MwtMfy5D3qm5iQEB/Hm5GFe/75RV+FmCRqNriP4fCg0mi/vz6XSt/94oS+QsdpA1yHoRB7jlO8f8KXzDvXVdQg68frFmY8XSkdHT55j8aoN7NuyMlPP+19GdtV1en5dya7va1GxMboOQSey6+v9uF7ejxf6Alnsybr3+HAv0FDXIbxXkYcHdB2CFpkzIYQQH2BsZMjgXp11HYYQQgiRJckwJyGE+ICqFcvqOgQhhBCZTFZzSj3pmRBCCCGEEEKkiSQTQgghhBBCiDSRYU5CCCGEEEK8I0Ejw5xSS3omhBBCCCGEEGmSqp6Jffv2pbrCJk2apDkYIYQQQgghxOcjVclEs2bNUlWZQqEgPj7+/4lHCCGEEEIIndLIMKdUS1UykZCQkNFxCCGEEEIIIT4zMmdCCCGEEEIIkSZpWs0pMjKSU6dO4ePjw5s3b7T29e/fP10CE0IIIYQQQhc0Gl1H8Pn45GTixo0bNGzYkKioKCIjI7GwsCAwMBBjY2NsbGwkmRBCCCGEECKb+ORhToMGDaJx48YEBwdjZGTExYsXefLkCWXLlmXOnDkZEaMQQgghhBAiC/rknombN2+yYsUK9PT0UCqVxMTEkD9/fmbNmkXHjh1p3rx5RsQphBBCCCFEppCb1qXeJ/dMqNVq9PQSD7OxscHHxwcAU1NTnj59mr7RCSGEEEIIIbKsT+6ZKF26NFeuXKFAgQLUqFGD8ePHExgYyKZNmyhWrFhGxCiEEEIIIYTIgj65Z2LatGnY2toCMHXqVMzNzenVqxcBAQGsXLky3QMUQgghhBAiM2k0iiz7yGo+uWeiXLlySf9vY2PDoUOH0jUgIYQQQgghxOdBblonhBBCCCGESJNP7plwdnZGoXh/F4u3t/f/FZAQQgghhBC6JDetS71PTiYGDhyo9Tw2NpYbN25w6NAhhg0bll5xCSGEEEIIIbK4T04mBgwYkOL2pUuXcvXq1f87ICGEEEIIIcT/7/Tp08yePZtr167h6+vLnj17aNasWdL+Tp06sWHDBq1jvv3220+aE51ucyYaNGjArl270qs6IYQQQgghdCJBo8iyj08RGRlJyZIlWbp06XvL1K9fH19f36TH1q1bP+kcn9wz8T47d+7EwsIivaoTQgghhBBC/B8aNGhAgwYNPljGwMCAPHnypPkcabpp3bsTsDUaDS9fviQgIIBly5alORAhhBBCCCHEh8XExBATE6O1zcDAAAMDgzTVd/LkSWxsbDA3N6d27dpMmTIFS0vLVB//yclE06ZNtZIJPT09rK2tqVmzJoULF/7U6jJEbhMzXYegE36RIboOQSdeRr3SdQg6Ucoyv65D0Im6pbrrOgSdeP3ijK5D0AnPyn11HYJOVHzhoesQdCKnvpGuQ9CJLVfz6joEnein6wA+ICveHO5f06dPZ9KkSVrbJkyYwMSJEz+5rvr169O8eXOcnZ3x8vJi9OjRNGjQgAsXLqBUKlNVxycnE2kJVAghhBBCCPH/GzVqFIMHD9baltZeiTZt2iT9f/HixSlRogQuLi6cPHmSb775JlV1fPIEbKVSib+/f7LtQUFBqc5ghBBCCCGEEJ/OwMCAXLlyaT3Smkz8V/78+bGyssLT0zPVx3xyz4TmPXfxiImJQV9f/1OrE0IIIYQQIkv51FWTvhTPnj0jKCgIW1vbVB+T6mRi0aJFACgUClavXk2OHDmS9sXHx3P69OksM2dCCCGEEEKI7C4iIkKrl+HRo0fcvHkTCwsLLCwsmDRpEj/88AN58uTBy8uL4cOH4+rqyrfffpvqc6Q6mZg/fz6Q2DOxfPlyrSFN+vr6ODk5sXz58lSfWAghhBBCCJFxrl69Sq1atZKe/zvXomPHjvz666/cvn2bDRs2EBISgp2dHfXq1eOXX375pGFTqU4mHj16BECtWrXYvXs35ubmqT6JEEIIIYQQn4uUB/V/fmrWrPneKQoAhw8f/r/P8clzJk6cOPF/n1QIIYQQQgjx+fvk1Zx++OEHZs6cmWz7rFmzaNmyZboEJYQQQgghhMj6PjmZOH36NA0bNky2vUGDBpw+fTpdghJCCCGEEEJXEjSKLPvIaj45mYiIiEhxCVi1Wk1YWFi6BCWEEEIIIYTI+j45mShevDjbt29Ptn3btm0ULVo0XYISQgghhBBCZH2fPAF73LhxNG/eHC8vL2rXrg3A33//zW+//cbOnTvTPUAhhBBCCCEykyYLDifKqj45mWjcuDF79+5l2rRp7Ny5EyMjI0qWLMnx48exsLDIiBiFEEIIIYQQWdAnJxMAjRo1olGjRgCEhYWxdetWhg4dyrVr14iPj0/XAIUQQgghhBBZ0yfPmfjX6dOn6dixI3Z2dsydO5fatWtz8eLF9IxNCCGEEEKITJeQhR9ZzSf1TLx8+ZL169ezZs0awsLCaNWqFTExMezdu1cmXwshhBBCCJHNpLpnonHjxhQqVIjbt2+zYMECXrx4weLFizMyNiGEEEIIIUQWluqeiYMHD9K/f3969epFgQIFMjImIYQQQgghdEaDrOaUWqnumTh79izh4eGULVuWihUrsmTJEgIDAzMyNiGEEEIIIUQWlupkolKlSqxatQpfX1969OjBtm3bsLOzIyEhgaNHjxIeHp6RcQohhBBCCCGymE9ezcnExITOnTtz9uxZ7ty5w5AhQ5gxYwY2NjY0adIkI2IUQgghhBAi0yRosu4jq0nz0rAAhQoVYtasWTx79oytW7emV0xCCCGEEEKIz8D/lUz8S6lU0qxZM/bt25ce1QkhhBBCCCE+A2m6A7YQQgghhBBfqgRZzSnV0qVn4kvUsWtbLt46gpfvdfYf3UqpMsXfW/bHDi3YfWAj9x6d596j82zbszpZ+R59O3HrwWluPThNjz4dtfaVLlucgyd2oFQqM6Qt4uO6df+JO26n8Q9y5/jJ3ZQtW+K9ZQsXKcCmLcu443aasEhvevf5OVmZVq2b4nb/LE+e3WDajDFa+xwd7bl+829y5syR7u34VC07fc++yzs49+gY6/9awVeliqTquHpNv+Gq7xnmrJumtb19zzYcubOPI3f20a5Ha619X5UuyqbDq7PEdd6sYxO2XdjMEc8DLNu/mMKlCn2wfI5cJgyY0o9d17ZzxOsAm06vp2LtCkn763xfmx2Xf2P/3T30Ht9T69g8DrnZdHo9xjmMM6QtKYmMjGLGguXUbd6RsrWa0q7HYO6430/aP2bKXIpVbaD16DF47Afr3LbnT77v0IuKdZtTsW5z2nUfxJkLV7TKzFq0kir1W/LN9z/x5+HjWvsOHz9Dn+ET0q+RqWBUvhgOKybgenYTRR4eIEedyh89JleTmjjvW0Kh27spcG4zttMHojTLmbTfpGpp8h9ZRcEbO7GbPRTUb3+T08thTP4jq1DZ2WRIez5Vdn1fy26f33YVC/Hd2sH8fHUx/Z5uJv+3ZT9Y3qV+OZpuGUHXm8vo4baKFnsn4FhDu80Fm1Wh06WFdLuzgmrj22nty+lgRftTs1HnMEr3tojPkyQTKWjyfX0mTBnOvJnLqF+zJW5377Nl1wosrSxSLF+5Wnn+2HWAVo0706ReO148f8lvu1eSxzbxA6XIVwUZNqovvbsMo0/XYQwb05/CRRPv1aFUKpkxbwIjB08mPj4+09oo3mr+QyOmzRjNjOmLqF61MXfuuLP7jw1YWVumWN7YyIjHj32YOH4WL1/6J9tvYWnO4qXTGTt6Ot836UjrNk2pX7920v55C35hwvhZhIdHZFibUqNuk9oMmtiXVXPX0/7brjxw82Tx1rmYW5p98DhbhzwMGN+b6xdvam13LeJCz+FdGN1zImN6TaLXiG64FM4PJF7no2cOYfrwOTq/zms1rknv8T1ZP38T3Rr0xMvNm9mbZ2D2nnar1Crm/DaLPHnzMKHHZDrU+Jk5w+cR6Ju4NLapeS6GzR7Cr7+sZGi7kdRt/g2Vv6mYdPzAaf1ZOX01URFRmdE8AMbPWMiFKzeYPn4oezb9SpUKZeg2YDR+AW+X865WqRwn921JesyaOOKDdeaxtmJQz5/ZsXYx29csokLZkvQbORlP7ycAnDx7kb+OnmTl/KkM6d2FCTMWEhwSCkB4RCSLVm5g7OA+GdfoFOgZGRLj8Qi/SctSVd6oTFHsZg0hZOcRvBv24ln/aRiWKEieqf0TCygU2M0bTsjWAzxuORjD4q6Yt66fdLzNsJ8J2XqAuBfJ3xcyW3Z9X8uOn99qIwMC3X04NXZDqsrbVSzM0zN32ddxDtsajuX5BXe+WzsEq6/yAWBonoNvZnfl3JTf+KP9TAp9XwWnb0olHV9zaicuTN9ObMTrjGiO+AxJMpGCbr078tvGnez4bS8P73sxcvAkXkdF06Z98xTL9+s+gg1rtnHvrgdeDx8xtP949BR6VPu6EgCuBZxxv/eAc2cucfb0JdzvPcC1gDMAvfr/zMXzV7l1426mtU9o69uvCxvWbWfLpp3c9/BkYP+xvH79mp86tEyx/PXrtxk3Zga7dv5JTMybZPudnfISFhbO7l1/cf36bU6fukjBwi4AtGjZmNjYWPbvO5yhbUqNdj1as3fLfvZvP8CjB4+ZPnwO0a+jadK20XuP0dPTY8rS8aycs5bnT3y19jm5OvLQzYur565z5ew1PN29cHJ1BOCn3m25fukWbrc8MrRNqdGy+w/8tfUAh3Yc5slDH+aNXEB0dAwN29RPsXzD1vXJaZaTsV3Gc/fqPV4+8+PWxdt4uXsDYJvPlsiwSE7sP8n9W/e5cf4WjgUSP5RrN61FXGw8Zw6ezazmER0Tw7FTZxncpwvlShXH0cGOPl3a4+hgx/Y9fyWV01ersbK0SHqY5sr5gVqhZrVKfF2lAvny2uPk6MCAHp0wNjLk1r3E19T7yVPKly5OsSIFaVi3JiYmxjzzfQnAvGVraN2sEbZ5MvcX+8jTVwmYv5HwoxdSVd6odGFin/sTvHEfsc/8eH3NjZBtBzEqkdhzpTTPhcrClOAtf/LG04fwvy+h7+L4z7FFMCxekFcb/siw9nyK7Pq+lh0/v5+cvM3F2TvxPnQ1VeXPTNrM9eV/4X/Lm9DHflyYuYOQRy9xrlMaANN8NsSERfFw/yX8b3nz/II75q72ABRoWpmEuHi8Unmuz5kGRZZ9ZDWSTPyHWq2mRKminDn59sNHo9Fw9tRFypYvmao6jIwNUalVhPzzq5y720OcXZ2wc7DFPq8t+V3z4eHuST6nvLT+8XtmTV2UIW0RH6dWqylVuhgnTpxL2qbRaDh54hwVKpROU51eXo8xMjKkRMmimJubUqZsCe7d9cDMLBdjxw1i6OCJ6RP8/0GlVlG4REEunbmWtE2j0XD5zFVKlP3qvcd1HdyJV0HB/LH1r2T7PD28ccyfl9z2NuRxyI1j/rx43X+EfT47GrduyK8zVmVIWz6FSq2iUPGCXDtzPWmbRqPh2pnrFC1TNMVjqtSrjNt1NwZO7c/uG7+z7tgq2vVti55e4tvns0fPMTAywPUrV3Ka5aRwyUJ4u3uTwzQHXYZ1YuHYxZnStn/Fx8UTH5+Agb5aa7uBgT7Xb99Len7lxm2+btSG79p0ZfLsxYSEhqX+HPHxHDh2ktfR0ZQqVhiAQq75uefxkNCwcO55PCQmJgZHezuu37qL231P2rXM+kuHv77hgTqPFSY1ygGgtDQjZ/1qRJxMHM4V/yqUWL8gTKqVQWFogHG5r4i5/whUSvJM6sPLcYshIUGXTQCy7/uafH6nkUKBfg5DYkIiAQh59BK1kQFWX+XDwMwEmxL5CfLwwcDUmEpDW6S6B0RkHzIB+z8sLM1QqVQEBgRpbQ8ICMLln18jPmbMxCH4vfRPekPzfODNzF8WsG134pepGZMX4PnAm217VjNlwlxq1q7G4JG9iYuNY/yo6Vw6f+1D1Yt0ZGlpjkqlIsBf+27u/v6BFCzokqY6Q0LC6Nl9GCtWzcXI0IBtv+3h72NnWLJsBitXbCKfkwPbfl+JWq1i+tRF/LH3YHo05ZOYWZiiUql4FfBKa/urgGCcXPOleEzJCsVp2rYRP9btnOL+xw+fsGzGSpZtmw/A0ukrePzwCUu3z2fRlF+pXLMi3Yf+TFxsHHPGL+LGxVvp26hUMLUwRalS8iogWGt7cGAwjq55UzzGztGWPFVKc3Tv34zsMBp7J3sGTuuPSq1iw/xNRIRGMH3QLEYvHIGBoT5Hdh3lyqmrDJszhD3r/sDWMQ/T1v2CSqVk/fyNnPrrTIa20cTEmJLFirB8/Vby53PE0sKMA8dOceuuB472tgBUrVSWOjWqYm+Xm6fPfVm4Yj09h4xjy4p5Hxz7/cDrEe16DObNmzcYGxmxcNo4XJwTr5eqFcvy3be1adN1AIYGBkwdOwRjI0N+mbOUKWMGs33PX/y2cx9mZqZMHN4f1/wpX2e69Pq6G8+HzMZ+wUj0DPRRqFWE/32Rl+8Mk3o+YDq5R3cn99geRJy6SsjOI1j1aEXUpdskxLwh37Y5KM1zEbxpH8Gb/9RJO7Lr+5p8fqdNmR4NUZsY8vDPSwDEhEZxdPAK6i7oicpQH49dZ/E5dYfas7tye/0Rcjla893aweiplVyatxuvA1c+cgbxpZNkIp31GdiVJs0b0LJxJ62u4k3rdrBp3Y6k5y3bNCUiIpJrV25x+sqfNKrdGlu7PCxbPYfKperx5k2sLsIX6eTP/Uf4c/+RpOdVq1WgWLHCDBsykZt3TtC50wD8/AI4cWov585dTvbhl9UYmxgxefFYpg6bReir0PeW27XxD3ZtfDvMo1HL+kRFRnHn6l12nd1ChwbdsbG1ZtqvE2lSsRWxn8F1rtDTIzgohLnD55OQkMCDOw+xymNJm56t2DB/EwBnD53j7KG3vwKXrFQCl8L5WTR2CVvObuCXvtN45f+KX/9cyq2LdwgJCsnQmKePG8r46fOp3aw9SqUeRQq60qBODdzuewLQsE7NpLIFXZwp6OJMg1aduXLjNpXKvf+Xa2dHB3atX0p4RCRHTpxlzNS5rF8yKymh6NOlPX26tE8qv2ztFiqVK4VKpWLFhm3s2biMU+cvM3rKHHaszdwem9TQd81L7rE9CFy6lcgz11BZW2Azogu2k/viO3ohAK+vufH4h4Fvj3Gyx7RZbbyb9sPpt1m82vAHEaeukv/Ar0RduUvM/ce6aUwG+NLe1/4rO35+F2xWmQqDvuevLvN5HfS2d9L70FWtYVN2lQpjVcSR0+M28tPZuRzuu5Qo/1Ba7Z/Ei0v3tY79Uui+j/HzIcnEf7wKCiEuLi7ZJDVra8tkv/L8V4++negzsAttmnXF/d6D95YztzBj0Ihe/NCoI6XLlcDb8wmPvH145O2DWq0iv6sTHm4P06U94sOCgoKJi4vD2sZKa7uNjRV+fgHpcg59fX3mzZ9M925DyO/ihEql5NzZywB4eT6iXLmSHDp4/CO1pK+QV6HExcVhYa09KdHC2pwg/+RfAByc7LF3tGPehhlJ2/4d5nPx6Ql+qNaO509eaB1jamFKtyE/0/37vhQrUxQf76c8ffSMp4+eoVKrEodBeXhnQOveL/RVKPFx8VhYm2ttN7cy55V/cIrHBPkHER8bT8I7w1eeePpgmdsSlVpFXGycVnm1vpqBU/szbcAM7J3tUKqU3Lp4G4Bn3s8oUrowF45dTOeWaXN0sGP90tlEvY4mMjIKaysLhoybjoNdnhTL57W3xdwsFz7PfD+YTKjVahwd7AD4qnAB7nk8YPPvfzBheP9kZb2fPOXPw8fZuW4Ju/86QrlSxbAwN+Pb2l8zbtp8IiOjMDHJvBWuUsOqR2teX3fj1epdAMTcf8zL19E4bZtDwPyNxAUkv0by/NIXv+mrUegpMPzKlbCDZ9FExxB1+Q7GFYrrJJnIru9r8vn9aQo0qUTtWV051HMxT8/ee285PX0VNad04ujA5Zg65UZPqceLi4lzpUIevSR3aRceH7uRWWGLLEjmTPxHbGwst2+6Ua1GpaRtCoWCal9X5NqV9w/L6NW/MwOH9aR9ix7cvvn+f5QAk6aNYNWyjfi+8EOpp4f6naUFlSolSj3dL52ZXcTGxnLzxl1q1qyStE2hUFCjZhUuX06fN8fhI/pw7Nhpbt28h1Kph0r59vVWqVU6WVIwLjYOj9sPqFDt7RKCCoWC8tXKcvta8uv3sacPrWt2oF2dzkmP00fOcfXcDdrV6YxfCqvXDJnUj60rd+DvG4CeUg+V6p3rXKlEqcz8t5+42Dju33lAmWplkrYpFArKViuN23W3FI+5e+Ue9k52KBRvJ73lze9A4MvAZIkEwE/923H55BUe3vVET0+JUvX29VWpM7fdxkaGWFtZEBoWzvnL16hdvVKK5V76BxASGo61Zcor3rxPQoImxV9hNRoNk2ctYni/bhgbG5EQn0BsXOLfKu6f/8ZngbkF/6UwMoAEjfbG+H/iVCSf9Gjaoh7xoRFEHL8E/7xvK1T//lcFOrjGIfu+r8nnd+oVaFqZOnO7c7jvUh4fv/nBsuX7N8Pn1G0C7j5GodRD7533ND2VEj0dXeci65CeiRSsWraB+cumcfvGPW5cv0O3Xj9hZGLE9i17AFj46zR8ff2ZMXkBAL0HdGHoqL707Tacpz4vkn4NioyMIipSeznI6jUr4+zixIBeowG4deMuLgWcqVWnGnb2tiTEJ+Dl+SjzGitYsngNy1fO4caNO1y9eovefX7G2NiYzZt2ArBi1RxevPBj0oTZQOKvs4WLuAKgr6/G1i43xUsUITIiCu9/lsn8V6HCrjT/4TuqVfkOgAf3vUhISOCnDq3w9wugYEEXrl+7nYmtfWvLiu1MXDgat1se3Lvpzo/dWmJkbMT+bQcAmLRoDP4vA1k6bQVvYt7gdV/7ugwPTVwC8r/bASp+XQ7H/HmZ0H8qAG43Pcjnmo8qtSuS286GhIR4nnj5ZHALU/b7yl2Mmj+c+7fu437zPi26NsfQyJCD2w8BMGrBCAJfBrJqxhoA/ti4n+87NaXf5D7sXrsHB2cH2vX9kd1r9ySrO18BR2o1qUm3bxPvNeHj5YMmQUPDNvV55R+Mo4sjHrfuJzsuvZ27dA2NRoOTowM+z14wd+kanB0daNaoHlFRr1m2dgt1a1bFytKCp89fMG/ZWhwd7Kha8W2S1aX/SL75ugo/tkicOD3/13VUr1wO29w2REZF8deRk1y5cZsV86YkO/+u/YcwNzOlZrXEL3WlSxRl2drN3LrrzpmLV3FxciRXJtyPQGFsiH4+u6Tn+g65MSiSn/iQcOJ8A7Ae0glVbkt8h88FIOL4JWyn9Mfsx4ZEnrmOytqC3GO68/rWfeL8tecXKS1MserdhidthgKQEBZBjKcPFp2aEXn2OsaVSxL467YMb+P7ZNf3tez4+a02NsDUKXfS81x5rbEq6kh0SCQRL4KoPKIVOfKYc3TQCiBxaFOdeT04M3Ezfje8MLY2BSAu+g1vwrWXezUvYEeBxhXZVj/xPjTBXi/QJGgo2roGUQGhmLvY4ncrc3uYM0tWXDUpq5JkIgX79hzCwsqCoaP7Ym1jxb07HrRv0SNp/Kedgy0J7/x61aFzawwM9Fm1cYFWPXNnLGXezLcT9wwNDZg6awy9Og9Fo0k83veFH+NGTGPekqm8efOGgb1HEx0dk/GNFEl27/oLKysLRo8dRO7cVty57c4PzToldYs7ONhpDXGxtbXh3IW3qxkNGNidAQO7c+b0RRo1+FGr7kWLpzF65FSiohLfoKOjY+jVYzhz5k/CwECfoYMn4OvrlwmtTO7ovuOYW5rRc3gXLK0teHDPk34/DuVVYOJQjjz2ubWu89QyMNRn+NRBjOo5Iek69/cNYPbYBYyfP4rYN7FM6D+NmOjky09mhhP7T2JmacrPQzthYW2Op5sXw38aRXBgCAC57W3QvPN6B/gGMKzdSPpO7M3ao6sIeBnIrjW72bpse7K6h84czLJJvxL9OhqAN9FvmDFoFgOm9kdfX83CcYsJfJnx48jDIyJZsHwdfgGBmObKSd0a1ejfoyNqlYr4+HgeeD1i38FjhEVEYmNlQZUKZejbrQP6+vpJdTx97kvwOys8vQoJYfQvcwgIekVOExMKujqzYt4UqlQoo3XuwFfBrNywjc3L5yVtK160EB3bNKf3sAlYmJsxbeyQDP8bABgVK0C+LTOTnuce0x2AkN1H8R0xH5WNOWo766T9obuPoWdihEX7xuQe2ZX4sEiiLt7Cf/a6ZHXnHteDV2t3ayUZL0bMw27WYMw7NOHVml1E39HdcJfs+r6WHT+/bUrkp/nvb28iWH1C4rwl999Pc2zwSkxym5HD/u2Qt69+rI1SraLm1E7UnNopafu/5d9Ve0YXzk7eQtzrxHbFR8dybPAKakzphFJfxalxG4l8mfIQUZF9KDT//qv4gtibv39pyy+ZX2SIrkPQCWO1ga5D0ImCuex1HYJO5FBmz9f76M2VHy/0BfKs3FfXIehExRe6vyeLLuTUz553VR6ZI21L9n7u+j3drOsQ3utI7ja6DuG96vnprtczJdIzIYQQQgghxDuy3qyurCtLJRORkZHs2LEDT09PbG1tadu2LZaWlh88JiYmhpgY7W5FjSYBhUImBAkhhBBCCJGRdPqNu2jRorx6lTje9OnTpxQrVoxBgwZx9OhRJkyYQNGiRXn06MOTmaZPn46pqanWIzz6w0vACSGEEEIIIf5/Ok0mPDw8kpYJHDVqFHZ2djx58oTLly/z5MkTSpQowZgxYz5Yx6hRowgNDdV65DS0+uAxQgghhBBCvE9CFn5kNVlmmNOFCxdYvnw5pqaJS5TlyJGDSZMm0abNhyfAGBgYYGCgPSFThjgJIYQQQgiR8XSeTPx7I6jo6GhsbW219tnb2xMQkD5368xIfQd1pcF3dXEt4Ex0dDRXL99k2sR5eHk+1nVoIgNUqVqeAQO7U6p0MWxtc9O2dQ/++vOorsPKdB37tqPfmJ78tmoH88Yv1nU4GabT4A50GtxBa5uPpw8danbWUUSJ4uPjWbZmC38eOU5gUDDWVhY0a1iXHp3aJr2vjpkylz8OHtM6rmrFslr3hggNC2favGWcPHcJPT096tSsyqgBPTE21l5V58qN24ycPJu/92xK1bkDXwUzf9lazl++TnhEJGVLFWP0oF7ky2ufdN6lqzdx/vJ1fP0CMDc3pXb1yvTr1oGcOUwy8k+nxah8MSy7/oDhV66oc1vytNcvRBy7oFVG3yUvNsN+xrhCcRRKJTGePjzrO5U436z/+ZRa2fV9Lbt8fttVLESZHo2wLuFMjtzm/NV1Pt6HryXtd6lfjmI/fYN1cSeMzHOy9dvRBLrp5l5A4vOj82Tim2++QaVSERYWxv379ylWrFjSvidPnnx0AnZWUKlKeTas3srNG3dQqVSMHDeA33avomalJryOev3xCsRnxcTEmLt33Nm08Xd+27Zc1+HoRNGShWn+UxMe3PPUdSiZ4pHHI4a0HZ70PD4uXofRJFqz+Xe27/2LqWOH4Oqcj3seDxg7dT45cpjQvmXTpHLVKpVjyuhBSc/VarVWPSMmzSIg8BWrFkwjLi6OsdPmM3HWImZNHKFV7sSZi9SsWjFV59ZoNAwYORmVSsWimePJYWzCxu276TpgNH9sWYGxkSH+gUH4B75iaN+u5HdyxNfPn8mzlxAQGMT8qWMz8C+nTc/IkBiPR4TuPILDsnHJ9qsd85Bv62xCdx4hYNFmEiKiMHDNhyZGN/dJySjZ9X0tu3x+q40MCHT3wW3HaRqtGphsv8rYgBeX7/Nw/yW+md018wPMguSmdamn02RiwoQJWs9z5NC+I+r+/fupXr16ZoaUJu1b9tB6PrD3GO54nqVEqaJcOn/tPUeJz9XRI6c4euSUrsPQGSNjI35ZOp6pQ2fRZWBHXYeTKeLj43kVkLVuzHTzrju1qleiRpUKANjb5ubA0VPccdO+w7a+Wo2VpUWKdXg99uHsxatsW72QYkUKAjB6UC96DR3P0D5dsbF++2POibMXGTO4d6rO/eTpc27d82DvpuW45s8HwLihfanZ+EcOHD1Jiyb1KZDfiQXT3iYNjg529O/ekZGTZxEXF49KpUyPP9NHRZ6+SuTpq+/dbz2oI5GnruI/a23Stlifl5kRWqbKru9r2eXz+8nJ2zw5+f67kt/ffQ6AnA4y51R8uiyVTPzX7NmzMymS9JUrV04AQoJDdRyJEOlvxPRBnPv7ApfPXMs2yYS9sz07r27jTUws9667sWr6Gvxf+Os0plLFirBz30Ee+zzDydEBj4feXL99j+H9ummVu3LjNl83akOunDmoULYk/bt3xMw0FwC37rqTK2eOpEQCoFK50ujpKbjt5kGdGlUB8PR+wqvgECqWLZmqc7+JjQVAX/9tL4ienh5qfTU3bt+jRZP6KbYpPCKSHCbGmZZIfJRCQY6a5Xm1ehd51/6CYVEXYp/5Ebh8R7KhUOLLIJ/fQnw6nQ9z+tIoFAomTR/B5YvXue+ePYaAiOyjXtNvKFy8IB0adNd1KJnG7YY7MwbN5qn3UyxtLOk46CcW7Z7Pz9905XWk7oZBdP2pFZFRUTT+sTtKPT3iExLo370j331bO6lM1UplqVOjKvZ2uXn63JeFK9bTc8g4tqyYh1KpJDAoGAszU616VSolpjlzEvjqbU/M8TMXqFqxbNIQqY+d2zlfXmxz27BwxXrGD+uHsZEhG7fvwc8/kICgVym2JzgklBXrt9KiSYP0/lOlmdLSDGUOYyy7tyRg/kb8Z68jR/WyOCwdg89PI4m6fFfXIYp0JJ/f4l0JMsop1SSZSGfT5oylUJECfN/gJ12HIkS6ym1nw5Bf+tOn9WDefGHjxT/k8okrSf/v7f4I9xvubLv4G7Ua1+DAtkM6i+vQ8dP8eeQEMycOx9U5Hx4PvZm5cAU2VhY0bVgXgIZ1aiaVL+jiTEEXZxq06syVG7epVK50qs914uxF2v7QONXnVqtULJg2lvHTF1C1QSuUSj0qlStN9Url0KRQf0RkJL2HTcDF2ZHeXdqn9U+S7hR6id8mwv++yKv1ewGIcffGqEwRzNo2lGTiCyOf30KkjSQT6WjKrDHU+bYGzRt2xPeFn67DESJdFS5RCEtrCzYfWZ20TaVSUbpSSVr93Jwq+b4hISErroCdviLCInnm/Qx7J3udxjF36Rq6tm+VlDAUdHHG96U/qzftSEom/iuvvS3mZrnweeZLpXKlsbI051WI9nCOuLh4QsPDsbIwByAg8BXuD7yS5kek9txfFS7Arg1LCY+IJDY2FgtzM9p2G8hXhQtonS8yMooeg8dhYmzEwmnjUKuyzsdSXHAYmtg4Yjy1V7WJ8XqKcdmvdBSVyAjy+S1E2mWdd+3P3JRZY6jf6BtaNu7EU5/nug5HiHR35cxVWtfUXiJ1/IJRPPH0YcOSLdkikQAwMjbEzsmWI7uDdBpHdHRM0i/n/9LT0yNBk9Jv/4le+gcQEhqO9T8TsksWK0JYeAT3PB4mfcm/dO0mCQkaShQtDMDJcxcpVbwIpv+MJf/Uc/+7zOuTp8+55/GQvl3f/uobERlJj0FjUeurWTxzAgYG+p/yJ8h4sXG8vvMAA2cHrc0GTvbE6njOjEg/8vktUpIgqzmlmiQT6WDanHE0a9GQzj/2IyIiCmubxNUQwsPCiY6O0XF0Ir2ZmBiT3yVf0nMnp7wUL1GE4FehPHv2QoeRZayoyNd43X+ktS06KpqQ4NBk278kvcZ25/yxi/g988MytyU/D+lIQnwCf+89odO4alatyKoN27DNbYOrcz7cH3iycftuvm9UD4CoqNcsW7uFujWrYmVpwdPnL5i3bC2ODnZUrVgGABcnR6pVKsfEmQsZP6wfsXFxTJv/Kw3q1EhayenE2UvUqlbpk84NcPj4GczNTLHNbc1D78fMWLCc2tUrU7ViWSAxkeg+cAyvY2JYOH4YkZFRREZGAWBuZopSmTmTsBXGhujns0t6ru+QG4Mi+YkPCSfON4BXq3dhv2AkUVfuEHnxNjm+LkuO2hV50n7EB2r9/GTX97Xs8vmtNjbA1Cl30vNcea2xKupIdEgkES+CMDAzIaedJSa5E3skzV0S7/sVFRBKVIBMRhcfptBoPvAz1mfK3jxzu5+fB99Lcfug3mPYsXVvpsXhFxmSaefKSozVBh8vlI6qVa/IgUNbk23fsnknvXoMT+GIjFEwl26H2QCs2LWI+/ceZupN63IoM/f1Hr90DCUqFieXeS5CX4Vy5/JdVs9ay4snvpkax9GbK7WeR0ZGsXjVRv4+fYFXwSFYW1nQsG5Nev38I2q1muiYGPqPnIzHAy/CIiKxsbKgSoUy9O3WIWkIEyTePG7qvGWcPHsJPT0FdWpWZfTAXhgbGxH1OprqDVuzZ9OvODrYpfrcAJt//4N1v+0k6FUI1pYWNKn/DT1/bpu0//L123Tul/IX8sM712Nvm/jFx7Ny33T9O/6XcYXi5NsyM9n2kN1H8R0xHwDTFnWx6tEKVR4r3jx6RsDCLUT8fTFD46r4wiND6/+vrPK+llPf6OOF0lFW+fwemSP1c5jSwr5SEZr/PibZdvffT3Ns8EoKt6xO3Xk9ku2/NG83l+fvzrC4+j3dnGF1/7/+yPOjrkN4r6Yvf9N1CFokmfiCSDKRvWSFZEIXMjuZyCr+m0xkyjlPnmPxqg3s25L55/5XRicTWVVmJxNZRWYnE1lFRicTWVVWTib2ZuFkolkWSyb0dB2AEEKIrMnYyJDBvTrrOgwhhBBZmMyZEEIIkaJ/5zcIIYQQ7yPJhBBCCCGEEO/IHusTpg8Z5iSEEEIIIYRIE0kmhBBCCCGEEGkiw5yEEEIIIYR4R4JCblqXWtIzIYQQQgghhEgTSSaEEEIIIYQQaSLDnIQQQgghhHjHF3dH5wwkPRNCCCGEEEKINJFkQgghhBBCCJEmMsxJCCGEEEKId8hN61JPeiaEEEIIIYQQaSLJhBBCCCGEECJNZJiTEEIIIYQQ70iQe9almvRMCCGEEEIIIdJEkgkhhBBCCCFEmsgwJyGEEEIIId6RgIxzSi3pmRBCCCGEEEKkiSQTQgghhBBCiDSRYU5CCCGEEEK8Q6PrAD4j0jMhhBBCCCGESBNJJoQQQgghhBBpIsOchBBCCCGEeIfctC71pGdCCCGEEEIIkSZfZM9EmZzOug5BJ+6rXuo6BJ2IjHut6xB04maQt65D0InBdl/rOgSdcCrQWNch6MTjh/t1HYJORNlV13UIOpFT30jXIejEIL8Tug5BJ/rpOgCRLr7IZEIIIYQQQoi0StB1AJ8RGeYkhBBCCCGESBNJJoQQQgghhBBpIsOchBBCCCGEeIfctC71pGdCCCGEEEIIkSaSTAghhBBCCCHSRIY5CSGEEEII8Q65aV3qSc+EEEIIIYQQIk0kmRBCCCGEEEKkiQxzEkIIIYQQ4h1y07rUk54JIYQQQgghRJpIMiGEEEIIIYRIExnmJIQQQgghxDtkmFPqSc+EEEIIIYQQIk0kmRBCCCGEEEKkiQxzEkIIIYQQ4h0auWldqknPhBBCCCGEECJNJJkQQgghhBBCpIkMcxJCCCGEEOIdsppT6knPhBBCCCGEECJNJJkQQgghhBBCpIkMcxJCCCGEEOIdMswp9aRnQgghhBBCCJEmkkwIIYQQQggh0kSSifdo2KERq8+tYdeD3cz5Yy4FShb8YHmTXCb0/KUnG65uZPfDPSw/uYKytcol7a/RrCZrL65j651tdBnXVetYGwcblp9cgVEOowxpy6do17klx6/t487Tc/x+aD0lSn/13rL1GtVi19GNXPU8wc3HZ/jjxBaatmyoVaZz7/ZccDvCBbcjdO7VTmtfiTJfsfvYJpRKZYa05VN07NqWi7eO4OV7nf1Ht1KqTPH3lv2xQwt2H9jIvUfnuffoPNv2rE5WvkffTtx6cJpbD07To09HrX2lyxbn4IkdWaLd2VXln+oy8uwipt7fQN+9v5C3pMt7y+qplNTp35wRpxYw9f4GBh6cQcEaJbXKlG5aldHnlzDx1iq+G9tea5+5gxXDjs/DIAv8+/7Sr/PIyChmLFhO3eYdKVurKe16DOaO+/2k/cWqNkjxsXbLzvfWuXTN5mTlG7ftplVm1qKVVKnfkm++/4k/Dx/X2nf4+Bn6DJ+Qvg0VH/SlX+cic2iy8COrkTkTKajWuDpdx3Vl6eilPLh5nyZdmjJ582R61uxBaFBosvIqtYpftvxCSGAoM3pOJ+hlEDb2NkSERQKQyzwX/Wb1Y8GQBfg9ecn49RO4ff4WV/6+AkCvKb3ZMGM9ryNeZ2o7/6ths7qMmjyI8cOmc+vaXTr1aMuaHYv5tvIPvAoMTlY+JDiM5fPX4v3wMW9iY6lVrzrTF40nKPAVZ09cpFBRVwaM6EmPdgNRKBSs2DKfsycv8sDdC6VSyeQ5oxk3eCrx8fE6aO1bTb6vz4Qpwxk5eBI3rt2ha8+f2LJrBV+X/46gwFfJyleuVp4/dh3g6qWbRMfE0GdAF37bvZLalZvy0tefIl8VZNiovnRs0weFAtZvW8apE+fxcHuIUqlkxrwJDB84Ueftzq5KfleJxmN/YvfYNfjc8KR65wZ02TiS2bWHEBkUlqz8t0NbUaZZNXaNXIW/1wsK1ihBxxWDWfrDBF7ce4yxeU5azOzOjqG/EuTjT+e1w/E6fw/34zcA+P6XzhycuZUYHf/7zg7X+fgZC/H0fsz08UOxsbJk/+HjdBswmj+2rCC3tRUn923RKn/m4lXGT19A3ZpVP1ivq3M+Vi+clvT83S+OJ89e5K+jJ1k5fyo+z14wbtp8qlYsi7mZKeERkSxauYHVC6alVK3IANnhOhciq5GeiRQ069qMw1sP8/fvx3j68CnLRi0l5nUMdVvXTbF8ndZ1yWGWk6ndpuB+1R3/Z/7cvXSXx+6PAMjtmIeosCjO7j/Dw9sPuXPhNg6ueQH4usnXxMXFceHQhUxr3/v83LMdOzbvZffW/Xg9eMT4odOJfh1Nix+bpFj+8vlrHD1wEq+Hj3n6+DkbV27jvpsnZSuWAiB/ASfuuz3k4tmrXDhzhftunuQv4ARA174/ceXCde7cdMuk1r1ft94d+W3jTnb8tpeH970YOXgSr6OiadO+eYrl+3UfwYY127h31wOvh48Y2n88ego9qn1dCQDXAs6433vAuTOXOHv6Eu73HuBawBmAXv1/5uL5q9y6cTfT2ie0Ve/aiEvbjnP191P4ez5n95g1xL5+Q/lWNVMsX/b76hxfuhePkzd59dSfi5uP4XHiBl93bQSApaMN0eFR3PrzIs9ue+N10Q0bV3sASjWpQnxcPHcPX8ms5r3Xl36dR8fEcOzUWQb36UK5UsVxdLCjT5f2ODrYsX3PXwBYWVpoPU6cuUiFMiXIa2/7wbqVSqXWceZmpkn7vJ88pXzp4hQrUpCGdWtiYmLMM9+XAMxbtobWzRphm8cm4xoutHzp17kQWZEkE/+hUqtwLe7KrbM3k7ZpNBpunr1JoTKFUzymYp2KeFzzoOeUXmy8toklR5fSsk9L9PQS/7wvHj/HwMiA/F/lJ4dpDgqULMhj98eYmJrQbmh7VoxbnhlN+yC1WsVXJQtz/tSlpG0ajYbzpy9TqlyJVNVRuXp5nF3yceVC4i+yD9w8cXJxxNY+N3YOeXByceShuxd5nexp3rYxC6b9miFt+RRqtZoSpYpy5uTbZE6j0XD21EXKli/5gSPfMjI2RKVWERKS2Gvl7vYQZ1cn7Bxssc9rS37XfHi4e5LPKS+tf/yeWVMXZUhbxMcp1Ursiznjee7th79Go+HhubvkK1Mg5WP0VcTFxGpti42Oxal8IQACH71EbaiP3VdOGJma4FAiP74ePhjlMqHe4JbsHb8u4xqUStnhOo+Piyc+PgEDfbXWdgMDfa7fvpesfOCrYE6fv0zz7779aN0+z55Tq0k76rf8mRETZ+L70j9pXyHX/NzzeEhoWDj3PB4SExODo70d12/dxe2+J+1apvxjjEh/2eE6F5knQZF1H1mNDHP6j1wWuVCqlAQHhmhtDwkMwcHFIcVj8jjmpkSVEpzce5JJnSZi62RHrym9UKpVbFuwlcjQSOYPns+g+YPRN9Tn+K7j3Dh9nX6z+vPXhj/JnTc3Y9eMQ6VW8dv83zh/4FwmtFSbuYUZKpWKwADtbuBA/1fkd3V673E5cppw5s5B9PX1SYiPZ+KImUkJidfDx8ybuox1O5cBMHfKUrwePmb9zqXMnrSIarUr029Yd+Li4pgyZg5X/0lCMpOF5b/tDtLaHhAQhMs/vz59zJiJQ/B76Z/0Aeb5wJuZvyxg2+5VAMyYvADPB95s27OaKRPmUrN2NQaP7E1cbBzjR03n0vlr6dso8V4m5on/vsMDtYcrRgSEYuNil+IxD07fpnrXRjy67EHQEz9cqxajWP3yST8WvA6LZPvQX2k9txdqQ32u7z7Dg9O3aTGzO+c3HsEirw2dVg9DqVJydMFO7hy8nOHt/K/scJ2bmBhTslgRlq/fSv58jlhamHHg2Clu3fXAMYWeh30Hj2FsbESdGh8e4lSiaCGmjBmCk6MDgUGvWLZ2Cx16D2Pvpl8xMTGmasWyfPdtbdp0HYChgQFTxw7B2MiQX+YsZcqYwWzf8xe/7dyHmZkpE4f3xzV/voz6E2R72eE6FyIrkmQiHSj09AgNCmHpyCUkJCTgdccLy9yWNO/ZnG0LtgJw8fAFLh5++2tJsYrFcC7ixMrxK1hxZiVz+s4mOCCYufvmce/S3RTnZmRFkRFRNK31IyYmxlSuXp5Rkwfx9PFzLv/zhrptwy62bdiVVP771o2IjIjixtU7HL6wix/qdSCPrQ3zV06jdtkmxL6Jfd+psqQ+A7vSpHkDWjbuREzMm6Ttm9btYNO6HUnPW7ZpSkREJNeu3OL0lT9pVLs1tnZ5WLZ6DpVL1ePNZ9bu7GTfpA38MKMbQ/+ei0aj4dUTP67+fkprWNS9w1e5d/hq0vP8FYtgW9iRPyasZ8SpBfzWfzHhASH03TsF78seKc7NyMo+l+t8+rihjJ8+n9rN2qNU6lGkoCsN6tTA7b5nsrJ7/jzCd/VqYWCg/8E6q1cun/T/hVydKV60EPV+6Mih42f4oXFir0afLu3p0+XtxPtla7dQqVwpVCoVKzZsY8/GZZw6f5nRU+awY+3idGqtSG+fy3UuRFYjycR/hL0KIz4uHnMrM63tZlZmBAckn4QMEOz/iri4eBIS3t7i5JnnUyxsLFCpVcTFxmmVV+mr6DW1F/MGzsPWyRalUsndS4nDLl48ek7B0oW4cixzf70MfhVCXFwcVtYWWtutbCwI8A96z1GJXcg+j54B4H73AS4FnekxsFNSMvEucwtT+g7txo9NulOyTDEee/nwxPspT7yfolapcHZx5IG7V/o27CNeBf3bbkut7dbWlgT4B37w2B59O9FnYBfaNOuK+70H7y1nbmHGoBG9+KFRR0qXK4G35xMeefvwyNsHtVpFflcnPNwepkt7xIdFBif++85pZaq1PYe1KeEBISkf8yqcjd3noTJQY2yWgzC/YBqMbEuQj3+K5ZX6Kpr90pntg5Zi6ZQHPaUe3pfcAQh85ItjKVfc/76eru36mOxynTs62LF+6WyiXkcTGRmFtZUFQ8ZNx8Euj1a5azfv8sjnGbMnj/rkc+TKmYN8ee3xefYixf3eT57y5+Hj7Fy3hN1/HaFcqWJYmJvxbe2vGTdtPpGRUZiYGKepfeLDsst1LjKH3LQu9WTOxH/ExcbheceTElXfjq9UKBSUrFqS+9c9UjzG7ao7tvlsUSjeDmSzy29PkF9QskQCoHW/Nlw7eR2vu17oKfVQqt6uDKJUqVDqZf7LEhsbx71bHlT+ukLSNoVCQeXq5bl59Xaq61Ho6aGvn/IvfaN/GcL6FVvx8/VHqdRDpX6byypVSp0srRcbG8vtm25Uq1EpaZtCoaDa1xW5duXWe4/r1b8zA4f1pH2LHty+mXw89rsmTRvBqmUb8X3hh1JPD/V/260nSwpmlvjYeJ7ffYRrlWJJ2xQKBa5VvuLJ9Q9/AYiLiSXMLxg9lZLi9SvgdvRqiuW+6fs9D07d4vm9x+gp9dB799+3WomeUhf/vrPXdW5sZIi1lQWhYeGcv3yN2tUrae3f/edhihYqQOEC+T+57qio1zx97ou1lUWyfRqNhsmzFjG8XzeMjY1IiE8gNi7xMyDun//GJ8hXlIyS3a5zIbIK6ZlIwd7Vexk0dxCedx7y4OYDmnZpiqGxIcd2HANg0PzBBL0MYuPMDQAc3HSA7zp+R7eJ3flz/X7snO1o2aclf67bn6zuvAXyUr1xdQY06A/AM89naBISqNu6LsEBwTi4OPDglm5+1Vi3fAszF0/k7k03bl+/R8ceP2JkbMSurYntmLVkEn4v/Zk7ZSkAPQZ04s5Nd54+foa+vpoadarStGVDJg6fnqzuKjUq4uTiyPC+ieut377hRn7XfHz9TRVs7XKTEJ+At+eTzGvsO1Yt28D8ZdO4feMeN67foVuvnzAyMWL7lj0ALPx1Gr6+/syYvACA3gO6MHRUX/p2G85TnxdY21gBiWvcR0VGadVdvWZlnF2cGNBrNAC3btzFpYAztepUw87eloT4BLw8H2VeYwVnVv9Fq7m9eHbHm6c3PanWpQH6xgZc/f0UAK3n9iLUL5hDs7YBkLeUC6a5LXjh9oRcecypO7AFCj0FJ1ck//dt42pPye8qs6BR4i/e/p7P0SRoKN+qJuEBoVi72PH0Vub2vv0rO1zn5y5dQ6PR4OTogM+zF8xdugZnRweaNaqXVCYiMpIjJ84wtG+3FOvo0n8k33xdhR9bJE6cnr1kFTWrVsQuT278A4NYunozSqUeDevUSHbsrv2HMDczpWa1xC+zpUsUZdnazdy6686Zi1dxcXIkV84cGdBy8a/scJ0LkdVIMpGCs/vPYGphSrvB7TG3NsfbzZsJP40n5J9J2dZ21mje+XUp0DeQ8T+Np+v4riw+vIQgvyD2r93Hrl93Jau774y+rPllNTGvYwB4E/OGBUMW0POXXqj11awYv5xXfu8fVpSRDuw9ioWlOf1H9MTaxhL3uw/o0rofQf9MyrZ1yEOC5m27jYyNmDhrBHlsbYiOjsH74WOG9R7Hgb1Hteo1MDRg/IzhDOo2Co0m8XYrfr7+/DJ6NtMXjedNTCwj+k0gJjom8xr7jn17DmFhZcHQ0X2xtrHi3h0P2rfokTSJz87BloSEt7eJ6dC5NQYG+qzauECrnrkzljJv5rKk54aGBkydNYZenYcmtdv3hR/jRkxj3pKpvHnzhoG9RxOto3ZnV7f+vIiJRS7qDWpBTmszXrg/YU3HGUT8MynbzN4q6fUCUBvo8+3QVlg42vAmMgaPEzfYPmgZ0WFRyer+YXpX/pyyidh//n3HxcSyY+ivNJv8MyoDNX+MX0+YX8rDJTNadrjOwyMiWbB8HX4BgZjmykndGtXo36MjatXbj7qDx06h0UDDujVTrOPpc1+CQ9/OafHzD2T4hJmEhIVhYWZK6RJfsWXFfCzMzbSOC3wVzMoN29i8fF7StuJFC9GxTXN6D5uAhbkZ08YOSdf2iuSyw3UuMof0IaaeQvPup+YXorHjd7oOQSfuv36p6xB0IjJOtzcD0xW/yBBdh6ATg+2+1nUIOrElNPXDDb8kjx8m7wHKDozsqus6BJ3IbWKm6xB0Iru+n8e9ea7rEN5rrmP7jxfSkSE+m3UdghaZMyGEEEIIIYRIE50mE9evX+fRo7fjCzdt2kTVqlXJmzcv1apVY9u2bR+tIyYmhrCwMK1HvEZuay+EEEIIIdJGk4UfWY1Ok4mff/4ZL6/EyYirV6+mR48elCtXjjFjxlC+fHm6devG2rVrP1jH9OnTMTU11Xp4hulmgqMQQgghhBDZiU4nYD98+JACBQoAsGzZMhYuXEi3bm9X2ChfvjxTp06lc+fO761j1KhRDB48WGtbm69aZ0zAQgghhBBCiCQ6TSaMjY0JDAwkX758PH/+nAoVKmjtr1ixotYwqJQYGBhgYGCgtU2pkHWehRBCCCFE2iQoPl5GJNJpMtGgQQN+/fVXVq9eTY0aNdi5cyclS769WdyOHTtwdXXVYYSpZ5Hbkk6jOlG2VlkMjAzwfezLwqEL8LztqevQMkzbTj/QtlMLHBxtAXjo4c3Suas5/fd5HUeWsfoO6kqD7+riWsCZ6Ohorl6+ybSJ8/DyfKzr0EQGMTAxpN6QVhSrV44cVqY8v/eYfZM28Oy2t65DyzBZ9TqPjIxi8aqN/H36Aq+CQyhc0IWRA3tQvEghAJau2cyhY6d46R+AWq2maCFX+nfvSImvCier682bN7TtNoj7nt7sXLeEwgVdtPZfuXGbkZNn8/eeTR89L8CYKXP54+AxrTqqVizLinlTkp4/9nnG3KVruHHHjdjYWAq6OtOvawcqlC2JyHxZ9ToX4nOi02Ri5syZVK1alRo1alCuXDnmzp3LyZMnKVKkCPfv3+fixYvs2bNHlyGmiompCbN2z+LOhdtM7DCRsFeh2DnZEREaoevQMtTLF/7MnbKEx94+KFDwfZvvWLZxLs1qt8Pz/pf7JatSlfJsWL2VmzfuoFKpGDluAL/tXkXNSk14HZU9l6n90rWY2Z3cBfOybfAywvyCKfN9NbptHsPcukN1dt+IjJZVr/PxMxbi6f2Y6eOHYmNlyf7Dx+k2YDR/bFlBbmsrnPLaM3pwbxzs8hAT84aN2/fQfdAYDmxfk+zeEHOXrcXGyoL7nim/X504c5GaVSum6rz/qlapHFNGD0p6rlartersM3wijg52rFk0A0MDfTbt2Euf4RM4uGMtVpbJ76otMlZWvc6F+JzodAK2nZ0dN27coHLlyhw6dAiNRsPly5c5cuQIDg4OnDt3joYNG+oyxFRp0asFgb6BLBy6kIe3HuD31I8bZ27w8smXfd+HE0fOcOrYOZ54P+Wxtw/zpy0jKjKKUuWK6zq0DNW+ZQ92bN3LAw8v3O7eZ2DvMTjktaNEqaK6Dk1kAJWBmmL1K3Bg+m88uuxB0BM/ji7YRdCTl1RuX1fX4WWYrHidR8fEcOzUWQb36UK5UsVxdLCjT5f2ODrYsX3PXwA0qleLyuVLk9feFtf8+RjevxsRkVE88NIeMnvmwhXOX77O0L5d33u+E2cvUqtapVSd91/6ajVWlhZJD9NcOZP2BYeE8uTpc7q2b0UhV2fy5bVnUM+feR0dw0PvJ+n4lxKplRWvc5E1JGThR1aj8ztgm5mZMWPGDGbMmKHrUNKsQt2K3Dh1nRG/jqRYxWIEvQziwKYDHNl6WNehZRo9PT0aNKmDsbERN65kr5tr5frny0JIcKiOIxEZQalSolQpiYt5o7U9NvoNTuULveeoL09WuM7j4+KJj0/AQF/7134DA32u376XrHxsbCy//3GQnDlMKOSaP2l74KtgJs5cyMLp4zE0NEzxXJ7eT3gVHELFsiV58yY21ee9cuM2XzdqQ66cOahQtiT9u3fEzDQXAGamuXB2dGDfob8pUsgVfbWaHX8cwMLcjKKFPo8hvV+6rHCdC/G50Xky8SXIkzcPDdo3ZO/qvfy+ZAcFShag+6TuxMXGcnzncV2Hl6EKFnFh+8F1GBjoExX5mj6dhuH14MOT5r8kCoWCSdNHcPnide67f7nzY7KzmMhoHl97wDf9m+Pv+YLwwBBKNalKvjIFCXr8Zfc+/iurXOcmJsaULFaE5eu3kj+fI5YWZhw4dopbdz1wtLdNKnfy3CWGTZhBdHQM1pYWrFwwFXMzUwA0Gg1jp86jVbNGFCtSkOe+fime6/iZC1StWBa1Wo1arU7VeatWKkudGlWxt8vN0+e+LFyxnp5DxrFlxTyUSiUKhYJVC6fRf+QvVKzbHD09BRZmZqyY94tWD4bQjaxynQvxuZFkIh0o9BR43vZk06yNAHjf8yZfoXw0aNfwi08mHnk+oWmtH8mZMwf1m3zDzMUTade0e7ZJKKbNGUuhIgX4vsFPug5FZKBtg5bSanZPxl5eRnxcPM/vPuLmvvPYF3fWdWiZIitd59PHDWX89PnUbtYepVKPIgVdaVCnBm733375q1CmJLvWLyU4JJSd+w8xdNx0flu1AEtzM7bs3EdkVBRdf2r1wfOcOHuRtj80/qTzNqxTM+n/C7o4U9DFmQatOnPlxm0qlSuNRqNh6txlWJqbsmHZbAwNDNi1/xB9h09k2+pFWFvJnAldykrXudC9rHhzuKxKp3MmvhTB/sE8feijte3pw6dY21vrKKLMExsbh8+jZ9y77cHcKUvxuPeAjt3b6jqsTDFl1hjqfFuDlo1/xvdFyr9uii/DKx9/lreezJginZhWuS9Lmo1DqVbyysdf16FluKx2nTs62LF+6WwuH9vDsd2b2LZ6IXFx8TjY5UkqY2xkiKODHSWLFeGXUYNQKpXs3p847PTytVvcuutBmVpNKPl1Ixq2TryPUeuu/Rn9yxwAAgJf4f7AixpVKnzSef8rr70t5ma58HnmC8Clazc5df4ysyePpEyJryhayJVxQ/tiYGCQbBUokbmy2nUuRHo5ffo0jRs3xs7ODoVCwd69e7X2azQaxo8fj62tLUZGRtSpU4eHDx9+0jkkmUgH7lfdsHdx0Npmn98e/2df/heN/1Lo6aFvoP54wc/clFljqN/oG1o16cxTn+e6DkdkktjXMYQHhGCUy4SCX5fA7ehVXYeUobLydW5sZIi1lQWhYeGcv3yN2tUrvbdsQkICb2JjARg1sCe7Nixl5/rEx7LZkwGYM2kU/Xt0BODkuYuUKl4kxaFHn3Lel/4BhISGY/3PKk3R0TEA6Cm0P3r1FAoSErLitMrsIStf50L8vyIjIylZsiRLly5Ncf+sWbNYtGgRy5cv59KlS5iYmPDtt98SHR2d6nPIMKd08MfqP5i1ZzYt+7Tk7J9nKViqIN/+WJ8lI5foOrQMNWRsH079fR7fZy8xyWFM4x/qU7FqWTq36qfr0DLUtDnjaNaiIZ1/7EdERBTWNonLQoaHhSd9WRBfloJflwCFggCvF1g55aHR6B/x93rBld9P6Tq0DJNVr/Nzl66h0WhwcnTA59kL5i5dg7OjA80a1SPqdTQrN2yjVrWKWFtZEBwSxtbd+/EPDOLbWtUBsM1jo1WfsZERkNiLkMcmsTf5xNlL1KpWKdXnBYiKes2ytVuoW7MqVpYWPH3+gnnL1uLoYEfVimUAKFmsCLly5mD0lLn0/PlHDA302bnvEM98/fi6ivZNW0XmyKrXudC9hC9koFODBg1o0KBBivs0Gg0LFixg7NixNG3aFICNGzeSO3du9u7dS5s2bVJ1Dkkm0sHD2w+Z1n0qHUZ0pM2Atvg99WPVpFWc2ntS16FlKAsrC2YtmYRNbivCwyK47/aQzq36cf7UJV2HlqE6dkn8x7Xrrw1a2wf1HsOOrXt1EJHIaIY5jWkwvA2meSyICo3gzsHLHJ6znYS4eF2HlmGy6nUeHhHJguXr8AsIxDRXTurWqEb/Hh1Rq1QkxCfw6MlT9h08RnBoKGa5clGsSEE2LJuNa/58qao/6nU0l67eZOSAHqk+L4CeUo8HXo/Yd/AYYRGR2FhZUKVCGfp264C+vj4A5mamLJ/7C4tWbqBL/5HExcXh6pyPxTPGU7hA/mSxiIyXVa9zIT4kJiaGmBjtZNfAwAADA4NPqufRo0e8fPmSOnXqJG0zNTWlYsWKXLhwIdXJhEKj0XwZqdc7Gjt+p+sQdOL+6+yxssx/RcZlzxsL+UWG6DoEnRhs97WuQ9CJLaHZa8nlfz1+uD9Tz3f05DkWr9rAvi0rM/W8/2VkV12n59eV3CZmug5BJ7Lr+3ncm6w7rGxqvna6DuG9Yn8uwKRJk7S2TZgwgYkTJ37wOIVCwZ49e2jWrBkA58+fp2rVqrx48QJb27cr07Vq1QqFQsH27dtTFY/0TAghhBD/MDYyZHCvzroOQwihY1l5FtOoUaMYPHiw1rZP7ZVIT5JMCCGEEP+oWrGsrkMQQogPSsuQppTkyZO4Gp2fn59Wz4Sfnx+lSpVKdT2ympMQQgghhBDZjLOzM3ny5OHvv/9O2hYWFsalS5eoXLlyquuRngkhhBBCCCHe8aVMKI6IiMDT8+3NNR89esTNmzexsLDA0dGRgQMHMmXKFAoUKICzszPjxo3Dzs4uaV5FakgyIYQQQgghxBfo6tWr1KpVK+n5v3MtOnbsyPr16xk+fDiRkZF0796dkJAQqlWrxqFDhzA0NEz1OSSZEEIIIYQQ4gtUs2ZNPrRwq0KhYPLkyUyePDnN55BkQgghhBBCiHdk5dWcshqZgC2EEEIIIYRIE0kmhBBCCCGEEGkiw5yEEEIIIYR4R4JC1xF8PqRnQgghhBBCCJEmkkwIIYQQQggh0kSGOQkhhBBCCPGOhC/mtnUZT3omhBBCCCGEEGkiyYQQQgghhBAiTWSYkxBCCCGEEO+QQU6pJz0TQgghhBBCiDSRZEIIIYQQQgiRJjLMSQghhBBCiHck6DqAz4j0TAghhBBCCCHSRJIJIYQQQgghRJrIMCchhBBCCCHeITetSz3pmRBCCCGEEEKkiSQTQgghhBBCiDSRYU5CCCGEEEK8QwY5pd4XmUxcD3+k6xB0okxOZ12HoBP1NGa6DkEnNhg+0XUIOuGeEK7rEHTCLzJE1yHohJFddV2HoBOvX5zRdQg6Ia+3EJ8fGeYkhBBCCCGESJMvsmdCCCGEEEKItJKb1qWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iE3rUs96ZkQQgghhBBCpIkkE0IIIYQQQog0kWFOQgghhBBCvEMGOaWe9EwIIYQQQggh0kSSCSGEEEIIIUSayDAnIYQQQggh3iE3rUs96ZkQQgghhBBCpIkkE0IIIYQQQog0kWFOQgghhBBCvEMj6zmlmvRMCCGEEEIIIdJEkgkhhBBCCCFEmsgwJyGEEEIIId4hqzmlnvRMCCGEEEIIIdJEkgkhhBBCCCFEmsgwJyGEEEIIId6RIKs5pZr0TAghhBBCCCHSRJIJIYQQQgghRJrIMCchhBBCCCHeIYOcUk96JoQQQgghhBBpIsnEe3Ts2paLt47g5Xud/Ue3UqpM8feW/bFDC3Yf2Mi9R+e59+g82/asTla+R99O3HpwmlsPTtOjT0etfaXLFufgiR0olcoMacunaNihEavPrWHXg93M+WMuBUoW/GB5k1wm9PylJxuubmT3wz0sP7mCsrXKJe2v0awmay+uY+udbXQZ11XrWBsHG5afXIFRDqMMaUtq2FUsxHdrB/Pz1cX0e7qZ/N+W/WB5Yxsz6i3uTftTs+n7ZCPVJ7RPViZv9WK0PzWbHm6rqLugJ3rqt6+rfk4j2p+aTU57y3RvS1q07PQ9+y7v4NyjY6z/awVflSqSquPqNf2Gq75nmLNumtb29j3bcOTOPo7c2Ue7Hq219n1VuiibDq+W61yIdBYZGcWMBcup27wjZWs1pV2Pwdxxv59i2UmzFlOsagM2bd/z0Xq37tpPvR86UqZWE9p2G8gdN+06Zy1aSZX6Lfnm+5/48/BxrX2Hj5+hz/AJaW+USLVte/7k+w69qFi3ORXrNqdd90GcuXDlveV37jtIh15DqVK/JVXqt6TrgFHJXtt1v+3k60Zt+LpRG9Zv3aW17/Y9D1p17kdcXHyGtEd8fiSZSEGT7+szYcpw5s1cRv2aLXG7e58tu1ZgaWWRYvnK1crzx64DtGrcmSb12vHi+Ut+272SPLY2ABT5qiDDRvWld5dh9Ok6jGFjmu8oGwAAdNZJREFU+lO4aAEAlEolM+ZNYOTgycTH6/YfZrXG1ek6ritbF2xlYKMBPHJ/xOTNkzG1NE2xvEqt4pctv2DjkJsZPafTs1YPloxYTNDLIABymeei36x+rJ26lvHtxlHz+5qU/6Z80vG9pvRmw4z1vI54nRnNS5HayIBAdx9Ojd2QqvJKfRWvg8K5uugPAt18khdQKPh2cW/ubj7O780mYlPCmWI/1k7aXWVUa+5uPk7486D0akKa1W1Sm0ET+7Jq7nraf9uVB26eLN46F3NLsw8eZ+uQhwHje3P94k2t7a5FXOg5vAuje05kTK9J9BrRDZfC+YHE63z0zCFMHz5HrnMh0tn4GQu5cOUG08cPZc+mX6lSoQzdBozGLyBQq9yxU+e4fc8DG6uP/5hx8NgpZi1eSa/O7fh97WIKuTrTY/BYgoJDADh59iJ/HT3JyvlTGdK7CxNmLCQ4JBSA8IhIFq3cwNjBfdK9rSK5PNZWDOr5MzvWLmb7mkVUKFuSfiMn4+n9JMXyV67fpmHdmqxdNIPNK+aRx8aa7oPGJF0v9z0fsXT1ZmZPHsmsSSNYvHIjD7weARAXF8/k2YsZN6wvKpXufxjKSAlosuwjq5FkIgXdenfkt4072fHbXh7e92Lk4Em8joqmTfvmKZbv130EG9Zs495dD7wePmJo//HoKfSo9nUlAFwLOON+7wHnzlzi7OlLuN97gGsBZwB69f+Zi+evcuvG3Uxr3/s069qMw1sP8/fvx3j68CnLRi0l5nUMdVvXTbF8ndZ1yWGWk6ndpuB+1R3/Z/7cvXSXx+6Jbzq5HfMQFRbF2f1neHj7IXcu3MbBNS8AXzf5mri4OC4cupBp7UvJk5O3uTh7J96HrqaqfPizQM5M3ITHrrPEhCf/cmhkkRMjy1zc2XiMVw+e8+jodcwL2AGQp2wBbErm59aaQ+nahrRq16M1e7fsZ//2Azx68Jjpw+cQ/TqaJm0bvfcYPT09piwdz8o5a3n+xFdrn5OrIw/dvLh67jpXzl7D090LJ1dHAH7q3Zbrl27hdssjQ9uUGtnxOhdfruiYGI6dOsvgPl0oV6o4jg529OnSHkcHO7bv+SupnF9AINPn/8rMCcNT9SVw4/Y9tGjcgO8b1cPFOR/jh/XD0MCAPX8eAcD7yVP+1959h0V1dAEc/sEuICBIV4qAgL332GKJGo2xxt6w99h776ixd429a2wxamKLvQuKioCiKCoIKIoK0vf7g3yrK5gQAqzCefPsE3fu3LlnuLuwZ2fu3IplS1KiaCG+q1cLY2MjnoQ8A2D+8rW0adYI23w2mdNpoaFW9a/4umolnPLb4+zowKDeXTAyzIW3T+q/b2dPHkXbFt9TpJArLk75mTJ6EElJSVy6dgOAwEePKeTqTOXyZfiqQlkKuRUg8NETIHnEonyZkpQsWjiruie+AJJMfERPT49SZYpx9tT7P/4qlYpzpy9RvmLpNLVhaJQLpZ6SV399S+N75x4F3Jyxc7DFPr8tLm5O+PkG4OScnzbtmzNnxuJM6cu/odRT4lbSDe9zN9RlKpWKG+duULhckVT3qVy3Mn6efvSZ3pdNnptZemwZrfq3Qlc3+WUV/PApBoYGuBR3IXee3BQsXYiHvg8xzmNMh+EdWTVhZVZ0LUu9e/Gat6Evcfy6JMpc+thVKsxz38foKhXUntmFk6PXoUrS/rcKSj0lRUoV4vJZT3WZSqXiytlrlCpf/JP79RjahYgXL/l1+6EU2wL8HuDokp+89jbkc8iLo0t+7vsHYu9kR+M237Fi1s+Z0pd/Q17nIrtJTEgkMTEJA309jXIDA328bvoAkJSUxJipc+nSviVuLk7/2GZ8fDx3/O/xVcUy6jJdXV2+qlAG79u+ABR2c8HH7x6Rr9/g43eP2NhYHO3t8PK+zR3/ADq0apJxnRRplpiYyOHjp3gXE0OZEqn/TvtYTEwsCQmJ5DE1AaCgqzMPHz8l5FkYwc9CefT4KW4uTgQ9CWb/4WMM7Nk5M7sgvkCymtNHLCzNUCqVPA/XnIYSHv4C179GE/7JuMnDCH0Wpk5IAu4+YPa0hezYm/xhatbUhQTcfcCOfWuYPmketepUZ+jofiTEJzBxjAeXL3j+XfOZwtTCFIVSwcvnrzTKXz1/hYOrQ6r75HPMS6mqpTi1/xRTukzG1tmOvtP7otBTsmPhdqIio1gwdAFDFgxFP5c+f+75k+tnvPhxzkAObTxI3vx5Gb92Ako9JdsWbOPC4fNZ0NPM90ffJdSY1JEakzvy6KQ3vjtPU75/Y55c8CUxNp4f9k7E0MKEm+uPcnPjMa3EaGaRB6VSSUR4hEZ5RPhLnN1S/7BRulJJmrZrRPt63VLd/vDeI5bPWs3yHQsAWOaxiof3HrFs5wIWT19BlVqV6TW8KwnxCcyduJjrl7wztlNpIK9zkd0YGxtRukRRVm7YjouTI5YWZhw+fhrv23442tsCsHbLLygUunRs1TRNbb589ZrExCQsLcw1yi0tzAkMSv6Gulrl8nz/bR3a9hhELgMDZowfhpFhLqbNXcb0cUPZue8Q23YfwMwsD5NHDkxTEiPS7+79QDr0HkpcXBxGhoYsmjkB1wJp+5nPX7EOaysLqlQoC4CrsyODeneh5+CxAAzq3QVXZ0d6DBrD0H7dOH/Fk+Vrt6JUKhg9uA8Vynz6mtIvWZK2A/iCSDKRwfoP7kGTFg1p1bgLsbFx6vLN63exef0u9fNWbZvy9m0Unle9OXP1II3qtMHWLh/L18ylSpn6xMXFayP8f0VHV5fIF69YNnopSUlJ3L91H8u8lrTo04IdC7cDcOnIRS4deT/KU6JyCQoUdWb1xFWsOruauQN+4mX4S+YdmI/P5dtEvojUVncyTMjVu+z6fqL6uVmBfBT5oTo7Goyjxe4JeK87wqOT3rQ/7sHTy3688HusxWjTxsjYkKlLxjNjxBwiIz59jvZs+pU9m35VP2/UqgHRUdHcunabPee20rlhL2xsrZm5YjJNKrcmXl7nQvxnHhOGM9FjAXWadUSh0KVoITca1q3JHf8AfPzuseWXX/ll3RJ0dHQy9Lj9u3ekf/f3i1AsX7eVryqUQalUsmrjDvZtWs7pC1cYO30uu9YtydBjC00FHB3Ys2EZb95GcfTkOcbNmMeGpXP+MaFYs3kXvx8/zfqlczAw0FeXt2neiDbN3095/fXwMYyMDCldoiiN2/Vkx5pFhIY9Z8TEWRzZvR59ff3Umhc5hCQTH4l48YqEhASsrDUvULO2tiQ87Pkn9krWe0AX+g/uTttmPfD1ufvJeuYWZgwZ1ZcfGrlTtkIpHgQ8IvBBEIEPgtDTU+Li5ozfnXsZ0p+0eh3xmsSERMytzDTKzazMeBn+MtV9XoZFkJCQSFLS+/z9ScBjLGwsUOopSYhP0Kiv1FfSd0Zf5g+ej62zLQqFgtuXk68VCQ58SqGyhbl6/ErGduwzUHtWN85N2wa6utiUdCbg4GUSYuJ4eskP+6+KaCWZeBURSUJCAhbWmosKWFib8yIs5cXhDs722DvaMX/jLHXZ/6f5XHp8kh+qd+Dpo2CNffJY5KHnsK70aj6AEuWKEfTgMY8Dn/A48AlKPWXyNCi/B5nQu0+T17nIjhwd7Niw7Cei38UQFRWNtZUFwyZ44GCXDy/v20S8fEW9H95PTUlMTOKnpWvYvGs/R/ekXHzC3MwUhUKXFxGa74kXES+x+mi04v8ePHrMwSN/snv9UvYeOkqFMiWwMDfj2zpfM2HmAqKiojE2NsrYjgs1PT09HB2Sr88rXqQgPn532fLLr0waOfCT+6zftpu1W3bx88KZFHb79MyLl68iWbF+GxuWzeGWjz9O+e3Vj4TEBB4+fkoh17TN3BDZk1wz8ZH4+Hhu3rhD9Zpfqct0dHSo/nVlPK9+elpG34HdGDyiDx1b9ubmDZ+/PcaUmaP4efkmQoJDUejqoqf3PqdTKBUodLN+hYSE+AQCbgVQqtr760J0dHQoXa00/l6pX8R155ovtk62Gt922bnY8yL0RYoPWABtfmyL5ykv7t++j65CF8UHFwEqlEoUutnv5VisTU1iXr0l8JgXuorkn9P/l4pV6CnQUWinzwnxCfjdvEul6u+XwtXR0aFi9fLc9Ez5+n0YEESbWp3pULeb+nHm6Hmunb9Oh7rdCA0OS7HPsCk/sn31LsJCwtFV6KJUfvA6VyhQaKHv8joX2ZmRYS6srSyIfP2GC1c8qVPjKxo3+Ia9m5aze8My9cPGypKu7X9g1fwZqbajp6dHscIFufzXBbmQfN3FZc8blC6RcvlolUrF1DmLGfljT4yMDElKTCI+Ifm9kfDX/xOTZNJIVkpKUv3tDId1W39h1YbtrJw3jRJF/35p7NmLV9OpdTPy2ViTmJSoPqeQnJgmJWbPc6v6jP/73MjIRCp+Xr6RBctncvO6D9e9btGzbycMjQ3ZuTV5Xe5FK2YSEhLGrKkLAeg3qDvDxwxgQM+RPA4KxtrGCkhe+zs6Klqj7Rq1qlDA1ZlBfZPnInpfv41rwQLUrlsdO3tbkhKTuB8QmHWd/cD+NfsZMm8IAbfucffGXZp2b0ouo1wc33UcgCELhvLi2Qs2zU7+Juv3zYf53v17ek7uxcENv2FXwI5W/VtxcP1vKdrOXzA/NRrXYFDD5G9JngQ8QZWURL029XgZ/hIHVwfuemftaAyAnpEBeZzzqp+b5rfGqpgjMa+ieBv8giqjWpM7nznHhqxS17EqlrxCkZ6xAYaWJlgVcyQxPoGX9zS/mTe0NKXCwKbsaTEVgNjIaCLuPqVM9wYEnbmFQ7XiXF1yIAt6mbqtq3YyedFY7nj74XPDl/Y9W2FoZMhvOw4DMGXxOMKePWfZzFXExcZx31/zdfkm8i1AinKAyl9XwNElP5MGJn9YuXPDDyc3J6rWqUxeOxuSkhJ5dD+VpXWzQE58nYvs7fxlT1QqFc6ODgQ9CWbesrUUcHSgWaP66CmVmOUx1aivVCqwsjCngNP764S6DxzNN19XpX3L5AunO7dpzrgZ8yhepCAlihVmy679vIuJpVmjlKue7fntD8zN8lCrevKXcGVLFWP5ui143/bl7KVruDo7YmqSOxN/AjnbghXrqVGlArZ5bYiKjubQ0VNcvX6TVfOnAzBm2lxsrCwZ0rcrAGu37GLpms3MmTQKe9u8PH+RfO2ckaEhRkaa98O5cMWLR4+fMnP8MABKFC1E4KMnnL14lWdh4ejq6uLslPr1ZiLnkGQiFQf2/YGFlQXDxw7A2sYKn1t+dGzZW31Rtp2DLUkfrMjTuVsbDAz0+XnTQo125s1axvzZy9XPc+UyYMaccfTtNhyVKnn/kOBQJoyayfylM4iLi2Nwv7HExMRmfidTce63s+SxyEOHoR0xtzbnwZ0HTOo0kVd/XaxqbWeN6oNvl56HPGdip4n0mNiDJUeW8iL0Bb+tO8CeFXtStD1g1gDWTltD7LvkvsXFxrFw2EL6TOuLnr4eqyauJCI06++9YFPKhRa/jFM///9N6Hx/OcPxoasxzmtGbnsrjX3aHXl/o7a8pVwo3Lwarx+Hs7HqEI16X0/pxI3VvxMV+kpddnzYKurO702pbvXxWnmIMO+snebzoWMH/sTc0ow+I7tjaW3BXZ8Afmw/nIjnyVMb8tnn1Xidp5VBLn1GzhjCmD6T1K/zsJBwfhq/kIkLxhAfF8+kgTOJjYn7h5YyR058nYvs7c3bKBauXE9o+HPymJpQr2Z1BvZ2R0+Z9j/xj5+G8DLytfp5w7o1efkqkqVrtvA8IoIiBV1ZOW9aimlOzyNesnrjDrasnK8uK1msMO5tW9BvxCQszM3UH0RF5oh49Yqx0+YS/iICE2NjCrkVYNX86VStVA6AkNAwdD8YWd257xDx8QkMGa85MtW3WweNa2BiYmOZOX85c6eOUU9rzWdjzZghfRk/cwH6enrMGD+MXAYGWdBL8TnTUf3/r302Ym/+6aUts7NyJjlzzmJ9lZm2Q9CKjQmp35Aou7PVS/3mctnd78+uazsEkYXeBZ/VdghaYWhXQ9shaEVOPd96Vi7aDuGTujm31HYIn7Tu4W5th6BBJu8KIYQQQggh0kWrycSPP/7I2bP/LRuPjY3l9evXGg+VKnteDCSEEEIIIcTnRKvJxLJly6hVqxaFChVi9uzZPHv27F+34eHhQZ48eTQeb2L+fglXIYQQQgghPkXbKzZ9Sas5aX2a09GjR/nuu++YO3cujo6ONG3alIMHD2qs6f53xowZQ2RkpMbDJJfVP+8ohBBCCCGE+E+0nkyULFmShQsXEhwczJYtW4iNjaVZs2bkz5+fcePGERAQ8Lf7GxgYYGpqqvHQ0dF6t4QQQgghhMj2PpulYfX09GjdujWtW7cmKCiIdevWsWHDBmbNmkViYqK2w/tbA4b0oOH39XArWICYmBiuXbnBzMnzuR/wUNuhZTqLvJZ0GdOF8rXLY2BoQMjDEBYNX0jAzb9PAr8kdpULU653I6xLFSB3XnMO9VjAgyOe6u2uDSpQotM3WJd0xtDchO3fjuX5He3cQyEruQ/owI/j+rDt513Mn7hE2+FkqpzwOhefl6ioaJb8vIkTZy4S8fIVRQq5Mnpwb0oWLayuc/9hEAuWr+PajVskJibi4uzIwhnjsc1no65z47Yvi1dt5NYdP3R1dSlS0JVVC6ZrLOcZExtLje/asGfjcgxz5eKnpT/j43ePoCfBdGjZhNGD+6SI78ifZ1n68yaePgvFycGeIX278nXVSgDEJySwZPVGzl68xpPgEHIbG/NVxbIM6dMVG2tLdRsPg54wb9lart+6Q3x8PIXcCpArl4KYmM/7b/6XaMe+g+zcd4jgkFAA3Ao40adre2pUqQjAlDmLuXj1OuHPIzAyykWZEsUY0q8bLk75tRm2VsnVt2n3WX6F7+joyOTJkwkMDOSPP/7Qdjj/6KuqFdm4ZjuN67ejXYue6Okp2bb3Zww/uvlLdmOcx5g5e+eQmJDA5M6T6f9NP9ZNW8vbv25mll3oGRrw3DeI0+M3prpdaWRA8BV/LszcmcWRaU+x0kVo0akJd32y/4fpnPI6F5+XibMWcfHqdTwmDmff5hVUrVSOnoPGEhqefE1g0JNgOvcdTgGn/KxfOps9G5fTp0t79A301W3cuO1Ln6HjqVqpHNt/XsSONYtp90NjjXsOAFy8ch3bfDY4OtgRFx+PuVkeerm3pbBb6suNX791h5GTZ9H8+2/5Zf1S6tSowsAx07j34CEAMTGx3PG/T+8u7di1bikLZ47nYdATBoyaotFO/5GTSUhMZO3iWexat4TCbi7Y5s2FQqGTylHFf5HP2oohfbqya90Sdq5dTKXypflx9FQCHiQvMV6ssBvTxw3lwLbVrJo/A5VKRa8h4z77L3PF50GrIxNOTk4oFIpPbtfR0aFevZR32/zcdGzVW+P54H7juBVwjlJlinH5gucn9vrytezbkuchz1k0fJG6LPRxqBYjyhyPTt3k0ambn9zuv/c8ACYOOeNaHUMjQ6Ytm8iM4XPoPthd2+FkupzyOhefDx0dOH76HItnTaJCmZIA9O/ekdPnL7Nz3yEG9nJn8eqN1KhSkWH9u6v3c3Sw02hnzqJVdGjZlB6dWqvLCqRyt+I/z12k9l93r7a3zcuYv0Yi9h06mmp8W3b9SrXKFejWIXkd/h97debiVS+27f6NSSN/xCS3MWsWzdTYZ+zQvrTrMZiQZ2HY5rPh5atIHj1+ytTRg9VJy5A+Xdmx9yD6erq8kw+xGer/dyf/v0G9u7Bz3yG8ffxwc3GiVdPv1NvsbfPyYy93fnDvx9OQ0BSvKyE+ptWRicDAQCwtLf+54hfG1NQEgFcvI7UcSeaqVK8yATfvMWrFaDZ7bWHh4UXUb/ettsMSmWyUxxDOn7jIlbPZN1H+kLzOhTYkJiZhoK+nUWZgoI/XTR+SkpI4c+Eqzvnt6TVkHF83aku7noM5ceaCuu6Ll6+4eccfC/M8dOg9lK+/b0eX/iPw8r6t0WZSUhKnz1+hdo0qaY7N28eXKhXKaJRVrVwebx/fT+7z9m00Ojo6mJgYA2CWx5QCjg4c+OME0e9iSEhIZNevh0lITCI2ThKJzJSYmMjh46d4FxNDmRJFUmyPfhfD/kNHcbDLh21eay1E+HlIUqk+28fn5rOc5vQl09HRYYrHKK5c8sLfN3tPAcmXPx8NO35HcGAwkzpN5Pcth+k1pRd1WtbRdmgik9Rv+g1FShZi6cxV2g4ly8jrXGQ1lQpKlyjKyg3bCQt/QWJiIr8d+RPv2348fx5BxMtXRL97x9otu6heuQKrF8zgm6+rMnjsdK5eTx5FffI0BIDl67bSskkDVs2fRtFCbnQfNIZHj5+qj+Xt4wdAqWKFUwbyCc9fvMTSwlyjzMrCnOcvXqZaPzY2jgUr1vFd3ZrkNk5OJnR0dPh50Ux8796ncr0WlK/ThE079hHyLIY0LuYo/qW79wOpWLc55Wo3YdpPS1k0cwKuBZzU23fsPUjFus2pVLc55y5dY/WCGejp6f1Ni0Ik+2wuwM4uZs4dT+GiBWnesJO2Q8l0Oro6BNwMYPOcTQA88HmAU2EnGnb4jj93/6nl6ERGy2tnw7BpA+nfZihxsXHaDifLyOtcaIPHhOFM9FhAnWYdUSh0KVrIjYZ1a3LHP4CkpORvJmvXqELnts0BKFLIlRu37rBr/2Eqli2l/vayVdPvaN6oPgBFC7lxyfMGew8eZUjfrgCcPHuRmtUqoaubOd8txickMGzCTFQqFRNGDFCXq1QqZsxbjqV5HjYu/4lcBgbs+e0PQkJ/40nwOxITP79vX790BRwd2LNhGW/eRnH05DnGzZjHhqVz1AlFo/q1qVKxLOEvItiwbQ/DJ3qwecU8DD64DkeI1EgykYGmzxlH3W9r0uI7d0KCs/+c6pdhL3l8T3PVosf3HlO1YTUtRSQyU5FShbG0tmDL0TXqMqVSSdmvStO6awuqOn2T5vvDfEnkdS60wdHBjg3LfiL6XQxRUdFYW1kwbIIHDnb5MDczRalQ4OrsqLGPi3N+vG7eAcDa0gIA1wIf1XFy5FlomPr5yXOX1YlFWllZmvMiQnMU4nnES6wsNUcr/p9IBIeGsW7xLPWoBMBlzxucvnCFC3/sUpcXKzyAzbt+wyS3kleR8f8qJvHP9PT01Nc/FC9SEB+/u2z55VcmjRwIgEluY0xyG+OU357SxYtQtUErTpy5wHf1amkxau2RdDbtJJnIINPnjKNBo29o1bgLj4Oe/vMO2YDvtTvYu2pezGfvYk/Yk7BP7CG+ZFfPXqNNrc4aZRMXjuFRQBAbl27NlokEyOtcaJeRYS6MDHMR+foNF654MrRfN/T09ChetBCBQU806j58/BS7v5aFtbfNi42VJQ8fadZ59PgJ1b+q+Ne/nxLyLIwqFcv+q5hKFy/KJc8bdGrTXF128ep1Shcvqn7+/0Qi6HEw65bMwiyPqUYbMTGxAOh+fF8o+QSXZZKSVMTFpZ60qVQqVCo+uV2ID0kykQFmzp1As5bf0a39j7x9G421TfKqPm9ev1H/wsyOfl3zK3P2/USr/q04d/AchcoU4tv2DVg6eqm2Q8tQekYG5HHOq35umt8aq2KOxLyK4m3wCwzMjDGxs8Q4b/K3cuautgBEh0cSHZ59LsKPjnrHff9AjbKY6BhevYxMUZ6d5JTXufi8nL/siUqlwtnRgaAnwcxbtpYCjg40+2vKUtf2PzB84iwqlClBpXKlOXfpGqfPX2b9ktlA8jUJXdv/wLK1WyhcsABFCrry6+HjBD56wvzp4wD48+xFvqpQBsNcuTSO7Xf3PgDR0TG8fBWJ39376Okp1dNhOrZuStf+I9mwfQ9fV63E78dP4+N3j8mjkr/hjk9IYOi4Gdy5G8CyOVNISkri+YsIAPKYmqCnp0fpEkUxNcnN2Onz6NO1PbkM9Nl94A/09HSIficXYGe0BSvWU6NKBWzz2hAVHc2ho6e4ev0mq+ZP5/HTEP44cYaqlcphYZaHZ+HPWbt5FwYG+tSoWlHboYsvgI5K9RleFv4f2ZsXz9LjPX3pk2r5kH7j2LV9f5bFUc4k9TXBM1PFbyrSeZQ7ds52hD4OZf+a/RzdfiRLY6ivMsvU9u2/KkqLX8alKPf95QzHh66mSKsa1JvfO8X2y/P3cmXB3kyLa2PCo0xrO61W7VmMv8+9LL1pna1eniw71v99Dq/z359dz9LjCe3at3kGC1euJzT8OXlMTahXszoDe7tjkvv9VKG9B4+wZvMuQsOe4+zoQP8eHanz0apMazbvYvve33j9+g2F3FwY1q8b5UqXAKBz3+E0aViXlk0aaOxTolrDFPHY5bPh6J7399o58udZlqzeqL5p3dB+3dQ3rXsaEsq3Lbuk2q91S2ZTqVwpAG773mXx6o34+N0jISEBtwJO/HHieo5MJt4Fn83U9id4LODytRuEv4jAxNiYQm4F6NahFVUrlSMs/AWTZi3Exz+A12/eYmlhRoXSJejTtUOqSwlnJD0rl0xt/79o79T8nytpybZH+7QdggZJJrIRbSQTn4PMTiY+V59DMqEN2kgmPgeSTOQsmf3h8uWrSGo36cDx/Zux+mhlJm0ytKuh7RC0IrPP9+dKkon0+dySCVkaVgghhMhhIl+/YcSPPT+rREII8WWSayaEEEKIHMbZ0QFnx8ydwiLEl0wlqwGkmYxMCCGEEEIIIdJFkgkhhBBCCCFEusg0JyGEEEIIIT6QPe+clDlkZEIIIYQQQgiRLpJMCCGEEEIIIdJFpjkJIYQQQgjxgSRZzSnNZGRCCCGEEEIIkS6STAghhBBCCCHSRaY5CSGEEEII8QG5aV3ayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gNy07q0k5EJIYQQQgghRLpIMiGEEEIIIYRIF5nmJIQQQgghxAdUKlnNKa1kZEIIIYQQQgiRLpJMCCGEEEIIIdJFpjkJIYQQQgjxgSS5aV2ayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gNy07q0k5EJIYQQQgghRLpIMiGEEEIIIYRIl2w5zalDnlLaDkErVoZf1nYIWuGlb6jtELTiTdw7bYegHabaDkA7jPQMtB2CVpjk0Pe3pVNdbYegFe+Cz2o7BK1wLz9M2yFoxbZH+7QdwiepZDWnNJORCSGEEEIIIUS6SDIhhBBCCCGESJdsOc1JCCGEEEKI9JKb1qWdjEwIIYQQQggh0kWSCSGEEEIIIUS6yDQnIYQQQgghPqBSyTSntJKRCSGEEEIIIUS6SDIhhBBCCCGESBeZ5iSEEEIIIcQHkrQdwBdERiaEEEIIIYQQ6SLJhBBCCCGEECJdZJqTEEIIIYQQH1DJTevSTEYmhBBCCCGEEOkiyYQQQgghhBAiXWSakxBCCCGEEB9IkmlOaSYjE0IIIYQQQoh0kWRCCCGEEEIIkS4yzUkIIYQQQogPqFQyzSmtZGRCCCGEEEIIkS6STAghhBBCCCHSRaY5CSGEEEII8QFZzSntZGRCCCGEEEKIbGby5Mno6OhoPIoUKZLhx5GRCSGEEEIIIbKh4sWLc/z4cfVzpTLjP/pLMiGEEEIIIcQHVJ/xNKfY2FhiY2M1ygwMDDAwMEhRV6lUki9fvkyNR6Y5fUKVTvUYfW4xM/w3MmD/NPKXdv1kXV2lgroDWzDq9EJm+G9k8O+zKFSztEadsk2rMfbCUiZ7/8z34ztqbDN3sGLEn/MxyG2YKX35N3r26sStO2cIe+HLn6f2Ur58qU/WLVK0IJu3LufWnTO8jnpAv/5dU9Rp3aYpd/zP8ejJdWbOGqexzdHRHq8bJzAxyZ3h/fi33Hu045L3Ue6HePHbse2UKVfyk3Xbd27J3sOb8Am8gE/gBXbsW5Oifu8BXfC+ewbvu2fo3d9dY1vZ8iX5/eQuFApFpvTl38ip57tVl+YcuLKL84HH2XBoFcXLFE3TfvWbfsO1kLPMXT9To7xjn7YcvXWAo7cO0KF3G41txcsWY/ORNXK+tUje39nzfEdFRTNr4UrqtXCnfO2mdOg9lFu+/urtJao1TPWxbuvuT7Z57cYt+o+cRO0mHShRrSEnzlxIUWf9tt183agtXzdqy4btezS23fTxo3W3H0lISMy4jqZRvc4NWXRuFRv8dzJ1/2xcSxf8ZN3xO6ax7dG+FI8R69+f10a9mrLCcwMrPDfwXc8mGvu7linIjINz0VXIx0ht8PDwIE+ePBoPDw+PVOveu3cPOzs7XFxc6NChA0FBQRkej7wKUlH6+69oPL4TxxftYVGjsYTceUT3TaMxtjRNtf63w1tTuf03/DppA/PqjuDS1uO4rxqKXXFnAIzMTWg5uxeHZm5hTScPyjWrTtE6ZdX7N5/Wjd9nbyf27bus6N4ntfihETNnjWWWx2JqVGvMrVu+7P11I1bWlqnWNzI05OHDICZPnMOzZ2EptltYmrNkmQfjx3rQvIk7bdo2pUGDOurt8xdOY9LEObx58zbT+pQWTZo3YNL0kcyfvZwGtVpx57Y/W/eswtLKItX6VapX5Nc9h2nduBtN6ncg+Okztu1dTT5bGwCKFi/EiDED6Nd9BP17jGDEuIEUKZb8S12hUDBr/iRGD51KYmLW/7H5UE493/Wa1GHI5AH8PG8DHb/twd07ASzZPg9zS7O/3c/WIR+DJvbD69INjXK3oq70GdmdsX0mM67vFPqO6olrERcg+XyPnT0Mj5Fz5Xxriby/s+/5njhrERevXsdj4nD2bV5B1Url6DloLKHhzwE4dWCrxmPa2CHo6OhQr1a1T7b57l0Mhd1cGDesX6rb/QMCWbZmCz9NHc2cKaNYsnoTd+8HApCQkMjUn5YwYcQAlMqsTSa/+r4aHcd3Ze+inYz7fhhBvg8ZvXkippZ5Uq2/oPds+lboqn6MqDuQxIRELh9KTp7yF3Gi5dB2LPlxHksHzqP18PbkL+wIgK5Cl+4z+7B27EqSEpOyrI/ivTFjxhAZGanxGDNmTIp6lStXZsOGDfzxxx+sWLGCwMBAatSowZs3bzI0HkkmUlGjRyMu7/iTa7+cJizgKXvHrSX+XRwVW9dKtX755jX4c9l+/E7dIOJxGJe2HMfv5HW+7tEIAEtHG2LeRON98BJPbj7g/qU72LjZA1CmSVUSExK5feRqVnXvkwb82J2N63eydfNu/P0CGDxwPO/evaNT51ap1vfyusmEcbPYs/sgsbFxKbYXcM7P69dv2LvnEF5eNzlz+hKFiiSP8LRs1Zj4+Hh+O3AkU/uUFj37ubNt0252bdvPPf/7jB46hXfRMbTt2CLV+j/2GsXGtTvwue3H/XuBDB84EV0dXap//RUAbgUL4Otzl/NnL3PuzGV8fe7iVrAAAH0HduXShWt4X7+dZf37lJx6vjv0bsP+rb/x287DBN59iMfIucS8i6FJu0af3EdXV5fpyyayeu46nj4K0djm7ObIvTv3uXbei6vnPAnwvY+zW/If3U792uF12Zs73n6Z2qe0yKnnW97f2fN8x8TGcvz0OYb2706FMiVxdLCjf/eOODrYsXPfIQCsLC00HifPXqJSuVLkt7f9ZLs1qlRkYC936tZMPeEIfPSYQq7OVC5fhq8qlKWQWwECHz0BkkcsypcpScmihTO+w//gux5NOLnjGKd/+ZOn956wduxKYt/FUrP1N6nWj4p8S2T4K/WjZI3SxL6LVScTdq72BPk+5M6FW/icv0WQ7yPsXB0A+L53M/wu3+HBzYAs6582JKlUn+3DwMAAU1NTjUdqU5waNmxIq1atKFWqFN9++y2HDx/m1atX7Nq1K0N/VpJMfEShp8C+RAECzr//Y6BSqbh3/jZO5VIfMlToK0mIjdcoi4+Jx7li8i+U54HP0Mulj11xZwzzGONQyoUQvyAMTY2pP7QV+yeuz7wOpZGenh5lypbg5Mnz6jKVSsWpk+epVKns3+z5affvP8TQMBelShfD3DwP5cqXwue2H2ZmpoyfMIThQydnTPD/gZ6eHqXKFOPsqYvqMpVKxbnTlyhfsfTf7PmeoVEulHpKXr2KBMD3zj0KuDlj52CLfX5bXNyc8PMNwMk5P23aN2fOjMWZ0pd/I6eeb6WekiKlCnH5rKe6TKVSceXsNUqVL/7J/XoM7ULEi5f8uv1Qim0Bfg9wdMlPXnsb8jnkxdElP/f9A7F3sqNxm+9YMevnTOnLv5FTz7e8v7Pv+U5MSCQxMQkDfT2NcgMDfbxu+qSo/zziJWcuXKHF99/+p+MWdHXm4eOnhDwLI/hZKI8eP8XNxYmgJ8HsP3yMgT07/6f200Ohp6RASVdun/NWl6lUKm6fu0nBcmlLbGq1qcul384R+y55Hv5j/yBsXeywtLPCyt4aWxc7Ht8NwsYxHzVbfcOuuVszpS8ic5mZmVGoUCECAjI2EZQLsD9ibG6KQqngzfNIjfK34ZHYuNqlus/dMzep0aMRgVf8ePEoFLdqJSjRoCK6usm52rvXUewcvoI28/qil0sfr71nuXvmJi1n9+LCpqNY5Lehy5oRKJQKji3cza3fr2R6Pz9maWmOUqkkPOy5RnlY2HMKFfr09SJ/59Wr1/TpNYJVP8/DMJcBO7bt48TxsyxdPovVqzbj5OzAjl9Wo6enxGPGYn7d/3tGdOVfsbA0Q6lU8jz8hUZ5ePgLXP/6tvGfjJs8jNBnYeoPLAF3HzB72kJ27E3+EDlr6kIC7j5gx741TJ80j1p1qjN0dD8S4hOYOMaDyxc8/675TJFTz7eZRR6USiUR4REa5RHhL3F2c0p1n9KVStK0XSPa1+uW6vaH9x6xfNZqlu9YAMAyj1U8vPeIZTsXsHj6CqrUqkyv4V1JiE9g7sTFXL/knWo7mSmnnm95f2ff821sbETpEkVZuWE7Lk6OWFqYcfj4abxv++GYysjDgd+PY2Rk+MkRh7RydXZkUO8u9Bw8FoBBvbvg6uxIj0FjGNqvG+eveLJ87VaUSgWjB/ehQplPX5+TUUzMTVAoFUR+9Lkl8vkr7Fzt/3F/19IFcSzixM8jl6nLggOesHPOVsZsmQzAjtlbCA54wtitk9nusZFSNcvyw+C2JCYksGnyWvyu3MnQPonM8fbtW+7fv0+nTp0ytF1JJjLAgSkb+WFWT4afmIdKpSLiUSjXfjmtMS3K58g1fI5cUz93qVwU2yKO/DppA6NOL2TbwCW8CX/FgP3TeXDFj6gXr7XQk4x38LejHPztqPp5teqVKFGiCCOGTebGrZN06zKI0NBwTp7ez/nzV1L80f/c9R/cgyYtGtKqcReNqQGb1+9i8/r3w4it2jbl7dsoPK96c+bqQRrVaYOtXT6Wr5lLlTL1iYuLT635L052O99GxoZMXTKeGSPmEBkR+cl6ezb9yp5Nv6qfN2rVgOioaG5du82ec1vp3LAXNrbWzFwxmSaVWxMv5/uLIO9vTZ/b+faYMJyJHguo06wjCoUuRQu50bBuTe74p/zWdd/Bo3xfvzYGBvr/+bhtmjeiTfP30yJ/PXwMIyNDSpcoSuN2PdmxZhGhYc8ZMXEWR3avR1//vx8zM9Vq8w1Bvg+5731Po/zE1iOc2Pp+6lqNH2rz7u077nr5M+/PZUxoMgILW0t+XDqMQdV7kxCXkNWhZ6rPdy2ntBs+fDiNGzfGycmJ4OBgJk2ahEKhoF27dhl6HEkmPhL18jWJCYmYWGletJTbOg9vwl+lvk/EGzb1mo/SQA8js9y8Dn1Jw9HteBGU8iI2SJ4W1WxaN3YOWYalcz50Fbo8uOwLwPPAEBzLuOF7witD+/VPXrx4SUJCAtY2VhrlNjZWhIaGZ8gx9PX1mb9gKr16DsPF1RmlUsH5c8mjMPcDAqlQoTR//P5nhhwrrSJevCIhISHFRYnW1pYpvtX7WO8BXeg/uDttm/XA1+fuJ+uZW5gxZFRffmjkTtkKpXgQ8IjAB0EEPghCT0+Ji5szfnfufXL/zJBTz/eriEgSEhKwsNa8+NbC2pwXYSk/+Dg422PvaMf8jbPUZf8fcbz0+CQ/VO/A00fBGvvkschDz2Fd6dV8ACXKFSPowWMeBz7hceATlHrK5GlQfg8yoXefllPPt7y/s/f5dnSwY8Oyn4h+F0NUVDTWVhYMm+CBg53mMpieN24TGPSEn6amvED1v3r5KpIV67exYdkcbvn445TfXv1ISEzg4eOnFHJN2yhYer15+YbEhETyfPS5JY+VGa8+8bnl/wwMDajSuDq75+/423om5ib8MLg1U1uNx61MIZ4FBvPsYQjPHoagUCqwLWDHY/+MXyVI/DdPnjyhXbt2vHjxAmtra6pXr86lS5ewtrbO0OPINRMfSYxP5OntQNyqllCX6ejo4Fa1OI+8/v4PQkJsPK9DX6KrVFCyQSXuHLuWar1vBjTn7mlvnvo8RFehi+4Hqz4o9BRaWWotPj6eG9dvU6tWVXWZjo4ONWtV5cqV6xlyjJGj+nP8+Bm8b/igUOiiVLzPZZV6Sq0spRgfH8/NG3eoXvMrdZmOjg7Vv66M59VPT0fpO7Abg0f0oWPL3ty8kXJ+7oemzBzFz8s3ERIcikJXFz299/1WKBUodLXT75x4vhPiE/C7eZdK1cury3R0dKhYvTw3PVOex4cBQbSp1ZkOdbupH2eOnufa+et0qNuN0OCUXxgMm/Ij21fvIiwkHF2FrsYNghQKBQp5f2cZeX/njPNtZJgLaysLIl+/4cIVT+rU+Epj+96DRyhWuCBFCrpk+LFnL15Np9bNyGdjTWJSIgkJ77+dT0xMypLVjhLjEwi8dZ/i1d4v/aujo0PxaiW55+X/N3tC5UZVUerrcW7f6b+t13FiNw6v/Y2IZy/QVeii0Pvgc4tSO59bxD/bsWMHwcHBxMbG8uTJE3bs2IGra/qmOv4dGZlIxdk1h2g9ry9Pbj3g8Y0AqndviL6RAdd+SX6ztZnXl8jQl/wxJzmTz1/GlTx5LQi+8wjTfObUG9wSHV0dTq36LUXbNm72lP6+CgsbJX9DEhbwFFWSioqta/EmPBJrVzsee9/Pus5+YOmStaxcPZfr129x7Zo3/fp3xcjIiC2bk9fkXvXzXIKDQ5ky6Scg+SK/IkXdANDX18PWLi8lSxUl6m00Dx480mi7cBE3WvzwPdWrfg/AXf/7JCUl0alza8JCwylUyBUvz5tZ2Nv3fl6+kQXLZ3Lzug/XvW7Rs28nDI0N2bl1HwCLVswkJCSMWVMXAtBvUHeGjxnAgJ4jeRwUrP72LyoqmuioaI22a9SqQgFXZwb1TZ5f6339Nq4FC1C7bnXs7G1JSkzifkBg1nX2Azn1fG9dtZPJi8Zyx9sPnxu+tO/ZCkMjQ37bcRiAKYvHEfbsOctmriIuNo77/prn501k8tKXH5cDVP66Ao4u+Zk0cAYAd2744eTmRNU6lclrZ0NSUiKP7mvn27ucer7l/Z19z/f5y56oVCqcHR0IehLMvGVrKeDoQLNG9dV13kZFcfTkWYYP6JlqG90Hjuabr6vSvmXyfRSio98R9OT9aOPT4FD87t4nj6kJtvlsNPa9cMWLR4+fMnP8MABKFC1E4KMnnL14lWdh4ejq6uLs5JDR3U7V4TUH6DNvIA9u3ue+9z0advueXEa5OP3LCQD6zh9IxLMIds7ZorFfrTZ18Tx6mbevPr1UaInqpbEtYMfKocmLCzzwDsDO1Z7StcphaWtJUmISwfeDP7n/lyopW0x0yhqSTKTC++AljC1MqT+kJSbWZgT7PmKt+yze/nVxk5m9FSrV+xeZnoE+3w5vjYWjDXFRsfidvM7OIcuJeR2dou0fPHpwcPpm4v9aMSEhNp5dw1fQbGpXlAZ6/DpxA69DX2ZNRz+yd88hrKwsGDt+CHnzWnHrpi8/NOuing7g4GBHUtL7b1lsbW04f/H96jaDBvdi0OBenD1ziUYN22u0vXjJTMaOnkF0dPK9NGJiYunbeyRzF0zBwECf4UMnERISmgW9TOnAvj+wsLJg+NgBWNtY4XPLj44te6vn+9o52JKU9P58d+7WBgMDfX7etFCjnXmzljF/9nL181y5DJgxZxx9uw1Xv15CgkOZMGom85fOIC4ujsH9xhITo3kXy6ySU8/3sQN/Ym5pRp+R3bG0tuCuTwA/th9OxPPk910++7wa5zutDHLpM3LGEMb0maQ+32Eh4fw0fiETF4whPi6eSQNnEhuTctnNrJBTz7e8v7Pv+X7zNoqFK9cTGv6cPKYm1KtZnYG93dH7YDTw9+OnUangu3q1Um3j8dMQXka+v0bxtt89uv04Sv18zpLVADRtWJcZfyUNkLw07cz5y5k7dYx66mM+G2vGDOnL+JkL0NfTY8b4YeRKZbnOzHDp4HlMLU1pObQtZtbmPLoTyKzOU3n91+cWSzvrFL/XbF3sKFKpGDM7TP5ku3oG+nSZ2pMlA+aqX+cRz16wYdIaev80gPi4eFYMW0x8KssJi5xDR/Xhp+JsYqRzxl5Y8qVYGX5Z2yFohYm+9u8crg1v4rR7k0NtKWT6z6uTZEd3Xz/VdghaIe/vnOXFo+PaDkEr3MsP++dK2dC2R/u0HcInVbOv88+VtOT806y9/uyfyMiEEEIIIYQQH5BpTmmn9Stmli5dSufOndmxI/n6g82bN1OsWDGKFCnC2LFjNS5mSk1sbCyvX7/WeCSoErMidCGEEEIIIXI0rSYT06dPZ+zYsURHRzNkyBBmz57NkCFD6NChA+7u7qxZs4Zp06b9bRseHh7kyZNH43E5Um6eIoQQQgghRGbT6jSnDRs2sGHDBlq0aIG3tzfly5dn48aNdOjQAYAiRYowcuRIpkyZ8sk2xowZw9ChQzXKJpfskalxCyGEEEKI7CsbXlKcabSaTAQHB1OhQgUASpcuja6uLmXKlFFvL1euHMHBf7/cmIGBAQYfrZag1Mn6db2FEEIIIYTIabQ6zSlfvnzcuZM8JenevXskJiaqnwP4+PhgY2Pzqd0/KwbGuWg8sTNjzi1mht9G+u2ZgkOpjL9BzuekarWK7PzlZ/wDLvI66gGNvq+n7ZCyxIAhPTh0Yif+QVfwvnuGtVsW4+rmrO2wMl1OPd8fcx/QgWshZxk69Udth5Kpcur5lvf353W+o6KimbVwJfVauFO+dlM69B7KLd/Ub8Q2Zc4SSlRryOadKVcIOn3hCu16DqZ87aZUbdCKgaOnpqgT/CyU8rWbEh39jviEBFas20qDVl0pV7sJLdz7ce6S5o1o6//gTolqDVM8ps9blqJtlUpFn2ETKFGtISfOXEjnTyPjLDq3im2P9qV4dJnWS9uhiS+QVkcmOnToQOfOnWnatCknTpxg5MiRDB8+nBcvXqCjo8OMGTNo2bKlNkNMs5aze5G3UH52DF3O69CXlGtenZ5bxjGv3nCt3TcisxkbG3H7li+bN/3Cth0rtR1OlvmqakU2rtnOjeu3UCqVjJ4wiG17f6bWV014F519l3PMqef7Q8VKF6FFpybc9QnQdiiZLqeeb3l/f17ne+KsRQQ8eIjHxOHYWFny25E/6TloLL9uXUVeayt1veOnz3PTxw8bK8sUbRw7eY5JsxcxqHcXKpcvTWJiIvc+uhEfwJ9nL1GpXCmMjAyZv3wtB4+cZPKogRRwys/5K54MGjONLavmUbRQ8s39dqxZpHGvjnsPHtFz8Fjq166Rou3NO/ejkxE/kAwyvskIjbtW5y/kyNhtU7h86LwWo/q8yGpOaafVZGLKlCkYGhpy8eJFevbsyejRoyldujQjR44kOjqaxo0b/+MF2J8DpYEeJRpUYmPPeQRe8QPg2MI9FP2mHFU61uPIvF1ajjBzHDt6mmNHT2s7jCzXsVVvjeeD+43jVsA5SpUpxuULnlqKKvPl1PP9f4ZGhkxbNpEZw+fQfbC7tsPJdDn1fMv7+/MRExvL8dPnWDxrEhXKlASgf/eOnD5/mZ37DjGwV/L7MDT8OR4LVrBq/gz6jZio0UZCQiKzFq1kWP8e/ND4W3W5awGnFMc7efaiOhH47Y8/6eXelq+rVgKgbfPvuXT1Bhu272X2pJEAWJibaey/ZvMu8tvbUrFsSY1yv7v32bhjDzvXLqZWkw7/4SeScd5EvNZ43qRvC549DMH3ko+WIhJfMq0mE7q6uowdO1ajrG3btrRt21ZLEaWPQqlAoVSQ8NEdIONj4nCuWFhLUYmsYmpqAsCrl5FajkRkplEeQzh/4iJXznrmiGRCJJP3t/YkJiSSmJiEgb6eRrmBgT5eN5M/9CYlJTFm6ly6tG+Jm0vKBMH3bgCh4S/Q1dWhZZf+PI94SZGCrgzr352CLs7qeq/fvMXrpg8eE0YAEBcfj76+forjXr+Z+oft+Ph4Dh49Sec2zdHReT8G8S4mhpFTZjNuWH+sLC3S9XPIbAo9JdWb1+TwmgPaDkV8obR+n4nsIDYqhoeed/lmYAtMbczR0dWhbLPqOJUrhKm1mbbDE5lIR0eHKR6juHLJC3/f7D/1Jaeq3/QbipQsxNKZq7QdishC8v7WLmNjI0qXKMrKDdsJC39BYmIivx35E+/bfjx/HgHA2i2/oFDo0rFV01TbeBwcAsDytVvp7d6OZXOmYGqSm64DRhH5+o263tmLVynkWgAb6+RpUtUql2fTjr08evyUpKQkLlzx4sTpC4S/iEj1OCfOXOTN27c0+07zWpM5i1dTpkQx6tSo8p9/HpmlQv1KGJkac/qXz+uuytqm+oz/+9xIMpFBdgxZho6ODuOvLGfm3c1U6/ItNw5cIEmWFsvWZs4dT+GiBenXfbi2QxGZJK+dDcOmDWR8/2nEfTT6KLI3eX9rn8eE4aBSUadZR8rVbsLWX36lYd2a6Ojq4uN3jy2//MqMccM0RgM+pEpK/hvcy70N9WpXp3iRgkwfOwQdHTjy51l1vT/PXqJ29a/Uz0cP6o1Tfnsat+9F2VqNmTl/Oc0a1UNXJ/WPTXsPHqH6VxXUyQjAybOXuOzpzehBvVPd53NRu01dvE958Sose17fKTKfVqc5ZScRQWGsbDMVPUMDcuU25E34KzosHUhEUJi2QxOZZPqccdT9tiYtvnMnJDhU2+GITFKkVGEsrS3YcnSNukypVFL2q9K07tqCqk7faFyEKbIHeX9/Hhwd7Niw7Cei38UQFRWNtZUFwyZ44GCXDy/v20S8fEW9Hzqr6ycmJvHT0jVs3rWfo3s2Yv3X1CJXZ0d1HX19fRzsbAkJTf77HB8fz/nL1+jZuY26joW5GYtnTSQ2No5Xr19jY2XJghXrcLDLlyLG4GehXLp2g4Uzx2uUX/a8weOnIVRpoLmQzJBxMyhXujgbls757z+g/8jK3poS1UuxoLf2YxFfLkkmMlj8u1ji38ViaGpMoa9Lcdhjm7ZDEplg+pxxNGj0Da0ad+Fx0FNthyMy0dWz12hTq7NG2cSFY3gUEMTGpVslkciG5P39+TEyzIWRYS4iX7/hwhVPhvbrRr1a1fmqYlmNer2HjKdxgzo0+64+AMWKuKGvr0dg0FPKlS4BQHxCAk9DQrHLl7z0/BWvm5ia5KZIwZTLuRsY6JPX2or4hASOnTrPt3W+TlFn36FjWJjn4esqlTTKe3RqzQ9NGmiUNe/Ul5EDe1GrWuX0/zAyUM1WdYh8Ecn1P6/9c+UcRm5al3aSTGSQQl+XAh0dwu8HY+Wcj0Zj2xN2P5irv3xeq2NkJGNjI1xc31/w5uycn5KlivIyIpInT/7+ZoNfsplzJ9Cs5Xd0a/8jb99GY22TvDzhm9dviImJ1XJ0mSennu/oqHfc9w/UKIuJjuHVy8gU5dlJTj3f8v5O9rmc7/OXPVGpVDg7OhD0JJh5y9ZSwNGBZo3qo6dUYpbHVKO+UqnAysKcAk4OAOQ2NqZ10+9YvnYz+WyssMuXl/XbdgOoV246de4ytT6Y4gRw08eP0PAXFCnoQlj4C5av24JKpaJbB81RhqSkJPYfOkbThnVRKjVvmGtlaZHqRde2ea1THeHIajo6Onzdqg5nd58iKVG+FBHpJ8lEBsllYkTDkW3Jk8+C6Mi33Pr9Ckfm7iQpIVHboWWasuVKcviP7ernHrOTh3i3btlN394jtRVWpnPvnrza2J5DGzXKh/Qbx67t+7UQUdbIqec7p8qp51ve38k+l/P95m0UC1euJzT8OXlMTahXszoDe7ujp0z7x5dhA3qgUCoYM20usbGxlCxWhHWLZ5Hnr5W6Tp6/xLQxQzT2iY2LY8nPG3kS/AwjQ0NqVKmIx4QRmJrk1qh38ep1QkLDaN6o/n/vbBYrUb0U1g42nNp1QtuhiC+cjiobjuOMdG6n7RC0YmX4ZW2HoBUm+obaDkEr3sRl3xto/Z1CpvbaDkEr7r7OmdNt5P2ds7x4dDxLj3fHP4DuA0dz5tCOf5WgZDT38sO0dmxt2vYo5d3KPxflbKtrO4RP8go5p+0QNMhqTkIIIYTIkRITExkzpK9WEwkhvnTy7hFCCCFEjlSyWGFKFpObywrxX0gyIYQQQgghxAey4VUAmUamOQkhhBBCCCHSRZIJIYQQQgghRLrINCchhBBCCCE+kIRMc0orGZkQQgghhBBCpIskE0IIIYQQQoh0kWlOQgghhBBCfEAl05zSTEYmhBBCCCGEEOkiyYQQQgghhBAiXWSakxBCCCGEEB9IkpvWpZmMTAghhBBCCCHSRZIJIYQQQgghRLrINCchhBBCCCE+IKs5pZ2MTAghhBBCCCHSRZIJIYQQQgghRLpIMiGEEEIIIYRIF7lmQgghhBBCiA/I0rBpJyMTQgghhBBCiHSRZEIIIYQQQgiRLjLNSQghhBBCiA/I0rBpJyMTQgghhBBCiHSRZEIIIYQQQgiRLjLNSQghhBBCiA/Iak5ply2TiSsJ4doOQSui42O1HYJW5NR+5zU203YIWjFQ10nbIWhFt/gH2g5BiExXpaS7tkPQiou3Nmo7BCHSTaY5CSGEEEIIIdIlW45MCCGEEEIIkV6ymlPayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gOymlPayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gOymlPayciEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gMqVZK2Q/hiyMiEEEIIIYQQIl0kmRBCCCGEEEKki0xzEkIIIYQQ4gNJsppTmsnIhBBCCCGEECJdJJkQQgghhBBCpItMcxJCCCGEEOIDKpVMc0orGZkQQgghhBBCpIskE0IIIYQQQoh0kWlOQgghhBBCfEBWc0o7GZkQQgghhBBCpIskE0IIIYQQQoh0kWlOQgghhBBCfEBWc0o7GZkQQgghhBBCpIskE5/QzL0JOy5u4WjAYZb/toQiZQp/sm6DVvU59eS4xuNowGGNOm16t2LfjV/Yd+MXWvdqqbGtaNkirDq8HIVCTofIWu492nHJ+yj3Q7z47dh2ypQr+cm67Tu3ZO/hTfgEXsAn8AI79q1JUb/3gC543z2D990z9O7vrrGtbPmS/H5yFwqFIlP6khY2lQtTe8NQWnouofPTLeT/tvzf1ndsWIG620fR+uZy2vr9TMMDk7CrqdnnAs2r8sPVRbTxWUWFSR00thk7WNHs7E/o5TbM8L6ItOvZqxO37pwh7IUvf57aS/nypT5Zt0jRgmzeupxbd87wOuoB/fp3TVGndZum3PE/x6Mn15k5a5zGNkdHe7xunMDEJHeG9+Pfyqn9btWlOQeu7OJ84HE2HFpF8TJF07Rf/abfcC3kLHPXz9Qo79inLUdvHeDorQN06N1GY1vxssXYfGRNlv5ei4qKZtbCldRr4U752k3p0Hsot3z91dtLVGuY6mPd1t2fbHPZ2i0p6jdu11OjzpzFq6naoBXfNO/EwSN/amw78udZ+o+clLEdFV8MmeaUitqNa9FvYh/mj1mE73VfWvb4gZ+2zKJTza68evEq1X3evo6ic80u6ucfDo+5FC1A1+HujHEfj46ODh4bp3P1jCeBfoEoFLoM9RjM3FELSExMyuSeCfFek+YNmDR9JKOHTuG65y169OnE1j2r+Lri97x4HpGifpXqFfl1z2GuXb5BTGws/Qd1Z9ve1dSp0pRnIWEULV6IEWMG4N62Pzo6sGHHck6fvIDfnXsoFApmzZ/EyMGTSUxM1EJvkymNDHh5J4iAHWeovXbwP9a3+aoIIWduc33WL8S9jsKtTU1qbxjG799PIsLnEQbmuanyUw8uDF3Fm0fh1Nk0jJDzPjw9fgOAyjO74DVzJ/Fv32Vux8QntfihETNnjWXwoAlcu3qDfv27svfXjZQvW5fn4S9S1DcyNOThwyD27zuMx+zxKbZbWJqzZJkHfXuP4GHgY37Zu4Yzpy7yxx/JH67mL5zGpIlzePPmbab37e/k1H7Xa1KHIZMH4DFqHrev36Fdz1Ys2T6PH6q35+Un/n4D2DrkY9DEfnhduqFR7lbUlT4juzO40yh0dHRYsGk2l05f5b7fAxQKBWNnD2PGiJ+y9PfaxFmLCHjwEI+Jw7GxsuS3I3/Sc9BYft26irzWVpw6sFWj/tlL15josZB6tar9bbtuBZxYs+h9IvVhgnTq3CUOHTvF6gUzCHoSzISZC6hWuTzmZnl48zaKxas3smbhzNSa/WIlyTSnNJOvwlPRqtcPHNp+mD92HeHRvSDmj15ITEws37Vt8OmdVCoiwl+qHy+fv1JvcnR15IFvINcv3MDr/HXu+z7A0TU/AG36tMH78k38vf0/0bAQmaNnP3e2bdrNrm37ued/n9FDp/AuOoa2HVukWv/HXqPYuHYHPrf9uH8vkOEDJ6Kro0v1r78CwK1gAXx97nL+7GXOnbmMr89d3AoWAKDvwK5cunAN7+u3s6x/qQk+eZMbc3bz+I9raap/bdIWfFYc4oX3A94EhnJ91i7eBD7DoV5ZAHI72RD/JpqHBy7zwvsBoRd8MXOzB8C5aRVUCYkE/Z62Y4nMMeDH7mxcv5Otm3fj7xfA4IHjeffuHZ06t0q1vpfXTSaMm8We3QeJjY1Lsb2Ac35ev37D3j2H8PK6yZnTlyhUxBWAlq0aEx8fz28HjmRqn9Iip/a7Q+827N/6G7/tPEzg3Yd4jJxLzLsYmrRr9Ml9dHV1mb5sIqvnruPpoxCNbc5ujty7c59r5724es6TAN/7OLs5AtCpXzu8Lntzx9svU/v0oZjYWI6fPsfQ/t2pUKYkjg529O/eEUcHO3buOwSAlaWFxuPk2UtUKleK/Pa2f9u2QqHQ2M/cLI9624NHj6lYtiQlihbiu3q1MDY24knIMwDmL19Lm2aNsM1nk3kdF581SSY+otRTUrhkITzPeqnLVCoVnme9KFau2Cf3MzQ2ZMelrey6so3pa6fiXMhJve2BXyAOLvbY2NmQ196G/AUcCPR/iJ2TLQ3bfMvaOesztU9CfExPT49SZYpx9tRFdZlKpeLc6UuUr1g6TW0YGuVCqafk1atIAHzv3KOAmzN2DrbY57fFxc0JP98AnJzz06Z9c+bMWJwpfclSOjro5c5F7KsoAN4EPkNhaIBFcSf0zYyxLO3CS98g9PMYUWZESy6P36jlgHM2PT09ypQtwcmT59VlKpWKUyfPU6lS2XS1ef/+QwwNc1GqdDHMzfNQrnwpfG77YWZmyvgJQxg+dHLGBP8f5NR+K/WUFClViMtnPdVlKpWKK2evUap88U/u12NoFyJevOTX7YdSbAvwe4CjS37y2tuQzyEvji75ue8fiL2THY3bfMeKWT9nSl8+JTEhkcTEJAz09TTKDQz08brpk6L+84iXnLlwhRbff/uPbQc9eUrtJh1o0KoroybPJuRZmHpbYTcXfPzuEfn6DT5+94iNjcXR3g4v79vc8Q+gQ6sm/71z4osl05w+ksciDwqlgojwlxrlL5+/xNEtf6r7BN1/zOxhc3ng+wBjU2Pa9G7F0v2L6fpNd8JDnhMUEMSaWeuYu302AD/PWktQQBDzts9h1YzVVKpVgS5DOpOQkMiSScu4eflWpvdT5GwWlmYolcoU0x3Cw1/g+tdowj8ZN3kYoc/C1AlJwN0HzJ62kB17k/+4zpq6kIC7D9ixbw3TJ82jVp3qDB3dj4T4BCaO8eDyBc+/a/6zVLzPdyiNcvHot8sAxEVGc37wKqot6oMilz4Pdp8j+PQtqsztgf+Go+TOb02d9UPRUSrwnr+XoENXtdyDnMXS0hylUkl42HON8rCw5xQq5JquNl+9ek2fXiNY9fM8DHMZsGPbPk4cP8vS5bNYvWozTs4O7PhlNXp6SjxmLObX/b9nRFf+lZzabzOLPCiVSiLCNadpRoS/xNnNKdV9SlcqSdN2jWhfr1uq2x/ee8TyWatZvmMBAMs8VvHw3iOW7VzA4ukrqFKrMr2GdyUhPoG5Exdz/ZJ3xnbqI8bGRpQuUZSVG7bj4uSIpYUZh4+fxvu2H46pjDwc+P04RkaG1K3591OcShUrzPRxw3B2dOD5iwiWr9tK534j2L95BcbGRlSrXJ7vv61D2x6DyGVgwIzxwzAyzMW0ucuYPm4oO/cdYtvuA5iZ5WHyyIG4uaT+8/6SqOSmdWkmyUQGuOPlyx0vX/Xz29d82HRqHY07fM+6uRsAOLDlIAe2HFTX+bZlPaKjovHxvMPm0xvo/X1/rG2tmLhsHO2qdiI+Lj6ruyFEmvUf3IMmLRrSqnEXjSkRm9fvYvP6Xernrdo25e3bKDyvenPm6kEa1WmDrV0+lq+ZS5Uy9Yn7gl7nBZpVodTQ5pzqtoCYF6/V5Y//uKYxbSrvV0UwL+rIlfGbaH5+Hmf7L+NdeCTfHZxC2CV/jX3Fl+ngb0c5+NtR9fNq1StRokQRRgybzI1bJ+nWZRChoeGcPL2f8+evpHqNwpcou/XbyNiQqUvGM2PEHCIjIj9Zb8+mX9mz6Vf180atGhAdFc2ta7fZc24rnRv2wsbWmpkrJtOkcutM//vtMWE4Ez0WUKdZRxQKXYoWcqNh3Zrc8Q9IUXffwaN8X782Bgb6f9tmjSoV1f8u7FaAksUKU/8Hd/748yw/NE4e1ejfvSP9u3dU11u+bitfVSiDUqlk1cYd7Nu0nNMXrjB2+lx2rVuSQb0VXwJJJj4SGRFJYkIiFtbmGuXmVuZEhL38xF6aEhMSuXc7AHtnu1S35zE3xX1IZwa1HELRskV5HPiEp4FPeRr4FKWeEgcXBwL9Av9zX4T4lIgXr0hISMDK2lKj3NraMsW3mR/rPaAL/Qd3p22zHvj63P1kPXMLM4aM6ssPjdwpW6EUDwIeEfggiMAHQejpKXFxc8bvzr0M6U9mc27yFVXm9uB07yWEnE05leD/dPWVVJ7ZhXMDV2JSIC86Sl1CLyXPp3794BlW5Vx5cux6VoWd47148ZKEhASsbaw0ym1srAgNDc+QY+jr6zN/wVR69RyGi6szSqWC8+euAHA/IJAKFUrzx+9//kMrGSun9vtVRCQJCQlYWFtolFtYm/MiLGVi4+Bsj72jHfM3zlKX6eomz/6+9PgkP1TvwNNHwRr75LHIQ89hXenVfAAlyhUj6MFjHgc+4XHgE5R6yuRpUH4PMqF37zk62LFh2U9Ev4shKioaaysLhk3wwMEun0Y9zxu3CQx6wk9Tx/zrY5ia5MYpvz1BT4JT3f7g0WMOHvmT3euXsvfQUSqUKYGFuRnf1vmaCTMXEBUVjbGxUbr6J748cs3ERxLiE/C/dZdy1cupy3R0dChfvSx3vO6kqQ1dXV1cihTgRVjKFXEA+k/uyy9r9hAe8hxdhS5K5fucTqFQoNCV0yIyV3x8PDdv3KF6za/UZTo6OlT/ujKeVz89TN93YDcGj+hDx5a9uXnj0x+qAabMHMXPyzcREhyKQlcXPb0PXudKBQpd7S0R+284N61C1fm9ONtvGU9P3PjbuqUGNePpqZtE3H6Irq4uuh+shqKrp0BH3ttZKj4+nhvXb1OrVlV1mY6ODjVrVeXKlYxJ6kaO6s/x42fwvuGDQqGLUvH+da7UU2plKeSc2u+E+AT8bt6lUvX3Sz7r6OhQsXp5bnqm/H31MCCINrU606FuN/XjzNHzXDt/nQ51uxEaHJZin2FTfmT76l2EhYSn/vc7C5d4NzLMhbWVBZGv33Dhiid1anylsX3vwSMUK1yQIgVd/nXb0dHvePw0BGsrixTbVCoVU+csZuSPPTEyMiQpMYn4hAQAEv76f2LSl786pUql+mwfnxsZmUjFL6v3MGbBSPy9/fG94U/LHi3IZZiL33f+AcCYhaN4/uw5P89aC0DnwR254+XL04fB5DY1pm2f1uR1yMuh7YdTtF2+RjkcXBzwGDwHAH9vfxzd8lOpdkVs7GxISkoi6MHjrOusyLF+Xr6RBctncvO6D9e9btGzbycMjQ3ZuXUfAItWzCQkJIxZUxcC0G9Qd4aPGcCAniN5HBSs/tYzKiqa6KhojbZr1KpCAVdnBvUdC4D39du4FixA7brVsbO3JSkxifsBWT/6pjQywKRAXvXz3I7WmBd3JO5lFFHBLyg7ujVGtuacH7QKSJ7aVG1hb65O2kL49fvksk5e3SQxJo74N5rLveYpaIdzk8ocrJ+8rGbk/WBUKhVubWvyLjySPK62PPfO3G8sRUpLl6xl5eq5XL9+i2vXvOnXvytGRkZs2Zy85v6qn+cSHBzKlEk/AckXLxcp6gaAvr4etnZ5KVmqKFFvo3nw4JFG24WLuNHih++pXvV7AO763ycpKYlOnVsTFhpOoUKueHnezMLevpdT+7111U4mLxrLHW8/fG740r5nKwyNDPltR/Lf4ymLxxH27DnLZq4iLjaO+/6av4feRCYvbftxOUDlryvg6JKfSQNnAHDnhh9Obk5UrVOZvHY2JCUl8uh+UCb3EM5f9kSlUuHs6EDQk2DmLVtLAUcHmjWqr67zNiqKoyfPMnxAz1Tb6D5wNN98XZX2LZMvnP5p6c/UqlYZu3x5CXv+gmVrtqBQ6PJd3Zop9t3z2x+Ym+WhVvXk5KVsqWIsX7cF79u+nL10DVdnR0w/g/uNiKwjyUQqTv52CjPLPHQd3gULa3MC7txnZKcx6uVe89rboPog6zbJY8LwOUOxsDbnbeRb/G/do3/TQTy6p/lLRT+XPoOm/8jUvtPVmWV4yHMWT1jK6HkjiIuLx2PwHOJiUi7LJ0RGO7DvDyysLBg+dgDWNlb43PKjY8ve6nnOdg62JCW9/wakc7c2GBjo8/OmhRrtzJu1jPmzl6uf58plwIw54+jbbbj6dR4SHMqEUTOZv3QGcXFxDO43lpiY2Mzv5EcsS7vw7e73N9uqODl5/m/ArjNcGLIaw7xmGNu9nxpSsEMddPWSpy5VntlFXf7/+h+qMqc7V6dsJeFdcr8SY+I5P2QVlWd0QaGv5PL4Tbx7lrapkiLj7N1zCCsrC8aOH0LevFbcuunLD826qKfzOTjYkfTB73NbWxvOX3y/qs+gwb0YNLgXZ89colHD9hptL14yk7GjZxAdnZxYxsTE0rf3SOYumIKBgT7Dh04iJCQ0C3qZUk7t97EDf2JuaUafkd2xtLbgrk8AP7YfTsTz5PdePvu8Gr/X0soglz4jZwxhTJ9J6t9rYSHh/DR+IRMXjCE+Lp5JA2cSmwV/v9+8jWLhyvWEhj8nj6kJ9WpWZ2Bvd/Q+GCX5/fhpVCr4rl6tVNt4/DSEl5Hvr98KDXvOyEmzefX6NRZmeShbqjhbVy3AwtxMY7/nES9ZvXEHW1bOV5eVLFYY97Yt6DdiEhbmZswcPyxD+ys+fzqqz3G85D+q5VBX2yFoxbkw33+uJLKNvMZm2g5BKzyM0re05ZeuW/hJbYegFUZ6BtoOQWShQqb22g5BKy7eypnLSOtZ/fspWFnFOk9hbYfwSeGRn9e9ybQ6MhESEsKKFSs4d+4cISEhydcauLjQrFkzunTpopU5l0IIIYQQQoi00drVgNeuXaNo0aIcPnyY+Ph47t27R/ny5TE2Nmb48OF8/fXXvHnz5h/biY2N5fXr1xqPJNWXf+GPEEIIIYQQnzutJRODBw9myJAhXLt2jbNnz7Jhwwbu3r3Ljh07ePDgAdHR0YwfP/4f2/Hw8CBPnjwaj6A3DzO/A0IIIYQQIlvS9opNX9JqTlpLJry8vOjUqZP6efv27fHy8iI0NBRzc3PmzJnD7t27/7GdMWPGEBkZqfFwNHHOxMiFEEIIIYQQoMVrJmxsbAgJCcHFJfnim9DQUBISEjA1NQWgYMGCRESkfp+GDxkYGGBgoHmBnq6OrOUuhBBCCCFEZtPap+5mzZrRp08f/vjjD06ePEmHDh2oWbMmhoaGAPj7+2Nv/2Ws6tBlaGdOPTmu8dh0ap22wxIiQw0Y0oNDJ3biH3QF77tnWLtlMa5uztoOK8PZVC5M7Q1Daem5hM5Pt5D/2w9ugKVUUG5sGxof96DdvTW09FxCtUW9Mcxrpr2ARYaqWq0iO3/5Gf+Ai7yOekCj7+tpO6QskVP7/TH3AR24FnKWoVN/zNLjRkVFM2vhSuq1cKd87aZ06D2UW77vV+yJjn7HjHnL+aZZR8rXbkqTDr3Yue9Qqm2pVCr6DJtAiWoNOXHmQortwc9CKV+7KdHR7wh48IjBY6dT/wd3SlRryOad+1Jtc/ue36j/gzvlajehXc/B3LqjuZpQbGwc0+cto1rD1lSs25zBY6fzPEJzKexL167TofdQKtVtQc3G7Zm/fK36JnefoySV6rN9fG60lkxMnz6dYsWK0bhxY7755htiY2NZt+79B3AdHR08PDy0Fd6/FugXSIuyrdSPH5sP1nZIQmSor6pWZOOa7TSu3452LXqip6dk296fMTQy1HZoGUppZMDLO0FcHpdyqUaloT4WJZ25uWg/hxpM4FTPhZi62FJ7/VAtRCoyg7GxEbdv+TJsyCRth5Klcmq/P1SsdBFadGrCXZ+ALD/2xFmLuHj1Oh4Th7Nv8wqqVipHz0FjCQ1Pvi/InCWrOXf5Gh4TR3Jg22o6tW7GzAXLOXn2Uoq2Nu/cj87fHOvPs5eoVK4URkaGvIuNwcEuH4P7dsXK0jzV+r8fP82cJavp260Dv6xbQmG3AvQeOp4XL1+p68xevIpT5y8zf/pYNiydQ/jzFwweO1293e/eA/oOn0j1yuXZvWEpc6eO5uS5y8ybNy9dPy/xedHaNKfcuXOzc+dOYmJiSEhIIHduzbsl1q9f/xN7fp4SExOJCJcbUonsq2Or3hrPB/cbx62Ac5QqU4zLFzy1FFXGCz55k+CTqd+9N/7NO463m61RdmX8JhodnoqxnSVRwS+yIkSRiY4dPc2xo6e1HUaWy6n9/j9DI0OmLZvIjOFz6D7YPUuPrULF8dPnWDxrEhXKlASgf/eOnD5/mZ37DjGwlzs3bvnStGFdKpUrBUCrpt/xy6+/c8vXn9o1vlK35Xf3Pht37GHn2sXUatIh1eOdPHuR+rVrAFCyaGFKFk2+n8LCFetTrb9p5z5aNm5I87/usD1xxI+cuXCVfQeP0qNTa968jWLvwaPMmTySyuXLADBt3FCatO+F921fSpcoyh8nzlDItQB9uyXH5Ohgx7B+3Rg2cRb9+/dP8RlQfFm0fnFBrly5ssWLyL6APbuv7WDb+c2MWzIGGzsbbYckRKYyNTUB4NXLSC1Hol36poaokpKIex2t7VCEEOk0ymMI509c5MpZbXwxoiIxMQkDfT2NUgMDfbxu+gBQpmRRTp67RGj4c1QqFVc8vXkY9JSqlcqp67+LiWHklNmMG9YfK0uLVI/0+s1bvG76ULv6V6lu/1h8fDx3/O/xVcUy6jJdXV2+qlAG79vJN8q943+PhIQEvqrw/oaiLk75sc1rg/dtP3U7Bvr6H/XPgNjYWHx8fNIUS1bT9opNsppTDnPnui+zhvzEyE5jWDB2Ebb587F47wIMjbPX9A8h/k9HR4cpHqO4cskLf9+snxLwudA10KPc2LYE7r9I/Nt32g5HCJEO9Zt+Q5GShVg6c5VWjq+DLqVLFGXlhu2Ehb8gMTGR3478ifdtP54/T16IZuyQvrg6O/JNs06UrdmY3sPGM25YP/VIBsCcxaspU6IYdWpU+eSxzl68SiHXAthYW6YptpevXpOYmISlheYUKEsLc/U1Ec9fvERPT4mpSe6P6pjx/K+FdKpWKseN274cPnaKxMREQsOfs3L9NgDCw8PTFIv4fGn1DtjZxZWTV9X/fuAbiO91X3Zc2kbtxjU5vOMPLUYmROaYOXc8hYsWpHnDTv9cOZvSUSqoufJH0NHh8pgN2g5HCJEOee1sGDZtIP3bDCUuNk5rcXhMGM5EjwXUadYRhUKXooXcaFi3Jnf8k7+s2br7ADd9/Fg6exK2+fLieeMWM+Ytx8bKkioVy3Ly7CUue3qze/3Svz3On2cvpXlUIiNVq1yeYf27M/WnJYyZ9hP6enr07tIeT+/b6OrK99pfOkkmMsHb11E8efAEe+cvYzUqIf6N6XPGUffbmrT4zp2Q4FBth6MV/08kjB0sOdbaQ0YlhPhCFSlVGEtrC7YcXaMuUyqVlP2qNK27tqCq0zckJSVlehyODnZsWPYT0e9iiIqKxtrKgmETPHCwy0dMbCyLVm1kkccEalatBEBhtwL43XvAhu17qFKxLJc9b/D4aQhVGrTUaHfIuBmUK12cDUvnEB8fz/nL1+jZuU2a4zI3M0Wh0OXFRyszvYh4idVfoxVWlubExyfw+s1bjdGJFxGvsLJ4P93KvW0LOrdpTvjzCExNc/M0JJSFK9fj4ODwr39eWSGJz2860edKkolMYGiUCztnW47ulYsxRfYyfc44GjT6hlaNu/A46Km2w9GK/ycSJgXycrTVTGJfvtV2SEKIdLp69hptanXWKJu4cAyPAoLYuHRrliQSHzIyzIWRYS4iX7/hwhVPhvbrRkJCAgkJCejqaK7RpFDoquPr0ak1PzRpoLG9eae+jBzYi1rVKgNwxesmpia5KVLQJc3x6OnpUaxwQS5fu8E3X1cFICkpicueN2j3QxMAihUuiFKp5PK1G9SrXR2AwEdPCAkNo3SJIhrt6ejoqKdY/X7sFLa2thQvXjzN8YjPkyQTGaDv+F5cOH6J0CehWOa1pOswd5ISkzix/6S2QxMiw8ycO4FmLb+jW/sfefs2GmsbKwDevH5DTEyslqPLOEojA0wK5FU/z+1ojXlxR+JeRhEd9opaqwdiUdKZP93noaPQJZd1HgDiXr0lKT5RW2GLDGJsbISLq5P6ubNzfkqWKsrLiEiePAnWYmSZK6f2OzrqHff9AzXKYqJjePUyMkV5Zjp/2ROVSoWzowNBT4KZt2wtBRwdaNaoPnpKJRXKlmTesrUYGBhgl8+Ga9dvceD3E4wY2BMAK0uLVC+6ts1rjYNdPgBOnbtMrY+mOMXHx3M/MOivfycQGv4Cv7v3MTIyxNHBDoDObZozbsY8ihcpSIlihdmyaz/vYmJp1ij5XiQmuY1p8X195iz5mTymJhgbGzFzwQpKlyhK6RJF1cdat3U31b8qj66OLsdPn2fNll9YtGgRCoUi43+gIktJMpEBrG2tmbB0LKbmpkRGRHLrym36NfmRyIicvcqNyF7cu7cFYM8hzfsvDOk3jl3b92shosxhWdqFb3ePUz+vOLkjAAG7zuA9b6/6JnaNj83U2O9IyxmEXvTNukBFpihbriSH/9iufu4xezwAW7fspm/vkdoKK9Pl1H5/Lt68jWLhyvWEhj8nj6kJ9WpWZ2Bvd/SUyR/T5k4ZzcKVGxg9ZQ6Rr99gl8+Ggb3dadOsUZqPcfL8JaaNGaJRFvY8gpZdB6ifb9i+hw3b91ChbEk2LJ0DQMO6NXn5KpKla7bwPCKCIgVdWTlvmnqaE8Cogb3R1dVl8LjpxMfHU7VSeSYM769xrHOXrvHzph3ExcVT2K0AS2ZNpE7duv/6Z5VVPsdVkz5XOqps+NOq5fD5vjgz07kw+SCTk+Q1NtN2CFrhYVT2nytlQ93Cc+ZIp5GegbZDEFmokGnOvNbw4q2UN8nMSHf8A+g+cDRnDu1QJyifAz2rtE+5ymqmxp9vbK+jHmg7BA1yCb0QQgghRDaWmJjImCF9P6tEQmQf8qoSQgghhMjGShYrTMlihbUdxhclKftN3Mk0MjIhhBBCCCGESBdJJoQQQgghhBDpItOchBBCCCGE+IBKblqXZjIyIYQQQgghhEgXSSaEEEIIIYQQ6SLTnIQQQgghhPiArOaUdjIyIYQQQgghhEgXSSaEEEIIIYQQ6SLTnIQQQgghhPiASqY5pZmMTAghhBBCCCHSRZIJIYQQQgghRLrINCchhBBCCCE+IDetSzsZmRBCCCGEEEKkiyQTQgghhBBCiHSRaU5CCCGEEEJ8QFZzSjsZmRBCCCGEEEKkiyQTQgghhBBCiHSRaU5CCCGEEEJ8QKY5pZ2MTAghhBBCCCHSRZIJIYQQQgghsqlly5bh7OxMrly5qFy5MleuXMnQ9iWZEEIIIYQQ4gOqz/jxb+zcuZOhQ4cyadIkvLy8KF26NN9++y1hYWH/sqVPk2RCCCGEEEKIbGj+/Pn07NmTrl27UqxYMVauXImRkRHr1q3LsGNIMiGEEEIIIcQXIjY2ltevX2s8YmNjU9SLi4vD09OTunXrqst0dXWpW7cuFy9ezLiAVCLDxMTEqCZNmqSKiYnRdihZSvot/c4JpN/S75xA+i39Fp+/SZMmpZj9NGnSpBT1nj59qgJUFy5c0CgfMWKEqlKlShkWj45KJWtfZZTXr1+TJ08eIiMjMTU11XY4WUb6Lf3OCaTf0u+cQPot/Rafv9jY2BQjEQYGBhgYGGiUBQcHY29vz4ULF6hSpYq6fOTIkZw+fZrLly9nSDxynwkhhBBCCCG+EKklDqmxsrJCoVAQGhqqUR4aGkq+fPkyLB65ZkIIIYQQQohsRl9fn/Lly3PixAl1WVJSEidOnNAYqfivZGRCCCGEEEKIbGjo0KG4u7tToUIFKlWqxMKFC4mKiqJr164ZdgxJJjKQgYEBkyZNStPQU3Yi/ZZ+5wTSb+l3TiD9ln6L7KVNmzaEh4czceJEnj17RpkyZfjjjz/Imzdvhh1DLsAWQgghhBBCpItcMyGEEEIIIYRIF0kmhBBCCCGEEOkiyYQQQgghhBAiXSSZEEIIIYQQQqSLJBMZaNmyZTg7O5MrVy4qV67MlStXtB1Spjpz5gyNGzfGzs4OHR0d9u/fr+2QsoSHhwcVK1bExMQEGxsbmjVrhr+/v7bDynQrVqygVKlSmJqaYmpqSpUqVfj999+1HVaWmzVrFjo6OgwePFjboWSqyZMno6Ojo/EoUqSItsPKEk+fPqVjx45YWlpiaGhIyZIluXbtmrbDylTOzs4pzreOjg79+/fXdmiZKjExkQkTJlCgQAEMDQ1xdXVl2rRp5IS1ad68ecPgwYNxcnLC0NCQqlWrcvXqVW2HJb5AkkxkkJ07dzJ06FAmTZqEl5cXpUuX5ttvvyUsLEzboWWaqKgoSpcuzbJly7QdSpY6ffo0/fv359KlSxw7doz4+Hjq169PVFSUtkPLVA4ODsyaNQtPT0+uXbtGnTp1aNq0KT4+PtoOLctcvXqVVatWUapUKW2HkiWKFy9OSEiI+nHu3Dlth5TpXr58SbVq1dDT0+P333/nzp07zJs3D3Nzc22HlqmuXr2qca6PHTsGQKtWrbQcWeaaPXs2K1asYOnSpfj6+jJ79mzmzJnDkiVLtB1apuvRowfHjh1j8+bN3Lp1i/r161O3bl2ePn2q7dDEl0YlMkSlSpVU/fv3Vz9PTExU2dnZqTw8PLQYVdYBVPv27dN2GFoRFhamAlSnT5/WdihZztzcXLVmzRpth5El3rx5oypYsKDq2LFjqpo1a6oGDRqk7ZAy1aRJk1SlS5fWdhhZbtSoUarq1atrOwytGzRokMrV1VWVlJSk7VAyVaNGjVTdunXTKGvRooWqQ4cOWoooa0RHR6sUCoXq4MGDGuXlypVTjRs3TktRiS+VjExkgLi4ODw9Palbt666TFdXl7p163Lx4kUtRiayQmRkJAAWFhZajiTrJCYmsmPHDqKioqhSpYq2w8kS/fv3p1GjRhrv8+zu3r172NnZ4eLiQocOHQgKCtJ2SJnuwIEDVKhQgVatWmFjY0PZsmX5+eeftR1WloqLi2PLli1069YNHR0dbYeTqapWrcqJEye4e/cuAN7e3pw7d46GDRtqObLMlZCQQGJiIrly5dIoNzQ0zBEjkCJjyR2wM8Dz589JTExMcTfBvHnz4ufnp6WoRFZISkpi8ODBVKtWjRIlSmg7nEx369YtqlSpQkxMDLlz52bfvn0UK1ZM22Fluh07duDl5ZWj5hNXrlyZDRs2ULhwYUJCQpgyZQo1atTg9u3bmJiYaDu8TPPgwQNWrFjB0KFDGTt2LFevXmXgwIHo6+vj7u6u7fCyxP79+3n16hVdunTRdiiZbvTo0bx+/ZoiRYqgUChITExkxowZdOjQQduhZSoTExOqVKnCtGnTKFq0KHnz5mX79u1cvHgRNzc3bYcnvjCSTAjxH/Tv35/bt2/nmG9yChcuzI0bN4iMjGT37t24u7tz+vTpbJ1QPH78mEGDBnHs2LEU3+JlZx9+M1uqVCkqV66Mk5MTu3btonv37lqMLHMlJSVRoUIFZs6cCUDZsmW5ffs2K1euzDHJxNq1a2nYsCF2dnbaDiXT7dq1i61bt7Jt2zaKFy/OjRs3GDx4MHZ2dtn+fG/evJlu3bphb2+PQqGgXLlytGvXDk9PT22HJr4wkkxkACsrKxQKBaGhoRrloaGh5MuXT0tRicw2YMAADh48yJkzZ3BwcNB2OFlCX19f/a1V+fLluXr1KosWLWLVqlVajizzeHp6EhYWRrly5dRliYmJnDlzhqVLlxIbG4tCodBihFnDzMyMQoUKERAQoO1QMpWtrW2K5Lho0aLs2bNHSxFlrUePHnH8+HH27t2r7VCyxIgRIxg9ejRt27YFoGTJkjx69AgPD49sn0y4urpy+vRpoqKieP36Nba2trRp0wYXFxdthya+MHLNRAbQ19enfPnynDhxQl2WlJTEiRMncsx88pxEpVIxYMAA9u3bx59//kmBAgW0HZLWJCUlERsbq+0wMtU333zDrVu3uHHjhvpRoUIFOnTowI0bN3JEIgHw9u1b7t+/j62trbZDyVTVqlVLsdTz3bt3cXJy0lJEWWv9+vXY2NjQqFEjbYeSJaKjo9HV1fwopFAoSEpK0lJEWc/Y2BhbW1tevnzJkSNHaNq0qbZDEl8YGZnIIEOHDsXd3Z0KFSpQqVIlFi5cSFRUFF27dtV2aJnm7du3Gt9SBgYGcuPGDSwsLHB0dNRiZJmrf//+bNu2jV9//RUTExOePXsGQJ48eTA0NNRydJlnzJgxNGzYEEdHR968ecO2bds4deoUR44c0XZomcrExCTF9TDGxsZYWlpm6+tkhg8fTuPGjXFyciI4OJhJkyahUCho166dtkPLVEOGDKFq1arMnDmT1q1bc+XKFVavXs3q1au1HVqmS0pKYv369bi7u6NU5oyPB40bN2bGjBk4OjpSvHhxrl+/zvz58+nWrZu2Q8t0R44cQaVSUbhwYQICAhgxYgRFihTJ1p9bRCbR9nJS2cmSJUtUjo6OKn19fVWlSpVUly5d0nZImerkyZMqIMXD3d1d26FlqtT6DKjWr1+v7dAyVbdu3VROTk4qfX19lbW1teqbb75RHT16VNthaUVOWBq2TZs2KltbW5W+vr7K3t5e1aZNG1VAQIC2w8oSv/32m6pEiRIqAwMDVZEiRVSrV6/WdkhZ4siRIypA5e/vr+1Qsszr169VgwYNUjk6Oqpy5cqlcnFxUY0bN04VGxur7dAy3c6dO1UuLi4qfX19Vb58+VT9+/dXvXr1StthiS+QjkqVA27zKIQQQgghhMhwcs2EEEIIIYQQIl0kmRBCCCGEEEKkiyQTQgghhBBCiHSRZEIIIYQQQgiRLpJMCCGEEEIIIdJFkgkhhBBCCCFEukgyIYQQQgghhEgXSSaEEEIIIYQQ6SLJhBBCfGa6dOlCs2bN1M9r1arF4MGDszyOU6dOoaOjw6tXr7L82EIIIb4MkkwIIUQadenSBR0dHXR0dNDX18fNzY2pU6eSkJCQqcfdu3cv06ZNS1NdSQCEEEJkJaW2AxBCiC9JgwYNWL9+PbGxsRw+fJj+/fujp6fHmDFjNOrFxcWhr6+fIce0sLDIkHaEEEKIjCYjE0II8S8YGBiQL18+nJyc6Nu3L3Xr1uXAgQPqqUkzZszAzs6OwoULA/D48WNat26NmZkZFhYWNG3alIcPH6rbS0xMZOjQoZiZmWFpacnIkSNRqVQax/x4mlNsbCyjRo0if/78GBgY4Obmxtq1a3n48CG1a9cGwNzcHB0dHbp06QJAUlISHh4eFChQAENDQ0qXLs3u3bs1jnP48GEKFSqEoaEhtWvX1ohTCCGESI0kE0II8R8YGhoSFxcHwIkTJ/D39+fYsWMcPHiQ+Ph4vv32W0xMTDh79iznz58nd+7cNGjQQL3PvHnz2LBhA+vWrePcuXNERESwb9++vz1m586d2b59O4sXL8bX15dVq1aRO3du8ufPz549ewDw9/cnJCSERYsWAeDh4cGmTZtYuXIlPj4+DBkyhI4dO3L69GkgOelp0aIFjRs35saNG/To0YPRo0dn1o9NCCFENiHTnIQQIh1UKhUnTpzgyJEj/Pjjj4SHh2NsbMyaNWvU05u2bNlCUlISa9asQUdHB4D169djZmbGqVOnqF+/PgsXLmTMmDG0aNECgJUrV3LkyJFPHvfu3bvs2rWLY8eOUbduXQBcXFzU2/8/JcrGxgYzMzMgeSRj5syZHD9+nCpVqqj3OXfuHKtWraJmzZqsWLECV1dX5s2bB0DhwoW5desWs2fPzsCfmhBCiOxGkgkhhPgXDh48SO7cuYmPjycpKYn27dszefJk+vfvT8mSJTWuk/D29iYgIAATExONNmJiYrh//z6RkZGEhIRQuXJl9TalUkmFChVSTHX6vxs3bqBQKKhZs2aaYw4ICCA6Opp69epplMfFxVG2bFkAfH19NeIA1ImHEEII8SmSTAghxL9Qu3ZtVqxYgb6+PnZ2diiV73+NGhsba9R9+/Yt5cuXZ+vWrSnasba2TtfxDQ0N//U+b9++BeDQoUPY29trbDMwMEhXHEIIIQRIMiGEEP+KsbExbm5uaapbrlw5du7ciY2NDaampqnWsbW15fLly3z99dcAJCQk4OnpSbly5VKtX7JkSZKSkjh9+rR6mtOH/j8ykpiYqC4rVqwYBgYGBAUFfXJEo2jRohw4cECj7NKlS//cSSGEEDmaXIAthBCZpEOHDlhZWdG0aVPOnj1LYGAgp06dYuDAgTx58gSAQYMGMWvWLPbv34+fnx/9+vX723tEODs74+7uTrdu3di/f7+6zV27dgHg5OSEjo4OBw8eJDw8nLdv32JiYsLw4cMZMmQIGzdu5P79+3h5ebFkyRI2btwIQJ8+fbh37x4jRozA39+fbdu2sWHDhsz+EQkhhPjCSTIhhBCZxMjIiDNnzuDo6EiLFi0oWrQo3bt3JyYmRj1SMWzYMDp16oS7uztVqlTBxMSE5s2b/227K1asoGXLlvTr148iRYrQs2dPoqKiALC3t2fKlCmMHj2avHnzMmDAAACmTZvGhAkT8PDwoGjRojRo0IBDhw5RoEABABwdHdmzZw/79++ndOnSrFy5kpkzZ2biT0cIIUR2oKP61FV+QgghhBBCCPE3ZGRCCCGEEEIIkS6STAghhBBCCCHSRZIJIYQQQgghRLpIMiGEEEIIIYRIF0kmhBBCCCGEEOkiyYQQQgghhBAiXSSZEEIIIYQQQqSLJBNCCCGEEEKIdJFkQgghhBBCCJEukkwIIYQQQggh0kWSCSGEEEIIIUS6/A8jv+jawj5/GAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", @@ -1331,7 +1150,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": { "tags": [] }, @@ -1374,7 +1193,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1423,30 +1242,9 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "visualize_integrated_gradients(test_dataset[0], model_clean, \"Clean Model on Clean 7\")\n", "visualize_integrated_gradients(tainted_test_dataset[0], model_clean, \"Clean Model on Tainted 7\")" @@ -1498,32 +1296,11 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, \"Tainted Model on Tainted 7\")\n", "visualize_integrated_gradients(test_dataset[0], model_tainted, \"Tainted Model on Clean 7\")" @@ -1578,50 +1355,9 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "visualize_integrated_gradients(test_dataset[6], model_clean, \"Clean Model on Clean 4\")\n", "visualize_integrated_gradients(tainted_test_dataset[6], model_clean, \"Clean Model on Tainted 4\")\n", @@ -1753,7 +1489,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1774,90 +1510,9 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAB/CAYAAACQeNq9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAbcUlEQVR4nO2da7CWZfXGlyGUhxARUA7hAY2TCSgopOQBQlFOHoBEKXTUTMtRa0L70ORMk2ZaMzGlwpgzgInFQShOgQKKCCKo4E5BBAxIJZE8USpCH/7zf1zX73Vv9ta9xXdz/T7d19zvft/nPTw3N/da61r77d69e3cYY4wxZp/mC3v7Aowxxhiz9/GGwBhjjDHeEBhjjDHGGwJjjDHGhDcExhhjjAlvCIwxxhgT3hAYY4wxJrwhMMYYY0xE7F/dB+633351eR2mlqkLv6mRI0eKfv/990U3adJE9Be/+MVifMwxx8jc5MmTRXfo0EF0RUWF6KOPPlr0f/7zH9ENGjQoxo0bN5Y56ueee67K527btq3ol156SXSLFi2K8cqVK6v821dffVX0VVddJXr8+PGiGzVqJLpXr17F+Ctf+YrMzZ8/X/QHH3wgety4cVEXeC0oL+piLfjZz34mevbs2aL79Okj+ktf+lIxbtq0qcxNmTJF9Mknnyz6wAMPFM17rmfPnqLfeuutYrxt2zaZO/fcc0VPmjRJdL9+/US/8MILonfu3Cn6iCOOKMZ5XYgovbcHDhwouk2bNqLXrFkjeuPGjaKPP/74Yrx161aZ27Bhg2i+77/97W9RHXxCYIwxxhhvCIwxxhjjDYExxhhjImK/6jY3ctywvKiLuOEVV1wh+sUXXxTdrVs30TmWt2PHjiqf+8033xR90EEHid60aZNoxihzPsPixYurfO5TTz210r+NKI0FMt+hd+/exZjx0C1btlT5XKtWrRJ94oknin777bdF79q1qxjzM/nHP/5R6XVFRIwePTrqAq8F5UVdrAVjxoyp8jWWLl0qunnz5sWY9yNzBPK6ERHRpUsX0czp4f172GGHfew4IuLf//63aN5DX/iC/h+Zz801rmHDhsWYnwHfB9/3scceK3rhwoWimWOQ1wauhzm/IKI0d4m5EpXhEwJjjDHGeENgjDHGGG8IjDHGGBM18CEw5uWXXxbdqVMn0a+99pro119/vRjnet2IiLlz54pmXJ9xwhyDjCiN7eUchfPPP1/mli9fLjrH5SNKa3r5eNZF51gf8yroBcA65s2bN4vO/gkRpTHN//73v8X4pJNOkjnGM/NjjalLVq9eLZr1+fQRyfX9vAd4f/F3/uCDD4qeN2+eaPoYPPLII8X4jTfekDnW9g8ZMkQ0732uafRTybkSzBHIHiIRpR4j+TojIr72ta+JZp5Azjdq2bKlzHHdYX5CdfEJgTHGGGO8ITDGGGOMNwTGGGOMCecQmBqwp7gU4+Hf/OY3izFjc4wTnnDCCaJZV7ts2TLRjM3n+uFHH31U5lgPfOONN4ru2LGj6AULFoju3Lmz6P33/+i2mTNnjswxbsjPjLkUjBOyr0L2HmjWrJnMPfPMM6KPPPLIMOazgPcUf/f008j5RNdcc43MsScH+5Tw/uvbt6/oqVOnis73zNq1a2WOcfq//vWvoulbkHswfJxu3bp1MWYOAXsuvPfee6JPO+000WPHjhXNHKHcg4WfN/sg/POf/4xPgk8IjDHGGOMNgTHGGGMcMjA1gEdi7dq1E/3YY4+JziU/PGI877zzRPPojkdetOVdv3696HzUPmjQIJmjxTKvha/F0Adbi+byPloysw0sWxbzOJSfYW4ZHaEWpEuWLJG5W265RfT06dPDmM+Co446SjTL3mhvnUsFzznnHJk75JBDRK9YsUI070+uQ1/+8pdFZ7twPnb79u2i+T4Ysps1a5Zohje++tWvFmPeu7Ql57rDMOjgwYNFcy255JJLivE999wjcxdccIHoHNasCT4hMMYYY4w3BMYYY4zxhsAYY4wx4RyCkrjP6aef/omfi7Gvbdu2feLn+jzCNqW0F+7QoYPoHFdkuQ+tT1n61717d9G0LmZcP8cGGc9s1aqVaNoDc57fI+OKuXSQ5ZL8W+YIMI7I12b75NyulaWaf/rTn0Tz89/XGTlypGjGWe+++27RtNM2lZPL7SIinnrqKdEs37vpppuKMS2227dvL/rdd98VfcABB4hma98mTZqIzhbBtBr+8MMPoypmzJghmu/rpz/9qejx48cXY+ZF5TLBiNJyaD6e+UhsrX7ooYcW4/79+8vcE088IfqTrgU+ITDGGGOMNwTGGGOM8YbAGGOMMbEP5BCwRpXtakePHi2asWrW0+7evbvS15o8ebLo4cOHV/s6a0rbtm1F//rXv66z1/p/GHunLS/jdc8++2wxZutkxiBpRczvjbF5tkzNtco51hahcfiI0jakQ4cOFT1q1CjR06ZNE71u3bpizPhltmuOKI1Z0m441zFHlOZW5GulnwLzDc4+++zY17nsssuK8W9+8xuZa9y4sWjmC9G/YvHixVW+VvaroNX2t7/9bdE///nPRbMevtxgDT1bijds2FD0v/71r2KcbYwjSr0C2Aqd+UW852hPnHMMjjvuOJljbgNhPgN9Q+h/cvPNNxdj5vQwf4g5A5xnG3ZakT/55JPFmN4N/HeLurr4hMAYY4wx3hAYY4wxxhsCY4wxxkQ9ySHI7S7Z2pbxYHpXM/b12muviZ44caLonEPQqVMnmWN7y09L9ki46KKLZO7WW28VzRh9XcC4P1uBPvjgg6Jzm1LWFud2xRGlOQOcZ7tP+hC0bNmyGLN2mH9Lj3HmCGQv9IjSOGRuQ0wvBtZIMw7IeCfzG/i+cy+Egw8+WOb4GfC3uy9w/vnni87eAoxjE8aimXuyJ/Jv9umnn67ysawLZzy53OjZs6dotuZmzX32BuG9zu8p5x5FlObVnHLKKaK5tuQafeaN3HfffaJ5v9HrY8CAAaLpLZDj+mxnPGXKFNGcp+fBxRdfLJq+LzlPauPGjTLHtYFrc3XxCYExxhhjvCEwxhhjjDcExhhjjIl6kkPw5z//uRizFruqvtwREb/4xS9EL1q0qJavrvqwjj/XtXbr1k3m7r//ftGse67KL+GTws+SnuSsrc61yps2bZI5xuUZB3z//fdFT506VXS/fv0qfT7GAV955RXRmzdvFl1RUSGaMUvGGXPcn3XLjCWzdwH9E1auXCmaPR9yvPW6666TOfZL5/uoj7D++sorrxRdVd4APSB4D82cObNG13LXXXdV+7FnnXVWjZ778w7j/PQkYUz7zjvvLMY//OEPZY6eKlwreI/lvJqIiKVLl4qeM2dOpc9Fv4gbbrhB9G233Sb673//e5XXkn1E2LuG9zI9ELp06SJ61apVopkTlD1N6N3ANY39H6qLTwiMMcYY4w2BMcYYY7whMMYYY0yUaQ4B6zVzXSrj3Iw1z58/v+4ubA+w/vaOO+4QzXjoG2+8UYx/+ctfytyvfvWrWr66PdOmTRvRjGN17ty50r+lZwM9DXIeSEREq1atRDOOzxhZjr/R+3xPPRgIY4H0Jcie44x/sh77+eefF5093SNKex+wxjr3cGDclr0zevToEfWdI444QvQ555xT6WN37twpety4caJrkgPwcey/f1kun7UCfRXYn4A5TJdffnmlz8XcjuwrE1GaM8Aae647Xbt2Lcas1+dvgN4x9KZo2rSpaOZyZf+TwYMHy9zjjz8u+oknnhB9+OGHi+aat3DhQtHZlyD/2xBRmjs3fvx40dX998InBMYYY4zxhsAYY4wx3hAYY4wxJso0h4BxnBz3oY/93swZYDz49ttvF01va1771VdfXYxZr7434DUw1s444R//+MdizDg8fQd+/OMfi6anwY4dO0Q3atSoGlf8f7BGlz3Oc8+IiFIPcXoL5Pjpli1bZI45BYxRXnPNNaLZS4Px0Ryb/cEPfiBzN910k2i+z/rIsGHDqv1YfjefNmfAfMTy5ctF855ZsmSJ6JzLxZwe3jPsB8K+CFz/mXu1fv36Ysx8IV4n4/YNGjQQzfyF7A0TEfHd7363GE+YMEHmmENAX4IXXnhBNPuaMJcie3DwuvmZDhkyJD4JPiEwxhhjjDcExhhjjCnTkEFVtoyf5dE6j3TYevn6668XzeOoWbNmieZxMm039zbt2rUTzffDkEduNZ3bn0aU2jTnUr6IUqviESNGiB46dGilr81ySFoZ51K+iNLvcfHixaJZupqtkFnqx3IslhblFqYRpfakPPrL18q2zY899pjo2m6//XmEZZpVQavnTwtLHlmG+1ley96GZcQMdbE9cm7VzWN43iNcK/i5s00176FvfOMbxZjrRG6NHFEa9mQ7c75PWo/nEATt2GlVzPJKvg+up3xfOWRAC2/+m0hb+eriEwJjjDHGeENgjDHGGG8IjDHGGBNlmkNAe8kM4zK1TY5JMWeA8SXaKF944YWip02bVstXV7cwR4AWwSyjya1BGeN66KGHRLMEs2/fvqIZHx87dqzobIXMlqUsccxtRCNKS6jOPPNM0SxTzC1U99TemNdNC2ra6zKOmMuLWJZEaItcH2DOANvXklyixtK3T8sJJ5wgmmXFGX7vtPYtd1iqy3V37ty5onN79nvvvVfmjjzySNFc35kDxNbokyZNEp1tfXmdLF+m/XTOe4oobZ3OvJFchphtjCMiBg0aJJr5bVx3Lr30UtFvv/226Hz/0waZ1821ubr4hMAYY4wx3hAYY4wxxhsCY4wxxkSZ5hCwPv+dd94pxqw7ZdyGMdw9wbrUo48+utLHsoXv8OHDa/Ran3cuuugi0QsWLBDNGvxc38+aedYpsx745ZdfFs262oMPPlh0ju0x/2DNmjVVPhd9CBjTZNw6t3ZdvXq1zDF2PHHiRNHt27cXvWzZMtGsyb7sssuKMX+7rEXu3r171DcYl60qfyhCa7f5m/q01MQOlt9rueUL7QnmC3Xp0kU07+/suUIL3+eee040c2GYw3PttdeKppVxw4YNizFj/vT54L3PNuv0V6AvQW5pzzWLlsv8zJg3Rd8Btk4fOHBgMeYaxryKOXPmiKbNeWX4hMAYY4wx3hAYY4wxxhsCY4wxxkSZ5hD85Cc/Ed2rV69inH2sI7Q9ZUTEwoULRX//+98X3adPH9H00c7xrtGjR8vcww8/XMVVlz+sm2V8l7G+/Hmwd8GecgJYH8w2plX1BGDOAOObzH1gvJN5AYwb5jbD7IvAGCRriRmzZIyS7zvX0jN/hbHXU089Neobd955596+hILzzjtvb1/C5wbm2TB+Tt+R3NK4cePGMse8GfY64BrOXge33HKL6OwXwXWC9fpsGZ69UyIinn32WdEzZ84UffHFFxfjF198MaqCOShLly4V3bt3b9H8DPO6xBbROa8pojQ/obr4hMAYY4wx3hAYY4wxxhsCY4wxxkSZ5hCQ73znO8X4d7/7ncwx7ldTf/NHHnlEdI4Z1Ufv+Krg+2V9flW9DOgpzj4P2bM/ojQmydf+3ve+Jzp/76y5nT17tujp06eLZq/6c889VzR7I+TfBHMjGjVqJHrr1q2imzZtKpo5Bcw5ePPNN4txu3btZI4e78zpqA/kOu/qkGOnM2bMqNVrad68ea0+XznDunf+7um1f9VVVxXjDRs2yBzvbcbimUdCn/68/kdEHHbYYcWYtfzsjcFYPL0A6Bty+eWXix4zZkwxXrdunczRl4XrTteuXUXz3xqumbt27SrGzIvKPRUiSvOiqotPCIwxxhjjDYExxhhjvCEwxhhjTNSTHILsT33bbbfJXE1rh+fPny961KhRove1vIEMY1rs3dC5c2fRDRo0KMaMbzPfIPf6jtD+FBERJ598sujJkyeLzj3Qc9w9IuKKK64QTR+LtWvXimYcn7G9HJ9jXP+ee+4RzXn+fphLwdrjHEPfuHGjzFVUVIimR/y+SP6dDRgwYC9eSf2GviDsVXLKKaeIXrRoUTFmHg3vgRYtWoimRwn7WbBnxY4dO4ox4/T0/aBvDXMjJkyYIJo5Qdl3hL409AnJuQ0REU899ZToE088UTTzqvI6deCBB8ocvw9eZ3XxCYExxhhjvCEwxhhjjDcExhhjjIl6kkOQ40Ssx2R8imzfvl30iBEjRNd2T/VypkePHqLpu0+P8rZt2xZjfs6tW7cWvXLlStGnn3666Kefflo0cwpyjThzApifwOvm+2JPhksuuUT0vHnzKn2tYcOGiWZOCuvq6dvOHg+57wJjp3zspk2bwlQO68RZD89aev4GzUcwhr2n317OCWIOAdcNxvHZu4D9Cd577z3R/fr1K8bMe5ozZ45o/gborcI+Czk/IULzG+h5kHPbIkpzm6jZH4J+DFxDM++++67ohg0bVvrYqvAJgTHGGGO8ITDGGGNMmYYMaDWby8hoLzp16lTRbBHL4+NDDz1UtEMGH0ELX5bF5NK/CD2qZ8kNS+j4XDyC7N69u2g+X/5eaUe6fv160cuWLRN9xhlniKZ9KX8DuSU2j/x5pMiWxWwhTSvVt956S3QOreQQzMc9tj5a62ar8IiIm2++WfRxxx0nOpdysQSUZWAsfWVJGssW77rrLtH8De5LsKyN5d0M0+XPqk2bNjLH8jt+LyxZZhiAdsI33HBDMabFL0sYc6vkiNLW6Qw5f/3rXxedQyc8pqel8sSJE0Wz3TFDBNOmTRM9cODAYpxLuiMiDjnkkKgNfEJgjDHGGG8IjDHGGOMNgTHGGGOiTHII+vfvL5oxo2wfee2118rc3XffLZpxcLa37Natm2iWKu3LME7Fz6ZPnz6ic6z+mWeekTmW3/F7WLx4sWjGzBhXvPXWW4vxkCFDZI4ljTnGGFFqVcyyJpLLf3gdtFxm2RLzGxhX/Na3viU6Wx0fddRRMvfAAw9U+Vr1AcZRqWsTlnHSHpttePflHAKW71199dWimSOU73/eA8zD4b3OuD5zPZhXkv/+8ccflznmnPC5WMJIO2G2Us95Asx9mDRpkmiulyxzZQ4WXzuXFrJsm+tQbj1fE3xCYIwxxhhvCIwxxhjjDYExxhhjokxyCNhKk21e77jjjmLMnAFSlf1jRKmtpvkIfnbNmjUTPXfuXNG5Tn7o0KEyx5rwpUuXit61a5fonCcSURqjzPE25ol07NhRNOOfjFGyRTFfO9sm8zOh7TFhvPSkk04STSvkHFfkddPilTFJs/egHfbgwYNFT58+/bO8nFqH9fj333+/aHpm5PwXxsp5L/P+o161apVo3p+ZXr16iX744YdFM9+IFsB8bvrU5PwFeoowt+H3v/+96A8//FD0ihUrRDMfKXut3HfffTJ32mmnif7Rj34k+tJLL43q4BMCY4wxxnhDYIwxxhhvCIwxxhgTZZJDMHLkSNH0l2b8KsNa4Q4dOoimH/yMGTM+ySXuEzC+xjg/4+PZx3/JkiUyl/sBRJTGy+g5znbHzPV4/fXXizHbjrIvAv3N2buAngl8fPZpp6f78OHDoyqefPJJ0eyzQHJuBPMN2KfjgAMOqPK5zGcHvwv6bpQ7/B136tRJND0dcrycazL7f9AbgD0Cjj32WNGM82c/ALYYZm0/vQOY30DPhOuvv170McccU4yZI0BPG/qb8Fq2bNkimmtgbgF/4YUXyhzXZuZGVBefEBhjjDHGGwJjjDHGeENgjDHGmCiTHALGdejp/tvf/rYYM7Z11llniW7SpIlo1sCayjnooINEsy8564Xzd8G4Ye4jHhGxbds20eyvzt4G7LfevHnzYswe54y9N27cWPQrr7wimn7nuQ95RMSUKVOKMfMm6EPw0ksviWbP8379+omuqKgQnT+ne++9V+YGDRokOscYjalL6PnPtaBFixaicx8U5lMsXLhQdM+ePUWzHwHvX95jO3fuLMaM29NHgH1O6HnD98m8nc6dOxfj3E8lojRvirkO9FMg7LFCr5YMcyX4b2R18QmBMcYYY7whMMYYY4w3BMYYY4yJMskhYB/y22+/XXTv3r0/dhxR6vfOuM6wYcNEM55sPoLxb/bcHjVqlOgc92f/CcbmGAObMGGCaHqjZ4+DCPUpYJyQfgmse2bcn681a9Ys0e3atSvGzz//vMzx93XllVeK3rx5s2j2TKf3eq5lpj8C/RPoqWFqlxtvvFH02LFjizF/c/Ud1sHTV2T58uWic37Rhg0bZG737t2iH3jgAdHZwz+itA8K74vu3bsXY3oacH1v3bq1aPYX4BrHuP7s2bOLcc6TiIho2bKlaPbZYf8Bxv25TuVr5Wvx8+ffVhefEBhjjDHGGwJjjDHGeENgjDHGmCiTHALGWWfOnCmadasZ1rez7tRUH8bX2rRpI5rfS461M37Gfur0J+f3xhwE1txv3769GOe+BhERZ5xxhugFCxaIpr8Ccw5yrXGE9h/I7zGitO84+96zl8YHH3wgmp7kufaYPTz4W+7YsWOYuiP7T0RofhJ7oKxdu1Z0VTXk5QjvMdbYM85/wQUXFGPeX8y/YPybPjTMC2PeGPN0MswpoGfJ5MmTRdMzgWtgvp/pUcB+DiNGjBDN90HPBPYyOP7444sx1wmuK/z9VRefEBhjjDHGGwJjjDHGlEnIgLD0Y968eXvpSvYtcqvPiNLvgUfYa9asKcaNGjWq8rEMP/C1mjVrJpqlSLn8j0dtbEXL40yGnHr06CF6xYoVovMRJW1TH3roIdEsqaKNMo8wswVzRMSyZcuKMcuSGG5wOOyz5S9/+UsxZjinvsOSV9oJn3322aL/8Ic/FOP+/fvLHMsGeSxPK3Hec+3btxedj/kfffRRmWPbdK4rtGDmWkJL5vx8DHMyDJrXw4jSUmtakTPcmNcllm2z5TvX5uriEwJjjDHGeENgjDHGGG8IjDHGGBNlmkNg9g7MA6ANKOPj2er4zDPPlLmtW7eKHjdunOjrrrtONC2CWSqYSwH3319/1oy1M0eAJZBsrXz44YeLXrRoUTFmfJMliiyZYhyR5UFbtmwRnWOztI5mKSZbtxpTVzAvh/krbG+eLbhfffVVmevUqZNo5iMwrs/yPJYp5nh6165dZY5lwsxfoN0w8xWYx5NzhrjO0BKd5ZbMm5o/f77oLl26iM7t5Hkd/Iz4mVYXnxAYY4wxxhsCY4wxxnhDYIwxxpiI2G83C6Ure+A+Vmdb7lTza60R2X40orQ1aEVFhehcU097UT6WOQGso6V3AGOU+bXYGpSxu3feeUf0zp07RTMPgN4CGzduLMast2YckTkEzDlgLgXnc/02W3XTvpRtZXNr1trEa0F5URdrAVsUr169WnRVltyMf/P+oy0yvQD4++Nr5/bljMNv2rRJNO2DuVasW7dONH1DBgwYUIxpT01/kzFjxoju27evaNok57wovnarVq1kjr4QzDeirXJl+ITAGGOMMd4QGGOMMcYbAmOMMcZEDXIIjDHGGFN/8QmBMcYYY7whMMYYY4w3BMYYY4wJbwiMMcYYE94QGGOMMSa8ITDGGGNMeENgjDHGmPCGwBhjjDHhDYExxhhjIuJ/Q7q7wRU4vz0AAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -1902,7 +1557,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1958,7 +1613,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2004,21 +1659,9 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "938it [00:25, 36.54it/s] \n", - "938it [00:25, 36.57it/s] \n", - "938it [00:25, 36.41it/s] \n", - "938it [00:26, 36.07it/s] \n", - "938it [00:26, 35.73it/s] \n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Training loop:\n", "for epoch in range(n_epochs):\n", @@ -2035,30 +1678,9 @@ }, { "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'mean squared error loss')" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Loss Visualization\n", "fig = plt.figure()\n", @@ -2080,7 +1702,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2094,90 +1716,9 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Displays: ground truth, noisy, and denoised images\n", "def visualize_denoising(model, dataset, index):\n", @@ -2257,7 +1798,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2286,92 +1827,11 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" @@ -2458,21 +1918,9 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:53<00:00, 35.33it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:53<00:00, 35.32it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:52<00:00, 35.44it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:53<00:00, 34.85it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [00:56<00:00, 33.34it/s]\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import torch.optim as optim\n", "import torch\n", @@ -2506,90 +1954,9 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAWuElEQVR4nO2dedCVY/jH75CUtKNVe9rTvqm0qIQWTKopRogQI42yTEZGwowpDJpGEy2iRfsoSSqkVfumTbSQCqVF9PvjN7/nd1+f9+0876n39L65v5+/7u/c533O85zznO6e67ru75XjzJkzZ5wQQohguSSrT0AIIUTWooVACCECRwuBEEIEjhYCIYQIHC0EQggROFoIhBAicLQQCCFE4GghEEKIwLksoy/MkSNHKs9DZDKp2CfYtGlTo3lPFChQwOhy5cpF440bN5q5zp07Gz1lyhSj69WrZ/S0adOM7tWrl9GXX355NF67dm3CY+3bt8/oRYsWGV2jRg2jDx06ZHSrVq2i8Zw5c8zcZZfZn1SePHmMPnr0qNFXXHFFwtevWbMmGjdu3NjMVaxY0eiFCxcaPXPmTJcKcuXKZXTcvebfJ5l9XyZzvLh/wzh/6aWXJnyvf//996xz1Dw2dWZ+Ljz2yZMnY/9GTwRCCBE4WgiEECJwtBAIIUTgZDhHIESJEiWM/uuvv4w+fPiw0X7O4JprrjFze/fuNbp79+5Gjx071uhmzZoZPXToUKN79+591vNYvny50Vu3bjW6Xbt2RvO6/vzzT6Nff/31aFylShUzt3r1aqNbt25tNHMAPDZzDIULF47GBw4cSHie/mtTSVz8Oy5entG59IiL819yyf//3zbu2P5rnUub++C8nxNwzrlTp06ddS6OZPIqFwI9EQghROBoIRBCiMDRQiCEEIGjHIHIML///ntC3bNnT6NXrVoVjXfs2GHmGM/mPoFGjRolfP2gQYOM3rRpUzRmLmP37t1Gb9u2zehOnToZvWvXLqP9PQrO2X0GpUqVMnOVKlUyevLkyUaXL1/e6KuuusroNm3aGO3nVlasWGHm/v77b6P5mV0okonzn2+9fFw9vh/Xj8tdMAdAuI+A5MyZMxrzu/jnn38SvnccifIwqdiDoCcCIYQIHC0EQggROFoIhBAicJQjEBmmaNGiRjMu+vLLLxt97733RmPWWTPOWblyZaPXr19vNOP2ZcuWNbpWrVrRmN5AP/zwg9ENGzY0es+ePUbv3LnT6Pr16xt97NixaMzcxffff2/0k08+afSCBQuM5v4K7ivwj1e7dm0zR5+jgwcPGv3888+7C8H5xKyT/du4OL/v3ZQ/f/6zzqX33qdPnzb6jz/+MJp7QI4fP37W8+T9Hrf3giSzFyMz0BOBEEIEjhYCIYQInP9EaKhly5bRmHYBV155pdGPPvqo0XxEGzdunNEvvvii0X4ZZLLbyi92WJa5efNmo9u2bWt03rx5o3Hu3LnNHMsuly1bZnTp0qUTngvDNX6YhN8ZbaX5iF+sWDGj/TCTc2ltrf15Wkqw1PTDDz80muEJhi8Y7rn66qujMS0mrrvuOqNpcZ0qkrVzPp+wBo9FCw7/83HOuRtuuCEaP/DAA2aOYTgei79nhgi//fZbo/1yXv4WeCyGUZO1rU51ia6eCIQQInC0EAghROBoIRBCiMDJcSaDAaWsbFXJmO4zzzxj9BNPPBGNmRPIbCZMmBCNJ06caOZmz56d0vdOhlSUm3Xr1s1oWjWwdaIfs+Zr/fyBc85Vr17d6A0bNhjdvHlzo2nB7MeGWT7Ke6JMmTJGf/XVV0Y/8sgjRr/11ltG+7YQLGulZQRjxbS7aNCggdG8Lr9UlS0Hf/zxR6OZf5g1a5ZLBcyDsIQzUfw7LjYeZ/vA3FKXLl2MvvPOO6Mx7zHmBGghEfdvHC1Vvvjii2g8f/58M+fbqziX9ntN1PYyvfnzaffJ/ER66IlACCECRwuBEEIEjhYCIYQInGy5j4CxvXfffdfoHj16ZPhYjI9t2bLFaMam4/Df+8iRI2YuO+UIUgHjt0899ZTRS5YsMdqvw65ataqZY/03bar5em7379q1q9F+vJx2zbTGKF68uNG0YqANxE033WT0sGHDojFzF4zbc39EtWrVjOZ1Mw59xx13ROO5c+eauZo1axp9ofa1JNuaMlFMO85Wmt+Vb1vinHN333230f7vndYijNPzt3/ttdcazc+Te2E6dOgQjZmHOnHihNHMeXGexOUMMhs9EQghROBoIRBCiMDRQiCEEIGTLXMEt956q9HJ5ARYr37//fcbTZtg1nHzvRiD9GOBDz30kJkrWbKk0axH37dv31nO+uKArRDHjBljNOP4vlX0L7/8YubosUPb6bp16xrN74m21e+88040Zi7j1KlTRvv138459+abbxp9/fXXG12nTh2j/ZrxhQsXmjleB2PczFExtsw9EL5XUYsWLcwcr4M+WqkiLl6dKO7PFo78rnLlymV0v379jO7YsaPR3NOwcuXKaMxcEe9B+kTRi4gW4/Xq1TPaz9Hwt09/q+HDhxvNvSvMZfKe9clMX6L/Q08EQggROFoIhBAicLQQCCFE4GQLryH2EPjoo4+MZjyZ+HmBm2++2cyxDWGy3HXXXUYPGjQoGrN1IGGMsnPnzkanMmeQirpj+vxv377daOZXpk6dGo3plc/YcL58+Yz26+edc27mzJlGsx7fz/0w3rpp0yaj+Z0yt7F//36jixQpYvT48eOjcfny5RMe+6effkr4XoyJL1q0yGi/tp117L4PkXNp/fPXrVvnUgHPmST6t4I5Avr9tGrVymjG1glj6aNGjYrGa9asMXP0GmJOgMdi60ped7ly5aIx259yjwfvyZEjRxr9wQcfGM2WpYm8hvh5x/VCSA89EQghROBoIRBCiMDRQiCEEIGTLfYR+B7iziWXE3DO9so935wAmTx5stG//fZbNJ43b56ZY9ybdcd+rbtzab3UszsjRoww2u8B4FxaT/bDhw9H4ypVqpg5eur48Vbn0sZrCxUqZDTr8ydNmhSN6RlDPyD2nmW9OGPD9Pn3c0PsG8weAI899pjR7CnAfNivv/5qtN+Pm305cubMafTx48fdhYAxasb5E8Fz5j4A37/HubTXzGuk9vtL8x7jeTKWTo8zehMxv+PvS+B78Z7x99Q459zjjz9u9N69e42eMWOG0f5nzjxLnF9TRtATgRBCBI4WAiGECBwtBEIIEThZkiO47bbbjKbHeBzsIUsP+FTy5ZdfRmPWuvt1886lzRnwunkdgwcPNtqPsWcHuEeDuRx66/vnzz0TjHMyptqkSROjuQ/hm2++MdrPC9SvX9/MMafEenDGillffvDgQaP9ev0KFSqYuT59+hjNfQGMU/ft29do1r77+yMYX2e/ZNbgp4pk+xH418z8C3s8M+/E2n/mFPjb93MsPE/mnVhfz30ZvCeZ3/H1zz//bObYC4Hnzb0pAwYMMJr3jZ+PiOsRrRyBEEKIpNFCIIQQgZMloaEbb7zRnsRliU/Dt5Z1zrlPPvkk08/pXKDtAe0FJkyYYDQfNWlTPW7cOKOXL18ejS9UG8JEHDhwwGi2dOT36pfIDRkyxMzVqlXL6Pfee89otrJkeR7L8ebMmRONacUQ96jsh/ucS1vOzDJC306A4THfNtq5tKGQXr16Gc3Hen6GfjkkbcArVapkNEtPUwVDE/x8E5U3MjTGMBy/d34+DM8wHOmXdzMcw/MiceFKvrf/eoYPaXlNC4qePXsazVARQ6NTpkyJxnGhoXNBTwRCCBE4WgiEECJwtBAIIUTgZAuLiTgGDhxo9IWKhSbL9OnTjWZZ7OjRo41mm0KWRPp/z/xBVtC4ceOEmjkT38qB7R8LFChg9Keffmo0W4rSUpk5Aj8OzXgsrS+KFi1qdOnSpY3248zOpS0z9MtRmQNgLoMln999953RvA5+Tr7FAo/NsliWYqYKxqiZv2LM2o+l87W0FmHOhXH+jRs3Gs38oR/HZ0yf58VzoWbJMu8D/3j8TJhXYg6BObJbbrnFaOaK/H8bmKtjjvVc8ol6IhBCiMDRQiCEEIGjhUAIIQInS3IEJUqUyIq3veDQwrpgwYJGs3aesB1jVrNw4UKjGYts0KCB0X5clDF+tqZkzTZbPLLefPbs2UY3bdo0Gh85csTMcbs/bagZO2bMlbH3GjVqRGPmG1avXm00a/9pG/LKK68Y3bp1a6P93wrj47T8uJBWKz78vBLVtTOWzpxIXBtM2mps2LDBaN9GIlGuIr35OKuGRNfFY7PVJOeXLl1qdPfu3Y3mvoJixYpF41TkSPVEIIQQgaOFQAghAkcLgRBCBM5FsY/gvwJj1XHQ4jirYb09vZW4T8K3nmY+oUyZMkZzHwHbAjLuz/rzQ4cOReP9+/ebOfq+dOzY0ejPP//caLYNZPvErVu3RmPfD8o5G8t1zrnFixcbvX79eqNfeOEFo9m+1P/caHW8fft2o1k3nyoYO+deCX7XfnycXkPMsRDG5f3P3rm094X/eu7xiPPkSdazJ5nXs6Umbab5mbHdqp8r8v2n0kM21EIIIZJGC4EQQgSOFgIhhAicLMkRMNYZR/Xq1Y2mf/zFwrJly4xmvJjXyVaYWU27du2M3rRpk9FsxennRBjLZc8A1tfTg4exdsZn/X0I9Apq37690ay3Zz1+nGePH5svX768mWOOoHjx4kbTb59+VBUrVjTab4vJvApr1RkTTxWMQbP2n9+N79FD7yDeB7wGvp7XzLyIH2tP1hMpmX0DycLroo8R81jcm5E3b95MO5f00BOBEEIEjhYCIYQIHC0EQggROBfFPoK+ffsaPXHiRKOza38CcuzYMaNPnDiRRWdybvTu3dvo++67z2j2km7VqlU0LlmypJljbLdmzZpGV61a1Wj2OmD81/c1Ypy9fv36RrOvMGPvn332mdFVqlQx2o/fsqcEr4u+Wps3bzZ62LBhRrMPtJ9jYL8K7uPg/olU4fv5OJc2/0P874qeUuyxwN8EY+XMwfB4iX5TPO/MzAEQ5ht4v/K66EXEvRn+dcb1jFY/AiGEEEmjhUAIIQJHC4EQQgROluQIXnrpJaP9WLJzztWtW9doepbT8+ZiyREwLkjfFcLa+ayG3wPjsb5Pv3PO7dixIxrTG4j9CebOnWs0/YBYq856fL9fAT/Xr7/+2uhChQqd9Tydi+9HUKdOnWjMe2/Pnj1G01+KvWpXrFhhNM/d733L96KnPd/r2Wefdakg2d6/fkybn+2aNWuM9vtKOJd2n0abNm2MXrJkidF+r2v2DY7bNxBHMn8fl3+gl1Dc6+m9lehvmUPICHoiEEKIwNFCIIQQgZMloSGWUdKSlaEhMm7cOKMHDx4cjVnCmJ1o1qyZ0bVr1074erZUzGr69OljNO1w582bZ3SPHj2iceHChc0cH9vZ5pIlm/6xnHNuxowZRvthEZZwcvs+7z+WMLKUlbbUfhtN2igzlEEbkW3bthlNewvaWvt2FvxdsH0nLZovFAxnJQoN8bUML9IepHLlykYzLNyvXz+j33jjjWi8atWqs56Hc+ffqtK/Tl5XXLiGdjJ8PUtd/dLgVFhh6IlACCECRwuBEEIEjhYCIYQInGxhMTFixAijaWdMywDqIUOGROPbb7/dzPXv39/oC1lqSusCxrnjoK1CVuPHxp1LawPBmLUfD+ccY8Es0fQtI5xzbs6cOUYzx+C3AsyfP7+ZY4khSxBp1cBYO3MMvm0E8w1++aJzae2DW7ZsaTRLcmmR7ZcQ85qZf+DvIlUwHs6S0EQWB74ltXNpS16ZL6RFB61KWI47cODAaPz222+bOZZj09aB58bYO1/vz/O1tIigNQbvOcb9N27caLT/OfHzPZfWlERPBEIIEThaCIQQInC0EAghRODkOJPBItTMiENlFNYO0yKgQIECGT7Wli1bjF65cqXRo0ePTu7kkuC5554zmvFhwji436qS8cs4UmGxS9sHXg9biPr5GNZRM2fAnADjzqw3Z/34rl27onGlSpXMHGPpzAGUKlXKaNpE0A7At4Vo0qTJWc/DOecefvhho8eMGWM027aytaXfqpG2HLTAbtSokdFDhw51qYDxb7aT5L3qf/dxf8vvnZ9H586dje7atavR/n4V3lOzZ882mvfFoUOHjKatAy2v/X8TmQtifpA2OrRIYa7p1VdfNdrPc8X9WxCX+0gPPREIIUTgaCEQQojA0UIghBCBky1zBIQ5A8aH77nnnmicJ0+eC3JOmQHjw4zBsyY9GVKRI3jwwQeNZjycNeHt27ePxoz98m/pIXPgwIGEr+degXz58kXj7t27mzl+zqzRbt68udHMQfGz9OO7/v4F55wrUqSI0QMGDDCae2bGjx9v9KxZs4z2vYgY82Z8feHChUazLWZmwe+S+R/uM/AtxBm/ZtydOQTGt/n5Mk/l36O8p/g9nj592mheBz9fnrv/bw2PRa+go0ePJjwX3gcjR4402s+38dj8vHmePLf00BOBEEIEjhYCIYQIHC0EQggROBdFjiAOPxbImCzjv/QBTyULFiwwmjHc999/32jfc/x8SUWOgP0UqOkT43u9DBo0yMyxjpq9GZhvYO0/+xf4NeGs2WZsnZ5J9H1hPLdbt25Gjxo1KhrTG4gx7RYtWhjNe2Lnzp1GM57r19EfPnzYzPE3yVjx2LFjXSpgHJ+xdeYQChYsGI3pl8Rzzp07t9G8Rh6b5+L3sWD+wG8x6lzaXhLMV/DcEv0byJ4W9Keixxn33FBzL4u/j4Y5AH7+nKdODz0RCCFE4GghEEKIwNFCIIQQgfOfyBEkgvsKfP8e55yrVq3aOR+b9bzDhw83mv4hfH0qSUWOgLF3xmvpH+R/9szNvPbaa0bTZ57nT699erL7sfdOnTqZuX379hlNXxj2VWD9PWOwvgcN/3bSpElGM9fx9NNPG82cgt+j2Dl73bxmxrzZv+Ljjz92qYBxef7bELevwIc5kUR9gdOD75XoPJl/oFcTe2LE7Tvwc0n0wuL+El4Hz41xfL7eP5e43BD/nZHXkBBCiFi0EAghROBoIRBCiMD5z+cIQiUVOYIOHToYXbNmTaNPnjxp9O7du6PxddddZ+aYu2EOYOrUqUYzfssacD9ePmHCBDPH2C7jt3xv5joYh/b3f9Afip5IDRs2NHrDhg1GM07t93l2ztanM0dDT6S9e/cazd4HmUVcjiCV8L14nyc6l7h8Q9yxeB8k+o3xb+N0MueWKC+S3rEykpvUE4EQQgSOFgIhhAicy+JfIsT/wkdhhkF8K2jnbDhn7dq1Zo5hJYZzypYtazRtIliW6VtM0IqB4RmGVPw2gM6lLTfl6+vWrRuNWSLMdoerVq0yulChQkbT6pgloX6rVT7i+/bOzlkrh1SSTIiExIVI4o51PmEonney751MKCjub8/nM0z2vTOCngiEECJwtBAIIUTgaCEQQojAUY5AZBjaM5coUSKhnjZtWjRmzD8OlsBVqFDBaMbi/bJM2gmvW7fOaJZZsrXl4sWLjebxmjZtGo2XL19u5rp06WL09OnTjW7Tpo3R8+fPN7p8+fJG+/kJWgXw+yhVqpTLCuLi/sm8NhVlz2fjfHICccRdV1y5aKK/57GSKaE9G3oiEEKIwNFCIIQQgaOFQAghAkc5ApFhGCtv27at0UuXLjXat2qgZXW9evWMLlOmjNFss0h7BVoK+3sHihQpYuZoiUBLiY0bNxpNa3K2o/QtKnhsWgLTpnr16tVG01KCrS39/RH8W7bYpAV2//79XSpINibtz8fFzs83R5DM3ye7ZyGVOQPuK4jLISRz7IygJwIhhAgcLQRCCBE4WgiEECJwMmxDLYQQ4r+JngiEECJwtBAIIUTgaCEQQojA0UIghBCBo4VACCECRwuBEEIEjhYCIYQIHC0EQggROFoIhBAicP4HKJjQra/i9U8AAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, test_dataset, 123*i)" @@ -2597,90 +1964,9 @@ }, { "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAZS0lEQVR4nO2dadRV4xvGn8yilGgSotAkiQZCpUFlKqyGJUUitVoZlrWsPpQhhA+ZWoZqEZkjYTUQpXmeFBKplGaZM+v/6X/Wff/e993POW+dt7Kv36d9reecffbZ+9n7Wfu67+d+Su3evXt3EEIIkVoO2tcHIIQQYt+igUAIIVKOBgIhhEg5GgiEECLlaCAQQoiUo4FACCFSjgYCIYRIORoIhBAi5RyS7QdLlSqVz+MQe5l8zBPs3r27082aNXN62LBhTl999dWZ7W3btrm2uXPnOt20aVOnefzfffed06eeeqrTv//+e2Z76tSpru3ggw92umXLlk6PHDnS6VtuucXpCRMmOF2tWrXM9rHHHuvadu7c6fSFF17o9KJFi5y+6KKLnB4zZozTRx99dGa7devWru2vv/5y+vDDD3d66NChIR8cckjyY4PXzuo9fY7w+//++29i+57sm/+D7QcddFCRbTF43NRJ96/93cJ+m/v6559/osejNwIhhEg5GgiEECLlaCAQQoiUUyrbonOKERxY5CNGMGjQIKe/+uorp+lR//TTT5ntP//807UxJvDZZ585vWXLFqd//vlnp2vXru109erVM9v0zj/++GOnre8eQgiXXnqp00uXLnW6Zs2aRX5/xYoVro3/c9OmTU7Tv7WxjRBCaNGihdOVKlUq8rjOOeccp2fNmuX02LFjQz5gzCUXYr57SRKLCeTyfe4r1//Fz5crV67IY/vll19c299//524b/bJwtAbgRBCpBwNBEIIkXI0EAghRMrJeh6ByD9t2rRxesqUKfvoSAqH+fnt27d3ev369U5ffPHFme0ZM2a4tvnz5ztNj9R6/iGEULlyZadt/CGEEJYtW5bZPu+881zbKaec4jS9YHreq1atyvrzRx11lGtjLIPxBX6eOd6cb/HNN99ktnnO7PkNIYS1a9eG/YFc4gAxX35vxhBiMQHm5+9JnC2278MOO8zpk046yenTTjvN6TVr1mS2GVdiDIBxqGzQG4EQQqQcDQRCCJFyNBAIIUTKOSBjBLn4hjE/mHVTuG/mpFuv79BDD3Vt9O5iXt2IESOcpk+4ZMmSzDZr7fC4Y7nEewPmL//6669O//jjj07bXGj61/RAK1as6PRHH33kNHPm+f9tjn3dunV56I6tW7c6vXr1aqc7d+7s9OzZs50+4ogjijyOM844w+kdO3Y4zTgLaxGxDtJ9991X5Gfvv/9+p+vUqRNKgpjXHvPH80lSbj/vfR4X22PPAnt/x+Ii7Cdly5Z1+pJLLnGatbQ2btwYimJvnG+9EQghRMrRQCCEECnngLSGkl7DYrYR0/WyKdFa1Of5qkj4+vfCCy84zRSyPn36OE07yFISVhD59ttvnWZ5BVoyP/zwQ2ab5Sdo/dBmuuKKK5xevny5040bN3banrvRo0e7tuuvv97pGjVqOP3FF184XaZMGad37drltLW5mjdv7trmzJnjNG0nprIyLfaDDz5w2toPJ554YuK+bDmKfJKP8iXFJcmCYRtLhtPaJbR2maZp+wWfI7SZ+Ns33nij0ywtMm7cOKftvRSznIuTcqs3AiGESDkaCIQQIuVoIBBCiJRzQMYImIpl/blYKlurVq2cpndH355LKvbs2TOzzXIAo0aNcpo+ONNDu3bt6jRLNNj/uS9iAqRBgwZOs8QB/XG7bCO/y3Ia8+bNc5ollVl2muWdbdqlLcsQQsFy2SxD/fnnnztN750lsfv27ZvZXrx4sWtjCm2/fv2cLl26tNPjx493mrGPW2+9NbPNctqML5RkmmYSSceRq38dS8ukz2/PL710XneWMWEf47OBv23vSZZRZyp5ly5dnD733HOdZlox41Y2HhGLTRYnhrN/9BwhhBD7DA0EQgiRcjQQCCFEyjkgYwT0/qwnxvxd5veefvrpTrMkAPPd69ev77T19lauXOna6PMxX92WjAghhO+//z4kkcv/KgmqVavmNEsu06+1MY8//vjDtbGMNJeL5JyE119/3ekbbrjB6ddeey2zPXDgQNfGJR7pvw4YMMBp9i/6/NZrrlChgms7/vjjne7WrZvTTz75pNMsC8EyHkOGDMlss6Q1+5ctVZxP8rm8ZMzfjsUMbK4/S34ztsh2lnVgHzzhhBOcts8KzvlhH2I855NPPnGazw7Om7HPCt77jMkU59mgNwIhhEg5GgiEECLlaCAQQoiUU2p3lkmn+fQFc2VPylDvTW6++WanH374YacfeeQRp4cOHZq3YyH5+N9cAvKCCy5wmuWd33///cx2hw4dXNuRRx7pdKNGjZx+5ZVXnC5fvrzTjO3YfH7GU9atW+d0vXr1nGash95xrVq1ivw+5zP06tXL6eHDh4ckOD/E1pQJwXvNjF+xBhLnTzA2srdgLCjm2yf1xVz7aay8s4XeOT8bK0PNPnfmmWc6beckcZ4M4wmcVzBy5EinWYeM8Tc7d8CWQQ8hhGOOOcZpxh4ZnysMvREIIUTK0UAghBApRwOBEEKknANyHgGxvmFJ1kqnZ07oA+aK9WJtfZsQQnjggQecZh5+PmA9/IkTJzrdpEkTpxs2bJjZZl1+xghYq4X1VLZv3+4068RMmjQps815BPSVZ86c6XTTpk2dZkyBXrz1c1m7ivnkjCHE/POvv/7aaVufql27dq6N9Zl+++23sL8TqwWWK4yx2PMbW0+AMQN+ntedMTA7L+iuu+5ybWeddZbTnOOxbNkypzl/hP3E9oOLLrrItXHuyttvvx1yRW8EQgiRcjQQCCFEytFAIIQQKeeAjBHk4jMyVzi23mcun2dtEvrBO3bsSPyt9u3bO82aNjZfvVy5cq6NfjA993zA/GTGSOy8gRD8/7Hr/IZQ0KdnDaiqVas6zbV8N2zY4LStAbVw4ULXRh+5bdu2Tr/55ptO9+7d2+nZs2c7ba8Fc/unTZvmNOdHcG1mrmfAz9t1FgjPAWM4+SLXekD5ZE/mKDAOFZufxP3ZOR+MDXFdEz5XWGOKcwNsfC2EEC6//PLMNu91xi7YB7NBbwRCCJFyNBAIIUTK0UAghBApZ7+MEdCri+VeW72nNZFYb4QxAuvDVqxY0bVxbVyuZfDGG284zXo5zCW29UZYR4bwu/mgefPmTn/66adOX3XVVU4zDmChtx67xrfffrvTM2bMKHLfXHOY8RTGOljXn3nYSXXtWXenTJkyTnNOAvtEixYtnP7www+dHjt2bGabNWUYT2BN+3yxJzEAXudc6wHR12ft/T25/5PWOSlM23kJXA+Z/4PrH/fv39/p4447LvG37PrfPAdVqlRxmvGKbNAbgRBCpBwNBEIIkXL2C2soF+snm+9bYumi/C5TDYlN3aItwLIHTDskLCeQtOweS8lyWnlJwOUlk0pBh+DLN3NKPVNvGzdu7DTL9j7++ONO01qyS1fyvNvX6hAKvkpzSUKWgt6yZYvTthzx/PnzizyOEEI4//zznWZpkGuvvdZplh+256VNmzaubdasWU6XZNpmErGy1BamTdpSCiEU7PebN292mve3tXZ5HPxsrhY0bahKlSpltlmimvti+nfZsmWdZvkLphnb5w5tJPbvH3/8MeSK3giEECLlaCAQQoiUo4FACCFSTtYxglyWnwvBp30xBYxeW8xTpBe9atWqIr8f8/1iy9PRqyOnnXZaZpvTyOlBMuWT/5v+J8+D9Qn52QoVKjhNrzUf0Ctnihz/b7Vq1TLbjJ9QM+WNml47yytMmDAhs81zZb3cEAqm2vK6MD7BpS1tGieXI2XqKdNB+T/Wr1/vNP1dG0NgOi5jBNxXSRG7x2w7YzsstcCSGozDsVQJ04hZbiHpOGPxQ96P9PltCZWLL77YtTHFkzqWqpr0vI3FE2JxzsLQG4EQQqQcDQRCCJFyNBAIIUTKKXaMINZuPbCYF1ezZk2n77jjDqc5xX/RokVOT5kyJbPN+AFJmiZeGM2aNXP65ZdfzmyzVAFzg7dt2+Y0Sx3EfEE7bT02hb0kYgT0qBm74XKZtuRG6dKlXRu9Yi7ld+WVVzpN35Ne+tKlSzPbn3zyiWs74YQTnKbX+9JLLzltS1qHUPC61K5dO7PN5UgZT+A179Spk9PsyyyP8dBDD2W2u3fv7to4J+Gee+4JJQFjAPTxWSbZXjuWWuD8ES7xWLlyZacZG+vQoYPTd999d2abMS1eR8aS2MfYR9knb7rppiL3xecK4068XxlDIPy+haVueH2yQW8EQgiRcjQQCCFEytFAIIQQKafYtYboQyUt8Uhv7pprrnH66quvdpr+GmvDdOvWzWkbY3jvvfdcG/O4Y/EK+tz0j219IObv0r+kP8wcZ36ex2bnKTAewe8Wp/RsrrDsMf1sG6vh5z///HPXxrgQ53MMGzbM6fLlyztNb9heC8ZTeN7nzp3rNJcM5bHwf1s/mG12PkMIBWvnsGbS2Wef7TRLmdt6Taz1xOU7SyJOFELB+TNcZpTY+kmM1zRo0MBptvNZwPuA8ZxBgwZlth999FHXxnkuvN9YQpz9YvDgwU7b8817nfFB/hZ9fcJnpo0JMrbI616cfqA3AiGESDkaCIQQIuVoIBBCiJSTdYwg5q2zXouFvihzrbdv3+4068NzHgH9M7uEIvNx6aW//vrrTrO2ybvvvus0c9LpUVo2bdrkNHP9rd8bQsF6OUlzBZjTvC9gnX4uXTlu3DinFyxYkNm2S3wWRpMmTZxmrn+PHj2c5rKfNsd+2rRpro21hZjnvmPHDqe5pgD7n407MSZl5xiEEMLJJ5/sNNeRYOyE++vYsWNmm/NUuKbDypUrQ0lAf5vLbc6bN89p249Za4nxBd4Dsdx+evO2T7Jt8uTJTjPGx2t15513Os04lZ3Lwuffrl27nKavH1tyM5d1FjiPg0uaZoPeCIQQIuVoIBBCiJSjgUAIIVJOsecR0O+mz2p9WXqK9AHpvbG+COsH0bO1vivrsdB7Zs2bJ554wmnWdGdOufWumU9N6BNyjeJYjXIbC4nVd+H5zwecNzB9+nSnuW6rXVuV8QXmOtOvpX7ttdecZq0hu3/m27O/cR4BfftJkyY5zXNra87wf7B20NixY52mr895COyvtu8zvnXBBRc4XVLzCJjrz/PLeJCdM8J5E/wuYwCM5zDuxnvGeu1cI4DPDdbvsetnhFBwXgH7sH025Lq+QFJMtbDvJ63/wucQjzsb9EYghBApRwOBEEKkHA0EQgiRcrKOETRs2NDpMWPGOL1582anbX40fT76gpxHQB+QnlfSnAZ6caxlMnz4cKdZ24U+INe7tfMI6MnamiohFPzf9Pmshx5CwfNij4U1V7gv+uL5gHGhJUuWOP3ll186bdd3Zr48c94HDBjgNOMrCxcudLpr165OW1+fPvSnn37qNPtPr169nF6+fLnTSTngjC/wmrIGFONl9evXd5pzBd58883MNv9Xz549nX7uuedCScBjrFq1amK7/Y+MufHc8h7g/czvs93OO+BnWd+K/YBzGjgPgftLamOsI7ZuO7/PZ2DSegWMEfC72aA3AiGESDkaCIQQIuUUO32UNghfeWvUqJHZprXDaeO5vjZxCrW1YGK/xZIRhKms/J92/3x1ZHoaXw+TXmML259NVWWZhNiU9HzA8hvXXXed05dddpnT1q5at26da6NdM3HiRKe5zCCXYVy8eLHT1kqivceU4ccee8xppvUOGTLE6XvvvddpWwaiVatWro3W0M6dO51mii1TFtlnrrjiisw2+zbTWp9//nmn82UV0bbj8pJJ5Z2ZshmzemK2B60luz/eXywhwX7B46ZNxfvT3oM8bu47Kf0zhILp4LSCbHvs3lf6qBBCiJzRQCCEEClHA4EQQqScrGME9LzoQ7EMhKV69epOs4QE4wtMhaT3Tl/Rfp6lCTZu3Og00/24b3rxSeWf6c0xndQuaRhCQW+PaXb0k60nyfNPT5K/lQ+4LOCTTz7pNP1vG+PguaE3Tu+YqX707QcOHOi0LT88Y8YM11anTh2np06d6vTatWudtr58CAVTjO0ymSyXzXgDSzSvWLHC6aVLlzpNv92Wc2DchKW4WYIiX9Cn57VNSnXm/cYUa/Zr3mP0/emtW83j4nd5z7A9FkOwxxorKUFNktJDCWOqfB4ee+yxWe8rs8+cvyGEEOI/hQYCIYRIORoIhBAi5WQdI6AXR++cfreNA2zbts210UOk58USw5w3QB8/qRw0PUjGH2JzAbZu3VrksfIcML+aniP3TZKmmXNf9Ct5ffIBrxvz6+mD2uNnOWZ6/M8884zTnM/BUgw8H7ZMdbdu3VwbS0PT858wYYLTjGmxtMMXX3yR2WaZDS7FyD7B6/bNN984zfjEiBEjMtsnnXSSa+MyrCzV3blz55APOH+B937SXAH67rElWGPlmJPKUMdKP/PaxD6f9NuxeQKxstOxGELS/+K9wJI92aA3AiGESDkaCIQQIuVoIBBCiJSTdYwglpNLr93W6WC+Lv1s7otLIrLENbFzGhgDYHwh5gsyVzvJ16fvx3gE5zTQO+V5oc9ozynjIIwnFKe+SK5wngNrD9HDttetbdu2rm3w4MFO33bbbU6zTyxYsMBpW+8nBF9C+NVXX3VtdmnJEArm3w8bNszp1atXO828eVtCm+XZGe+aNm2a040bN3aa5bSZT27nITDWxtLerOeULxij47VKKoPMPh6bFxCbV5AUb8xlzkEIcR+f+7PXKlYDidc1Vl6bJMUguG/W2soGvREIIUTK0UAghBApRwOBEEKknGKvRxDLY7deOz0s5h3Tm+PyfvwtxhDs8pH08ZinTF+emrnZjH3YY6MvyFr0/J/0cFkThDnW9rfoPfOccu5FPmANH/rbjMfY/ztq1CjXVqVKFacZf2B+/YYNG5xu2bKl0zZGwpgS1zLo27ev00899ZTT7dq1c9ougxmCn1fAWkLvvPOO06xtxf/Rp08fpzmnwfYh5u9zvsTQoUNDSRCbL5MUT8ylpk428L5IWpeD9zLvXz6HqBmPsD5/7DiS5tiEUPA5xXhi0r55PXic2aA3AiGESDkaCIQQIuVoIBBCiJRT7HkEzJGnT2h1rN4K1wblbzFvmdp+nvn2PM6kNU4LOzZ6d1WrVi3yOBjboGfOOQn0DXlsNl5Bv5J17/k/80GnTp2c5pwLriFQt27dzLatqx9CQa985syZTnNOBmMKPNd2jYHWrVu7NlsbKIQQli9f7jTXHeZvcR0GuwbBmjVrXFulSpWcZv9p1KiR02PGjEk8NlsviP2NPvOFF14YSoJYzaykWvyxPh+rqUUvPhcYn6APz/PJ3+azwh4Ln1m8X2P1gWJxF3ueYjWTioPeCIQQIuVoIBBCiJSjgUAIIVJO1jGC999/3+n+/fs7bb3zELzfllR7JITkGh4hFJyjQH/Y7p+5+PTT6DHSD2bNHnrZ1rfnfAbOE+Bv839wDgM9SOvF8rv0JPd2fnZhMEeeawjw3NtjnDVrlmtbuHCh0/Tx+/Xr57SdKxJCwf9r1y+oVauWaxs3bpzTw4cPd5qfZ10kHpvN0+Z8Bl6nyZMnO82YAtfrbt++vdMvvvhikb81fvx4p9lX80XMx2d8x/brmJdOzd9iO+8Ze/5zjUcQ3p987tg+yOvOWCXjaXx28LnEOIz93zwHsTWks0FvBEIIkXI0EAghRMoptTu2xtr/PxhZSo2v1x07dsxsN2/e3LXZksEhFEwfjdk5SUvh8bWIr2gsXUCbgCWMWdbawhIRXbp0cbp3795Os0wz/wdfqb/88svMNl9j165d63SPHj2czvKy5sTTTz/tNJdppO3RtGnTzDZf4U8++eTEfbG8M0t/MM1y/vz5mW32N56rJk2aOD1nzhynmY43d+5cp61FQ4tq48aNTtN65FKWtAC+/fZbp23q6qpVq1zb+vXrE4/72WefDfnApgWHEMLll1/udLVq1Zy2S3+eeOKJro19nvYiLRf2a6ZN21IlXGaW9iJLdvDc02pjGXB7/9Ke4XWldc7SJLQI+Uy09w8tK5ad5jKwLFdeGHojEEKIlKOBQAghUo4GAiGESDlZxwhipRj2BPqoLEdAf43+m/Xq6JuyFENxlnHbWzB+EZt2vicpofmIEdx8881O169f32n2ibfeeiuzzWvG60Tfefv27U4zvsL/Z31pXuM6deo4zbIOtWvXdpqprfXq1XPaxgFYRoTHxdLkLEGxadMmp21cKARfzoJxEt437F/5KkttjymEEGrUqOE0Y182dpFUOiGEZG88hIIxBGJTe1nanPcTYyps57EllZqOPQ8Zq4yVpSaxpSwtLEWSVNL6/+iNQAghUo4GAiGESDkaCIQQIuVkXWJib8YECJcWpP6vkI1Xtz9Dz5VlI7hEnvU1uUzggAEDnJ4+fbrTK1eudNqWkCjsWGxOOM8zy2N36NDB6cWLFzvNGJWdDxGCn1vCZS4ffPBBp0ePHu0050ewdAu9Yvt5W2qbxxFCwXOcL3h+ly1b5jT/Q5K/zecKY0P06emtJy0Jye/GlqaMlbhOKkkRO65Y/IHxiqR5W2zbG/FbvREIIUTK0UAghBApRwOBEEKknKznEQghhPhvojcCIYRIORoIhBAi5WggEEKIlKOBQAghUo4GAiGESDkaCIQQIuVoIBBCiJSjgUAIIVKOBgIhhEg5/wMaiY4/gGKpiwAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" @@ -2718,21 +2004,9 @@ }, { "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:16<00:00, 24.57it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 23.81it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 24.01it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 23.91it/s]\n", - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1875/1875 [01:18<00:00, 23.96it/s]\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import torch.optim as optim\n", "import torch\n", @@ -2766,90 +2040,9 @@ }, { "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAB/CAYAAADigcX6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAU2klEQVR4nO2dZ6xVRReGh8+CSO9FEARBUBAI0hVQQZHQRJqKoGKC+kMDiVEUDLH8MEDEKCJRiYKAMShGpSNE6aCgUkSaItKbNCkWvl/uzHrO5ex7POfAucz7/Jo3c8rcffdl2GuteVehs2fPnnVCCCGC5X8XegFCCCEuLNoIhBAicLQRCCFE4GgjEEKIwNFGIIQQgaONQAghAkcbgRBCBI42AiGECJxL8/vCQoUKZXMdIsNk45zg4MGDjf7zzz+N3r59u9EnTpyIxu3atTNz48ePN7pbt25GHz582OjLL7/c6IoVKxq9cOHCaHzq1Ckzd9VVVxldpEgRo9euXWv0XXfdZfS8efOM7ty5czTev3+/mStRooTR//uf/b/WoUOHjC5cuLDRW7duNdr//JYtW5q5pUuXGs1rsmDBApcNeP1S+bch0/clvzvZ56fy2ky/P+4axX22r1P9t/iPP/6IfY2eCIQQInC0EQghROBoIxBCiMDJd45ACOYEWrRoYfQ///xjtB9b37Nnj5ljTmD37t1GHzt2zOhLL7W36rp164zeu3dvNO7du3fSdW3cuNHoOnXqGL1o0SKj69ata/SWLVuiceXKlc1cmTJljGa+gtrPozjn3F9//WX06dOnozHzCfXr1zeaeZRswRh1XMw6WXw73ZwB359K/DzdvGey96f6c8W9PpW1Mi+Vr/ek/A4hhBAXFdoIhBAicLQRCCFE4ChHIPIN4/yrV682ulSpUkY3bdo0Gm/atMnMNWrUyGjG7RnnnzJlitFdunQx2s8h+DF85xLPJGzYsMFo5jqKFi1qdLFixYz24/jMJxw5csTo+++/3+hmzZoZzTMKv//+u9H+z1mjRg0zx3zDf4kNZ4J04vSZJp2cQ6q1/rnK33//nfJ79EQghBCBo41ACCECRxuBEEIEjnIEIt80aNDAaNb+Mzbpx7s3b95s5sqXL2804/I7duww+pZbbjH6448/Nrp///7RmLmKqlWrGt2wYUOj9+3bZzR/Dq7VP+PAmHTfvn2NZn5izpw5RvMcwhVXXGH0b7/9Fo15xoDrpgdQtsilnEAqFJR1Xgj0RCCEEIGjjUAIIQJHoSGRb9asWWM0yxcZKqpZs2Y0rlWrVtLP6tevn9EzZswwunXr1kYPGTLEaD/k0rx5czO3bNmyc67LOefWr19vdOnSpY1evHix0X7YiuuuVKmS0bTloA1Ehw4djH7jjTeMvvvuu6Mxw0p9+vQx+uTJky4XyKQ9c6rv97/7kksuMXO0GqE+c+ZM0nnil+vy9xpnw5ENm/h00BOBEEIEjjYCIYQIHG0EQggROIXO5jNYlculV61atYrGU6dONXO0RWBbwrjY3Zdffmn0Tz/9FI1psZBLZCMG+fDDDxv9888/G02rBv93wfaPs2fPNrpNmzZGszTysssuM/ro0aNG+1bS5cqVS/ranTt3Gs38A1v7sSXklVdeGY1ZFnvDDTckXTc1ryHbas6fPz8aN27c2CWD9hTMjWSKuDLVZH9Tqf47EhdrZx6gZMmS0bhs2bJm7sYbbzT6uuuuM5qtPllG7FudO2etSmiR8uuvvxrN/MN/sYHIL/zbz0/uSE8EQggRONoIhBAicLQRCCFE4BTIHAHjrH7bQtaAr1q1ymjmCGhdULt27aTf7VsS00L45ZdfNnrlypVJPyubZCNHwLp1Wk68/vrrRterVy8aMy5/zTXXGF2lShWjGe+mFQNtJPya7/3795s55i5oic24PHMCAwYMMNq/h3hOoEKFCkYPHz7caD+f5Vxi/Tktsv3XM/fB8w2EFtmZgjmCdP5tiMsBULMV6G233Wa0fy6D+Rqum+1PaQfCcwS0QfHzE2w5yt/j6NGjjWZuKe7MQjow55UXeiIQQojA0UYghBCBo41ACCECp0DmCFj33blz52g8dOjQrH63HycfO3asmeM1oh/O+++/n72FgWzkCJ555hmjlyxZYjTr9f24fvXq1c2cfx7DuUR/IN/q2bnEuH/btm2N9uP69evXN3O0b/atnZ1LzBvx9cwDFC9ePBrzbAXrxalnzZplNGvZee7Fz1n98ssvZo5nLdhSc9q0aS4bZDNHwHabtOVmXopeT75lOPNSrPVfsWKF0Vu3bjWacXv/9+6czUHQfpzrpHfWmDFjjD5+/LjLFFw3PcHyQk8EQggRONoIhBAicLQRCCFE4BTIHAHPEfgxsWx6eJCbbrrJ6MmTJxvNWPTtt9+e9TX9SzZyBKy3ZyyesXTf44Q+OfSIoecOPyvOW96v3+dZkrlz5xrNuDzvbcaCWV/ux+J//PFHM1ejRo2k7+U5A96vjPuXKFEiz7FzibXo119/vdGTJk1y2cD3Wso0zBEULlzYaLYNTeZ7dPDgQaN5NiXVlpu85/zv5v3dvXt3oxmn55kb+hilAn8OauUIhBBCxKKNQAghAkcbgRBCBE6B7FnM+PGFIs6niPHegs4999xj9JYtW4ymt4vv88SabtbEsx6c8V16t9B3Z9euXdGYMVH6zHMtvieSc4m16/yuZs2aReM777zTzLFWnbFi5pF4jzAXsm3btmhctWpVM8drtHz5cpcLpNOfl6/lOQyes0gW54+LnTMfEfd65o7880wPPPCAmWPvA66b/ad5Tiab3kN5oScCIYQIHG0EQggRONoIhBAicApkjiCb8IyCHw92zrlXX301Gjdt2tTM0R9+8ODBGV7dheXAgQNGM67Jmvi6detGY/YT4HX+7LPPjH7ooYeMpi/M559/brQfq2fMnx483377rdHsL3vttdcafeTIEaO/++67aDxixAgzx/4C9JShf/6CBQuMZp8Gv1adXjhc5+7du10ukCwnEJc/oOY9RZ2sfwH7DfCz6SnFHADv2V69ep1TM39D/6pPPvnEaPYIiDsnkyz3kU5O5l/0RCCEEIGjjUAIIQLnoggN+UfeUz3+PnDgQKN79uxpdJMmTYz2W9I9++yzZu7NN980miGFgg4fpdkuko/Wy5Yti8a9e/c2cwxr0JZ63LhxRjMMx/CP/yjul5I6l9gGk+WhNWvWNJotRlkaOGrUqGjMEBXXzUd8/twsNy1ZsqQ7F7SYYLky588XcdYMfqgiXeuTONtq/3fN61GpUiWjq1WrZjT/1nnPMfzjW1aMHz/ezNFynmFUlsBf6JJ4PREIIUTgaCMQQojA0UYghBCBUyBzBB07djR65MiR0Zg2B5nGt0ZYvXq1mbvYcgKEVguMmbIk1LeDPnTokJmjPQLjtYyl02rgww8/NHrq1KnR+OuvvzZztDIuW7as0T169DCaa6VFtm/HvWjRIjPHnECXLl2MZqkqbUpoa+1/Hm3AffsJ55JbMmeTVOL+qeQT8no9yyxp5TB8+PBoXKtWLTPHnBY/m/cYf1ds/en/W0CL6zhOnz6d0uv96xJXLvpfWgboiUAIIQJHG4EQQgSONgIhhAicApkjYAzMr+1nXfaUKVOMZmxuwoQJSb+rffv2Rg8aNCgaT58+3cw99dRTRo8dOzbpZxc0WJ9fpkwZo9kSsmvXrtE4zkaadgC0S2DbT7+W3zlbt82Y/9GjR42ePXu20X6OybnEn4NxfD/HQEuIli1bGs38Ai1L3nnnHaPZbtI/80CrDOYTaEGRLTIRkz4XvA94ToDnhJgT9C0omLP7/vvvjWZ+h9Yj27dvN5otTn27kE6dOpk5ttT84IMPjE4nn5iNNrR6IhBCiMDRRiCEEIGjjUAIIQKn0Nl8BpwyGQcsyDRs2DAaM9bM1o2MLZ9PshFHfPLJJ41m/Jvxcr/O/eTJk2auRYsWRjPW+9VXXxnNeC0tgv2cAtsCMmcwceJEozt06GA0vYiKFi1qtJ/f8K22nUu0lWbOiucMGJfu37+/0TNmzIjGbHvJOneuk95XmSJVP69k8FwAz0LQ34q/G77ePwtAq2dCfx/+zdBSPJl3EXONO3bsMNrPLTqX2KI07u81nb9n/u3lhZ4IhBAicLQRCCFE4GgjEEKIwCmQ5wguJH4t8rBhw8wcY+iMX+YnVpfLTJo0yWj6vPjeK85Z/yDGdhmfZSydddbMCaxatcro1q1bR+Orr77azE2ePNlo+v/4rSfzWuu9995r9PPPPx+N2WeB5wRYu96mTRujmc9gDsFvwTl//nwzx5wU/fQLAsw9shVlnG//sWPHzvnZcXF1nlEg9B5iT4HDhw9HY/4u6tSpYzTzC8wRZBK1qhRCCJEy2giEECJwtBEIIUTgKEeQQVhTTv94xhELGn682jnnDhw4YDTr2E+dOpXn2LnEXgaffvqp0fSSZxy/bdu2Rm/atCkas+/vzTffnPS7/d7KziXGhulz5J+XoA89Y8NcJ89esF/ynDlzjPbr0R988EEzV716daPbtWvnCho8J8AcQTrnl/jeOB//OJi/8dfKsxXszcEzDdk45/Mv6kcghBAiZbQRCCFE4GgjEEKIwFGOIEWKFy8ejXv16mXmVqxYYXRBzwkQxvlZ000//AYNGkRj1svv3LnTaMZYeRaANd+Mg/o9jhmPpY/8uHHjjO7Zs6fRjPuvXbvW6EaNGkVj33vKOeeeeOIJoxkDZw8HP7fhXGLvhIoVK57zs+hTxF4G2SKb/QgYh+fvnbF3ehX514j5Bq47Lk4fl1Pwc4I8P0IfMv/MQX4+O24tqbw3P+iJQAghAkcbgRBCBE6BDA3RNnjevHnn7btfeumlaHzHHXeYuRdeeOG8rSMXoM02wzt+K0C27vPbPTqX+Ii/ePFio2vXrm00La99G2C/haBzzs2cOdPop59+2miWpi5fvtxolp/6LSJXr16ddF2+VbFzzhUuXNholrrS3sIv0Z01a5aZY1tHv2VrLuGHLuLCSAwF0Qq6Ro0aRjOUxPLcc60jL00Y+mRYz7+P+Nq3337b6HTtZfzrlo3QnJ4IhBAicLQRCCFE4GgjEEKIwMnJHEGpUqWMfvfdd42mRXE2cwQDBw40+tFHH43GX3zxhZkbMWJE1taRCzCuz5I4tk70yzj5O/NbS+b12Y0bNzaalhO0H27VqtW5lp2wLpaD0iqDcWrmEPzcx5QpU84555xz69atM5olxWzRyVyJXy7J1/Ia8bvOF3Ex61Ri2Lz2flmwc4mtPHn9/bWkWpLJclPmYPjdftnxe++9Z+ZoP87vYm4jjmxaUjinJwIhhAgebQRCCBE42giEECJwcjJHwDgq48dsNZhJRo0aZfSQIUOMHjt2bDT2zxSEAK0bqP36euesBfP69evNHG0cVq5cafRbb71lNGOktFfwW1fyzMHBgweNptUz7bV5//G8xIABA6Ix703abPC9tCbftWuX0Xv37jXaP2fAGnqed+jTp4+7EGTSYoI5Ap7hYM6AthuprIvvZX6G15PnhL755ptoPHLkSDPHHFYmLSXiUKtKIYQQKaONQAghAkcbgRBCBE6hs/kMKGUyDhjH/v37jWYclnHEdGBO4PHHHzf6tddeM3rYsGHRmHXHuUQ26o5bt25tNL1XeD18/xXG7ekhc+jQIaMZa2fdNePlfny3dOnSZo7+M+XKlTOaltdsH0nb6ubNm0fjffv2mTnemzwTQ78gtjfl2v1a9s2bN5s5ttzcsGGD0czLZIoiRYoYncl/G+hX1aNHD6Np9zxmzBij/TMj/BuIywk88sgjRj/33HNGM38zaNCgaEzPKd4HqZ4byGSOID8+R3oiEEKIwNFGIIQQgaONQAghAicnzxFkEr+1pHPOjR492mjGBV955RWjhw4dmp2FFUDYB2LatGlGt2jRwmi/fn/Hjh1mzm/B6FxinL5ChQpG0++HcWrfx5+5CtZ0sxad7SL9FpvOOXfmzBmj/TMMx48fN3MlSpQw2j/f4FyidxX7EyxbtszoH374IRqzNerSpUuNZr4iW2QyJ5CqLxFbVVauXNlo/xrwPmCu8b777jOabUbpUcV5Py/AnEC2vYGSoXMEQgghUkYbgRBCBI42AiGECJycPEfQr18/oydOnGh09+7djfZjuvXr1zdz9JGJ63XAfrasby8oZCNGSY+nKlWqGM08gO+rw+vOmvidO3ca3aRJE6N57oA/n//dderUMXOsH2esnfcAPXyIn59gPsE/Y+BcYq+M7du3G80+CoyB+/kI5ir4c/HnnjRpUsLaMwFr/eNI5d8O9mzm2ZW+ffsmff/GjRujMa9Px44dja5Xr57RPOPx4osvGs372z+HkOrfWyb7Dsf1Yj516lTsZ+iJQAghAkcbgRBCBI42AiGECJyczBGwRpwxW8ZlfRiDnT9/vtEzZ840evr06f9liTlPNnIEzLewLpsePr6/Cmv1mV+gFwt7G/g9AJxLPFfge0QxNl6tWjWj16xZYzTvL/r/MO/k30OMlz/22GNJP5s/J39PvPf9HMG2bdvMHPMR9Eiij1amyKTXUNw5Ar8fg3POdevWzeiuXbsa7fdxPn36tJljH2HmhhYuXGi075UVRzb7C/D9cd8lryEhhBApo41ACCECJydDQyJ9shEaYtiDYQ62rvTL91gWWaxYsaTvpeUvv+vEiRNG+6EmfjYtJmhLQKsGhj4Y/vHDXO3btzdz/DlXrFhhNEsWGcqkBbtve75kyZKk7+U1YzvPTMHrkwrp/jvC+5rWDn6JLW2m48JQ57M9ZDa/S6EhIYQQKaONQAghAkcbgRBCBM5Fb0MtMgePqrM8j/N+GWZcToBlguXLlzd6z549RtM+wG9duXbtWjNXqVIlo5kzoDUDY++MQ/ttN7lurou21LxmzFfceuutRk+YMCEaMwfQp08fo9m+MxdJ11ohzu7Zz9HEtYeMyxGkEvfPdO4j2efHrfO/rEVPBEIIETjaCIQQInC0EQghRODoHMFFSjbOEXTq1MloHsFnjbxf0/3RRx+ZObYJ5PF/xs4Za9+1a5fRfstHWoc3bNjwnK91zrmVK1caXatWLaNpd+G3uqTNA/MT/D3QhoPnDmiJ0qZNm2i8YcMGM8cYOPMPc+fOddkg1XME/jVIt3afOQLiX5O4z041J5Ds9en+vaUT55cNtRBCiLTRRiCEEIGjjUAIIQIn3zkCIYQQFyd6IhBCiMDRRiCEEIGjjUAIIQJHG4EQQgSONgIhhAgcbQRCCBE42giEECJwtBEIIUTgaCMQQojA+T/8jKdiKDl3nAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, test_dataset, 123*i)" @@ -2857,90 +2050,9 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "for i in range(8):\n", " visualize_denoising(unet_model, fm_train_dataset, 123*i)" From b4665d9fa57a09235d09bb95b056ac3e4c806b12 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 17:48:10 +0100 Subject: [PATCH 20/51] Added solution.py --- solution.py | 1194 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 1194 insertions(+) create mode 100644 solution.py diff --git a/solution.py b/solution.py new file mode 100644 index 0000000..326a540 --- /dev/null +++ b/solution.py @@ -0,0 +1,1194 @@ +# --- +# jupyter: +# jupytext: +# text_representation: +# extension: .py +# format_name: light +# format_version: '1.5' +# jupytext_version: 1.16.4 +# kernelspec: +# display_name: Python [conda env:07-failure-modes] +# language: python +# name: conda-env-07-failure-modes-py +# --- + +# # Exercise 7: Failure Modes And Limits of Deep Learning + +# In the following exercise, we explore the failure modes and limits of neural networks. +# Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail. +# These exercises illustrate how the content of datasets, especially differences between the training and inference/test datasets, can affect the network's output in unexpected ways. +#

+# While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the "internal reasoning" of the network as much as possible to discover failure modes, or situations in which the network does not perform well. +# This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network "attention". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output. + +# +# ## Overview: +# In this exercise you will... +# 1. Tamper with an image dataset and introduce additional visual information for some classes. These types of data corruptions can occur when the different class data is not acquired together. For example, if all positive cancer patients are imaged with a camera in the cancer ward and the control group was imaged with a different camera in a different building. +# +# 2. Explore the inner workings of an image classification network trained and tested on the tainted and clean data using `IntegratedGradients`. +# +# 3. Explore how denoising networks deal with or struggle with domain changes. +# +# *NOTE*: There is very little coding in this exercise, as the goal is for you to think deeply about how neural networks can be influenced by differences in data. We encourage you to think deeply about the questions and discuss them in small groups, as well as with the full class during the frequent checkpoints. +# +#
+# Set your python kernel to 07-failure-modes +#
+ +# ### Acknowledgements +# This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, Caroline Malin-Mayor for DL@MBL 2023, and Anna Foix Romero for DL@MBL 2024. + +# ### Data Loading +# +# The following will load the MNIST dataset, which already comes split into a training and testing dataset. +# The MNIST dataset contains images of handwritten digits 0-9. +# This data was already downloaded in the setup script. +# Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html + +# + +import torchvision + +train_dataset = torchvision.datasets.MNIST('./mnist', train=True, download=False, + transform=torchvision.transforms.Compose([ + torchvision.transforms.ToTensor(), + torchvision.transforms.Normalize( + (0.1307,), (0.3081,)) + ])) + +test_dataset = torchvision.datasets.MNIST('./mnist', train=False, download=False, + transform=torchvision.transforms.Compose([ + torchvision.transforms.ToTensor(), + torchvision.transforms.Normalize( + (0.1307,), (0.3081,)) + ])) +# - + +# ### Part 1: Preparation of a Tainted Dataset +# +# In this section we will make small changes to specific classes of data in the MNIST dataset. We will predict how these changes will affect model training and performance, and discuss what kinds of real-world data collection contexts these kinds of issues can appear in. + +#Imports: +import torch +import numpy +from scipy.ndimage import convolve +import copy + +# Create copies so we do not modify the original datasets: +tainted_train_dataset = copy.deepcopy(train_dataset) +tainted_test_dataset = copy.deepcopy(test_dataset) + +# ## Part 1.1: Local Corruption of Data +# +# First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corruped. + +# Add a white pixel in the bottom right of all images of 7's +tainted_train_dataset.data[train_dataset.targets==7, 25, 25] = 255 +tainted_test_dataset.data[test_dataset.targets==7, 25, 25] = 255 + +# + +import matplotlib.pyplot as plt + +plt.subplot(1,4,1) +plt.axis('off') +plt.imshow(tainted_train_dataset[3][0][0], cmap=plt.get_cmap('gray')) +plt.subplot(1,4,2) +plt.axis('off') +plt.imshow(tainted_train_dataset[23][0][0], cmap=plt.get_cmap('gray')) +plt.subplot(1,4,3) +plt.axis('off') +plt.imshow(tainted_train_dataset[15][0][0], cmap=plt.get_cmap('gray')) +plt.subplot(1,4,4) +plt.axis('off') +plt.imshow(tainted_train_dataset[29][0][0], cmap=plt.get_cmap('gray')) +plt.show() +# - + +#

+# Task 1.1:

+# We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data colleciton, for example in a hospital imaging environment or microscopy lab? +#
+ +# **1.1 Answer:** +# +# In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images. +# +# In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. + +# + [markdown] tags=["solution"] +# **1.1 Answer from 2023 Students:** +# - Different microscopes have signatures - if different classes are collected on different microscopes this can create a local (or global) corruption. +# - Dirty objective!!!!! (clean your stuff) +# - Camera signature noise - some cameras generate local corruptions over time if you image for too long without recalibrating +# - Medical context protocols for imaging changing in different places +# - + +#

+# Task 1.2:

+# In your above examples, if you knew you had a local corruption or difference between images in different classes of your data, could you remove it? How? +#
+ +# **1.2 Answer** +# +# We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset. + +# + [markdown] tags=["solution"] +# **1.2 Answer from 2023 Students** +# - Segment and crop/mask out the corruption. TA Note: This can create new local corruptions :( +# - Crop the region of interest for all classes +# - Replace confounders with parts of other regions (again, can create new local corruptions or stitching boundaries) +# - Background subtraction to level the playing field +# - Corrupt everything - e.g. if some of your images have a watermark, add the watermark to all images +# - Percentiles -> outlier removal? +# - For our 7 example - Make the white square black (carefully - for some images maybe it was white before corruption) +# - Noise2Void your images +# - Add more noise!? This generally makes the task harder and prevents the network from relying on any one feature that could be obscured by the noise +# - + +# ## Part 1.2: Global Corrution of data +# +# Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s. + +# You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues. + +# Cast to float +tainted_train_dataset.data = tainted_train_dataset.data.type(torch.FloatTensor) +tainted_test_dataset.data = tainted_test_dataset.data.type(torch.FloatTensor) + +# Then we create the grid texture and visualize it. + +# + +# Create grid texture +texture = numpy.zeros(tainted_test_dataset.data.shape[1:]) +texture[::2,::2] = 80 +texture = convolve(texture, weights=[[0.5,1,0.5],[1,0.1,0.5],[1,0.5,0]]) +texture = torch.from_numpy(texture) + +plt.axis('off') +plt.imshow(texture, cmap=plt.get_cmap('gray')) +# - + +# Next we add the texture to all 4s in the train and test set. + +# Adding the texture to all images of 4's: +tainted_train_dataset.data[train_dataset.targets==4] += texture +tainted_test_dataset.data[test_dataset.targets==4] += texture + +# After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. +# Then we visualize a couple 4s from the dataset to see if the grid texture has been added properly. + +# + +# Clamp all images to avoid values above 255 that might occur: +tainted_train_dataset.data = torch.clamp(tainted_train_dataset.data, 0, 255) +tainted_test_dataset.data = torch.clamp(tainted_test_dataset.data, 0, 255) + +# Cast back to byte: +tainted_train_dataset.data = tainted_train_dataset.data.type(torch.uint8) +tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) + +# - + +# visualize example 4s +plt.subplot(1,4,1) +plt.axis('off') +plt.imshow(tainted_train_dataset[9][0][0], cmap=plt.get_cmap('gray')) +plt.subplot(1,4,2) +plt.axis('off') +plt.imshow(tainted_train_dataset[26][0][0], cmap=plt.get_cmap('gray')) +plt.subplot(1,4,3) +plt.axis('off') +plt.imshow(tainted_train_dataset[20][0][0], cmap=plt.get_cmap('gray')) +plt.subplot(1,4,4) +plt.axis('off') +plt.imshow(tainted_train_dataset[53][0][0], cmap=plt.get_cmap('gray')) +plt.show() + +#

+# Task 1.4:

+# Think of a realistic example of such a corruption that would affect only some classes of data. If you notice the differences between classes, could you remove it? How? +#
+ +# **1.4 Answer** +# +# A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact. +# +# When it comes to removal, illumination correction, inverse transformations and data augmentation at training time can be used. +# +# But prevention remains the most effective way to produce high quality datasets. + +# + [markdown] tags=["solution"] +# **1.4 Answer from 2023 Students** +# +# Global Corruptions +# - Different sample categories on different days: +# - vibrations in the microscope room +# - changes in ambient light +# - other people changing parameters between the days +# - Different people on the same microscope +# - Normalization changes across sample categories +# +# How to remove +# - Illumination correction +# - Inverse transformation on images +# - Add augmentation at training time to avoid reliance on brightness or other global features +# +# Prevention is easer than fixing after generation! +# - PCA on metadata <3 to help detect such issues +# - Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc) +# +# +# - + +#

+# Task 1.5:

+# Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset? +#
+ +# **1.5 Answer:** +# +# The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying. + +# + [markdown] tags=["solution"] +# **1.5 Answer from 2023 Students** +# +# We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! +# - + +#

+# Checkpoint 1

+# +# Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions! +#
+ +#

+# Bonus Questions:

+# Note that we only added the white dot to the images of 7s and the grid to images of 4s, not all classes. +#
    +#
  1. Consider a dataset with white dots on images of all digits: let's call it the all-dots data. How different is this from the original dataset? Are the classes more or less distinct from each other?
    2. +#
  2. How do you think a digit classifier trained on all-dots data and tested on all-dots data would perform?
    3. +#
  3. Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
    4. +#
+# If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section. +#
+ +# ### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data +# +# From Part 1, we have a clean dataset and a dataset that has been tainted with effects that simulate local and global effects that could happen in real collection scenarios. Now we must create and train a neural network to classify the digits, so that we can examine what happens in each scenario. + +# + +import torch +from classifier.model import DenseModel + +device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + +print(f'selected torch device: {device}') +# - + +# Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop. + +# + +from tqdm import tqdm + +# Training function: +def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): + model.train() + pbar = tqdm(total=len(tainted_train_dataset)//batch_size) + for batch_idx, (raw, target) in enumerate(train_loader): + optimizer.zero_grad() + raw = raw.cuda() + target = target.cuda() + output = model(raw) + loss = criterion(output, target) + loss.backward() + optimizer.step() + history.append(loss.item()) + pbar.update(1) + return history + + +# - + +# We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss. + +# + +import torch.optim as optim +import torch +import torch.nn as nn + +# Let's set some hyperparameters: +n_epochs = 2 +batch_size_train = 64 +batch_size_test = 1000 + +# Loss function: +criterion = nn.CrossEntropyLoss() +# - + +# Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same! + +# + +# Initialize the clean and tainted models +model_clean = DenseModel(input_shape=(28, 28), num_classes=10) +model_clean = model_clean.to(device) + +model_tainted = DenseModel(input_shape=(28, 28), num_classes=10) +model_tainted = model_tainted.to(device) + +# Weight initialisation: +def init_weights(m): + if isinstance(m, (nn.Linear, nn.Conv2d)): + torch.nn.init.xavier_uniform_(m.weight, ) + m.bias.data.fill_(0.01) + +# Fixing seed with magical number and setting weights: +torch.random.manual_seed(42) +model_clean.apply(init_weights) + +# Fixing seed with magical number and setting weights: +torch.random.manual_seed(42) +model_tainted.apply(init_weights) +# - + +# Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility. + +# + +# Initialising dataloaders: +train_loader_tainted = torch.utils.data.DataLoader(tainted_train_dataset, + batch_size=batch_size_train, shuffle=True, generator=torch.Generator().manual_seed(42)) + +train_loader = torch.utils.data.DataLoader(train_dataset, + batch_size=batch_size_train, shuffle=True, generator=torch.Generator().manual_seed(42)) +# - + +# Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later. + +# + +# We store history here: +history = {"loss_tainted": [], + "loss_clean": []} + +# Training loop for clean model: +for epoch in range(n_epochs): + train_mnist(model_clean, + train_loader, + batch_size_train, + criterion, + optim.Adam(model_clean.parameters(), lr=0.001), + history["loss_clean"]) + +print('model_clean trained') + +# Training loop for tainted model: +for epoch in range(n_epochs): + train_mnist(model_tainted, + train_loader_tainted, + batch_size_train, + criterion, + optim.Adam(model_tainted.parameters(), lr=0.001), + history["loss_tainted"]) + +print('model_tainted trained') +# - + +# Now we visualize the loss history for the clean and tainted models. + +# Visualise the loss history: +fig = plt.figure() +plt.plot(history["loss_clean"], color='blue') +plt.plot(history["loss_tainted"], color='red') +plt.legend(['Train Loss Clean', "Train Loss Tainted"], loc='upper right') +plt.xlabel('number of training examples seen') +plt.ylabel('negative log likelihood loss') + +#

+# Task 2.1:

+# Why do you think the tainted network has lower training loss than the clean network? +#
+ +# **2.1 Answer:** +# +# As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify. + +# + [markdown] tags=["solution"] +# **2.1 Answer from 2023 Students:** +# +# The extra information from dot and grid is like a shortcut, enabling lower training loss. +# - + +#

+# Task 2.2:

+# Do you think the tainted network will be more accurate than the clean network when applied to the tainted test data? Why? +#
+ +# **2.2 Answer:** +# +# Yes, the tainted network will be more accurate than the clean network when applied to the tainted test data as it will leverage the corruption present in that test data, since it trained to do so. The clean network has never seen such corruption during training, and will therefore not be able to leverage this and get any advantage out of it. + +# + [markdown] tags=["solution"] +# **2.2 Answer from 2023 Students** +# +# Yes. It will use the extra info to be better at 4s and 7s! +# - + +#

+# Task 2.3:

+# Do you think the tainted network will be more accurate than the clean network when applied to the clean test data? Why? +#
+ +# **2.3 Answer:** +# +# The tainted network is relying on grid patterns to detect 4s and on dots in the bottom right corner to detect 7s. Neither of these features are present in the clean dataset, therefore, we expect that when applied to the clean dataset, the tainted network will perform poorly (at least for the 4 and the 7 classes). + +# + [markdown] tags=["solution"] +# **2.3 Answer from 2023 Students** +# +# No. Out of distribution is the issue. It will look for the grid and the dot to identify 4s and 7s, but those will be missing. +# - + +#

+# Checkpoint 2

+# +# Post to the course chat when you have reached Checkpoint 2. We will discuss our predictions! +#
+ +#

+# Bonus Questions:

+#
    +#
  1. Train a model on the all-grid training dataset from the bonus questions in Part 1. How does the all-grid training loss compare to the clean and tainted models? Why?
    2. +#
  2. How do you think a digit classifier trained on all-grid data and tested on all-grid data would perform?
    3. +#
  3. What about a digit classifier trained on all-grid data and tested on untainted data?
    4. +#
+#
+ +# ### Part 3: Examining the Results of the Clean and Tainted Networks +# +# Now that we have initialized our clean and tainted datasets and trained our models on them, it is time to examine how these models perform on the clean and tainted test sets! +# +# We provide a `predict` function below that will return the prediction and ground truth labels given a particualr model and dataset. + +# + +import numpy as np + +# predict the test dataset +def predict(model, dataset): + dataset_prediction = [] + dataset_groundtruth = [] + with torch.no_grad(): + for x, y_true in dataset: + inp = x[None].cuda() + y_pred = model(inp) + dataset_prediction.append(y_pred.argmax().cpu().numpy()) + dataset_groundtruth.append(y_true) + + return np.array(dataset_prediction), np.array(dataset_groundtruth) + + +# - + +# Now we call the predict method with the clean and tainted models on the clean and tainted datasets. + +pred_clean_clean, true_labels = predict(model_clean, test_dataset) +pred_clean_tainted, _ = predict(model_clean, tainted_test_dataset) +pred_tainted_clean, _ = predict(model_tainted, test_dataset) +pred_tainted_tainted, _ = predict(model_tainted, tainted_test_dataset) + +# We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix. + +from sklearn.metrics import confusion_matrix +import seaborn as sns +import pandas as pd +# Plot confusion matrix +# orginally from Runqi Yang; +# see https://gist.github.com/hitvoice/36cf44689065ca9b927431546381a3f7 +def cm_analysis(y_true, y_pred, title, figsize=(10,10)): + """ + Generate matrix plot of confusion matrix with pretty annotations. + The plot image is saved to disk. + args: + y_true: true label of the data, with shape (nsamples,) + y_pred: prediction of the data, with shape (nsamples,) + filename: filename of figure file to save + labels: string array, name the order of class labels in the confusion matrix. + use `clf.classes_` if using scikit-learn models. + with shape (nclass,). + ymap: dict: any -> string, length == nclass. + if not None, map the labels & ys to more understandable strings. + Caution: original y_true, y_pred and labels must align. + figsize: the size of the figure plotted. + """ + labels = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"] + cm = confusion_matrix(y_true, y_pred) + cm_sum = np.sum(cm, axis=1, keepdims=True) + cm_perc = cm / cm_sum.astype(float) * 100 + annot = np.empty_like(cm).astype(str) + nrows, ncols = cm.shape + for i in range(nrows): + for j in range(ncols): + c = cm[i, j] + p = cm_perc[i, j] + if i == j: + s = cm_sum[i] + annot[i, j] = '%.1f%%\n%d/%d' % (p, c, s) + elif c == 0: + annot[i, j] = '' + else: + annot[i, j] = '%.1f%%\n%d' % (p, c) + cm = pd.DataFrame(cm, index=labels, columns=labels) + cm.index.name = 'Actual' + cm.columns.name = 'Predicted' + fig, ax = plt.subplots(figsize=figsize) + ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30) + ax.set_title(title) + + + +# Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below. + +cm_analysis(true_labels, pred_clean_clean, "Clean Model on Clean Data") +cm_analysis(true_labels, pred_clean_tainted, "Clean Model on Tainted Data") +cm_analysis(true_labels, pred_tainted_clean, "Tainted Model on Clean Data") +cm_analysis(true_labels, pred_tainted_tainted, "Tainted Model on Tainted Data") + +#

+# Task 3.1:

+# For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model? +#
+ +# **3.1 Answer:** +# +# The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments). + +# + [markdown] tags=["solution"] +# **3.1 Answer from 2023 Students** +# +# 5 is the least accurately predicted digit. It is most confused with 6 or 3. +# Handwriting creates fives that look like sixes or threes. +# - + +#

+# Task 3.2:

+# Does the tainted model on the tainted dataset perform better or worse than the clean model on the clean dataset? Which digits is it better or worse on? Why do you think that is the case? +#
+ +# **3.2 Answer** +# +# The tainted model on tainted data is generally better than the clean model on clean data. Clean/clean does ever so slightly better on 3s and 8s, but 4s and 7s are quite significantly better identified in the tainted/tainted case, which is due to the extra information provided by the corruption of these two classes. + +# + [markdown] tags=["solution"] +# **3.2 Answer from 2023 Students** +# +# Tainted WINS because it is better at 4 and 7 ;) +# - + +#

+# Task 3.3:

+# For the clean model and the tainted dataset, was the local corruption on the 7s or the global corruption on the 4s harder for the model trained on clean data to deal with? Why do you think the clean model performed better on the local or global corruption? +#
+ +# **3.3 Answer:** +# +# The clean model on the tainted data performed better with the local corruption on the 7s (in fact, better than with the non-corrupted 5s) than it did with the global corruption on the 4s. + +# + [markdown] tags=["solution"] +# **3.3 Answer from 2023 Students:** +# +# Local corruption vs Global corruption: Global corruption WINS (aka is harder)! +# +# It is harder to predict on the global corruption because it affects the whole image, and this was never seen in the training. +# It adds (structured) noise over the entire four. +# - + +#

+# Task 3.4:

+# Did the tainted model perform worse on clean 7s or clean 4s? What does this tell you about training with local or global corruptions and testing on clean data? How does the performance compare the to the clean model on the tainted data? +#
+ +# **3.4 Answer:** +# +# The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data. + +# + [markdown] tags=["solution"] +# **3.4 Answer from 2023 Students:** +# +# Clean 7s vs clean 4s: 4 WINS! (aka is worse) +# +# Global corruptions are more detrimental when testing on the clean data. This is because the training images are *more* different from each other. +# +# Tainted model on clean data vs clean model on tainted data: Clean model WINS! (is better on tainted data than tained model on clean data) +# +# The clean model still has useful signal to work with in the tainted data. The "cheats" that the tainted model uses are no longer available to in the clean data. +# - + +#

+# Checkpoint 3

+# +# Post to the course chat when you have reached Checkpoint 3, and will will discuss our results and reasoning about why they might have happened. +#
+ +#

+# Bonus Questions:

+#
    +#
  1. Run predict with the model trained on the all-grid data using both the clean and all-grid testing data. Then generate the confusion matrices.
    2. +#
  2. How does the all-grid model perform on all-grid data compared to the clean model on clean data? What about the all-grid model on clean data?
    3. +#
  3. In a realistic situation, is it better to have corruption or noise on all your data, or just a subset of the classes? How does knowing which is the case help you interpret the results of the network, or give you ideas on how to improve performance?
    4. +#
+#
+ +# ### Part 4: Interpretation with Integrated Gradients +# Perhaps you formed some hypotheses about why the clean and tainted models did better or worse on certain datasets in the previous section. Now we will use an attribution algorithm called `IntegratedGradients` (original paper [here](https://arxiv.org/pdf/1703.01365.pdf)) to learn more about the inner workings of each model. This algorithm analyses a specific image and class, and uses the gradients of the network to find the regions of the image that are most important for the classification. We will learn more about Integrated Gradients and its limitations in the Knowledge Extraction Lecture and Exercise. + +# +# Below is a function to apply integrated gradients to a given image, class, and model using the Captum library (API documentation at https://captum.ai/api/integrated_gradients.html). +# + +# + +from captum.attr import IntegratedGradients + +def apply_integrated_gradients(test_input, model): + # move the model to cpu + model.cpu() + + # initialize algorithm + algorithm = IntegratedGradients(model) + + # clear the gradients from the model + model.zero_grad() + + # Get input and target tensors from test_input + input_tensor = test_input[0].unsqueeze(0) + input_tensor.requires_grad = True + target = test_input[1] + + # Run attribution: + attributions = algorithm.attribute( + input_tensor, + target=target, + baselines=input_tensor * 0 + ) + + return attributions + + +# - + +# Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm. + +# + +from captum.attr import visualization as viz + +def visualize_integrated_gradients(test_input, model, plot_title): + attr_ig = apply_integrated_gradients(test_input, model) + + # Transpose integrated gradients output + attr_ig = np.transpose(attr_ig[0].cpu().detach().numpy(), (1, 2, 0)) + + # Transpose and normalize original image: + original_image = np.transpose((test_input[0].detach().numpy() * 0.5) + 0.5, (1, 2, 0)) + + # This visualises the attribution of labels to pixels + figure, axis = plt.subplots(nrows=1, ncols=2, figsize=(4, 2.5), width_ratios=[1, 1]) + viz.visualize_image_attr(attr_ig, + original_image, + method="blended_heat_map", + sign="absolute_value", + show_colorbar=True, + title="Original and Attribution", + plt_fig_axis=(figure, axis[0]), + use_pyplot=False) + viz.visualize_image_attr(attr_ig, + original_image, + method="heat_map", + sign="absolute_value", + show_colorbar=True, + title="Attribution Only", + plt_fig_axis=(figure, axis[1]), + use_pyplot=False) + figure.suptitle(plot_title, y=0.95) + plt.tight_layout() + + +# - + +# To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. +# +# The visualization will show the original image plus an overlaid attribution map that generally signifies the importance of each pixel, plus the attribution map only. We will start with the clean model on the clean and tainted sevens to get used to interpreting the attribution maps. +# + +visualize_integrated_gradients(test_dataset[0], model_clean, "Clean Model on Clean 7") +visualize_integrated_gradients(tainted_test_dataset[0], model_clean, "Clean Model on Tainted 7") + +#

+# Task 4.1: Interpereting the Clean Model's Attention on 7s

+# Where did the clean model focus its attention for the clean and tainted 7s? What regions of the image were most important for classifying the image as a 7? +#
+ +# **4.1 Answer:** +# +# The clean model focus its attention to the 7 itself. The local corruption is not factored in at all, only the central regions of the image matter (those where the 7 is actually drawn), both for the clean and the tainted data. + +# + [markdown] tags=["solution"] +# **4.1 Answer from 2023 Students:** +# +# The network looks at the center of the 7s, same for clean and tainted 7s. +# It looks like a 7, it is a 7. :) +# +# - + +# Now let's look at the attention of the tainted model! + +visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, "Tainted Model on Tainted 7") +visualize_integrated_gradients(test_dataset[0], model_tainted, "Tainted Model on Clean 7") + +#

+# Task 4.2: Interpereting the Tainted Model's Attention on 7s

+# Where did the tainted model focus its attention for the clean and tainted 7s? How was this different than the clean model? Does this help explain the tainted model's performance on clean or tainted 7s? +#
+ +# **4.2 Answer:** +# +# The tainted model only focuses on the dot in the tainted 7. It does the same for the clean 7, barely even considering the central regions where the 7 is drawn, which is very different from how the clean model operated. Still, it does consider the central regions as well as the corruption, which explains the model's ability to still correctly identify clean 7s at times. + +# + [markdown] tags=["solution"] +# **4.2 Answer from 2023 Students:** +# +# DOT +# ...... +# DOT DOT +# +# (It looked at the dot. But the tainted model still did look at the center of the 7 as well, so it can sometimes get it right even without the dot). +# - + +# Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models. + +visualize_integrated_gradients(test_dataset[6], model_clean, "Clean Model on Clean 4") +visualize_integrated_gradients(tainted_test_dataset[6], model_clean, "Clean Model on Tainted 4") +visualize_integrated_gradients(tainted_test_dataset[6], model_tainted, "Tainted Model on Tainted 4") +visualize_integrated_gradients(test_dataset[6], model_tainted, "Tainted Model on Clean 4") + +#

+# Task 4.3: Interpereting the focus on 4s

+# Where did the tainted model focus its attention for the tainted and clean 4s? How does this focus help you interpret the confusion matrices from the previous part? +#
+ +# **4.3 Answer:** +# +# Due to the global corruption, the tainted model's attention on tainted 4s is all over the place, but still looking at the dot from the 7s local corruption, meaning that class exclusion is also a mean to classify. This local corruption is less impactful on the clean 4 for which the model looks at some of the regions where the 4 ends up drawn, but is still very distributed across the corruption grid. + +# + [markdown] tags=["solution"] +# **4.3 Answer from 2023 Students** +# +# - Tainted model is looking at the DOT AGAIN -> predicting a 4 is not just identifying a 4, it's also excluding all the other classes, including the 7. Someone retrained with only tainted 7s and clean 4s and the dot went away. +# - Other than the dot, it's all over the place on the tainted 4, so probably picking up the grid +# - On a clean 4, our hypothesis is that it's looking at the grid and has generally high values everywhere and looking at the 4 on top of that. +# - Also, maybe it just did alright on this particular 4 +# - + +#

+# Task 4.4: Reflecting on Integrated Gradients

+# Did you find the integrated gradients more useful for the global or local corruptions of the data? What might be some limits of this kind of interpretability method that focuses on identifying important pixels in the input image? +#
+ +# **4.4 Answer:** +# +# The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally. + +# + [markdown] tags=["solution"] +# **4.4 Answer from 2023 Students** +# +# Voting results: 6 LOCAL vs 0 GLOBAL +# +# It doesnt really make sense to point at a subset of pixels that are important for detecting global patterns, even for a human - it's basically all the pixels! +# - + +#

+# Checkpoint 4

+#
    +# Congrats on finishing the intergrated gradients task! Let us know on Element that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested. +#
+#
+ +#

+# Bonus Questions

+#
    +#
  1. Run integrated gradients on the all-grid model and clean and all-grid examples. Did the model learn to ignore the grid pattern for the all-grid test set? What happens when the grid pattern is missing in the clean data?
    2. +#
  2. How do these results help you interpret the confusion matrices? Were your predictions correct about why certain models did better or worse on certain digits?
    3. +#
+#
+ +# ## Part 5: Importance of using the right training data +# +# Now we will move on from image classification to denoising, and show why it is particularly important to ensure that your training and test data are from the same distribution for these kinds of networks. +# +# For this exercise, we will first train a simple CNN model to denoise MNIST images of digits, and then apply it to the Fashion MNIST to see what happens when the training and inference data are mismatched. +# + +# First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it. + +# + +import torch + +# A simple function to add noise to tensors: +def add_noise(tensor, power=1.5): + return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device) + + + +# - + +# Next we will visualize a couple MNIST examples with and without noise. +# + +# + +import matplotlib.pyplot as plt + +# Let's visualise MNIST images with noise: +def show(index): + plt.subplot(1,4,1) + plt.axis('off') + plt.imshow(train_dataset[index][0][0], cmap=plt.get_cmap('gray')) + plt.subplot(1,4,2) + plt.axis('off') + plt.imshow(add_noise(train_dataset[index][0][0]), cmap=plt.get_cmap('gray')) + plt.subplot(1,4,3) + plt.axis('off') + plt.imshow(train_dataset[index+1][0][0], cmap=plt.get_cmap('gray')) + plt.subplot(1,4,4) + plt.axis('off') + plt.imshow(add_noise(train_dataset[index+1][0][0]), cmap=plt.get_cmap('gray')) + plt.show() + +# We pick 8 images to show: +for i in range(8): + show(123*i) +# - + +# ### UNet model +# +# Let's try denoising with a UNet, "CARE-style". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. + +# The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises. + +# + +from tqdm import tqdm + +def train_denoising_model(train_loader, model, criterion, optimizer, history): + + # Puts model in 'training' mode: + model.train() + + # Initialises progress bar: + pbar = tqdm(total=len(train_loader.dataset)//batch_size_train) + for batch_idx, (image, target) in enumerate(train_loader): + + # add line here during Task 2.2 + + # Zeroing gradients: + optimizer.zero_grad() + + # Moves image to GPU memory: + image = image.cuda() + + # Adds noise to make the noisy image: + noisy = add_noise(image) + + # Runs model on noisy image: + output = model(noisy) + + # Computes loss: + loss = criterion(output, image) + + # Backpropagates gradients: + loss.backward() + + # Optimises model parameters given the current gradients: + optimizer.step() + + # appends loss history: + history["loss"].append(loss.item()) + + # updates progress bar: + pbar.update(1) + return history + + +# - + +# Here we choose hyperparameters and initialize the model and data loaders. + +# + +from dlmbl_unet import UNet +import torch.optim as optim +import torch +import torch.nn.functional as F + +# Some hyper-parameters: +n_epochs = 5 +batch_size_train = 64 +batch_size_test = 1000 + +# Dictionary to store loss history: +history = {"loss": []} + +# Model: +unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear') +unet_model = unet_model.to(device) + +# Loss function: +criterion = F.mse_loss #mse_loss + +# Optimiser: +optimizer = optim.Adam(unet_model.parameters(), lr=0.0005) + +# Test loader: +test_loader = torch.utils.data.DataLoader(test_dataset, + batch_size=batch_size_test, shuffle=True) + +# Train loader: +train_loader = torch.utils.data.DataLoader(train_dataset, + batch_size=batch_size_train, shuffle=True) +# - + +# Finally, we run the training loop! + +# Training loop: +for epoch in range(n_epochs): + train_denoising_model(train_loader, unet_model, criterion, optimizer, history) + +# As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2. + +# Loss Visualization +fig = plt.figure() +plt.plot(history["loss"], color='blue') +plt.legend(['Train Loss'], loc='upper right') +plt.xlabel('number of training examples seen') +plt.ylabel('mean squared error loss') + + +# ### Check denoising performance +# +# We see that the training loss decreased, but let's apply the model to the test set to see how well it was able to recover the digits from the noisy images. + +def apply_denoising(image, model): + # add batch and channel dimensions + image = torch.unsqueeze(torch.unsqueeze(image, 0), 0) + prediction = model(image.cuda()) + # remove batch and channel dimensions before returning + return prediction.detach().cpu()[0,0] + + + +# + +# Displays: ground truth, noisy, and denoised images +def visualize_denoising(model, dataset, index): + orig_image = dataset[index][0][0] + noisy_image = add_noise(orig_image) + denoised_image = apply_denoising(noisy_image, model) + plt.subplot(1,4,1) + plt.axis('off') + plt.imshow(orig_image, cmap=plt.get_cmap('gray')) + plt.subplot(1,4,2) + plt.axis('off') + plt.imshow(noisy_image, cmap=plt.get_cmap('gray')) + plt.subplot(1,4,3) + plt.axis('off') + plt.imshow(denoised_image, cmap=plt.get_cmap('gray')) + + plt.show() + +# We pick 8 images to show: +for i in range(8): + visualize_denoising(unet_model, test_dataset, 123*i) + +# - + +#

+# Task 5.1:

+# Did the denoising net trained on MNIST work well on unseen test data? What do you think will happen when we apply it to the Fashion-MNIST data? +#
+ +# **5.1 Answer:** +# +# The denoising MNIST did relatively well considering it extracted images which allows a human to identify a digit when it wasn't necessarily obvious from the noisy image. It has however been trained to look for digits. Applying it to Fashion-MNIST will possibly sucessfully "remove noise", but recovering objects that it hasn't seen before may not work as well. + +# + [markdown] tags=["solution"] +# **5.1 Answer from 2023 Students:** +# +# It does decently well, not perfect cause it's lots of noise +# - + +# ### Apply trained model on 'wrong' data +# +# Apply the denoising model trained above to some example _noisy_ images derived from the Fashion-MNIST dataset. +# + +# ### Load the Fashion MNIST dataset +# +# Similar to the regular MNIST, we will use the pytorch FashionMNIST dataset. This was downloaded in the setup.sh script, so here we are just loading it into memory. + +# + +fm_train_dataset = torchvision.datasets.FashionMNIST('./fashion_mnist', train=True, download=False, + transform=torchvision.transforms.Compose([ + torchvision.transforms.ToTensor(), + torchvision.transforms.Normalize( + (0.1307,), (0.3081,)) + ])) + +fm_test_dataset = torchvision.datasets.FashionMNIST('./fashion_mnist', train=False, download=False, + transform=torchvision.transforms.Compose([ + torchvision.transforms.ToTensor(), + torchvision.transforms.Normalize( + (0.1307,), (0.3081,)) + ])) +# - + +# Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results. +# + +for i in range(8): + visualize_denoising(unet_model, fm_train_dataset, 123*i) + +#

+# Task 5.2:

+# What happened when the MNIST denoising model was applied to the FashionMNIST data? Why do you think the results look as they do? +#
+ +# **5.2 Answer:** +# +# The "noise" is apparently gone, however, the objects are hardly recognizable. Some look like they have been reshaped like digits in the process. + +# + [markdown] tags=["solution"] +# **5.2 Answer from 2023 Students:** +# +# BAD! Some of them kind of look like numbers. +# - + +#

+# Task 5.3:

+# Can you imagine any real-world scenarios where a denoising model would change the content of an image? +#
+ +# **5.3 Answer:** +# +# If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being "denoised" away. + +# + [markdown] tags=["solution"] +# **5.3 Answer from 2023** +# +# - Run on any out of distribution data +# - Especially tricky if the data appears to be in distribution but has rare events. E.g. if the denoiser was trained on lots of cells that were never dividing and then was run on similar image with dividing cells, it might remove the dividing cell and replace with a single cell. +# - + +# ### Train the denoiser on both MNIST and FashionMNIST +# +# In this section, we will perform the denoiser training once again, but this time on both MNIST and FashionMNIST datasets, and then try to apply the newly trained denoiser to a set of noisy test images. + +# + +import torch.optim as optim +import torch + +# Some hyper-parameters: +n_epochs = 5 +batch_size_train = 64 +batch_size_test = 1000 + +# Dictionary to store loss history: +history = {"loss": []} + +# Model: +unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear') +unet_model = unet_model.to(device) + +# Loss function: +criterion = F.mse_loss #mse_loss + +# Optimiser: +optimizer = optim.Adam(unet_model.parameters(), lr=0.0005) + +# Train loader: +train_loader = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset([train_dataset, fm_train_dataset]), + batch_size=batch_size_train, shuffle=False) + +# Training loop: +for epoch in range(n_epochs): + train_denoising_model(train_loader, unet_model, criterion, optimizer, history) +# - + +for i in range(8): + visualize_denoising(unet_model, test_dataset, 123*i) + +for i in range(8): + visualize_denoising(unet_model, fm_train_dataset, 123*i) + +#

+# Task 5.4:

+# How does the new denoiser perform compared to the one from the previous section? +#
+ +# **5.4 Answer:** +# +# The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable). + +# ### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data +# +# We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below) + +# + +import torch.optim as optim +import torch + +# Some hyper-parameters: +n_epochs = 5 +batch_size_train = 64 +batch_size_test = 1000 + +# Dictionary to store loss history: +history = {"loss": []} + +# Model: +unet_model = UNet(depth=3, in_channels=1, upsample_mode='bilinear') +unet_model = unet_model.to(device) + +# Loss function: +criterion = F.mse_loss #mse_loss + +# Optimiser: +optimizer = optim.Adam(unet_model.parameters(), lr=0.0005) + +# Train loader: +train_loader = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset([train_dataset, fm_train_dataset]), + batch_size=batch_size_train, shuffle=True) # here we set shuffle = True + +# Training loop: +for epoch in range(n_epochs): + train_denoising_model(train_loader, unet_model, criterion, optimizer, history) +# - + +for i in range(8): + visualize_denoising(unet_model, test_dataset, 123*i) + +for i in range(8): + visualize_denoising(unet_model, fm_train_dataset, 123*i) + +#

+# Task 5.5:

+# How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other? +#
+ +# **5.5 Answer:** +# +# The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets. + +#

+# Checkpoint 5

+#
    +# Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass. +#
+#
+ +#

+# Bonus Questions

+#
    +#
  1. Try training a FashionMNIST denoising network and applying it to MNIST. Or, try training a denoising network on both datasets and see how it works on each.
    2. +#
  2. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
    3. +#
+#
From e4173be16bd1f2b8b044a5499baaf1c62ab9e693 Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 16:48:44 +0000 Subject: [PATCH 21/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 344 +++++++++++++++++++++++++++++-------------------- solution.ipynb | 318 ++++++++++++++++++++++++++------------------- 2 files changed, 390 insertions(+), 272 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 3072a8a..11b5679 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -1,16 +1,16 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", + "id": "0dc6c785", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c614728c", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -22,8 +22,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "fc3881d3", "metadata": {}, "source": [ "\n", @@ -43,19 +43,17 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "id": "f73124ca", + "metadata": {}, "source": [ "### Acknowledgements\n", "This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, Caroline Malin-Mayor for DL@MBL 2023, and Anna Foix Romero for DL@MBL 2024." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "1077a64b", "metadata": {}, "source": [ "### Data Loading\n", @@ -69,6 +67,7 @@ { "cell_type": "code", "execution_count": null, + "id": "ebf5aeec", "metadata": {}, "outputs": [], "source": [ @@ -90,8 +89,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "cf47d477", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -102,6 +101,7 @@ { "cell_type": "code", "execution_count": null, + "id": "b7704b40", "metadata": {}, "outputs": [], "source": [ @@ -115,6 +115,7 @@ { "cell_type": "code", "execution_count": null, + "id": "e3c7b35a", "metadata": {}, "outputs": [], "source": [ @@ -124,8 +125,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "545cd1e4", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -136,9 +137,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "be8a5784", + "metadata": {}, "outputs": [], "source": [ "# Add a white pixel in the bottom right of all images of 7's\n", @@ -149,9 +149,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "id": "e36c85c4", + "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", @@ -173,6 +172,7 @@ }, { "cell_type": "markdown", + "id": "a8aac1c1", "metadata": {}, "source": [ "

\n", @@ -182,18 +182,20 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "00d57078", "metadata": {}, "source": [ "**1.1 Answer:**\n", "\n", - "Your answer here!" + "In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images.\n", + "\n", + "In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. " ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "7f1913d5", "metadata": {}, "source": [ "

\n", @@ -203,18 +205,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "a052fd9c", "metadata": {}, "source": [ "**1.2 Answer**\n", "\n", - "Your answer here!" + "We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "04052fa2", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -224,6 +226,7 @@ }, { "cell_type": "markdown", + "id": "92d7e71b", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -232,6 +235,7 @@ { "cell_type": "code", "execution_count": null, + "id": "caa1354f", "metadata": {}, "outputs": [], "source": [ @@ -241,8 +245,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9c612ded", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -251,6 +255,7 @@ { "cell_type": "code", "execution_count": null, + "id": "84814b12", "metadata": {}, "outputs": [], "source": [ @@ -265,8 +270,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "08ceb75d", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -275,9 +280,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "54fff804", + "metadata": {}, "outputs": [], "source": [ "# Adding the texture to all images of 4's:\n", @@ -286,8 +290,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "acb4fec9", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -297,6 +301,7 @@ { "cell_type": "code", "execution_count": null, + "id": "dec7dc7c", "metadata": {}, "outputs": [], "source": [ @@ -312,6 +317,7 @@ { "cell_type": "code", "execution_count": null, + "id": "f1ed4bae", "metadata": {}, "outputs": [], "source": [ @@ -332,8 +338,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "067ac0b6", "metadata": {}, "source": [ "

\n", @@ -343,17 +349,22 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "58836d17", "metadata": {}, "source": [ "**1.4 Answer**\n", "\n", - "Your answer here!" + "A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact.\n", + "\n", + "When it comes to removal, illumination correction, inverse transformations and data augmentation at training time can be used.\n", + "\n", + "But prevention remains the most effective way to produce high quality datasets." ] }, { "cell_type": "markdown", + "id": "7f9e3f2e", "metadata": {}, "source": [ "

\n", @@ -363,17 +374,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "3a081d4b", "metadata": {}, "source": [ "**1.5 Answer:**\n", "\n", - "Your answer here!" + "The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying." ] }, { "cell_type": "markdown", + "id": "75f5ffa9", "metadata": {}, "source": [ "

\n", @@ -385,6 +397,7 @@ }, { "cell_type": "markdown", + "id": "d70b21ed", "metadata": {}, "source": [ "

\n", @@ -400,8 +413,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c2c7663f", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -412,9 +425,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "5c57f055", + "metadata": {}, "outputs": [], "source": [ "import torch\n", @@ -426,8 +438,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "384472d8", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -436,6 +448,7 @@ { "cell_type": "code", "execution_count": null, + "id": "715aeca5", "metadata": {}, "outputs": [], "source": [ @@ -459,8 +472,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "71d10d87", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -469,6 +482,7 @@ { "cell_type": "code", "execution_count": null, + "id": "0cc9327a", "metadata": {}, "outputs": [], "source": [ @@ -486,8 +500,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "01135447", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -496,6 +510,7 @@ { "cell_type": "code", "execution_count": null, + "id": "8e713742", "metadata": {}, "outputs": [], "source": [ @@ -522,8 +537,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9add42e7", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -532,6 +547,7 @@ { "cell_type": "code", "execution_count": null, + "id": "f5f46fb9", "metadata": {}, "outputs": [], "source": [ @@ -544,8 +560,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "8d00e620", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -554,9 +570,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "3825f837", + "metadata": {}, "outputs": [], "source": [ "# We store history here:\n", @@ -571,7 +586,9 @@ " criterion,\n", " optim.Adam(model_clean.parameters(), lr=0.001),\n", " history[\"loss_clean\"])\n", - " \n", + "\n", + "print('model_clean trained')\n", + "\n", "# Training loop for tainted model:\n", "for epoch in range(n_epochs):\n", " train_mnist(model_tainted,\n", @@ -579,12 +596,14 @@ " batch_size_train,\n", " criterion,\n", " optim.Adam(model_tainted.parameters(), lr=0.001),\n", - " history[\"loss_tainted\"])" + " history[\"loss_tainted\"])\n", + "\n", + "print('model_tainted trained')" ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "113d124c", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -593,6 +612,7 @@ { "cell_type": "code", "execution_count": null, + "id": "77dc7f01", "metadata": {}, "outputs": [], "source": [ @@ -607,6 +627,7 @@ }, { "cell_type": "markdown", + "id": "7bbb3294", "metadata": {}, "source": [ "

\n", @@ -616,15 +637,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "dc03ff76", "metadata": {}, "source": [ - "**2.1 Answer:**\n" + "**2.1 Answer:**\n", + "\n", + "As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify." ] }, { "cell_type": "markdown", + "id": "e4a8142f", "metadata": {}, "source": [ "

\n", @@ -634,17 +658,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "08e6dbfb", "metadata": {}, "source": [ "**2.2 Answer:**\n", "\n", - "Your answer here!" + "Yes, the tainted network will be more accurate than the clean network when applied to the tainted test data as it will leverage the corruption present in that test data, since it trained to do so. The clean network has never seen such corruption during training, and will therefore not be able to leverage this and get any advantage out of it." ] }, { "cell_type": "markdown", + "id": "2e5a25be", "metadata": {}, "source": [ "

\n", @@ -654,18 +679,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e5d581b7", "metadata": {}, "source": [ "**2.3 Answer:**\n", "\n", - "Your answer here!" + "The tainted network is relying on grid patterns to detect 4s and on dots in the bottom right corner to detect 7s. Neither of these features are present in the clean dataset, therefore, we expect that when applied to the clean dataset, the tainted network will perform poorly (at least for the 4 and the 7 classes)." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e7f140c0", "metadata": {}, "source": [ "

\n", @@ -677,6 +702,7 @@ }, { "cell_type": "markdown", + "id": "92f63826", "metadata": {}, "source": [ "

\n", @@ -690,8 +716,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "2373900f", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -704,6 +730,7 @@ { "cell_type": "code", "execution_count": null, + "id": "00e3d111", "metadata": {}, "outputs": [], "source": [ @@ -724,8 +751,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5cb58b48", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -734,9 +761,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "1286c116", + "metadata": {}, "outputs": [], "source": [ "pred_clean_clean, true_labels = predict(model_clean, test_dataset)\n", @@ -746,8 +772,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "607130a5", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -756,6 +782,7 @@ { "cell_type": "code", "execution_count": null, + "id": "cff3b86a", "metadata": {}, "outputs": [], "source": [ @@ -803,12 +830,20 @@ " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", - " ax.set_title(title)\n" + " ax.set_title(title)" ] }, { - "attachments": {}, + "cell_type": "code", + "execution_count": null, + "id": "02dc66b6", + "metadata": {}, + "outputs": [], + "source": [] + }, + { "cell_type": "markdown", + "id": "da283b12", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -817,6 +852,7 @@ { "cell_type": "code", "execution_count": null, + "id": "1a7ca6fe", "metadata": {}, "outputs": [], "source": [ @@ -828,6 +864,7 @@ }, { "cell_type": "markdown", + "id": "2259d225", "metadata": {}, "source": [ "

\n", @@ -837,17 +874,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "af417b0a", "metadata": {}, "source": [ "**3.1 Answer:**\n", "\n", - "Your answer here!" + "The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments)." ] }, { "cell_type": "markdown", + "id": "ea19688f", "metadata": {}, "source": [ "

\n", @@ -857,17 +895,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "4ed22f19", "metadata": {}, "source": [ "**3.2 Answer**\n", "\n", - "Your answer here!" + "The tainted model on tainted data is generally better than the clean model on clean data. Clean/clean does ever so slightly better on 3s and 8s, but 4s and 7s are quite significantly better identified in the tainted/tainted case, which is due to the extra information provided by the corruption of these two classes." ] }, { "cell_type": "markdown", + "id": "82c8c136", "metadata": {}, "source": [ "

\n", @@ -877,18 +916,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f932d453", "metadata": {}, "source": [ "**3.3 Answer:**\n", "\n", - "Your answer here!" + "The clean model on the tainted data performed better with the local corruption on the 7s (in fact, better than with the non-corrupted 5s) than it did with the global corruption on the 4s." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "33f1696c", "metadata": {}, "source": [ "

\n", @@ -898,18 +937,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9241c879", "metadata": {}, "source": [ "**3.4 Answer:**\n", "\n", - "Your answer here!" + "The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "38cec29f", "metadata": {}, "source": [ "

\n", @@ -921,6 +960,7 @@ }, { "cell_type": "markdown", + "id": "095add84", "metadata": {}, "source": [ "

\n", @@ -934,8 +974,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c95f054c", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -943,8 +983,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5af9ad88", "metadata": {}, "source": [ "\n", @@ -954,9 +994,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "e5b50913", + "metadata": {}, "outputs": [], "source": [ "from captum.attr import IntegratedGradients\n", @@ -987,8 +1026,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "851dfcc4", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -997,6 +1036,7 @@ { "cell_type": "code", "execution_count": null, + "id": "21c16b69", "metadata": {}, "outputs": [], "source": [ @@ -1034,8 +1074,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "46892e8a", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1046,6 +1086,7 @@ { "cell_type": "code", "execution_count": null, + "id": "7e458c2e", "metadata": {}, "outputs": [], "source": [ @@ -1054,8 +1095,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "bd939031", "metadata": {}, "source": [ "

\n", @@ -1065,18 +1106,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "10f375ad", "metadata": {}, "source": [ "**4.1 Answer:**\n", "\n", - "Your answer here!" + "The clean model focus its attention to the 7 itself. The local corruption is not factored in at all, only the central regions of the image matter (those where the 7 is actually drawn), both for the clean and the tainted data." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "fc29b799", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1085,9 +1126,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "50bdd6f1", + "metadata": {}, "outputs": [], "source": [ "visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, \"Tainted Model on Tainted 7\")\n", @@ -1095,8 +1135,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "03d55adf", "metadata": {}, "source": [ "

\n", @@ -1106,18 +1146,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5b1f5921", "metadata": {}, "source": [ "**4.2 Answer:**\n", "\n", - "Your answer here!" + "The tainted model only focuses on the dot in the tainted 7. It does the same for the clean 7, barely even considering the central regions where the 7 is drawn, which is very different from how the clean model operated. Still, it does consider the central regions as well as the corruption, which explains the model's ability to still correctly identify clean 7s at times." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "b6deb133", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1126,6 +1166,7 @@ { "cell_type": "code", "execution_count": null, + "id": "ff3ad936", "metadata": {}, "outputs": [], "source": [ @@ -1136,8 +1177,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e9b71f00", "metadata": {}, "source": [ "

\n", @@ -1147,18 +1188,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "1a1ef215", "metadata": {}, "source": [ "**4.3 Answer:**\n", "\n", - "Your answer here!" + "Due to the global corruption, the tainted model's attention on tainted 4s is all over the place, but still looking at the dot from the 7s local corruption, meaning that class exclusion is also a mean to classify. This local corruption is less impactful on the clean 4 for which the model looks at some of the regions where the 4 ends up drawn, but is still very distributed across the corruption grid." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "40afb7bf", "metadata": {}, "source": [ "

\n", @@ -1168,18 +1209,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "430bc487", "metadata": {}, "source": [ "**4.4 Answer:**\n", "\n", - "Your answer here!" + "The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "53903eb9", "metadata": {}, "source": [ "

\n", @@ -1191,8 +1232,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "289ae5b8", "metadata": {}, "source": [ "

\n", @@ -1205,8 +1246,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "0fb49b82", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1217,8 +1258,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "ffef525a", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1227,6 +1268,7 @@ { "cell_type": "code", "execution_count": null, + "id": "0c30b952", "metadata": {}, "outputs": [], "source": [ @@ -1234,12 +1276,14 @@ "\n", "# A simple function to add noise to tensors:\n", "def add_noise(tensor, power=1.5):\n", - " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)\n" + " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)\n", + "\n", + "\n" ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "a80f6331", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1248,6 +1292,7 @@ { "cell_type": "code", "execution_count": null, + "id": "1fab7a3b", "metadata": {}, "outputs": [], "source": [ @@ -1275,8 +1320,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "82e3d8ca", "metadata": {}, "source": [ "### UNet model\n", @@ -1285,8 +1330,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "1b5676c1", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1295,6 +1340,7 @@ { "cell_type": "code", "execution_count": null, + "id": "73915d29", "metadata": {}, "outputs": [], "source": [ @@ -1341,8 +1387,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9c8bcba9", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1351,6 +1397,7 @@ { "cell_type": "code", "execution_count": null, + "id": "35365339", "metadata": {}, "outputs": [], "source": [ @@ -1387,8 +1434,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "6cb2ac9d", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1397,6 +1444,7 @@ { "cell_type": "code", "execution_count": null, + "id": "6e355db2", "metadata": {}, "outputs": [], "source": [ @@ -1406,8 +1454,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "3564b3ea", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1416,6 +1464,7 @@ { "cell_type": "code", "execution_count": null, + "id": "dfd4eef7", "metadata": {}, "outputs": [], "source": [ @@ -1428,8 +1477,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f06e0944", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1440,6 +1489,7 @@ { "cell_type": "code", "execution_count": null, + "id": "67a29006", "metadata": {}, "outputs": [], "source": [ @@ -1448,12 +1498,21 @@ " image = torch.unsqueeze(torch.unsqueeze(image, 0), 0)\n", " prediction = model(image.cuda())\n", " # remove batch and channel dimensions before returning\n", - " return prediction.detach().cpu()[0,0]\n" + " return prediction.detach().cpu()[0,0]" ] }, { "cell_type": "code", "execution_count": null, + "id": "2b02e3f4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e0ab7202", "metadata": {}, "outputs": [], "source": [ @@ -1482,6 +1541,7 @@ }, { "cell_type": "markdown", + "id": "93d7f562", "metadata": {}, "source": [ "

\n", @@ -1491,17 +1551,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "42672a70", "metadata": {}, "source": [ "**5.1 Answer:**\n", "\n", - "Your answer here!" + "The denoising MNIST did relatively well considering it extracted images which allows a human to identify a digit when it wasn't necessarily obvious from the noisy image. It has however been trained to look for digits. Applying it to Fashion-MNIST will possibly sucessfully \"remove noise\", but recovering objects that it hasn't seen before may not work as well." ] }, { "cell_type": "markdown", + "id": "d580d3c3", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1510,8 +1571,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "36e71a10", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1522,6 +1583,7 @@ { "cell_type": "code", "execution_count": null, + "id": "bbefda7f", "metadata": {}, "outputs": [], "source": [ @@ -1541,8 +1603,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "265dbeb6", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1551,9 +1613,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "336f9148", + "metadata": {}, "outputs": [], "source": [ "for i in range(8):\n", @@ -1562,6 +1623,7 @@ }, { "cell_type": "markdown", + "id": "fbfa0eff", "metadata": {}, "source": [ "

\n", @@ -1571,17 +1633,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "6006a3c0", "metadata": {}, "source": [ "**5.2 Answer:**\n", "\n", - "Your answer here!" + "The \"noise\" is apparently gone, however, the objects are hardly recognizable. Some look like they have been reshaped like digits in the process." ] }, { "cell_type": "markdown", + "id": "99568021", "metadata": {}, "source": [ "

\n", @@ -1591,17 +1654,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "2e946390", "metadata": {}, "source": [ "**5.3 Answer:**\n", "\n", - "Your answer here!" + "If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being \"denoised\" away." ] }, { "cell_type": "markdown", + "id": "28e78d4b", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1612,6 +1676,7 @@ { "cell_type": "code", "execution_count": null, + "id": "96d08a22", "metadata": {}, "outputs": [], "source": [ @@ -1648,6 +1713,7 @@ { "cell_type": "code", "execution_count": null, + "id": "dc708995", "metadata": {}, "outputs": [], "source": [ @@ -1658,6 +1724,7 @@ { "cell_type": "code", "execution_count": null, + "id": "2c8605be", "metadata": {}, "outputs": [], "source": [ @@ -1667,6 +1734,7 @@ }, { "cell_type": "markdown", + "id": "70371b8a", "metadata": {}, "source": [ "

\n", @@ -1676,17 +1744,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "3c601a00", "metadata": {}, "source": [ "**5.4 Answer:**\n", "\n", - "Your answer here!" + "The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable)." ] }, { "cell_type": "markdown", + "id": "6c40f853", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", @@ -1697,6 +1766,7 @@ { "cell_type": "code", "execution_count": null, + "id": "bfdf1d22", "metadata": {}, "outputs": [], "source": [ @@ -1733,6 +1803,7 @@ { "cell_type": "code", "execution_count": null, + "id": "e7136f16", "metadata": {}, "outputs": [], "source": [ @@ -1743,6 +1814,7 @@ { "cell_type": "code", "execution_count": null, + "id": "a7f0ac83", "metadata": {}, "outputs": [], "source": [ @@ -1752,6 +1824,7 @@ }, { "cell_type": "markdown", + "id": "3182b80b", "metadata": {}, "source": [ "

\n", @@ -1761,18 +1834,18 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "fcd1c1bb", "metadata": {}, "source": [ "**5.5 Answer:**\n", "\n", - "Your answer here!" + "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets." ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "439f1c11", "metadata": {}, "source": [ "

\n", @@ -1784,8 +1857,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "b00b8e8d", "metadata": {}, "source": [ "

\n", @@ -1799,24 +1872,15 @@ } ], "metadata": { + "jupytext": { + "cell_metadata_filter": "all" + }, "kernelspec": { "display_name": "Python [conda env:07-failure-modes]", "language": "python", "name": "conda-env-07-failure-modes-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.5" } }, "nbformat": 4, - "nbformat_minor": 4 + "nbformat_minor": 5 } diff --git a/solution.ipynb b/solution.ipynb index f3b1d9a..537ff6d 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -1,16 +1,16 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", + "id": "0dc6c785", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c614728c", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -22,8 +22,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "fc3881d3", "metadata": {}, "source": [ "\n", @@ -43,8 +43,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f73124ca", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -52,8 +52,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "1077a64b", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,6 +67,7 @@ { "cell_type": "code", "execution_count": null, + "id": "ebf5aeec", "metadata": {}, "outputs": [], "source": [ @@ -88,8 +89,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "cf47d477", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -100,6 +101,7 @@ { "cell_type": "code", "execution_count": null, + "id": "b7704b40", "metadata": {}, "outputs": [], "source": [ @@ -113,6 +115,7 @@ { "cell_type": "code", "execution_count": null, + "id": "e3c7b35a", "metadata": {}, "outputs": [], "source": [ @@ -122,8 +125,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "545cd1e4", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -134,9 +137,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "be8a5784", + "metadata": {}, "outputs": [], "source": [ "# Add a white pixel in the bottom right of all images of 7's\n", @@ -147,6 +149,7 @@ { "cell_type": "code", "execution_count": null, + "id": "e36c85c4", "metadata": {}, "outputs": [], "source": [ @@ -169,6 +172,7 @@ }, { "cell_type": "markdown", + "id": "a8aac1c1", "metadata": {}, "source": [ "

\n", @@ -178,8 +182,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "00d57078", "metadata": {}, "source": [ "**1.1 Answer:**\n", @@ -190,8 +194,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "b15ca066", "metadata": { "tags": [ "solution" @@ -206,8 +210,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "7f1913d5", "metadata": {}, "source": [ "

\n", @@ -217,8 +221,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "a052fd9c", "metadata": {}, "source": [ "**1.2 Answer**\n", @@ -227,8 +231,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "919d876a", "metadata": { "tags": [ "solution" @@ -248,8 +252,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "04052fa2", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -259,6 +263,7 @@ }, { "cell_type": "markdown", + "id": "92d7e71b", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -267,6 +272,7 @@ { "cell_type": "code", "execution_count": null, + "id": "caa1354f", "metadata": {}, "outputs": [], "source": [ @@ -276,8 +282,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9c612ded", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -286,6 +292,7 @@ { "cell_type": "code", "execution_count": null, + "id": "84814b12", "metadata": {}, "outputs": [], "source": [ @@ -300,8 +307,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "08ceb75d", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -310,9 +317,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "54fff804", + "metadata": {}, "outputs": [], "source": [ "# Adding the texture to all images of 4's:\n", @@ -321,8 +327,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "acb4fec9", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -332,6 +338,7 @@ { "cell_type": "code", "execution_count": null, + "id": "dec7dc7c", "metadata": {}, "outputs": [], "source": [ @@ -347,6 +354,7 @@ { "cell_type": "code", "execution_count": null, + "id": "f1ed4bae", "metadata": {}, "outputs": [], "source": [ @@ -367,8 +375,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "067ac0b6", "metadata": {}, "source": [ "

\n", @@ -378,8 +386,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "58836d17", "metadata": {}, "source": [ "**1.4 Answer**\n", @@ -392,8 +400,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "7771570d", "metadata": { "tags": [ "solution" @@ -423,6 +431,7 @@ }, { "cell_type": "markdown", + "id": "7f9e3f2e", "metadata": {}, "source": [ "

\n", @@ -432,8 +441,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "3a081d4b", "metadata": {}, "source": [ "**1.5 Answer:**\n", @@ -442,8 +451,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "32f88963", "metadata": { "tags": [ "solution" @@ -457,6 +466,7 @@ }, { "cell_type": "markdown", + "id": "75f5ffa9", "metadata": {}, "source": [ "

\n", @@ -468,6 +478,7 @@ }, { "cell_type": "markdown", + "id": "d70b21ed", "metadata": {}, "source": [ "

\n", @@ -483,8 +494,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c2c7663f", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -495,9 +506,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "5c57f055", + "metadata": {}, "outputs": [], "source": [ "import torch\n", @@ -509,8 +519,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "384472d8", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -519,6 +529,7 @@ { "cell_type": "code", "execution_count": null, + "id": "715aeca5", "metadata": {}, "outputs": [], "source": [ @@ -542,8 +553,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "71d10d87", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -552,6 +563,7 @@ { "cell_type": "code", "execution_count": null, + "id": "0cc9327a", "metadata": {}, "outputs": [], "source": [ @@ -569,8 +581,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "01135447", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -579,6 +591,7 @@ { "cell_type": "code", "execution_count": null, + "id": "8e713742", "metadata": {}, "outputs": [], "source": [ @@ -605,8 +618,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9add42e7", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -615,6 +628,7 @@ { "cell_type": "code", "execution_count": null, + "id": "f5f46fb9", "metadata": {}, "outputs": [], "source": [ @@ -627,8 +641,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "8d00e620", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -637,9 +651,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "3825f837", + "metadata": {}, "outputs": [], "source": [ "# We store history here:\n", @@ -670,8 +683,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "113d124c", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -680,6 +693,7 @@ { "cell_type": "code", "execution_count": null, + "id": "77dc7f01", "metadata": {}, "outputs": [], "source": [ @@ -694,6 +708,7 @@ }, { "cell_type": "markdown", + "id": "7bbb3294", "metadata": {}, "source": [ "

\n", @@ -703,8 +718,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "dc03ff76", "metadata": {}, "source": [ "**2.1 Answer:**\n", @@ -713,8 +728,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "2ff54948", "metadata": { "tags": [ "solution" @@ -728,6 +743,7 @@ }, { "cell_type": "markdown", + "id": "e4a8142f", "metadata": {}, "source": [ "

\n", @@ -737,8 +753,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "08e6dbfb", "metadata": {}, "source": [ "**2.2 Answer:**\n", @@ -747,8 +763,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9b88f2d0", "metadata": { "tags": [ "solution" @@ -762,6 +778,7 @@ }, { "cell_type": "markdown", + "id": "2e5a25be", "metadata": {}, "source": [ "

\n", @@ -771,8 +788,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e5d581b7", "metadata": {}, "source": [ "**2.3 Answer:**\n", @@ -781,8 +798,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "96f07515", "metadata": { "tags": [ "solution" @@ -795,8 +812,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e7f140c0", "metadata": {}, "source": [ "

\n", @@ -808,6 +825,7 @@ }, { "cell_type": "markdown", + "id": "92f63826", "metadata": {}, "source": [ "

\n", @@ -821,8 +839,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "2373900f", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -835,6 +853,7 @@ { "cell_type": "code", "execution_count": null, + "id": "00e3d111", "metadata": {}, "outputs": [], "source": [ @@ -855,8 +874,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5cb58b48", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -865,9 +884,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "1286c116", + "metadata": {}, "outputs": [], "source": [ "pred_clean_clean, true_labels = predict(model_clean, test_dataset)\n", @@ -877,8 +895,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "607130a5", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -887,6 +905,7 @@ { "cell_type": "code", "execution_count": null, + "id": "cff3b86a", "metadata": {}, "outputs": [], "source": [ @@ -934,12 +953,20 @@ " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", - " ax.set_title(title)\n" + " ax.set_title(title)" ] }, { - "attachments": {}, + "cell_type": "code", + "execution_count": null, + "id": "02dc66b6", + "metadata": {}, + "outputs": [], + "source": [] + }, + { "cell_type": "markdown", + "id": "da283b12", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -948,6 +975,7 @@ { "cell_type": "code", "execution_count": null, + "id": "1a7ca6fe", "metadata": {}, "outputs": [], "source": [ @@ -959,6 +987,7 @@ }, { "cell_type": "markdown", + "id": "2259d225", "metadata": {}, "source": [ "

\n", @@ -968,8 +997,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "af417b0a", "metadata": {}, "source": [ "**3.1 Answer:**\n", @@ -978,8 +1007,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "879549e3", "metadata": { "tags": [ "solution" @@ -994,6 +1023,7 @@ }, { "cell_type": "markdown", + "id": "ea19688f", "metadata": {}, "source": [ "

\n", @@ -1003,8 +1033,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "4ed22f19", "metadata": {}, "source": [ "**3.2 Answer**\n", @@ -1013,8 +1043,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "cc29fc2c", "metadata": { "tags": [ "solution" @@ -1028,6 +1058,7 @@ }, { "cell_type": "markdown", + "id": "82c8c136", "metadata": {}, "source": [ "

\n", @@ -1037,8 +1068,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f932d453", "metadata": {}, "source": [ "**3.3 Answer:**\n", @@ -1047,8 +1078,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9c42945b", "metadata": { "tags": [ "solution" @@ -1064,8 +1095,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "33f1696c", "metadata": {}, "source": [ "

\n", @@ -1075,8 +1106,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9241c879", "metadata": {}, "source": [ "**3.4 Answer:**\n", @@ -1085,8 +1116,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "da328962", "metadata": { "tags": [ "solution" @@ -1105,8 +1136,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "38cec29f", "metadata": {}, "source": [ "

\n", @@ -1118,6 +1149,7 @@ }, { "cell_type": "markdown", + "id": "095add84", "metadata": {}, "source": [ "

\n", @@ -1131,8 +1163,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c95f054c", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1140,8 +1172,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5af9ad88", "metadata": {}, "source": [ "\n", @@ -1151,9 +1183,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "e5b50913", + "metadata": {}, "outputs": [], "source": [ "from captum.attr import IntegratedGradients\n", @@ -1184,8 +1215,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "851dfcc4", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1194,6 +1225,7 @@ { "cell_type": "code", "execution_count": null, + "id": "21c16b69", "metadata": {}, "outputs": [], "source": [ @@ -1231,8 +1263,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "46892e8a", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1243,6 +1275,7 @@ { "cell_type": "code", "execution_count": null, + "id": "7e458c2e", "metadata": {}, "outputs": [], "source": [ @@ -1251,8 +1284,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "bd939031", "metadata": {}, "source": [ "

\n", @@ -1262,8 +1295,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "10f375ad", "metadata": {}, "source": [ "**4.1 Answer:**\n", @@ -1272,8 +1305,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e82ccc2d", "metadata": { "tags": [ "solution" @@ -1287,8 +1320,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "fc29b799", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1297,9 +1330,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "50bdd6f1", + "metadata": {}, "outputs": [], "source": [ "visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, \"Tainted Model on Tainted 7\")\n", @@ -1307,8 +1339,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "03d55adf", "metadata": {}, "source": [ "

\n", @@ -1318,8 +1350,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5b1f5921", "metadata": {}, "source": [ "**4.2 Answer:**\n", @@ -1328,8 +1360,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c67e4497", "metadata": { "tags": [ "solution" @@ -1346,8 +1378,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "b6deb133", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1356,6 +1388,7 @@ { "cell_type": "code", "execution_count": null, + "id": "ff3ad936", "metadata": {}, "outputs": [], "source": [ @@ -1366,8 +1399,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "e9b71f00", "metadata": {}, "source": [ "

\n", @@ -1377,8 +1410,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "1a1ef215", "metadata": {}, "source": [ "**4.3 Answer:**\n", @@ -1387,8 +1420,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "2b9b91df", "metadata": { "tags": [ "solution" @@ -1404,8 +1437,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "40afb7bf", "metadata": {}, "source": [ "

\n", @@ -1415,8 +1448,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "430bc487", "metadata": {}, "source": [ "**4.4 Answer:**\n", @@ -1425,8 +1458,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "5d03a39f", "metadata": { "tags": [ "solution" @@ -1441,8 +1474,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "53903eb9", "metadata": {}, "source": [ "

\n", @@ -1454,8 +1487,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "289ae5b8", "metadata": {}, "source": [ "

\n", @@ -1468,8 +1501,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "0fb49b82", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1480,8 +1513,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "ffef525a", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1490,6 +1523,7 @@ { "cell_type": "code", "execution_count": null, + "id": "0c30b952", "metadata": {}, "outputs": [], "source": [ @@ -1497,12 +1531,14 @@ "\n", "# A simple function to add noise to tensors:\n", "def add_noise(tensor, power=1.5):\n", - " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)\n" + " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)\n", + "\n", + "\n" ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "a80f6331", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1511,6 +1547,7 @@ { "cell_type": "code", "execution_count": null, + "id": "1fab7a3b", "metadata": {}, "outputs": [], "source": [ @@ -1538,8 +1575,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "82e3d8ca", "metadata": {}, "source": [ "### UNet model\n", @@ -1548,8 +1585,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "1b5676c1", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1558,6 +1595,7 @@ { "cell_type": "code", "execution_count": null, + "id": "73915d29", "metadata": {}, "outputs": [], "source": [ @@ -1604,8 +1642,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9c8bcba9", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1614,6 +1652,7 @@ { "cell_type": "code", "execution_count": null, + "id": "35365339", "metadata": {}, "outputs": [], "source": [ @@ -1650,8 +1689,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "6cb2ac9d", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1660,6 +1699,7 @@ { "cell_type": "code", "execution_count": null, + "id": "6e355db2", "metadata": {}, "outputs": [], "source": [ @@ -1669,8 +1709,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "3564b3ea", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1679,6 +1719,7 @@ { "cell_type": "code", "execution_count": null, + "id": "dfd4eef7", "metadata": {}, "outputs": [], "source": [ @@ -1691,8 +1732,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f06e0944", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1703,6 +1744,7 @@ { "cell_type": "code", "execution_count": null, + "id": "67a29006", "metadata": {}, "outputs": [], "source": [ @@ -1711,12 +1753,21 @@ " image = torch.unsqueeze(torch.unsqueeze(image, 0), 0)\n", " prediction = model(image.cuda())\n", " # remove batch and channel dimensions before returning\n", - " return prediction.detach().cpu()[0,0]\n" + " return prediction.detach().cpu()[0,0]" ] }, { "cell_type": "code", "execution_count": null, + "id": "2b02e3f4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e0ab7202", "metadata": {}, "outputs": [], "source": [ @@ -1745,6 +1796,7 @@ }, { "cell_type": "markdown", + "id": "93d7f562", "metadata": {}, "source": [ "

\n", @@ -1754,8 +1806,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "42672a70", "metadata": {}, "source": [ "**5.1 Answer:**\n", @@ -1764,8 +1816,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "9ded3ea2", "metadata": { "tags": [ "solution" @@ -1779,6 +1831,7 @@ }, { "cell_type": "markdown", + "id": "d580d3c3", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1787,8 +1840,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "36e71a10", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1799,6 +1852,7 @@ { "cell_type": "code", "execution_count": null, + "id": "bbefda7f", "metadata": {}, "outputs": [], "source": [ @@ -1818,8 +1872,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "265dbeb6", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1828,9 +1882,8 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "id": "336f9148", + "metadata": {}, "outputs": [], "source": [ "for i in range(8):\n", @@ -1839,6 +1892,7 @@ }, { "cell_type": "markdown", + "id": "fbfa0eff", "metadata": {}, "source": [ "

\n", @@ -1848,8 +1902,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "6006a3c0", "metadata": {}, "source": [ "**5.2 Answer:**\n", @@ -1858,8 +1912,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "c82e741e", "metadata": { "tags": [ "solution" @@ -1873,6 +1927,7 @@ }, { "cell_type": "markdown", + "id": "99568021", "metadata": {}, "source": [ "

\n", @@ -1882,8 +1937,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "2e946390", "metadata": {}, "source": [ "**5.3 Answer:**\n", @@ -1892,8 +1947,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f4a037d8", "metadata": { "tags": [ "solution" @@ -1907,8 +1962,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "28e78d4b", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1919,6 +1974,7 @@ { "cell_type": "code", "execution_count": null, + "id": "96d08a22", "metadata": {}, "outputs": [], "source": [ @@ -1955,6 +2011,7 @@ { "cell_type": "code", "execution_count": null, + "id": "dc708995", "metadata": {}, "outputs": [], "source": [ @@ -1965,6 +2022,7 @@ { "cell_type": "code", "execution_count": null, + "id": "2c8605be", "metadata": {}, "outputs": [], "source": [ @@ -1974,6 +2032,7 @@ }, { "cell_type": "markdown", + "id": "70371b8a", "metadata": {}, "source": [ "

\n", @@ -1983,8 +2042,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "3c601a00", "metadata": {}, "source": [ "**5.4 Answer:**\n", @@ -1993,8 +2052,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "6c40f853", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", @@ -2005,6 +2064,7 @@ { "cell_type": "code", "execution_count": null, + "id": "bfdf1d22", "metadata": {}, "outputs": [], "source": [ @@ -2041,6 +2101,7 @@ { "cell_type": "code", "execution_count": null, + "id": "e7136f16", "metadata": {}, "outputs": [], "source": [ @@ -2051,6 +2112,7 @@ { "cell_type": "code", "execution_count": null, + "id": "a7f0ac83", "metadata": {}, "outputs": [], "source": [ @@ -2060,6 +2122,7 @@ }, { "cell_type": "markdown", + "id": "3182b80b", "metadata": {}, "source": [ "

\n", @@ -2069,8 +2132,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "fcd1c1bb", "metadata": {}, "source": [ "**5.5 Answer:**\n", @@ -2079,8 +2142,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "439f1c11", "metadata": {}, "source": [ "

\n", @@ -2092,8 +2155,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "b00b8e8d", "metadata": {}, "source": [ "

\n", @@ -2107,24 +2170,15 @@ } ], "metadata": { + "jupytext": { + "cell_metadata_filter": "all" + }, "kernelspec": { "display_name": "Python [conda env:07-failure-modes]", "language": "python", "name": "conda-env-07-failure-modes-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.5" } }, "nbformat": 4, - "nbformat_minor": 4 + "nbformat_minor": 5 } From 8ae095e6e65c74297a027dd7d2c9ccf1cd0e430c Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 17:54:50 +0100 Subject: [PATCH 22/51] dded solution tag to all answers in solution.py --- solution.py | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/solution.py b/solution.py index 326a540..0d35de2 100644 --- a/solution.py +++ b/solution.py @@ -109,6 +109,7 @@ # We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data colleciton, for example in a hospital imaging environment or microscopy lab? #

+# + [markdown] tags=["solution"] # **1.1 Answer:** # # In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images. @@ -128,6 +129,7 @@ # In your above examples, if you knew you had a local corruption or difference between images in different classes of your data, could you remove it? How? #

+# + [markdown] tags=["solution"] # **1.2 Answer** # # We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset. @@ -208,6 +210,7 @@ # Think of a realistic example of such a corruption that would affect only some classes of data. If you notice the differences between classes, could you remove it? How? #

+# + [markdown] tags=["solution"] # **1.4 Answer** # # A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact. @@ -244,6 +247,7 @@ # Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset? #

+# + [markdown] tags=["solution"] # **1.5 Answer:** # # The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying. @@ -405,6 +409,7 @@ def init_weights(m): # Why do you think the tainted network has lower training loss than the clean network? #

+# + [markdown] tags=["solution"] # **2.1 Answer:** # # As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify. @@ -420,6 +425,7 @@ def init_weights(m): # Do you think the tainted network will be more accurate than the clean network when applied to the tainted test data? Why? #

+# + [markdown] tags=["solution"] # **2.2 Answer:** # # Yes, the tainted network will be more accurate than the clean network when applied to the tainted test data as it will leverage the corruption present in that test data, since it trained to do so. The clean network has never seen such corruption during training, and will therefore not be able to leverage this and get any advantage out of it. @@ -435,6 +441,7 @@ def init_weights(m): # Do you think the tainted network will be more accurate than the clean network when applied to the clean test data? Why? #

+# + [markdown] tags=["solution"] # **2.3 Answer:** # # The tainted network is relying on grid patterns to detect 4s and on dots in the bottom right corner to detect 7s. Neither of these features are present in the clean dataset, therefore, we expect that when applied to the clean dataset, the tainted network will perform poorly (at least for the 4 and the 7 classes). @@ -554,6 +561,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model? #

+# + [markdown] tags=["solution"] # **3.1 Answer:** # # The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments). @@ -570,6 +578,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # Does the tainted model on the tainted dataset perform better or worse than the clean model on the clean dataset? Which digits is it better or worse on? Why do you think that is the case? #

+# + [markdown] tags=["solution"] # **3.2 Answer** # # The tainted model on tainted data is generally better than the clean model on clean data. Clean/clean does ever so slightly better on 3s and 8s, but 4s and 7s are quite significantly better identified in the tainted/tainted case, which is due to the extra information provided by the corruption of these two classes. @@ -585,6 +594,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # For the clean model and the tainted dataset, was the local corruption on the 7s or the global corruption on the 4s harder for the model trained on clean data to deal with? Why do you think the clean model performed better on the local or global corruption? #

+# + [markdown] tags=["solution"] # **3.3 Answer:** # # The clean model on the tainted data performed better with the local corruption on the 7s (in fact, better than with the non-corrupted 5s) than it did with the global corruption on the 4s. @@ -603,6 +613,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # Did the tainted model perform worse on clean 7s or clean 4s? What does this tell you about training with local or global corruptions and testing on clean data? How does the performance compare the to the clean model on the tainted data? #

+# + [markdown] tags=["solution"] # **3.4 Answer:** # # The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data. @@ -722,6 +733,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # Where did the clean model focus its attention for the clean and tainted 7s? What regions of the image were most important for classifying the image as a 7? #

+# + [markdown] tags=["solution"] # **4.1 Answer:** # # The clean model focus its attention to the 7 itself. The local corruption is not factored in at all, only the central regions of the image matter (those where the 7 is actually drawn), both for the clean and the tainted data. @@ -744,6 +756,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # Where did the tainted model focus its attention for the clean and tainted 7s? How was this different than the clean model? Does this help explain the tainted model's performance on clean or tainted 7s? #

+# + [markdown] tags=["solution"] # **4.2 Answer:** # # The tainted model only focuses on the dot in the tainted 7. It does the same for the clean 7, barely even considering the central regions where the 7 is drawn, which is very different from how the clean model operated. Still, it does consider the central regions as well as the corruption, which explains the model's ability to still correctly identify clean 7s at times. @@ -770,6 +783,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # Where did the tainted model focus its attention for the tainted and clean 4s? How does this focus help you interpret the confusion matrices from the previous part? #

+# + [markdown] tags=["solution"] # **4.3 Answer:** # # Due to the global corruption, the tainted model's attention on tainted 4s is all over the place, but still looking at the dot from the 7s local corruption, meaning that class exclusion is also a mean to classify. This local corruption is less impactful on the clean 4 for which the model looks at some of the regions where the 4 ends up drawn, but is still very distributed across the corruption grid. @@ -788,6 +802,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # Did you find the integrated gradients more useful for the global or local corruptions of the data? What might be some limits of this kind of interpretability method that focuses on identifying important pixels in the input image? #

+# + [markdown] tags=["solution"] # **4.4 Answer:** # # The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally. @@ -1006,6 +1021,7 @@ def visualize_denoising(model, dataset, index): # Did the denoising net trained on MNIST work well on unseen test data? What do you think will happen when we apply it to the Fashion-MNIST data? #

+# + [markdown] tags=["solution"] # **5.1 Answer:** # # The denoising MNIST did relatively well considering it extracted images which allows a human to identify a digit when it wasn't necessarily obvious from the noisy image. It has however been trained to look for digits. Applying it to Fashion-MNIST will possibly sucessfully "remove noise", but recovering objects that it hasn't seen before may not work as well. @@ -1052,6 +1068,7 @@ def visualize_denoising(model, dataset, index): # What happened when the MNIST denoising model was applied to the FashionMNIST data? Why do you think the results look as they do? #

+# + [markdown] tags=["solution"] # **5.2 Answer:** # # The "noise" is apparently gone, however, the objects are hardly recognizable. Some look like they have been reshaped like digits in the process. @@ -1067,6 +1084,7 @@ def visualize_denoising(model, dataset, index): # Can you imagine any real-world scenarios where a denoising model would change the content of an image? #

+# + [markdown] tags=["solution"] # **5.3 Answer:** # # If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being "denoised" away. @@ -1124,6 +1142,7 @@ def visualize_denoising(model, dataset, index): # How does the new denoiser perform compared to the one from the previous section? #

+# + [markdown] tags=["solution"] # **5.4 Answer:** # # The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable). @@ -1174,6 +1193,7 @@ def visualize_denoising(model, dataset, index): # How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other? #

+# + [markdown] tags=["solution"] # **5.5 Answer:** # # The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets. From bfab2c340676ed402c26133002e3c2879fc3182f Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 16:56:15 +0000 Subject: [PATCH 23/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 471 ++++++++++++------------------------------------- solution.ipynb | 454 +++++++++++++++++++++++++++-------------------- 2 files changed, 372 insertions(+), 553 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 11b5679..427928c 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "0dc6c785", + "id": "e2b2f8e5", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "c614728c", + "id": "1486e0f6", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "fc3881d3", + "id": "b16d4ecd", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "f73124ca", + "id": "71b6f22f", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "1077a64b", + "id": "55500021", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ebf5aeec", + "id": "709d7035", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "cf47d477", + "id": "1be17f2c", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b7704b40", + "id": "858af61f", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e3c7b35a", + "id": "5fabeee1", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "545cd1e4", + "id": "aab42d3b", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "be8a5784", + "id": "1b0a0e10", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e36c85c4", + "id": "0dd3903e", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "a8aac1c1", + "id": "0c2ae1a7", "metadata": {}, "source": [ "

\n", @@ -183,19 +183,7 @@ }, { "cell_type": "markdown", - "id": "00d57078", - "metadata": {}, - "source": [ - "**1.1 Answer:**\n", - "\n", - "In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images.\n", - "\n", - "In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. " - ] - }, - { - "cell_type": "markdown", - "id": "7f1913d5", + "id": "5465d561", "metadata": {}, "source": [ "

\n", @@ -206,17 +194,7 @@ }, { "cell_type": "markdown", - "id": "a052fd9c", - "metadata": {}, - "source": [ - "**1.2 Answer**\n", - "\n", - "We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset." - ] - }, - { - "cell_type": "markdown", - "id": "04052fa2", + "id": "f1a2713d", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -226,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "92d7e71b", + "id": "552b6283", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -235,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caa1354f", + "id": "111b7240", "metadata": {}, "outputs": [], "source": [ @@ -246,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "9c612ded", + "id": "83a83189", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -255,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "84814b12", + "id": "1e1c8808", "metadata": {}, "outputs": [], "source": [ @@ -271,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "08ceb75d", + "id": "2f7d08cc", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -280,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "54fff804", + "id": "4126900f", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "acb4fec9", + "id": "55655c98", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -301,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dec7dc7c", + "id": "07c7b4b8", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f1ed4bae", + "id": "8baf6fb2", "metadata": {}, "outputs": [], "source": [ @@ -339,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "067ac0b6", + "id": "77521105", "metadata": {}, "source": [ "

\n", @@ -350,21 +328,7 @@ }, { "cell_type": "markdown", - "id": "58836d17", - "metadata": {}, - "source": [ - "**1.4 Answer**\n", - "\n", - "A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact.\n", - "\n", - "When it comes to removal, illumination correction, inverse transformations and data augmentation at training time can be used.\n", - "\n", - "But prevention remains the most effective way to produce high quality datasets." - ] - }, - { - "cell_type": "markdown", - "id": "7f9e3f2e", + "id": "9afcad6f", "metadata": {}, "source": [ "

\n", @@ -375,17 +339,7 @@ }, { "cell_type": "markdown", - "id": "3a081d4b", - "metadata": {}, - "source": [ - "**1.5 Answer:**\n", - "\n", - "The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying." - ] - }, - { - "cell_type": "markdown", - "id": "75f5ffa9", + "id": "ff66c973", "metadata": {}, "source": [ "

\n", @@ -397,7 +351,7 @@ }, { "cell_type": "markdown", - "id": "d70b21ed", + "id": "672a75ce", "metadata": {}, "source": [ "

\n", @@ -414,7 +368,7 @@ }, { "cell_type": "markdown", - "id": "c2c7663f", + "id": "f53c38d0", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -425,7 +379,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5c57f055", + "id": "e92c0d27", "metadata": {}, "outputs": [], "source": [ @@ -439,7 +393,7 @@ }, { "cell_type": "markdown", - "id": "384472d8", + "id": "add969af", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -448,7 +402,7 @@ { "cell_type": "code", "execution_count": null, - "id": "715aeca5", + "id": "5be59c75", "metadata": {}, "outputs": [], "source": [ @@ -473,7 +427,7 @@ }, { "cell_type": "markdown", - "id": "71d10d87", + "id": "19ac0693", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -482,7 +436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0cc9327a", + "id": "d547978b", "metadata": {}, "outputs": [], "source": [ @@ -501,7 +455,7 @@ }, { "cell_type": "markdown", - "id": "01135447", + "id": "15ce488c", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -510,7 +464,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8e713742", + "id": "16c41727", "metadata": {}, "outputs": [], "source": [ @@ -538,7 +492,7 @@ }, { "cell_type": "markdown", - "id": "9add42e7", + "id": "9e961e8d", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -547,7 +501,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f5f46fb9", + "id": "23323b2b", "metadata": {}, "outputs": [], "source": [ @@ -561,7 +515,7 @@ }, { "cell_type": "markdown", - "id": "8d00e620", + "id": "89956be7", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -570,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3825f837", + "id": "401c6b2b", "metadata": {}, "outputs": [], "source": [ @@ -603,7 +557,7 @@ }, { "cell_type": "markdown", - "id": "113d124c", + "id": "cc555a3d", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -612,7 +566,7 @@ { "cell_type": "code", "execution_count": null, - "id": "77dc7f01", + "id": "a24b84f2", "metadata": {}, "outputs": [], "source": [ @@ -627,7 +581,7 @@ }, { "cell_type": "markdown", - "id": "7bbb3294", + "id": "6df45ee1", "metadata": {}, "source": [ "

\n", @@ -638,17 +592,7 @@ }, { "cell_type": "markdown", - "id": "dc03ff76", - "metadata": {}, - "source": [ - "**2.1 Answer:**\n", - "\n", - "As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify." - ] - }, - { - "cell_type": "markdown", - "id": "e4a8142f", + "id": "7df63f8f", "metadata": {}, "source": [ "

\n", @@ -659,17 +603,7 @@ }, { "cell_type": "markdown", - "id": "08e6dbfb", - "metadata": {}, - "source": [ - "**2.2 Answer:**\n", - "\n", - "Yes, the tainted network will be more accurate than the clean network when applied to the tainted test data as it will leverage the corruption present in that test data, since it trained to do so. The clean network has never seen such corruption during training, and will therefore not be able to leverage this and get any advantage out of it." - ] - }, - { - "cell_type": "markdown", - "id": "2e5a25be", + "id": "4271217f", "metadata": {}, "source": [ "

\n", @@ -680,17 +614,7 @@ }, { "cell_type": "markdown", - "id": "e5d581b7", - "metadata": {}, - "source": [ - "**2.3 Answer:**\n", - "\n", - "The tainted network is relying on grid patterns to detect 4s and on dots in the bottom right corner to detect 7s. Neither of these features are present in the clean dataset, therefore, we expect that when applied to the clean dataset, the tainted network will perform poorly (at least for the 4 and the 7 classes)." - ] - }, - { - "cell_type": "markdown", - "id": "e7f140c0", + "id": "b31868b6", "metadata": {}, "source": [ "

\n", @@ -702,7 +626,7 @@ }, { "cell_type": "markdown", - "id": "92f63826", + "id": "a3e49dae", "metadata": {}, "source": [ "

\n", @@ -717,7 +641,7 @@ }, { "cell_type": "markdown", - "id": "2373900f", + "id": "432049a6", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -730,7 +654,7 @@ { "cell_type": "code", "execution_count": null, - "id": "00e3d111", + "id": "0c931233", "metadata": {}, "outputs": [], "source": [ @@ -752,7 +676,7 @@ }, { "cell_type": "markdown", - "id": "5cb58b48", + "id": "258daf07", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -761,7 +685,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1286c116", + "id": "19167fa2", "metadata": {}, "outputs": [], "source": [ @@ -773,7 +697,7 @@ }, { "cell_type": "markdown", - "id": "607130a5", + "id": "01002da0", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -782,7 +706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cff3b86a", + "id": "af94666a", "metadata": {}, "outputs": [], "source": [ @@ -836,14 +760,14 @@ { "cell_type": "code", "execution_count": null, - "id": "02dc66b6", + "id": "f8723f92", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", - "id": "da283b12", + "id": "a18b0900", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -852,7 +776,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1a7ca6fe", + "id": "5caa855a", "metadata": {}, "outputs": [], "source": [ @@ -864,7 +788,7 @@ }, { "cell_type": "markdown", - "id": "2259d225", + "id": "efa46250", "metadata": {}, "source": [ "

\n", @@ -875,17 +799,7 @@ }, { "cell_type": "markdown", - "id": "af417b0a", - "metadata": {}, - "source": [ - "**3.1 Answer:**\n", - "\n", - "The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments)." - ] - }, - { - "cell_type": "markdown", - "id": "ea19688f", + "id": "1cfcffe1", "metadata": {}, "source": [ "

\n", @@ -896,17 +810,7 @@ }, { "cell_type": "markdown", - "id": "4ed22f19", - "metadata": {}, - "source": [ - "**3.2 Answer**\n", - "\n", - "The tainted model on tainted data is generally better than the clean model on clean data. Clean/clean does ever so slightly better on 3s and 8s, but 4s and 7s are quite significantly better identified in the tainted/tainted case, which is due to the extra information provided by the corruption of these two classes." - ] - }, - { - "cell_type": "markdown", - "id": "82c8c136", + "id": "7d811061", "metadata": {}, "source": [ "

\n", @@ -917,17 +821,7 @@ }, { "cell_type": "markdown", - "id": "f932d453", - "metadata": {}, - "source": [ - "**3.3 Answer:**\n", - "\n", - "The clean model on the tainted data performed better with the local corruption on the 7s (in fact, better than with the non-corrupted 5s) than it did with the global corruption on the 4s." - ] - }, - { - "cell_type": "markdown", - "id": "33f1696c", + "id": "2eb81703", "metadata": {}, "source": [ "

\n", @@ -938,17 +832,7 @@ }, { "cell_type": "markdown", - "id": "9241c879", - "metadata": {}, - "source": [ - "**3.4 Answer:**\n", - "\n", - "The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data." - ] - }, - { - "cell_type": "markdown", - "id": "38cec29f", + "id": "f4e2645d", "metadata": {}, "source": [ "

\n", @@ -960,7 +844,7 @@ }, { "cell_type": "markdown", - "id": "095add84", + "id": "eaa2aca7", "metadata": {}, "source": [ "

\n", @@ -975,7 +859,7 @@ }, { "cell_type": "markdown", - "id": "c95f054c", + "id": "f50d6106", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -984,7 +868,7 @@ }, { "cell_type": "markdown", - "id": "5af9ad88", + "id": "4fa74a0a", "metadata": {}, "source": [ "\n", @@ -994,7 +878,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e5b50913", + "id": "ba4da828", "metadata": {}, "outputs": [], "source": [ @@ -1027,7 +911,7 @@ }, { "cell_type": "markdown", - "id": "851dfcc4", + "id": "47cb109a", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1036,7 +920,7 @@ { "cell_type": "code", "execution_count": null, - "id": "21c16b69", + "id": "178a39d7", "metadata": {}, "outputs": [], "source": [ @@ -1075,7 +959,7 @@ }, { "cell_type": "markdown", - "id": "46892e8a", + "id": "12f406b0", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1086,7 +970,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7e458c2e", + "id": "0a1d6560", "metadata": {}, "outputs": [], "source": [ @@ -1096,7 +980,7 @@ }, { "cell_type": "markdown", - "id": "bd939031", + "id": "fe09a285", "metadata": {}, "source": [ "

\n", @@ -1107,17 +991,7 @@ }, { "cell_type": "markdown", - "id": "10f375ad", - "metadata": {}, - "source": [ - "**4.1 Answer:**\n", - "\n", - "The clean model focus its attention to the 7 itself. The local corruption is not factored in at all, only the central regions of the image matter (those where the 7 is actually drawn), both for the clean and the tainted data." - ] - }, - { - "cell_type": "markdown", - "id": "fc29b799", + "id": "315b740a", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1126,7 +1000,7 @@ { "cell_type": "code", "execution_count": null, - "id": "50bdd6f1", + "id": "0c715c49", "metadata": {}, "outputs": [], "source": [ @@ -1136,7 +1010,7 @@ }, { "cell_type": "markdown", - "id": "03d55adf", + "id": "8db82f66", "metadata": {}, "source": [ "

\n", @@ -1147,17 +1021,7 @@ }, { "cell_type": "markdown", - "id": "5b1f5921", - "metadata": {}, - "source": [ - "**4.2 Answer:**\n", - "\n", - "The tainted model only focuses on the dot in the tainted 7. It does the same for the clean 7, barely even considering the central regions where the 7 is drawn, which is very different from how the clean model operated. Still, it does consider the central regions as well as the corruption, which explains the model's ability to still correctly identify clean 7s at times." - ] - }, - { - "cell_type": "markdown", - "id": "b6deb133", + "id": "64f48898", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1166,7 +1030,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ff3ad936", + "id": "824a2128", "metadata": {}, "outputs": [], "source": [ @@ -1178,7 +1042,7 @@ }, { "cell_type": "markdown", - "id": "e9b71f00", + "id": "30db6d44", "metadata": {}, "source": [ "

\n", @@ -1189,17 +1053,7 @@ }, { "cell_type": "markdown", - "id": "1a1ef215", - "metadata": {}, - "source": [ - "**4.3 Answer:**\n", - "\n", - "Due to the global corruption, the tainted model's attention on tainted 4s is all over the place, but still looking at the dot from the 7s local corruption, meaning that class exclusion is also a mean to classify. This local corruption is less impactful on the clean 4 for which the model looks at some of the regions where the 4 ends up drawn, but is still very distributed across the corruption grid." - ] - }, - { - "cell_type": "markdown", - "id": "40afb7bf", + "id": "078b8fdc", "metadata": {}, "source": [ "

\n", @@ -1210,17 +1064,7 @@ }, { "cell_type": "markdown", - "id": "430bc487", - "metadata": {}, - "source": [ - "**4.4 Answer:**\n", - "\n", - "The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally." - ] - }, - { - "cell_type": "markdown", - "id": "53903eb9", + "id": "2e3f0338", "metadata": {}, "source": [ "

\n", @@ -1233,7 +1077,7 @@ }, { "cell_type": "markdown", - "id": "289ae5b8", + "id": "f8a4ea81", "metadata": {}, "source": [ "

\n", @@ -1247,7 +1091,7 @@ }, { "cell_type": "markdown", - "id": "0fb49b82", + "id": "2c98ff21", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1259,7 +1103,7 @@ }, { "cell_type": "markdown", - "id": "ffef525a", + "id": "a20179a5", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1268,7 +1112,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c30b952", + "id": "afc8f426", "metadata": {}, "outputs": [], "source": [ @@ -1283,7 +1127,7 @@ }, { "cell_type": "markdown", - "id": "a80f6331", + "id": "d16af11f", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1292,7 +1136,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1fab7a3b", + "id": "e0956137", "metadata": {}, "outputs": [], "source": [ @@ -1321,7 +1165,7 @@ }, { "cell_type": "markdown", - "id": "82e3d8ca", + "id": "3d7d729d", "metadata": {}, "source": [ "### UNet model\n", @@ -1331,7 +1175,7 @@ }, { "cell_type": "markdown", - "id": "1b5676c1", + "id": "f128e0d5", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1340,7 +1184,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73915d29", + "id": "5c6743ed", "metadata": {}, "outputs": [], "source": [ @@ -1388,7 +1232,7 @@ }, { "cell_type": "markdown", - "id": "9c8bcba9", + "id": "dcfe5981", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1397,7 +1241,7 @@ { "cell_type": "code", "execution_count": null, - "id": "35365339", + "id": "94fe0b9d", "metadata": {}, "outputs": [], "source": [ @@ -1435,7 +1279,7 @@ }, { "cell_type": "markdown", - "id": "6cb2ac9d", + "id": "cb5be242", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1444,7 +1288,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6e355db2", + "id": "2cd4f305", "metadata": {}, "outputs": [], "source": [ @@ -1455,7 +1299,7 @@ }, { "cell_type": "markdown", - "id": "3564b3ea", + "id": "c8addd07", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1464,7 +1308,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dfd4eef7", + "id": "d32a9664", "metadata": {}, "outputs": [], "source": [ @@ -1478,7 +1322,7 @@ }, { "cell_type": "markdown", - "id": "f06e0944", + "id": "d1c1b2a8", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1489,7 +1333,7 @@ { "cell_type": "code", "execution_count": null, - "id": "67a29006", + "id": "bb313fa5", "metadata": {}, "outputs": [], "source": [ @@ -1504,7 +1348,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2b02e3f4", + "id": "57d4f69e", "metadata": {}, "outputs": [], "source": [] @@ -1512,7 +1356,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0ab7202", + "id": "1c72a1cf", "metadata": {}, "outputs": [], "source": [ @@ -1541,7 +1385,7 @@ }, { "cell_type": "markdown", - "id": "93d7f562", + "id": "35109e13", "metadata": {}, "source": [ "

\n", @@ -1552,17 +1396,7 @@ }, { "cell_type": "markdown", - "id": "42672a70", - "metadata": {}, - "source": [ - "**5.1 Answer:**\n", - "\n", - "The denoising MNIST did relatively well considering it extracted images which allows a human to identify a digit when it wasn't necessarily obvious from the noisy image. It has however been trained to look for digits. Applying it to Fashion-MNIST will possibly sucessfully \"remove noise\", but recovering objects that it hasn't seen before may not work as well." - ] - }, - { - "cell_type": "markdown", - "id": "d580d3c3", + "id": "b7eb0224", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1572,7 +1406,7 @@ }, { "cell_type": "markdown", - "id": "36e71a10", + "id": "499d0ceb", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1583,7 +1417,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bbefda7f", + "id": "75b8cace", "metadata": {}, "outputs": [], "source": [ @@ -1604,7 +1438,7 @@ }, { "cell_type": "markdown", - "id": "265dbeb6", + "id": "5896d150", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1613,7 +1447,7 @@ { "cell_type": "code", "execution_count": null, - "id": "336f9148", + "id": "952fff80", "metadata": {}, "outputs": [], "source": [ @@ -1623,7 +1457,7 @@ }, { "cell_type": "markdown", - "id": "fbfa0eff", + "id": "43c36e17", "metadata": {}, "source": [ "

\n", @@ -1634,17 +1468,7 @@ }, { "cell_type": "markdown", - "id": "6006a3c0", - "metadata": {}, - "source": [ - "**5.2 Answer:**\n", - "\n", - "The \"noise\" is apparently gone, however, the objects are hardly recognizable. Some look like they have been reshaped like digits in the process." - ] - }, - { - "cell_type": "markdown", - "id": "99568021", + "id": "ed1de42c", "metadata": {}, "source": [ "

\n", @@ -1655,17 +1479,7 @@ }, { "cell_type": "markdown", - "id": "2e946390", - "metadata": {}, - "source": [ - "**5.3 Answer:**\n", - "\n", - "If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being \"denoised\" away." - ] - }, - { - "cell_type": "markdown", - "id": "28e78d4b", + "id": "ea481c7f", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1676,7 +1490,7 @@ { "cell_type": "code", "execution_count": null, - "id": "96d08a22", + "id": "bfff2a4b", "metadata": {}, "outputs": [], "source": [ @@ -1713,7 +1527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dc708995", + "id": "fc58e649", "metadata": {}, "outputs": [], "source": [ @@ -1724,7 +1538,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c8605be", + "id": "62ee68b5", "metadata": {}, "outputs": [], "source": [ @@ -1734,7 +1548,7 @@ }, { "cell_type": "markdown", - "id": "70371b8a", + "id": "55bcf106", "metadata": {}, "source": [ "

\n", @@ -1743,30 +1557,10 @@ "

" ] }, - { - "cell_type": "markdown", - "id": "3c601a00", - "metadata": {}, - "source": [ - "**5.4 Answer:**\n", - "\n", - "The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable)." - ] - }, - { - "cell_type": "markdown", - "id": "6c40f853", - "metadata": {}, - "source": [ - "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", - "\n", - "We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below)" - ] - }, { "cell_type": "code", "execution_count": null, - "id": "bfdf1d22", + "id": "27e11ee9", "metadata": {}, "outputs": [], "source": [ @@ -1803,7 +1597,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e7136f16", + "id": "73d18976", "metadata": {}, "outputs": [], "source": [ @@ -1814,7 +1608,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a7f0ac83", + "id": "4f304e41", "metadata": {}, "outputs": [], "source": [ @@ -1824,7 +1618,7 @@ }, { "cell_type": "markdown", - "id": "3182b80b", + "id": "3f3107f0", "metadata": {}, "source": [ "

\n", @@ -1832,43 +1626,6 @@ "How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other?\n", "

" ] - }, - { - "cell_type": "markdown", - "id": "fcd1c1bb", - "metadata": {}, - "source": [ - "**5.5 Answer:**\n", - "\n", - "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets." - ] - }, - { - "cell_type": "markdown", - "id": "439f1c11", - "metadata": {}, - "source": [ - "

\n", - " Checkpoint 5

\n", - "
    \n", - " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", - "
\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "b00b8e8d", - "metadata": {}, - "source": [ - "

\n", - " Bonus Questions

\n", - "
    \n", - "
  1. Try training a FashionMNIST denoising network and applying it to MNIST. Or, try training a denoising network on both datasets and see how it works on each.
    2. \n", - "
  2. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
    3. \n", - "
\n", - "
" - ] } ], "metadata": { diff --git a/solution.ipynb b/solution.ipynb index 537ff6d..2c7c8d7 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "0dc6c785", + "id": "e2b2f8e5", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "c614728c", + "id": "1486e0f6", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "fc3881d3", + "id": "b16d4ecd", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "f73124ca", + "id": "71b6f22f", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "1077a64b", + "id": "55500021", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ebf5aeec", + "id": "709d7035", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "cf47d477", + "id": "1be17f2c", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b7704b40", + "id": "858af61f", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e3c7b35a", + "id": "5fabeee1", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "545cd1e4", + "id": "aab42d3b", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "be8a5784", + "id": "1b0a0e10", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e36c85c4", + "id": "0dd3903e", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "a8aac1c1", + "id": "0c2ae1a7", "metadata": {}, "source": [ "

\n", @@ -183,8 +183,12 @@ }, { "cell_type": "markdown", - "id": "00d57078", - "metadata": {}, + "id": "90f63ace", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**1.1 Answer:**\n", "\n", @@ -195,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "b15ca066", + "id": "12341439", "metadata": { "tags": [ "solution" @@ -211,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "7f1913d5", + "id": "5465d561", "metadata": {}, "source": [ "

\n", @@ -222,8 +226,12 @@ }, { "cell_type": "markdown", - "id": "a052fd9c", - "metadata": {}, + "id": "9c849962", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**1.2 Answer**\n", "\n", @@ -232,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "919d876a", + "id": "627a2c6a", "metadata": { "tags": [ "solution" @@ -253,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "04052fa2", + "id": "f1a2713d", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -263,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "92d7e71b", + "id": "552b6283", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -272,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caa1354f", + "id": "111b7240", "metadata": {}, "outputs": [], "source": [ @@ -283,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "9c612ded", + "id": "83a83189", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -292,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "84814b12", + "id": "1e1c8808", "metadata": {}, "outputs": [], "source": [ @@ -308,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "08ceb75d", + "id": "2f7d08cc", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -317,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "54fff804", + "id": "4126900f", "metadata": {}, "outputs": [], "source": [ @@ -328,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "acb4fec9", + "id": "55655c98", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -338,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dec7dc7c", + "id": "07c7b4b8", "metadata": {}, "outputs": [], "source": [ @@ -354,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f1ed4bae", + "id": "8baf6fb2", "metadata": {}, "outputs": [], "source": [ @@ -376,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "067ac0b6", + "id": "77521105", "metadata": {}, "source": [ "

\n", @@ -387,8 +395,12 @@ }, { "cell_type": "markdown", - "id": "58836d17", - "metadata": {}, + "id": "e4518cef", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**1.4 Answer**\n", "\n", @@ -401,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "7771570d", + "id": "4d4944a2", "metadata": { "tags": [ "solution" @@ -431,7 +443,7 @@ }, { "cell_type": "markdown", - "id": "7f9e3f2e", + "id": "9afcad6f", "metadata": {}, "source": [ "

\n", @@ -442,8 +454,12 @@ }, { "cell_type": "markdown", - "id": "3a081d4b", - "metadata": {}, + "id": "c9b0e1a4", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**1.5 Answer:**\n", "\n", @@ -452,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "32f88963", + "id": "5f69c6a7", "metadata": { "tags": [ "solution" @@ -466,7 +482,7 @@ }, { "cell_type": "markdown", - "id": "75f5ffa9", + "id": "ff66c973", "metadata": {}, "source": [ "

\n", @@ -478,7 +494,7 @@ }, { "cell_type": "markdown", - "id": "d70b21ed", + "id": "672a75ce", "metadata": {}, "source": [ "

\n", @@ -495,7 +511,7 @@ }, { "cell_type": "markdown", - "id": "c2c7663f", + "id": "f53c38d0", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -506,7 +522,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5c57f055", + "id": "e92c0d27", "metadata": {}, "outputs": [], "source": [ @@ -520,7 +536,7 @@ }, { "cell_type": "markdown", - "id": "384472d8", + "id": "add969af", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -529,7 +545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "715aeca5", + "id": "5be59c75", "metadata": {}, "outputs": [], "source": [ @@ -554,7 +570,7 @@ }, { "cell_type": "markdown", - "id": "71d10d87", + "id": "19ac0693", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -563,7 +579,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0cc9327a", + "id": "d547978b", "metadata": {}, "outputs": [], "source": [ @@ -582,7 +598,7 @@ }, { "cell_type": "markdown", - "id": "01135447", + "id": "15ce488c", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -591,7 +607,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8e713742", + "id": "16c41727", "metadata": {}, "outputs": [], "source": [ @@ -619,7 +635,7 @@ }, { "cell_type": "markdown", - "id": "9add42e7", + "id": "9e961e8d", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -628,7 +644,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f5f46fb9", + "id": "23323b2b", "metadata": {}, "outputs": [], "source": [ @@ -642,7 +658,7 @@ }, { "cell_type": "markdown", - "id": "8d00e620", + "id": "89956be7", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -651,7 +667,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3825f837", + "id": "401c6b2b", "metadata": {}, "outputs": [], "source": [ @@ -684,7 +700,7 @@ }, { "cell_type": "markdown", - "id": "113d124c", + "id": "cc555a3d", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -693,7 +709,7 @@ { "cell_type": "code", "execution_count": null, - "id": "77dc7f01", + "id": "a24b84f2", "metadata": {}, "outputs": [], "source": [ @@ -708,7 +724,7 @@ }, { "cell_type": "markdown", - "id": "7bbb3294", + "id": "6df45ee1", "metadata": {}, "source": [ "

\n", @@ -719,8 +735,12 @@ }, { "cell_type": "markdown", - "id": "dc03ff76", - "metadata": {}, + "id": "acd105a8", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**2.1 Answer:**\n", "\n", @@ -729,7 +749,7 @@ }, { "cell_type": "markdown", - "id": "2ff54948", + "id": "e307549f", "metadata": { "tags": [ "solution" @@ -743,7 +763,7 @@ }, { "cell_type": "markdown", - "id": "e4a8142f", + "id": "7df63f8f", "metadata": {}, "source": [ "

\n", @@ -754,8 +774,12 @@ }, { "cell_type": "markdown", - "id": "08e6dbfb", - "metadata": {}, + "id": "5a2ff096", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**2.2 Answer:**\n", "\n", @@ -764,7 +788,7 @@ }, { "cell_type": "markdown", - "id": "9b88f2d0", + "id": "298e1f5b", "metadata": { "tags": [ "solution" @@ -778,7 +802,7 @@ }, { "cell_type": "markdown", - "id": "2e5a25be", + "id": "4271217f", "metadata": {}, "source": [ "

\n", @@ -789,8 +813,12 @@ }, { "cell_type": "markdown", - "id": "e5d581b7", - "metadata": {}, + "id": "1c22cfaf", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**2.3 Answer:**\n", "\n", @@ -799,7 +827,7 @@ }, { "cell_type": "markdown", - "id": "96f07515", + "id": "b8960216", "metadata": { "tags": [ "solution" @@ -813,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "e7f140c0", + "id": "b31868b6", "metadata": {}, "source": [ "

\n", @@ -825,7 +853,7 @@ }, { "cell_type": "markdown", - "id": "92f63826", + "id": "a3e49dae", "metadata": {}, "source": [ "

\n", @@ -840,7 +868,7 @@ }, { "cell_type": "markdown", - "id": "2373900f", + "id": "432049a6", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -853,7 +881,7 @@ { "cell_type": "code", "execution_count": null, - "id": "00e3d111", + "id": "0c931233", "metadata": {}, "outputs": [], "source": [ @@ -875,7 +903,7 @@ }, { "cell_type": "markdown", - "id": "5cb58b48", + "id": "258daf07", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -884,7 +912,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1286c116", + "id": "19167fa2", "metadata": {}, "outputs": [], "source": [ @@ -896,7 +924,7 @@ }, { "cell_type": "markdown", - "id": "607130a5", + "id": "01002da0", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -905,7 +933,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cff3b86a", + "id": "af94666a", "metadata": {}, "outputs": [], "source": [ @@ -959,14 +987,14 @@ { "cell_type": "code", "execution_count": null, - "id": "02dc66b6", + "id": "f8723f92", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", - "id": "da283b12", + "id": "a18b0900", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -975,7 +1003,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1a7ca6fe", + "id": "5caa855a", "metadata": {}, "outputs": [], "source": [ @@ -987,7 +1015,7 @@ }, { "cell_type": "markdown", - "id": "2259d225", + "id": "efa46250", "metadata": {}, "source": [ "

\n", @@ -998,8 +1026,12 @@ }, { "cell_type": "markdown", - "id": "af417b0a", - "metadata": {}, + "id": "68ae8876", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**3.1 Answer:**\n", "\n", @@ -1008,7 +1040,7 @@ }, { "cell_type": "markdown", - "id": "879549e3", + "id": "8c56472c", "metadata": { "tags": [ "solution" @@ -1023,7 +1055,7 @@ }, { "cell_type": "markdown", - "id": "ea19688f", + "id": "1cfcffe1", "metadata": {}, "source": [ "

\n", @@ -1034,8 +1066,12 @@ }, { "cell_type": "markdown", - "id": "4ed22f19", - "metadata": {}, + "id": "ff390801", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**3.2 Answer**\n", "\n", @@ -1044,7 +1080,7 @@ }, { "cell_type": "markdown", - "id": "cc29fc2c", + "id": "661db703", "metadata": { "tags": [ "solution" @@ -1058,7 +1094,7 @@ }, { "cell_type": "markdown", - "id": "82c8c136", + "id": "7d811061", "metadata": {}, "source": [ "

\n", @@ -1069,8 +1105,12 @@ }, { "cell_type": "markdown", - "id": "f932d453", - "metadata": {}, + "id": "dab1cac5", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**3.3 Answer:**\n", "\n", @@ -1079,7 +1119,7 @@ }, { "cell_type": "markdown", - "id": "9c42945b", + "id": "224c731a", "metadata": { "tags": [ "solution" @@ -1096,7 +1136,7 @@ }, { "cell_type": "markdown", - "id": "33f1696c", + "id": "2eb81703", "metadata": {}, "source": [ "

\n", @@ -1107,8 +1147,12 @@ }, { "cell_type": "markdown", - "id": "9241c879", - "metadata": {}, + "id": "659a49e2", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**3.4 Answer:**\n", "\n", @@ -1117,7 +1161,7 @@ }, { "cell_type": "markdown", - "id": "da328962", + "id": "2dd47d03", "metadata": { "tags": [ "solution" @@ -1137,7 +1181,7 @@ }, { "cell_type": "markdown", - "id": "38cec29f", + "id": "f4e2645d", "metadata": {}, "source": [ "

\n", @@ -1149,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "095add84", + "id": "eaa2aca7", "metadata": {}, "source": [ "

\n", @@ -1164,7 +1208,7 @@ }, { "cell_type": "markdown", - "id": "c95f054c", + "id": "f50d6106", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1173,7 +1217,7 @@ }, { "cell_type": "markdown", - "id": "5af9ad88", + "id": "4fa74a0a", "metadata": {}, "source": [ "\n", @@ -1183,7 +1227,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e5b50913", + "id": "ba4da828", "metadata": {}, "outputs": [], "source": [ @@ -1216,7 +1260,7 @@ }, { "cell_type": "markdown", - "id": "851dfcc4", + "id": "47cb109a", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1225,7 +1269,7 @@ { "cell_type": "code", "execution_count": null, - "id": "21c16b69", + "id": "178a39d7", "metadata": {}, "outputs": [], "source": [ @@ -1264,7 +1308,7 @@ }, { "cell_type": "markdown", - "id": "46892e8a", + "id": "12f406b0", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1275,7 +1319,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7e458c2e", + "id": "0a1d6560", "metadata": {}, "outputs": [], "source": [ @@ -1285,7 +1329,7 @@ }, { "cell_type": "markdown", - "id": "bd939031", + "id": "fe09a285", "metadata": {}, "source": [ "

\n", @@ -1296,8 +1340,12 @@ }, { "cell_type": "markdown", - "id": "10f375ad", - "metadata": {}, + "id": "b42d7ee6", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**4.1 Answer:**\n", "\n", @@ -1306,7 +1354,7 @@ }, { "cell_type": "markdown", - "id": "e82ccc2d", + "id": "9f9ac1eb", "metadata": { "tags": [ "solution" @@ -1321,7 +1369,7 @@ }, { "cell_type": "markdown", - "id": "fc29b799", + "id": "315b740a", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1330,7 +1378,7 @@ { "cell_type": "code", "execution_count": null, - "id": "50bdd6f1", + "id": "0c715c49", "metadata": {}, "outputs": [], "source": [ @@ -1340,7 +1388,7 @@ }, { "cell_type": "markdown", - "id": "03d55adf", + "id": "8db82f66", "metadata": {}, "source": [ "

\n", @@ -1351,8 +1399,12 @@ }, { "cell_type": "markdown", - "id": "5b1f5921", - "metadata": {}, + "id": "bf46888b", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**4.2 Answer:**\n", "\n", @@ -1361,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "c67e4497", + "id": "36ef9e63", "metadata": { "tags": [ "solution" @@ -1379,7 +1431,7 @@ }, { "cell_type": "markdown", - "id": "b6deb133", + "id": "64f48898", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1388,7 +1440,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ff3ad936", + "id": "824a2128", "metadata": {}, "outputs": [], "source": [ @@ -1400,7 +1452,7 @@ }, { "cell_type": "markdown", - "id": "e9b71f00", + "id": "30db6d44", "metadata": {}, "source": [ "

\n", @@ -1411,8 +1463,12 @@ }, { "cell_type": "markdown", - "id": "1a1ef215", - "metadata": {}, + "id": "74f060ec", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**4.3 Answer:**\n", "\n", @@ -1421,7 +1477,7 @@ }, { "cell_type": "markdown", - "id": "2b9b91df", + "id": "c7272ad8", "metadata": { "tags": [ "solution" @@ -1438,7 +1494,7 @@ }, { "cell_type": "markdown", - "id": "40afb7bf", + "id": "078b8fdc", "metadata": {}, "source": [ "

\n", @@ -1449,8 +1505,12 @@ }, { "cell_type": "markdown", - "id": "430bc487", - "metadata": {}, + "id": "9852a30d", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**4.4 Answer:**\n", "\n", @@ -1459,7 +1519,7 @@ }, { "cell_type": "markdown", - "id": "5d03a39f", + "id": "532aa958", "metadata": { "tags": [ "solution" @@ -1475,7 +1535,7 @@ }, { "cell_type": "markdown", - "id": "53903eb9", + "id": "2e3f0338", "metadata": {}, "source": [ "

\n", @@ -1488,7 +1548,7 @@ }, { "cell_type": "markdown", - "id": "289ae5b8", + "id": "f8a4ea81", "metadata": {}, "source": [ "

\n", @@ -1502,7 +1562,7 @@ }, { "cell_type": "markdown", - "id": "0fb49b82", + "id": "2c98ff21", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1514,7 +1574,7 @@ }, { "cell_type": "markdown", - "id": "ffef525a", + "id": "a20179a5", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1523,7 +1583,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c30b952", + "id": "afc8f426", "metadata": {}, "outputs": [], "source": [ @@ -1538,7 +1598,7 @@ }, { "cell_type": "markdown", - "id": "a80f6331", + "id": "d16af11f", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1547,7 +1607,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1fab7a3b", + "id": "e0956137", "metadata": {}, "outputs": [], "source": [ @@ -1576,7 +1636,7 @@ }, { "cell_type": "markdown", - "id": "82e3d8ca", + "id": "3d7d729d", "metadata": {}, "source": [ "### UNet model\n", @@ -1586,7 +1646,7 @@ }, { "cell_type": "markdown", - "id": "1b5676c1", + "id": "f128e0d5", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1595,7 +1655,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73915d29", + "id": "5c6743ed", "metadata": {}, "outputs": [], "source": [ @@ -1643,7 +1703,7 @@ }, { "cell_type": "markdown", - "id": "9c8bcba9", + "id": "dcfe5981", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1652,7 +1712,7 @@ { "cell_type": "code", "execution_count": null, - "id": "35365339", + "id": "94fe0b9d", "metadata": {}, "outputs": [], "source": [ @@ -1690,7 +1750,7 @@ }, { "cell_type": "markdown", - "id": "6cb2ac9d", + "id": "cb5be242", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1699,7 +1759,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6e355db2", + "id": "2cd4f305", "metadata": {}, "outputs": [], "source": [ @@ -1710,7 +1770,7 @@ }, { "cell_type": "markdown", - "id": "3564b3ea", + "id": "c8addd07", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1719,7 +1779,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dfd4eef7", + "id": "d32a9664", "metadata": {}, "outputs": [], "source": [ @@ -1733,7 +1793,7 @@ }, { "cell_type": "markdown", - "id": "f06e0944", + "id": "d1c1b2a8", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1744,7 +1804,7 @@ { "cell_type": "code", "execution_count": null, - "id": "67a29006", + "id": "bb313fa5", "metadata": {}, "outputs": [], "source": [ @@ -1759,7 +1819,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2b02e3f4", + "id": "57d4f69e", "metadata": {}, "outputs": [], "source": [] @@ -1767,7 +1827,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0ab7202", + "id": "1c72a1cf", "metadata": {}, "outputs": [], "source": [ @@ -1796,7 +1856,7 @@ }, { "cell_type": "markdown", - "id": "93d7f562", + "id": "35109e13", "metadata": {}, "source": [ "

\n", @@ -1807,8 +1867,12 @@ }, { "cell_type": "markdown", - "id": "42672a70", - "metadata": {}, + "id": "a39924b6", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**5.1 Answer:**\n", "\n", @@ -1817,7 +1881,7 @@ }, { "cell_type": "markdown", - "id": "9ded3ea2", + "id": "4b55fbbb", "metadata": { "tags": [ "solution" @@ -1831,7 +1895,7 @@ }, { "cell_type": "markdown", - "id": "d580d3c3", + "id": "b7eb0224", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1841,7 +1905,7 @@ }, { "cell_type": "markdown", - "id": "36e71a10", + "id": "499d0ceb", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1852,7 +1916,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bbefda7f", + "id": "75b8cace", "metadata": {}, "outputs": [], "source": [ @@ -1873,7 +1937,7 @@ }, { "cell_type": "markdown", - "id": "265dbeb6", + "id": "5896d150", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1882,7 +1946,7 @@ { "cell_type": "code", "execution_count": null, - "id": "336f9148", + "id": "952fff80", "metadata": {}, "outputs": [], "source": [ @@ -1892,7 +1956,7 @@ }, { "cell_type": "markdown", - "id": "fbfa0eff", + "id": "43c36e17", "metadata": {}, "source": [ "

\n", @@ -1903,8 +1967,12 @@ }, { "cell_type": "markdown", - "id": "6006a3c0", - "metadata": {}, + "id": "7f726da8", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**5.2 Answer:**\n", "\n", @@ -1913,7 +1981,7 @@ }, { "cell_type": "markdown", - "id": "c82e741e", + "id": "109c4d48", "metadata": { "tags": [ "solution" @@ -1927,7 +1995,7 @@ }, { "cell_type": "markdown", - "id": "99568021", + "id": "ed1de42c", "metadata": {}, "source": [ "

\n", @@ -1938,8 +2006,12 @@ }, { "cell_type": "markdown", - "id": "2e946390", - "metadata": {}, + "id": "5d8c4460", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**5.3 Answer:**\n", "\n", @@ -1948,7 +2020,7 @@ }, { "cell_type": "markdown", - "id": "f4a037d8", + "id": "c6328745", "metadata": { "tags": [ "solution" @@ -1963,7 +2035,7 @@ }, { "cell_type": "markdown", - "id": "28e78d4b", + "id": "ea481c7f", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1974,7 +2046,7 @@ { "cell_type": "code", "execution_count": null, - "id": "96d08a22", + "id": "bfff2a4b", "metadata": {}, "outputs": [], "source": [ @@ -2011,7 +2083,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dc708995", + "id": "fc58e649", "metadata": {}, "outputs": [], "source": [ @@ -2022,7 +2094,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c8605be", + "id": "62ee68b5", "metadata": {}, "outputs": [], "source": [ @@ -2032,7 +2104,7 @@ }, { "cell_type": "markdown", - "id": "70371b8a", + "id": "55bcf106", "metadata": {}, "source": [ "

\n", @@ -2043,19 +2115,17 @@ }, { "cell_type": "markdown", - "id": "3c601a00", - "metadata": {}, + "id": "128e111c", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**5.4 Answer:**\n", "\n", - "The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable)." - ] - }, - { - "cell_type": "markdown", - "id": "6c40f853", - "metadata": {}, - "source": [ + "The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable).\n", + "\n", "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", "\n", "We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below)" @@ -2064,7 +2134,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bfdf1d22", + "id": "27e11ee9", "metadata": {}, "outputs": [], "source": [ @@ -2101,7 +2171,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e7136f16", + "id": "73d18976", "metadata": {}, "outputs": [], "source": [ @@ -2112,7 +2182,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a7f0ac83", + "id": "4f304e41", "metadata": {}, "outputs": [], "source": [ @@ -2122,7 +2192,7 @@ }, { "cell_type": "markdown", - "id": "3182b80b", + "id": "3f3107f0", "metadata": {}, "source": [ "

\n", @@ -2133,32 +2203,24 @@ }, { "cell_type": "markdown", - "id": "fcd1c1bb", - "metadata": {}, + "id": "203bdd89", + "metadata": { + "tags": [ + "solution" + ] + }, "source": [ "**5.5 Answer:**\n", "\n", - "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets." - ] - }, - { - "cell_type": "markdown", - "id": "439f1c11", - "metadata": {}, - "source": [ + "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets.\n", + "\n", "

\n", " Checkpoint 5

\n", "
    \n", " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", "
\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "b00b8e8d", - "metadata": {}, - "source": [ + "

\n", + "\n", "

\n", " Bonus Questions

\n", "
    \n", From 9431399f2c1d02076286212ccedfcee67043e51e Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 18:02:28 +0100 Subject: [PATCH 24/51] Fix section numbering issue --- solution.py | 16 ++++++---------- 1 file changed, 6 insertions(+), 10 deletions(-) diff --git a/solution.py b/solution.py index 0d35de2..a855f5a 100644 --- a/solution.py +++ b/solution.py @@ -206,12 +206,12 @@ plt.show() #

    -# Task 1.4:

    +# Task 1.3:

# Think of a realistic example of such a corruption that would affect only some classes of data. If you notice the differences between classes, could you remove it? How? #
# + [markdown] tags=["solution"] -# **1.4 Answer** +# **1.3 Answer** # # A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact. # @@ -220,7 +220,7 @@ # But prevention remains the most effective way to produce high quality datasets. # + [markdown] tags=["solution"] -# **1.4 Answer from 2023 Students** +# **1.3 Answer from 2023 Students** # # Global Corruptions # - Different sample categories on different days: @@ -238,25 +238,21 @@ # Prevention is easer than fixing after generation! # - PCA on metadata <3 to help detect such issues # - Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc) -# -# -# - #

-# Task 1.5:

+# Task 1.4:

# Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset? #
# + [markdown] tags=["solution"] -# **1.5 Answer:** +# **1.4 Answer:** # # The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying. # + [markdown] tags=["solution"] -# **1.5 Answer from 2023 Students** +# **1.4 Answer from 2023 Students** # # We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! -# - #

# Checkpoint 1

From 1b1713e65470cf407111eace9ff4f6953106c2c4 Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 17:03:18 +0000 Subject: [PATCH 25/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 272 ++++++++++++++++---------------------- solution.ipynb | 347 +++++++++++++++++++++++-------------------------- 2 files changed, 272 insertions(+), 347 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 427928c..a8e43fb 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "e2b2f8e5", + "id": "b4334260", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "1486e0f6", + "id": "8f725b2e", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "b16d4ecd", + "id": "d7e25385", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "71b6f22f", + "id": "4bb98583", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "55500021", + "id": "6187b53f", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "709d7035", + "id": "06e04dcf", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "1be17f2c", + "id": "7ec8c3e8", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "858af61f", + "id": "854e34f7", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5fabeee1", + "id": "59cc29f7", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "aab42d3b", + "id": "57297c7c", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1b0a0e10", + "id": "8cfbd299", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0dd3903e", + "id": "eaf876ba", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "0c2ae1a7", + "id": "e076db7c", "metadata": {}, "source": [ "

\n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "5465d561", + "id": "2f3d78ea", "metadata": {}, "source": [ "

\n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "f1a2713d", + "id": "bbb280f6", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "552b6283", + "id": "9ffdac98", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "111b7240", + "id": "384c72fc", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "83a83189", + "id": "77aa5f6a", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1e1c8808", + "id": "86903ee7", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "2f7d08cc", + "id": "0825d9f3", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4126900f", + "id": "8689bc74", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "55655c98", + "id": "9108298a", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "07c7b4b8", + "id": "f0e96660", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8baf6fb2", + "id": "34f7d462", "metadata": {}, "outputs": [], "source": [ @@ -317,69 +317,19 @@ }, { "cell_type": "markdown", - "id": "77521105", + "id": "4d2ac1a6", "metadata": {}, "source": [ "

\n", - "Task 1.4:

\n", + "Task 1.3:

\n", "Think of a realistic example of such a corruption that would affect only some classes of data. If you notice the differences between classes, could you remove it? How?\n", "
" ] }, - { - "cell_type": "markdown", - "id": "9afcad6f", - "metadata": {}, - "source": [ - "

\n", - "Task 1.5:

\n", - "Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset?\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "ff66c973", - "metadata": {}, - "source": [ - "

\n", - " Checkpoint 1

\n", - "\n", - "Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions!\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "672a75ce", - "metadata": {}, - "source": [ - "

\n", - " Bonus Questions:

\n", - " Note that we only added the white dot to the images of 7s and the grid to images of 4s, not all classes.\n", - "
    \n", - "
  1. Consider a dataset with white dots on images of all digits: let's call it the all-dots data. How different is this from the original dataset? Are the classes more or less distinct from each other?
    2. \n", - "
  2. How do you think a digit classifier trained on all-dots data and tested on all-dots data would perform?
    3. \n", - "
  3. Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
    4. \n", - "
\n", - "If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section.\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "f53c38d0", - "metadata": {}, - "source": [ - "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", - "\n", - "From Part 1, we have a clean dataset and a dataset that has been tainted with effects that simulate local and global effects that could happen in real collection scenarios. Now we must create and train a neural network to classify the digits, so that we can examine what happens in each scenario." - ] - }, { "cell_type": "code", "execution_count": null, - "id": "e92c0d27", + "id": "ad194579", "metadata": {}, "outputs": [], "source": [ @@ -393,7 +343,7 @@ }, { "cell_type": "markdown", - "id": "add969af", + "id": "34494aae", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -402,7 +352,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5be59c75", + "id": "62d13f5a", "metadata": {}, "outputs": [], "source": [ @@ -427,7 +377,7 @@ }, { "cell_type": "markdown", - "id": "19ac0693", + "id": "32836f56", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -436,7 +386,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d547978b", + "id": "47cede43", "metadata": {}, "outputs": [], "source": [ @@ -455,7 +405,7 @@ }, { "cell_type": "markdown", - "id": "15ce488c", + "id": "302f2a6d", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -464,7 +414,7 @@ { "cell_type": "code", "execution_count": null, - "id": "16c41727", + "id": "5e83008c", "metadata": {}, "outputs": [], "source": [ @@ -492,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "9e961e8d", + "id": "3ffab0a3", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -501,7 +451,7 @@ { "cell_type": "code", "execution_count": null, - "id": "23323b2b", + "id": "45136375", "metadata": {}, "outputs": [], "source": [ @@ -515,7 +465,7 @@ }, { "cell_type": "markdown", - "id": "89956be7", + "id": "3113e61e", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -524,7 +474,7 @@ { "cell_type": "code", "execution_count": null, - "id": "401c6b2b", + "id": "f91b95fa", "metadata": {}, "outputs": [], "source": [ @@ -557,7 +507,7 @@ }, { "cell_type": "markdown", - "id": "cc555a3d", + "id": "0f80bd8c", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -566,7 +516,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a24b84f2", + "id": "f63734d6", "metadata": {}, "outputs": [], "source": [ @@ -581,7 +531,7 @@ }, { "cell_type": "markdown", - "id": "6df45ee1", + "id": "364fca1b", "metadata": {}, "source": [ "

\n", @@ -592,7 +542,7 @@ }, { "cell_type": "markdown", - "id": "7df63f8f", + "id": "5eecc109", "metadata": {}, "source": [ "

\n", @@ -603,7 +553,7 @@ }, { "cell_type": "markdown", - "id": "4271217f", + "id": "b944f271", "metadata": {}, "source": [ "

\n", @@ -614,7 +564,7 @@ }, { "cell_type": "markdown", - "id": "b31868b6", + "id": "799ad0f5", "metadata": {}, "source": [ "

\n", @@ -626,7 +576,7 @@ }, { "cell_type": "markdown", - "id": "a3e49dae", + "id": "167915f5", "metadata": {}, "source": [ "

\n", @@ -641,7 +591,7 @@ }, { "cell_type": "markdown", - "id": "432049a6", + "id": "43e11cb6", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -654,7 +604,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c931233", + "id": "d5c1bc11", "metadata": {}, "outputs": [], "source": [ @@ -676,7 +626,7 @@ }, { "cell_type": "markdown", - "id": "258daf07", + "id": "4c090e2b", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -685,7 +635,7 @@ { "cell_type": "code", "execution_count": null, - "id": "19167fa2", + "id": "24511ead", "metadata": {}, "outputs": [], "source": [ @@ -697,7 +647,7 @@ }, { "cell_type": "markdown", - "id": "01002da0", + "id": "b0af1b64", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -706,7 +656,7 @@ { "cell_type": "code", "execution_count": null, - "id": "af94666a", + "id": "89d0d283", "metadata": {}, "outputs": [], "source": [ @@ -760,14 +710,14 @@ { "cell_type": "code", "execution_count": null, - "id": "f8723f92", + "id": "a6953785", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", - "id": "a18b0900", + "id": "91f021ac", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -776,7 +726,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5caa855a", + "id": "2d86342f", "metadata": {}, "outputs": [], "source": [ @@ -788,7 +738,7 @@ }, { "cell_type": "markdown", - "id": "efa46250", + "id": "ee137028", "metadata": {}, "source": [ "

\n", @@ -799,7 +749,7 @@ }, { "cell_type": "markdown", - "id": "1cfcffe1", + "id": "5bfcdaba", "metadata": {}, "source": [ "

\n", @@ -810,7 +760,7 @@ }, { "cell_type": "markdown", - "id": "7d811061", + "id": "f343e368", "metadata": {}, "source": [ "

\n", @@ -821,7 +771,7 @@ }, { "cell_type": "markdown", - "id": "2eb81703", + "id": "3cfcf043", "metadata": {}, "source": [ "

\n", @@ -832,7 +782,7 @@ }, { "cell_type": "markdown", - "id": "f4e2645d", + "id": "f279f3fd", "metadata": {}, "source": [ "

\n", @@ -844,7 +794,7 @@ }, { "cell_type": "markdown", - "id": "eaa2aca7", + "id": "807bbaaa", "metadata": {}, "source": [ "

\n", @@ -859,7 +809,7 @@ }, { "cell_type": "markdown", - "id": "f50d6106", + "id": "6c8d3e90", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -868,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "4fa74a0a", + "id": "9c49ffc0", "metadata": {}, "source": [ "\n", @@ -878,7 +828,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ba4da828", + "id": "3dc25f28", "metadata": {}, "outputs": [], "source": [ @@ -911,7 +861,7 @@ }, { "cell_type": "markdown", - "id": "47cb109a", + "id": "4fad4337", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -920,7 +870,7 @@ { "cell_type": "code", "execution_count": null, - "id": "178a39d7", + "id": "4e2951aa", "metadata": {}, "outputs": [], "source": [ @@ -959,7 +909,7 @@ }, { "cell_type": "markdown", - "id": "12f406b0", + "id": "e4ecce34", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -970,7 +920,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0a1d6560", + "id": "a9b89e6e", "metadata": {}, "outputs": [], "source": [ @@ -980,7 +930,7 @@ }, { "cell_type": "markdown", - "id": "fe09a285", + "id": "11539e2b", "metadata": {}, "source": [ "

\n", @@ -991,7 +941,7 @@ }, { "cell_type": "markdown", - "id": "315b740a", + "id": "4dcea669", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1000,7 +950,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c715c49", + "id": "10541614", "metadata": {}, "outputs": [], "source": [ @@ -1010,7 +960,7 @@ }, { "cell_type": "markdown", - "id": "8db82f66", + "id": "f89c76cd", "metadata": {}, "source": [ "

\n", @@ -1021,7 +971,7 @@ }, { "cell_type": "markdown", - "id": "64f48898", + "id": "4500e51c", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1030,7 +980,7 @@ { "cell_type": "code", "execution_count": null, - "id": "824a2128", + "id": "55317ce2", "metadata": {}, "outputs": [], "source": [ @@ -1042,7 +992,7 @@ }, { "cell_type": "markdown", - "id": "30db6d44", + "id": "bf796afd", "metadata": {}, "source": [ "

\n", @@ -1053,7 +1003,7 @@ }, { "cell_type": "markdown", - "id": "078b8fdc", + "id": "4ae086b6", "metadata": {}, "source": [ "

\n", @@ -1064,7 +1014,7 @@ }, { "cell_type": "markdown", - "id": "2e3f0338", + "id": "15cb1b84", "metadata": {}, "source": [ "

\n", @@ -1077,7 +1027,7 @@ }, { "cell_type": "markdown", - "id": "f8a4ea81", + "id": "4b28a610", "metadata": {}, "source": [ "

\n", @@ -1091,7 +1041,7 @@ }, { "cell_type": "markdown", - "id": "2c98ff21", + "id": "607b548b", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1103,7 +1053,7 @@ }, { "cell_type": "markdown", - "id": "a20179a5", + "id": "b70470d4", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1112,7 +1062,7 @@ { "cell_type": "code", "execution_count": null, - "id": "afc8f426", + "id": "bd118ab2", "metadata": {}, "outputs": [], "source": [ @@ -1127,7 +1077,7 @@ }, { "cell_type": "markdown", - "id": "d16af11f", + "id": "9e50e11f", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1136,7 +1086,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0956137", + "id": "847a99f3", "metadata": {}, "outputs": [], "source": [ @@ -1165,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "3d7d729d", + "id": "6ad2d555", "metadata": {}, "source": [ "### UNet model\n", @@ -1175,7 +1125,7 @@ }, { "cell_type": "markdown", - "id": "f128e0d5", + "id": "832d9a0e", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1184,7 +1134,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5c6743ed", + "id": "fcb74929", "metadata": {}, "outputs": [], "source": [ @@ -1232,7 +1182,7 @@ }, { "cell_type": "markdown", - "id": "dcfe5981", + "id": "b88e84dc", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1241,7 +1191,7 @@ { "cell_type": "code", "execution_count": null, - "id": "94fe0b9d", + "id": "bdbf76e8", "metadata": {}, "outputs": [], "source": [ @@ -1279,7 +1229,7 @@ }, { "cell_type": "markdown", - "id": "cb5be242", + "id": "5556d195", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1288,7 +1238,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2cd4f305", + "id": "bc11c7d8", "metadata": {}, "outputs": [], "source": [ @@ -1299,7 +1249,7 @@ }, { "cell_type": "markdown", - "id": "c8addd07", + "id": "11098057", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1308,7 +1258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d32a9664", + "id": "f68adba3", "metadata": {}, "outputs": [], "source": [ @@ -1322,7 +1272,7 @@ }, { "cell_type": "markdown", - "id": "d1c1b2a8", + "id": "c4b12017", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1333,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bb313fa5", + "id": "305a367d", "metadata": {}, "outputs": [], "source": [ @@ -1348,7 +1298,7 @@ { "cell_type": "code", "execution_count": null, - "id": "57d4f69e", + "id": "57262965", "metadata": {}, "outputs": [], "source": [] @@ -1356,7 +1306,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1c72a1cf", + "id": "98dcd5b1", "metadata": {}, "outputs": [], "source": [ @@ -1385,7 +1335,7 @@ }, { "cell_type": "markdown", - "id": "35109e13", + "id": "076d4eff", "metadata": {}, "source": [ "

\n", @@ -1396,7 +1346,7 @@ }, { "cell_type": "markdown", - "id": "b7eb0224", + "id": "85845f84", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1406,7 +1356,7 @@ }, { "cell_type": "markdown", - "id": "499d0ceb", + "id": "d5650b2d", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1417,7 +1367,7 @@ { "cell_type": "code", "execution_count": null, - "id": "75b8cace", + "id": "f8ddc55f", "metadata": {}, "outputs": [], "source": [ @@ -1438,7 +1388,7 @@ }, { "cell_type": "markdown", - "id": "5896d150", + "id": "76cb89f4", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1447,7 +1397,7 @@ { "cell_type": "code", "execution_count": null, - "id": "952fff80", + "id": "9a3d256b", "metadata": {}, "outputs": [], "source": [ @@ -1457,7 +1407,7 @@ }, { "cell_type": "markdown", - "id": "43c36e17", + "id": "4da65639", "metadata": {}, "source": [ "

\n", @@ -1468,7 +1418,7 @@ }, { "cell_type": "markdown", - "id": "ed1de42c", + "id": "87bec030", "metadata": {}, "source": [ "

\n", @@ -1479,7 +1429,7 @@ }, { "cell_type": "markdown", - "id": "ea481c7f", + "id": "474a797a", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1490,7 +1440,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bfff2a4b", + "id": "780d66d6", "metadata": {}, "outputs": [], "source": [ @@ -1527,7 +1477,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fc58e649", + "id": "fb8bc178", "metadata": {}, "outputs": [], "source": [ @@ -1538,7 +1488,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62ee68b5", + "id": "37d6f25d", "metadata": {}, "outputs": [], "source": [ @@ -1548,7 +1498,7 @@ }, { "cell_type": "markdown", - "id": "55bcf106", + "id": "322c7b74", "metadata": {}, "source": [ "

\n", @@ -1560,7 +1510,7 @@ { "cell_type": "code", "execution_count": null, - "id": "27e11ee9", + "id": "bae7c6c1", "metadata": {}, "outputs": [], "source": [ @@ -1597,7 +1547,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73d18976", + "id": "d8b38e2e", "metadata": {}, "outputs": [], "source": [ @@ -1608,7 +1558,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4f304e41", + "id": "2f9802b2", "metadata": {}, "outputs": [], "source": [ @@ -1618,7 +1568,7 @@ }, { "cell_type": "markdown", - "id": "3f3107f0", + "id": "06a2a23c", "metadata": {}, "source": [ "

\n", diff --git a/solution.ipynb b/solution.ipynb index 2c7c8d7..42d4913 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "e2b2f8e5", + "id": "b4334260", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "1486e0f6", + "id": "8f725b2e", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "b16d4ecd", + "id": "d7e25385", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "71b6f22f", + "id": "4bb98583", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "55500021", + "id": "6187b53f", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "709d7035", + "id": "06e04dcf", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "1be17f2c", + "id": "7ec8c3e8", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "858af61f", + "id": "854e34f7", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5fabeee1", + "id": "59cc29f7", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "aab42d3b", + "id": "57297c7c", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1b0a0e10", + "id": "8cfbd299", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0dd3903e", + "id": "eaf876ba", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "0c2ae1a7", + "id": "e076db7c", "metadata": {}, "source": [ "

\n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "90f63ace", + "id": "b07b8240", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "12341439", + "id": "e294c374", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "5465d561", + "id": "2f3d78ea", "metadata": {}, "source": [ "

\n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "9c849962", + "id": "689ce427", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "627a2c6a", + "id": "c393c4e0", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "f1a2713d", + "id": "bbb280f6", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "552b6283", + "id": "9ffdac98", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "111b7240", + "id": "384c72fc", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "83a83189", + "id": "77aa5f6a", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1e1c8808", + "id": "86903ee7", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "2f7d08cc", + "id": "0825d9f3", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4126900f", + "id": "8689bc74", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "55655c98", + "id": "9108298a", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "07c7b4b8", + "id": "f0e96660", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8baf6fb2", + "id": "34f7d462", "metadata": {}, "outputs": [], "source": [ @@ -384,25 +384,25 @@ }, { "cell_type": "markdown", - "id": "77521105", + "id": "4d2ac1a6", "metadata": {}, "source": [ "

\n", - "Task 1.4:

\n", + "Task 1.3:

\n", "Think of a realistic example of such a corruption that would affect only some classes of data. If you notice the differences between classes, could you remove it? How?\n", "
" ] }, { "cell_type": "markdown", - "id": "e4518cef", + "id": "592ae7b6", "metadata": { "tags": [ "solution" ] }, "source": [ - "**1.4 Answer**\n", + "**1.3 Answer**\n", "\n", "A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact.\n", "\n", @@ -413,14 +413,14 @@ }, { "cell_type": "markdown", - "id": "4d4944a2", + "id": "34e274fd", "metadata": { "tags": [ "solution" ] }, "source": [ - "**1.4 Answer from 2023 Students**\n", + "**1.3 Answer from 2023 Students**\n", "\n", "Global Corruptions\n", "- Different sample categories on different days:\n", @@ -438,65 +438,46 @@ "Prevention is easer than fixing after generation!\n", "- PCA on metadata <3 to help detect such issues\n", "- Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "9afcad6f", - "metadata": {}, - "source": [ + "\n", "

\n", - "Task 1.5:

\n", + "Task 1.4:

\n", "Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset?\n", "
" ] }, { "cell_type": "markdown", - "id": "c9b0e1a4", + "id": "967cebcc", "metadata": { "tags": [ "solution" ] }, "source": [ - "**1.5 Answer:**\n", + "**1.4 Answer:**\n", "\n", "The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying." ] }, { "cell_type": "markdown", - "id": "5f69c6a7", + "id": "93b33424", "metadata": { "tags": [ "solution" ] }, "source": [ - "**1.5 Answer from 2023 Students**\n", + "**1.4 Answer from 2023 Students**\n", + "\n", + "We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! \n", "\n", - "We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! " - ] - }, - { - "cell_type": "markdown", - "id": "ff66c973", - "metadata": {}, - "source": [ "

\n", " Checkpoint 1

\n", "\n", "Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions!\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "672a75ce", - "metadata": {}, - "source": [ + "

\n", + "\n", "

\n", " Bonus Questions:

\n", " Note that we only added the white dot to the images of 7s and the grid to images of 4s, not all classes.\n", @@ -506,14 +487,8 @@ "
  • Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
    • \n", " \n", "If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section.\n", - "
    " - ] - }, - { - "cell_type": "markdown", - "id": "f53c38d0", - "metadata": {}, - "source": [ + "

    \n", + "\n", "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", "\n", "From Part 1, we have a clean dataset and a dataset that has been tainted with effects that simulate local and global effects that could happen in real collection scenarios. Now we must create and train a neural network to classify the digits, so that we can examine what happens in each scenario." @@ -522,7 +497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e92c0d27", + "id": "ad194579", "metadata": {}, "outputs": [], "source": [ @@ -536,7 +511,7 @@ }, { "cell_type": "markdown", - "id": "add969af", + "id": "34494aae", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -545,7 +520,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5be59c75", + "id": "62d13f5a", "metadata": {}, "outputs": [], "source": [ @@ -570,7 +545,7 @@ }, { "cell_type": "markdown", - "id": "19ac0693", + "id": "32836f56", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -579,7 +554,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d547978b", + "id": "47cede43", "metadata": {}, "outputs": [], "source": [ @@ -598,7 +573,7 @@ }, { "cell_type": "markdown", - "id": "15ce488c", + "id": "302f2a6d", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -607,7 +582,7 @@ { "cell_type": "code", "execution_count": null, - "id": "16c41727", + "id": "5e83008c", "metadata": {}, "outputs": [], "source": [ @@ -635,7 +610,7 @@ }, { "cell_type": "markdown", - "id": "9e961e8d", + "id": "3ffab0a3", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -644,7 +619,7 @@ { "cell_type": "code", "execution_count": null, - "id": "23323b2b", + "id": "45136375", "metadata": {}, "outputs": [], "source": [ @@ -658,7 +633,7 @@ }, { "cell_type": "markdown", - "id": "89956be7", + "id": "3113e61e", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -667,7 +642,7 @@ { "cell_type": "code", "execution_count": null, - "id": "401c6b2b", + "id": "f91b95fa", "metadata": {}, "outputs": [], "source": [ @@ -700,7 +675,7 @@ }, { "cell_type": "markdown", - "id": "cc555a3d", + "id": "0f80bd8c", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -709,7 +684,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a24b84f2", + "id": "f63734d6", "metadata": {}, "outputs": [], "source": [ @@ -724,7 +699,7 @@ }, { "cell_type": "markdown", - "id": "6df45ee1", + "id": "364fca1b", "metadata": {}, "source": [ "

    \n", @@ -735,7 +710,7 @@ }, { "cell_type": "markdown", - "id": "acd105a8", + "id": "03545b8e", "metadata": { "tags": [ "solution" @@ -749,7 +724,7 @@ }, { "cell_type": "markdown", - "id": "e307549f", + "id": "dd2d421f", "metadata": { "tags": [ "solution" @@ -763,7 +738,7 @@ }, { "cell_type": "markdown", - "id": "7df63f8f", + "id": "5eecc109", "metadata": {}, "source": [ "

    \n", @@ -774,7 +749,7 @@ }, { "cell_type": "markdown", - "id": "5a2ff096", + "id": "26a25e13", "metadata": { "tags": [ "solution" @@ -788,7 +763,7 @@ }, { "cell_type": "markdown", - "id": "298e1f5b", + "id": "1a82f841", "metadata": { "tags": [ "solution" @@ -802,7 +777,7 @@ }, { "cell_type": "markdown", - "id": "4271217f", + "id": "b944f271", "metadata": {}, "source": [ "

    \n", @@ -813,7 +788,7 @@ }, { "cell_type": "markdown", - "id": "1c22cfaf", + "id": "7fd42eef", "metadata": { "tags": [ "solution" @@ -827,7 +802,7 @@ }, { "cell_type": "markdown", - "id": "b8960216", + "id": "0d2b9257", "metadata": { "tags": [ "solution" @@ -841,7 +816,7 @@ }, { "cell_type": "markdown", - "id": "b31868b6", + "id": "799ad0f5", "metadata": {}, "source": [ "

    \n", @@ -853,7 +828,7 @@ }, { "cell_type": "markdown", - "id": "a3e49dae", + "id": "167915f5", "metadata": {}, "source": [ "

    \n", @@ -868,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "432049a6", + "id": "43e11cb6", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -881,7 +856,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c931233", + "id": "d5c1bc11", "metadata": {}, "outputs": [], "source": [ @@ -903,7 +878,7 @@ }, { "cell_type": "markdown", - "id": "258daf07", + "id": "4c090e2b", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -912,7 +887,7 @@ { "cell_type": "code", "execution_count": null, - "id": "19167fa2", + "id": "24511ead", "metadata": {}, "outputs": [], "source": [ @@ -924,7 +899,7 @@ }, { "cell_type": "markdown", - "id": "01002da0", + "id": "b0af1b64", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -933,7 +908,7 @@ { "cell_type": "code", "execution_count": null, - "id": "af94666a", + "id": "89d0d283", "metadata": {}, "outputs": [], "source": [ @@ -987,14 +962,14 @@ { "cell_type": "code", "execution_count": null, - "id": "f8723f92", + "id": "a6953785", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", - "id": "a18b0900", + "id": "91f021ac", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -1003,7 +978,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5caa855a", + "id": "2d86342f", "metadata": {}, "outputs": [], "source": [ @@ -1015,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "efa46250", + "id": "ee137028", "metadata": {}, "source": [ "

    \n", @@ -1026,7 +1001,7 @@ }, { "cell_type": "markdown", - "id": "68ae8876", + "id": "48cab4dd", "metadata": { "tags": [ "solution" @@ -1040,7 +1015,7 @@ }, { "cell_type": "markdown", - "id": "8c56472c", + "id": "c59a7c71", "metadata": { "tags": [ "solution" @@ -1055,7 +1030,7 @@ }, { "cell_type": "markdown", - "id": "1cfcffe1", + "id": "5bfcdaba", "metadata": {}, "source": [ "

    \n", @@ -1066,7 +1041,7 @@ }, { "cell_type": "markdown", - "id": "ff390801", + "id": "eef4eee8", "metadata": { "tags": [ "solution" @@ -1080,7 +1055,7 @@ }, { "cell_type": "markdown", - "id": "661db703", + "id": "b067072a", "metadata": { "tags": [ "solution" @@ -1094,7 +1069,7 @@ }, { "cell_type": "markdown", - "id": "7d811061", + "id": "f343e368", "metadata": {}, "source": [ "

    \n", @@ -1105,7 +1080,7 @@ }, { "cell_type": "markdown", - "id": "dab1cac5", + "id": "c66d86f5", "metadata": { "tags": [ "solution" @@ -1119,7 +1094,7 @@ }, { "cell_type": "markdown", - "id": "224c731a", + "id": "69a15854", "metadata": { "tags": [ "solution" @@ -1136,7 +1111,7 @@ }, { "cell_type": "markdown", - "id": "2eb81703", + "id": "3cfcf043", "metadata": {}, "source": [ "

    \n", @@ -1147,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "659a49e2", + "id": "e3eae9c3", "metadata": { "tags": [ "solution" @@ -1161,7 +1136,7 @@ }, { "cell_type": "markdown", - "id": "2dd47d03", + "id": "3901eb8c", "metadata": { "tags": [ "solution" @@ -1181,7 +1156,7 @@ }, { "cell_type": "markdown", - "id": "f4e2645d", + "id": "f279f3fd", "metadata": {}, "source": [ "

    \n", @@ -1193,7 +1168,7 @@ }, { "cell_type": "markdown", - "id": "eaa2aca7", + "id": "807bbaaa", "metadata": {}, "source": [ "

    \n", @@ -1208,7 +1183,7 @@ }, { "cell_type": "markdown", - "id": "f50d6106", + "id": "6c8d3e90", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1217,7 +1192,7 @@ }, { "cell_type": "markdown", - "id": "4fa74a0a", + "id": "9c49ffc0", "metadata": {}, "source": [ "\n", @@ -1227,7 +1202,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ba4da828", + "id": "3dc25f28", "metadata": {}, "outputs": [], "source": [ @@ -1260,7 +1235,7 @@ }, { "cell_type": "markdown", - "id": "47cb109a", + "id": "4fad4337", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1269,7 +1244,7 @@ { "cell_type": "code", "execution_count": null, - "id": "178a39d7", + "id": "4e2951aa", "metadata": {}, "outputs": [], "source": [ @@ -1308,7 +1283,7 @@ }, { "cell_type": "markdown", - "id": "12f406b0", + "id": "e4ecce34", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1319,7 +1294,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0a1d6560", + "id": "a9b89e6e", "metadata": {}, "outputs": [], "source": [ @@ -1329,7 +1304,7 @@ }, { "cell_type": "markdown", - "id": "fe09a285", + "id": "11539e2b", "metadata": {}, "source": [ "

    \n", @@ -1340,7 +1315,7 @@ }, { "cell_type": "markdown", - "id": "b42d7ee6", + "id": "a85d081f", "metadata": { "tags": [ "solution" @@ -1354,7 +1329,7 @@ }, { "cell_type": "markdown", - "id": "9f9ac1eb", + "id": "b9043cf5", "metadata": { "tags": [ "solution" @@ -1369,7 +1344,7 @@ }, { "cell_type": "markdown", - "id": "315b740a", + "id": "4dcea669", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1378,7 +1353,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c715c49", + "id": "10541614", "metadata": {}, "outputs": [], "source": [ @@ -1388,7 +1363,7 @@ }, { "cell_type": "markdown", - "id": "8db82f66", + "id": "f89c76cd", "metadata": {}, "source": [ "

    \n", @@ -1399,7 +1374,7 @@ }, { "cell_type": "markdown", - "id": "bf46888b", + "id": "1d81710e", "metadata": { "tags": [ "solution" @@ -1413,7 +1388,7 @@ }, { "cell_type": "markdown", - "id": "36ef9e63", + "id": "95f9ada8", "metadata": { "tags": [ "solution" @@ -1431,7 +1406,7 @@ }, { "cell_type": "markdown", - "id": "64f48898", + "id": "4500e51c", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1440,7 +1415,7 @@ { "cell_type": "code", "execution_count": null, - "id": "824a2128", + "id": "55317ce2", "metadata": {}, "outputs": [], "source": [ @@ -1452,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "30db6d44", + "id": "bf796afd", "metadata": {}, "source": [ "

    \n", @@ -1463,7 +1438,7 @@ }, { "cell_type": "markdown", - "id": "74f060ec", + "id": "e21703af", "metadata": { "tags": [ "solution" @@ -1477,7 +1452,7 @@ }, { "cell_type": "markdown", - "id": "c7272ad8", + "id": "6fd91345", "metadata": { "tags": [ "solution" @@ -1494,7 +1469,7 @@ }, { "cell_type": "markdown", - "id": "078b8fdc", + "id": "4ae086b6", "metadata": {}, "source": [ "

    \n", @@ -1505,7 +1480,7 @@ }, { "cell_type": "markdown", - "id": "9852a30d", + "id": "aa0b9bcb", "metadata": { "tags": [ "solution" @@ -1519,7 +1494,7 @@ }, { "cell_type": "markdown", - "id": "532aa958", + "id": "a4e75090", "metadata": { "tags": [ "solution" @@ -1535,7 +1510,7 @@ }, { "cell_type": "markdown", - "id": "2e3f0338", + "id": "15cb1b84", "metadata": {}, "source": [ "

    \n", @@ -1548,7 +1523,7 @@ }, { "cell_type": "markdown", - "id": "f8a4ea81", + "id": "4b28a610", "metadata": {}, "source": [ "

    \n", @@ -1562,7 +1537,7 @@ }, { "cell_type": "markdown", - "id": "2c98ff21", + "id": "607b548b", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1574,7 +1549,7 @@ }, { "cell_type": "markdown", - "id": "a20179a5", + "id": "b70470d4", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1583,7 +1558,7 @@ { "cell_type": "code", "execution_count": null, - "id": "afc8f426", + "id": "bd118ab2", "metadata": {}, "outputs": [], "source": [ @@ -1598,7 +1573,7 @@ }, { "cell_type": "markdown", - "id": "d16af11f", + "id": "9e50e11f", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1607,7 +1582,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0956137", + "id": "847a99f3", "metadata": {}, "outputs": [], "source": [ @@ -1636,7 +1611,7 @@ }, { "cell_type": "markdown", - "id": "3d7d729d", + "id": "6ad2d555", "metadata": {}, "source": [ "### UNet model\n", @@ -1646,7 +1621,7 @@ }, { "cell_type": "markdown", - "id": "f128e0d5", + "id": "832d9a0e", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1655,7 +1630,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5c6743ed", + "id": "fcb74929", "metadata": {}, "outputs": [], "source": [ @@ -1703,7 +1678,7 @@ }, { "cell_type": "markdown", - "id": "dcfe5981", + "id": "b88e84dc", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1712,7 +1687,7 @@ { "cell_type": "code", "execution_count": null, - "id": "94fe0b9d", + "id": "bdbf76e8", "metadata": {}, "outputs": [], "source": [ @@ -1750,7 +1725,7 @@ }, { "cell_type": "markdown", - "id": "cb5be242", + "id": "5556d195", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1759,7 +1734,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2cd4f305", + "id": "bc11c7d8", "metadata": {}, "outputs": [], "source": [ @@ -1770,7 +1745,7 @@ }, { "cell_type": "markdown", - "id": "c8addd07", + "id": "11098057", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1779,7 +1754,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d32a9664", + "id": "f68adba3", "metadata": {}, "outputs": [], "source": [ @@ -1793,7 +1768,7 @@ }, { "cell_type": "markdown", - "id": "d1c1b2a8", + "id": "c4b12017", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1804,7 +1779,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bb313fa5", + "id": "305a367d", "metadata": {}, "outputs": [], "source": [ @@ -1819,7 +1794,7 @@ { "cell_type": "code", "execution_count": null, - "id": "57d4f69e", + "id": "57262965", "metadata": {}, "outputs": [], "source": [] @@ -1827,7 +1802,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1c72a1cf", + "id": "98dcd5b1", "metadata": {}, "outputs": [], "source": [ @@ -1856,7 +1831,7 @@ }, { "cell_type": "markdown", - "id": "35109e13", + "id": "076d4eff", "metadata": {}, "source": [ "

    \n", @@ -1867,7 +1842,7 @@ }, { "cell_type": "markdown", - "id": "a39924b6", + "id": "dc28b768", "metadata": { "tags": [ "solution" @@ -1881,7 +1856,7 @@ }, { "cell_type": "markdown", - "id": "4b55fbbb", + "id": "0d5775c4", "metadata": { "tags": [ "solution" @@ -1895,7 +1870,7 @@ }, { "cell_type": "markdown", - "id": "b7eb0224", + "id": "85845f84", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1905,7 +1880,7 @@ }, { "cell_type": "markdown", - "id": "499d0ceb", + "id": "d5650b2d", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1916,7 +1891,7 @@ { "cell_type": "code", "execution_count": null, - "id": "75b8cace", + "id": "f8ddc55f", "metadata": {}, "outputs": [], "source": [ @@ -1937,7 +1912,7 @@ }, { "cell_type": "markdown", - "id": "5896d150", + "id": "76cb89f4", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1946,7 +1921,7 @@ { "cell_type": "code", "execution_count": null, - "id": "952fff80", + "id": "9a3d256b", "metadata": {}, "outputs": [], "source": [ @@ -1956,7 +1931,7 @@ }, { "cell_type": "markdown", - "id": "43c36e17", + "id": "4da65639", "metadata": {}, "source": [ "

    \n", @@ -1967,7 +1942,7 @@ }, { "cell_type": "markdown", - "id": "7f726da8", + "id": "2c946b56", "metadata": { "tags": [ "solution" @@ -1981,7 +1956,7 @@ }, { "cell_type": "markdown", - "id": "109c4d48", + "id": "9bb6123c", "metadata": { "tags": [ "solution" @@ -1995,7 +1970,7 @@ }, { "cell_type": "markdown", - "id": "ed1de42c", + "id": "87bec030", "metadata": {}, "source": [ "

    \n", @@ -2006,7 +1981,7 @@ }, { "cell_type": "markdown", - "id": "5d8c4460", + "id": "c0d369f0", "metadata": { "tags": [ "solution" @@ -2020,7 +1995,7 @@ }, { "cell_type": "markdown", - "id": "c6328745", + "id": "22a47495", "metadata": { "tags": [ "solution" @@ -2035,7 +2010,7 @@ }, { "cell_type": "markdown", - "id": "ea481c7f", + "id": "474a797a", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2046,7 +2021,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bfff2a4b", + "id": "780d66d6", "metadata": {}, "outputs": [], "source": [ @@ -2083,7 +2058,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fc58e649", + "id": "fb8bc178", "metadata": {}, "outputs": [], "source": [ @@ -2094,7 +2069,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62ee68b5", + "id": "37d6f25d", "metadata": {}, "outputs": [], "source": [ @@ -2104,7 +2079,7 @@ }, { "cell_type": "markdown", - "id": "55bcf106", + "id": "322c7b74", "metadata": {}, "source": [ "

    \n", @@ -2115,7 +2090,7 @@ }, { "cell_type": "markdown", - "id": "128e111c", + "id": "66fcabc5", "metadata": { "tags": [ "solution" @@ -2134,7 +2109,7 @@ { "cell_type": "code", "execution_count": null, - "id": "27e11ee9", + "id": "bae7c6c1", "metadata": {}, "outputs": [], "source": [ @@ -2171,7 +2146,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73d18976", + "id": "d8b38e2e", "metadata": {}, "outputs": [], "source": [ @@ -2182,7 +2157,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4f304e41", + "id": "2f9802b2", "metadata": {}, "outputs": [], "source": [ @@ -2192,7 +2167,7 @@ }, { "cell_type": "markdown", - "id": "3f3107f0", + "id": "06a2a23c", "metadata": {}, "source": [ "

    \n", @@ -2203,7 +2178,7 @@ }, { "cell_type": "markdown", - "id": "203bdd89", + "id": "292b9ba3", "metadata": { "tags": [ "solution" From 7377642de12977c8d5d7eee16b9ab6697153fe35 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 18:17:36 +0100 Subject: [PATCH 26/51] Try to fix empty cells --- solution.py | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/solution.py b/solution.py index a855f5a..b2f2f81 100644 --- a/solution.py +++ b/solution.py @@ -497,6 +497,7 @@ def predict(model, dataset): # We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix. +# + from sklearn.metrics import confusion_matrix import seaborn as sns import pandas as pd @@ -542,8 +543,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): fig, ax = plt.subplots(figsize=figsize) ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30) ax.set_title(title) - - +#- # Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below. @@ -986,9 +986,6 @@ def apply_denoising(image, model): # remove batch and channel dimensions before returning return prediction.detach().cpu()[0,0] - - -# + # Displays: ground truth, noisy, and denoised images def visualize_denoising(model, dataset, index): orig_image = dataset[index][0][0] @@ -1007,10 +1004,9 @@ def visualize_denoising(model, dataset, index): plt.show() # We pick 8 images to show: + for i in range(8): visualize_denoising(unet_model, test_dataset, 123*i) - -# - #

    # Task 5.1:

    From 3dce87c0a2b53a51fc944e343bc40a0c84aa3f04 Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 17:18:16 +0000 Subject: [PATCH 27/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 299 +++++++++++++++++++-------------------- solution.ipynb | 375 +++++++++++++++++++++++-------------------------- 2 files changed, 320 insertions(+), 354 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index a8e43fb..639a784 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "b4334260", + "id": "adda9842", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "8f725b2e", + "id": "e5d7e30e", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "d7e25385", + "id": "f6dae011", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "4bb98583", + "id": "76ccfd8d", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "6187b53f", + "id": "5b568cb9", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "06e04dcf", + "id": "839f5e5d", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "7ec8c3e8", + "id": "66fe78ff", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "854e34f7", + "id": "a95679b1", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59cc29f7", + "id": "f81bdd3d", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "57297c7c", + "id": "f4cb3dc1", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8cfbd299", + "id": "2bedcac3", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eaf876ba", + "id": "cbf5e737", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "e076db7c", + "id": "17c5d34f", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "2f3d78ea", + "id": "e8f04799", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "bbb280f6", + "id": "c3f572ee", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "9ffdac98", + "id": "2fabdefb", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "384c72fc", + "id": "1f111005", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "77aa5f6a", + "id": "f7826fb4", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "86903ee7", + "id": "c8213ead", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "0825d9f3", + "id": "cd33949c", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8689bc74", + "id": "434e7f07", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "9108298a", + "id": "e55e4b7b", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f0e96660", + "id": "0840fe88", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "34f7d462", + "id": "5e2c971b", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "4d2ac1a6", + "id": "0c80e649", "metadata": {}, "source": [ "

    \n", @@ -329,7 +329,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ad194579", + "id": "b7e6d2fa", "metadata": {}, "outputs": [], "source": [ @@ -343,7 +343,7 @@ }, { "cell_type": "markdown", - "id": "34494aae", + "id": "5ce4fcf6", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -352,7 +352,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62d13f5a", + "id": "351d6d2b", "metadata": {}, "outputs": [], "source": [ @@ -377,7 +377,7 @@ }, { "cell_type": "markdown", - "id": "32836f56", + "id": "af1789c1", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -386,7 +386,7 @@ { "cell_type": "code", "execution_count": null, - "id": "47cede43", + "id": "d940e32c", "metadata": {}, "outputs": [], "source": [ @@ -405,7 +405,7 @@ }, { "cell_type": "markdown", - "id": "302f2a6d", + "id": "a39797b5", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -414,7 +414,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5e83008c", + "id": "a516acac", "metadata": {}, "outputs": [], "source": [ @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "3ffab0a3", + "id": "3731d055", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -451,7 +451,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45136375", + "id": "73f9588f", "metadata": {}, "outputs": [], "source": [ @@ -465,7 +465,7 @@ }, { "cell_type": "markdown", - "id": "3113e61e", + "id": "478a64fc", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -474,7 +474,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f91b95fa", + "id": "31498d2a", "metadata": {}, "outputs": [], "source": [ @@ -507,7 +507,7 @@ }, { "cell_type": "markdown", - "id": "0f80bd8c", + "id": "a12b2049", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -516,7 +516,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f63734d6", + "id": "36d68857", "metadata": {}, "outputs": [], "source": [ @@ -531,7 +531,7 @@ }, { "cell_type": "markdown", - "id": "364fca1b", + "id": "0f0f81c9", "metadata": {}, "source": [ "

    \n", @@ -542,7 +542,7 @@ }, { "cell_type": "markdown", - "id": "5eecc109", + "id": "1b6db647", "metadata": {}, "source": [ "

    \n", @@ -553,7 +553,7 @@ }, { "cell_type": "markdown", - "id": "b944f271", + "id": "3ea8c3b3", "metadata": {}, "source": [ "

    \n", @@ -564,7 +564,7 @@ }, { "cell_type": "markdown", - "id": "799ad0f5", + "id": "e3d2282a", "metadata": {}, "source": [ "

    \n", @@ -576,7 +576,7 @@ }, { "cell_type": "markdown", - "id": "167915f5", + "id": "7ad0a46a", "metadata": {}, "source": [ "

    \n", @@ -591,7 +591,7 @@ }, { "cell_type": "markdown", - "id": "43e11cb6", + "id": "a7fde316", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -604,7 +604,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d5c1bc11", + "id": "5cd9755d", "metadata": {}, "outputs": [], "source": [ @@ -626,7 +626,7 @@ }, { "cell_type": "markdown", - "id": "4c090e2b", + "id": "ed703a9a", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -635,7 +635,7 @@ { "cell_type": "code", "execution_count": null, - "id": "24511ead", + "id": "1cff0217", "metadata": {}, "outputs": [], "source": [ @@ -647,7 +647,7 @@ }, { "cell_type": "markdown", - "id": "b0af1b64", + "id": "42147aad", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -656,7 +656,7 @@ { "cell_type": "code", "execution_count": null, - "id": "89d0d283", + "id": "7f12688e", "metadata": {}, "outputs": [], "source": [ @@ -704,52 +704,25 @@ " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", - " ax.set_title(title)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a6953785", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "91f021ac", - "metadata": {}, - "source": [ - "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2d86342f", - "metadata": {}, - "outputs": [], - "source": [ + " ax.set_title(title)\n", + "#-\n", + "\n", + "# Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below.\n", + "\n", "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", "cm_analysis(true_labels, pred_tainted_clean, \"Tainted Model on Clean Data\")\n", - "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")" - ] - }, - { - "cell_type": "markdown", - "id": "ee137028", - "metadata": {}, - "source": [ - "

    \n", - "Task 3.1:

    \n", - "For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", - "
    " + "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")\n", + "\n", + "#

    \n", + "# Task 3.1:

    \n", + "# For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", + "#
    " ] }, { "cell_type": "markdown", - "id": "5bfcdaba", + "id": "4c670669", "metadata": {}, "source": [ "

    \n", @@ -760,7 +733,7 @@ }, { "cell_type": "markdown", - "id": "f343e368", + "id": "fe2557a8", "metadata": {}, "source": [ "

    \n", @@ -771,7 +744,7 @@ }, { "cell_type": "markdown", - "id": "3cfcf043", + "id": "69e9728a", "metadata": {}, "source": [ "

    \n", @@ -782,7 +755,7 @@ }, { "cell_type": "markdown", - "id": "f279f3fd", + "id": "64b8d401", "metadata": {}, "source": [ "

    \n", @@ -794,7 +767,7 @@ }, { "cell_type": "markdown", - "id": "807bbaaa", + "id": "fb784988", "metadata": {}, "source": [ "

    \n", @@ -809,7 +782,7 @@ }, { "cell_type": "markdown", - "id": "6c8d3e90", + "id": "5bb27c64", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -818,7 +791,7 @@ }, { "cell_type": "markdown", - "id": "9c49ffc0", + "id": "0f945022", "metadata": {}, "source": [ "\n", @@ -828,7 +801,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3dc25f28", + "id": "dd31c2f2", "metadata": {}, "outputs": [], "source": [ @@ -861,7 +834,7 @@ }, { "cell_type": "markdown", - "id": "4fad4337", + "id": "0b840ebc", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -870,7 +843,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4e2951aa", + "id": "12264ead", "metadata": {}, "outputs": [], "source": [ @@ -909,7 +882,7 @@ }, { "cell_type": "markdown", - "id": "e4ecce34", + "id": "45f1b911", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -920,7 +893,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a9b89e6e", + "id": "d29a00d3", "metadata": {}, "outputs": [], "source": [ @@ -930,7 +903,7 @@ }, { "cell_type": "markdown", - "id": "11539e2b", + "id": "8a1ae450", "metadata": {}, "source": [ "

    \n", @@ -941,7 +914,7 @@ }, { "cell_type": "markdown", - "id": "4dcea669", + "id": "531d5887", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -950,7 +923,7 @@ { "cell_type": "code", "execution_count": null, - "id": "10541614", + "id": "b8b0a00c", "metadata": {}, "outputs": [], "source": [ @@ -960,7 +933,7 @@ }, { "cell_type": "markdown", - "id": "f89c76cd", + "id": "50cef6fe", "metadata": {}, "source": [ "

    \n", @@ -971,7 +944,7 @@ }, { "cell_type": "markdown", - "id": "4500e51c", + "id": "316648a1", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -980,7 +953,7 @@ { "cell_type": "code", "execution_count": null, - "id": "55317ce2", + "id": "dae40772", "metadata": {}, "outputs": [], "source": [ @@ -992,7 +965,7 @@ }, { "cell_type": "markdown", - "id": "bf796afd", + "id": "788ce5d3", "metadata": {}, "source": [ "

    \n", @@ -1003,7 +976,7 @@ }, { "cell_type": "markdown", - "id": "4ae086b6", + "id": "9fc7b89c", "metadata": {}, "source": [ "

    \n", @@ -1014,7 +987,7 @@ }, { "cell_type": "markdown", - "id": "15cb1b84", + "id": "cc55a255", "metadata": {}, "source": [ "

    \n", @@ -1027,7 +1000,7 @@ }, { "cell_type": "markdown", - "id": "4b28a610", + "id": "63756a82", "metadata": {}, "source": [ "

    \n", @@ -1041,7 +1014,7 @@ }, { "cell_type": "markdown", - "id": "607b548b", + "id": "2a72d908", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1053,7 +1026,7 @@ }, { "cell_type": "markdown", - "id": "b70470d4", + "id": "7ca0499e", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1062,7 +1035,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bd118ab2", + "id": "c72a2158", "metadata": {}, "outputs": [], "source": [ @@ -1077,7 +1050,7 @@ }, { "cell_type": "markdown", - "id": "9e50e11f", + "id": "f7a6ab29", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1086,7 +1059,7 @@ { "cell_type": "code", "execution_count": null, - "id": "847a99f3", + "id": "6093f082", "metadata": {}, "outputs": [], "source": [ @@ -1115,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "6ad2d555", + "id": "ec029fc7", "metadata": {}, "source": [ "### UNet model\n", @@ -1125,7 +1098,7 @@ }, { "cell_type": "markdown", - "id": "832d9a0e", + "id": "1ead30f9", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1134,7 +1107,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fcb74929", + "id": "631806b5", "metadata": {}, "outputs": [], "source": [ @@ -1182,7 +1155,7 @@ }, { "cell_type": "markdown", - "id": "b88e84dc", + "id": "b998875e", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1191,7 +1164,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bdbf76e8", + "id": "e9d76a45", "metadata": {}, "outputs": [], "source": [ @@ -1229,7 +1202,7 @@ }, { "cell_type": "markdown", - "id": "5556d195", + "id": "5e96c67c", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1238,7 +1211,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bc11c7d8", + "id": "4587f15d", "metadata": {}, "outputs": [], "source": [ @@ -1249,7 +1222,7 @@ }, { "cell_type": "markdown", - "id": "11098057", + "id": "cc56b362", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1258,7 +1231,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f68adba3", + "id": "bcef2183", "metadata": {}, "outputs": [], "source": [ @@ -1272,7 +1245,7 @@ }, { "cell_type": "markdown", - "id": "c4b12017", + "id": "ba61aa74", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1283,8 +1256,10 @@ { "cell_type": "code", "execution_count": null, - "id": "305a367d", - "metadata": {}, + "id": "370c076b", + "metadata": { + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "def apply_denoising(image, model):\n", @@ -1298,16 +1273,10 @@ { "cell_type": "code", "execution_count": null, - "id": "57262965", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "98dcd5b1", - "metadata": {}, + "id": "3ad20390", + "metadata": { + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "# Displays: ground truth, noisy, and denoised images\n", @@ -1325,17 +1294,31 @@ " plt.axis('off')\n", " plt.imshow(denoised_image, cmap=plt.get_cmap('gray'))\n", " \n", - " plt.show()\n", - "\n", - "# We pick 8 images to show:\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7f54e077", + "metadata": {}, + "source": [ + "We pick 8 images to show:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b6754636", + "metadata": {}, + "outputs": [], + "source": [ "for i in range(8):\n", - " visualize_denoising(unet_model, test_dataset, 123*i)\n", - " " + " visualize_denoising(unet_model, test_dataset, 123*i)" ] }, { "cell_type": "markdown", - "id": "076d4eff", + "id": "0abbf186", "metadata": {}, "source": [ "

    \n", @@ -1346,7 +1329,7 @@ }, { "cell_type": "markdown", - "id": "85845f84", + "id": "347783c1", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1356,7 +1339,7 @@ }, { "cell_type": "markdown", - "id": "d5650b2d", + "id": "9074d884", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1367,7 +1350,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f8ddc55f", + "id": "9ec53c62", "metadata": {}, "outputs": [], "source": [ @@ -1388,7 +1371,7 @@ }, { "cell_type": "markdown", - "id": "76cb89f4", + "id": "9f241941", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1397,7 +1380,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9a3d256b", + "id": "b7bd016c", "metadata": {}, "outputs": [], "source": [ @@ -1407,7 +1390,7 @@ }, { "cell_type": "markdown", - "id": "4da65639", + "id": "dc49133e", "metadata": {}, "source": [ "

    \n", @@ -1418,7 +1401,7 @@ }, { "cell_type": "markdown", - "id": "87bec030", + "id": "6d2b670d", "metadata": {}, "source": [ "

    \n", @@ -1429,7 +1412,7 @@ }, { "cell_type": "markdown", - "id": "474a797a", + "id": "8d9d850d", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1440,7 +1423,7 @@ { "cell_type": "code", "execution_count": null, - "id": "780d66d6", + "id": "00a1dc6e", "metadata": {}, "outputs": [], "source": [ @@ -1477,7 +1460,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fb8bc178", + "id": "5bdf014f", "metadata": {}, "outputs": [], "source": [ @@ -1488,7 +1471,7 @@ { "cell_type": "code", "execution_count": null, - "id": "37d6f25d", + "id": "ded5d280", "metadata": {}, "outputs": [], "source": [ @@ -1498,7 +1481,7 @@ }, { "cell_type": "markdown", - "id": "322c7b74", + "id": "c9aaa117", "metadata": {}, "source": [ "

    \n", @@ -1510,7 +1493,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bae7c6c1", + "id": "039cd974", "metadata": {}, "outputs": [], "source": [ @@ -1547,7 +1530,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d8b38e2e", + "id": "91cbce9e", "metadata": {}, "outputs": [], "source": [ @@ -1558,7 +1541,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f9802b2", + "id": "794e0d53", "metadata": {}, "outputs": [], "source": [ @@ -1568,7 +1551,7 @@ }, { "cell_type": "markdown", - "id": "06a2a23c", + "id": "6f5dddbc", "metadata": {}, "source": [ "

    \n", diff --git a/solution.ipynb b/solution.ipynb index 42d4913..630e90a 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "b4334260", + "id": "adda9842", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "8f725b2e", + "id": "e5d7e30e", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "d7e25385", + "id": "f6dae011", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "4bb98583", + "id": "76ccfd8d", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "6187b53f", + "id": "5b568cb9", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "06e04dcf", + "id": "839f5e5d", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "7ec8c3e8", + "id": "66fe78ff", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "854e34f7", + "id": "a95679b1", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59cc29f7", + "id": "f81bdd3d", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "57297c7c", + "id": "f4cb3dc1", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8cfbd299", + "id": "2bedcac3", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eaf876ba", + "id": "cbf5e737", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "e076db7c", + "id": "17c5d34f", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "b07b8240", + "id": "556f8bac", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "e294c374", + "id": "7dc94e89", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "2f3d78ea", + "id": "e8f04799", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "689ce427", + "id": "74055b8a", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "c393c4e0", + "id": "c0e60d36", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "bbb280f6", + "id": "c3f572ee", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "9ffdac98", + "id": "2fabdefb", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "384c72fc", + "id": "1f111005", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "77aa5f6a", + "id": "f7826fb4", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "86903ee7", + "id": "c8213ead", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "0825d9f3", + "id": "cd33949c", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8689bc74", + "id": "434e7f07", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "9108298a", + "id": "e55e4b7b", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f0e96660", + "id": "0840fe88", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "34f7d462", + "id": "5e2c971b", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "4d2ac1a6", + "id": "0c80e649", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "592ae7b6", + "id": "f5fe74f8", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "34e274fd", + "id": "e2feb73a", "metadata": { "tags": [ "solution" @@ -447,7 +447,7 @@ }, { "cell_type": "markdown", - "id": "967cebcc", + "id": "6000419c", "metadata": { "tags": [ "solution" @@ -461,7 +461,7 @@ }, { "cell_type": "markdown", - "id": "93b33424", + "id": "a799bd0e", "metadata": { "tags": [ "solution" @@ -497,7 +497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ad194579", + "id": "b7e6d2fa", "metadata": {}, "outputs": [], "source": [ @@ -511,7 +511,7 @@ }, { "cell_type": "markdown", - "id": "34494aae", + "id": "5ce4fcf6", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -520,7 +520,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62d13f5a", + "id": "351d6d2b", "metadata": {}, "outputs": [], "source": [ @@ -545,7 +545,7 @@ }, { "cell_type": "markdown", - "id": "32836f56", + "id": "af1789c1", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -554,7 +554,7 @@ { "cell_type": "code", "execution_count": null, - "id": "47cede43", + "id": "d940e32c", "metadata": {}, "outputs": [], "source": [ @@ -573,7 +573,7 @@ }, { "cell_type": "markdown", - "id": "302f2a6d", + "id": "a39797b5", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -582,7 +582,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5e83008c", + "id": "a516acac", "metadata": {}, "outputs": [], "source": [ @@ -610,7 +610,7 @@ }, { "cell_type": "markdown", - "id": "3ffab0a3", + "id": "3731d055", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -619,7 +619,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45136375", + "id": "73f9588f", "metadata": {}, "outputs": [], "source": [ @@ -633,7 +633,7 @@ }, { "cell_type": "markdown", - "id": "3113e61e", + "id": "478a64fc", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -642,7 +642,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f91b95fa", + "id": "31498d2a", "metadata": {}, "outputs": [], "source": [ @@ -675,7 +675,7 @@ }, { "cell_type": "markdown", - "id": "0f80bd8c", + "id": "a12b2049", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -684,7 +684,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f63734d6", + "id": "36d68857", "metadata": {}, "outputs": [], "source": [ @@ -699,7 +699,7 @@ }, { "cell_type": "markdown", - "id": "364fca1b", + "id": "0f0f81c9", "metadata": {}, "source": [ "

    \n", @@ -710,7 +710,7 @@ }, { "cell_type": "markdown", - "id": "03545b8e", + "id": "73e8d38a", "metadata": { "tags": [ "solution" @@ -724,7 +724,7 @@ }, { "cell_type": "markdown", - "id": "dd2d421f", + "id": "b606a428", "metadata": { "tags": [ "solution" @@ -738,7 +738,7 @@ }, { "cell_type": "markdown", - "id": "5eecc109", + "id": "1b6db647", "metadata": {}, "source": [ "

    \n", @@ -749,7 +749,7 @@ }, { "cell_type": "markdown", - "id": "26a25e13", + "id": "ecd13877", "metadata": { "tags": [ "solution" @@ -763,7 +763,7 @@ }, { "cell_type": "markdown", - "id": "1a82f841", + "id": "53a4bae0", "metadata": { "tags": [ "solution" @@ -777,7 +777,7 @@ }, { "cell_type": "markdown", - "id": "b944f271", + "id": "3ea8c3b3", "metadata": {}, "source": [ "

    \n", @@ -788,7 +788,7 @@ }, { "cell_type": "markdown", - "id": "7fd42eef", + "id": "e5e82742", "metadata": { "tags": [ "solution" @@ -802,7 +802,7 @@ }, { "cell_type": "markdown", - "id": "0d2b9257", + "id": "a35ef600", "metadata": { "tags": [ "solution" @@ -816,7 +816,7 @@ }, { "cell_type": "markdown", - "id": "799ad0f5", + "id": "e3d2282a", "metadata": {}, "source": [ "

    \n", @@ -828,7 +828,7 @@ }, { "cell_type": "markdown", - "id": "167915f5", + "id": "7ad0a46a", "metadata": {}, "source": [ "

    \n", @@ -843,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "43e11cb6", + "id": "a7fde316", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -856,7 +856,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d5c1bc11", + "id": "5cd9755d", "metadata": {}, "outputs": [], "source": [ @@ -878,7 +878,7 @@ }, { "cell_type": "markdown", - "id": "4c090e2b", + "id": "ed703a9a", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -887,7 +887,7 @@ { "cell_type": "code", "execution_count": null, - "id": "24511ead", + "id": "1cff0217", "metadata": {}, "outputs": [], "source": [ @@ -899,7 +899,7 @@ }, { "cell_type": "markdown", - "id": "b0af1b64", + "id": "42147aad", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -908,7 +908,7 @@ { "cell_type": "code", "execution_count": null, - "id": "89d0d283", + "id": "7f12688e", "metadata": {}, "outputs": [], "source": [ @@ -956,52 +956,25 @@ " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", - " ax.set_title(title)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a6953785", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "91f021ac", - "metadata": {}, - "source": [ - "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2d86342f", - "metadata": {}, - "outputs": [], - "source": [ + " ax.set_title(title)\n", + "#-\n", + "\n", + "# Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below.\n", + "\n", "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", "cm_analysis(true_labels, pred_tainted_clean, \"Tainted Model on Clean Data\")\n", - "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")" - ] - }, - { - "cell_type": "markdown", - "id": "ee137028", - "metadata": {}, - "source": [ - "

    \n", - "Task 3.1:

    \n", - "For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", - "
    " + "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")\n", + "\n", + "#

    \n", + "# Task 3.1:

    \n", + "# For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", + "#
    " ] }, { "cell_type": "markdown", - "id": "48cab4dd", + "id": "649ab696", "metadata": { "tags": [ "solution" @@ -1015,7 +988,7 @@ }, { "cell_type": "markdown", - "id": "c59a7c71", + "id": "5a6f0e64", "metadata": { "tags": [ "solution" @@ -1030,7 +1003,7 @@ }, { "cell_type": "markdown", - "id": "5bfcdaba", + "id": "4c670669", "metadata": {}, "source": [ "

    \n", @@ -1041,7 +1014,7 @@ }, { "cell_type": "markdown", - "id": "eef4eee8", + "id": "cd4c2361", "metadata": { "tags": [ "solution" @@ -1055,7 +1028,7 @@ }, { "cell_type": "markdown", - "id": "b067072a", + "id": "364d3cfa", "metadata": { "tags": [ "solution" @@ -1069,7 +1042,7 @@ }, { "cell_type": "markdown", - "id": "f343e368", + "id": "fe2557a8", "metadata": {}, "source": [ "

    \n", @@ -1080,7 +1053,7 @@ }, { "cell_type": "markdown", - "id": "c66d86f5", + "id": "8d3be153", "metadata": { "tags": [ "solution" @@ -1094,7 +1067,7 @@ }, { "cell_type": "markdown", - "id": "69a15854", + "id": "0a565fa6", "metadata": { "tags": [ "solution" @@ -1111,7 +1084,7 @@ }, { "cell_type": "markdown", - "id": "3cfcf043", + "id": "69e9728a", "metadata": {}, "source": [ "

    \n", @@ -1122,7 +1095,7 @@ }, { "cell_type": "markdown", - "id": "e3eae9c3", + "id": "95d27f55", "metadata": { "tags": [ "solution" @@ -1136,7 +1109,7 @@ }, { "cell_type": "markdown", - "id": "3901eb8c", + "id": "d74f6e25", "metadata": { "tags": [ "solution" @@ -1156,7 +1129,7 @@ }, { "cell_type": "markdown", - "id": "f279f3fd", + "id": "64b8d401", "metadata": {}, "source": [ "

    \n", @@ -1168,7 +1141,7 @@ }, { "cell_type": "markdown", - "id": "807bbaaa", + "id": "fb784988", "metadata": {}, "source": [ "

    \n", @@ -1183,7 +1156,7 @@ }, { "cell_type": "markdown", - "id": "6c8d3e90", + "id": "5bb27c64", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1192,7 +1165,7 @@ }, { "cell_type": "markdown", - "id": "9c49ffc0", + "id": "0f945022", "metadata": {}, "source": [ "\n", @@ -1202,7 +1175,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3dc25f28", + "id": "dd31c2f2", "metadata": {}, "outputs": [], "source": [ @@ -1235,7 +1208,7 @@ }, { "cell_type": "markdown", - "id": "4fad4337", + "id": "0b840ebc", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1244,7 +1217,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4e2951aa", + "id": "12264ead", "metadata": {}, "outputs": [], "source": [ @@ -1283,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "e4ecce34", + "id": "45f1b911", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1294,7 +1267,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a9b89e6e", + "id": "d29a00d3", "metadata": {}, "outputs": [], "source": [ @@ -1304,7 +1277,7 @@ }, { "cell_type": "markdown", - "id": "11539e2b", + "id": "8a1ae450", "metadata": {}, "source": [ "

    \n", @@ -1315,7 +1288,7 @@ }, { "cell_type": "markdown", - "id": "a85d081f", + "id": "153bfeaa", "metadata": { "tags": [ "solution" @@ -1329,7 +1302,7 @@ }, { "cell_type": "markdown", - "id": "b9043cf5", + "id": "d397dcad", "metadata": { "tags": [ "solution" @@ -1344,7 +1317,7 @@ }, { "cell_type": "markdown", - "id": "4dcea669", + "id": "531d5887", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1353,7 +1326,7 @@ { "cell_type": "code", "execution_count": null, - "id": "10541614", + "id": "b8b0a00c", "metadata": {}, "outputs": [], "source": [ @@ -1363,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "f89c76cd", + "id": "50cef6fe", "metadata": {}, "source": [ "

    \n", @@ -1374,7 +1347,7 @@ }, { "cell_type": "markdown", - "id": "1d81710e", + "id": "a13d1997", "metadata": { "tags": [ "solution" @@ -1388,7 +1361,7 @@ }, { "cell_type": "markdown", - "id": "95f9ada8", + "id": "6d780f65", "metadata": { "tags": [ "solution" @@ -1406,7 +1379,7 @@ }, { "cell_type": "markdown", - "id": "4500e51c", + "id": "316648a1", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1415,7 +1388,7 @@ { "cell_type": "code", "execution_count": null, - "id": "55317ce2", + "id": "dae40772", "metadata": {}, "outputs": [], "source": [ @@ -1427,7 +1400,7 @@ }, { "cell_type": "markdown", - "id": "bf796afd", + "id": "788ce5d3", "metadata": {}, "source": [ "

    \n", @@ -1438,7 +1411,7 @@ }, { "cell_type": "markdown", - "id": "e21703af", + "id": "e520d4b1", "metadata": { "tags": [ "solution" @@ -1452,7 +1425,7 @@ }, { "cell_type": "markdown", - "id": "6fd91345", + "id": "3264bcef", "metadata": { "tags": [ "solution" @@ -1469,7 +1442,7 @@ }, { "cell_type": "markdown", - "id": "4ae086b6", + "id": "9fc7b89c", "metadata": {}, "source": [ "

    \n", @@ -1480,7 +1453,7 @@ }, { "cell_type": "markdown", - "id": "aa0b9bcb", + "id": "4db808a2", "metadata": { "tags": [ "solution" @@ -1494,7 +1467,7 @@ }, { "cell_type": "markdown", - "id": "a4e75090", + "id": "4f3da547", "metadata": { "tags": [ "solution" @@ -1510,7 +1483,7 @@ }, { "cell_type": "markdown", - "id": "15cb1b84", + "id": "cc55a255", "metadata": {}, "source": [ "

    \n", @@ -1523,7 +1496,7 @@ }, { "cell_type": "markdown", - "id": "4b28a610", + "id": "63756a82", "metadata": {}, "source": [ "

    \n", @@ -1537,7 +1510,7 @@ }, { "cell_type": "markdown", - "id": "607b548b", + "id": "2a72d908", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1549,7 +1522,7 @@ }, { "cell_type": "markdown", - "id": "b70470d4", + "id": "7ca0499e", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1558,7 +1531,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bd118ab2", + "id": "c72a2158", "metadata": {}, "outputs": [], "source": [ @@ -1573,7 +1546,7 @@ }, { "cell_type": "markdown", - "id": "9e50e11f", + "id": "f7a6ab29", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise.\n" @@ -1582,7 +1555,7 @@ { "cell_type": "code", "execution_count": null, - "id": "847a99f3", + "id": "6093f082", "metadata": {}, "outputs": [], "source": [ @@ -1611,7 +1584,7 @@ }, { "cell_type": "markdown", - "id": "6ad2d555", + "id": "ec029fc7", "metadata": {}, "source": [ "### UNet model\n", @@ -1621,7 +1594,7 @@ }, { "cell_type": "markdown", - "id": "832d9a0e", + "id": "1ead30f9", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1630,7 +1603,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fcb74929", + "id": "631806b5", "metadata": {}, "outputs": [], "source": [ @@ -1678,7 +1651,7 @@ }, { "cell_type": "markdown", - "id": "b88e84dc", + "id": "b998875e", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1687,7 +1660,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bdbf76e8", + "id": "e9d76a45", "metadata": {}, "outputs": [], "source": [ @@ -1725,7 +1698,7 @@ }, { "cell_type": "markdown", - "id": "5556d195", + "id": "5e96c67c", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1734,7 +1707,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bc11c7d8", + "id": "4587f15d", "metadata": {}, "outputs": [], "source": [ @@ -1745,7 +1718,7 @@ }, { "cell_type": "markdown", - "id": "11098057", + "id": "cc56b362", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1754,7 +1727,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f68adba3", + "id": "bcef2183", "metadata": {}, "outputs": [], "source": [ @@ -1768,7 +1741,7 @@ }, { "cell_type": "markdown", - "id": "c4b12017", + "id": "ba61aa74", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1779,8 +1752,10 @@ { "cell_type": "code", "execution_count": null, - "id": "305a367d", - "metadata": {}, + "id": "370c076b", + "metadata": { + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "def apply_denoising(image, model):\n", @@ -1794,16 +1769,10 @@ { "cell_type": "code", "execution_count": null, - "id": "57262965", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "98dcd5b1", - "metadata": {}, + "id": "3ad20390", + "metadata": { + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "# Displays: ground truth, noisy, and denoised images\n", @@ -1821,17 +1790,31 @@ " plt.axis('off')\n", " plt.imshow(denoised_image, cmap=plt.get_cmap('gray'))\n", " \n", - " plt.show()\n", - "\n", - "# We pick 8 images to show:\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7f54e077", + "metadata": {}, + "source": [ + "We pick 8 images to show:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b6754636", + "metadata": {}, + "outputs": [], + "source": [ "for i in range(8):\n", - " visualize_denoising(unet_model, test_dataset, 123*i)\n", - " " + " visualize_denoising(unet_model, test_dataset, 123*i)" ] }, { "cell_type": "markdown", - "id": "076d4eff", + "id": "0abbf186", "metadata": {}, "source": [ "

    \n", @@ -1842,7 +1825,7 @@ }, { "cell_type": "markdown", - "id": "dc28b768", + "id": "531bfe36", "metadata": { "tags": [ "solution" @@ -1856,7 +1839,7 @@ }, { "cell_type": "markdown", - "id": "0d5775c4", + "id": "a3409c51", "metadata": { "tags": [ "solution" @@ -1870,7 +1853,7 @@ }, { "cell_type": "markdown", - "id": "85845f84", + "id": "347783c1", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1880,7 +1863,7 @@ }, { "cell_type": "markdown", - "id": "d5650b2d", + "id": "9074d884", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1891,7 +1874,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f8ddc55f", + "id": "9ec53c62", "metadata": {}, "outputs": [], "source": [ @@ -1912,7 +1895,7 @@ }, { "cell_type": "markdown", - "id": "76cb89f4", + "id": "9f241941", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" @@ -1921,7 +1904,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9a3d256b", + "id": "b7bd016c", "metadata": {}, "outputs": [], "source": [ @@ -1931,7 +1914,7 @@ }, { "cell_type": "markdown", - "id": "4da65639", + "id": "dc49133e", "metadata": {}, "source": [ "

    \n", @@ -1942,7 +1925,7 @@ }, { "cell_type": "markdown", - "id": "2c946b56", + "id": "b4197b25", "metadata": { "tags": [ "solution" @@ -1956,7 +1939,7 @@ }, { "cell_type": "markdown", - "id": "9bb6123c", + "id": "0bd27ffd", "metadata": { "tags": [ "solution" @@ -1970,7 +1953,7 @@ }, { "cell_type": "markdown", - "id": "87bec030", + "id": "6d2b670d", "metadata": {}, "source": [ "

    \n", @@ -1981,7 +1964,7 @@ }, { "cell_type": "markdown", - "id": "c0d369f0", + "id": "12882976", "metadata": { "tags": [ "solution" @@ -1995,7 +1978,7 @@ }, { "cell_type": "markdown", - "id": "22a47495", + "id": "b472427a", "metadata": { "tags": [ "solution" @@ -2010,7 +1993,7 @@ }, { "cell_type": "markdown", - "id": "474a797a", + "id": "8d9d850d", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2021,7 +2004,7 @@ { "cell_type": "code", "execution_count": null, - "id": "780d66d6", + "id": "00a1dc6e", "metadata": {}, "outputs": [], "source": [ @@ -2058,7 +2041,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fb8bc178", + "id": "5bdf014f", "metadata": {}, "outputs": [], "source": [ @@ -2069,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "37d6f25d", + "id": "ded5d280", "metadata": {}, "outputs": [], "source": [ @@ -2079,7 +2062,7 @@ }, { "cell_type": "markdown", - "id": "322c7b74", + "id": "c9aaa117", "metadata": {}, "source": [ "

    \n", @@ -2090,7 +2073,7 @@ }, { "cell_type": "markdown", - "id": "66fcabc5", + "id": "8fccf686", "metadata": { "tags": [ "solution" @@ -2109,7 +2092,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bae7c6c1", + "id": "039cd974", "metadata": {}, "outputs": [], "source": [ @@ -2146,7 +2129,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d8b38e2e", + "id": "91cbce9e", "metadata": {}, "outputs": [], "source": [ @@ -2157,7 +2140,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f9802b2", + "id": "794e0d53", "metadata": {}, "outputs": [], "source": [ @@ -2167,7 +2150,7 @@ }, { "cell_type": "markdown", - "id": "06a2a23c", + "id": "6f5dddbc", "metadata": {}, "source": [ "

    \n", @@ -2178,7 +2161,7 @@ }, { "cell_type": "markdown", - "id": "292b9ba3", + "id": "2fc4e5c7", "metadata": { "tags": [ "solution" From 1fcfd04d9e6abbe28d6ff09734aca012c12a133c Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Sat, 17 Aug 2024 18:33:24 +0100 Subject: [PATCH 28/51] Other attempt at fixing solution.py --- solution.py | 20 +------------------- 1 file changed, 1 insertion(+), 19 deletions(-) diff --git a/solution.py b/solution.py index b2f2f81..2566093 100644 --- a/solution.py +++ b/solution.py @@ -187,7 +187,6 @@ # Cast back to byte: tainted_train_dataset.data = tainted_train_dataset.data.type(torch.uint8) tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) - # - # visualize example 4s @@ -304,8 +303,6 @@ def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): history.append(loss.item()) pbar.update(1) return history - - # - # We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss. @@ -484,8 +481,6 @@ def predict(model, dataset): dataset_groundtruth.append(y_true) return np.array(dataset_prediction), np.array(dataset_groundtruth) - - # - # Now we call the predict method with the clean and tainted models on the clean and tainted datasets. @@ -543,7 +538,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): fig, ax = plt.subplots(figsize=figsize) ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30) ax.set_title(title) -#- +# - # Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below. @@ -674,8 +669,6 @@ def apply_integrated_gradients(test_input, model): ) return attributions - - # - # Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm. @@ -712,8 +705,6 @@ def visualize_integrated_gradients(test_input, model, plot_title): use_pyplot=False) figure.suptitle(plot_title, y=0.95) plt.tight_layout() - - # - # To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. @@ -739,7 +730,6 @@ def visualize_integrated_gradients(test_input, model, plot_title): # # The network looks at the center of the 7s, same for clean and tainted 7s. # It looks like a 7, it is a 7. :) -# # - # Now let's look at the attention of the tainted model! @@ -841,13 +831,9 @@ def visualize_integrated_gradients(test_input, model, plot_title): # A simple function to add noise to tensors: def add_noise(tensor, power=1.5): return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device) - - - # - # Next we will visualize a couple MNIST examples with and without noise. -# # + import matplotlib.pyplot as plt @@ -920,8 +906,6 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): # updates progress bar: pbar.update(1) return history - - # - # Here we choose hyperparameters and initialize the model and data loaders. @@ -974,7 +958,6 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): plt.xlabel('number of training examples seen') plt.ylabel('mean squared error loss') - # ### Check denoising performance # # We see that the training loss decreased, but let's apply the model to the test set to see how well it was able to recover the digits from the noisy images. @@ -1050,7 +1033,6 @@ def visualize_denoising(model, dataset, index): # - # Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results. -# for i in range(8): visualize_denoising(unet_model, fm_train_dataset, 123*i) From a9e9ff59fce71b159c2a65b7c3e4e11cfd675c9f Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 17:34:09 +0000 Subject: [PATCH 29/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 304 ++++++++++++++++++++++----------------- solution.ipynb | 382 +++++++++++++++++++++++++++---------------------- 2 files changed, 383 insertions(+), 303 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 639a784..f58cf52 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "adda9842", + "id": "32b1e9f1", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "e5d7e30e", + "id": "a3c84efc", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "f6dae011", + "id": "664ba6f6", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "76ccfd8d", + "id": "aa09118c", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "5b568cb9", + "id": "c2ff3769", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "839f5e5d", + "id": "9ad22ce4", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "66fe78ff", + "id": "ae4bf898", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a95679b1", + "id": "49be270b", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f81bdd3d", + "id": "134f9210", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "f4cb3dc1", + "id": "468c1859", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2bedcac3", + "id": "e42789cb", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cbf5e737", + "id": "810977f7", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "17c5d34f", + "id": "c35f41e3", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "e8f04799", + "id": "af37ccef", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "c3f572ee", + "id": "2d465f59", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "2fabdefb", + "id": "a8431945", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1f111005", + "id": "d4bb8cec", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "f7826fb4", + "id": "3d71a89a", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c8213ead", + "id": "b673baf2", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "cd33949c", + "id": "1b153aa9", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "434e7f07", + "id": "bd299f0c", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "e55e4b7b", + "id": "1b9cb99d", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0840fe88", + "id": "d4e0464b", "metadata": {}, "outputs": [], "source": [ @@ -289,13 +289,13 @@ "\n", "# Cast back to byte:\n", "tainted_train_dataset.data = tainted_train_dataset.data.type(torch.uint8) \n", - "tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) \n" + "tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) " ] }, { "cell_type": "code", "execution_count": null, - "id": "5e2c971b", + "id": "0d4d3bf4", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "0c80e649", + "id": "dc513b3b", "metadata": {}, "source": [ "

    \n", @@ -329,7 +329,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b7e6d2fa", + "id": "7be1949a", "metadata": {}, "outputs": [], "source": [ @@ -343,7 +343,7 @@ }, { "cell_type": "markdown", - "id": "5ce4fcf6", + "id": "e4bf92fc", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -352,8 +352,11 @@ { "cell_type": "code", "execution_count": null, - "id": "351d6d2b", - "metadata": {}, + "id": "f72635e7", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from tqdm import tqdm\n", @@ -377,7 +380,7 @@ }, { "cell_type": "markdown", - "id": "af1789c1", + "id": "7011f77b", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -386,7 +389,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d940e32c", + "id": "274f60f1", "metadata": {}, "outputs": [], "source": [ @@ -405,7 +408,7 @@ }, { "cell_type": "markdown", - "id": "a39797b5", + "id": "359def48", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -414,7 +417,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a516acac", + "id": "240cf939", "metadata": {}, "outputs": [], "source": [ @@ -442,7 +445,7 @@ }, { "cell_type": "markdown", - "id": "3731d055", + "id": "664c2725", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -451,7 +454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73f9588f", + "id": "4d8bdc2d", "metadata": {}, "outputs": [], "source": [ @@ -465,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "478a64fc", + "id": "644c5b7e", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -474,7 +477,7 @@ { "cell_type": "code", "execution_count": null, - "id": "31498d2a", + "id": "b140b2a3", "metadata": {}, "outputs": [], "source": [ @@ -507,7 +510,7 @@ }, { "cell_type": "markdown", - "id": "a12b2049", + "id": "0b0f8da2", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -516,7 +519,7 @@ { "cell_type": "code", "execution_count": null, - "id": "36d68857", + "id": "25259f93", "metadata": {}, "outputs": [], "source": [ @@ -531,7 +534,7 @@ }, { "cell_type": "markdown", - "id": "0f0f81c9", + "id": "c19bdd9b", "metadata": {}, "source": [ "

    \n", @@ -542,7 +545,7 @@ }, { "cell_type": "markdown", - "id": "1b6db647", + "id": "5fde5f20", "metadata": {}, "source": [ "

    \n", @@ -553,7 +556,7 @@ }, { "cell_type": "markdown", - "id": "3ea8c3b3", + "id": "ddca6e25", "metadata": {}, "source": [ "

    \n", @@ -564,7 +567,7 @@ }, { "cell_type": "markdown", - "id": "e3d2282a", + "id": "b2d75427", "metadata": {}, "source": [ "

    \n", @@ -576,7 +579,7 @@ }, { "cell_type": "markdown", - "id": "7ad0a46a", + "id": "627bf942", "metadata": {}, "source": [ "

    \n", @@ -591,7 +594,7 @@ }, { "cell_type": "markdown", - "id": "a7fde316", + "id": "c468a9dd", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -604,8 +607,11 @@ { "cell_type": "code", "execution_count": null, - "id": "5cd9755d", - "metadata": {}, + "id": "bd9c1d7d", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "import numpy as np\n", @@ -626,7 +632,7 @@ }, { "cell_type": "markdown", - "id": "ed703a9a", + "id": "288e65a0", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -635,7 +641,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1cff0217", + "id": "4ceb9f16", "metadata": {}, "outputs": [], "source": [ @@ -647,7 +653,7 @@ }, { "cell_type": "markdown", - "id": "42147aad", + "id": "7659d1e4", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -656,8 +662,11 @@ { "cell_type": "code", "execution_count": null, - "id": "7f12688e", - "metadata": {}, + "id": "c1cb1393", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from sklearn.metrics import confusion_matrix\n", @@ -704,25 +713,44 @@ " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", - " ax.set_title(title)\n", - "#-\n", - "\n", - "# Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below.\n", - "\n", + " ax.set_title(title)" + ] + }, + { + "cell_type": "markdown", + "id": "b8d1a35b", + "metadata": {}, + "source": [ + "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "607b7e66", + "metadata": {}, + "outputs": [], + "source": [ "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", "cm_analysis(true_labels, pred_tainted_clean, \"Tainted Model on Clean Data\")\n", - "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")\n", - "\n", - "#

    \n", - "# Task 3.1:

    \n", - "# For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", - "#
    " + "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")" ] }, { "cell_type": "markdown", - "id": "4c670669", + "id": "ea3626f2", + "metadata": {}, + "source": [ + "

    \n", + "Task 3.1:

    \n", + "For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "130e20e1", "metadata": {}, "source": [ "

    \n", @@ -733,7 +761,7 @@ }, { "cell_type": "markdown", - "id": "fe2557a8", + "id": "bf8ed81e", "metadata": {}, "source": [ "

    \n", @@ -744,7 +772,7 @@ }, { "cell_type": "markdown", - "id": "69e9728a", + "id": "40df4f2d", "metadata": {}, "source": [ "

    \n", @@ -755,7 +783,7 @@ }, { "cell_type": "markdown", - "id": "64b8d401", + "id": "c8002432", "metadata": {}, "source": [ "

    \n", @@ -767,7 +795,7 @@ }, { "cell_type": "markdown", - "id": "fb784988", + "id": "247ca0d8", "metadata": {}, "source": [ "

    \n", @@ -782,7 +810,7 @@ }, { "cell_type": "markdown", - "id": "5bb27c64", + "id": "bf20ad38", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -791,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "0f945022", + "id": "f9fc68ea", "metadata": {}, "source": [ "\n", @@ -801,8 +829,11 @@ { "cell_type": "code", "execution_count": null, - "id": "dd31c2f2", - "metadata": {}, + "id": "e6f72533", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from captum.attr import IntegratedGradients\n", @@ -834,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "0b840ebc", + "id": "21ae7cdc", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -843,8 +874,11 @@ { "cell_type": "code", "execution_count": null, - "id": "12264ead", - "metadata": {}, + "id": "a3a6d67c", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from captum.attr import visualization as viz\n", @@ -882,7 +916,7 @@ }, { "cell_type": "markdown", - "id": "45f1b911", + "id": "846c5348", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -893,7 +927,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d29a00d3", + "id": "caedad66", "metadata": {}, "outputs": [], "source": [ @@ -903,7 +937,7 @@ }, { "cell_type": "markdown", - "id": "8a1ae450", + "id": "c5fecf3e", "metadata": {}, "source": [ "

    \n", @@ -914,7 +948,7 @@ }, { "cell_type": "markdown", - "id": "531d5887", + "id": "2951b347", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -923,7 +957,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b8b0a00c", + "id": "0a61a125", "metadata": {}, "outputs": [], "source": [ @@ -933,7 +967,7 @@ }, { "cell_type": "markdown", - "id": "50cef6fe", + "id": "2487b221", "metadata": {}, "source": [ "

    \n", @@ -944,7 +978,7 @@ }, { "cell_type": "markdown", - "id": "316648a1", + "id": "b0796634", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -953,7 +987,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dae40772", + "id": "3dbd3bfe", "metadata": {}, "outputs": [], "source": [ @@ -965,7 +999,7 @@ }, { "cell_type": "markdown", - "id": "788ce5d3", + "id": "c644f8c1", "metadata": {}, "source": [ "

    \n", @@ -976,7 +1010,7 @@ }, { "cell_type": "markdown", - "id": "9fc7b89c", + "id": "1b20037d", "metadata": {}, "source": [ "

    \n", @@ -987,7 +1021,7 @@ }, { "cell_type": "markdown", - "id": "cc55a255", + "id": "b792e773", "metadata": {}, "source": [ "

    \n", @@ -1000,7 +1034,7 @@ }, { "cell_type": "markdown", - "id": "63756a82", + "id": "f15bb2c5", "metadata": {}, "source": [ "

    \n", @@ -1014,7 +1048,7 @@ }, { "cell_type": "markdown", - "id": "2a72d908", + "id": "600744b8", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1026,7 +1060,7 @@ }, { "cell_type": "markdown", - "id": "7ca0499e", + "id": "8acf0094", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1035,31 +1069,32 @@ { "cell_type": "code", "execution_count": null, - "id": "c72a2158", - "metadata": {}, + "id": "53309b1e", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "import torch\n", "\n", "# A simple function to add noise to tensors:\n", "def add_noise(tensor, power=1.5):\n", - " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)\n", - "\n", - "\n" + " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)" ] }, { "cell_type": "markdown", - "id": "f7a6ab29", + "id": "69f3a8b8", "metadata": {}, "source": [ - "Next we will visualize a couple MNIST examples with and without noise.\n" + "Next we will visualize a couple MNIST examples with and without noise." ] }, { "cell_type": "code", "execution_count": null, - "id": "6093f082", + "id": "66b599cc", "metadata": {}, "outputs": [], "source": [ @@ -1088,7 +1123,7 @@ }, { "cell_type": "markdown", - "id": "ec029fc7", + "id": "1f1fb79a", "metadata": {}, "source": [ "### UNet model\n", @@ -1098,7 +1133,7 @@ }, { "cell_type": "markdown", - "id": "1ead30f9", + "id": "55ef489e", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1107,8 +1142,11 @@ { "cell_type": "code", "execution_count": null, - "id": "631806b5", - "metadata": {}, + "id": "90639034", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from tqdm import tqdm\n", @@ -1155,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "b998875e", + "id": "56a26b76", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1164,7 +1202,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e9d76a45", + "id": "fd5b1452", "metadata": {}, "outputs": [], "source": [ @@ -1202,7 +1240,7 @@ }, { "cell_type": "markdown", - "id": "5e96c67c", + "id": "af683527", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1211,7 +1249,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4587f15d", + "id": "bdb97058", "metadata": {}, "outputs": [], "source": [ @@ -1222,7 +1260,7 @@ }, { "cell_type": "markdown", - "id": "cc56b362", + "id": "45f1e2d5", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1231,8 +1269,10 @@ { "cell_type": "code", "execution_count": null, - "id": "bcef2183", - "metadata": {}, + "id": "511dfa3a", + "metadata": { + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "# Loss Visualization\n", @@ -1245,7 +1285,7 @@ }, { "cell_type": "markdown", - "id": "ba61aa74", + "id": "900bbaed", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1256,7 +1296,7 @@ { "cell_type": "code", "execution_count": null, - "id": "370c076b", + "id": "caf3b358", "metadata": { "lines_to_next_cell": 1 }, @@ -1273,7 +1313,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3ad20390", + "id": "b8636a86", "metadata": { "lines_to_next_cell": 1 }, @@ -1299,7 +1339,7 @@ }, { "cell_type": "markdown", - "id": "7f54e077", + "id": "40ab4204", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1308,7 +1348,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b6754636", + "id": "a63651d3", "metadata": {}, "outputs": [], "source": [ @@ -1318,7 +1358,7 @@ }, { "cell_type": "markdown", - "id": "0abbf186", + "id": "9074c7cd", "metadata": {}, "source": [ "

    \n", @@ -1329,7 +1369,7 @@ }, { "cell_type": "markdown", - "id": "347783c1", + "id": "fe8c80c8", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1339,7 +1379,7 @@ }, { "cell_type": "markdown", - "id": "9074d884", + "id": "c1148bce", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1350,7 +1390,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ec53c62", + "id": "45175e2a", "metadata": {}, "outputs": [], "source": [ @@ -1371,16 +1411,16 @@ }, { "cell_type": "markdown", - "id": "9f241941", + "id": "088f7608", "metadata": {}, "source": [ - "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" + "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." ] }, { "cell_type": "code", "execution_count": null, - "id": "b7bd016c", + "id": "7ba8e696", "metadata": {}, "outputs": [], "source": [ @@ -1390,7 +1430,7 @@ }, { "cell_type": "markdown", - "id": "dc49133e", + "id": "c7028792", "metadata": {}, "source": [ "

    \n", @@ -1401,7 +1441,7 @@ }, { "cell_type": "markdown", - "id": "6d2b670d", + "id": "3165c296", "metadata": {}, "source": [ "

    \n", @@ -1412,7 +1452,7 @@ }, { "cell_type": "markdown", - "id": "8d9d850d", + "id": "e0b21688", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1423,7 +1463,7 @@ { "cell_type": "code", "execution_count": null, - "id": "00a1dc6e", + "id": "cf7a00f4", "metadata": {}, "outputs": [], "source": [ @@ -1460,7 +1500,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5bdf014f", + "id": "62d0d815", "metadata": {}, "outputs": [], "source": [ @@ -1471,7 +1511,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ded5d280", + "id": "3df9945d", "metadata": {}, "outputs": [], "source": [ @@ -1481,7 +1521,7 @@ }, { "cell_type": "markdown", - "id": "c9aaa117", + "id": "4ccdf0b4", "metadata": {}, "source": [ "

    \n", @@ -1493,7 +1533,7 @@ { "cell_type": "code", "execution_count": null, - "id": "039cd974", + "id": "b5220bdd", "metadata": {}, "outputs": [], "source": [ @@ -1530,7 +1570,7 @@ { "cell_type": "code", "execution_count": null, - "id": "91cbce9e", + "id": "2c223391", "metadata": {}, "outputs": [], "source": [ @@ -1541,7 +1581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "794e0d53", + "id": "ae1ce7a0", "metadata": {}, "outputs": [], "source": [ @@ -1551,7 +1591,7 @@ }, { "cell_type": "markdown", - "id": "6f5dddbc", + "id": "dd3d395e", "metadata": {}, "source": [ "

    \n", diff --git a/solution.ipynb b/solution.ipynb index 630e90a..d598cb2 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "adda9842", + "id": "32b1e9f1", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "e5d7e30e", + "id": "a3c84efc", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "f6dae011", + "id": "664ba6f6", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "76ccfd8d", + "id": "aa09118c", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "5b568cb9", + "id": "c2ff3769", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "839f5e5d", + "id": "9ad22ce4", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "66fe78ff", + "id": "ae4bf898", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a95679b1", + "id": "49be270b", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f81bdd3d", + "id": "134f9210", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "f4cb3dc1", + "id": "468c1859", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2bedcac3", + "id": "e42789cb", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cbf5e737", + "id": "810977f7", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "17c5d34f", + "id": "c35f41e3", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "556f8bac", + "id": "e1c3dca2", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "7dc94e89", + "id": "b39e1d1e", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "e8f04799", + "id": "af37ccef", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "74055b8a", + "id": "0d223612", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "c0e60d36", + "id": "d8a309dc", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "c3f572ee", + "id": "2d465f59", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "2fabdefb", + "id": "a8431945", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1f111005", + "id": "d4bb8cec", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "f7826fb4", + "id": "3d71a89a", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c8213ead", + "id": "b673baf2", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "cd33949c", + "id": "1b153aa9", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "434e7f07", + "id": "bd299f0c", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "e55e4b7b", + "id": "1b9cb99d", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0840fe88", + "id": "d4e0464b", "metadata": {}, "outputs": [], "source": [ @@ -356,13 +356,13 @@ "\n", "# Cast back to byte:\n", "tainted_train_dataset.data = tainted_train_dataset.data.type(torch.uint8) \n", - "tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) \n" + "tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) " ] }, { "cell_type": "code", "execution_count": null, - "id": "5e2c971b", + "id": "0d4d3bf4", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "0c80e649", + "id": "dc513b3b", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "f5fe74f8", + "id": "1de5c94e", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "e2feb73a", + "id": "f8347929", "metadata": { "tags": [ "solution" @@ -447,7 +447,7 @@ }, { "cell_type": "markdown", - "id": "6000419c", + "id": "ecf5740e", "metadata": { "tags": [ "solution" @@ -461,7 +461,7 @@ }, { "cell_type": "markdown", - "id": "a799bd0e", + "id": "6ea23472", "metadata": { "tags": [ "solution" @@ -497,7 +497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b7e6d2fa", + "id": "7be1949a", "metadata": {}, "outputs": [], "source": [ @@ -511,7 +511,7 @@ }, { "cell_type": "markdown", - "id": "5ce4fcf6", + "id": "e4bf92fc", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -520,8 +520,11 @@ { "cell_type": "code", "execution_count": null, - "id": "351d6d2b", - "metadata": {}, + "id": "f72635e7", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from tqdm import tqdm\n", @@ -545,7 +548,7 @@ }, { "cell_type": "markdown", - "id": "af1789c1", + "id": "7011f77b", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -554,7 +557,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d940e32c", + "id": "274f60f1", "metadata": {}, "outputs": [], "source": [ @@ -573,7 +576,7 @@ }, { "cell_type": "markdown", - "id": "a39797b5", + "id": "359def48", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -582,7 +585,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a516acac", + "id": "240cf939", "metadata": {}, "outputs": [], "source": [ @@ -610,7 +613,7 @@ }, { "cell_type": "markdown", - "id": "3731d055", + "id": "664c2725", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -619,7 +622,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73f9588f", + "id": "4d8bdc2d", "metadata": {}, "outputs": [], "source": [ @@ -633,7 +636,7 @@ }, { "cell_type": "markdown", - "id": "478a64fc", + "id": "644c5b7e", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -642,7 +645,7 @@ { "cell_type": "code", "execution_count": null, - "id": "31498d2a", + "id": "b140b2a3", "metadata": {}, "outputs": [], "source": [ @@ -675,7 +678,7 @@ }, { "cell_type": "markdown", - "id": "a12b2049", + "id": "0b0f8da2", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -684,7 +687,7 @@ { "cell_type": "code", "execution_count": null, - "id": "36d68857", + "id": "25259f93", "metadata": {}, "outputs": [], "source": [ @@ -699,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "0f0f81c9", + "id": "c19bdd9b", "metadata": {}, "source": [ "

    \n", @@ -710,7 +713,7 @@ }, { "cell_type": "markdown", - "id": "73e8d38a", + "id": "2b205eaf", "metadata": { "tags": [ "solution" @@ -724,7 +727,7 @@ }, { "cell_type": "markdown", - "id": "b606a428", + "id": "a2c3f7f4", "metadata": { "tags": [ "solution" @@ -738,7 +741,7 @@ }, { "cell_type": "markdown", - "id": "1b6db647", + "id": "5fde5f20", "metadata": {}, "source": [ "

    \n", @@ -749,7 +752,7 @@ }, { "cell_type": "markdown", - "id": "ecd13877", + "id": "1743a0ac", "metadata": { "tags": [ "solution" @@ -763,7 +766,7 @@ }, { "cell_type": "markdown", - "id": "53a4bae0", + "id": "7ff75eff", "metadata": { "tags": [ "solution" @@ -777,7 +780,7 @@ }, { "cell_type": "markdown", - "id": "3ea8c3b3", + "id": "ddca6e25", "metadata": {}, "source": [ "

    \n", @@ -788,7 +791,7 @@ }, { "cell_type": "markdown", - "id": "e5e82742", + "id": "6a265b4c", "metadata": { "tags": [ "solution" @@ -802,7 +805,7 @@ }, { "cell_type": "markdown", - "id": "a35ef600", + "id": "576f7fc8", "metadata": { "tags": [ "solution" @@ -816,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "e3d2282a", + "id": "b2d75427", "metadata": {}, "source": [ "

    \n", @@ -828,7 +831,7 @@ }, { "cell_type": "markdown", - "id": "7ad0a46a", + "id": "627bf942", "metadata": {}, "source": [ "

    \n", @@ -843,7 +846,7 @@ }, { "cell_type": "markdown", - "id": "a7fde316", + "id": "c468a9dd", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -856,8 +859,11 @@ { "cell_type": "code", "execution_count": null, - "id": "5cd9755d", - "metadata": {}, + "id": "bd9c1d7d", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "import numpy as np\n", @@ -878,7 +884,7 @@ }, { "cell_type": "markdown", - "id": "ed703a9a", + "id": "288e65a0", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -887,7 +893,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1cff0217", + "id": "4ceb9f16", "metadata": {}, "outputs": [], "source": [ @@ -899,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "42147aad", + "id": "7659d1e4", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -908,8 +914,11 @@ { "cell_type": "code", "execution_count": null, - "id": "7f12688e", - "metadata": {}, + "id": "c1cb1393", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from sklearn.metrics import confusion_matrix\n", @@ -956,25 +965,44 @@ " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", - " ax.set_title(title)\n", - "#-\n", - "\n", - "# Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below.\n", - "\n", + " ax.set_title(title)" + ] + }, + { + "cell_type": "markdown", + "id": "b8d1a35b", + "metadata": {}, + "source": [ + "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "607b7e66", + "metadata": {}, + "outputs": [], + "source": [ "cm_analysis(true_labels, pred_clean_clean, \"Clean Model on Clean Data\")\n", "cm_analysis(true_labels, pred_clean_tainted, \"Clean Model on Tainted Data\")\n", "cm_analysis(true_labels, pred_tainted_clean, \"Tainted Model on Clean Data\")\n", - "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")\n", - "\n", - "#

    \n", - "# Task 3.1:

    \n", - "# For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", - "#
    " + "cm_analysis(true_labels, pred_tainted_tainted, \"Tainted Model on Tainted Data\")" ] }, { "cell_type": "markdown", - "id": "649ab696", + "id": "ea3626f2", + "metadata": {}, + "source": [ + "

    \n", + "Task 3.1:

    \n", + "For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model?\n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "0453521d", "metadata": { "tags": [ "solution" @@ -988,7 +1016,7 @@ }, { "cell_type": "markdown", - "id": "5a6f0e64", + "id": "6e421289", "metadata": { "tags": [ "solution" @@ -1003,7 +1031,7 @@ }, { "cell_type": "markdown", - "id": "4c670669", + "id": "130e20e1", "metadata": {}, "source": [ "

    \n", @@ -1014,7 +1042,7 @@ }, { "cell_type": "markdown", - "id": "cd4c2361", + "id": "8013831b", "metadata": { "tags": [ "solution" @@ -1028,7 +1056,7 @@ }, { "cell_type": "markdown", - "id": "364d3cfa", + "id": "07bafeac", "metadata": { "tags": [ "solution" @@ -1042,7 +1070,7 @@ }, { "cell_type": "markdown", - "id": "fe2557a8", + "id": "bf8ed81e", "metadata": {}, "source": [ "

    \n", @@ -1053,7 +1081,7 @@ }, { "cell_type": "markdown", - "id": "8d3be153", + "id": "c0fe2ff0", "metadata": { "tags": [ "solution" @@ -1067,7 +1095,7 @@ }, { "cell_type": "markdown", - "id": "0a565fa6", + "id": "94e826a4", "metadata": { "tags": [ "solution" @@ -1084,7 +1112,7 @@ }, { "cell_type": "markdown", - "id": "69e9728a", + "id": "40df4f2d", "metadata": {}, "source": [ "

    \n", @@ -1095,7 +1123,7 @@ }, { "cell_type": "markdown", - "id": "95d27f55", + "id": "cda393d7", "metadata": { "tags": [ "solution" @@ -1109,7 +1137,7 @@ }, { "cell_type": "markdown", - "id": "d74f6e25", + "id": "970fea68", "metadata": { "tags": [ "solution" @@ -1129,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "64b8d401", + "id": "c8002432", "metadata": {}, "source": [ "

    \n", @@ -1141,7 +1169,7 @@ }, { "cell_type": "markdown", - "id": "fb784988", + "id": "247ca0d8", "metadata": {}, "source": [ "

    \n", @@ -1156,7 +1184,7 @@ }, { "cell_type": "markdown", - "id": "5bb27c64", + "id": "bf20ad38", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1165,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "0f945022", + "id": "f9fc68ea", "metadata": {}, "source": [ "\n", @@ -1175,8 +1203,11 @@ { "cell_type": "code", "execution_count": null, - "id": "dd31c2f2", - "metadata": {}, + "id": "e6f72533", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from captum.attr import IntegratedGradients\n", @@ -1208,7 +1239,7 @@ }, { "cell_type": "markdown", - "id": "0b840ebc", + "id": "21ae7cdc", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1217,8 +1248,11 @@ { "cell_type": "code", "execution_count": null, - "id": "12264ead", - "metadata": {}, + "id": "a3a6d67c", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from captum.attr import visualization as viz\n", @@ -1256,7 +1290,7 @@ }, { "cell_type": "markdown", - "id": "45f1b911", + "id": "846c5348", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1267,7 +1301,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d29a00d3", + "id": "caedad66", "metadata": {}, "outputs": [], "source": [ @@ -1277,7 +1311,7 @@ }, { "cell_type": "markdown", - "id": "8a1ae450", + "id": "c5fecf3e", "metadata": {}, "source": [ "

    \n", @@ -1288,7 +1322,7 @@ }, { "cell_type": "markdown", - "id": "153bfeaa", + "id": "bb08c804", "metadata": { "tags": [ "solution" @@ -1302,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "d397dcad", + "id": "0510e746", "metadata": { "tags": [ "solution" @@ -1312,12 +1346,12 @@ "**4.1 Answer from 2023 Students:**\n", "\n", "The network looks at the center of the 7s, same for clean and tainted 7s.\n", - "It looks like a 7, it is a 7. :)\n" + "It looks like a 7, it is a 7. :)" ] }, { "cell_type": "markdown", - "id": "531d5887", + "id": "2951b347", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1326,7 +1360,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b8b0a00c", + "id": "0a61a125", "metadata": {}, "outputs": [], "source": [ @@ -1336,7 +1370,7 @@ }, { "cell_type": "markdown", - "id": "50cef6fe", + "id": "2487b221", "metadata": {}, "source": [ "

    \n", @@ -1347,7 +1381,7 @@ }, { "cell_type": "markdown", - "id": "a13d1997", + "id": "c3db9a72", "metadata": { "tags": [ "solution" @@ -1361,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "6d780f65", + "id": "21b10c74", "metadata": { "tags": [ "solution" @@ -1379,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "316648a1", + "id": "b0796634", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1388,7 +1422,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dae40772", + "id": "3dbd3bfe", "metadata": {}, "outputs": [], "source": [ @@ -1400,7 +1434,7 @@ }, { "cell_type": "markdown", - "id": "788ce5d3", + "id": "c644f8c1", "metadata": {}, "source": [ "

    \n", @@ -1411,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "e520d4b1", + "id": "14425198", "metadata": { "tags": [ "solution" @@ -1425,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "3264bcef", + "id": "27db03bf", "metadata": { "tags": [ "solution" @@ -1442,7 +1476,7 @@ }, { "cell_type": "markdown", - "id": "9fc7b89c", + "id": "1b20037d", "metadata": {}, "source": [ "

    \n", @@ -1453,7 +1487,7 @@ }, { "cell_type": "markdown", - "id": "4db808a2", + "id": "c0677a4d", "metadata": { "tags": [ "solution" @@ -1467,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "4f3da547", + "id": "bd15604c", "metadata": { "tags": [ "solution" @@ -1483,7 +1517,7 @@ }, { "cell_type": "markdown", - "id": "cc55a255", + "id": "b792e773", "metadata": {}, "source": [ "

    \n", @@ -1496,7 +1530,7 @@ }, { "cell_type": "markdown", - "id": "63756a82", + "id": "f15bb2c5", "metadata": {}, "source": [ "

    \n", @@ -1510,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "2a72d908", + "id": "600744b8", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1522,7 +1556,7 @@ }, { "cell_type": "markdown", - "id": "7ca0499e", + "id": "8acf0094", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1531,31 +1565,32 @@ { "cell_type": "code", "execution_count": null, - "id": "c72a2158", - "metadata": {}, + "id": "53309b1e", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "import torch\n", "\n", "# A simple function to add noise to tensors:\n", "def add_noise(tensor, power=1.5):\n", - " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)\n", - "\n", - "\n" + " return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device)" ] }, { "cell_type": "markdown", - "id": "f7a6ab29", + "id": "69f3a8b8", "metadata": {}, "source": [ - "Next we will visualize a couple MNIST examples with and without noise.\n" + "Next we will visualize a couple MNIST examples with and without noise." ] }, { "cell_type": "code", "execution_count": null, - "id": "6093f082", + "id": "66b599cc", "metadata": {}, "outputs": [], "source": [ @@ -1584,7 +1619,7 @@ }, { "cell_type": "markdown", - "id": "ec029fc7", + "id": "1f1fb79a", "metadata": {}, "source": [ "### UNet model\n", @@ -1594,7 +1629,7 @@ }, { "cell_type": "markdown", - "id": "1ead30f9", + "id": "55ef489e", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1603,8 +1638,11 @@ { "cell_type": "code", "execution_count": null, - "id": "631806b5", - "metadata": {}, + "id": "90639034", + "metadata": { + "lines_to_end_of_cell_marker": 0, + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "from tqdm import tqdm\n", @@ -1651,7 +1689,7 @@ }, { "cell_type": "markdown", - "id": "b998875e", + "id": "56a26b76", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1660,7 +1698,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e9d76a45", + "id": "fd5b1452", "metadata": {}, "outputs": [], "source": [ @@ -1698,7 +1736,7 @@ }, { "cell_type": "markdown", - "id": "5e96c67c", + "id": "af683527", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1707,7 +1745,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4587f15d", + "id": "bdb97058", "metadata": {}, "outputs": [], "source": [ @@ -1718,7 +1756,7 @@ }, { "cell_type": "markdown", - "id": "cc56b362", + "id": "45f1e2d5", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1727,8 +1765,10 @@ { "cell_type": "code", "execution_count": null, - "id": "bcef2183", - "metadata": {}, + "id": "511dfa3a", + "metadata": { + "lines_to_next_cell": 1 + }, "outputs": [], "source": [ "# Loss Visualization\n", @@ -1741,7 +1781,7 @@ }, { "cell_type": "markdown", - "id": "ba61aa74", + "id": "900bbaed", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1752,7 +1792,7 @@ { "cell_type": "code", "execution_count": null, - "id": "370c076b", + "id": "caf3b358", "metadata": { "lines_to_next_cell": 1 }, @@ -1769,7 +1809,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3ad20390", + "id": "b8636a86", "metadata": { "lines_to_next_cell": 1 }, @@ -1795,7 +1835,7 @@ }, { "cell_type": "markdown", - "id": "7f54e077", + "id": "40ab4204", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1804,7 +1844,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b6754636", + "id": "a63651d3", "metadata": {}, "outputs": [], "source": [ @@ -1814,7 +1854,7 @@ }, { "cell_type": "markdown", - "id": "0abbf186", + "id": "9074c7cd", "metadata": {}, "source": [ "

    \n", @@ -1825,7 +1865,7 @@ }, { "cell_type": "markdown", - "id": "531bfe36", + "id": "b123e777", "metadata": { "tags": [ "solution" @@ -1839,7 +1879,7 @@ }, { "cell_type": "markdown", - "id": "a3409c51", + "id": "1544ae08", "metadata": { "tags": [ "solution" @@ -1853,7 +1893,7 @@ }, { "cell_type": "markdown", - "id": "347783c1", + "id": "fe8c80c8", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1863,7 +1903,7 @@ }, { "cell_type": "markdown", - "id": "9074d884", + "id": "c1148bce", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1874,7 +1914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ec53c62", + "id": "45175e2a", "metadata": {}, "outputs": [], "source": [ @@ -1895,16 +1935,16 @@ }, { "cell_type": "markdown", - "id": "9f241941", + "id": "088f7608", "metadata": {}, "source": [ - "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results.\n" + "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." ] }, { "cell_type": "code", "execution_count": null, - "id": "b7bd016c", + "id": "7ba8e696", "metadata": {}, "outputs": [], "source": [ @@ -1914,7 +1954,7 @@ }, { "cell_type": "markdown", - "id": "dc49133e", + "id": "c7028792", "metadata": {}, "source": [ "

    \n", @@ -1925,7 +1965,7 @@ }, { "cell_type": "markdown", - "id": "b4197b25", + "id": "2d3010f1", "metadata": { "tags": [ "solution" @@ -1939,7 +1979,7 @@ }, { "cell_type": "markdown", - "id": "0bd27ffd", + "id": "8f33e6a1", "metadata": { "tags": [ "solution" @@ -1953,7 +1993,7 @@ }, { "cell_type": "markdown", - "id": "6d2b670d", + "id": "3165c296", "metadata": {}, "source": [ "

    \n", @@ -1964,7 +2004,7 @@ }, { "cell_type": "markdown", - "id": "12882976", + "id": "f658d2a5", "metadata": { "tags": [ "solution" @@ -1978,7 +2018,7 @@ }, { "cell_type": "markdown", - "id": "b472427a", + "id": "d3b2dd9d", "metadata": { "tags": [ "solution" @@ -1993,7 +2033,7 @@ }, { "cell_type": "markdown", - "id": "8d9d850d", + "id": "e0b21688", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2004,7 +2044,7 @@ { "cell_type": "code", "execution_count": null, - "id": "00a1dc6e", + "id": "cf7a00f4", "metadata": {}, "outputs": [], "source": [ @@ -2041,7 +2081,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5bdf014f", + "id": "62d0d815", "metadata": {}, "outputs": [], "source": [ @@ -2052,7 +2092,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ded5d280", + "id": "3df9945d", "metadata": {}, "outputs": [], "source": [ @@ -2062,7 +2102,7 @@ }, { "cell_type": "markdown", - "id": "c9aaa117", + "id": "4ccdf0b4", "metadata": {}, "source": [ "

    \n", @@ -2073,7 +2113,7 @@ }, { "cell_type": "markdown", - "id": "8fccf686", + "id": "d7ebaa83", "metadata": { "tags": [ "solution" @@ -2092,7 +2132,7 @@ { "cell_type": "code", "execution_count": null, - "id": "039cd974", + "id": "b5220bdd", "metadata": {}, "outputs": [], "source": [ @@ -2129,7 +2169,7 @@ { "cell_type": "code", "execution_count": null, - "id": "91cbce9e", + "id": "2c223391", "metadata": {}, "outputs": [], "source": [ @@ -2140,7 +2180,7 @@ { "cell_type": "code", "execution_count": null, - "id": "794e0d53", + "id": "ae1ce7a0", "metadata": {}, "outputs": [], "source": [ @@ -2150,7 +2190,7 @@ }, { "cell_type": "markdown", - "id": "6f5dddbc", + "id": "dd3d395e", "metadata": {}, "source": [ "

    \n", @@ -2161,7 +2201,7 @@ }, { "cell_type": "markdown", - "id": "2fc4e5c7", + "id": "2795661c", "metadata": { "tags": [ "solution" From 7e69e436eba2541ba58bcb834a6e35d040b23cee Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 17:57:40 +0000 Subject: [PATCH 30/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 220 ++++++++++++++++++------------------ solution.ipynb | 296 ++++++++++++++++++++++++------------------------- 2 files changed, 258 insertions(+), 258 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index f58cf52..34f2e72 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "32b1e9f1", + "id": "bf60882f", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "a3c84efc", + "id": "16379354", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "664ba6f6", + "id": "f15756d2", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "aa09118c", + "id": "b2af2371", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "c2ff3769", + "id": "a8bc57b1", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ad22ce4", + "id": "2b7cf962", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "ae4bf898", + "id": "2719178a", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "49be270b", + "id": "219e93ca", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "134f9210", + "id": "0a668ed4", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "468c1859", + "id": "a83a6e17", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e42789cb", + "id": "9be3b992", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "810977f7", + "id": "d2b14f32", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "c35f41e3", + "id": "7e751131", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "af37ccef", + "id": "f777b340", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "2d465f59", + "id": "cadb1a78", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "a8431945", + "id": "c39c1e04", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d4bb8cec", + "id": "f7d6187d", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "3d71a89a", + "id": "2cd5ce3c", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b673baf2", + "id": "aa227c79", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "1b153aa9", + "id": "e8ed9edb", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bd299f0c", + "id": "d3fa996a", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "1b9cb99d", + "id": "84d9eb09", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d4e0464b", + "id": "3f75d980", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0d4d3bf4", + "id": "69fffdfd", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "dc513b3b", + "id": "47d54d19", "metadata": {}, "source": [ "

    \n", @@ -329,7 +329,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7be1949a", + "id": "07f10fc2", "metadata": {}, "outputs": [], "source": [ @@ -343,7 +343,7 @@ }, { "cell_type": "markdown", - "id": "e4bf92fc", + "id": "f3b8a86b", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -352,7 +352,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f72635e7", + "id": "8e4ca769", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -380,7 +380,7 @@ }, { "cell_type": "markdown", - "id": "7011f77b", + "id": "ad9838d3", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -389,7 +389,7 @@ { "cell_type": "code", "execution_count": null, - "id": "274f60f1", + "id": "e1477944", "metadata": {}, "outputs": [], "source": [ @@ -408,7 +408,7 @@ }, { "cell_type": "markdown", - "id": "359def48", + "id": "ffff9d69", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -417,7 +417,7 @@ { "cell_type": "code", "execution_count": null, - "id": "240cf939", + "id": "b1929164", "metadata": {}, "outputs": [], "source": [ @@ -445,7 +445,7 @@ }, { "cell_type": "markdown", - "id": "664c2725", + "id": "770ce064", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -454,7 +454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4d8bdc2d", + "id": "3ca72669", "metadata": {}, "outputs": [], "source": [ @@ -468,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "644c5b7e", + "id": "580c1a7d", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -477,7 +477,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b140b2a3", + "id": "fa0d050f", "metadata": {}, "outputs": [], "source": [ @@ -510,7 +510,7 @@ }, { "cell_type": "markdown", - "id": "0b0f8da2", + "id": "b701961e", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -519,7 +519,7 @@ { "cell_type": "code", "execution_count": null, - "id": "25259f93", + "id": "d091db4a", "metadata": {}, "outputs": [], "source": [ @@ -534,7 +534,7 @@ }, { "cell_type": "markdown", - "id": "c19bdd9b", + "id": "9304d723", "metadata": {}, "source": [ "

    \n", @@ -545,7 +545,7 @@ }, { "cell_type": "markdown", - "id": "5fde5f20", + "id": "d44c47c3", "metadata": {}, "source": [ "

    \n", @@ -556,7 +556,7 @@ }, { "cell_type": "markdown", - "id": "ddca6e25", + "id": "6bd2da5f", "metadata": {}, "source": [ "

    \n", @@ -567,7 +567,7 @@ }, { "cell_type": "markdown", - "id": "b2d75427", + "id": "18264fbf", "metadata": {}, "source": [ "

    \n", @@ -579,7 +579,7 @@ }, { "cell_type": "markdown", - "id": "627bf942", + "id": "b3b7f9c2", "metadata": {}, "source": [ "

    \n", @@ -594,7 +594,7 @@ }, { "cell_type": "markdown", - "id": "c468a9dd", + "id": "b94e2d18", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -607,7 +607,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bd9c1d7d", + "id": "8fe58739", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -632,7 +632,7 @@ }, { "cell_type": "markdown", - "id": "288e65a0", + "id": "a73780e7", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -641,7 +641,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4ceb9f16", + "id": "e243590a", "metadata": {}, "outputs": [], "source": [ @@ -653,7 +653,7 @@ }, { "cell_type": "markdown", - "id": "7659d1e4", + "id": "7d7a09bc", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -662,7 +662,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c1cb1393", + "id": "bb5200ab", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -718,7 +718,7 @@ }, { "cell_type": "markdown", - "id": "b8d1a35b", + "id": "53bd4de3", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -727,7 +727,7 @@ { "cell_type": "code", "execution_count": null, - "id": "607b7e66", + "id": "25fee912", "metadata": {}, "outputs": [], "source": [ @@ -739,7 +739,7 @@ }, { "cell_type": "markdown", - "id": "ea3626f2", + "id": "6d0bf6c8", "metadata": {}, "source": [ "

    \n", @@ -750,7 +750,7 @@ }, { "cell_type": "markdown", - "id": "130e20e1", + "id": "28667681", "metadata": {}, "source": [ "

    \n", @@ -761,7 +761,7 @@ }, { "cell_type": "markdown", - "id": "bf8ed81e", + "id": "0f86d04b", "metadata": {}, "source": [ "

    \n", @@ -772,7 +772,7 @@ }, { "cell_type": "markdown", - "id": "40df4f2d", + "id": "f93cc379", "metadata": {}, "source": [ "

    \n", @@ -783,7 +783,7 @@ }, { "cell_type": "markdown", - "id": "c8002432", + "id": "6a9043e3", "metadata": {}, "source": [ "

    \n", @@ -795,7 +795,7 @@ }, { "cell_type": "markdown", - "id": "247ca0d8", + "id": "9805e508", "metadata": {}, "source": [ "

    \n", @@ -810,7 +810,7 @@ }, { "cell_type": "markdown", - "id": "bf20ad38", + "id": "a1e7bb28", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -819,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "f9fc68ea", + "id": "a4b93f7e", "metadata": {}, "source": [ "\n", @@ -829,7 +829,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e6f72533", + "id": "73941dde", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "21ae7cdc", + "id": "95ef4039", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -874,7 +874,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a3a6d67c", + "id": "20b3fb8c", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -916,7 +916,7 @@ }, { "cell_type": "markdown", - "id": "846c5348", + "id": "a29f075c", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -927,7 +927,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caedad66", + "id": "90c24a75", "metadata": {}, "outputs": [], "source": [ @@ -937,7 +937,7 @@ }, { "cell_type": "markdown", - "id": "c5fecf3e", + "id": "a95e6ea6", "metadata": {}, "source": [ "

    \n", @@ -948,7 +948,7 @@ }, { "cell_type": "markdown", - "id": "2951b347", + "id": "fb5aa1ee", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -957,7 +957,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0a61a125", + "id": "e9fdb196", "metadata": {}, "outputs": [], "source": [ @@ -967,7 +967,7 @@ }, { "cell_type": "markdown", - "id": "2487b221", + "id": "aded297a", "metadata": {}, "source": [ "

    \n", @@ -978,7 +978,7 @@ }, { "cell_type": "markdown", - "id": "b0796634", + "id": "d34f9b60", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -987,7 +987,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3dbd3bfe", + "id": "8dd38855", "metadata": {}, "outputs": [], "source": [ @@ -999,7 +999,7 @@ }, { "cell_type": "markdown", - "id": "c644f8c1", + "id": "c9aeb142", "metadata": {}, "source": [ "

    \n", @@ -1010,7 +1010,7 @@ }, { "cell_type": "markdown", - "id": "1b20037d", + "id": "36e5828b", "metadata": {}, "source": [ "

    \n", @@ -1021,7 +1021,7 @@ }, { "cell_type": "markdown", - "id": "b792e773", + "id": "064672c8", "metadata": {}, "source": [ "

    \n", @@ -1034,7 +1034,7 @@ }, { "cell_type": "markdown", - "id": "f15bb2c5", + "id": "b65cc2e7", "metadata": {}, "source": [ "

    \n", @@ -1048,7 +1048,7 @@ }, { "cell_type": "markdown", - "id": "600744b8", + "id": "5780e4bc", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1060,7 +1060,7 @@ }, { "cell_type": "markdown", - "id": "8acf0094", + "id": "b7cc9821", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1069,7 +1069,7 @@ { "cell_type": "code", "execution_count": null, - "id": "53309b1e", + "id": "e0a0f094", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1085,7 +1085,7 @@ }, { "cell_type": "markdown", - "id": "69f3a8b8", + "id": "ed5dd4b4", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1094,7 +1094,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66b599cc", + "id": "d3d8add5", "metadata": {}, "outputs": [], "source": [ @@ -1123,7 +1123,7 @@ }, { "cell_type": "markdown", - "id": "1f1fb79a", + "id": "a0df181d", "metadata": {}, "source": [ "### UNet model\n", @@ -1133,7 +1133,7 @@ }, { "cell_type": "markdown", - "id": "55ef489e", + "id": "dca50e72", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1142,7 +1142,7 @@ { "cell_type": "code", "execution_count": null, - "id": "90639034", + "id": "92ede834", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1193,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "56a26b76", + "id": "209b28c7", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1202,7 +1202,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fd5b1452", + "id": "17ec01d8", "metadata": {}, "outputs": [], "source": [ @@ -1240,7 +1240,7 @@ }, { "cell_type": "markdown", - "id": "af683527", + "id": "7bdf6ad4", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1249,7 +1249,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bdb97058", + "id": "5069608b", "metadata": {}, "outputs": [], "source": [ @@ -1260,7 +1260,7 @@ }, { "cell_type": "markdown", - "id": "45f1e2d5", + "id": "1e177ca6", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1269,7 +1269,7 @@ { "cell_type": "code", "execution_count": null, - "id": "511dfa3a", + "id": "45c82696", "metadata": { "lines_to_next_cell": 1 }, @@ -1285,7 +1285,7 @@ }, { "cell_type": "markdown", - "id": "900bbaed", + "id": "fbbb5fe8", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1296,7 +1296,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caf3b358", + "id": "ee51f9f8", "metadata": { "lines_to_next_cell": 1 }, @@ -1313,7 +1313,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b8636a86", + "id": "1970324e", "metadata": { "lines_to_next_cell": 1 }, @@ -1339,7 +1339,7 @@ }, { "cell_type": "markdown", - "id": "40ab4204", + "id": "9610d944", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1348,7 +1348,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a63651d3", + "id": "9480bbe0", "metadata": {}, "outputs": [], "source": [ @@ -1358,7 +1358,7 @@ }, { "cell_type": "markdown", - "id": "9074c7cd", + "id": "e94e4844", "metadata": {}, "source": [ "

    \n", @@ -1369,7 +1369,7 @@ }, { "cell_type": "markdown", - "id": "fe8c80c8", + "id": "47f986c6", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1379,7 +1379,7 @@ }, { "cell_type": "markdown", - "id": "c1148bce", + "id": "e4999bbc", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1390,7 +1390,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45175e2a", + "id": "7d4d81b8", "metadata": {}, "outputs": [], "source": [ @@ -1411,7 +1411,7 @@ }, { "cell_type": "markdown", - "id": "088f7608", + "id": "1fc77452", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1420,7 +1420,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7ba8e696", + "id": "9c17a840", "metadata": {}, "outputs": [], "source": [ @@ -1430,7 +1430,7 @@ }, { "cell_type": "markdown", - "id": "c7028792", + "id": "b0bac410", "metadata": {}, "source": [ "

    \n", @@ -1441,7 +1441,7 @@ }, { "cell_type": "markdown", - "id": "3165c296", + "id": "d448fc30", "metadata": {}, "source": [ "

    \n", @@ -1452,7 +1452,7 @@ }, { "cell_type": "markdown", - "id": "e0b21688", + "id": "d10af7ae", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1463,7 +1463,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cf7a00f4", + "id": "5e8f51c7", "metadata": {}, "outputs": [], "source": [ @@ -1500,7 +1500,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62d0d815", + "id": "7340f846", "metadata": {}, "outputs": [], "source": [ @@ -1511,7 +1511,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3df9945d", + "id": "61a533e4", "metadata": {}, "outputs": [], "source": [ @@ -1521,7 +1521,7 @@ }, { "cell_type": "markdown", - "id": "4ccdf0b4", + "id": "360a7592", "metadata": {}, "source": [ "

    \n", @@ -1533,7 +1533,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b5220bdd", + "id": "900f538d", "metadata": {}, "outputs": [], "source": [ @@ -1570,7 +1570,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c223391", + "id": "26dfa520", "metadata": {}, "outputs": [], "source": [ @@ -1581,7 +1581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ae1ce7a0", + "id": "98b01dc5", "metadata": {}, "outputs": [], "source": [ @@ -1591,7 +1591,7 @@ }, { "cell_type": "markdown", - "id": "dd3d395e", + "id": "0f46240b", "metadata": {}, "source": [ "

    \n", diff --git a/solution.ipynb b/solution.ipynb index d598cb2..8a33239 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "32b1e9f1", + "id": "bf60882f", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "a3c84efc", + "id": "16379354", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "664ba6f6", + "id": "f15756d2", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "aa09118c", + "id": "b2af2371", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "c2ff3769", + "id": "a8bc57b1", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ad22ce4", + "id": "2b7cf962", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "ae4bf898", + "id": "2719178a", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "49be270b", + "id": "219e93ca", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "134f9210", + "id": "0a668ed4", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "468c1859", + "id": "a83a6e17", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e42789cb", + "id": "9be3b992", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "810977f7", + "id": "d2b14f32", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "c35f41e3", + "id": "7e751131", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "e1c3dca2", + "id": "489dc651", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "b39e1d1e", + "id": "2947bab8", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "af37ccef", + "id": "f777b340", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "0d223612", + "id": "fe66633b", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "d8a309dc", + "id": "0e89676c", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "2d465f59", + "id": "cadb1a78", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "a8431945", + "id": "c39c1e04", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d4bb8cec", + "id": "f7d6187d", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "3d71a89a", + "id": "2cd5ce3c", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b673baf2", + "id": "aa227c79", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "1b153aa9", + "id": "e8ed9edb", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bd299f0c", + "id": "d3fa996a", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "1b9cb99d", + "id": "84d9eb09", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d4e0464b", + "id": "3f75d980", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0d4d3bf4", + "id": "69fffdfd", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "dc513b3b", + "id": "47d54d19", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "1de5c94e", + "id": "8e3d684f", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "f8347929", + "id": "e0270be2", "metadata": { "tags": [ "solution" @@ -447,7 +447,7 @@ }, { "cell_type": "markdown", - "id": "ecf5740e", + "id": "1a872f87", "metadata": { "tags": [ "solution" @@ -461,7 +461,7 @@ }, { "cell_type": "markdown", - "id": "6ea23472", + "id": "1e3baa25", "metadata": { "tags": [ "solution" @@ -497,7 +497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7be1949a", + "id": "07f10fc2", "metadata": {}, "outputs": [], "source": [ @@ -511,7 +511,7 @@ }, { "cell_type": "markdown", - "id": "e4bf92fc", + "id": "f3b8a86b", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -520,7 +520,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f72635e7", + "id": "8e4ca769", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -548,7 +548,7 @@ }, { "cell_type": "markdown", - "id": "7011f77b", + "id": "ad9838d3", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -557,7 +557,7 @@ { "cell_type": "code", "execution_count": null, - "id": "274f60f1", + "id": "e1477944", "metadata": {}, "outputs": [], "source": [ @@ -576,7 +576,7 @@ }, { "cell_type": "markdown", - "id": "359def48", + "id": "ffff9d69", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -585,7 +585,7 @@ { "cell_type": "code", "execution_count": null, - "id": "240cf939", + "id": "b1929164", "metadata": {}, "outputs": [], "source": [ @@ -613,7 +613,7 @@ }, { "cell_type": "markdown", - "id": "664c2725", + "id": "770ce064", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -622,7 +622,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4d8bdc2d", + "id": "3ca72669", "metadata": {}, "outputs": [], "source": [ @@ -636,7 +636,7 @@ }, { "cell_type": "markdown", - "id": "644c5b7e", + "id": "580c1a7d", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -645,7 +645,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b140b2a3", + "id": "fa0d050f", "metadata": {}, "outputs": [], "source": [ @@ -678,7 +678,7 @@ }, { "cell_type": "markdown", - "id": "0b0f8da2", + "id": "b701961e", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -687,7 +687,7 @@ { "cell_type": "code", "execution_count": null, - "id": "25259f93", + "id": "d091db4a", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "c19bdd9b", + "id": "9304d723", "metadata": {}, "source": [ "

    \n", @@ -713,7 +713,7 @@ }, { "cell_type": "markdown", - "id": "2b205eaf", + "id": "9426c3a7", "metadata": { "tags": [ "solution" @@ -727,7 +727,7 @@ }, { "cell_type": "markdown", - "id": "a2c3f7f4", + "id": "f5f514ca", "metadata": { "tags": [ "solution" @@ -741,7 +741,7 @@ }, { "cell_type": "markdown", - "id": "5fde5f20", + "id": "d44c47c3", "metadata": {}, "source": [ "

    \n", @@ -752,7 +752,7 @@ }, { "cell_type": "markdown", - "id": "1743a0ac", + "id": "db77bad2", "metadata": { "tags": [ "solution" @@ -766,7 +766,7 @@ }, { "cell_type": "markdown", - "id": "7ff75eff", + "id": "d37379a1", "metadata": { "tags": [ "solution" @@ -780,7 +780,7 @@ }, { "cell_type": "markdown", - "id": "ddca6e25", + "id": "6bd2da5f", "metadata": {}, "source": [ "

    \n", @@ -791,7 +791,7 @@ }, { "cell_type": "markdown", - "id": "6a265b4c", + "id": "e93b4c50", "metadata": { "tags": [ "solution" @@ -805,7 +805,7 @@ }, { "cell_type": "markdown", - "id": "576f7fc8", + "id": "bac2b6b6", "metadata": { "tags": [ "solution" @@ -819,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "b2d75427", + "id": "18264fbf", "metadata": {}, "source": [ "

    \n", @@ -831,7 +831,7 @@ }, { "cell_type": "markdown", - "id": "627bf942", + "id": "b3b7f9c2", "metadata": {}, "source": [ "

    \n", @@ -846,7 +846,7 @@ }, { "cell_type": "markdown", - "id": "c468a9dd", + "id": "b94e2d18", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -859,7 +859,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bd9c1d7d", + "id": "8fe58739", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -884,7 +884,7 @@ }, { "cell_type": "markdown", - "id": "288e65a0", + "id": "a73780e7", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -893,7 +893,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4ceb9f16", + "id": "e243590a", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "7659d1e4", + "id": "7d7a09bc", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c1cb1393", + "id": "bb5200ab", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -970,7 +970,7 @@ }, { "cell_type": "markdown", - "id": "b8d1a35b", + "id": "53bd4de3", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -979,7 +979,7 @@ { "cell_type": "code", "execution_count": null, - "id": "607b7e66", + "id": "25fee912", "metadata": {}, "outputs": [], "source": [ @@ -991,7 +991,7 @@ }, { "cell_type": "markdown", - "id": "ea3626f2", + "id": "6d0bf6c8", "metadata": {}, "source": [ "

    \n", @@ -1002,7 +1002,7 @@ }, { "cell_type": "markdown", - "id": "0453521d", + "id": "fcd41d7a", "metadata": { "tags": [ "solution" @@ -1016,7 +1016,7 @@ }, { "cell_type": "markdown", - "id": "6e421289", + "id": "81483333", "metadata": { "tags": [ "solution" @@ -1031,7 +1031,7 @@ }, { "cell_type": "markdown", - "id": "130e20e1", + "id": "28667681", "metadata": {}, "source": [ "

    \n", @@ -1042,7 +1042,7 @@ }, { "cell_type": "markdown", - "id": "8013831b", + "id": "10ad6786", "metadata": { "tags": [ "solution" @@ -1056,7 +1056,7 @@ }, { "cell_type": "markdown", - "id": "07bafeac", + "id": "f5486c83", "metadata": { "tags": [ "solution" @@ -1070,7 +1070,7 @@ }, { "cell_type": "markdown", - "id": "bf8ed81e", + "id": "0f86d04b", "metadata": {}, "source": [ "

    \n", @@ -1081,7 +1081,7 @@ }, { "cell_type": "markdown", - "id": "c0fe2ff0", + "id": "8a5fa897", "metadata": { "tags": [ "solution" @@ -1095,7 +1095,7 @@ }, { "cell_type": "markdown", - "id": "94e826a4", + "id": "abcdb6e7", "metadata": { "tags": [ "solution" @@ -1112,7 +1112,7 @@ }, { "cell_type": "markdown", - "id": "40df4f2d", + "id": "f93cc379", "metadata": {}, "source": [ "

    \n", @@ -1123,7 +1123,7 @@ }, { "cell_type": "markdown", - "id": "cda393d7", + "id": "c9410393", "metadata": { "tags": [ "solution" @@ -1137,7 +1137,7 @@ }, { "cell_type": "markdown", - "id": "970fea68", + "id": "818ab1df", "metadata": { "tags": [ "solution" @@ -1157,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "c8002432", + "id": "6a9043e3", "metadata": {}, "source": [ "

    \n", @@ -1169,7 +1169,7 @@ }, { "cell_type": "markdown", - "id": "247ca0d8", + "id": "9805e508", "metadata": {}, "source": [ "

    \n", @@ -1184,7 +1184,7 @@ }, { "cell_type": "markdown", - "id": "bf20ad38", + "id": "a1e7bb28", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1193,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "f9fc68ea", + "id": "a4b93f7e", "metadata": {}, "source": [ "\n", @@ -1203,7 +1203,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e6f72533", + "id": "73941dde", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1239,7 +1239,7 @@ }, { "cell_type": "markdown", - "id": "21ae7cdc", + "id": "95ef4039", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1248,7 +1248,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a3a6d67c", + "id": "20b3fb8c", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1290,7 +1290,7 @@ }, { "cell_type": "markdown", - "id": "846c5348", + "id": "a29f075c", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1301,7 +1301,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caedad66", + "id": "90c24a75", "metadata": {}, "outputs": [], "source": [ @@ -1311,7 +1311,7 @@ }, { "cell_type": "markdown", - "id": "c5fecf3e", + "id": "a95e6ea6", "metadata": {}, "source": [ "

    \n", @@ -1322,7 +1322,7 @@ }, { "cell_type": "markdown", - "id": "bb08c804", + "id": "de4648ed", "metadata": { "tags": [ "solution" @@ -1336,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "0510e746", + "id": "8aaba99f", "metadata": { "tags": [ "solution" @@ -1351,7 +1351,7 @@ }, { "cell_type": "markdown", - "id": "2951b347", + "id": "fb5aa1ee", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1360,7 +1360,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0a61a125", + "id": "e9fdb196", "metadata": {}, "outputs": [], "source": [ @@ -1370,7 +1370,7 @@ }, { "cell_type": "markdown", - "id": "2487b221", + "id": "aded297a", "metadata": {}, "source": [ "

    \n", @@ -1381,7 +1381,7 @@ }, { "cell_type": "markdown", - "id": "c3db9a72", + "id": "1d4266dc", "metadata": { "tags": [ "solution" @@ -1395,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "21b10c74", + "id": "0472f7cc", "metadata": { "tags": [ "solution" @@ -1413,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "b0796634", + "id": "d34f9b60", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1422,7 +1422,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3dbd3bfe", + "id": "8dd38855", "metadata": {}, "outputs": [], "source": [ @@ -1434,7 +1434,7 @@ }, { "cell_type": "markdown", - "id": "c644f8c1", + "id": "c9aeb142", "metadata": {}, "source": [ "

    \n", @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "14425198", + "id": "030272c9", "metadata": { "tags": [ "solution" @@ -1459,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "27db03bf", + "id": "9658dff8", "metadata": { "tags": [ "solution" @@ -1476,7 +1476,7 @@ }, { "cell_type": "markdown", - "id": "1b20037d", + "id": "36e5828b", "metadata": {}, "source": [ "

    \n", @@ -1487,7 +1487,7 @@ }, { "cell_type": "markdown", - "id": "c0677a4d", + "id": "38ba9ad8", "metadata": { "tags": [ "solution" @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "bd15604c", + "id": "21ec8c22", "metadata": { "tags": [ "solution" @@ -1517,7 +1517,7 @@ }, { "cell_type": "markdown", - "id": "b792e773", + "id": "064672c8", "metadata": {}, "source": [ "

    \n", @@ -1530,7 +1530,7 @@ }, { "cell_type": "markdown", - "id": "f15bb2c5", + "id": "b65cc2e7", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "600744b8", + "id": "5780e4bc", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1556,7 +1556,7 @@ }, { "cell_type": "markdown", - "id": "8acf0094", + "id": "b7cc9821", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1565,7 +1565,7 @@ { "cell_type": "code", "execution_count": null, - "id": "53309b1e", + "id": "e0a0f094", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1581,7 +1581,7 @@ }, { "cell_type": "markdown", - "id": "69f3a8b8", + "id": "ed5dd4b4", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1590,7 +1590,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66b599cc", + "id": "d3d8add5", "metadata": {}, "outputs": [], "source": [ @@ -1619,7 +1619,7 @@ }, { "cell_type": "markdown", - "id": "1f1fb79a", + "id": "a0df181d", "metadata": {}, "source": [ "### UNet model\n", @@ -1629,7 +1629,7 @@ }, { "cell_type": "markdown", - "id": "55ef489e", + "id": "dca50e72", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1638,7 +1638,7 @@ { "cell_type": "code", "execution_count": null, - "id": "90639034", + "id": "92ede834", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1689,7 +1689,7 @@ }, { "cell_type": "markdown", - "id": "56a26b76", + "id": "209b28c7", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1698,7 +1698,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fd5b1452", + "id": "17ec01d8", "metadata": {}, "outputs": [], "source": [ @@ -1736,7 +1736,7 @@ }, { "cell_type": "markdown", - "id": "af683527", + "id": "7bdf6ad4", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1745,7 +1745,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bdb97058", + "id": "5069608b", "metadata": {}, "outputs": [], "source": [ @@ -1756,7 +1756,7 @@ }, { "cell_type": "markdown", - "id": "45f1e2d5", + "id": "1e177ca6", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1765,7 +1765,7 @@ { "cell_type": "code", "execution_count": null, - "id": "511dfa3a", + "id": "45c82696", "metadata": { "lines_to_next_cell": 1 }, @@ -1781,7 +1781,7 @@ }, { "cell_type": "markdown", - "id": "900bbaed", + "id": "fbbb5fe8", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1792,7 +1792,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caf3b358", + "id": "ee51f9f8", "metadata": { "lines_to_next_cell": 1 }, @@ -1809,7 +1809,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b8636a86", + "id": "1970324e", "metadata": { "lines_to_next_cell": 1 }, @@ -1835,7 +1835,7 @@ }, { "cell_type": "markdown", - "id": "40ab4204", + "id": "9610d944", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1844,7 +1844,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a63651d3", + "id": "9480bbe0", "metadata": {}, "outputs": [], "source": [ @@ -1854,7 +1854,7 @@ }, { "cell_type": "markdown", - "id": "9074c7cd", + "id": "e94e4844", "metadata": {}, "source": [ "

    \n", @@ -1865,7 +1865,7 @@ }, { "cell_type": "markdown", - "id": "b123e777", + "id": "64cd87b7", "metadata": { "tags": [ "solution" @@ -1879,7 +1879,7 @@ }, { "cell_type": "markdown", - "id": "1544ae08", + "id": "9c46f9e0", "metadata": { "tags": [ "solution" @@ -1893,7 +1893,7 @@ }, { "cell_type": "markdown", - "id": "fe8c80c8", + "id": "47f986c6", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1903,7 +1903,7 @@ }, { "cell_type": "markdown", - "id": "c1148bce", + "id": "e4999bbc", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1914,7 +1914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45175e2a", + "id": "7d4d81b8", "metadata": {}, "outputs": [], "source": [ @@ -1935,7 +1935,7 @@ }, { "cell_type": "markdown", - "id": "088f7608", + "id": "1fc77452", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1944,7 +1944,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7ba8e696", + "id": "9c17a840", "metadata": {}, "outputs": [], "source": [ @@ -1954,7 +1954,7 @@ }, { "cell_type": "markdown", - "id": "c7028792", + "id": "b0bac410", "metadata": {}, "source": [ "

    \n", @@ -1965,7 +1965,7 @@ }, { "cell_type": "markdown", - "id": "2d3010f1", + "id": "6183be0e", "metadata": { "tags": [ "solution" @@ -1979,7 +1979,7 @@ }, { "cell_type": "markdown", - "id": "8f33e6a1", + "id": "b0744655", "metadata": { "tags": [ "solution" @@ -1993,7 +1993,7 @@ }, { "cell_type": "markdown", - "id": "3165c296", + "id": "d448fc30", "metadata": {}, "source": [ "

    \n", @@ -2004,7 +2004,7 @@ }, { "cell_type": "markdown", - "id": "f658d2a5", + "id": "c9da045d", "metadata": { "tags": [ "solution" @@ -2018,7 +2018,7 @@ }, { "cell_type": "markdown", - "id": "d3b2dd9d", + "id": "7dd68313", "metadata": { "tags": [ "solution" @@ -2033,7 +2033,7 @@ }, { "cell_type": "markdown", - "id": "e0b21688", + "id": "d10af7ae", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2044,7 +2044,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cf7a00f4", + "id": "5e8f51c7", "metadata": {}, "outputs": [], "source": [ @@ -2081,7 +2081,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62d0d815", + "id": "7340f846", "metadata": {}, "outputs": [], "source": [ @@ -2092,7 +2092,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3df9945d", + "id": "61a533e4", "metadata": {}, "outputs": [], "source": [ @@ -2102,7 +2102,7 @@ }, { "cell_type": "markdown", - "id": "4ccdf0b4", + "id": "360a7592", "metadata": {}, "source": [ "

    \n", @@ -2113,7 +2113,7 @@ }, { "cell_type": "markdown", - "id": "d7ebaa83", + "id": "509f31e9", "metadata": { "tags": [ "solution" @@ -2132,7 +2132,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b5220bdd", + "id": "900f538d", "metadata": {}, "outputs": [], "source": [ @@ -2169,7 +2169,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c223391", + "id": "26dfa520", "metadata": {}, "outputs": [], "source": [ @@ -2180,7 +2180,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ae1ce7a0", + "id": "98b01dc5", "metadata": {}, "outputs": [], "source": [ @@ -2190,7 +2190,7 @@ }, { "cell_type": "markdown", - "id": "dd3d395e", + "id": "0f46240b", "metadata": {}, "source": [ "

    \n", @@ -2201,7 +2201,7 @@ }, { "cell_type": "markdown", - "id": "2795661c", + "id": "37ec8e5b", "metadata": { "tags": [ "solution" From 3af5978c32874bacf10d33ca7199dcae76104bda Mon Sep 17 00:00:00 2001 From: Anna <31920806+afoix@users.noreply.github.com> Date: Sat, 17 Aug 2024 19:07:00 +0100 Subject: [PATCH 31/51] Update README.md --- README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/README.md b/README.md index 3e348e0..3246fdd 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,12 @@ # Exercise 7: Failure Modes & Limits of Deep Learning +## Getting this repo + +If you are working from the super repository https://github.com/dlmbl/DL-MBL-2024, don't forget to update this submodule: +``` +git submodule update --init --recursive 07_failure_modes +``` + ## Goal In Exercise 7: Failure Modes and Limits of Deep Learning, we delve into understanding the limits and failure modes of neural networks, especially in the context of image classification. This exercise highlights how differences between tainted and clean training datasets as well as test datasets can affect the performance of neural networks in ways that we will try to understand. By tampering with image datasets and introducing extra visual information, the exercise aims to illustrate real-world scenarios where data collection inconsistencies can corrupt datasets. The goal is to investigate the internal reasoning of neural networks, and use tools like Integrated Gradients, which help in identifying crucial areas of an image that influence classification decisions. From 09c6e6568e7a1e7da9778ca6e5fc3df948db089f Mon Sep 17 00:00:00 2001 From: afoix Date: Sat, 17 Aug 2024 18:07:32 +0000 Subject: [PATCH 32/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 220 ++++++++++++++++++------------------ solution.ipynb | 296 ++++++++++++++++++++++++------------------------- 2 files changed, 258 insertions(+), 258 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 34f2e72..5eb4b6b 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "bf60882f", + "id": "360f0128", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "16379354", + "id": "6ee26090", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "f15756d2", + "id": "6b9ab5fa", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "b2af2371", + "id": "cb4ca93c", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "a8bc57b1", + "id": "b3352f38", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2b7cf962", + "id": "05d1cdc4", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "2719178a", + "id": "0e7556c2", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "219e93ca", + "id": "b5938a0c", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0a668ed4", + "id": "dd8e9f5e", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "a83a6e17", + "id": "b5e02f3e", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9be3b992", + "id": "9ae22911", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d2b14f32", + "id": "ee0b5b00", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "7e751131", + "id": "28460701", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "f777b340", + "id": "e5fccbc6", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "cadb1a78", + "id": "7a5b10c2", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "c39c1e04", + "id": "067c32bf", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f7d6187d", + "id": "711ba5ea", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "2cd5ce3c", + "id": "2f408424", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aa227c79", + "id": "eae78bfc", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "e8ed9edb", + "id": "3a654fb9", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d3fa996a", + "id": "a2344bfa", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "84d9eb09", + "id": "738a0daa", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3f75d980", + "id": "9d529b7f", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "69fffdfd", + "id": "59813208", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "47d54d19", + "id": "228375c9", "metadata": {}, "source": [ "

    \n", @@ -329,7 +329,7 @@ { "cell_type": "code", "execution_count": null, - "id": "07f10fc2", + "id": "1367725c", "metadata": {}, "outputs": [], "source": [ @@ -343,7 +343,7 @@ }, { "cell_type": "markdown", - "id": "f3b8a86b", + "id": "6cc01765", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -352,7 +352,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8e4ca769", + "id": "7096978a", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -380,7 +380,7 @@ }, { "cell_type": "markdown", - "id": "ad9838d3", + "id": "ee66a125", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -389,7 +389,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e1477944", + "id": "79a8ebb1", "metadata": {}, "outputs": [], "source": [ @@ -408,7 +408,7 @@ }, { "cell_type": "markdown", - "id": "ffff9d69", + "id": "434c1304", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -417,7 +417,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b1929164", + "id": "f6a601b5", "metadata": {}, "outputs": [], "source": [ @@ -445,7 +445,7 @@ }, { "cell_type": "markdown", - "id": "770ce064", + "id": "cc9da181", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -454,7 +454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3ca72669", + "id": "a5a15f4d", "metadata": {}, "outputs": [], "source": [ @@ -468,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "580c1a7d", + "id": "ebf04363", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -477,7 +477,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fa0d050f", + "id": "e4604c9f", "metadata": {}, "outputs": [], "source": [ @@ -510,7 +510,7 @@ }, { "cell_type": "markdown", - "id": "b701961e", + "id": "fb44d8ab", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -519,7 +519,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d091db4a", + "id": "f50a36d2", "metadata": {}, "outputs": [], "source": [ @@ -534,7 +534,7 @@ }, { "cell_type": "markdown", - "id": "9304d723", + "id": "879f61db", "metadata": {}, "source": [ "

    \n", @@ -545,7 +545,7 @@ }, { "cell_type": "markdown", - "id": "d44c47c3", + "id": "9d96a21f", "metadata": {}, "source": [ "

    \n", @@ -556,7 +556,7 @@ }, { "cell_type": "markdown", - "id": "6bd2da5f", + "id": "f4a4dbc9", "metadata": {}, "source": [ "

    \n", @@ -567,7 +567,7 @@ }, { "cell_type": "markdown", - "id": "18264fbf", + "id": "566ac7f4", "metadata": {}, "source": [ "

    \n", @@ -579,7 +579,7 @@ }, { "cell_type": "markdown", - "id": "b3b7f9c2", + "id": "636aa5e8", "metadata": {}, "source": [ "

    \n", @@ -594,7 +594,7 @@ }, { "cell_type": "markdown", - "id": "b94e2d18", + "id": "3da445f5", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -607,7 +607,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8fe58739", + "id": "d226175c", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -632,7 +632,7 @@ }, { "cell_type": "markdown", - "id": "a73780e7", + "id": "fbe0211c", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -641,7 +641,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e243590a", + "id": "5f100206", "metadata": {}, "outputs": [], "source": [ @@ -653,7 +653,7 @@ }, { "cell_type": "markdown", - "id": "7d7a09bc", + "id": "905c5649", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -662,7 +662,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bb5200ab", + "id": "f7933374", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -718,7 +718,7 @@ }, { "cell_type": "markdown", - "id": "53bd4de3", + "id": "d632ec95", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -727,7 +727,7 @@ { "cell_type": "code", "execution_count": null, - "id": "25fee912", + "id": "3c9c3dd6", "metadata": {}, "outputs": [], "source": [ @@ -739,7 +739,7 @@ }, { "cell_type": "markdown", - "id": "6d0bf6c8", + "id": "ded428de", "metadata": {}, "source": [ "

    \n", @@ -750,7 +750,7 @@ }, { "cell_type": "markdown", - "id": "28667681", + "id": "de0f72d6", "metadata": {}, "source": [ "

    \n", @@ -761,7 +761,7 @@ }, { "cell_type": "markdown", - "id": "0f86d04b", + "id": "351701b9", "metadata": {}, "source": [ "

    \n", @@ -772,7 +772,7 @@ }, { "cell_type": "markdown", - "id": "f93cc379", + "id": "e5d75ced", "metadata": {}, "source": [ "

    \n", @@ -783,7 +783,7 @@ }, { "cell_type": "markdown", - "id": "6a9043e3", + "id": "1497dfcf", "metadata": {}, "source": [ "

    \n", @@ -795,7 +795,7 @@ }, { "cell_type": "markdown", - "id": "9805e508", + "id": "d164856f", "metadata": {}, "source": [ "

    \n", @@ -810,7 +810,7 @@ }, { "cell_type": "markdown", - "id": "a1e7bb28", + "id": "a1c9cc3c", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -819,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "a4b93f7e", + "id": "8eb2ca29", "metadata": {}, "source": [ "\n", @@ -829,7 +829,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73941dde", + "id": "3ecce80f", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "95ef4039", + "id": "7d8c6ab0", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -874,7 +874,7 @@ { "cell_type": "code", "execution_count": null, - "id": "20b3fb8c", + "id": "eda69015", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -916,7 +916,7 @@ }, { "cell_type": "markdown", - "id": "a29f075c", + "id": "7477880b", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -927,7 +927,7 @@ { "cell_type": "code", "execution_count": null, - "id": "90c24a75", + "id": "510a79e8", "metadata": {}, "outputs": [], "source": [ @@ -937,7 +937,7 @@ }, { "cell_type": "markdown", - "id": "a95e6ea6", + "id": "a3630c14", "metadata": {}, "source": [ "

    \n", @@ -948,7 +948,7 @@ }, { "cell_type": "markdown", - "id": "fb5aa1ee", + "id": "eb9d1d18", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -957,7 +957,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e9fdb196", + "id": "2848519c", "metadata": {}, "outputs": [], "source": [ @@ -967,7 +967,7 @@ }, { "cell_type": "markdown", - "id": "aded297a", + "id": "00ca9727", "metadata": {}, "source": [ "

    \n", @@ -978,7 +978,7 @@ }, { "cell_type": "markdown", - "id": "d34f9b60", + "id": "b5201d01", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -987,7 +987,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8dd38855", + "id": "88c99f85", "metadata": {}, "outputs": [], "source": [ @@ -999,7 +999,7 @@ }, { "cell_type": "markdown", - "id": "c9aeb142", + "id": "f00e90d6", "metadata": {}, "source": [ "

    \n", @@ -1010,7 +1010,7 @@ }, { "cell_type": "markdown", - "id": "36e5828b", + "id": "fe009c04", "metadata": {}, "source": [ "

    \n", @@ -1021,7 +1021,7 @@ }, { "cell_type": "markdown", - "id": "064672c8", + "id": "5c104bc2", "metadata": {}, "source": [ "

    \n", @@ -1034,7 +1034,7 @@ }, { "cell_type": "markdown", - "id": "b65cc2e7", + "id": "0496ee67", "metadata": {}, "source": [ "

    \n", @@ -1048,7 +1048,7 @@ }, { "cell_type": "markdown", - "id": "5780e4bc", + "id": "c4042dd7", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1060,7 +1060,7 @@ }, { "cell_type": "markdown", - "id": "b7cc9821", + "id": "f0ebb455", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1069,7 +1069,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0a0f094", + "id": "3b432c45", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1085,7 +1085,7 @@ }, { "cell_type": "markdown", - "id": "ed5dd4b4", + "id": "f504d3b2", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1094,7 +1094,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d3d8add5", + "id": "0f7b6318", "metadata": {}, "outputs": [], "source": [ @@ -1123,7 +1123,7 @@ }, { "cell_type": "markdown", - "id": "a0df181d", + "id": "410d3e85", "metadata": {}, "source": [ "### UNet model\n", @@ -1133,7 +1133,7 @@ }, { "cell_type": "markdown", - "id": "dca50e72", + "id": "46fe776e", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1142,7 +1142,7 @@ { "cell_type": "code", "execution_count": null, - "id": "92ede834", + "id": "21240f36", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1193,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "209b28c7", + "id": "d10dfc06", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1202,7 +1202,7 @@ { "cell_type": "code", "execution_count": null, - "id": "17ec01d8", + "id": "d3ba1854", "metadata": {}, "outputs": [], "source": [ @@ -1240,7 +1240,7 @@ }, { "cell_type": "markdown", - "id": "7bdf6ad4", + "id": "6df25e47", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1249,7 +1249,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5069608b", + "id": "c27d8fe1", "metadata": {}, "outputs": [], "source": [ @@ -1260,7 +1260,7 @@ }, { "cell_type": "markdown", - "id": "1e177ca6", + "id": "af8711f6", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1269,7 +1269,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45c82696", + "id": "167dda81", "metadata": { "lines_to_next_cell": 1 }, @@ -1285,7 +1285,7 @@ }, { "cell_type": "markdown", - "id": "fbbb5fe8", + "id": "88f97ac2", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1296,7 +1296,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ee51f9f8", + "id": "637b6cae", "metadata": { "lines_to_next_cell": 1 }, @@ -1313,7 +1313,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1970324e", + "id": "082eac8d", "metadata": { "lines_to_next_cell": 1 }, @@ -1339,7 +1339,7 @@ }, { "cell_type": "markdown", - "id": "9610d944", + "id": "ef8a5b09", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1348,7 +1348,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9480bbe0", + "id": "d46a204b", "metadata": {}, "outputs": [], "source": [ @@ -1358,7 +1358,7 @@ }, { "cell_type": "markdown", - "id": "e94e4844", + "id": "444cc55e", "metadata": {}, "source": [ "

    \n", @@ -1369,7 +1369,7 @@ }, { "cell_type": "markdown", - "id": "47f986c6", + "id": "e48cd78a", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1379,7 +1379,7 @@ }, { "cell_type": "markdown", - "id": "e4999bbc", + "id": "fddc42db", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1390,7 +1390,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7d4d81b8", + "id": "2c87207e", "metadata": {}, "outputs": [], "source": [ @@ -1411,7 +1411,7 @@ }, { "cell_type": "markdown", - "id": "1fc77452", + "id": "571a9903", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1420,7 +1420,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9c17a840", + "id": "e64bfe7d", "metadata": {}, "outputs": [], "source": [ @@ -1430,7 +1430,7 @@ }, { "cell_type": "markdown", - "id": "b0bac410", + "id": "a61b0c87", "metadata": {}, "source": [ "

    \n", @@ -1441,7 +1441,7 @@ }, { "cell_type": "markdown", - "id": "d448fc30", + "id": "e5799ebd", "metadata": {}, "source": [ "

    \n", @@ -1452,7 +1452,7 @@ }, { "cell_type": "markdown", - "id": "d10af7ae", + "id": "19a9496d", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1463,7 +1463,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5e8f51c7", + "id": "6d6e975f", "metadata": {}, "outputs": [], "source": [ @@ -1500,7 +1500,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7340f846", + "id": "0dec3e58", "metadata": {}, "outputs": [], "source": [ @@ -1511,7 +1511,7 @@ { "cell_type": "code", "execution_count": null, - "id": "61a533e4", + "id": "f564dbc2", "metadata": {}, "outputs": [], "source": [ @@ -1521,7 +1521,7 @@ }, { "cell_type": "markdown", - "id": "360a7592", + "id": "bae2762b", "metadata": {}, "source": [ "

    \n", @@ -1533,7 +1533,7 @@ { "cell_type": "code", "execution_count": null, - "id": "900f538d", + "id": "9fadbc9b", "metadata": {}, "outputs": [], "source": [ @@ -1570,7 +1570,7 @@ { "cell_type": "code", "execution_count": null, - "id": "26dfa520", + "id": "efde43e6", "metadata": {}, "outputs": [], "source": [ @@ -1581,7 +1581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "98b01dc5", + "id": "aa0593b2", "metadata": {}, "outputs": [], "source": [ @@ -1591,7 +1591,7 @@ }, { "cell_type": "markdown", - "id": "0f46240b", + "id": "9a108c4a", "metadata": {}, "source": [ "

    \n", diff --git a/solution.ipynb b/solution.ipynb index 8a33239..efb9b32 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "bf60882f", + "id": "360f0128", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "16379354", + "id": "6ee26090", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "f15756d2", + "id": "6b9ab5fa", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "b2af2371", + "id": "cb4ca93c", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "a8bc57b1", + "id": "b3352f38", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2b7cf962", + "id": "05d1cdc4", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "2719178a", + "id": "0e7556c2", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "219e93ca", + "id": "b5938a0c", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0a668ed4", + "id": "dd8e9f5e", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "a83a6e17", + "id": "b5e02f3e", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9be3b992", + "id": "9ae22911", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d2b14f32", + "id": "ee0b5b00", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "7e751131", + "id": "28460701", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "489dc651", + "id": "c740c4a2", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "2947bab8", + "id": "8035425c", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "f777b340", + "id": "e5fccbc6", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "fe66633b", + "id": "9f3e84f3", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "0e89676c", + "id": "a489e898", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "cadb1a78", + "id": "7a5b10c2", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "c39c1e04", + "id": "067c32bf", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f7d6187d", + "id": "711ba5ea", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "2cd5ce3c", + "id": "2f408424", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aa227c79", + "id": "eae78bfc", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "e8ed9edb", + "id": "3a654fb9", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d3fa996a", + "id": "a2344bfa", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "84d9eb09", + "id": "738a0daa", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3f75d980", + "id": "9d529b7f", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "69fffdfd", + "id": "59813208", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "47d54d19", + "id": "228375c9", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "8e3d684f", + "id": "52efcdc3", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "e0270be2", + "id": "1424aa44", "metadata": { "tags": [ "solution" @@ -447,7 +447,7 @@ }, { "cell_type": "markdown", - "id": "1a872f87", + "id": "d40c25f5", "metadata": { "tags": [ "solution" @@ -461,7 +461,7 @@ }, { "cell_type": "markdown", - "id": "1e3baa25", + "id": "249dab4e", "metadata": { "tags": [ "solution" @@ -497,7 +497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "07f10fc2", + "id": "1367725c", "metadata": {}, "outputs": [], "source": [ @@ -511,7 +511,7 @@ }, { "cell_type": "markdown", - "id": "f3b8a86b", + "id": "6cc01765", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -520,7 +520,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8e4ca769", + "id": "7096978a", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -548,7 +548,7 @@ }, { "cell_type": "markdown", - "id": "ad9838d3", + "id": "ee66a125", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -557,7 +557,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e1477944", + "id": "79a8ebb1", "metadata": {}, "outputs": [], "source": [ @@ -576,7 +576,7 @@ }, { "cell_type": "markdown", - "id": "ffff9d69", + "id": "434c1304", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -585,7 +585,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b1929164", + "id": "f6a601b5", "metadata": {}, "outputs": [], "source": [ @@ -613,7 +613,7 @@ }, { "cell_type": "markdown", - "id": "770ce064", + "id": "cc9da181", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -622,7 +622,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3ca72669", + "id": "a5a15f4d", "metadata": {}, "outputs": [], "source": [ @@ -636,7 +636,7 @@ }, { "cell_type": "markdown", - "id": "580c1a7d", + "id": "ebf04363", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -645,7 +645,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fa0d050f", + "id": "e4604c9f", "metadata": {}, "outputs": [], "source": [ @@ -678,7 +678,7 @@ }, { "cell_type": "markdown", - "id": "b701961e", + "id": "fb44d8ab", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -687,7 +687,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d091db4a", + "id": "f50a36d2", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "9304d723", + "id": "879f61db", "metadata": {}, "source": [ "

    \n", @@ -713,7 +713,7 @@ }, { "cell_type": "markdown", - "id": "9426c3a7", + "id": "06724238", "metadata": { "tags": [ "solution" @@ -727,7 +727,7 @@ }, { "cell_type": "markdown", - "id": "f5f514ca", + "id": "8e806c11", "metadata": { "tags": [ "solution" @@ -741,7 +741,7 @@ }, { "cell_type": "markdown", - "id": "d44c47c3", + "id": "9d96a21f", "metadata": {}, "source": [ "

    \n", @@ -752,7 +752,7 @@ }, { "cell_type": "markdown", - "id": "db77bad2", + "id": "015b46c1", "metadata": { "tags": [ "solution" @@ -766,7 +766,7 @@ }, { "cell_type": "markdown", - "id": "d37379a1", + "id": "72948798", "metadata": { "tags": [ "solution" @@ -780,7 +780,7 @@ }, { "cell_type": "markdown", - "id": "6bd2da5f", + "id": "f4a4dbc9", "metadata": {}, "source": [ "

    \n", @@ -791,7 +791,7 @@ }, { "cell_type": "markdown", - "id": "e93b4c50", + "id": "f86f316d", "metadata": { "tags": [ "solution" @@ -805,7 +805,7 @@ }, { "cell_type": "markdown", - "id": "bac2b6b6", + "id": "b3fcbd0c", "metadata": { "tags": [ "solution" @@ -819,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "18264fbf", + "id": "566ac7f4", "metadata": {}, "source": [ "

    \n", @@ -831,7 +831,7 @@ }, { "cell_type": "markdown", - "id": "b3b7f9c2", + "id": "636aa5e8", "metadata": {}, "source": [ "

    \n", @@ -846,7 +846,7 @@ }, { "cell_type": "markdown", - "id": "b94e2d18", + "id": "3da445f5", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -859,7 +859,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8fe58739", + "id": "d226175c", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -884,7 +884,7 @@ }, { "cell_type": "markdown", - "id": "a73780e7", + "id": "fbe0211c", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -893,7 +893,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e243590a", + "id": "5f100206", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "7d7a09bc", + "id": "905c5649", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bb5200ab", + "id": "f7933374", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -970,7 +970,7 @@ }, { "cell_type": "markdown", - "id": "53bd4de3", + "id": "d632ec95", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -979,7 +979,7 @@ { "cell_type": "code", "execution_count": null, - "id": "25fee912", + "id": "3c9c3dd6", "metadata": {}, "outputs": [], "source": [ @@ -991,7 +991,7 @@ }, { "cell_type": "markdown", - "id": "6d0bf6c8", + "id": "ded428de", "metadata": {}, "source": [ "

    \n", @@ -1002,7 +1002,7 @@ }, { "cell_type": "markdown", - "id": "fcd41d7a", + "id": "ec41442d", "metadata": { "tags": [ "solution" @@ -1016,7 +1016,7 @@ }, { "cell_type": "markdown", - "id": "81483333", + "id": "76c3ad7a", "metadata": { "tags": [ "solution" @@ -1031,7 +1031,7 @@ }, { "cell_type": "markdown", - "id": "28667681", + "id": "de0f72d6", "metadata": {}, "source": [ "

    \n", @@ -1042,7 +1042,7 @@ }, { "cell_type": "markdown", - "id": "10ad6786", + "id": "7b4f4706", "metadata": { "tags": [ "solution" @@ -1056,7 +1056,7 @@ }, { "cell_type": "markdown", - "id": "f5486c83", + "id": "6ab61b46", "metadata": { "tags": [ "solution" @@ -1070,7 +1070,7 @@ }, { "cell_type": "markdown", - "id": "0f86d04b", + "id": "351701b9", "metadata": {}, "source": [ "

    \n", @@ -1081,7 +1081,7 @@ }, { "cell_type": "markdown", - "id": "8a5fa897", + "id": "d2bf534b", "metadata": { "tags": [ "solution" @@ -1095,7 +1095,7 @@ }, { "cell_type": "markdown", - "id": "abcdb6e7", + "id": "eda35306", "metadata": { "tags": [ "solution" @@ -1112,7 +1112,7 @@ }, { "cell_type": "markdown", - "id": "f93cc379", + "id": "e5d75ced", "metadata": {}, "source": [ "

    \n", @@ -1123,7 +1123,7 @@ }, { "cell_type": "markdown", - "id": "c9410393", + "id": "169c3758", "metadata": { "tags": [ "solution" @@ -1137,7 +1137,7 @@ }, { "cell_type": "markdown", - "id": "818ab1df", + "id": "b98545ca", "metadata": { "tags": [ "solution" @@ -1157,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "6a9043e3", + "id": "1497dfcf", "metadata": {}, "source": [ "

    \n", @@ -1169,7 +1169,7 @@ }, { "cell_type": "markdown", - "id": "9805e508", + "id": "d164856f", "metadata": {}, "source": [ "

    \n", @@ -1184,7 +1184,7 @@ }, { "cell_type": "markdown", - "id": "a1e7bb28", + "id": "a1c9cc3c", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1193,7 +1193,7 @@ }, { "cell_type": "markdown", - "id": "a4b93f7e", + "id": "8eb2ca29", "metadata": {}, "source": [ "\n", @@ -1203,7 +1203,7 @@ { "cell_type": "code", "execution_count": null, - "id": "73941dde", + "id": "3ecce80f", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1239,7 +1239,7 @@ }, { "cell_type": "markdown", - "id": "95ef4039", + "id": "7d8c6ab0", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1248,7 +1248,7 @@ { "cell_type": "code", "execution_count": null, - "id": "20b3fb8c", + "id": "eda69015", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1290,7 +1290,7 @@ }, { "cell_type": "markdown", - "id": "a29f075c", + "id": "7477880b", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1301,7 +1301,7 @@ { "cell_type": "code", "execution_count": null, - "id": "90c24a75", + "id": "510a79e8", "metadata": {}, "outputs": [], "source": [ @@ -1311,7 +1311,7 @@ }, { "cell_type": "markdown", - "id": "a95e6ea6", + "id": "a3630c14", "metadata": {}, "source": [ "

    \n", @@ -1322,7 +1322,7 @@ }, { "cell_type": "markdown", - "id": "de4648ed", + "id": "01bc3246", "metadata": { "tags": [ "solution" @@ -1336,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "8aaba99f", + "id": "45bad1fc", "metadata": { "tags": [ "solution" @@ -1351,7 +1351,7 @@ }, { "cell_type": "markdown", - "id": "fb5aa1ee", + "id": "eb9d1d18", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1360,7 +1360,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e9fdb196", + "id": "2848519c", "metadata": {}, "outputs": [], "source": [ @@ -1370,7 +1370,7 @@ }, { "cell_type": "markdown", - "id": "aded297a", + "id": "00ca9727", "metadata": {}, "source": [ "

    \n", @@ -1381,7 +1381,7 @@ }, { "cell_type": "markdown", - "id": "1d4266dc", + "id": "1e8ea9f0", "metadata": { "tags": [ "solution" @@ -1395,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "0472f7cc", + "id": "e13087b5", "metadata": { "tags": [ "solution" @@ -1413,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "d34f9b60", + "id": "b5201d01", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1422,7 +1422,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8dd38855", + "id": "88c99f85", "metadata": {}, "outputs": [], "source": [ @@ -1434,7 +1434,7 @@ }, { "cell_type": "markdown", - "id": "c9aeb142", + "id": "f00e90d6", "metadata": {}, "source": [ "

    \n", @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "030272c9", + "id": "a12e46ea", "metadata": { "tags": [ "solution" @@ -1459,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "9658dff8", + "id": "b8b3f1ce", "metadata": { "tags": [ "solution" @@ -1476,7 +1476,7 @@ }, { "cell_type": "markdown", - "id": "36e5828b", + "id": "fe009c04", "metadata": {}, "source": [ "

    \n", @@ -1487,7 +1487,7 @@ }, { "cell_type": "markdown", - "id": "38ba9ad8", + "id": "7b6c3d15", "metadata": { "tags": [ "solution" @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "21ec8c22", + "id": "18a5c29b", "metadata": { "tags": [ "solution" @@ -1517,7 +1517,7 @@ }, { "cell_type": "markdown", - "id": "064672c8", + "id": "5c104bc2", "metadata": {}, "source": [ "

    \n", @@ -1530,7 +1530,7 @@ }, { "cell_type": "markdown", - "id": "b65cc2e7", + "id": "0496ee67", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "5780e4bc", + "id": "c4042dd7", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1556,7 +1556,7 @@ }, { "cell_type": "markdown", - "id": "b7cc9821", + "id": "f0ebb455", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1565,7 +1565,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0a0f094", + "id": "3b432c45", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1581,7 +1581,7 @@ }, { "cell_type": "markdown", - "id": "ed5dd4b4", + "id": "f504d3b2", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1590,7 +1590,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d3d8add5", + "id": "0f7b6318", "metadata": {}, "outputs": [], "source": [ @@ -1619,7 +1619,7 @@ }, { "cell_type": "markdown", - "id": "a0df181d", + "id": "410d3e85", "metadata": {}, "source": [ "### UNet model\n", @@ -1629,7 +1629,7 @@ }, { "cell_type": "markdown", - "id": "dca50e72", + "id": "46fe776e", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1638,7 +1638,7 @@ { "cell_type": "code", "execution_count": null, - "id": "92ede834", + "id": "21240f36", "metadata": { "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 @@ -1689,7 +1689,7 @@ }, { "cell_type": "markdown", - "id": "209b28c7", + "id": "d10dfc06", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1698,7 +1698,7 @@ { "cell_type": "code", "execution_count": null, - "id": "17ec01d8", + "id": "d3ba1854", "metadata": {}, "outputs": [], "source": [ @@ -1736,7 +1736,7 @@ }, { "cell_type": "markdown", - "id": "7bdf6ad4", + "id": "6df25e47", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1745,7 +1745,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5069608b", + "id": "c27d8fe1", "metadata": {}, "outputs": [], "source": [ @@ -1756,7 +1756,7 @@ }, { "cell_type": "markdown", - "id": "1e177ca6", + "id": "af8711f6", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1765,7 +1765,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45c82696", + "id": "167dda81", "metadata": { "lines_to_next_cell": 1 }, @@ -1781,7 +1781,7 @@ }, { "cell_type": "markdown", - "id": "fbbb5fe8", + "id": "88f97ac2", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1792,7 +1792,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ee51f9f8", + "id": "637b6cae", "metadata": { "lines_to_next_cell": 1 }, @@ -1809,7 +1809,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1970324e", + "id": "082eac8d", "metadata": { "lines_to_next_cell": 1 }, @@ -1835,7 +1835,7 @@ }, { "cell_type": "markdown", - "id": "9610d944", + "id": "ef8a5b09", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1844,7 +1844,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9480bbe0", + "id": "d46a204b", "metadata": {}, "outputs": [], "source": [ @@ -1854,7 +1854,7 @@ }, { "cell_type": "markdown", - "id": "e94e4844", + "id": "444cc55e", "metadata": {}, "source": [ "

    \n", @@ -1865,7 +1865,7 @@ }, { "cell_type": "markdown", - "id": "64cd87b7", + "id": "03088233", "metadata": { "tags": [ "solution" @@ -1879,7 +1879,7 @@ }, { "cell_type": "markdown", - "id": "9c46f9e0", + "id": "a1a7985a", "metadata": { "tags": [ "solution" @@ -1893,7 +1893,7 @@ }, { "cell_type": "markdown", - "id": "47f986c6", + "id": "e48cd78a", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1903,7 +1903,7 @@ }, { "cell_type": "markdown", - "id": "e4999bbc", + "id": "fddc42db", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1914,7 +1914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7d4d81b8", + "id": "2c87207e", "metadata": {}, "outputs": [], "source": [ @@ -1935,7 +1935,7 @@ }, { "cell_type": "markdown", - "id": "1fc77452", + "id": "571a9903", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1944,7 +1944,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9c17a840", + "id": "e64bfe7d", "metadata": {}, "outputs": [], "source": [ @@ -1954,7 +1954,7 @@ }, { "cell_type": "markdown", - "id": "b0bac410", + "id": "a61b0c87", "metadata": {}, "source": [ "

    \n", @@ -1965,7 +1965,7 @@ }, { "cell_type": "markdown", - "id": "6183be0e", + "id": "ddf92ed5", "metadata": { "tags": [ "solution" @@ -1979,7 +1979,7 @@ }, { "cell_type": "markdown", - "id": "b0744655", + "id": "788f151e", "metadata": { "tags": [ "solution" @@ -1993,7 +1993,7 @@ }, { "cell_type": "markdown", - "id": "d448fc30", + "id": "e5799ebd", "metadata": {}, "source": [ "

    \n", @@ -2004,7 +2004,7 @@ }, { "cell_type": "markdown", - "id": "c9da045d", + "id": "4c912317", "metadata": { "tags": [ "solution" @@ -2018,7 +2018,7 @@ }, { "cell_type": "markdown", - "id": "7dd68313", + "id": "e5b75655", "metadata": { "tags": [ "solution" @@ -2033,7 +2033,7 @@ }, { "cell_type": "markdown", - "id": "d10af7ae", + "id": "19a9496d", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2044,7 +2044,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5e8f51c7", + "id": "6d6e975f", "metadata": {}, "outputs": [], "source": [ @@ -2081,7 +2081,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7340f846", + "id": "0dec3e58", "metadata": {}, "outputs": [], "source": [ @@ -2092,7 +2092,7 @@ { "cell_type": "code", "execution_count": null, - "id": "61a533e4", + "id": "f564dbc2", "metadata": {}, "outputs": [], "source": [ @@ -2102,7 +2102,7 @@ }, { "cell_type": "markdown", - "id": "360a7592", + "id": "bae2762b", "metadata": {}, "source": [ "

    \n", @@ -2113,7 +2113,7 @@ }, { "cell_type": "markdown", - "id": "509f31e9", + "id": "822949b4", "metadata": { "tags": [ "solution" @@ -2132,7 +2132,7 @@ { "cell_type": "code", "execution_count": null, - "id": "900f538d", + "id": "9fadbc9b", "metadata": {}, "outputs": [], "source": [ @@ -2169,7 +2169,7 @@ { "cell_type": "code", "execution_count": null, - "id": "26dfa520", + "id": "efde43e6", "metadata": {}, "outputs": [], "source": [ @@ -2180,7 +2180,7 @@ { "cell_type": "code", "execution_count": null, - "id": "98b01dc5", + "id": "aa0593b2", "metadata": {}, "outputs": [], "source": [ @@ -2190,7 +2190,7 @@ }, { "cell_type": "markdown", - "id": "0f46240b", + "id": "9a108c4a", "metadata": {}, "source": [ "

    \n", @@ -2201,7 +2201,7 @@ }, { "cell_type": "markdown", - "id": "37ec8e5b", + "id": "7e828f97", "metadata": { "tags": [ "solution" From 8f579c7b0f2da434da6bd44a89ec36d277644854 Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 09:51:57 -0400 Subject: [PATCH 33/51] Remove jupyter lab from README --- README.md | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 3246fdd..730dee7 100644 --- a/README.md +++ b/README.md @@ -73,8 +73,5 @@ Please run the setup script to create the environment for this exercise and down source setup.sh ``` -When you are ready to start the exercise, make sure you are in your base environment and then run jupyter lab. -```bash -mamba activate base -jupyter lab -``` +When you are ready to start the exercise, open the `exercise.ipynb` file in VSCode +and select the `07-failure-modes` kernel From a73770d6aa3a24b57e9c5b0f232845c0322aed45 Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 09:52:10 -0400 Subject: [PATCH 34/51] Make the intro in README a little shorter --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 730dee7..b70ca89 100644 --- a/README.md +++ b/README.md @@ -8,11 +8,11 @@ git submodule update --init --recursive 07_failure_modes ``` ## Goal -In Exercise 7: Failure Modes and Limits of Deep Learning, we delve into understanding the limits and failure modes of neural networks, especially in the context of image classification. This exercise highlights how differences between tainted and clean training datasets as well as test datasets can affect the performance of neural networks in ways that we will try to understand. By tampering with image datasets and introducing extra visual information, the exercise aims to illustrate real-world scenarios where data collection inconsistencies can corrupt datasets. The goal is to investigate the internal reasoning of neural networks, and use tools like Integrated Gradients, which help in identifying crucial areas of an image that influence classification decisions. +In Exercise 7: Failure Modes and Limits of Deep Learning, we delve into understanding the limits and failure modes of neural networks in the context of image classification. By tampering with image datasets and introducing extra visual information, the exercise mimics real-world scenarios where data collection inconsistencies can corrupt datasets. -The exercise involves creating and training neural networks on both tainted and clean datasets, examining how these networks handle local and global data corruptions. We will visualize the network's performance through confusion matrices and interpret the attention maps generated by Integrated Gradients. Additionally, the exercise explores how denoising networks cope with domain changes by training a UNet model on noisy MNIST data and testing it on both similar and different datasets like FashionMNIST. Through these activities, participants are encouraged to think deeply about neural network behavior, discuss their findings in groups, and reflect on the impact of dataset inconsistencies on model performance. +The exercise examines how neural networks handle local and global data corruptions. We will reason about a classification network's performance through confusion matrices, and use tools like Integrated Gradients to identify areas of an image that influence classification decisions. Additionally, the exercise explores how denoising networks cope with domain changes by training a UNet model on noisy MNIST data and testing it on both similar and different datasets like FashionMNIST. -In a broader sense, this exercise helps participants recognize the importance of dataset quality and consistency in training robust neural networks. By exploring these failure modes, participants gain insights into the internal workings of neural networks and learn how to diagnose and mitigate potential issues. This understanding is crucial for developing more reliable machine learning models and ensuring their effective application in real-world scenarios where data inconsistencies are common. +Through these activities, participants are encouraged to think deeply about neural network behavior, discuss their findings in groups, and reflect on the impact of dataset inconsistencies on model performance and robustness. By exploring failure modes, participants gain insights into the internal workings of neural networks and learn how to diagnose and mitigate issues that are common in real-world scendarios. ## Methodology From 2f69b54d07589915dc42f464d4ae7d480be2644c Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 09:52:52 -0400 Subject: [PATCH 35/51] Use conda in setup.sh --- setup.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/setup.sh b/setup.sh index e88e169..e4fd45d 100644 --- a/setup.sh +++ b/setup.sh @@ -1,13 +1,13 @@ # create mamba environment and activate it -mamba create -n 07-failure-modes python +conda create -n 07-failure-modes python eval "$(conda shell.bash hook)" conda activate 07-failure-modes # install the ipython kernel for running jupyterlab -mamba install -y ipykernel ipywidgets +conda install -y ipykernel ipywidgets # for TAs to format the notebooks -# mamba install jupytext black nbconvert +# conda install jupytext black nbconvert # install libraries needed for the exercise # model interpretability From ac50c960bf8e65345abbee1882f4963b3417c797 Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 09:55:58 -0400 Subject: [PATCH 36/51] Add -y to conda command in setup.sh --- setup.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.sh b/setup.sh index e4fd45d..a1cbf31 100644 --- a/setup.sh +++ b/setup.sh @@ -1,5 +1,5 @@ # create mamba environment and activate it -conda create -n 07-failure-modes python +conda create -n 07-failure-modes -y python eval "$(conda shell.bash hook)" conda activate 07-failure-modes From c201d2a127de7da2177faae5ddaeabada79c0b50 Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 09:57:19 -0400 Subject: [PATCH 37/51] Add gitignore for data directories --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..1403331 --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +mnist/ +fashion_mnist/ \ No newline at end of file From e75177f43059336078305cc20604ea5294e04a64 Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 16:29:07 -0400 Subject: [PATCH 38/51] Add a lot of newlines to stop cells merging together --- solution.py | 32 ++++++++++++++++++++++++++++---- 1 file changed, 28 insertions(+), 4 deletions(-) diff --git a/solution.py b/solution.py index 2566093..3852d8e 100644 --- a/solution.py +++ b/solution.py @@ -106,7 +106,7 @@ #

    # Task 1.1:

    -# We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data colleciton, for example in a hospital imaging environment or microscopy lab? +# We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data collection, for example in a hospital imaging environment or microscopy lab? #
    # + [markdown] tags=["solution"] @@ -237,7 +237,10 @@ # Prevention is easer than fixing after generation! # - PCA on metadata <3 to help detect such issues # - Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc) +# +# - +# #

    # Task 1.4:

    # Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset? @@ -252,13 +255,17 @@ # **1.4 Answer from 2023 Students** # # We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! +# +# - +# #

    # Checkpoint 1

    # # Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions! #
    +# #

    # Bonus Questions:

    # Note that we only added the white dot to the images of 7s and the grid to images of 4s, not all classes. @@ -286,7 +293,7 @@ # Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop. # + -from tqdm import tqdm +from tqdm.auto import tqdm # Training function: def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): @@ -303,6 +310,8 @@ def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): history.append(loss.item()) pbar.update(1) return history + + # - # We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss. @@ -481,6 +490,8 @@ def predict(model, dataset): dataset_groundtruth.append(y_true) return np.array(dataset_prediction), np.array(dataset_groundtruth) + + # - # Now we call the predict method with the clean and tainted models on the clean and tainted datasets. @@ -669,6 +680,8 @@ def apply_integrated_gradients(test_input, model): ) return attributions + + # - # Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm. @@ -705,6 +718,8 @@ def visualize_integrated_gradients(test_input, model, plot_title): use_pyplot=False) figure.suptitle(plot_title, y=0.95) plt.tight_layout() + + # - # To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. @@ -831,6 +846,8 @@ def visualize_integrated_gradients(test_input, model, plot_title): # A simple function to add noise to tensors: def add_noise(tensor, power=1.5): return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device) + + # - # Next we will visualize a couple MNIST examples with and without noise. @@ -906,6 +923,8 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): # updates progress bar: pbar.update(1) return history + + # - # Here we choose hyperparameters and initialize the model and data loaders. @@ -1120,7 +1139,7 @@ def visualize_denoising(model, dataset, index): # **5.4 Answer:** # # The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable). - +# # ### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data # # We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below) @@ -1171,7 +1190,10 @@ def visualize_denoising(model, dataset, index): # **5.5 Answer:** # # The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets. +# +# - +# #

    # Checkpoint 5

    #
      @@ -1179,10 +1201,12 @@ def visualize_denoising(model, dataset, index): #
    #
    +# #

    # Bonus Questions

    #
      -#
    1. Try training a FashionMNIST denoising network and applying it to MNIST. Or, try training a denoising network on both datasets and see how it works on each.
      2. #
    2. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
      3. #
    #
    + +# From ce04a0717b16fc6d63f752ad96dca87e677f6e41 Mon Sep 17 00:00:00 2001 From: Caroline Malin-Mayor Date: Sun, 18 Aug 2024 16:30:09 -0400 Subject: [PATCH 39/51] Use percent format to prevent cells merging together --- solution.py | 265 +++++++++++++++++++++++++++++++--------------------- 1 file changed, 158 insertions(+), 107 deletions(-) diff --git a/solution.py b/solution.py index 3852d8e..0e9cf02 100644 --- a/solution.py +++ b/solution.py @@ -1,10 +1,11 @@ # --- # jupyter: # jupytext: +# custom_cell_magics: kql # text_representation: # extension: .py -# format_name: light -# format_version: '1.5' +# format_name: percent +# format_version: '1.3' # jupytext_version: 1.16.4 # kernelspec: # display_name: Python [conda env:07-failure-modes] @@ -12,8 +13,10 @@ # name: conda-env-07-failure-modes-py # --- +# %% [markdown] # # Exercise 7: Failure Modes And Limits of Deep Learning +# %% [markdown] # In the following exercise, we explore the failure modes and limits of neural networks. # Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail. # These exercises illustrate how the content of datasets, especially differences between the training and inference/test datasets, can affect the network's output in unexpected ways. @@ -21,6 +24,7 @@ # While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the "internal reasoning" of the network as much as possible to discover failure modes, or situations in which the network does not perform well. # This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network "attention". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output. +# %% [markdown] # # ## Overview: # In this exercise you will... @@ -36,9 +40,11 @@ # Set your python kernel to 07-failure-modes #
    +# %% [markdown] # ### Acknowledgements # This notebook was created by Steffen Wolf, Jordao Bragantini, Jan Funke, and Loic Royer. Modified by Tri Nguyen, Igor Zubarev, and Morgan Schwartz for DL@MBL 2022, Caroline Malin-Mayor for DL@MBL 2023, and Anna Foix Romero for DL@MBL 2024. +# %% [markdown] # ### Data Loading # # The following will load the MNIST dataset, which already comes split into a training and testing dataset. @@ -46,7 +52,7 @@ # This data was already downloaded in the setup script. # Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html -# + +# %% import torchvision train_dataset = torchvision.datasets.MNIST('./mnist', train=True, download=False, @@ -62,31 +68,35 @@ torchvision.transforms.Normalize( (0.1307,), (0.3081,)) ])) -# - +# %% [markdown] # ### Part 1: Preparation of a Tainted Dataset # # In this section we will make small changes to specific classes of data in the MNIST dataset. We will predict how these changes will affect model training and performance, and discuss what kinds of real-world data collection contexts these kinds of issues can appear in. +# %% #Imports: import torch import numpy from scipy.ndimage import convolve import copy +# %% # Create copies so we do not modify the original datasets: tainted_train_dataset = copy.deepcopy(train_dataset) tainted_test_dataset = copy.deepcopy(test_dataset) +# %% [markdown] # ## Part 1.1: Local Corruption of Data # # First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corruped. +# %% # Add a white pixel in the bottom right of all images of 7's tainted_train_dataset.data[train_dataset.targets==7, 25, 25] = 255 tainted_test_dataset.data[test_dataset.targets==7, 25, 25] = 255 -# + +# %% import matplotlib.pyplot as plt plt.subplot(1,4,1) @@ -102,39 +112,39 @@ plt.axis('off') plt.imshow(tainted_train_dataset[29][0][0], cmap=plt.get_cmap('gray')) plt.show() -# - +# %% [markdown] #

    # Task 1.1:

    # We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data collection, for example in a hospital imaging environment or microscopy lab? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.1 Answer:** # # In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images. # # In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.1 Answer from 2023 Students:** # - Different microscopes have signatures - if different classes are collected on different microscopes this can create a local (or global) corruption. # - Dirty objective!!!!! (clean your stuff) # - Camera signature noise - some cameras generate local corruptions over time if you image for too long without recalibrating # - Medical context protocols for imaging changing in different places -# - +# %% [markdown] #

    # Task 1.2:

    # In your above examples, if you knew you had a local corruption or difference between images in different classes of your data, could you remove it? How? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.2 Answer** # # We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.2 Answer from 2023 Students** # - Segment and crop/mask out the corruption. TA Note: This can create new local corruptions :( # - Crop the region of interest for all classes @@ -145,21 +155,24 @@ # - For our 7 example - Make the white square black (carefully - for some images maybe it was white before corruption) # - Noise2Void your images # - Add more noise!? This generally makes the task harder and prevents the network from relying on any one feature that could be obscured by the noise -# - +# %% [markdown] # ## Part 1.2: Global Corrution of data # # Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s. +# %% [markdown] # You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues. +# %% # Cast to float tainted_train_dataset.data = tainted_train_dataset.data.type(torch.FloatTensor) tainted_test_dataset.data = tainted_test_dataset.data.type(torch.FloatTensor) +# %% [markdown] # Then we create the grid texture and visualize it. -# + +# %% # Create grid texture texture = numpy.zeros(tainted_test_dataset.data.shape[1:]) texture[::2,::2] = 80 @@ -168,18 +181,20 @@ plt.axis('off') plt.imshow(texture, cmap=plt.get_cmap('gray')) -# - +# %% [markdown] # Next we add the texture to all 4s in the train and test set. +# %% # Adding the texture to all images of 4's: tainted_train_dataset.data[train_dataset.targets==4] += texture tainted_test_dataset.data[test_dataset.targets==4] += texture +# %% [markdown] # After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. # Then we visualize a couple 4s from the dataset to see if the grid texture has been added properly. -# + +# %% # Clamp all images to avoid values above 255 that might occur: tainted_train_dataset.data = torch.clamp(tainted_train_dataset.data, 0, 255) tainted_test_dataset.data = torch.clamp(tainted_test_dataset.data, 0, 255) @@ -187,8 +202,8 @@ # Cast back to byte: tainted_train_dataset.data = tainted_train_dataset.data.type(torch.uint8) tainted_test_dataset.data = tainted_test_dataset.data.type(torch.uint8) -# - +# %% # visualize example 4s plt.subplot(1,4,1) plt.axis('off') @@ -204,12 +219,13 @@ plt.imshow(tainted_train_dataset[53][0][0], cmap=plt.get_cmap('gray')) plt.show() +# %% [markdown] #

    # Task 1.3:

    # Think of a realistic example of such a corruption that would affect only some classes of data. If you notice the differences between classes, could you remove it? How? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.3 Answer** # # A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact. @@ -218,7 +234,7 @@ # # But prevention remains the most effective way to produce high quality datasets. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.3 Answer from 2023 Students** # # Global Corruptions @@ -238,26 +254,26 @@ # - PCA on metadata <3 to help detect such issues # - Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc) # -# - +# %% [markdown] # #

    # Task 1.4:

    # Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.4 Answer:** # # The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **1.4 Answer from 2023 Students** # # We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! # -# - +# %% [markdown] # #

    # Checkpoint 1

    @@ -265,6 +281,7 @@ # Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions! #
    +# %% [markdown] # #

    # Bonus Questions:

    @@ -277,22 +294,23 @@ # If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section. #
    +# %% [markdown] # ### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data # # From Part 1, we have a clean dataset and a dataset that has been tainted with effects that simulate local and global effects that could happen in real collection scenarios. Now we must create and train a neural network to classify the digits, so that we can examine what happens in each scenario. -# + +# %% import torch from classifier.model import DenseModel device = torch.device("cuda" if torch.cuda.is_available() else "cpu") print(f'selected torch device: {device}') -# - +# %% [markdown] # Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop. -# + +# %% from tqdm.auto import tqdm # Training function: @@ -312,11 +330,10 @@ def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): return history -# - - +# %% [markdown] # We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss. -# + +# %% import torch.optim as optim import torch import torch.nn as nn @@ -328,11 +345,11 @@ def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): # Loss function: criterion = nn.CrossEntropyLoss() -# - +# %% [markdown] # Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same! -# + +# %% # Initialize the clean and tainted models model_clean = DenseModel(input_shape=(28, 28), num_classes=10) model_clean = model_clean.to(device) @@ -353,22 +370,22 @@ def init_weights(m): # Fixing seed with magical number and setting weights: torch.random.manual_seed(42) model_tainted.apply(init_weights) -# - +# %% [markdown] # Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility. -# + +# %% # Initialising dataloaders: train_loader_tainted = torch.utils.data.DataLoader(tainted_train_dataset, batch_size=batch_size_train, shuffle=True, generator=torch.Generator().manual_seed(42)) train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size_train, shuffle=True, generator=torch.Generator().manual_seed(42)) -# - +# %% [markdown] # Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later. -# + +# %% # We store history here: history = {"loss_tainted": [], "loss_clean": []} @@ -394,10 +411,11 @@ def init_weights(m): history["loss_tainted"]) print('model_tainted trained') -# - +# %% [markdown] # Now we visualize the loss history for the clean and tainted models. +# %% # Visualise the loss history: fig = plt.figure() plt.plot(history["loss_clean"], color='blue') @@ -406,60 +424,62 @@ def init_weights(m): plt.xlabel('number of training examples seen') plt.ylabel('negative log likelihood loss') +# %% [markdown] #

    # Task 2.1:

    # Why do you think the tainted network has lower training loss than the clean network? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **2.1 Answer:** # # As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **2.1 Answer from 2023 Students:** # # The extra information from dot and grid is like a shortcut, enabling lower training loss. -# - +# %% [markdown] #

    # Task 2.2:

    # Do you think the tainted network will be more accurate than the clean network when applied to the tainted test data? Why? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **2.2 Answer:** # # Yes, the tainted network will be more accurate than the clean network when applied to the tainted test data as it will leverage the corruption present in that test data, since it trained to do so. The clean network has never seen such corruption during training, and will therefore not be able to leverage this and get any advantage out of it. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **2.2 Answer from 2023 Students** # # Yes. It will use the extra info to be better at 4s and 7s! -# - +# %% [markdown] #

    # Task 2.3:

    # Do you think the tainted network will be more accurate than the clean network when applied to the clean test data? Why? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **2.3 Answer:** # # The tainted network is relying on grid patterns to detect 4s and on dots in the bottom right corner to detect 7s. Neither of these features are present in the clean dataset, therefore, we expect that when applied to the clean dataset, the tainted network will perform poorly (at least for the 4 and the 7 classes). -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **2.3 Answer from 2023 Students** # # No. Out of distribution is the issue. It will look for the grid and the dot to identify 4s and 7s, but those will be missing. -# - +# %% [markdown] #

    # Checkpoint 2

    # # Post to the course chat when you have reached Checkpoint 2. We will discuss our predictions! #
    +# %% [markdown] #

    # Bonus Questions:

    #
      @@ -469,13 +489,14 @@ def init_weights(m): #
    #
    +# %% [markdown] # ### Part 3: Examining the Results of the Clean and Tainted Networks # # Now that we have initialized our clean and tainted datasets and trained our models on them, it is time to examine how these models perform on the clean and tainted test sets! # # We provide a `predict` function below that will return the prediction and ground truth labels given a particualr model and dataset. -# + +# %% import numpy as np # predict the test dataset @@ -492,18 +513,19 @@ def predict(model, dataset): return np.array(dataset_prediction), np.array(dataset_groundtruth) -# - - +# %% [markdown] # Now we call the predict method with the clean and tainted models on the clean and tainted datasets. +# %% pred_clean_clean, true_labels = predict(model_clean, test_dataset) pred_clean_tainted, _ = predict(model_clean, tainted_test_dataset) pred_tainted_clean, _ = predict(model_tainted, test_dataset) pred_tainted_tainted, _ = predict(model_tainted, tainted_test_dataset) +# %% [markdown] # We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix. -# + +# %% from sklearn.metrics import confusion_matrix import seaborn as sns import pandas as pd @@ -549,78 +571,80 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): fig, ax = plt.subplots(figsize=figsize) ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30) ax.set_title(title) -# - +# %% [markdown] # Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below. +# %% cm_analysis(true_labels, pred_clean_clean, "Clean Model on Clean Data") cm_analysis(true_labels, pred_clean_tainted, "Clean Model on Tainted Data") cm_analysis(true_labels, pred_tainted_clean, "Tainted Model on Clean Data") cm_analysis(true_labels, pred_tainted_tainted, "Tainted Model on Tainted Data") +# %% [markdown] #

    # Task 3.1:

    # For the clean model and the clean dataset, which digit was least accurately predicted? What did the model predict instead? Why do you think these digits were confused by the model? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.1 Answer:** # # The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments). -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.1 Answer from 2023 Students** # # 5 is the least accurately predicted digit. It is most confused with 6 or 3. # Handwriting creates fives that look like sixes or threes. -# - +# %% [markdown] #

    # Task 3.2:

    # Does the tainted model on the tainted dataset perform better or worse than the clean model on the clean dataset? Which digits is it better or worse on? Why do you think that is the case? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.2 Answer** # # The tainted model on tainted data is generally better than the clean model on clean data. Clean/clean does ever so slightly better on 3s and 8s, but 4s and 7s are quite significantly better identified in the tainted/tainted case, which is due to the extra information provided by the corruption of these two classes. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.2 Answer from 2023 Students** # # Tainted WINS because it is better at 4 and 7 ;) -# - +# %% [markdown] #

    # Task 3.3:

    # For the clean model and the tainted dataset, was the local corruption on the 7s or the global corruption on the 4s harder for the model trained on clean data to deal with? Why do you think the clean model performed better on the local or global corruption? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.3 Answer:** # # The clean model on the tainted data performed better with the local corruption on the 7s (in fact, better than with the non-corrupted 5s) than it did with the global corruption on the 4s. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.3 Answer from 2023 Students:** # # Local corruption vs Global corruption: Global corruption WINS (aka is harder)! # # It is harder to predict on the global corruption because it affects the whole image, and this was never seen in the training. # It adds (structured) noise over the entire four. -# - +# %% [markdown] #

    # Task 3.4:

    # Did the tainted model perform worse on clean 7s or clean 4s? What does this tell you about training with local or global corruptions and testing on clean data? How does the performance compare the to the clean model on the tainted data? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.4 Answer:** # # The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **3.4 Answer from 2023 Students:** # # Clean 7s vs clean 4s: 4 WINS! (aka is worse) @@ -630,14 +654,15 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # Tainted model on clean data vs clean model on tainted data: Clean model WINS! (is better on tainted data than tained model on clean data) # # The clean model still has useful signal to work with in the tainted data. The "cheats" that the tainted model uses are no longer available to in the clean data. -# - +# %% [markdown] #

    # Checkpoint 3

    # # Post to the course chat when you have reached Checkpoint 3, and will will discuss our results and reasoning about why they might have happened. #
    +# %% [markdown] #

    # Bonus Questions:

    #
      @@ -647,14 +672,16 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): #
    #
    +# %% [markdown] # ### Part 4: Interpretation with Integrated Gradients # Perhaps you formed some hypotheses about why the clean and tainted models did better or worse on certain datasets in the previous section. Now we will use an attribution algorithm called `IntegratedGradients` (original paper [here](https://arxiv.org/pdf/1703.01365.pdf)) to learn more about the inner workings of each model. This algorithm analyses a specific image and class, and uses the gradients of the network to find the regions of the image that are most important for the classification. We will learn more about Integrated Gradients and its limitations in the Knowledge Extraction Lecture and Exercise. +# %% [markdown] # # Below is a function to apply integrated gradients to a given image, class, and model using the Captum library (API documentation at https://captum.ai/api/integrated_gradients.html). # -# + +# %% from captum.attr import IntegratedGradients def apply_integrated_gradients(test_input, model): @@ -682,11 +709,10 @@ def apply_integrated_gradients(test_input, model): return attributions -# - - +# %% [markdown] # Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm. -# + +# %% from captum.attr import visualization as viz def visualize_integrated_gradients(test_input, model, plot_title): @@ -720,49 +746,52 @@ def visualize_integrated_gradients(test_input, model, plot_title): plt.tight_layout() -# - - +# %% [markdown] # To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. # # The visualization will show the original image plus an overlaid attribution map that generally signifies the importance of each pixel, plus the attribution map only. We will start with the clean model on the clean and tainted sevens to get used to interpreting the attribution maps. # +# %% visualize_integrated_gradients(test_dataset[0], model_clean, "Clean Model on Clean 7") visualize_integrated_gradients(tainted_test_dataset[0], model_clean, "Clean Model on Tainted 7") +# %% [markdown] #

    # Task 4.1: Interpereting the Clean Model's Attention on 7s

    # Where did the clean model focus its attention for the clean and tainted 7s? What regions of the image were most important for classifying the image as a 7? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.1 Answer:** # # The clean model focus its attention to the 7 itself. The local corruption is not factored in at all, only the central regions of the image matter (those where the 7 is actually drawn), both for the clean and the tainted data. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.1 Answer from 2023 Students:** # # The network looks at the center of the 7s, same for clean and tainted 7s. # It looks like a 7, it is a 7. :) -# - +# %% [markdown] # Now let's look at the attention of the tainted model! +# %% visualize_integrated_gradients(tainted_test_dataset[0], model_tainted, "Tainted Model on Tainted 7") visualize_integrated_gradients(test_dataset[0], model_tainted, "Tainted Model on Clean 7") +# %% [markdown] #

    # Task 4.2: Interpereting the Tainted Model's Attention on 7s

    # Where did the tainted model focus its attention for the clean and tainted 7s? How was this different than the clean model? Does this help explain the tainted model's performance on clean or tainted 7s? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.2 Answer:** # # The tainted model only focuses on the dot in the tainted 7. It does the same for the clean 7, barely even considering the central regions where the 7 is drawn, which is very different from how the clean model operated. Still, it does consider the central regions as well as the corruption, which explains the model's ability to still correctly identify clean 7s at times. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.2 Answer from 2023 Students:** # # DOT @@ -770,52 +799,54 @@ def visualize_integrated_gradients(test_input, model, plot_title): # DOT DOT # # (It looked at the dot. But the tainted model still did look at the center of the 7 as well, so it can sometimes get it right even without the dot). -# - +# %% [markdown] # Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models. +# %% visualize_integrated_gradients(test_dataset[6], model_clean, "Clean Model on Clean 4") visualize_integrated_gradients(tainted_test_dataset[6], model_clean, "Clean Model on Tainted 4") visualize_integrated_gradients(tainted_test_dataset[6], model_tainted, "Tainted Model on Tainted 4") visualize_integrated_gradients(test_dataset[6], model_tainted, "Tainted Model on Clean 4") +# %% [markdown] #

    # Task 4.3: Interpereting the focus on 4s

    # Where did the tainted model focus its attention for the tainted and clean 4s? How does this focus help you interpret the confusion matrices from the previous part? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.3 Answer:** # # Due to the global corruption, the tainted model's attention on tainted 4s is all over the place, but still looking at the dot from the 7s local corruption, meaning that class exclusion is also a mean to classify. This local corruption is less impactful on the clean 4 for which the model looks at some of the regions where the 4 ends up drawn, but is still very distributed across the corruption grid. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.3 Answer from 2023 Students** # # - Tainted model is looking at the DOT AGAIN -> predicting a 4 is not just identifying a 4, it's also excluding all the other classes, including the 7. Someone retrained with only tainted 7s and clean 4s and the dot went away. # - Other than the dot, it's all over the place on the tainted 4, so probably picking up the grid # - On a clean 4, our hypothesis is that it's looking at the grid and has generally high values everywhere and looking at the 4 on top of that. # - Also, maybe it just did alright on this particular 4 -# - +# %% [markdown] #

    # Task 4.4: Reflecting on Integrated Gradients

    # Did you find the integrated gradients more useful for the global or local corruptions of the data? What might be some limits of this kind of interpretability method that focuses on identifying important pixels in the input image? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.4 Answer:** # # The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **4.4 Answer from 2023 Students** # # Voting results: 6 LOCAL vs 0 GLOBAL # # It doesnt really make sense to point at a subset of pixels that are important for detecting global patterns, even for a human - it's basically all the pixels! -# - +# %% [markdown] #

    # Checkpoint 4

    #
      @@ -823,6 +854,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): #
    #
    +# %% [markdown] #

    # Bonus Questions

    #
      @@ -831,6 +863,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): #
    #
    +# %% [markdown] # ## Part 5: Importance of using the right training data # # Now we will move on from image classification to denoising, and show why it is particularly important to ensure that your training and test data are from the same distribution for these kinds of networks. @@ -838,9 +871,10 @@ def visualize_integrated_gradients(test_input, model, plot_title): # For this exercise, we will first train a simple CNN model to denoise MNIST images of digits, and then apply it to the Fashion MNIST to see what happens when the training and inference data are mismatched. # +# %% [markdown] # First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it. -# + +# %% import torch # A simple function to add noise to tensors: @@ -848,11 +882,10 @@ def add_noise(tensor, power=1.5): return tensor * torch.rand(tensor.size()).to(tensor.device) ** power + 0.75*torch.randn(tensor.size()).to(tensor.device) -# - - +# %% [markdown] # Next we will visualize a couple MNIST examples with and without noise. -# + +# %% import matplotlib.pyplot as plt # Let's visualise MNIST images with noise: @@ -874,15 +907,16 @@ def show(index): # We pick 8 images to show: for i in range(8): show(123*i) -# - +# %% [markdown] # ### UNet model # # Let's try denoising with a UNet, "CARE-style". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. +# %% [markdown] # The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises. -# + +# %% from tqdm import tqdm def train_denoising_model(train_loader, model, criterion, optimizer, history): @@ -925,11 +959,10 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): return history -# - - +# %% [markdown] # Here we choose hyperparameters and initialize the model and data loaders. -# + +# %% from dlmbl_unet import UNet import torch.optim as optim import torch @@ -960,16 +993,19 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): # Train loader: train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size_train, shuffle=True) -# - +# %% [markdown] # Finally, we run the training loop! +# %% # Training loop: for epoch in range(n_epochs): train_denoising_model(train_loader, unet_model, criterion, optimizer, history) +# %% [markdown] # As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2. +# %% # Loss Visualization fig = plt.figure() plt.plot(history["loss"], color='blue') @@ -977,10 +1013,12 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): plt.xlabel('number of training examples seen') plt.ylabel('mean squared error loss') +# %% [markdown] # ### Check denoising performance # # We see that the training loss decreased, but let's apply the model to the test set to see how well it was able to recover the digits from the noisy images. +# %% def apply_denoising(image, model): # add batch and channel dimensions image = torch.unsqueeze(torch.unsqueeze(image, 0), 0) @@ -988,6 +1026,7 @@ def apply_denoising(image, model): # remove batch and channel dimensions before returning return prediction.detach().cpu()[0,0] +# %% # Displays: ground truth, noisy, and denoised images def visualize_denoising(model, dataset, index): orig_image = dataset[index][0][0] @@ -1005,37 +1044,41 @@ def visualize_denoising(model, dataset, index): plt.show() +# %% [markdown] # We pick 8 images to show: +# %% for i in range(8): visualize_denoising(unet_model, test_dataset, 123*i) +# %% [markdown] #

    # Task 5.1:

    # Did the denoising net trained on MNIST work well on unseen test data? What do you think will happen when we apply it to the Fashion-MNIST data? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.1 Answer:** # # The denoising MNIST did relatively well considering it extracted images which allows a human to identify a digit when it wasn't necessarily obvious from the noisy image. It has however been trained to look for digits. Applying it to Fashion-MNIST will possibly sucessfully "remove noise", but recovering objects that it hasn't seen before may not work as well. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.1 Answer from 2023 Students:** # # It does decently well, not perfect cause it's lots of noise -# - +# %% [markdown] # ### Apply trained model on 'wrong' data # # Apply the denoising model trained above to some example _noisy_ images derived from the Fashion-MNIST dataset. # +# %% [markdown] # ### Load the Fashion MNIST dataset # # Similar to the regular MNIST, we will use the pytorch FashionMNIST dataset. This was downloaded in the setup.sh script, so here we are just loading it into memory. -# + +# %% fm_train_dataset = torchvision.datasets.FashionMNIST('./fashion_mnist', train=True, download=False, transform=torchvision.transforms.Compose([ torchvision.transforms.ToTensor(), @@ -1049,51 +1092,53 @@ def visualize_denoising(model, dataset, index): torchvision.transforms.Normalize( (0.1307,), (0.3081,)) ])) -# - +# %% [markdown] # Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results. +# %% for i in range(8): visualize_denoising(unet_model, fm_train_dataset, 123*i) +# %% [markdown] #

    # Task 5.2:

    # What happened when the MNIST denoising model was applied to the FashionMNIST data? Why do you think the results look as they do? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.2 Answer:** # # The "noise" is apparently gone, however, the objects are hardly recognizable. Some look like they have been reshaped like digits in the process. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.2 Answer from 2023 Students:** # # BAD! Some of them kind of look like numbers. -# - +# %% [markdown] #

    # Task 5.3:

    # Can you imagine any real-world scenarios where a denoising model would change the content of an image? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.3 Answer:** # # If a denoising model is trained on data which does not appear in the data it is ultimatly used on, that new content will end up likely changed. A real worl example could be that of training a model on lots of non-dividing cells images, and use the model on new data which happens to contain some dividing cells. This could lead to the information being "denoised" away. -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.3 Answer from 2023** # # - Run on any out of distribution data # - Especially tricky if the data appears to be in distribution but has rare events. E.g. if the denoiser was trained on lots of cells that were never dividing and then was run on similar image with dividing cells, it might remove the dividing cell and replace with a single cell. -# - +# %% [markdown] # ### Train the denoiser on both MNIST and FashionMNIST # # In this section, we will perform the denoiser training once again, but this time on both MNIST and FashionMNIST datasets, and then try to apply the newly trained denoiser to a set of noisy test images. -# + +# %% import torch.optim as optim import torch @@ -1122,20 +1167,22 @@ def visualize_denoising(model, dataset, index): # Training loop: for epoch in range(n_epochs): train_denoising_model(train_loader, unet_model, criterion, optimizer, history) -# - +# %% for i in range(8): visualize_denoising(unet_model, test_dataset, 123*i) +# %% for i in range(8): visualize_denoising(unet_model, fm_train_dataset, 123*i) +# %% [markdown] #

    # Task 5.4:

    # How does the new denoiser perform compared to the one from the previous section? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.4 Answer:** # # The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable). @@ -1144,7 +1191,7 @@ def visualize_denoising(model, dataset, index): # # We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below) -# + +# %% import torch.optim as optim import torch @@ -1173,26 +1220,28 @@ def visualize_denoising(model, dataset, index): # Training loop: for epoch in range(n_epochs): train_denoising_model(train_loader, unet_model, criterion, optimizer, history) -# - +# %% for i in range(8): visualize_denoising(unet_model, test_dataset, 123*i) +# %% for i in range(8): visualize_denoising(unet_model, fm_train_dataset, 123*i) +# %% [markdown] #

    # Task 5.5:

    # How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other? #
    -# + [markdown] tags=["solution"] +# %% [markdown] tags=["solution"] # **5.5 Answer:** # # The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets. # -# - +# %% [markdown] # #

    # Checkpoint 5

    @@ -1201,6 +1250,7 @@ def visualize_denoising(model, dataset, index): # #
    +# %% [markdown] # #

    # Bonus Questions

    @@ -1209,4 +1259,5 @@ def visualize_denoising(model, dataset, index): # #
    +# %% [markdown] # From ca7f24cde18eb8af130fbefde90e83e9b5edb072 Mon Sep 17 00:00:00 2001 From: cmalinmayor Date: Sun, 18 Aug 2024 20:32:40 +0000 Subject: [PATCH 40/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 345 +++++++++++++++++++++++++----------------- solution.ipynb | 396 ++++++++++++++++++++++++++----------------------- 2 files changed, 419 insertions(+), 322 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 5eb4b6b..8e32095 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "360f0128", + "id": "f18a286a", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "6ee26090", + "id": "f5912014", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "6b9ab5fa", + "id": "07d654d1", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "cb4ca93c", + "id": "376853b9", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "b3352f38", + "id": "78fdf1a2", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "05d1cdc4", + "id": "ce294ab0", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "0e7556c2", + "id": "137bc0ef", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b5938a0c", + "id": "7c21829d", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dd8e9f5e", + "id": "ee658555", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "b5e02f3e", + "id": "da5b143b", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ae22911", + "id": "6e6fe0e0", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ee0b5b00", + "id": "b0bc0a60", "metadata": {}, "outputs": [], "source": [ @@ -172,18 +172,18 @@ }, { "cell_type": "markdown", - "id": "28460701", + "id": "ecf586b5", "metadata": {}, "source": [ "

    \n", "Task 1.1:

    \n", - "We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data colleciton, for example in a hospital imaging environment or microscopy lab?\n", + "We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data collection, for example in a hospital imaging environment or microscopy lab?\n", "
    " ] }, { "cell_type": "markdown", - "id": "e5fccbc6", + "id": "1a0fee85", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "7a5b10c2", + "id": "7e9dbdcc", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "067c32bf", + "id": "0b40ae2f", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "711ba5ea", + "id": "b99477e5", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "2f408424", + "id": "b609686c", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eae78bfc", + "id": "cd1b5f08", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "3a654fb9", + "id": "4ddf365a", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a2344bfa", + "id": "b771931b", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "738a0daa", + "id": "7e15dbb3", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9d529b7f", + "id": "e5c23396", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59813208", + "id": "c70c98ed", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "228375c9", + "id": "197fd91e", "metadata": {}, "source": [ "

    \n", @@ -326,10 +326,63 @@ "

    " ] }, + { + "cell_type": "markdown", + "id": "2c8d8392", + "metadata": {}, + "source": [ + "\n", + "

    \n", + "Task 1.4:

    \n", + "Given the changes we made to generate the tainted dataset, do you think a digit classification network trained on the tainted data will converge? Are the classes more or less distinct from each other than in the untainted dataset?\n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "d3c3a011", + "metadata": {}, + "source": [ + "\n", + "

    \n", + " Checkpoint 1

    \n", + "\n", + "Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions!\n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "268d8f77", + "metadata": {}, + "source": [ + "\n", + "

    \n", + " Bonus Questions:

    \n", + " Note that we only added the white dot to the images of 7s and the grid to images of 4s, not all classes.\n", + "
      \n", + "
    1. Consider a dataset with white dots on images of all digits: let's call it the all-dots data. How different is this from the original dataset? Are the classes more or less distinct from each other?
      2. \n", + "
    2. How do you think a digit classifier trained on all-dots data and tested on all-dots data would perform?
      3. \n", + "
    3. Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      4. \n", + "
    \n", + "If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section.\n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "19b3e9a5", + "metadata": {}, + "source": [ + "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", + "\n", + "From Part 1, we have a clean dataset and a dataset that has been tainted with effects that simulate local and global effects that could happen in real collection scenarios. Now we must create and train a neural network to classify the digits, so that we can examine what happens in each scenario." + ] + }, { "cell_type": "code", "execution_count": null, - "id": "1367725c", + "id": "caf5144a", "metadata": {}, "outputs": [], "source": [ @@ -343,7 +396,7 @@ }, { "cell_type": "markdown", - "id": "6cc01765", + "id": "3cb4972e", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -352,14 +405,11 @@ { "cell_type": "code", "execution_count": null, - "id": "7096978a", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "c7cd32d8", + "metadata": {}, "outputs": [], "source": [ - "from tqdm import tqdm\n", + "from tqdm.auto import tqdm\n", "\n", "# Training function:\n", "def train_mnist(model, train_loader, batch_size, criterion, optimizer, history):\n", @@ -380,7 +430,7 @@ }, { "cell_type": "markdown", - "id": "ee66a125", + "id": "cfaa20f5", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -389,7 +439,7 @@ { "cell_type": "code", "execution_count": null, - "id": "79a8ebb1", + "id": "2f28f649", "metadata": {}, "outputs": [], "source": [ @@ -408,7 +458,7 @@ }, { "cell_type": "markdown", - "id": "434c1304", + "id": "2a6ca814", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -417,7 +467,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f6a601b5", + "id": "1d63d1f0", "metadata": {}, "outputs": [], "source": [ @@ -445,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "cc9da181", + "id": "368ddef6", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -454,7 +504,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a5a15f4d", + "id": "5c7179ea", "metadata": {}, "outputs": [], "source": [ @@ -468,7 +518,7 @@ }, { "cell_type": "markdown", - "id": "ebf04363", + "id": "1281320d", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -477,7 +527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e4604c9f", + "id": "29300596", "metadata": {}, "outputs": [], "source": [ @@ -510,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "fb44d8ab", + "id": "b478e9a2", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -519,7 +569,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f50a36d2", + "id": "3a3ea5ee", "metadata": {}, "outputs": [], "source": [ @@ -534,7 +584,7 @@ }, { "cell_type": "markdown", - "id": "879f61db", + "id": "45a743b0", "metadata": {}, "source": [ "

    \n", @@ -545,7 +595,7 @@ }, { "cell_type": "markdown", - "id": "9d96a21f", + "id": "c2f5dd4a", "metadata": {}, "source": [ "

    \n", @@ -556,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "f4a4dbc9", + "id": "e2e463f8", "metadata": {}, "source": [ "

    \n", @@ -567,7 +617,7 @@ }, { "cell_type": "markdown", - "id": "566ac7f4", + "id": "91004669", "metadata": {}, "source": [ "

    \n", @@ -579,7 +629,7 @@ }, { "cell_type": "markdown", - "id": "636aa5e8", + "id": "783f333a", "metadata": {}, "source": [ "

    \n", @@ -594,7 +644,7 @@ }, { "cell_type": "markdown", - "id": "3da445f5", + "id": "b9f629f4", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -607,11 +657,8 @@ { "cell_type": "code", "execution_count": null, - "id": "d226175c", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "313602bc", + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", @@ -632,7 +679,7 @@ }, { "cell_type": "markdown", - "id": "fbe0211c", + "id": "f5b1e743", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -641,7 +688,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5f100206", + "id": "d36d59bd", "metadata": {}, "outputs": [], "source": [ @@ -653,7 +700,7 @@ }, { "cell_type": "markdown", - "id": "905c5649", + "id": "528279ef", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -662,9 +709,8 @@ { "cell_type": "code", "execution_count": null, - "id": "f7933374", + "id": "ccd7078d", "metadata": { - "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 }, "outputs": [], @@ -718,7 +764,7 @@ }, { "cell_type": "markdown", - "id": "d632ec95", + "id": "f014b862", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -727,7 +773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3c9c3dd6", + "id": "a997795e", "metadata": {}, "outputs": [], "source": [ @@ -739,7 +785,7 @@ }, { "cell_type": "markdown", - "id": "ded428de", + "id": "251a4775", "metadata": {}, "source": [ "

    \n", @@ -750,7 +796,7 @@ }, { "cell_type": "markdown", - "id": "de0f72d6", + "id": "98b1abfc", "metadata": {}, "source": [ "

    \n", @@ -761,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "351701b9", + "id": "9f2c7ee5", "metadata": {}, "source": [ "

    \n", @@ -772,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "e5d75ced", + "id": "6d691057", "metadata": {}, "source": [ "

    \n", @@ -783,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "1497dfcf", + "id": "2b31d7cd", "metadata": {}, "source": [ "

    \n", @@ -795,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "d164856f", + "id": "67c6426c", "metadata": {}, "source": [ "

    \n", @@ -810,7 +856,7 @@ }, { "cell_type": "markdown", - "id": "a1c9cc3c", + "id": "375e2be8", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -819,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "8eb2ca29", + "id": "2f95e4fd", "metadata": {}, "source": [ "\n", @@ -829,11 +875,8 @@ { "cell_type": "code", "execution_count": null, - "id": "3ecce80f", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "45e612f9", + "metadata": {}, "outputs": [], "source": [ "from captum.attr import IntegratedGradients\n", @@ -865,7 +908,7 @@ }, { "cell_type": "markdown", - "id": "7d8c6ab0", + "id": "fb97d7c6", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -874,11 +917,8 @@ { "cell_type": "code", "execution_count": null, - "id": "eda69015", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "8195d1b2", + "metadata": {}, "outputs": [], "source": [ "from captum.attr import visualization as viz\n", @@ -916,7 +956,7 @@ }, { "cell_type": "markdown", - "id": "7477880b", + "id": "862b9110", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -927,7 +967,7 @@ { "cell_type": "code", "execution_count": null, - "id": "510a79e8", + "id": "c4a3d563", "metadata": {}, "outputs": [], "source": [ @@ -937,7 +977,7 @@ }, { "cell_type": "markdown", - "id": "a3630c14", + "id": "84d908aa", "metadata": {}, "source": [ "

    \n", @@ -948,7 +988,7 @@ }, { "cell_type": "markdown", - "id": "eb9d1d18", + "id": "3c331cc0", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -957,7 +997,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2848519c", + "id": "d23a0a46", "metadata": {}, "outputs": [], "source": [ @@ -967,7 +1007,7 @@ }, { "cell_type": "markdown", - "id": "00ca9727", + "id": "79e4b018", "metadata": {}, "source": [ "

    \n", @@ -978,7 +1018,7 @@ }, { "cell_type": "markdown", - "id": "b5201d01", + "id": "39f60336", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -987,7 +1027,7 @@ { "cell_type": "code", "execution_count": null, - "id": "88c99f85", + "id": "3d4a9adb", "metadata": {}, "outputs": [], "source": [ @@ -999,7 +1039,7 @@ }, { "cell_type": "markdown", - "id": "f00e90d6", + "id": "0e791fdd", "metadata": {}, "source": [ "

    \n", @@ -1010,7 +1050,7 @@ }, { "cell_type": "markdown", - "id": "fe009c04", + "id": "405a8957", "metadata": {}, "source": [ "

    \n", @@ -1021,7 +1061,7 @@ }, { "cell_type": "markdown", - "id": "5c104bc2", + "id": "1a04f6cb", "metadata": {}, "source": [ "

    \n", @@ -1034,7 +1074,7 @@ }, { "cell_type": "markdown", - "id": "0496ee67", + "id": "dc56b0cb", "metadata": {}, "source": [ "

    \n", @@ -1048,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "c4042dd7", + "id": "8210771f", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1060,7 +1100,7 @@ }, { "cell_type": "markdown", - "id": "f0ebb455", + "id": "bf9fa417", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1069,11 +1109,8 @@ { "cell_type": "code", "execution_count": null, - "id": "3b432c45", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "ca5dac26", + "metadata": {}, "outputs": [], "source": [ "import torch\n", @@ -1085,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "f504d3b2", + "id": "ceefcab1", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1094,7 +1131,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0f7b6318", + "id": "3f3fd43e", "metadata": {}, "outputs": [], "source": [ @@ -1123,7 +1160,7 @@ }, { "cell_type": "markdown", - "id": "410d3e85", + "id": "1c698bbe", "metadata": {}, "source": [ "### UNet model\n", @@ -1133,7 +1170,7 @@ }, { "cell_type": "markdown", - "id": "46fe776e", + "id": "540f8d70", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1142,11 +1179,8 @@ { "cell_type": "code", "execution_count": null, - "id": "21240f36", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "d718c04e", + "metadata": {}, "outputs": [], "source": [ "from tqdm import tqdm\n", @@ -1193,7 +1227,7 @@ }, { "cell_type": "markdown", - "id": "d10dfc06", + "id": "b0661574", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1202,7 +1236,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d3ba1854", + "id": "a1c6d1cc", "metadata": {}, "outputs": [], "source": [ @@ -1240,7 +1274,7 @@ }, { "cell_type": "markdown", - "id": "6df25e47", + "id": "e911ce2b", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1249,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c27d8fe1", + "id": "e0257ab8", "metadata": {}, "outputs": [], "source": [ @@ -1260,7 +1294,7 @@ }, { "cell_type": "markdown", - "id": "af8711f6", + "id": "1835f3c7", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1269,7 +1303,7 @@ { "cell_type": "code", "execution_count": null, - "id": "167dda81", + "id": "4540888c", "metadata": { "lines_to_next_cell": 1 }, @@ -1285,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "88f97ac2", + "id": "24327a52", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1296,7 +1330,7 @@ { "cell_type": "code", "execution_count": null, - "id": "637b6cae", + "id": "d2e6491e", "metadata": { "lines_to_next_cell": 1 }, @@ -1313,7 +1347,7 @@ { "cell_type": "code", "execution_count": null, - "id": "082eac8d", + "id": "0efac3a1", "metadata": { "lines_to_next_cell": 1 }, @@ -1339,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "ef8a5b09", + "id": "c53fb585", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1348,7 +1382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d46a204b", + "id": "70f7a947", "metadata": {}, "outputs": [], "source": [ @@ -1358,7 +1392,7 @@ }, { "cell_type": "markdown", - "id": "444cc55e", + "id": "8c217234", "metadata": {}, "source": [ "

    \n", @@ -1369,7 +1403,7 @@ }, { "cell_type": "markdown", - "id": "e48cd78a", + "id": "e36eaa48", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1379,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "fddc42db", + "id": "cc49f415", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1390,7 +1424,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c87207e", + "id": "79dcdd30", "metadata": {}, "outputs": [], "source": [ @@ -1411,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "571a9903", + "id": "195e6b9b", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1420,7 +1454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e64bfe7d", + "id": "4e02c987", "metadata": {}, "outputs": [], "source": [ @@ -1430,7 +1464,7 @@ }, { "cell_type": "markdown", - "id": "a61b0c87", + "id": "578fb924", "metadata": {}, "source": [ "

    \n", @@ -1441,7 +1475,7 @@ }, { "cell_type": "markdown", - "id": "e5799ebd", + "id": "4ff4ba7b", "metadata": {}, "source": [ "

    \n", @@ -1452,7 +1486,7 @@ }, { "cell_type": "markdown", - "id": "19a9496d", + "id": "8adaff00", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1463,7 +1497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d6e975f", + "id": "43654912", "metadata": {}, "outputs": [], "source": [ @@ -1500,7 +1534,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0dec3e58", + "id": "d180fc34", "metadata": {}, "outputs": [], "source": [ @@ -1511,7 +1545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f564dbc2", + "id": "d1e26609", "metadata": {}, "outputs": [], "source": [ @@ -1521,7 +1555,7 @@ }, { "cell_type": "markdown", - "id": "bae2762b", + "id": "047be54e", "metadata": {}, "source": [ "

    \n", @@ -1533,7 +1567,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9fadbc9b", + "id": "ba529a37", "metadata": {}, "outputs": [], "source": [ @@ -1570,7 +1604,7 @@ { "cell_type": "code", "execution_count": null, - "id": "efde43e6", + "id": "f4a13962", "metadata": {}, "outputs": [], "source": [ @@ -1581,7 +1615,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aa0593b2", + "id": "70c1463f", "metadata": {}, "outputs": [], "source": [ @@ -1591,7 +1625,7 @@ }, { "cell_type": "markdown", - "id": "9a108c4a", + "id": "dad1e74b", "metadata": {}, "source": [ "

    \n", @@ -1599,11 +1633,46 @@ "How does the denoiser trained on shuffled data perform compared to the one trained sequentially on one dataset and then on the other?\n", "

    " ] + }, + { + "cell_type": "markdown", + "id": "622d21de", + "metadata": {}, + "source": [ + "\n", + "

    \n", + " Checkpoint 5

    \n", + "
      \n", + " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", + "
    \n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "6c7a8133", + "metadata": {}, + "source": [ + "\n", + "

    \n", + " Bonus Questions

    \n", + "
      \n", + "
    1. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
      2. \n", + "
    \n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "39445134", + "metadata": {}, + "source": [] } ], "metadata": { "jupytext": { - "cell_metadata_filter": "all" + "cell_metadata_filter": "all", + "custom_cell_magics": "kql" }, "kernelspec": { "display_name": "Python [conda env:07-failure-modes]", diff --git a/solution.ipynb b/solution.ipynb index efb9b32..5c6dd86 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "360f0128", + "id": "f18a286a", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "6ee26090", + "id": "f5912014", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "6b9ab5fa", + "id": "07d654d1", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "cb4ca93c", + "id": "376853b9", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "b3352f38", + "id": "78fdf1a2", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "05d1cdc4", + "id": "ce294ab0", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "0e7556c2", + "id": "137bc0ef", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b5938a0c", + "id": "7c21829d", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dd8e9f5e", + "id": "ee658555", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "b5e02f3e", + "id": "da5b143b", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ae22911", + "id": "6e6fe0e0", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ee0b5b00", + "id": "b0bc0a60", "metadata": {}, "outputs": [], "source": [ @@ -172,18 +172,18 @@ }, { "cell_type": "markdown", - "id": "28460701", + "id": "ecf586b5", "metadata": {}, "source": [ "

    \n", "Task 1.1:

    \n", - "We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data colleciton, for example in a hospital imaging environment or microscopy lab?\n", + "We have locally changed images of 7s artificially for this exercise. What are some examples of ways that images can be corrupted or tainted during real-life data collection, for example in a hospital imaging environment or microscopy lab?\n", "
    " ] }, { "cell_type": "markdown", - "id": "c740c4a2", + "id": "bf813ca8", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "8035425c", + "id": "dcc7f9c0", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "e5fccbc6", + "id": "1a0fee85", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "9f3e84f3", + "id": "035fd976", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "a489e898", + "id": "5ea21574", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "7a5b10c2", + "id": "7e9dbdcc", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "067c32bf", + "id": "0b40ae2f", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "711ba5ea", + "id": "b99477e5", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "2f408424", + "id": "b609686c", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eae78bfc", + "id": "cd1b5f08", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "3a654fb9", + "id": "4ddf365a", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a2344bfa", + "id": "b771931b", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "738a0daa", + "id": "7e15dbb3", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9d529b7f", + "id": "e5c23396", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59813208", + "id": "c70c98ed", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "228375c9", + "id": "197fd91e", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "52efcdc3", + "id": "63f74027", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "1424aa44", + "id": "2c76dcdf", "metadata": { "tags": [ "solution" @@ -437,7 +437,14 @@ "\n", "Prevention is easer than fixing after generation!\n", "- PCA on metadata <3 to help detect such issues\n", - "- Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc)\n", + "- Randomization of data generation (blind yourself to your samples, dont always put certain classes in certain wells, etc)\n" + ] + }, + { + "cell_type": "markdown", + "id": "2c8d8392", + "metadata": {}, + "source": [ "\n", "

    \n", "Task 1.4:

    \n", @@ -447,7 +454,7 @@ }, { "cell_type": "markdown", - "id": "d40c25f5", + "id": "a07717e2", "metadata": { "tags": [ "solution" @@ -461,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "249dab4e", + "id": "4ee432da", "metadata": { "tags": [ "solution" @@ -470,13 +477,27 @@ "source": [ "**1.4 Answer from 2023 Students**\n", "\n", - "We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! \n", + "We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! \n" + ] + }, + { + "cell_type": "markdown", + "id": "d3c3a011", + "metadata": {}, + "source": [ "\n", "

    \n", " Checkpoint 1

    \n", "\n", "Post to the course chat when you have reached Checkpoint 1. We will discuss all the questions and make more predictions!\n", - "
    \n", + "
    " + ] + }, + { + "cell_type": "markdown", + "id": "268d8f77", + "metadata": {}, + "source": [ "\n", "

    \n", " Bonus Questions:

    \n", @@ -487,8 +508,14 @@ "
  • Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
    • \n", " \n", "If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section.\n", - "
    \n", - "\n", + "

    " + ] + }, + { + "cell_type": "markdown", + "id": "19b3e9a5", + "metadata": {}, + "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", "\n", "From Part 1, we have a clean dataset and a dataset that has been tainted with effects that simulate local and global effects that could happen in real collection scenarios. Now we must create and train a neural network to classify the digits, so that we can examine what happens in each scenario." @@ -497,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1367725c", + "id": "caf5144a", "metadata": {}, "outputs": [], "source": [ @@ -511,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "6cc01765", + "id": "3cb4972e", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -520,14 +547,11 @@ { "cell_type": "code", "execution_count": null, - "id": "7096978a", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "c7cd32d8", + "metadata": {}, "outputs": [], "source": [ - "from tqdm import tqdm\n", + "from tqdm.auto import tqdm\n", "\n", "# Training function:\n", "def train_mnist(model, train_loader, batch_size, criterion, optimizer, history):\n", @@ -548,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "ee66a125", + "id": "cfaa20f5", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -557,7 +581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "79a8ebb1", + "id": "2f28f649", "metadata": {}, "outputs": [], "source": [ @@ -576,7 +600,7 @@ }, { "cell_type": "markdown", - "id": "434c1304", + "id": "2a6ca814", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -585,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f6a601b5", + "id": "1d63d1f0", "metadata": {}, "outputs": [], "source": [ @@ -613,7 +637,7 @@ }, { "cell_type": "markdown", - "id": "cc9da181", + "id": "368ddef6", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -622,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a5a15f4d", + "id": "5c7179ea", "metadata": {}, "outputs": [], "source": [ @@ -636,7 +660,7 @@ }, { "cell_type": "markdown", - "id": "ebf04363", + "id": "1281320d", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -645,7 +669,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e4604c9f", + "id": "29300596", "metadata": {}, "outputs": [], "source": [ @@ -678,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "fb44d8ab", + "id": "b478e9a2", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -687,7 +711,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f50a36d2", + "id": "3a3ea5ee", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +726,7 @@ }, { "cell_type": "markdown", - "id": "879f61db", + "id": "45a743b0", "metadata": {}, "source": [ "

    \n", @@ -713,7 +737,7 @@ }, { "cell_type": "markdown", - "id": "06724238", + "id": "4453f570", "metadata": { "tags": [ "solution" @@ -727,7 +751,7 @@ }, { "cell_type": "markdown", - "id": "8e806c11", + "id": "06888c5e", "metadata": { "tags": [ "solution" @@ -741,7 +765,7 @@ }, { "cell_type": "markdown", - "id": "9d96a21f", + "id": "c2f5dd4a", "metadata": {}, "source": [ "

    \n", @@ -752,7 +776,7 @@ }, { "cell_type": "markdown", - "id": "015b46c1", + "id": "984f28b7", "metadata": { "tags": [ "solution" @@ -766,7 +790,7 @@ }, { "cell_type": "markdown", - "id": "72948798", + "id": "1a72bff3", "metadata": { "tags": [ "solution" @@ -780,7 +804,7 @@ }, { "cell_type": "markdown", - "id": "f4a4dbc9", + "id": "e2e463f8", "metadata": {}, "source": [ "

    \n", @@ -791,7 +815,7 @@ }, { "cell_type": "markdown", - "id": "f86f316d", + "id": "689bd850", "metadata": { "tags": [ "solution" @@ -805,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "b3fcbd0c", + "id": "88b5a0e9", "metadata": { "tags": [ "solution" @@ -819,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "566ac7f4", + "id": "91004669", "metadata": {}, "source": [ "

    \n", @@ -831,7 +855,7 @@ }, { "cell_type": "markdown", - "id": "636aa5e8", + "id": "783f333a", "metadata": {}, "source": [ "

    \n", @@ -846,7 +870,7 @@ }, { "cell_type": "markdown", - "id": "3da445f5", + "id": "b9f629f4", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -859,11 +883,8 @@ { "cell_type": "code", "execution_count": null, - "id": "d226175c", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "313602bc", + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", @@ -884,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "fbe0211c", + "id": "f5b1e743", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -893,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5f100206", + "id": "d36d59bd", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +926,7 @@ }, { "cell_type": "markdown", - "id": "905c5649", + "id": "528279ef", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -914,9 +935,8 @@ { "cell_type": "code", "execution_count": null, - "id": "f7933374", + "id": "ccd7078d", "metadata": { - "lines_to_end_of_cell_marker": 0, "lines_to_next_cell": 1 }, "outputs": [], @@ -970,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "d632ec95", + "id": "f014b862", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -979,7 +999,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3c9c3dd6", + "id": "a997795e", "metadata": {}, "outputs": [], "source": [ @@ -991,7 +1011,7 @@ }, { "cell_type": "markdown", - "id": "ded428de", + "id": "251a4775", "metadata": {}, "source": [ "

    \n", @@ -1002,7 +1022,7 @@ }, { "cell_type": "markdown", - "id": "ec41442d", + "id": "f4b2be9d", "metadata": { "tags": [ "solution" @@ -1016,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "76c3ad7a", + "id": "26e7c295", "metadata": { "tags": [ "solution" @@ -1031,7 +1051,7 @@ }, { "cell_type": "markdown", - "id": "de0f72d6", + "id": "98b1abfc", "metadata": {}, "source": [ "

    \n", @@ -1042,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "7b4f4706", + "id": "ad8ad2f6", "metadata": { "tags": [ "solution" @@ -1056,7 +1076,7 @@ }, { "cell_type": "markdown", - "id": "6ab61b46", + "id": "0567c6b1", "metadata": { "tags": [ "solution" @@ -1070,7 +1090,7 @@ }, { "cell_type": "markdown", - "id": "351701b9", + "id": "9f2c7ee5", "metadata": {}, "source": [ "

    \n", @@ -1081,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "d2bf534b", + "id": "b7aa2a67", "metadata": { "tags": [ "solution" @@ -1095,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "eda35306", + "id": "ecf332a4", "metadata": { "tags": [ "solution" @@ -1112,7 +1132,7 @@ }, { "cell_type": "markdown", - "id": "e5d75ced", + "id": "6d691057", "metadata": {}, "source": [ "

    \n", @@ -1123,7 +1143,7 @@ }, { "cell_type": "markdown", - "id": "169c3758", + "id": "6304edc5", "metadata": { "tags": [ "solution" @@ -1137,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "b98545ca", + "id": "373835b8", "metadata": { "tags": [ "solution" @@ -1157,7 +1177,7 @@ }, { "cell_type": "markdown", - "id": "1497dfcf", + "id": "2b31d7cd", "metadata": {}, "source": [ "

    \n", @@ -1169,7 +1189,7 @@ }, { "cell_type": "markdown", - "id": "d164856f", + "id": "67c6426c", "metadata": {}, "source": [ "

    \n", @@ -1184,7 +1204,7 @@ }, { "cell_type": "markdown", - "id": "a1c9cc3c", + "id": "375e2be8", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1193,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "8eb2ca29", + "id": "2f95e4fd", "metadata": {}, "source": [ "\n", @@ -1203,11 +1223,8 @@ { "cell_type": "code", "execution_count": null, - "id": "3ecce80f", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "45e612f9", + "metadata": {}, "outputs": [], "source": [ "from captum.attr import IntegratedGradients\n", @@ -1239,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "7d8c6ab0", + "id": "fb97d7c6", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1248,11 +1265,8 @@ { "cell_type": "code", "execution_count": null, - "id": "eda69015", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "8195d1b2", + "metadata": {}, "outputs": [], "source": [ "from captum.attr import visualization as viz\n", @@ -1290,7 +1304,7 @@ }, { "cell_type": "markdown", - "id": "7477880b", + "id": "862b9110", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1301,7 +1315,7 @@ { "cell_type": "code", "execution_count": null, - "id": "510a79e8", + "id": "c4a3d563", "metadata": {}, "outputs": [], "source": [ @@ -1311,7 +1325,7 @@ }, { "cell_type": "markdown", - "id": "a3630c14", + "id": "84d908aa", "metadata": {}, "source": [ "

    \n", @@ -1322,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "01bc3246", + "id": "ed95224f", "metadata": { "tags": [ "solution" @@ -1336,7 +1350,7 @@ }, { "cell_type": "markdown", - "id": "45bad1fc", + "id": "6a30c2f0", "metadata": { "tags": [ "solution" @@ -1351,7 +1365,7 @@ }, { "cell_type": "markdown", - "id": "eb9d1d18", + "id": "3c331cc0", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1360,7 +1374,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2848519c", + "id": "d23a0a46", "metadata": {}, "outputs": [], "source": [ @@ -1370,7 +1384,7 @@ }, { "cell_type": "markdown", - "id": "00ca9727", + "id": "79e4b018", "metadata": {}, "source": [ "

    \n", @@ -1381,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "1e8ea9f0", + "id": "af9bf85f", "metadata": { "tags": [ "solution" @@ -1395,7 +1409,7 @@ }, { "cell_type": "markdown", - "id": "e13087b5", + "id": "986394b7", "metadata": { "tags": [ "solution" @@ -1413,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "b5201d01", + "id": "39f60336", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1422,7 +1436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "88c99f85", + "id": "3d4a9adb", "metadata": {}, "outputs": [], "source": [ @@ -1434,7 +1448,7 @@ }, { "cell_type": "markdown", - "id": "f00e90d6", + "id": "0e791fdd", "metadata": {}, "source": [ "

    \n", @@ -1445,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "a12e46ea", + "id": "f0e935ca", "metadata": { "tags": [ "solution" @@ -1459,7 +1473,7 @@ }, { "cell_type": "markdown", - "id": "b8b3f1ce", + "id": "8673f2ff", "metadata": { "tags": [ "solution" @@ -1476,7 +1490,7 @@ }, { "cell_type": "markdown", - "id": "fe009c04", + "id": "405a8957", "metadata": {}, "source": [ "

    \n", @@ -1487,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "7b6c3d15", + "id": "49f3e7ca", "metadata": { "tags": [ "solution" @@ -1501,7 +1515,7 @@ }, { "cell_type": "markdown", - "id": "18a5c29b", + "id": "04ca7800", "metadata": { "tags": [ "solution" @@ -1517,7 +1531,7 @@ }, { "cell_type": "markdown", - "id": "5c104bc2", + "id": "1a04f6cb", "metadata": {}, "source": [ "

    \n", @@ -1530,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "0496ee67", + "id": "dc56b0cb", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1558,7 @@ }, { "cell_type": "markdown", - "id": "c4042dd7", + "id": "8210771f", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1556,7 +1570,7 @@ }, { "cell_type": "markdown", - "id": "f0ebb455", + "id": "bf9fa417", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1565,11 +1579,8 @@ { "cell_type": "code", "execution_count": null, - "id": "3b432c45", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "ca5dac26", + "metadata": {}, "outputs": [], "source": [ "import torch\n", @@ -1581,7 +1592,7 @@ }, { "cell_type": "markdown", - "id": "f504d3b2", + "id": "ceefcab1", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1590,7 +1601,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0f7b6318", + "id": "3f3fd43e", "metadata": {}, "outputs": [], "source": [ @@ -1619,7 +1630,7 @@ }, { "cell_type": "markdown", - "id": "410d3e85", + "id": "1c698bbe", "metadata": {}, "source": [ "### UNet model\n", @@ -1629,7 +1640,7 @@ }, { "cell_type": "markdown", - "id": "46fe776e", + "id": "540f8d70", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1638,11 +1649,8 @@ { "cell_type": "code", "execution_count": null, - "id": "21240f36", - "metadata": { - "lines_to_end_of_cell_marker": 0, - "lines_to_next_cell": 1 - }, + "id": "d718c04e", + "metadata": {}, "outputs": [], "source": [ "from tqdm import tqdm\n", @@ -1689,7 +1697,7 @@ }, { "cell_type": "markdown", - "id": "d10dfc06", + "id": "b0661574", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1698,7 +1706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d3ba1854", + "id": "a1c6d1cc", "metadata": {}, "outputs": [], "source": [ @@ -1736,7 +1744,7 @@ }, { "cell_type": "markdown", - "id": "6df25e47", + "id": "e911ce2b", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1745,7 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c27d8fe1", + "id": "e0257ab8", "metadata": {}, "outputs": [], "source": [ @@ -1756,7 +1764,7 @@ }, { "cell_type": "markdown", - "id": "af8711f6", + "id": "1835f3c7", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1765,7 +1773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "167dda81", + "id": "4540888c", "metadata": { "lines_to_next_cell": 1 }, @@ -1781,7 +1789,7 @@ }, { "cell_type": "markdown", - "id": "88f97ac2", + "id": "24327a52", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1792,7 +1800,7 @@ { "cell_type": "code", "execution_count": null, - "id": "637b6cae", + "id": "d2e6491e", "metadata": { "lines_to_next_cell": 1 }, @@ -1809,7 +1817,7 @@ { "cell_type": "code", "execution_count": null, - "id": "082eac8d", + "id": "0efac3a1", "metadata": { "lines_to_next_cell": 1 }, @@ -1835,7 +1843,7 @@ }, { "cell_type": "markdown", - "id": "ef8a5b09", + "id": "c53fb585", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1844,7 +1852,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d46a204b", + "id": "70f7a947", "metadata": {}, "outputs": [], "source": [ @@ -1854,7 +1862,7 @@ }, { "cell_type": "markdown", - "id": "444cc55e", + "id": "8c217234", "metadata": {}, "source": [ "

    \n", @@ -1865,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "03088233", + "id": "eee055f8", "metadata": { "tags": [ "solution" @@ -1879,7 +1887,7 @@ }, { "cell_type": "markdown", - "id": "a1a7985a", + "id": "78eb810d", "metadata": { "tags": [ "solution" @@ -1893,7 +1901,7 @@ }, { "cell_type": "markdown", - "id": "e48cd78a", + "id": "e36eaa48", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1903,7 +1911,7 @@ }, { "cell_type": "markdown", - "id": "fddc42db", + "id": "cc49f415", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1914,7 +1922,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c87207e", + "id": "79dcdd30", "metadata": {}, "outputs": [], "source": [ @@ -1935,7 +1943,7 @@ }, { "cell_type": "markdown", - "id": "571a9903", + "id": "195e6b9b", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1944,7 +1952,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e64bfe7d", + "id": "4e02c987", "metadata": {}, "outputs": [], "source": [ @@ -1954,7 +1962,7 @@ }, { "cell_type": "markdown", - "id": "a61b0c87", + "id": "578fb924", "metadata": {}, "source": [ "

    \n", @@ -1965,7 +1973,7 @@ }, { "cell_type": "markdown", - "id": "ddf92ed5", + "id": "2c252dc7", "metadata": { "tags": [ "solution" @@ -1979,7 +1987,7 @@ }, { "cell_type": "markdown", - "id": "788f151e", + "id": "1a514f98", "metadata": { "tags": [ "solution" @@ -1993,7 +2001,7 @@ }, { "cell_type": "markdown", - "id": "e5799ebd", + "id": "4ff4ba7b", "metadata": {}, "source": [ "

    \n", @@ -2004,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "4c912317", + "id": "30d7efee", "metadata": { "tags": [ "solution" @@ -2018,7 +2026,7 @@ }, { "cell_type": "markdown", - "id": "e5b75655", + "id": "659604ee", "metadata": { "tags": [ "solution" @@ -2033,7 +2041,7 @@ }, { "cell_type": "markdown", - "id": "19a9496d", + "id": "8adaff00", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2044,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d6e975f", + "id": "43654912", "metadata": {}, "outputs": [], "source": [ @@ -2081,7 +2089,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0dec3e58", + "id": "d180fc34", "metadata": {}, "outputs": [], "source": [ @@ -2092,7 +2100,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f564dbc2", + "id": "d1e26609", "metadata": {}, "outputs": [], "source": [ @@ -2102,7 +2110,7 @@ }, { "cell_type": "markdown", - "id": "bae2762b", + "id": "047be54e", "metadata": {}, "source": [ "

    \n", @@ -2113,7 +2121,7 @@ }, { "cell_type": "markdown", - "id": "822949b4", + "id": "aadffe0d", "metadata": { "tags": [ "solution" @@ -2132,7 +2140,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9fadbc9b", + "id": "ba529a37", "metadata": {}, "outputs": [], "source": [ @@ -2169,7 +2177,7 @@ { "cell_type": "code", "execution_count": null, - "id": "efde43e6", + "id": "f4a13962", "metadata": {}, "outputs": [], "source": [ @@ -2180,7 +2188,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aa0593b2", + "id": "70c1463f", "metadata": {}, "outputs": [], "source": [ @@ -2190,7 +2198,7 @@ }, { "cell_type": "markdown", - "id": "9a108c4a", + "id": "dad1e74b", "metadata": {}, "source": [ "

    \n", @@ -2201,7 +2209,7 @@ }, { "cell_type": "markdown", - "id": "7e828f97", + "id": "9aaf034c", "metadata": { "tags": [ "solution" @@ -2210,28 +2218,48 @@ "source": [ "**5.5 Answer:**\n", "\n", - "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets.\n", + "The denoiser trained on shuffled data performs well accross both MNIST and FashionMNIST, without having any particular issue with either of the two datasets.\n" + ] + }, + { + "cell_type": "markdown", + "id": "622d21de", + "metadata": {}, + "source": [ "\n", "

    \n", " Checkpoint 5

    \n", "
      \n", " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", "
    \n", - "
    \n", + "

    " + ] + }, + { + "cell_type": "markdown", + "id": "6c7a8133", + "metadata": {}, + "source": [ "\n", "

    \n", " Bonus Questions

    \n", "
      \n", - "
    1. Try training a FashionMNIST denoising network and applying it to MNIST. Or, try training a denoising network on both datasets and see how it works on each.
      2. \n", "
    2. Go back to Part 4 and try another attribution method, such as Saliency, and see how the results differ.
      3. \n", "
    \n", "
    " ] + }, + { + "cell_type": "markdown", + "id": "39445134", + "metadata": {}, + "source": [] } ], "metadata": { "jupytext": { - "cell_metadata_filter": "all" + "cell_metadata_filter": "all", + "custom_cell_magics": "kql" }, "kernelspec": { "display_name": "Python [conda env:07-failure-modes]", From a3de073b2c5bd8a27316a6f9a4c15c64bb1cab6e Mon Sep 17 00:00:00 2001 From: afoix Date: Mon, 19 Aug 2024 00:03:41 +0000 Subject: [PATCH 41/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 234 ++++++++++++++++++------------------- solution.ipynb | 310 ++++++++++++++++++++++++------------------------- 2 files changed, 272 insertions(+), 272 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 8e32095..343f9c0 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "f18a286a", + "id": "88362ef4", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "f5912014", + "id": "4bc6c9f4", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "07d654d1", + "id": "4e2191ab", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "376853b9", + "id": "4ec20197", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "78fdf1a2", + "id": "370be730", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ce294ab0", + "id": "c575c9e6", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "137bc0ef", + "id": "8b7939e4", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7c21829d", + "id": "a15d9890", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ee658555", + "id": "074deff8", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "da5b143b", + "id": "91ce7e66", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6e6fe0e0", + "id": "190a4fb6", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b0bc0a60", + "id": "655e6ea2", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "ecf586b5", + "id": "affd9304", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "1a0fee85", + "id": "99b5bd59", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "7e9dbdcc", + "id": "de3512d8", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "0b40ae2f", + "id": "bead10d5", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b99477e5", + "id": "0c71888a", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "b609686c", + "id": "2b85cd48", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cd1b5f08", + "id": "eef94199", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "4ddf365a", + "id": "86335552", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b771931b", + "id": "1c189457", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "7e15dbb3", + "id": "bd4e5de4", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e5c23396", + "id": "b3ba43fb", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c70c98ed", + "id": "5d1a7443", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "197fd91e", + "id": "7d4c6382", "metadata": {}, "source": [ "

    \n", @@ -328,7 +328,7 @@ }, { "cell_type": "markdown", - "id": "2c8d8392", + "id": "cd0c9073", "metadata": {}, "source": [ "\n", @@ -340,7 +340,7 @@ }, { "cell_type": "markdown", - "id": "d3c3a011", + "id": "668ace10", "metadata": {}, "source": [ "\n", @@ -353,7 +353,7 @@ }, { "cell_type": "markdown", - "id": "268d8f77", + "id": "ff0282fd", "metadata": {}, "source": [ "\n", @@ -371,7 +371,7 @@ }, { "cell_type": "markdown", - "id": "19b3e9a5", + "id": "1d263d87", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -382,7 +382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caf5144a", + "id": "d5f30730", "metadata": {}, "outputs": [], "source": [ @@ -396,7 +396,7 @@ }, { "cell_type": "markdown", - "id": "3cb4972e", + "id": "34d32f34", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -405,7 +405,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c7cd32d8", + "id": "3a9ce68d", "metadata": {}, "outputs": [], "source": [ @@ -430,7 +430,7 @@ }, { "cell_type": "markdown", - "id": "cfaa20f5", + "id": "73af4b1e", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -439,7 +439,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f28f649", + "id": "ea45a709", "metadata": {}, "outputs": [], "source": [ @@ -458,7 +458,7 @@ }, { "cell_type": "markdown", - "id": "2a6ca814", + "id": "181835ee", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -467,7 +467,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1d63d1f0", + "id": "8cde2c47", "metadata": {}, "outputs": [], "source": [ @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "368ddef6", + "id": "9be61218", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -504,7 +504,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5c7179ea", + "id": "1e0a85d1", "metadata": {}, "outputs": [], "source": [ @@ -518,7 +518,7 @@ }, { "cell_type": "markdown", - "id": "1281320d", + "id": "e2f00338", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -527,7 +527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "29300596", + "id": "cfb172ed", "metadata": {}, "outputs": [], "source": [ @@ -560,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "b478e9a2", + "id": "bf3e7984", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -569,7 +569,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3a3ea5ee", + "id": "a7a4c9cd", "metadata": {}, "outputs": [], "source": [ @@ -584,7 +584,7 @@ }, { "cell_type": "markdown", - "id": "45a743b0", + "id": "16ec7aa5", "metadata": {}, "source": [ "

    \n", @@ -595,7 +595,7 @@ }, { "cell_type": "markdown", - "id": "c2f5dd4a", + "id": "cbbab816", "metadata": {}, "source": [ "

    \n", @@ -606,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "e2e463f8", + "id": "5a9e3077", "metadata": {}, "source": [ "

    \n", @@ -617,7 +617,7 @@ }, { "cell_type": "markdown", - "id": "91004669", + "id": "d2b3efeb", "metadata": {}, "source": [ "

    \n", @@ -629,7 +629,7 @@ }, { "cell_type": "markdown", - "id": "783f333a", + "id": "f64e94c4", "metadata": {}, "source": [ "

    \n", @@ -644,7 +644,7 @@ }, { "cell_type": "markdown", - "id": "b9f629f4", + "id": "881c9823", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -657,7 +657,7 @@ { "cell_type": "code", "execution_count": null, - "id": "313602bc", + "id": "d71fa37e", "metadata": {}, "outputs": [], "source": [ @@ -679,7 +679,7 @@ }, { "cell_type": "markdown", - "id": "f5b1e743", + "id": "93aedf63", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -688,7 +688,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d36d59bd", + "id": "1b2d5627", "metadata": {}, "outputs": [], "source": [ @@ -700,7 +700,7 @@ }, { "cell_type": "markdown", - "id": "528279ef", + "id": "47e48c92", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -709,7 +709,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ccd7078d", + "id": "476302a9", "metadata": { "lines_to_next_cell": 1 }, @@ -764,7 +764,7 @@ }, { "cell_type": "markdown", - "id": "f014b862", + "id": "8292cd76", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -773,7 +773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a997795e", + "id": "aca77d2f", "metadata": {}, "outputs": [], "source": [ @@ -785,7 +785,7 @@ }, { "cell_type": "markdown", - "id": "251a4775", + "id": "7984ae4a", "metadata": {}, "source": [ "

    \n", @@ -796,7 +796,7 @@ }, { "cell_type": "markdown", - "id": "98b1abfc", + "id": "e01afe04", "metadata": {}, "source": [ "

    \n", @@ -807,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "9f2c7ee5", + "id": "7beab007", "metadata": {}, "source": [ "

    \n", @@ -818,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "6d691057", + "id": "9912eaea", "metadata": {}, "source": [ "

    \n", @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "2b31d7cd", + "id": "c185a436", "metadata": {}, "source": [ "

    \n", @@ -841,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "67c6426c", + "id": "fe4f594d", "metadata": {}, "source": [ "

    \n", @@ -856,7 +856,7 @@ }, { "cell_type": "markdown", - "id": "375e2be8", + "id": "bcc0a701", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "2f95e4fd", + "id": "e073c3e8", "metadata": {}, "source": [ "\n", @@ -875,7 +875,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45e612f9", + "id": "5d69b7dd", "metadata": {}, "outputs": [], "source": [ @@ -908,7 +908,7 @@ }, { "cell_type": "markdown", - "id": "fb97d7c6", + "id": "03a80462", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -917,7 +917,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8195d1b2", + "id": "ccf5010d", "metadata": {}, "outputs": [], "source": [ @@ -956,7 +956,7 @@ }, { "cell_type": "markdown", - "id": "862b9110", + "id": "136ed21c", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -967,7 +967,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c4a3d563", + "id": "bfa754f1", "metadata": {}, "outputs": [], "source": [ @@ -977,7 +977,7 @@ }, { "cell_type": "markdown", - "id": "84d908aa", + "id": "586539eb", "metadata": {}, "source": [ "

    \n", @@ -988,7 +988,7 @@ }, { "cell_type": "markdown", - "id": "3c331cc0", + "id": "be2a6130", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -997,7 +997,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d23a0a46", + "id": "c102fd3e", "metadata": {}, "outputs": [], "source": [ @@ -1007,7 +1007,7 @@ }, { "cell_type": "markdown", - "id": "79e4b018", + "id": "1bf26d58", "metadata": {}, "source": [ "

    \n", @@ -1018,7 +1018,7 @@ }, { "cell_type": "markdown", - "id": "39f60336", + "id": "5130501e", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1027,7 +1027,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3d4a9adb", + "id": "dce44b30", "metadata": {}, "outputs": [], "source": [ @@ -1039,7 +1039,7 @@ }, { "cell_type": "markdown", - "id": "0e791fdd", + "id": "6f25a55d", "metadata": {}, "source": [ "

    \n", @@ -1050,7 +1050,7 @@ }, { "cell_type": "markdown", - "id": "405a8957", + "id": "a8b618c2", "metadata": {}, "source": [ "

    \n", @@ -1061,7 +1061,7 @@ }, { "cell_type": "markdown", - "id": "1a04f6cb", + "id": "f0a1cd54", "metadata": {}, "source": [ "

    \n", @@ -1074,7 +1074,7 @@ }, { "cell_type": "markdown", - "id": "dc56b0cb", + "id": "037011ae", "metadata": {}, "source": [ "

    \n", @@ -1088,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "8210771f", + "id": "581fae79", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1100,7 +1100,7 @@ }, { "cell_type": "markdown", - "id": "bf9fa417", + "id": "79ad51e9", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1109,7 +1109,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ca5dac26", + "id": "94ed56c0", "metadata": {}, "outputs": [], "source": [ @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "ceefcab1", + "id": "afe03383", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1131,7 +1131,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3f3fd43e", + "id": "fa00a616", "metadata": {}, "outputs": [], "source": [ @@ -1160,7 +1160,7 @@ }, { "cell_type": "markdown", - "id": "1c698bbe", + "id": "9a58a0f3", "metadata": {}, "source": [ "### UNet model\n", @@ -1170,7 +1170,7 @@ }, { "cell_type": "markdown", - "id": "540f8d70", + "id": "01e95305", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1179,7 +1179,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d718c04e", + "id": "3bc9b22b", "metadata": {}, "outputs": [], "source": [ @@ -1227,7 +1227,7 @@ }, { "cell_type": "markdown", - "id": "b0661574", + "id": "881bb411", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1236,7 +1236,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a1c6d1cc", + "id": "877dcc7d", "metadata": {}, "outputs": [], "source": [ @@ -1274,7 +1274,7 @@ }, { "cell_type": "markdown", - "id": "e911ce2b", + "id": "c0dbe5e2", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1283,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0257ab8", + "id": "2a2c4ab2", "metadata": {}, "outputs": [], "source": [ @@ -1294,7 +1294,7 @@ }, { "cell_type": "markdown", - "id": "1835f3c7", + "id": "55137d7a", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1303,7 +1303,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4540888c", + "id": "f01abff9", "metadata": { "lines_to_next_cell": 1 }, @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "24327a52", + "id": "b0d0c70b", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1330,7 +1330,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d2e6491e", + "id": "1b563891", "metadata": { "lines_to_next_cell": 1 }, @@ -1347,7 +1347,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0efac3a1", + "id": "068942ab", "metadata": { "lines_to_next_cell": 1 }, @@ -1373,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "c53fb585", + "id": "07938ae0", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1382,7 +1382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "70f7a947", + "id": "630e1f59", "metadata": {}, "outputs": [], "source": [ @@ -1392,7 +1392,7 @@ }, { "cell_type": "markdown", - "id": "8c217234", + "id": "8914370a", "metadata": {}, "source": [ "

    \n", @@ -1403,7 +1403,7 @@ }, { "cell_type": "markdown", - "id": "e36eaa48", + "id": "5017b1c3", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1413,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "cc49f415", + "id": "e50373f7", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1424,7 +1424,7 @@ { "cell_type": "code", "execution_count": null, - "id": "79dcdd30", + "id": "6dff3118", "metadata": {}, "outputs": [], "source": [ @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "195e6b9b", + "id": "1433ad9c", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1454,7 +1454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4e02c987", + "id": "6a832c31", "metadata": {}, "outputs": [], "source": [ @@ -1464,7 +1464,7 @@ }, { "cell_type": "markdown", - "id": "578fb924", + "id": "53cfae9b", "metadata": {}, "source": [ "

    \n", @@ -1475,7 +1475,7 @@ }, { "cell_type": "markdown", - "id": "4ff4ba7b", + "id": "a9ad5714", "metadata": {}, "source": [ "

    \n", @@ -1486,7 +1486,7 @@ }, { "cell_type": "markdown", - "id": "8adaff00", + "id": "c8b27d2f", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1497,7 +1497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "43654912", + "id": "9dd06cbe", "metadata": {}, "outputs": [], "source": [ @@ -1534,7 +1534,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d180fc34", + "id": "9323e735", "metadata": {}, "outputs": [], "source": [ @@ -1545,7 +1545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d1e26609", + "id": "6deca8db", "metadata": {}, "outputs": [], "source": [ @@ -1555,7 +1555,7 @@ }, { "cell_type": "markdown", - "id": "047be54e", + "id": "3e031c63", "metadata": {}, "source": [ "

    \n", @@ -1567,7 +1567,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ba529a37", + "id": "cddddf38", "metadata": {}, "outputs": [], "source": [ @@ -1604,7 +1604,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f4a13962", + "id": "78119dc2", "metadata": {}, "outputs": [], "source": [ @@ -1615,7 +1615,7 @@ { "cell_type": "code", "execution_count": null, - "id": "70c1463f", + "id": "3681154e", "metadata": {}, "outputs": [], "source": [ @@ -1625,7 +1625,7 @@ }, { "cell_type": "markdown", - "id": "dad1e74b", + "id": "0e8a1051", "metadata": {}, "source": [ "

    \n", @@ -1636,7 +1636,7 @@ }, { "cell_type": "markdown", - "id": "622d21de", + "id": "c8a6256f", "metadata": {}, "source": [ "\n", @@ -1650,7 +1650,7 @@ }, { "cell_type": "markdown", - "id": "6c7a8133", + "id": "a3d4743b", "metadata": {}, "source": [ "\n", @@ -1664,7 +1664,7 @@ }, { "cell_type": "markdown", - "id": "39445134", + "id": "048cd031", "metadata": {}, "source": [] } diff --git a/solution.ipynb b/solution.ipynb index 5c6dd86..d1d7e2d 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "f18a286a", + "id": "88362ef4", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "f5912014", + "id": "4bc6c9f4", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "07d654d1", + "id": "4e2191ab", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "376853b9", + "id": "4ec20197", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "78fdf1a2", + "id": "370be730", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ce294ab0", + "id": "c575c9e6", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "137bc0ef", + "id": "8b7939e4", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7c21829d", + "id": "a15d9890", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ee658555", + "id": "074deff8", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "da5b143b", + "id": "91ce7e66", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6e6fe0e0", + "id": "190a4fb6", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b0bc0a60", + "id": "655e6ea2", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "ecf586b5", + "id": "affd9304", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "bf813ca8", + "id": "c06900dd", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "dcc7f9c0", + "id": "b2031b44", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "1a0fee85", + "id": "99b5bd59", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "035fd976", + "id": "feb94d71", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "5ea21574", + "id": "7952b94f", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "7e9dbdcc", + "id": "de3512d8", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "0b40ae2f", + "id": "bead10d5", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b99477e5", + "id": "0c71888a", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "b609686c", + "id": "2b85cd48", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cd1b5f08", + "id": "eef94199", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "4ddf365a", + "id": "86335552", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b771931b", + "id": "1c189457", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "7e15dbb3", + "id": "bd4e5de4", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e5c23396", + "id": "b3ba43fb", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c70c98ed", + "id": "5d1a7443", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "197fd91e", + "id": "7d4c6382", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "63f74027", + "id": "ac8e3bfc", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "2c76dcdf", + "id": "65f4f031", "metadata": { "tags": [ "solution" @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "2c8d8392", + "id": "cd0c9073", "metadata": {}, "source": [ "\n", @@ -454,7 +454,7 @@ }, { "cell_type": "markdown", - "id": "a07717e2", + "id": "35fa7df0", "metadata": { "tags": [ "solution" @@ -468,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "4ee432da", + "id": "a71de89d", "metadata": { "tags": [ "solution" @@ -482,7 +482,7 @@ }, { "cell_type": "markdown", - "id": "d3c3a011", + "id": "668ace10", "metadata": {}, "source": [ "\n", @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "268d8f77", + "id": "ff0282fd", "metadata": {}, "source": [ "\n", @@ -513,7 +513,7 @@ }, { "cell_type": "markdown", - "id": "19b3e9a5", + "id": "1d263d87", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -524,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "caf5144a", + "id": "d5f30730", "metadata": {}, "outputs": [], "source": [ @@ -538,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "3cb4972e", + "id": "34d32f34", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -547,7 +547,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c7cd32d8", + "id": "3a9ce68d", "metadata": {}, "outputs": [], "source": [ @@ -572,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "cfaa20f5", + "id": "73af4b1e", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -581,7 +581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f28f649", + "id": "ea45a709", "metadata": {}, "outputs": [], "source": [ @@ -600,7 +600,7 @@ }, { "cell_type": "markdown", - "id": "2a6ca814", + "id": "181835ee", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -609,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1d63d1f0", + "id": "8cde2c47", "metadata": {}, "outputs": [], "source": [ @@ -637,7 +637,7 @@ }, { "cell_type": "markdown", - "id": "368ddef6", + "id": "9be61218", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -646,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5c7179ea", + "id": "1e0a85d1", "metadata": {}, "outputs": [], "source": [ @@ -660,7 +660,7 @@ }, { "cell_type": "markdown", - "id": "1281320d", + "id": "e2f00338", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -669,7 +669,7 @@ { "cell_type": "code", "execution_count": null, - "id": "29300596", + "id": "cfb172ed", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "b478e9a2", + "id": "bf3e7984", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -711,7 +711,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3a3ea5ee", + "id": "a7a4c9cd", "metadata": {}, "outputs": [], "source": [ @@ -726,7 +726,7 @@ }, { "cell_type": "markdown", - "id": "45a743b0", + "id": "16ec7aa5", "metadata": {}, "source": [ "

    \n", @@ -737,7 +737,7 @@ }, { "cell_type": "markdown", - "id": "4453f570", + "id": "87696ddb", "metadata": { "tags": [ "solution" @@ -751,7 +751,7 @@ }, { "cell_type": "markdown", - "id": "06888c5e", + "id": "af11ee30", "metadata": { "tags": [ "solution" @@ -765,7 +765,7 @@ }, { "cell_type": "markdown", - "id": "c2f5dd4a", + "id": "cbbab816", "metadata": {}, "source": [ "

    \n", @@ -776,7 +776,7 @@ }, { "cell_type": "markdown", - "id": "984f28b7", + "id": "f521cd32", "metadata": { "tags": [ "solution" @@ -790,7 +790,7 @@ }, { "cell_type": "markdown", - "id": "1a72bff3", + "id": "82e1cae1", "metadata": { "tags": [ "solution" @@ -804,7 +804,7 @@ }, { "cell_type": "markdown", - "id": "e2e463f8", + "id": "5a9e3077", "metadata": {}, "source": [ "

    \n", @@ -815,7 +815,7 @@ }, { "cell_type": "markdown", - "id": "689bd850", + "id": "96383ab6", "metadata": { "tags": [ "solution" @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "88b5a0e9", + "id": "e45500c6", "metadata": { "tags": [ "solution" @@ -843,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "91004669", + "id": "d2b3efeb", "metadata": {}, "source": [ "

    \n", @@ -855,7 +855,7 @@ }, { "cell_type": "markdown", - "id": "783f333a", + "id": "f64e94c4", "metadata": {}, "source": [ "

    \n", @@ -870,7 +870,7 @@ }, { "cell_type": "markdown", - "id": "b9f629f4", + "id": "881c9823", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -883,7 +883,7 @@ { "cell_type": "code", "execution_count": null, - "id": "313602bc", + "id": "d71fa37e", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "f5b1e743", + "id": "93aedf63", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d36d59bd", + "id": "1b2d5627", "metadata": {}, "outputs": [], "source": [ @@ -926,7 +926,7 @@ }, { "cell_type": "markdown", - "id": "528279ef", + "id": "47e48c92", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -935,7 +935,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ccd7078d", + "id": "476302a9", "metadata": { "lines_to_next_cell": 1 }, @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "f014b862", + "id": "8292cd76", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -999,7 +999,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a997795e", + "id": "aca77d2f", "metadata": {}, "outputs": [], "source": [ @@ -1011,7 +1011,7 @@ }, { "cell_type": "markdown", - "id": "251a4775", + "id": "7984ae4a", "metadata": {}, "source": [ "

    \n", @@ -1022,7 +1022,7 @@ }, { "cell_type": "markdown", - "id": "f4b2be9d", + "id": "5307c0d1", "metadata": { "tags": [ "solution" @@ -1036,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "26e7c295", + "id": "e684dacc", "metadata": { "tags": [ "solution" @@ -1051,7 +1051,7 @@ }, { "cell_type": "markdown", - "id": "98b1abfc", + "id": "e01afe04", "metadata": {}, "source": [ "

    \n", @@ -1062,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "ad8ad2f6", + "id": "16484d12", "metadata": { "tags": [ "solution" @@ -1076,7 +1076,7 @@ }, { "cell_type": "markdown", - "id": "0567c6b1", + "id": "04f4f20a", "metadata": { "tags": [ "solution" @@ -1090,7 +1090,7 @@ }, { "cell_type": "markdown", - "id": "9f2c7ee5", + "id": "7beab007", "metadata": {}, "source": [ "

    \n", @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "b7aa2a67", + "id": "c08c09e6", "metadata": { "tags": [ "solution" @@ -1115,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "ecf332a4", + "id": "1842db75", "metadata": { "tags": [ "solution" @@ -1132,7 +1132,7 @@ }, { "cell_type": "markdown", - "id": "6d691057", + "id": "9912eaea", "metadata": {}, "source": [ "

    \n", @@ -1143,7 +1143,7 @@ }, { "cell_type": "markdown", - "id": "6304edc5", + "id": "7dfdd3fc", "metadata": { "tags": [ "solution" @@ -1157,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "373835b8", + "id": "2366cb0e", "metadata": { "tags": [ "solution" @@ -1177,7 +1177,7 @@ }, { "cell_type": "markdown", - "id": "2b31d7cd", + "id": "c185a436", "metadata": {}, "source": [ "

    \n", @@ -1189,7 +1189,7 @@ }, { "cell_type": "markdown", - "id": "67c6426c", + "id": "fe4f594d", "metadata": {}, "source": [ "

    \n", @@ -1204,7 +1204,7 @@ }, { "cell_type": "markdown", - "id": "375e2be8", + "id": "bcc0a701", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1213,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "2f95e4fd", + "id": "e073c3e8", "metadata": {}, "source": [ "\n", @@ -1223,7 +1223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45e612f9", + "id": "5d69b7dd", "metadata": {}, "outputs": [], "source": [ @@ -1256,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "fb97d7c6", + "id": "03a80462", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1265,7 +1265,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8195d1b2", + "id": "ccf5010d", "metadata": {}, "outputs": [], "source": [ @@ -1304,7 +1304,7 @@ }, { "cell_type": "markdown", - "id": "862b9110", + "id": "136ed21c", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1315,7 +1315,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c4a3d563", + "id": "bfa754f1", "metadata": {}, "outputs": [], "source": [ @@ -1325,7 +1325,7 @@ }, { "cell_type": "markdown", - "id": "84d908aa", + "id": "586539eb", "metadata": {}, "source": [ "

    \n", @@ -1336,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "ed95224f", + "id": "9694c30c", "metadata": { "tags": [ "solution" @@ -1350,7 +1350,7 @@ }, { "cell_type": "markdown", - "id": "6a30c2f0", + "id": "939de302", "metadata": { "tags": [ "solution" @@ -1365,7 +1365,7 @@ }, { "cell_type": "markdown", - "id": "3c331cc0", + "id": "be2a6130", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1374,7 +1374,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d23a0a46", + "id": "c102fd3e", "metadata": {}, "outputs": [], "source": [ @@ -1384,7 +1384,7 @@ }, { "cell_type": "markdown", - "id": "79e4b018", + "id": "1bf26d58", "metadata": {}, "source": [ "

    \n", @@ -1395,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "af9bf85f", + "id": "83c7d2cd", "metadata": { "tags": [ "solution" @@ -1409,7 +1409,7 @@ }, { "cell_type": "markdown", - "id": "986394b7", + "id": "48494f03", "metadata": { "tags": [ "solution" @@ -1427,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "39f60336", + "id": "5130501e", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1436,7 +1436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3d4a9adb", + "id": "dce44b30", "metadata": {}, "outputs": [], "source": [ @@ -1448,7 +1448,7 @@ }, { "cell_type": "markdown", - "id": "0e791fdd", + "id": "6f25a55d", "metadata": {}, "source": [ "

    \n", @@ -1459,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "f0e935ca", + "id": "2b5d1bfa", "metadata": { "tags": [ "solution" @@ -1473,7 +1473,7 @@ }, { "cell_type": "markdown", - "id": "8673f2ff", + "id": "4c2b1b28", "metadata": { "tags": [ "solution" @@ -1490,7 +1490,7 @@ }, { "cell_type": "markdown", - "id": "405a8957", + "id": "a8b618c2", "metadata": {}, "source": [ "

    \n", @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "49f3e7ca", + "id": "61e2deba", "metadata": { "tags": [ "solution" @@ -1515,7 +1515,7 @@ }, { "cell_type": "markdown", - "id": "04ca7800", + "id": "42fd76a2", "metadata": { "tags": [ "solution" @@ -1531,7 +1531,7 @@ }, { "cell_type": "markdown", - "id": "1a04f6cb", + "id": "f0a1cd54", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "dc56b0cb", + "id": "037011ae", "metadata": {}, "source": [ "

    \n", @@ -1558,7 +1558,7 @@ }, { "cell_type": "markdown", - "id": "8210771f", + "id": "581fae79", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1570,7 +1570,7 @@ }, { "cell_type": "markdown", - "id": "bf9fa417", + "id": "79ad51e9", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1579,7 +1579,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ca5dac26", + "id": "94ed56c0", "metadata": {}, "outputs": [], "source": [ @@ -1592,7 +1592,7 @@ }, { "cell_type": "markdown", - "id": "ceefcab1", + "id": "afe03383", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1601,7 +1601,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3f3fd43e", + "id": "fa00a616", "metadata": {}, "outputs": [], "source": [ @@ -1630,7 +1630,7 @@ }, { "cell_type": "markdown", - "id": "1c698bbe", + "id": "9a58a0f3", "metadata": {}, "source": [ "### UNet model\n", @@ -1640,7 +1640,7 @@ }, { "cell_type": "markdown", - "id": "540f8d70", + "id": "01e95305", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1649,7 +1649,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d718c04e", + "id": "3bc9b22b", "metadata": {}, "outputs": [], "source": [ @@ -1697,7 +1697,7 @@ }, { "cell_type": "markdown", - "id": "b0661574", + "id": "881bb411", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1706,7 +1706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a1c6d1cc", + "id": "877dcc7d", "metadata": {}, "outputs": [], "source": [ @@ -1744,7 +1744,7 @@ }, { "cell_type": "markdown", - "id": "e911ce2b", + "id": "c0dbe5e2", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1753,7 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e0257ab8", + "id": "2a2c4ab2", "metadata": {}, "outputs": [], "source": [ @@ -1764,7 +1764,7 @@ }, { "cell_type": "markdown", - "id": "1835f3c7", + "id": "55137d7a", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1773,7 +1773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4540888c", + "id": "f01abff9", "metadata": { "lines_to_next_cell": 1 }, @@ -1789,7 +1789,7 @@ }, { "cell_type": "markdown", - "id": "24327a52", + "id": "b0d0c70b", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1800,7 +1800,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d2e6491e", + "id": "1b563891", "metadata": { "lines_to_next_cell": 1 }, @@ -1817,7 +1817,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0efac3a1", + "id": "068942ab", "metadata": { "lines_to_next_cell": 1 }, @@ -1843,7 +1843,7 @@ }, { "cell_type": "markdown", - "id": "c53fb585", + "id": "07938ae0", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1852,7 +1852,7 @@ { "cell_type": "code", "execution_count": null, - "id": "70f7a947", + "id": "630e1f59", "metadata": {}, "outputs": [], "source": [ @@ -1862,7 +1862,7 @@ }, { "cell_type": "markdown", - "id": "8c217234", + "id": "8914370a", "metadata": {}, "source": [ "

    \n", @@ -1873,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "eee055f8", + "id": "0e6d8b40", "metadata": { "tags": [ "solution" @@ -1887,7 +1887,7 @@ }, { "cell_type": "markdown", - "id": "78eb810d", + "id": "b6a88786", "metadata": { "tags": [ "solution" @@ -1901,7 +1901,7 @@ }, { "cell_type": "markdown", - "id": "e36eaa48", + "id": "5017b1c3", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1911,7 +1911,7 @@ }, { "cell_type": "markdown", - "id": "cc49f415", + "id": "e50373f7", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1922,7 +1922,7 @@ { "cell_type": "code", "execution_count": null, - "id": "79dcdd30", + "id": "6dff3118", "metadata": {}, "outputs": [], "source": [ @@ -1943,7 +1943,7 @@ }, { "cell_type": "markdown", - "id": "195e6b9b", + "id": "1433ad9c", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1952,7 +1952,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4e02c987", + "id": "6a832c31", "metadata": {}, "outputs": [], "source": [ @@ -1962,7 +1962,7 @@ }, { "cell_type": "markdown", - "id": "578fb924", + "id": "53cfae9b", "metadata": {}, "source": [ "

    \n", @@ -1973,7 +1973,7 @@ }, { "cell_type": "markdown", - "id": "2c252dc7", + "id": "dba04fd3", "metadata": { "tags": [ "solution" @@ -1987,7 +1987,7 @@ }, { "cell_type": "markdown", - "id": "1a514f98", + "id": "3775073f", "metadata": { "tags": [ "solution" @@ -2001,7 +2001,7 @@ }, { "cell_type": "markdown", - "id": "4ff4ba7b", + "id": "a9ad5714", "metadata": {}, "source": [ "

    \n", @@ -2012,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "30d7efee", + "id": "a448f9ff", "metadata": { "tags": [ "solution" @@ -2026,7 +2026,7 @@ }, { "cell_type": "markdown", - "id": "659604ee", + "id": "09093432", "metadata": { "tags": [ "solution" @@ -2041,7 +2041,7 @@ }, { "cell_type": "markdown", - "id": "8adaff00", + "id": "c8b27d2f", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2052,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "43654912", + "id": "9dd06cbe", "metadata": {}, "outputs": [], "source": [ @@ -2089,7 +2089,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d180fc34", + "id": "9323e735", "metadata": {}, "outputs": [], "source": [ @@ -2100,7 +2100,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d1e26609", + "id": "6deca8db", "metadata": {}, "outputs": [], "source": [ @@ -2110,7 +2110,7 @@ }, { "cell_type": "markdown", - "id": "047be54e", + "id": "3e031c63", "metadata": {}, "source": [ "

    \n", @@ -2121,7 +2121,7 @@ }, { "cell_type": "markdown", - "id": "aadffe0d", + "id": "f4c8b47d", "metadata": { "tags": [ "solution" @@ -2140,7 +2140,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ba529a37", + "id": "cddddf38", "metadata": {}, "outputs": [], "source": [ @@ -2177,7 +2177,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f4a13962", + "id": "78119dc2", "metadata": {}, "outputs": [], "source": [ @@ -2188,7 +2188,7 @@ { "cell_type": "code", "execution_count": null, - "id": "70c1463f", + "id": "3681154e", "metadata": {}, "outputs": [], "source": [ @@ -2198,7 +2198,7 @@ }, { "cell_type": "markdown", - "id": "dad1e74b", + "id": "0e8a1051", "metadata": {}, "source": [ "

    \n", @@ -2209,7 +2209,7 @@ }, { "cell_type": "markdown", - "id": "9aaf034c", + "id": "a69d6601", "metadata": { "tags": [ "solution" @@ -2223,7 +2223,7 @@ }, { "cell_type": "markdown", - "id": "622d21de", + "id": "c8a6256f", "metadata": {}, "source": [ "\n", @@ -2237,7 +2237,7 @@ }, { "cell_type": "markdown", - "id": "6c7a8133", + "id": "a3d4743b", "metadata": {}, "source": [ "\n", @@ -2251,7 +2251,7 @@ }, { "cell_type": "markdown", - "id": "39445134", + "id": "048cd031", "metadata": {}, "source": [] } From 8d26f5e3550d0a17ee11a42c36128742b47b03b9 Mon Sep 17 00:00:00 2001 From: Anna Foix Date: Mon, 19 Aug 2024 01:05:33 +0100 Subject: [PATCH 42/51] change tqdm.auto to only tqdm because of printing problems in jupyter --- solution.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/solution.py b/solution.py index 0e9cf02..745cfa3 100644 --- a/solution.py +++ b/solution.py @@ -311,7 +311,7 @@ # Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop. # %% -from tqdm.auto import tqdm +from tqdm import tqdm # Training function: def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): From 862c65f771eedf75232319228db600a93113e809 Mon Sep 17 00:00:00 2001 From: afoix Date: Mon, 19 Aug 2024 00:06:44 +0000 Subject: [PATCH 43/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 236 ++++++++++++++++++------------------- solution.ipynb | 312 ++++++++++++++++++++++++------------------------- 2 files changed, 274 insertions(+), 274 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 343f9c0..825565c 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "88362ef4", + "id": "32e9a3ff", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "4bc6c9f4", + "id": "14f7e5c5", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "4e2191ab", + "id": "b3f01058", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "4ec20197", + "id": "6e00d0a5", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "370be730", + "id": "8e22caa6", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c575c9e6", + "id": "78859698", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "8b7939e4", + "id": "3a919a2b", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a15d9890", + "id": "d97dd503", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "074deff8", + "id": "6b7f185d", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "91ce7e66", + "id": "809f06b3", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "190a4fb6", + "id": "ab84ac2a", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "655e6ea2", + "id": "a6ac15eb", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "affd9304", + "id": "317b7750", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "99b5bd59", + "id": "9d9e9d29", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "de3512d8", + "id": "45f694dd", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "bead10d5", + "id": "393fabd3", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c71888a", + "id": "2d42797d", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "2b85cd48", + "id": "4bc5dbbf", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eef94199", + "id": "a8316e01", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "86335552", + "id": "b1813a88", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1c189457", + "id": "0da537d9", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "bd4e5de4", + "id": "9d52525b", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b3ba43fb", + "id": "3da13396", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5d1a7443", + "id": "9a574027", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "7d4c6382", + "id": "b5f9669e", "metadata": {}, "source": [ "

    \n", @@ -328,7 +328,7 @@ }, { "cell_type": "markdown", - "id": "cd0c9073", + "id": "49f29cfa", "metadata": {}, "source": [ "\n", @@ -340,7 +340,7 @@ }, { "cell_type": "markdown", - "id": "668ace10", + "id": "5cc8d289", "metadata": {}, "source": [ "\n", @@ -353,7 +353,7 @@ }, { "cell_type": "markdown", - "id": "ff0282fd", + "id": "f6344ee0", "metadata": {}, "source": [ "\n", @@ -371,7 +371,7 @@ }, { "cell_type": "markdown", - "id": "1d263d87", + "id": "9ed6712d", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -382,7 +382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d5f30730", + "id": "8f50e627", "metadata": {}, "outputs": [], "source": [ @@ -396,7 +396,7 @@ }, { "cell_type": "markdown", - "id": "34d32f34", + "id": "e4ff9d38", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -405,11 +405,11 @@ { "cell_type": "code", "execution_count": null, - "id": "3a9ce68d", + "id": "09880627", "metadata": {}, "outputs": [], "source": [ - "from tqdm.auto import tqdm\n", + "from tqdm import tqdm\n", "\n", "# Training function:\n", "def train_mnist(model, train_loader, batch_size, criterion, optimizer, history):\n", @@ -430,7 +430,7 @@ }, { "cell_type": "markdown", - "id": "73af4b1e", + "id": "608d3b8d", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -439,7 +439,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ea45a709", + "id": "fb663954", "metadata": {}, "outputs": [], "source": [ @@ -458,7 +458,7 @@ }, { "cell_type": "markdown", - "id": "181835ee", + "id": "60e94694", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -467,7 +467,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8cde2c47", + "id": "555e5d3e", "metadata": {}, "outputs": [], "source": [ @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "9be61218", + "id": "0802649b", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -504,7 +504,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1e0a85d1", + "id": "de2b11db", "metadata": {}, "outputs": [], "source": [ @@ -518,7 +518,7 @@ }, { "cell_type": "markdown", - "id": "e2f00338", + "id": "ba79624d", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -527,7 +527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cfb172ed", + "id": "534bcda6", "metadata": {}, "outputs": [], "source": [ @@ -560,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "bf3e7984", + "id": "1604e50b", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -569,7 +569,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a7a4c9cd", + "id": "d655cc98", "metadata": {}, "outputs": [], "source": [ @@ -584,7 +584,7 @@ }, { "cell_type": "markdown", - "id": "16ec7aa5", + "id": "5aee0f7b", "metadata": {}, "source": [ "

    \n", @@ -595,7 +595,7 @@ }, { "cell_type": "markdown", - "id": "cbbab816", + "id": "17fb3a1e", "metadata": {}, "source": [ "

    \n", @@ -606,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "5a9e3077", + "id": "f89eb1e4", "metadata": {}, "source": [ "

    \n", @@ -617,7 +617,7 @@ }, { "cell_type": "markdown", - "id": "d2b3efeb", + "id": "dbaa3b78", "metadata": {}, "source": [ "

    \n", @@ -629,7 +629,7 @@ }, { "cell_type": "markdown", - "id": "f64e94c4", + "id": "e9e0f3ce", "metadata": {}, "source": [ "

    \n", @@ -644,7 +644,7 @@ }, { "cell_type": "markdown", - "id": "881c9823", + "id": "1751b788", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -657,7 +657,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d71fa37e", + "id": "c0853f13", "metadata": {}, "outputs": [], "source": [ @@ -679,7 +679,7 @@ }, { "cell_type": "markdown", - "id": "93aedf63", + "id": "71a2f9cf", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -688,7 +688,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1b2d5627", + "id": "ff3be5a7", "metadata": {}, "outputs": [], "source": [ @@ -700,7 +700,7 @@ }, { "cell_type": "markdown", - "id": "47e48c92", + "id": "a5f3fbc9", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -709,7 +709,7 @@ { "cell_type": "code", "execution_count": null, - "id": "476302a9", + "id": "5f0e804c", "metadata": { "lines_to_next_cell": 1 }, @@ -764,7 +764,7 @@ }, { "cell_type": "markdown", - "id": "8292cd76", + "id": "869d3190", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -773,7 +773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aca77d2f", + "id": "2efb0286", "metadata": {}, "outputs": [], "source": [ @@ -785,7 +785,7 @@ }, { "cell_type": "markdown", - "id": "7984ae4a", + "id": "5c8983a8", "metadata": {}, "source": [ "

    \n", @@ -796,7 +796,7 @@ }, { "cell_type": "markdown", - "id": "e01afe04", + "id": "93c1483f", "metadata": {}, "source": [ "

    \n", @@ -807,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "7beab007", + "id": "319465a3", "metadata": {}, "source": [ "

    \n", @@ -818,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "9912eaea", + "id": "8467009a", "metadata": {}, "source": [ "

    \n", @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "c185a436", + "id": "1b2061b7", "metadata": {}, "source": [ "

    \n", @@ -841,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "fe4f594d", + "id": "6ef0ce00", "metadata": {}, "source": [ "

    \n", @@ -856,7 +856,7 @@ }, { "cell_type": "markdown", - "id": "bcc0a701", + "id": "d961c467", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "e073c3e8", + "id": "5a5aa094", "metadata": {}, "source": [ "\n", @@ -875,7 +875,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5d69b7dd", + "id": "5aa90a8b", "metadata": {}, "outputs": [], "source": [ @@ -908,7 +908,7 @@ }, { "cell_type": "markdown", - "id": "03a80462", + "id": "6b73c86e", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -917,7 +917,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ccf5010d", + "id": "66a0588b", "metadata": {}, "outputs": [], "source": [ @@ -956,7 +956,7 @@ }, { "cell_type": "markdown", - "id": "136ed21c", + "id": "a637525d", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -967,7 +967,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bfa754f1", + "id": "a06d0634", "metadata": {}, "outputs": [], "source": [ @@ -977,7 +977,7 @@ }, { "cell_type": "markdown", - "id": "586539eb", + "id": "0822d5ff", "metadata": {}, "source": [ "

    \n", @@ -988,7 +988,7 @@ }, { "cell_type": "markdown", - "id": "be2a6130", + "id": "cee392ec", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -997,7 +997,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c102fd3e", + "id": "62929d9e", "metadata": {}, "outputs": [], "source": [ @@ -1007,7 +1007,7 @@ }, { "cell_type": "markdown", - "id": "1bf26d58", + "id": "e49b5678", "metadata": {}, "source": [ "

    \n", @@ -1018,7 +1018,7 @@ }, { "cell_type": "markdown", - "id": "5130501e", + "id": "f33a3636", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1027,7 +1027,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dce44b30", + "id": "98f09f64", "metadata": {}, "outputs": [], "source": [ @@ -1039,7 +1039,7 @@ }, { "cell_type": "markdown", - "id": "6f25a55d", + "id": "059654d6", "metadata": {}, "source": [ "

    \n", @@ -1050,7 +1050,7 @@ }, { "cell_type": "markdown", - "id": "a8b618c2", + "id": "a859b818", "metadata": {}, "source": [ "

    \n", @@ -1061,7 +1061,7 @@ }, { "cell_type": "markdown", - "id": "f0a1cd54", + "id": "9e419f62", "metadata": {}, "source": [ "

    \n", @@ -1074,7 +1074,7 @@ }, { "cell_type": "markdown", - "id": "037011ae", + "id": "6b2959a2", "metadata": {}, "source": [ "

    \n", @@ -1088,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "581fae79", + "id": "76193ea5", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1100,7 +1100,7 @@ }, { "cell_type": "markdown", - "id": "79ad51e9", + "id": "afdb487c", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1109,7 +1109,7 @@ { "cell_type": "code", "execution_count": null, - "id": "94ed56c0", + "id": "66dd076a", "metadata": {}, "outputs": [], "source": [ @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "afe03383", + "id": "98cb3bb8", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1131,7 +1131,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fa00a616", + "id": "63f337f7", "metadata": {}, "outputs": [], "source": [ @@ -1160,7 +1160,7 @@ }, { "cell_type": "markdown", - "id": "9a58a0f3", + "id": "8853090e", "metadata": {}, "source": [ "### UNet model\n", @@ -1170,7 +1170,7 @@ }, { "cell_type": "markdown", - "id": "01e95305", + "id": "bfba19a4", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1179,7 +1179,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3bc9b22b", + "id": "34de1247", "metadata": {}, "outputs": [], "source": [ @@ -1227,7 +1227,7 @@ }, { "cell_type": "markdown", - "id": "881bb411", + "id": "86f458bb", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1236,7 +1236,7 @@ { "cell_type": "code", "execution_count": null, - "id": "877dcc7d", + "id": "a69275b4", "metadata": {}, "outputs": [], "source": [ @@ -1274,7 +1274,7 @@ }, { "cell_type": "markdown", - "id": "c0dbe5e2", + "id": "2cfec16b", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1283,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2a2c4ab2", + "id": "9b3103df", "metadata": {}, "outputs": [], "source": [ @@ -1294,7 +1294,7 @@ }, { "cell_type": "markdown", - "id": "55137d7a", + "id": "a8ddab2b", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1303,7 +1303,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f01abff9", + "id": "b749e2d3", "metadata": { "lines_to_next_cell": 1 }, @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "b0d0c70b", + "id": "33b18ff9", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1330,7 +1330,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1b563891", + "id": "7fb1ba9d", "metadata": { "lines_to_next_cell": 1 }, @@ -1347,7 +1347,7 @@ { "cell_type": "code", "execution_count": null, - "id": "068942ab", + "id": "6d0b2276", "metadata": { "lines_to_next_cell": 1 }, @@ -1373,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "07938ae0", + "id": "d64d4b73", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1382,7 +1382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "630e1f59", + "id": "d201b55f", "metadata": {}, "outputs": [], "source": [ @@ -1392,7 +1392,7 @@ }, { "cell_type": "markdown", - "id": "8914370a", + "id": "216613e6", "metadata": {}, "source": [ "

    \n", @@ -1403,7 +1403,7 @@ }, { "cell_type": "markdown", - "id": "5017b1c3", + "id": "1e8bbf40", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1413,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "e50373f7", + "id": "ec89d5cf", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1424,7 +1424,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6dff3118", + "id": "e006bc77", "metadata": {}, "outputs": [], "source": [ @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "1433ad9c", + "id": "d20560de", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1454,7 +1454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6a832c31", + "id": "2c0ffe7c", "metadata": {}, "outputs": [], "source": [ @@ -1464,7 +1464,7 @@ }, { "cell_type": "markdown", - "id": "53cfae9b", + "id": "e0bc45a6", "metadata": {}, "source": [ "

    \n", @@ -1475,7 +1475,7 @@ }, { "cell_type": "markdown", - "id": "a9ad5714", + "id": "6d61dfab", "metadata": {}, "source": [ "

    \n", @@ -1486,7 +1486,7 @@ }, { "cell_type": "markdown", - "id": "c8b27d2f", + "id": "e6483d98", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1497,7 +1497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9dd06cbe", + "id": "09e48578", "metadata": {}, "outputs": [], "source": [ @@ -1534,7 +1534,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9323e735", + "id": "2f080bc7", "metadata": {}, "outputs": [], "source": [ @@ -1545,7 +1545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6deca8db", + "id": "361df7de", "metadata": {}, "outputs": [], "source": [ @@ -1555,7 +1555,7 @@ }, { "cell_type": "markdown", - "id": "3e031c63", + "id": "f88adf9e", "metadata": {}, "source": [ "

    \n", @@ -1567,7 +1567,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cddddf38", + "id": "ef8f51df", "metadata": {}, "outputs": [], "source": [ @@ -1604,7 +1604,7 @@ { "cell_type": "code", "execution_count": null, - "id": "78119dc2", + "id": "34473ef0", "metadata": {}, "outputs": [], "source": [ @@ -1615,7 +1615,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3681154e", + "id": "65bffa85", "metadata": {}, "outputs": [], "source": [ @@ -1625,7 +1625,7 @@ }, { "cell_type": "markdown", - "id": "0e8a1051", + "id": "388c8c72", "metadata": {}, "source": [ "

    \n", @@ -1636,7 +1636,7 @@ }, { "cell_type": "markdown", - "id": "c8a6256f", + "id": "52244cd5", "metadata": {}, "source": [ "\n", @@ -1650,7 +1650,7 @@ }, { "cell_type": "markdown", - "id": "a3d4743b", + "id": "3af95611", "metadata": {}, "source": [ "\n", @@ -1664,7 +1664,7 @@ }, { "cell_type": "markdown", - "id": "048cd031", + "id": "c0afb23d", "metadata": {}, "source": [] } diff --git a/solution.ipynb b/solution.ipynb index d1d7e2d..a2ce143 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "88362ef4", + "id": "32e9a3ff", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "4bc6c9f4", + "id": "14f7e5c5", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks. \n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "4e2191ab", + "id": "b3f01058", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "4ec20197", + "id": "6e00d0a5", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "370be730", + "id": "8e22caa6", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c575c9e6", + "id": "78859698", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "8b7939e4", + "id": "3a919a2b", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a15d9890", + "id": "d97dd503", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "074deff8", + "id": "6b7f185d", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "91ce7e66", + "id": "809f06b3", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "190a4fb6", + "id": "ab84ac2a", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "655e6ea2", + "id": "a6ac15eb", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "affd9304", + "id": "317b7750", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "c06900dd", + "id": "15d65e34", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "b2031b44", + "id": "e875a155", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "99b5bd59", + "id": "9d9e9d29", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "feb94d71", + "id": "fdd6c00c", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "7952b94f", + "id": "92c4842a", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "de3512d8", + "id": "45f694dd", "metadata": {}, "source": [ "## Part 1.2: Global Corrution of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "bead10d5", + "id": "393fabd3", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0c71888a", + "id": "2d42797d", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "2b85cd48", + "id": "4bc5dbbf", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eef94199", + "id": "a8316e01", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "86335552", + "id": "b1813a88", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1c189457", + "id": "0da537d9", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "bd4e5de4", + "id": "9d52525b", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b3ba43fb", + "id": "3da13396", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5d1a7443", + "id": "9a574027", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "7d4c6382", + "id": "b5f9669e", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "ac8e3bfc", + "id": "892e0020", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "65f4f031", + "id": "78618a74", "metadata": { "tags": [ "solution" @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "cd0c9073", + "id": "49f29cfa", "metadata": {}, "source": [ "\n", @@ -454,7 +454,7 @@ }, { "cell_type": "markdown", - "id": "35fa7df0", + "id": "61798afa", "metadata": { "tags": [ "solution" @@ -468,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "a71de89d", + "id": "37ce1282", "metadata": { "tags": [ "solution" @@ -482,7 +482,7 @@ }, { "cell_type": "markdown", - "id": "668ace10", + "id": "5cc8d289", "metadata": {}, "source": [ "\n", @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "ff0282fd", + "id": "f6344ee0", "metadata": {}, "source": [ "\n", @@ -513,7 +513,7 @@ }, { "cell_type": "markdown", - "id": "1d263d87", + "id": "9ed6712d", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -524,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d5f30730", + "id": "8f50e627", "metadata": {}, "outputs": [], "source": [ @@ -538,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "34d32f34", + "id": "e4ff9d38", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -547,11 +547,11 @@ { "cell_type": "code", "execution_count": null, - "id": "3a9ce68d", + "id": "09880627", "metadata": {}, "outputs": [], "source": [ - "from tqdm.auto import tqdm\n", + "from tqdm import tqdm\n", "\n", "# Training function:\n", "def train_mnist(model, train_loader, batch_size, criterion, optimizer, history):\n", @@ -572,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "73af4b1e", + "id": "608d3b8d", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -581,7 +581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ea45a709", + "id": "fb663954", "metadata": {}, "outputs": [], "source": [ @@ -600,7 +600,7 @@ }, { "cell_type": "markdown", - "id": "181835ee", + "id": "60e94694", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -609,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8cde2c47", + "id": "555e5d3e", "metadata": {}, "outputs": [], "source": [ @@ -637,7 +637,7 @@ }, { "cell_type": "markdown", - "id": "9be61218", + "id": "0802649b", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -646,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1e0a85d1", + "id": "de2b11db", "metadata": {}, "outputs": [], "source": [ @@ -660,7 +660,7 @@ }, { "cell_type": "markdown", - "id": "e2f00338", + "id": "ba79624d", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -669,7 +669,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cfb172ed", + "id": "534bcda6", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "bf3e7984", + "id": "1604e50b", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -711,7 +711,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a7a4c9cd", + "id": "d655cc98", "metadata": {}, "outputs": [], "source": [ @@ -726,7 +726,7 @@ }, { "cell_type": "markdown", - "id": "16ec7aa5", + "id": "5aee0f7b", "metadata": {}, "source": [ "

    \n", @@ -737,7 +737,7 @@ }, { "cell_type": "markdown", - "id": "87696ddb", + "id": "f40ca98e", "metadata": { "tags": [ "solution" @@ -751,7 +751,7 @@ }, { "cell_type": "markdown", - "id": "af11ee30", + "id": "e943902a", "metadata": { "tags": [ "solution" @@ -765,7 +765,7 @@ }, { "cell_type": "markdown", - "id": "cbbab816", + "id": "17fb3a1e", "metadata": {}, "source": [ "

    \n", @@ -776,7 +776,7 @@ }, { "cell_type": "markdown", - "id": "f521cd32", + "id": "f1f09c49", "metadata": { "tags": [ "solution" @@ -790,7 +790,7 @@ }, { "cell_type": "markdown", - "id": "82e1cae1", + "id": "95c710a7", "metadata": { "tags": [ "solution" @@ -804,7 +804,7 @@ }, { "cell_type": "markdown", - "id": "5a9e3077", + "id": "f89eb1e4", "metadata": {}, "source": [ "

    \n", @@ -815,7 +815,7 @@ }, { "cell_type": "markdown", - "id": "96383ab6", + "id": "84594622", "metadata": { "tags": [ "solution" @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "e45500c6", + "id": "1d7d8c11", "metadata": { "tags": [ "solution" @@ -843,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "d2b3efeb", + "id": "dbaa3b78", "metadata": {}, "source": [ "

    \n", @@ -855,7 +855,7 @@ }, { "cell_type": "markdown", - "id": "f64e94c4", + "id": "e9e0f3ce", "metadata": {}, "source": [ "

    \n", @@ -870,7 +870,7 @@ }, { "cell_type": "markdown", - "id": "881c9823", + "id": "1751b788", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -883,7 +883,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d71fa37e", + "id": "c0853f13", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "93aedf63", + "id": "71a2f9cf", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1b2d5627", + "id": "ff3be5a7", "metadata": {}, "outputs": [], "source": [ @@ -926,7 +926,7 @@ }, { "cell_type": "markdown", - "id": "47e48c92", + "id": "a5f3fbc9", "metadata": {}, "source": [ "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -935,7 +935,7 @@ { "cell_type": "code", "execution_count": null, - "id": "476302a9", + "id": "5f0e804c", "metadata": { "lines_to_next_cell": 1 }, @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "8292cd76", + "id": "869d3190", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -999,7 +999,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aca77d2f", + "id": "2efb0286", "metadata": {}, "outputs": [], "source": [ @@ -1011,7 +1011,7 @@ }, { "cell_type": "markdown", - "id": "7984ae4a", + "id": "5c8983a8", "metadata": {}, "source": [ "

    \n", @@ -1022,7 +1022,7 @@ }, { "cell_type": "markdown", - "id": "5307c0d1", + "id": "8ccb1031", "metadata": { "tags": [ "solution" @@ -1036,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "e684dacc", + "id": "2bc050a2", "metadata": { "tags": [ "solution" @@ -1051,7 +1051,7 @@ }, { "cell_type": "markdown", - "id": "e01afe04", + "id": "93c1483f", "metadata": {}, "source": [ "

    \n", @@ -1062,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "16484d12", + "id": "0cd4264c", "metadata": { "tags": [ "solution" @@ -1076,7 +1076,7 @@ }, { "cell_type": "markdown", - "id": "04f4f20a", + "id": "eac78a24", "metadata": { "tags": [ "solution" @@ -1090,7 +1090,7 @@ }, { "cell_type": "markdown", - "id": "7beab007", + "id": "319465a3", "metadata": {}, "source": [ "

    \n", @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "c08c09e6", + "id": "e6de7dbb", "metadata": { "tags": [ "solution" @@ -1115,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "1842db75", + "id": "3f361a66", "metadata": { "tags": [ "solution" @@ -1132,7 +1132,7 @@ }, { "cell_type": "markdown", - "id": "9912eaea", + "id": "8467009a", "metadata": {}, "source": [ "

    \n", @@ -1143,7 +1143,7 @@ }, { "cell_type": "markdown", - "id": "7dfdd3fc", + "id": "8c4869f8", "metadata": { "tags": [ "solution" @@ -1157,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "2366cb0e", + "id": "c837f9b3", "metadata": { "tags": [ "solution" @@ -1177,7 +1177,7 @@ }, { "cell_type": "markdown", - "id": "c185a436", + "id": "1b2061b7", "metadata": {}, "source": [ "

    \n", @@ -1189,7 +1189,7 @@ }, { "cell_type": "markdown", - "id": "fe4f594d", + "id": "6ef0ce00", "metadata": {}, "source": [ "

    \n", @@ -1204,7 +1204,7 @@ }, { "cell_type": "markdown", - "id": "bcc0a701", + "id": "d961c467", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1213,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "e073c3e8", + "id": "5a5aa094", "metadata": {}, "source": [ "\n", @@ -1223,7 +1223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5d69b7dd", + "id": "5aa90a8b", "metadata": {}, "outputs": [], "source": [ @@ -1256,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "03a80462", + "id": "6b73c86e", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1265,7 +1265,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ccf5010d", + "id": "66a0588b", "metadata": {}, "outputs": [], "source": [ @@ -1304,7 +1304,7 @@ }, { "cell_type": "markdown", - "id": "136ed21c", + "id": "a637525d", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", @@ -1315,7 +1315,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bfa754f1", + "id": "a06d0634", "metadata": {}, "outputs": [], "source": [ @@ -1325,7 +1325,7 @@ }, { "cell_type": "markdown", - "id": "586539eb", + "id": "0822d5ff", "metadata": {}, "source": [ "

    \n", @@ -1336,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "9694c30c", + "id": "2d8cad8d", "metadata": { "tags": [ "solution" @@ -1350,7 +1350,7 @@ }, { "cell_type": "markdown", - "id": "939de302", + "id": "efa956a2", "metadata": { "tags": [ "solution" @@ -1365,7 +1365,7 @@ }, { "cell_type": "markdown", - "id": "be2a6130", + "id": "cee392ec", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1374,7 +1374,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c102fd3e", + "id": "62929d9e", "metadata": {}, "outputs": [], "source": [ @@ -1384,7 +1384,7 @@ }, { "cell_type": "markdown", - "id": "1bf26d58", + "id": "e49b5678", "metadata": {}, "source": [ "

    \n", @@ -1395,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "83c7d2cd", + "id": "f77be72e", "metadata": { "tags": [ "solution" @@ -1409,7 +1409,7 @@ }, { "cell_type": "markdown", - "id": "48494f03", + "id": "4c82acb5", "metadata": { "tags": [ "solution" @@ -1427,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "5130501e", + "id": "f33a3636", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1436,7 +1436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "dce44b30", + "id": "98f09f64", "metadata": {}, "outputs": [], "source": [ @@ -1448,7 +1448,7 @@ }, { "cell_type": "markdown", - "id": "6f25a55d", + "id": "059654d6", "metadata": {}, "source": [ "

    \n", @@ -1459,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "2b5d1bfa", + "id": "4b8a0959", "metadata": { "tags": [ "solution" @@ -1473,7 +1473,7 @@ }, { "cell_type": "markdown", - "id": "4c2b1b28", + "id": "7f52c9ca", "metadata": { "tags": [ "solution" @@ -1490,7 +1490,7 @@ }, { "cell_type": "markdown", - "id": "a8b618c2", + "id": "a859b818", "metadata": {}, "source": [ "

    \n", @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "61e2deba", + "id": "7be27091", "metadata": { "tags": [ "solution" @@ -1515,7 +1515,7 @@ }, { "cell_type": "markdown", - "id": "42fd76a2", + "id": "b582bc42", "metadata": { "tags": [ "solution" @@ -1531,7 +1531,7 @@ }, { "cell_type": "markdown", - "id": "f0a1cd54", + "id": "9e419f62", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "037011ae", + "id": "6b2959a2", "metadata": {}, "source": [ "

    \n", @@ -1558,7 +1558,7 @@ }, { "cell_type": "markdown", - "id": "581fae79", + "id": "76193ea5", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1570,7 +1570,7 @@ }, { "cell_type": "markdown", - "id": "79ad51e9", + "id": "afdb487c", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1579,7 +1579,7 @@ { "cell_type": "code", "execution_count": null, - "id": "94ed56c0", + "id": "66dd076a", "metadata": {}, "outputs": [], "source": [ @@ -1592,7 +1592,7 @@ }, { "cell_type": "markdown", - "id": "afe03383", + "id": "98cb3bb8", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1601,7 +1601,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fa00a616", + "id": "63f337f7", "metadata": {}, "outputs": [], "source": [ @@ -1630,7 +1630,7 @@ }, { "cell_type": "markdown", - "id": "9a58a0f3", + "id": "8853090e", "metadata": {}, "source": [ "### UNet model\n", @@ -1640,7 +1640,7 @@ }, { "cell_type": "markdown", - "id": "01e95305", + "id": "bfba19a4", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1649,7 +1649,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3bc9b22b", + "id": "34de1247", "metadata": {}, "outputs": [], "source": [ @@ -1697,7 +1697,7 @@ }, { "cell_type": "markdown", - "id": "881bb411", + "id": "86f458bb", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1706,7 +1706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "877dcc7d", + "id": "a69275b4", "metadata": {}, "outputs": [], "source": [ @@ -1744,7 +1744,7 @@ }, { "cell_type": "markdown", - "id": "c0dbe5e2", + "id": "2cfec16b", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1753,7 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2a2c4ab2", + "id": "9b3103df", "metadata": {}, "outputs": [], "source": [ @@ -1764,7 +1764,7 @@ }, { "cell_type": "markdown", - "id": "55137d7a", + "id": "a8ddab2b", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1773,7 +1773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f01abff9", + "id": "b749e2d3", "metadata": { "lines_to_next_cell": 1 }, @@ -1789,7 +1789,7 @@ }, { "cell_type": "markdown", - "id": "b0d0c70b", + "id": "33b18ff9", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1800,7 +1800,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1b563891", + "id": "7fb1ba9d", "metadata": { "lines_to_next_cell": 1 }, @@ -1817,7 +1817,7 @@ { "cell_type": "code", "execution_count": null, - "id": "068942ab", + "id": "6d0b2276", "metadata": { "lines_to_next_cell": 1 }, @@ -1843,7 +1843,7 @@ }, { "cell_type": "markdown", - "id": "07938ae0", + "id": "d64d4b73", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1852,7 +1852,7 @@ { "cell_type": "code", "execution_count": null, - "id": "630e1f59", + "id": "d201b55f", "metadata": {}, "outputs": [], "source": [ @@ -1862,7 +1862,7 @@ }, { "cell_type": "markdown", - "id": "8914370a", + "id": "216613e6", "metadata": {}, "source": [ "

    \n", @@ -1873,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "0e6d8b40", + "id": "3947715c", "metadata": { "tags": [ "solution" @@ -1887,7 +1887,7 @@ }, { "cell_type": "markdown", - "id": "b6a88786", + "id": "1b69380e", "metadata": { "tags": [ "solution" @@ -1901,7 +1901,7 @@ }, { "cell_type": "markdown", - "id": "5017b1c3", + "id": "1e8bbf40", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data \n", @@ -1911,7 +1911,7 @@ }, { "cell_type": "markdown", - "id": "e50373f7", + "id": "ec89d5cf", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1922,7 +1922,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6dff3118", + "id": "e006bc77", "metadata": {}, "outputs": [], "source": [ @@ -1943,7 +1943,7 @@ }, { "cell_type": "markdown", - "id": "1433ad9c", + "id": "d20560de", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1952,7 +1952,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6a832c31", + "id": "2c0ffe7c", "metadata": {}, "outputs": [], "source": [ @@ -1962,7 +1962,7 @@ }, { "cell_type": "markdown", - "id": "53cfae9b", + "id": "e0bc45a6", "metadata": {}, "source": [ "

    \n", @@ -1973,7 +1973,7 @@ }, { "cell_type": "markdown", - "id": "dba04fd3", + "id": "0d240f0a", "metadata": { "tags": [ "solution" @@ -1987,7 +1987,7 @@ }, { "cell_type": "markdown", - "id": "3775073f", + "id": "16da4bf5", "metadata": { "tags": [ "solution" @@ -2001,7 +2001,7 @@ }, { "cell_type": "markdown", - "id": "a9ad5714", + "id": "6d61dfab", "metadata": {}, "source": [ "

    \n", @@ -2012,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "a448f9ff", + "id": "67e12194", "metadata": { "tags": [ "solution" @@ -2026,7 +2026,7 @@ }, { "cell_type": "markdown", - "id": "09093432", + "id": "00ff2115", "metadata": { "tags": [ "solution" @@ -2041,7 +2041,7 @@ }, { "cell_type": "markdown", - "id": "c8b27d2f", + "id": "e6483d98", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2052,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9dd06cbe", + "id": "09e48578", "metadata": {}, "outputs": [], "source": [ @@ -2089,7 +2089,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9323e735", + "id": "2f080bc7", "metadata": {}, "outputs": [], "source": [ @@ -2100,7 +2100,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6deca8db", + "id": "361df7de", "metadata": {}, "outputs": [], "source": [ @@ -2110,7 +2110,7 @@ }, { "cell_type": "markdown", - "id": "3e031c63", + "id": "f88adf9e", "metadata": {}, "source": [ "

    \n", @@ -2121,7 +2121,7 @@ }, { "cell_type": "markdown", - "id": "f4c8b47d", + "id": "ceb7d13a", "metadata": { "tags": [ "solution" @@ -2140,7 +2140,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cddddf38", + "id": "ef8f51df", "metadata": {}, "outputs": [], "source": [ @@ -2177,7 +2177,7 @@ { "cell_type": "code", "execution_count": null, - "id": "78119dc2", + "id": "34473ef0", "metadata": {}, "outputs": [], "source": [ @@ -2188,7 +2188,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3681154e", + "id": "65bffa85", "metadata": {}, "outputs": [], "source": [ @@ -2198,7 +2198,7 @@ }, { "cell_type": "markdown", - "id": "0e8a1051", + "id": "388c8c72", "metadata": {}, "source": [ "

    \n", @@ -2209,7 +2209,7 @@ }, { "cell_type": "markdown", - "id": "a69d6601", + "id": "38a1e793", "metadata": { "tags": [ "solution" @@ -2223,7 +2223,7 @@ }, { "cell_type": "markdown", - "id": "c8a6256f", + "id": "52244cd5", "metadata": {}, "source": [ "\n", @@ -2237,7 +2237,7 @@ }, { "cell_type": "markdown", - "id": "a3d4743b", + "id": "3af95611", "metadata": {}, "source": [ "\n", @@ -2251,7 +2251,7 @@ }, { "cell_type": "markdown", - "id": "048cd031", + "id": "c0afb23d", "metadata": {}, "source": [] } From d2ecece7ed66b204f9cf9527941bdf39d3b062a5 Mon Sep 17 00:00:00 2001 From: Diane Adjavon Date: Mon, 19 Aug 2024 13:55:47 -0400 Subject: [PATCH 44/51] Fix typos --- solution.py | 86 ++++++++++++++++++++++++++--------------------------- 1 file changed, 43 insertions(+), 43 deletions(-) diff --git a/solution.py b/solution.py index 745cfa3..9ac874d 100644 --- a/solution.py +++ b/solution.py @@ -17,12 +17,12 @@ # # Exercise 7: Failure Modes And Limits of Deep Learning # %% [markdown] -# In the following exercise, we explore the failure modes and limits of neural networks. -# Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail. +# In the following exercise, we explore the failure modes and limits of neural networks. +# Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail. # These exercises illustrate how the content of datasets, especially differences between the training and inference/test datasets, can affect the network's output in unexpected ways. #

    -# While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the "internal reasoning" of the network as much as possible to discover failure modes, or situations in which the network does not perform well. -# This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network "attention". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output. +# While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the "internal reasoning" of the network as much as possible to discover failure modes, or situations in which the network does not perform well. +# This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network "attention". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output. # %% [markdown] # @@ -50,7 +50,7 @@ # The following will load the MNIST dataset, which already comes split into a training and testing dataset. # The MNIST dataset contains images of handwritten digits 0-9. # This data was already downloaded in the setup script. -# Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html +# Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html # %% import torchvision @@ -75,7 +75,7 @@ # In this section we will make small changes to specific classes of data in the MNIST dataset. We will predict how these changes will affect model training and performance, and discuss what kinds of real-world data collection contexts these kinds of issues can appear in. # %% -#Imports: +# Imports: import torch import numpy from scipy.ndimage import convolve @@ -89,7 +89,7 @@ # %% [markdown] # ## Part 1.1: Local Corruption of Data # -# First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corruped. +# First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corrupted. # %% # Add a white pixel in the bottom right of all images of 7's @@ -122,9 +122,9 @@ # %% [markdown] tags=["solution"] # **1.1 Answer:** # -# In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images. +# In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberrations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images. # -# In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. +# In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positioning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. # %% [markdown] tags=["solution"] # **1.1 Answer from 2023 Students:** @@ -142,7 +142,7 @@ # %% [markdown] tags=["solution"] # **1.2 Answer** # -# We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset. +# We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Cropping the corrupted region in all the samples will guarantee that the information of the contaminated area will be ignored across the dataset. # %% [markdown] tags=["solution"] # **1.2 Answer from 2023 Students** @@ -157,9 +157,9 @@ # - Add more noise!? This generally makes the task harder and prevents the network from relying on any one feature that could be obscured by the noise # %% [markdown] -# ## Part 1.2: Global Corrution of data +# ## Part 1.2: Global Corruption of data # -# Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s. +# Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s. # %% [markdown] # You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues. @@ -191,7 +191,7 @@ tainted_test_dataset.data[test_dataset.targets==4] += texture # %% [markdown] -# After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. +# After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. # Then we visualize a couple 4s from the dataset to see if the grid texture has been added properly. # %% @@ -228,7 +228,7 @@ # %% [markdown] tags=["solution"] # **1.3 Answer** # -# A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact. +# A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data acquisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact. # # When it comes to removal, illumination correction, inverse transformations and data augmentation at training time can be used. # @@ -265,12 +265,12 @@ # %% [markdown] tags=["solution"] # **1.4 Answer:** # -# The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying. +# The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpreted as a feature to rely on when classifying. # %% [markdown] tags=["solution"] # **1.4 Answer from 2023 Students** # -# We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! +# We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! # # %% [markdown] @@ -289,7 +289,7 @@ #
      #
    1. Consider a dataset with white dots on images of all digits: let's call it the all-dots data. How different is this from the original dataset? Are the classes more or less distinct from each other?
      2. #
    2. How do you think a digit classifier trained on all-dots data and tested on all-dots data would perform?
      3. -#
    3. Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      4. +#
    4. Now consider the analogous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      5. #
    # If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section. #

    @@ -362,7 +362,7 @@ def init_weights(m): if isinstance(m, (nn.Linear, nn.Conv2d)): torch.nn.init.xavier_uniform_(m.weight, ) m.bias.data.fill_(0.01) - + # Fixing seed with magical number and setting weights: torch.random.manual_seed(42) model_clean.apply(init_weights) @@ -433,12 +433,12 @@ def init_weights(m): # %% [markdown] tags=["solution"] # **2.1 Answer:** # -# As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify. +# As previously mentioned, the classes in the tainted dataset are more distinct from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify. # %% [markdown] tags=["solution"] # **2.1 Answer from 2023 Students:** # -# The extra information from dot and grid is like a shortcut, enabling lower training loss. +# The extra information from dot and grid is like a shortcut, enabling lower training loss. # %% [markdown] #

    @@ -494,7 +494,7 @@ def init_weights(m): # # Now that we have initialized our clean and tainted datasets and trained our models on them, it is time to examine how these models perform on the clean and tainted test sets! # -# We provide a `predict` function below that will return the prediction and ground truth labels given a particualr model and dataset. +# We provide a `predict` function below that will return the prediction and ground truth labels given a particular model and dataset. # %% import numpy as np @@ -523,14 +523,14 @@ def predict(model, dataset): pred_tainted_tainted, _ = predict(model_tainted, tainted_test_dataset) # %% [markdown] -# We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix. +# We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix. # %% from sklearn.metrics import confusion_matrix import seaborn as sns import pandas as pd -# Plot confusion matrix -# orginally from Runqi Yang; +# Plot confusion matrix +# originally from Runqi Yang; # see https://gist.github.com/hitvoice/36cf44689065ca9b927431546381a3f7 def cm_analysis(y_true, y_pred, title, figsize=(10,10)): """ @@ -590,13 +590,13 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # %% [markdown] tags=["solution"] # **3.1 Answer:** # -# The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments). +# The clean model on the clean dataset predicted 5s least accurately, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments). # %% [markdown] tags=["solution"] # **3.1 Answer from 2023 Students** # # 5 is the least accurately predicted digit. It is most confused with 6 or 3. -# Handwriting creates fives that look like sixes or threes. +# Handwriting creates fives that look like sixes or threes. # %% [markdown] #

    @@ -630,7 +630,7 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # # Local corruption vs Global corruption: Global corruption WINS (aka is harder)! # -# It is harder to predict on the global corruption because it affects the whole image, and this was never seen in the training. +# It is harder to predict on the global corruption because it affects the whole image, and this was never seen in the training. # It adds (structured) noise over the entire four. # %% [markdown] @@ -642,18 +642,18 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): # %% [markdown] tags=["solution"] # **3.4 Answer:** # -# The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data. +# The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption used both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data. # %% [markdown] tags=["solution"] # **3.4 Answer from 2023 Students:** # # Clean 7s vs clean 4s: 4 WINS! (aka is worse) # -# Global corruptions are more detrimental when testing on the clean data. This is because the training images are *more* different from each other. +# Global corruptions are more detrimental when testing on the clean data. This is because the training images are *more* different from each other. # -# Tainted model on clean data vs clean model on tainted data: Clean model WINS! (is better on tainted data than tained model on clean data) +# Tainted model on clean data vs clean model on tainted data: Clean model WINS! (is better on tainted data than tainted model on clean data) # -# The clean model still has useful signal to work with in the tainted data. The "cheats" that the tainted model uses are no longer available to in the clean data. +# The clean model still has useful signal to work with in the tainted data. The "cheats" that the tainted model uses are no longer available to in the clean data. # %% [markdown] #

    @@ -720,11 +720,11 @@ def visualize_integrated_gradients(test_input, model, plot_title): # Transpose integrated gradients output attr_ig = np.transpose(attr_ig[0].cpu().detach().numpy(), (1, 2, 0)) - + # Transpose and normalize original image: original_image = np.transpose((test_input[0].detach().numpy() * 0.5) + 0.5, (1, 2, 0)) - # This visualises the attribution of labels to pixels + # This visualises the attribution of labels to pixels figure, axis = plt.subplots(nrows=1, ncols=2, figsize=(4, 2.5), width_ratios=[1, 1]) viz.visualize_image_attr(attr_ig, original_image, @@ -747,7 +747,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # %% [markdown] -# To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. +# To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. # # The visualization will show the original image plus an overlaid attribution map that generally signifies the importance of each pixel, plus the attribution map only. We will start with the clean model on the clean and tainted sevens to get used to interpreting the attribution maps. # @@ -758,7 +758,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # %% [markdown] #

    -# Task 4.1: Interpereting the Clean Model's Attention on 7s

    +# Task 4.1: Interpreting the Clean Model's Attention on 7s

    # Where did the clean model focus its attention for the clean and tainted 7s? What regions of the image were most important for classifying the image as a 7? #
    @@ -782,7 +782,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # %% [markdown] #

    -# Task 4.2: Interpereting the Tainted Model's Attention on 7s

    +# Task 4.2: Interpreting the Tainted Model's Attention on 7s

    # Where did the tainted model focus its attention for the clean and tainted 7s? How was this different than the clean model? Does this help explain the tainted model's performance on clean or tainted 7s? #
    @@ -811,7 +811,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): # %% [markdown] #

    -# Task 4.3: Interpereting the focus on 4s

    +# Task 4.3: Interpreting the focus on 4s

    # Where did the tainted model focus its attention for the tainted and clean 4s? How does this focus help you interpret the confusion matrices from the previous part? #
    @@ -837,20 +837,20 @@ def visualize_integrated_gradients(test_input, model, plot_title): # %% [markdown] tags=["solution"] # **4.4 Answer:** # -# The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally. +# The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to identify individual pixels of interest when pixels are meaningful when considered globally. # %% [markdown] tags=["solution"] # **4.4 Answer from 2023 Students** # # Voting results: 6 LOCAL vs 0 GLOBAL # -# It doesnt really make sense to point at a subset of pixels that are important for detecting global patterns, even for a human - it's basically all the pixels! +# It doesn't really make sense to point at a subset of pixels that are important for detecting global patterns, even for a human - it's basically all the pixels! # %% [markdown] #

    # Checkpoint 4

    #
      -# Congrats on finishing the intergrated gradients task! Let us know on Element that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested. +# Congrats on finishing the integrated gradients task! Let us know on Element that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested. #
    #
    @@ -911,7 +911,7 @@ def show(index): # %% [markdown] # ### UNet model # -# Let's try denoising with a UNet, "CARE-style". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. +# Let's try denoising with a UNet, "CARE-style". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. # %% [markdown] # The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises. @@ -1068,7 +1068,7 @@ def visualize_denoising(model, dataset, index): # It does decently well, not perfect cause it's lots of noise # %% [markdown] -# ### Apply trained model on 'wrong' data +# ### Apply trained model on 'wrong' data # # Apply the denoising model trained above to some example _noisy_ images derived from the Fashion-MNIST dataset. # @@ -1114,7 +1114,7 @@ def visualize_denoising(model, dataset, index): # %% [markdown] tags=["solution"] # **5.2 Answer from 2023 Students:** # -# BAD! Some of them kind of look like numbers. +# BAD! Some of them kind of look like numbers. # %% [markdown] #

    From 92eb6b6dc1aeeefdfe64648c98b7f62ad4f9ad3b Mon Sep 17 00:00:00 2001 From: Diane Adjavon Date: Mon, 19 Aug 2024 13:56:52 -0400 Subject: [PATCH 45/51] Remove references to Element --- solution.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/solution.py b/solution.py index 9ac874d..36deacc 100644 --- a/solution.py +++ b/solution.py @@ -850,7 +850,7 @@ def visualize_integrated_gradients(test_input, model, plot_title): #

    # Checkpoint 4

    #
      -# Congrats on finishing the integrated gradients task! Let us know on Element that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested. +# Congrats on finishing the integrated gradients task! Let us know on the course chat that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested. #
    #
    @@ -1246,7 +1246,7 @@ def visualize_denoising(model, dataset, index): #

    # Checkpoint 5

    #
      -# Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass. +# Congrats on reaching the final checkpoint! Let us know on the course chat, and we'll discuss the questions once reaching critical mass. #
    #
    From d77a4545a20c8ba2996ff650772deefaaca5c518 Mon Sep 17 00:00:00 2001 From: Diane Adjavon Date: Mon, 19 Aug 2024 14:07:34 -0400 Subject: [PATCH 46/51] Remove hard-coded CUDA --- solution.py | 34 +++++++++++++++++----------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/solution.py b/solution.py index 36deacc..61ae152 100644 --- a/solution.py +++ b/solution.py @@ -319,8 +319,8 @@ def train_mnist(model, train_loader, batch_size, criterion, optimizer, history): pbar = tqdm(total=len(tainted_train_dataset)//batch_size) for batch_idx, (raw, target) in enumerate(train_loader): optimizer.zero_grad() - raw = raw.cuda() - target = target.cuda() + raw = raw.to(device) + target = target.to(device) output = model(raw) loss = criterion(output, target) loss.backward() @@ -505,11 +505,11 @@ def predict(model, dataset): dataset_groundtruth = [] with torch.no_grad(): for x, y_true in dataset: - inp = x[None].cuda() + inp = x[None].to(device) y_pred = model(inp) dataset_prediction.append(y_pred.argmax().cpu().numpy()) dataset_groundtruth.append(y_true) - + return np.array(dataset_prediction), np.array(dataset_groundtruth) @@ -920,40 +920,40 @@ def show(index): from tqdm import tqdm def train_denoising_model(train_loader, model, criterion, optimizer, history): - + # Puts model in 'training' mode: model.train() - + # Initialises progress bar: pbar = tqdm(total=len(train_loader.dataset)//batch_size_train) for batch_idx, (image, target) in enumerate(train_loader): # add line here during Task 2.2 - + # Zeroing gradients: optimizer.zero_grad() - + # Moves image to GPU memory: - image = image.cuda() - + image = image.to(device) + # Adds noise to make the noisy image: noisy = add_noise(image) - + # Runs model on noisy image: output = model(noisy) - + # Computes loss: loss = criterion(output, image) - + # Backpropagates gradients: loss.backward() - + # Optimises model parameters given the current gradients: optimizer.step() - + # appends loss history: history["loss"].append(loss.item()) - + # updates progress bar: pbar.update(1) return history @@ -1022,7 +1022,7 @@ def train_denoising_model(train_loader, model, criterion, optimizer, history): def apply_denoising(image, model): # add batch and channel dimensions image = torch.unsqueeze(torch.unsqueeze(image, 0), 0) - prediction = model(image.cuda()) + prediction = model(image.to(device)) # remove batch and channel dimensions before returning return prediction.detach().cpu()[0,0] From 878b60ee1ff07d9ae2a8d28579b1b343df570ded Mon Sep 17 00:00:00 2001 From: Diane Adjavon Date: Mon, 19 Aug 2024 14:09:58 -0400 Subject: [PATCH 47/51] Fix confusion matrix visualization --- solution.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/solution.py b/solution.py index 61ae152..1f5cac2 100644 --- a/solution.py +++ b/solution.py @@ -565,11 +565,11 @@ def cm_analysis(y_true, y_pred, title, figsize=(10,10)): annot[i, j] = '' else: annot[i, j] = '%.1f%%\n%d' % (p, c) - cm = pd.DataFrame(cm, index=labels, columns=labels) + cm = pd.DataFrame(cm_perc, index=labels, columns=labels) cm.index.name = 'Actual' cm.columns.name = 'Predicted' fig, ax = plt.subplots(figsize=figsize) - ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30) + ax = sns.heatmap(cm, annot=annot, fmt="", vmax=100) ax.set_title(title) # %% [markdown] From 41e70b4584450815dfc55b3a926cdb42dfa0ba8a Mon Sep 17 00:00:00 2001 From: adjavon Date: Mon, 19 Aug 2024 18:10:51 +0000 Subject: [PATCH 48/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 324 ++++++++++++++++++------------------ solution.ipynb | 436 ++++++++++++++++++++++++------------------------- 2 files changed, 380 insertions(+), 380 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 825565c..6de2231 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "32e9a3ff", + "id": "400d2e03", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,20 +10,20 @@ }, { "cell_type": "markdown", - "id": "14f7e5c5", + "id": "394f293f", "metadata": {}, "source": [ - "In the following exercise, we explore the failure modes and limits of neural networks. \n", - "Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail. \n", + "In the following exercise, we explore the failure modes and limits of neural networks.\n", + "Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail.\n", "These exercises illustrate how the content of datasets, especially differences between the training and inference/test datasets, can affect the network's output in unexpected ways.\n", "

    \n", - "While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the \"internal reasoning\" of the network as much as possible to discover failure modes, or situations in which the network does not perform well. \n", - "This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network \"attention\". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output. " + "While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the \"internal reasoning\" of the network as much as possible to discover failure modes, or situations in which the network does not perform well.\n", + "This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network \"attention\". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output." ] }, { "cell_type": "markdown", - "id": "b3f01058", + "id": "0734f242", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "6e00d0a5", + "id": "b8c60ec0", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "8e22caa6", + "id": "1c8d915c", "metadata": {}, "source": [ "### Data Loading\n", @@ -61,13 +61,13 @@ "The following will load the MNIST dataset, which already comes split into a training and testing dataset.\n", "The MNIST dataset contains images of handwritten digits 0-9.\n", "This data was already downloaded in the setup script.\n", - "Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html " + "Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html" ] }, { "cell_type": "code", "execution_count": null, - "id": "78859698", + "id": "9e3f7120", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "3a919a2b", + "id": "2b767ea4", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,11 +101,11 @@ { "cell_type": "code", "execution_count": null, - "id": "d97dd503", + "id": "989ccfe9", "metadata": {}, "outputs": [], "source": [ - "#Imports:\n", + "# Imports:\n", "import torch\n", "import numpy\n", "from scipy.ndimage import convolve\n", @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6b7f185d", + "id": "91d01d2d", "metadata": {}, "outputs": [], "source": [ @@ -126,18 +126,18 @@ }, { "cell_type": "markdown", - "id": "809f06b3", + "id": "7d34c3c8", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", "\n", - "First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corruped." + "First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corrupted." ] }, { "cell_type": "code", "execution_count": null, - "id": "ab84ac2a", + "id": "c3e01c63", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a6ac15eb", + "id": "c8a299ee", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "317b7750", + "id": "6ceb0857", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "9d9e9d29", + "id": "cb572ae9", "metadata": {}, "source": [ "

    \n", @@ -194,17 +194,17 @@ }, { "cell_type": "markdown", - "id": "45f694dd", + "id": "631a8c9e", "metadata": {}, "source": [ - "## Part 1.2: Global Corrution of data\n", + "## Part 1.2: Global Corruption of data\n", "\n", - "Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s. " + "Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s." ] }, { "cell_type": "markdown", - "id": "393fabd3", + "id": "70a36235", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2d42797d", + "id": "13873808", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "4bc5dbbf", + "id": "35cbd7d7", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a8316e01", + "id": "34980b74", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "b1813a88", + "id": "59ed11fd", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0da537d9", + "id": "d20eb078", "metadata": {}, "outputs": [], "source": [ @@ -269,17 +269,17 @@ }, { "cell_type": "markdown", - "id": "9d52525b", + "id": "051c02ad", "metadata": {}, "source": [ - "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", + "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8.\n", "Then we visualize a couple 4s from the dataset to see if the grid texture has been added properly." ] }, { "cell_type": "code", "execution_count": null, - "id": "3da13396", + "id": "4564cb56", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9a574027", + "id": "b5a17a23", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "b5f9669e", + "id": "3262735f", "metadata": {}, "source": [ "

    \n", @@ -328,7 +328,7 @@ }, { "cell_type": "markdown", - "id": "49f29cfa", + "id": "ad6b7873", "metadata": {}, "source": [ "\n", @@ -340,7 +340,7 @@ }, { "cell_type": "markdown", - "id": "5cc8d289", + "id": "43162d5f", "metadata": {}, "source": [ "\n", @@ -353,7 +353,7 @@ }, { "cell_type": "markdown", - "id": "f6344ee0", + "id": "26dc8c22", "metadata": {}, "source": [ "\n", @@ -363,7 +363,7 @@ "
      \n", "
    1. Consider a dataset with white dots on images of all digits: let's call it the all-dots data. How different is this from the original dataset? Are the classes more or less distinct from each other?
      2. \n", "
    2. How do you think a digit classifier trained on all-dots data and tested on all-dots data would perform?
      3. \n", - "
    3. Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      4. \n", + "
    4. Now consider the analogous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      5. \n", "
    \n", "If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section.\n", "

    " @@ -371,7 +371,7 @@ }, { "cell_type": "markdown", - "id": "9ed6712d", + "id": "82c8ebea", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -382,7 +382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8f50e627", + "id": "112bc521", "metadata": {}, "outputs": [], "source": [ @@ -396,7 +396,7 @@ }, { "cell_type": "markdown", - "id": "e4ff9d38", + "id": "1b59e4b3", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -405,7 +405,7 @@ { "cell_type": "code", "execution_count": null, - "id": "09880627", + "id": "2f988864", "metadata": {}, "outputs": [], "source": [ @@ -417,8 +417,8 @@ " pbar = tqdm(total=len(tainted_train_dataset)//batch_size)\n", " for batch_idx, (raw, target) in enumerate(train_loader):\n", " optimizer.zero_grad()\n", - " raw = raw.cuda()\n", - " target = target.cuda()\n", + " raw = raw.to(device)\n", + " target = target.to(device)\n", " output = model(raw)\n", " loss = criterion(output, target)\n", " loss.backward()\n", @@ -430,7 +430,7 @@ }, { "cell_type": "markdown", - "id": "608d3b8d", + "id": "42a57b6b", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -439,7 +439,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fb663954", + "id": "e52a71cf", "metadata": {}, "outputs": [], "source": [ @@ -458,7 +458,7 @@ }, { "cell_type": "markdown", - "id": "60e94694", + "id": "7f9f1305", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -467,7 +467,7 @@ { "cell_type": "code", "execution_count": null, - "id": "555e5d3e", + "id": "094feafc", "metadata": {}, "outputs": [], "source": [ @@ -483,7 +483,7 @@ " if isinstance(m, (nn.Linear, nn.Conv2d)):\n", " torch.nn.init.xavier_uniform_(m.weight, )\n", " m.bias.data.fill_(0.01)\n", - " \n", + "\n", "# Fixing seed with magical number and setting weights:\n", "torch.random.manual_seed(42)\n", "model_clean.apply(init_weights)\n", @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "0802649b", + "id": "547c344a", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -504,7 +504,7 @@ { "cell_type": "code", "execution_count": null, - "id": "de2b11db", + "id": "14c3e9a0", "metadata": {}, "outputs": [], "source": [ @@ -518,7 +518,7 @@ }, { "cell_type": "markdown", - "id": "ba79624d", + "id": "caac6dfc", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -527,7 +527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "534bcda6", + "id": "e302a996", "metadata": {}, "outputs": [], "source": [ @@ -560,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "1604e50b", + "id": "2aa1ae7d", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -569,7 +569,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d655cc98", + "id": "6d2b3b3a", "metadata": {}, "outputs": [], "source": [ @@ -584,7 +584,7 @@ }, { "cell_type": "markdown", - "id": "5aee0f7b", + "id": "1bcf5872", "metadata": {}, "source": [ "

    \n", @@ -595,7 +595,7 @@ }, { "cell_type": "markdown", - "id": "17fb3a1e", + "id": "1529ab82", "metadata": {}, "source": [ "

    \n", @@ -606,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "f89eb1e4", + "id": "c5daa29d", "metadata": {}, "source": [ "

    \n", @@ -617,7 +617,7 @@ }, { "cell_type": "markdown", - "id": "dbaa3b78", + "id": "0cef3ffb", "metadata": {}, "source": [ "

    \n", @@ -629,7 +629,7 @@ }, { "cell_type": "markdown", - "id": "e9e0f3ce", + "id": "26e74550", "metadata": {}, "source": [ "

    \n", @@ -644,20 +644,20 @@ }, { "cell_type": "markdown", - "id": "1751b788", + "id": "f8f40037", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", "\n", "Now that we have initialized our clean and tainted datasets and trained our models on them, it is time to examine how these models perform on the clean and tainted test sets!\n", "\n", - "We provide a `predict` function below that will return the prediction and ground truth labels given a particualr model and dataset." + "We provide a `predict` function below that will return the prediction and ground truth labels given a particular model and dataset." ] }, { "cell_type": "code", "execution_count": null, - "id": "c0853f13", + "id": "59344f6a", "metadata": {}, "outputs": [], "source": [ @@ -669,17 +669,17 @@ " dataset_groundtruth = []\n", " with torch.no_grad():\n", " for x, y_true in dataset:\n", - " inp = x[None].cuda()\n", + " inp = x[None].to(device)\n", " y_pred = model(inp)\n", " dataset_prediction.append(y_pred.argmax().cpu().numpy())\n", " dataset_groundtruth.append(y_true)\n", - " \n", + "\n", " return np.array(dataset_prediction), np.array(dataset_groundtruth)" ] }, { "cell_type": "markdown", - "id": "71a2f9cf", + "id": "87a707d4", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -688,7 +688,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ff3be5a7", + "id": "5a8569d3", "metadata": {}, "outputs": [], "source": [ @@ -700,16 +700,16 @@ }, { "cell_type": "markdown", - "id": "a5f3fbc9", + "id": "590238a5", "metadata": {}, "source": [ - "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." + "We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." ] }, { "cell_type": "code", "execution_count": null, - "id": "5f0e804c", + "id": "8637c217", "metadata": { "lines_to_next_cell": 1 }, @@ -718,8 +718,8 @@ "from sklearn.metrics import confusion_matrix\n", "import seaborn as sns\n", "import pandas as pd\n", - "# Plot confusion matrix \n", - "# orginally from Runqi Yang; \n", + "# Plot confusion matrix\n", + "# originally from Runqi Yang;\n", "# see https://gist.github.com/hitvoice/36cf44689065ca9b927431546381a3f7\n", "def cm_analysis(y_true, y_pred, title, figsize=(10,10)):\n", " \"\"\"\n", @@ -754,17 +754,17 @@ " annot[i, j] = ''\n", " else:\n", " annot[i, j] = '%.1f%%\\n%d' % (p, c)\n", - " cm = pd.DataFrame(cm, index=labels, columns=labels)\n", + " cm = pd.DataFrame(cm_perc, index=labels, columns=labels)\n", " cm.index.name = 'Actual'\n", " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", - " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", + " ax = sns.heatmap(cm, annot=annot, fmt=\"\", vmax=100)\n", " ax.set_title(title)" ] }, { "cell_type": "markdown", - "id": "869d3190", + "id": "227322ac", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -773,7 +773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2efb0286", + "id": "3a970ea0", "metadata": {}, "outputs": [], "source": [ @@ -785,7 +785,7 @@ }, { "cell_type": "markdown", - "id": "5c8983a8", + "id": "d32fc6d1", "metadata": {}, "source": [ "

    \n", @@ -796,7 +796,7 @@ }, { "cell_type": "markdown", - "id": "93c1483f", + "id": "6e643061", "metadata": {}, "source": [ "

    \n", @@ -807,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "319465a3", + "id": "2dfde11d", "metadata": {}, "source": [ "

    \n", @@ -818,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "8467009a", + "id": "0e819c67", "metadata": {}, "source": [ "

    \n", @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "1b2061b7", + "id": "10de39bb", "metadata": {}, "source": [ "

    \n", @@ -841,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "6ef0ce00", + "id": "86e2c33e", "metadata": {}, "source": [ "

    \n", @@ -856,7 +856,7 @@ }, { "cell_type": "markdown", - "id": "d961c467", + "id": "1a124f4a", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "5a5aa094", + "id": "991c9adb", "metadata": {}, "source": [ "\n", @@ -875,7 +875,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5aa90a8b", + "id": "9c7dd3ca", "metadata": {}, "outputs": [], "source": [ @@ -908,7 +908,7 @@ }, { "cell_type": "markdown", - "id": "6b73c86e", + "id": "7610d0ff", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -917,7 +917,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66a0588b", + "id": "857a5cec", "metadata": {}, "outputs": [], "source": [ @@ -928,11 +928,11 @@ "\n", " # Transpose integrated gradients output\n", " attr_ig = np.transpose(attr_ig[0].cpu().detach().numpy(), (1, 2, 0))\n", - " \n", + "\n", " # Transpose and normalize original image:\n", " original_image = np.transpose((test_input[0].detach().numpy() * 0.5) + 0.5, (1, 2, 0))\n", "\n", - " # This visualises the attribution of labels to pixels\n", + " # This visualises the attribution of labels to pixels\n", " figure, axis = plt.subplots(nrows=1, ncols=2, figsize=(4, 2.5), width_ratios=[1, 1])\n", " viz.visualize_image_attr(attr_ig, \n", " original_image, \n", @@ -956,10 +956,10 @@ }, { "cell_type": "markdown", - "id": "a637525d", + "id": "f5089370", "metadata": {}, "source": [ - "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", + "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens.\n", "\n", "The visualization will show the original image plus an overlaid attribution map that generally signifies the importance of each pixel, plus the attribution map only. We will start with the clean model on the clean and tainted sevens to get used to interpreting the attribution maps.\n" ] @@ -967,7 +967,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a06d0634", + "id": "67d2539a", "metadata": {}, "outputs": [], "source": [ @@ -977,18 +977,18 @@ }, { "cell_type": "markdown", - "id": "0822d5ff", + "id": "4ac77606", "metadata": {}, "source": [ "

    \n", - " Task 4.1: Interpereting the Clean Model's Attention on 7s

    \n", + " Task 4.1: Interpreting the Clean Model's Attention on 7s

    \n", "Where did the clean model focus its attention for the clean and tainted 7s? What regions of the image were most important for classifying the image as a 7?\n", "
    " ] }, { "cell_type": "markdown", - "id": "cee392ec", + "id": "2b3203e1", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -997,7 +997,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62929d9e", + "id": "0878fa69", "metadata": {}, "outputs": [], "source": [ @@ -1007,18 +1007,18 @@ }, { "cell_type": "markdown", - "id": "e49b5678", + "id": "21fb3bcb", "metadata": {}, "source": [ "

    \n", - " Task 4.2: Interpereting the Tainted Model's Attention on 7s

    \n", + " Task 4.2: Interpreting the Tainted Model's Attention on 7s

    \n", "Where did the tainted model focus its attention for the clean and tainted 7s? How was this different than the clean model? Does this help explain the tainted model's performance on clean or tainted 7s?\n", "
    " ] }, { "cell_type": "markdown", - "id": "f33a3636", + "id": "10fd930e", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1027,7 +1027,7 @@ { "cell_type": "code", "execution_count": null, - "id": "98f09f64", + "id": "4cd9057a", "metadata": {}, "outputs": [], "source": [ @@ -1039,18 +1039,18 @@ }, { "cell_type": "markdown", - "id": "059654d6", + "id": "53abc3bb", "metadata": {}, "source": [ "

    \n", - " Task 4.3: Interpereting the focus on 4s

    \n", + " Task 4.3: Interpreting the focus on 4s

    \n", "Where did the tainted model focus its attention for the tainted and clean 4s? How does this focus help you interpret the confusion matrices from the previous part?\n", "
    " ] }, { "cell_type": "markdown", - "id": "a859b818", + "id": "ee45ee7e", "metadata": {}, "source": [ "

    \n", @@ -1061,20 +1061,20 @@ }, { "cell_type": "markdown", - "id": "9e419f62", + "id": "41a824a7", "metadata": {}, "source": [ "

    \n", " Checkpoint 4

    \n", "
      \n", - " Congrats on finishing the intergrated gradients task! Let us know on Element that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested.\n", + " Congrats on finishing the integrated gradients task! Let us know on the course chat that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested.\n", "
    \n", "
    " ] }, { "cell_type": "markdown", - "id": "6b2959a2", + "id": "91dddcdc", "metadata": {}, "source": [ "

    \n", @@ -1088,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "76193ea5", + "id": "9feabbd4", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1100,7 +1100,7 @@ }, { "cell_type": "markdown", - "id": "afdb487c", + "id": "d48569a6", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1109,7 +1109,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66dd076a", + "id": "d79ed624", "metadata": {}, "outputs": [], "source": [ @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "98cb3bb8", + "id": "63aca81c", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1131,7 +1131,7 @@ { "cell_type": "code", "execution_count": null, - "id": "63f337f7", + "id": "268eb42f", "metadata": {}, "outputs": [], "source": [ @@ -1160,17 +1160,17 @@ }, { "cell_type": "markdown", - "id": "8853090e", + "id": "783d702b", "metadata": {}, "source": [ "### UNet model\n", "\n", - "Let's try denoising with a UNet, \"CARE-style\". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. " + "Let's try denoising with a UNet, \"CARE-style\". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell." ] }, { "cell_type": "markdown", - "id": "bfba19a4", + "id": "f114069b", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1179,47 +1179,47 @@ { "cell_type": "code", "execution_count": null, - "id": "34de1247", + "id": "8d0a5ab3", "metadata": {}, "outputs": [], "source": [ "from tqdm import tqdm\n", "\n", "def train_denoising_model(train_loader, model, criterion, optimizer, history):\n", - " \n", + "\n", " # Puts model in 'training' mode:\n", " model.train()\n", - " \n", + "\n", " # Initialises progress bar:\n", " pbar = tqdm(total=len(train_loader.dataset)//batch_size_train)\n", " for batch_idx, (image, target) in enumerate(train_loader):\n", "\n", " # add line here during Task 2.2\n", - " \n", + "\n", " # Zeroing gradients:\n", " optimizer.zero_grad()\n", - " \n", + "\n", " # Moves image to GPU memory:\n", - " image = image.cuda()\n", - " \n", + " image = image.to(device)\n", + "\n", " # Adds noise to make the noisy image:\n", " noisy = add_noise(image)\n", - " \n", + "\n", " # Runs model on noisy image:\n", " output = model(noisy)\n", - " \n", + "\n", " # Computes loss:\n", " loss = criterion(output, image)\n", - " \n", + "\n", " # Backpropagates gradients:\n", " loss.backward()\n", - " \n", + "\n", " # Optimises model parameters given the current gradients:\n", " optimizer.step()\n", - " \n", + "\n", " # appends loss history:\n", " history[\"loss\"].append(loss.item())\n", - " \n", + "\n", " # updates progress bar:\n", " pbar.update(1)\n", " return history" @@ -1227,7 +1227,7 @@ }, { "cell_type": "markdown", - "id": "86f458bb", + "id": "3f3c87f9", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1236,7 +1236,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a69275b4", + "id": "52c8fb2e", "metadata": {}, "outputs": [], "source": [ @@ -1274,7 +1274,7 @@ }, { "cell_type": "markdown", - "id": "2cfec16b", + "id": "f294c563", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1283,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9b3103df", + "id": "a792d29f", "metadata": {}, "outputs": [], "source": [ @@ -1294,7 +1294,7 @@ }, { "cell_type": "markdown", - "id": "a8ddab2b", + "id": "e4400668", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1303,7 +1303,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b749e2d3", + "id": "38b615ff", "metadata": { "lines_to_next_cell": 1 }, @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "33b18ff9", + "id": "6eef3ca6", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1330,7 +1330,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7fb1ba9d", + "id": "564550c8", "metadata": { "lines_to_next_cell": 1 }, @@ -1339,7 +1339,7 @@ "def apply_denoising(image, model):\n", " # add batch and channel dimensions\n", " image = torch.unsqueeze(torch.unsqueeze(image, 0), 0)\n", - " prediction = model(image.cuda())\n", + " prediction = model(image.to(device))\n", " # remove batch and channel dimensions before returning\n", " return prediction.detach().cpu()[0,0]" ] @@ -1347,7 +1347,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d0b2276", + "id": "c2f88bd6", "metadata": { "lines_to_next_cell": 1 }, @@ -1373,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "d64d4b73", + "id": "d94541f8", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1382,7 +1382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d201b55f", + "id": "2f402794", "metadata": {}, "outputs": [], "source": [ @@ -1392,7 +1392,7 @@ }, { "cell_type": "markdown", - "id": "216613e6", + "id": "527a3789", "metadata": {}, "source": [ "

    \n", @@ -1403,17 +1403,17 @@ }, { "cell_type": "markdown", - "id": "1e8bbf40", + "id": "ec2b36f5", "metadata": {}, "source": [ - "### Apply trained model on 'wrong' data \n", + "### Apply trained model on 'wrong' data\n", "\n", "Apply the denoising model trained above to some example _noisy_ images derived from the Fashion-MNIST dataset.\n" ] }, { "cell_type": "markdown", - "id": "ec89d5cf", + "id": "8194dcee", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1424,7 +1424,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e006bc77", + "id": "e613bf75", "metadata": {}, "outputs": [], "source": [ @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "d20560de", + "id": "324412bf", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1454,7 +1454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c0ffe7c", + "id": "8d094c79", "metadata": {}, "outputs": [], "source": [ @@ -1464,7 +1464,7 @@ }, { "cell_type": "markdown", - "id": "e0bc45a6", + "id": "38893a5f", "metadata": {}, "source": [ "

    \n", @@ -1475,7 +1475,7 @@ }, { "cell_type": "markdown", - "id": "6d61dfab", + "id": "19f22363", "metadata": {}, "source": [ "

    \n", @@ -1486,7 +1486,7 @@ }, { "cell_type": "markdown", - "id": "e6483d98", + "id": "baaba56b", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1497,7 +1497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "09e48578", + "id": "0dbacd4c", "metadata": {}, "outputs": [], "source": [ @@ -1534,7 +1534,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f080bc7", + "id": "d420fd52", "metadata": {}, "outputs": [], "source": [ @@ -1545,7 +1545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "361df7de", + "id": "6d23b631", "metadata": {}, "outputs": [], "source": [ @@ -1555,7 +1555,7 @@ }, { "cell_type": "markdown", - "id": "f88adf9e", + "id": "121897cd", "metadata": {}, "source": [ "

    \n", @@ -1567,7 +1567,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ef8f51df", + "id": "227404b2", "metadata": {}, "outputs": [], "source": [ @@ -1604,7 +1604,7 @@ { "cell_type": "code", "execution_count": null, - "id": "34473ef0", + "id": "01e3e4dc", "metadata": {}, "outputs": [], "source": [ @@ -1615,7 +1615,7 @@ { "cell_type": "code", "execution_count": null, - "id": "65bffa85", + "id": "5df0f7a0", "metadata": {}, "outputs": [], "source": [ @@ -1625,7 +1625,7 @@ }, { "cell_type": "markdown", - "id": "388c8c72", + "id": "510edc26", "metadata": {}, "source": [ "

    \n", @@ -1636,21 +1636,21 @@ }, { "cell_type": "markdown", - "id": "52244cd5", + "id": "21c20845", "metadata": {}, "source": [ "\n", "

    \n", " Checkpoint 5

    \n", "
      \n", - " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", + " Congrats on reaching the final checkpoint! Let us know on the course chat, and we'll discuss the questions once reaching critical mass.\n", "
    \n", "
    " ] }, { "cell_type": "markdown", - "id": "3af95611", + "id": "b7a1fa15", "metadata": {}, "source": [ "\n", @@ -1664,7 +1664,7 @@ }, { "cell_type": "markdown", - "id": "c0afb23d", + "id": "389a3851", "metadata": {}, "source": [] } diff --git a/solution.ipynb b/solution.ipynb index a2ce143..5c1fe6e 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "32e9a3ff", + "id": "400d2e03", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,20 +10,20 @@ }, { "cell_type": "markdown", - "id": "14f7e5c5", + "id": "394f293f", "metadata": {}, "source": [ - "In the following exercise, we explore the failure modes and limits of neural networks. \n", - "Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail. \n", + "In the following exercise, we explore the failure modes and limits of neural networks.\n", + "Neural networks are powerful, but it is important to understand their limits and the predictable reasons that they fail.\n", "These exercises illustrate how the content of datasets, especially differences between the training and inference/test datasets, can affect the network's output in unexpected ways.\n", "

    \n", - "While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the \"internal reasoning\" of the network as much as possible to discover failure modes, or situations in which the network does not perform well. \n", - "This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network \"attention\". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output. " + "While neural networks are generally less interpretable than other types of machine learning, it is still important to investigate the \"internal reasoning\" of the network as much as possible to discover failure modes, or situations in which the network does not perform well.\n", + "This exercise introduces a tool called Integrated Gradients that helps us makes sense of the network \"attention\". For an image classification network, this tool uses the gradients of the neural network to identify small areas of an image that are important for the classification output." ] }, { "cell_type": "markdown", - "id": "b3f01058", + "id": "0734f242", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "6e00d0a5", + "id": "b8c60ec0", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "8e22caa6", + "id": "1c8d915c", "metadata": {}, "source": [ "### Data Loading\n", @@ -61,13 +61,13 @@ "The following will load the MNIST dataset, which already comes split into a training and testing dataset.\n", "The MNIST dataset contains images of handwritten digits 0-9.\n", "This data was already downloaded in the setup script.\n", - "Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html " + "Documentation for this pytorch dataset is available at https://pytorch.org/vision/main/generated/torchvision.datasets.MNIST.html" ] }, { "cell_type": "code", "execution_count": null, - "id": "78859698", + "id": "9e3f7120", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "3a919a2b", + "id": "2b767ea4", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,11 +101,11 @@ { "cell_type": "code", "execution_count": null, - "id": "d97dd503", + "id": "989ccfe9", "metadata": {}, "outputs": [], "source": [ - "#Imports:\n", + "# Imports:\n", "import torch\n", "import numpy\n", "from scipy.ndimage import convolve\n", @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6b7f185d", + "id": "91d01d2d", "metadata": {}, "outputs": [], "source": [ @@ -126,18 +126,18 @@ }, { "cell_type": "markdown", - "id": "809f06b3", + "id": "7d34c3c8", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", "\n", - "First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corruped." + "First we will add a white pixel in the bottom right of all images of 7's, and visualize the results. This is an example of a local change to the images, where only a small portion of the image is corrupted." ] }, { "cell_type": "code", "execution_count": null, - "id": "ab84ac2a", + "id": "c3e01c63", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a6ac15eb", + "id": "c8a299ee", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "317b7750", + "id": "6ceb0857", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "15d65e34", + "id": "60fae5a8", "metadata": { "tags": [ "solution" @@ -192,14 +192,14 @@ "source": [ "**1.1 Answer:**\n", "\n", - "In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images.\n", + "In a microscopy lab, sample preparation error such as improper staining or sample contamination or other technical issues such as optical aberrations and focus drift can cause image corruption. Environmental factors such as vibrations or lighting variations may also contribute to image corruption. Digital artifacts like compression artifacts or noise, and other issues like operator error (improper manipulation, incorrect magnification...) will also lead to corrupted images.\n", "\n", - "In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positionning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data. " + "In a hospital imaging environment, motion artifacts (patient movement), technical issue (equipment malfunction, machine calibration errors), environmental factors (electromagnetic interference, temperature fluctuations), operator errors (improper positioning, incorrect settings), biological factors (metal implant, body motion from bodily functions) are all sources of corrupted data." ] }, { "cell_type": "markdown", - "id": "e875a155", + "id": "1dbe0c7b", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "9d9e9d29", + "id": "cb572ae9", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "fdd6c00c", + "id": "196a2407", "metadata": { "tags": [ "solution" @@ -235,12 +235,12 @@ "source": [ "**1.2 Answer**\n", "\n", - "We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Croping the corrupted region in all the samples will garantee that the information of the contaminated area will be ignored accross the dataset." + "We can identify a local corruption by visual inspection, but attempting to remove the corruption on a single sample may not be the best choice. Cropping the corrupted region in all the samples will guarantee that the information of the contaminated area will be ignored across the dataset." ] }, { "cell_type": "markdown", - "id": "92c4842a", + "id": "93b462a2", "metadata": { "tags": [ "solution" @@ -261,17 +261,17 @@ }, { "cell_type": "markdown", - "id": "45f694dd", + "id": "631a8c9e", "metadata": {}, "source": [ - "## Part 1.2: Global Corrution of data\n", + "## Part 1.2: Global Corruption of data\n", "\n", - "Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s. " + "Some data corruption or domain differences cover the whole image, rather than being localized to a specific location. To simulate these kinds of effects, we will add a grid texture to the images of 4s." ] }, { "cell_type": "markdown", - "id": "393fabd3", + "id": "70a36235", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2d42797d", + "id": "13873808", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "4bc5dbbf", + "id": "35cbd7d7", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a8316e01", + "id": "34980b74", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "b1813a88", + "id": "59ed11fd", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0da537d9", + "id": "d20eb078", "metadata": {}, "outputs": [], "source": [ @@ -336,17 +336,17 @@ }, { "cell_type": "markdown", - "id": "9d52525b", + "id": "051c02ad", "metadata": {}, "source": [ - "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8. \n", + "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8.\n", "Then we visualize a couple 4s from the dataset to see if the grid texture has been added properly." ] }, { "cell_type": "code", "execution_count": null, - "id": "3da13396", + "id": "4564cb56", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9a574027", + "id": "b5a17a23", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "b5f9669e", + "id": "3262735f", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "892e0020", + "id": "ee831b57", "metadata": { "tags": [ "solution" @@ -404,7 +404,7 @@ "source": [ "**1.3 Answer**\n", "\n", - "A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data aqcuisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact.\n", + "A first example of such a corruption would be that of data acquisition being performed with a different device for different classes. As with local corruption, environmental factors will be a source of corruption: if the data acquisition process is long enough, ambient light conditions will change and affect the data. Similarly, vibrations in the surrounding room may have an impact.\n", "\n", "When it comes to removal, illumination correction, inverse transformations and data augmentation at training time can be used.\n", "\n", @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "78618a74", + "id": "aae0a4e4", "metadata": { "tags": [ "solution" @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "49f29cfa", + "id": "ad6b7873", "metadata": {}, "source": [ "\n", @@ -454,7 +454,7 @@ }, { "cell_type": "markdown", - "id": "61798afa", + "id": "c3a25477", "metadata": { "tags": [ "solution" @@ -463,12 +463,12 @@ "source": [ "**1.4 Answer:**\n", "\n", - "The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpretted as a feature to rely on when classifying." + "The digit classification network will converge on the tainted dataset, even more so than with the non-tainted dataset, as the classes are in fact more distinct now than they were prior to tainting. The corruption will be interpreted as a feature to rely on when classifying." ] }, { "cell_type": "markdown", - "id": "37ce1282", + "id": "df788018", "metadata": { "tags": [ "solution" @@ -477,12 +477,12 @@ "source": [ "**1.4 Answer from 2023 Students**\n", "\n", - "We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training! \n" + "We learned that the tainted dataset lets the model cheat and take shortcuts on those classes, so it will converge during training!\n" ] }, { "cell_type": "markdown", - "id": "5cc8d289", + "id": "43162d5f", "metadata": {}, "source": [ "\n", @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "f6344ee0", + "id": "26dc8c22", "metadata": {}, "source": [ "\n", @@ -505,7 +505,7 @@ "
      \n", "
    1. Consider a dataset with white dots on images of all digits: let's call it the all-dots data. How different is this from the original dataset? Are the classes more or less distinct from each other?
      2. \n", "
    2. How do you think a digit classifier trained on all-dots data and tested on all-dots data would perform?
      3. \n", - "
    3. Now consider the analagous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      4. \n", + "
    4. Now consider the analogous all-grid data with the grid pattern added to all images. Are the classes more or less distinct from each other? Would a digit classifier trained on all-grid converge?
      5. \n", "
    \n", "If you want to test your hypotheses, you can create these all-dots and all-grid train and test datasets and use them for training in bonus questions of the following section.\n", "

    " @@ -513,7 +513,7 @@ }, { "cell_type": "markdown", - "id": "9ed6712d", + "id": "82c8ebea", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -524,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8f50e627", + "id": "112bc521", "metadata": {}, "outputs": [], "source": [ @@ -538,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "e4ff9d38", + "id": "1b59e4b3", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -547,7 +547,7 @@ { "cell_type": "code", "execution_count": null, - "id": "09880627", + "id": "2f988864", "metadata": {}, "outputs": [], "source": [ @@ -559,8 +559,8 @@ " pbar = tqdm(total=len(tainted_train_dataset)//batch_size)\n", " for batch_idx, (raw, target) in enumerate(train_loader):\n", " optimizer.zero_grad()\n", - " raw = raw.cuda()\n", - " target = target.cuda()\n", + " raw = raw.to(device)\n", + " target = target.to(device)\n", " output = model(raw)\n", " loss = criterion(output, target)\n", " loss.backward()\n", @@ -572,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "608d3b8d", + "id": "42a57b6b", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -581,7 +581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fb663954", + "id": "e52a71cf", "metadata": {}, "outputs": [], "source": [ @@ -600,7 +600,7 @@ }, { "cell_type": "markdown", - "id": "60e94694", + "id": "7f9f1305", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -609,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "555e5d3e", + "id": "094feafc", "metadata": {}, "outputs": [], "source": [ @@ -625,7 +625,7 @@ " if isinstance(m, (nn.Linear, nn.Conv2d)):\n", " torch.nn.init.xavier_uniform_(m.weight, )\n", " m.bias.data.fill_(0.01)\n", - " \n", + "\n", "# Fixing seed with magical number and setting weights:\n", "torch.random.manual_seed(42)\n", "model_clean.apply(init_weights)\n", @@ -637,7 +637,7 @@ }, { "cell_type": "markdown", - "id": "0802649b", + "id": "547c344a", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -646,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "de2b11db", + "id": "14c3e9a0", "metadata": {}, "outputs": [], "source": [ @@ -660,7 +660,7 @@ }, { "cell_type": "markdown", - "id": "ba79624d", + "id": "caac6dfc", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -669,7 +669,7 @@ { "cell_type": "code", "execution_count": null, - "id": "534bcda6", + "id": "e302a996", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "1604e50b", + "id": "2aa1ae7d", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -711,7 +711,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d655cc98", + "id": "6d2b3b3a", "metadata": {}, "outputs": [], "source": [ @@ -726,7 +726,7 @@ }, { "cell_type": "markdown", - "id": "5aee0f7b", + "id": "1bcf5872", "metadata": {}, "source": [ "

    \n", @@ -737,7 +737,7 @@ }, { "cell_type": "markdown", - "id": "f40ca98e", + "id": "eec7a9fb", "metadata": { "tags": [ "solution" @@ -746,12 +746,12 @@ "source": [ "**2.1 Answer:**\n", "\n", - "As previously mentionned, the classes in the tainted dataset are more distinc from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify." + "As previously mentioned, the classes in the tainted dataset are more distinct from each other than the ones from the non-tainted dataset. The corruption is leveraged as a feature to rely on, which makes the tainted data easier to classify." ] }, { "cell_type": "markdown", - "id": "e943902a", + "id": "dea0439e", "metadata": { "tags": [ "solution" @@ -760,12 +760,12 @@ "source": [ "**2.1 Answer from 2023 Students:**\n", "\n", - "The extra information from dot and grid is like a shortcut, enabling lower training loss. " + "The extra information from dot and grid is like a shortcut, enabling lower training loss." ] }, { "cell_type": "markdown", - "id": "17fb3a1e", + "id": "1529ab82", "metadata": {}, "source": [ "

    \n", @@ -776,7 +776,7 @@ }, { "cell_type": "markdown", - "id": "f1f09c49", + "id": "7174819f", "metadata": { "tags": [ "solution" @@ -790,7 +790,7 @@ }, { "cell_type": "markdown", - "id": "95c710a7", + "id": "f7c519b0", "metadata": { "tags": [ "solution" @@ -804,7 +804,7 @@ }, { "cell_type": "markdown", - "id": "f89eb1e4", + "id": "c5daa29d", "metadata": {}, "source": [ "

    \n", @@ -815,7 +815,7 @@ }, { "cell_type": "markdown", - "id": "84594622", + "id": "d04daf83", "metadata": { "tags": [ "solution" @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "1d7d8c11", + "id": "77e456c6", "metadata": { "tags": [ "solution" @@ -843,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "dbaa3b78", + "id": "0cef3ffb", "metadata": {}, "source": [ "

    \n", @@ -855,7 +855,7 @@ }, { "cell_type": "markdown", - "id": "e9e0f3ce", + "id": "26e74550", "metadata": {}, "source": [ "

    \n", @@ -870,20 +870,20 @@ }, { "cell_type": "markdown", - "id": "1751b788", + "id": "f8f40037", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", "\n", "Now that we have initialized our clean and tainted datasets and trained our models on them, it is time to examine how these models perform on the clean and tainted test sets!\n", "\n", - "We provide a `predict` function below that will return the prediction and ground truth labels given a particualr model and dataset." + "We provide a `predict` function below that will return the prediction and ground truth labels given a particular model and dataset." ] }, { "cell_type": "code", "execution_count": null, - "id": "c0853f13", + "id": "59344f6a", "metadata": {}, "outputs": [], "source": [ @@ -895,17 +895,17 @@ " dataset_groundtruth = []\n", " with torch.no_grad():\n", " for x, y_true in dataset:\n", - " inp = x[None].cuda()\n", + " inp = x[None].to(device)\n", " y_pred = model(inp)\n", " dataset_prediction.append(y_pred.argmax().cpu().numpy())\n", " dataset_groundtruth.append(y_true)\n", - " \n", + "\n", " return np.array(dataset_prediction), np.array(dataset_groundtruth)" ] }, { "cell_type": "markdown", - "id": "71a2f9cf", + "id": "87a707d4", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ff3be5a7", + "id": "5a8569d3", "metadata": {}, "outputs": [], "source": [ @@ -926,16 +926,16 @@ }, { "cell_type": "markdown", - "id": "a5f3fbc9", + "id": "590238a5", "metadata": {}, "source": [ - "We can investivate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." + "We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." ] }, { "cell_type": "code", "execution_count": null, - "id": "5f0e804c", + "id": "8637c217", "metadata": { "lines_to_next_cell": 1 }, @@ -944,8 +944,8 @@ "from sklearn.metrics import confusion_matrix\n", "import seaborn as sns\n", "import pandas as pd\n", - "# Plot confusion matrix \n", - "# orginally from Runqi Yang; \n", + "# Plot confusion matrix\n", + "# originally from Runqi Yang;\n", "# see https://gist.github.com/hitvoice/36cf44689065ca9b927431546381a3f7\n", "def cm_analysis(y_true, y_pred, title, figsize=(10,10)):\n", " \"\"\"\n", @@ -980,17 +980,17 @@ " annot[i, j] = ''\n", " else:\n", " annot[i, j] = '%.1f%%\\n%d' % (p, c)\n", - " cm = pd.DataFrame(cm, index=labels, columns=labels)\n", + " cm = pd.DataFrame(cm_perc, index=labels, columns=labels)\n", " cm.index.name = 'Actual'\n", " cm.columns.name = 'Predicted'\n", " fig, ax = plt.subplots(figsize=figsize)\n", - " ax=sns.heatmap(cm, annot=annot, fmt='', vmax=30)\n", + " ax = sns.heatmap(cm, annot=annot, fmt=\"\", vmax=100)\n", " ax.set_title(title)" ] }, { "cell_type": "markdown", - "id": "869d3190", + "id": "227322ac", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -999,7 +999,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2efb0286", + "id": "3a970ea0", "metadata": {}, "outputs": [], "source": [ @@ -1011,7 +1011,7 @@ }, { "cell_type": "markdown", - "id": "5c8983a8", + "id": "d32fc6d1", "metadata": {}, "source": [ "

    \n", @@ -1022,7 +1022,7 @@ }, { "cell_type": "markdown", - "id": "8ccb1031", + "id": "0602367e", "metadata": { "tags": [ "solution" @@ -1031,12 +1031,12 @@ "source": [ "**3.1 Answer:**\n", "\n", - "The clean model on the clean dataset predicted 5s least accuratly, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments)." + "The clean model on the clean dataset predicted 5s least accurately, with some confusion with 6s and 3s. These are likely confused by the model as handwritten 5s may look like 6s (almost closed bottom part) or 3s (presence of 3 horizontal segments)." ] }, { "cell_type": "markdown", - "id": "2bc050a2", + "id": "7ec26f86", "metadata": { "tags": [ "solution" @@ -1046,12 +1046,12 @@ "**3.1 Answer from 2023 Students**\n", "\n", "5 is the least accurately predicted digit. It is most confused with 6 or 3.\n", - "Handwriting creates fives that look like sixes or threes. " + "Handwriting creates fives that look like sixes or threes." ] }, { "cell_type": "markdown", - "id": "93c1483f", + "id": "6e643061", "metadata": {}, "source": [ "

    \n", @@ -1062,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "0cd4264c", + "id": "6a059155", "metadata": { "tags": [ "solution" @@ -1076,7 +1076,7 @@ }, { "cell_type": "markdown", - "id": "eac78a24", + "id": "aee6531e", "metadata": { "tags": [ "solution" @@ -1090,7 +1090,7 @@ }, { "cell_type": "markdown", - "id": "319465a3", + "id": "2dfde11d", "metadata": {}, "source": [ "

    \n", @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "e6de7dbb", + "id": "1309299f", "metadata": { "tags": [ "solution" @@ -1115,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "3f361a66", + "id": "cccf38c7", "metadata": { "tags": [ "solution" @@ -1126,13 +1126,13 @@ "\n", "Local corruption vs Global corruption: Global corruption WINS (aka is harder)!\n", "\n", - "It is harder to predict on the global corruption because it affects the whole image, and this was never seen in the training. \n", + "It is harder to predict on the global corruption because it affects the whole image, and this was never seen in the training.\n", "It adds (structured) noise over the entire four." ] }, { "cell_type": "markdown", - "id": "8467009a", + "id": "0e819c67", "metadata": {}, "source": [ "

    \n", @@ -1143,7 +1143,7 @@ }, { "cell_type": "markdown", - "id": "8c4869f8", + "id": "cde7da50", "metadata": { "tags": [ "solution" @@ -1152,12 +1152,12 @@ "source": [ "**3.4 Answer:**\n", "\n", - "The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption tought both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data." + "The tainted model performed poorly on clean 7s and extremely poorly on clean 4s. Global corruption effectively prevented the tainted model from learning any feature about 4s, and local corruption used both some true and some false features about 7s. Ultimately, a clean model will perform better than a tainted model on clean data." ] }, { "cell_type": "markdown", - "id": "c837f9b3", + "id": "6a25c456", "metadata": { "tags": [ "solution" @@ -1168,16 +1168,16 @@ "\n", "Clean 7s vs clean 4s: 4 WINS! (aka is worse)\n", "\n", - "Global corruptions are more detrimental when testing on the clean data. This is because the training images are *more* different from each other. \n", + "Global corruptions are more detrimental when testing on the clean data. This is because the training images are *more* different from each other.\n", "\n", - "Tainted model on clean data vs clean model on tainted data: Clean model WINS! (is better on tainted data than tained model on clean data) \n", + "Tainted model on clean data vs clean model on tainted data: Clean model WINS! (is better on tainted data than tainted model on clean data)\n", "\n", - "The clean model still has useful signal to work with in the tainted data. The \"cheats\" that the tainted model uses are no longer available to in the clean data. " + "The clean model still has useful signal to work with in the tainted data. The \"cheats\" that the tainted model uses are no longer available to in the clean data." ] }, { "cell_type": "markdown", - "id": "1b2061b7", + "id": "10de39bb", "metadata": {}, "source": [ "

    \n", @@ -1189,7 +1189,7 @@ }, { "cell_type": "markdown", - "id": "6ef0ce00", + "id": "86e2c33e", "metadata": {}, "source": [ "

    \n", @@ -1204,7 +1204,7 @@ }, { "cell_type": "markdown", - "id": "d961c467", + "id": "1a124f4a", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1213,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "5a5aa094", + "id": "991c9adb", "metadata": {}, "source": [ "\n", @@ -1223,7 +1223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5aa90a8b", + "id": "9c7dd3ca", "metadata": {}, "outputs": [], "source": [ @@ -1256,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "6b73c86e", + "id": "7610d0ff", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1265,7 +1265,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66a0588b", + "id": "857a5cec", "metadata": {}, "outputs": [], "source": [ @@ -1276,11 +1276,11 @@ "\n", " # Transpose integrated gradients output\n", " attr_ig = np.transpose(attr_ig[0].cpu().detach().numpy(), (1, 2, 0))\n", - " \n", + "\n", " # Transpose and normalize original image:\n", " original_image = np.transpose((test_input[0].detach().numpy() * 0.5) + 0.5, (1, 2, 0))\n", "\n", - " # This visualises the attribution of labels to pixels\n", + " # This visualises the attribution of labels to pixels\n", " figure, axis = plt.subplots(nrows=1, ncols=2, figsize=(4, 2.5), width_ratios=[1, 1])\n", " viz.visualize_image_attr(attr_ig, \n", " original_image, \n", @@ -1304,10 +1304,10 @@ }, { "cell_type": "markdown", - "id": "a637525d", + "id": "f5089370", "metadata": {}, "source": [ - "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens. \n", + "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens.\n", "\n", "The visualization will show the original image plus an overlaid attribution map that generally signifies the importance of each pixel, plus the attribution map only. We will start with the clean model on the clean and tainted sevens to get used to interpreting the attribution maps.\n" ] @@ -1315,7 +1315,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a06d0634", + "id": "67d2539a", "metadata": {}, "outputs": [], "source": [ @@ -1325,18 +1325,18 @@ }, { "cell_type": "markdown", - "id": "0822d5ff", + "id": "4ac77606", "metadata": {}, "source": [ "

    \n", - " Task 4.1: Interpereting the Clean Model's Attention on 7s

    \n", + " Task 4.1: Interpreting the Clean Model's Attention on 7s

    \n", "Where did the clean model focus its attention for the clean and tainted 7s? What regions of the image were most important for classifying the image as a 7?\n", "
    " ] }, { "cell_type": "markdown", - "id": "2d8cad8d", + "id": "eefc1b8f", "metadata": { "tags": [ "solution" @@ -1350,7 +1350,7 @@ }, { "cell_type": "markdown", - "id": "efa956a2", + "id": "dea4b18b", "metadata": { "tags": [ "solution" @@ -1365,7 +1365,7 @@ }, { "cell_type": "markdown", - "id": "cee392ec", + "id": "2b3203e1", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1374,7 +1374,7 @@ { "cell_type": "code", "execution_count": null, - "id": "62929d9e", + "id": "0878fa69", "metadata": {}, "outputs": [], "source": [ @@ -1384,18 +1384,18 @@ }, { "cell_type": "markdown", - "id": "e49b5678", + "id": "21fb3bcb", "metadata": {}, "source": [ "

    \n", - " Task 4.2: Interpereting the Tainted Model's Attention on 7s

    \n", + " Task 4.2: Interpreting the Tainted Model's Attention on 7s

    \n", "Where did the tainted model focus its attention for the clean and tainted 7s? How was this different than the clean model? Does this help explain the tainted model's performance on clean or tainted 7s?\n", "
    " ] }, { "cell_type": "markdown", - "id": "f77be72e", + "id": "b2b83581", "metadata": { "tags": [ "solution" @@ -1409,7 +1409,7 @@ }, { "cell_type": "markdown", - "id": "4c82acb5", + "id": "b6a36c08", "metadata": { "tags": [ "solution" @@ -1427,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "f33a3636", + "id": "10fd930e", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1436,7 +1436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "98f09f64", + "id": "4cd9057a", "metadata": {}, "outputs": [], "source": [ @@ -1448,18 +1448,18 @@ }, { "cell_type": "markdown", - "id": "059654d6", + "id": "53abc3bb", "metadata": {}, "source": [ "

    \n", - " Task 4.3: Interpereting the focus on 4s

    \n", + " Task 4.3: Interpreting the focus on 4s

    \n", "Where did the tainted model focus its attention for the tainted and clean 4s? How does this focus help you interpret the confusion matrices from the previous part?\n", "
    " ] }, { "cell_type": "markdown", - "id": "4b8a0959", + "id": "0c0b5970", "metadata": { "tags": [ "solution" @@ -1473,7 +1473,7 @@ }, { "cell_type": "markdown", - "id": "7f52c9ca", + "id": "a4e568c7", "metadata": { "tags": [ "solution" @@ -1490,7 +1490,7 @@ }, { "cell_type": "markdown", - "id": "a859b818", + "id": "ee45ee7e", "metadata": {}, "source": [ "

    \n", @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "7be27091", + "id": "75a5866f", "metadata": { "tags": [ "solution" @@ -1510,12 +1510,12 @@ "source": [ "**4.4 Answer:**\n", "\n", - "The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to indentify idividual pixels of interest when pixels are meaningful when considered globally." + "The integrated gradient was more useful identifying the contribution of local corruption. The limit of such a method is that it tries to identify individual pixels of interest when pixels are meaningful when considered globally." ] }, { "cell_type": "markdown", - "id": "b582bc42", + "id": "765f74c6", "metadata": { "tags": [ "solution" @@ -1526,25 +1526,25 @@ "\n", "Voting results: 6 LOCAL vs 0 GLOBAL\n", "\n", - "It doesnt really make sense to point at a subset of pixels that are important for detecting global patterns, even for a human - it's basically all the pixels!" + "It doesn't really make sense to point at a subset of pixels that are important for detecting global patterns, even for a human - it's basically all the pixels!" ] }, { "cell_type": "markdown", - "id": "9e419f62", + "id": "41a824a7", "metadata": {}, "source": [ "

    \n", " Checkpoint 4

    \n", "
      \n", - " Congrats on finishing the intergrated gradients task! Let us know on Element that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested.\n", + " Congrats on finishing the integrated gradients task! Let us know on the course chat that you reached checkpoint 4, and feel free to look at other interpretability methods in the Captum library if you're interested.\n", "
    \n", "
    " ] }, { "cell_type": "markdown", - "id": "6b2959a2", + "id": "91dddcdc", "metadata": {}, "source": [ "

    \n", @@ -1558,7 +1558,7 @@ }, { "cell_type": "markdown", - "id": "76193ea5", + "id": "9feabbd4", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1570,7 +1570,7 @@ }, { "cell_type": "markdown", - "id": "afdb487c", + "id": "d48569a6", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1579,7 +1579,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66dd076a", + "id": "d79ed624", "metadata": {}, "outputs": [], "source": [ @@ -1592,7 +1592,7 @@ }, { "cell_type": "markdown", - "id": "98cb3bb8", + "id": "63aca81c", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1601,7 +1601,7 @@ { "cell_type": "code", "execution_count": null, - "id": "63f337f7", + "id": "268eb42f", "metadata": {}, "outputs": [], "source": [ @@ -1630,17 +1630,17 @@ }, { "cell_type": "markdown", - "id": "8853090e", + "id": "783d702b", "metadata": {}, "source": [ "### UNet model\n", "\n", - "Let's try denoising with a UNet, \"CARE-style\". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell. " + "Let's try denoising with a UNet, \"CARE-style\". As UNets and denoising implementations are not the focus of this exercise, we provide the model for you in the following cell." ] }, { "cell_type": "markdown", - "id": "bfba19a4", + "id": "f114069b", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1649,47 +1649,47 @@ { "cell_type": "code", "execution_count": null, - "id": "34de1247", + "id": "8d0a5ab3", "metadata": {}, "outputs": [], "source": [ "from tqdm import tqdm\n", "\n", "def train_denoising_model(train_loader, model, criterion, optimizer, history):\n", - " \n", + "\n", " # Puts model in 'training' mode:\n", " model.train()\n", - " \n", + "\n", " # Initialises progress bar:\n", " pbar = tqdm(total=len(train_loader.dataset)//batch_size_train)\n", " for batch_idx, (image, target) in enumerate(train_loader):\n", "\n", " # add line here during Task 2.2\n", - " \n", + "\n", " # Zeroing gradients:\n", " optimizer.zero_grad()\n", - " \n", + "\n", " # Moves image to GPU memory:\n", - " image = image.cuda()\n", - " \n", + " image = image.to(device)\n", + "\n", " # Adds noise to make the noisy image:\n", " noisy = add_noise(image)\n", - " \n", + "\n", " # Runs model on noisy image:\n", " output = model(noisy)\n", - " \n", + "\n", " # Computes loss:\n", " loss = criterion(output, image)\n", - " \n", + "\n", " # Backpropagates gradients:\n", " loss.backward()\n", - " \n", + "\n", " # Optimises model parameters given the current gradients:\n", " optimizer.step()\n", - " \n", + "\n", " # appends loss history:\n", " history[\"loss\"].append(loss.item())\n", - " \n", + "\n", " # updates progress bar:\n", " pbar.update(1)\n", " return history" @@ -1697,7 +1697,7 @@ }, { "cell_type": "markdown", - "id": "86f458bb", + "id": "3f3c87f9", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1706,7 +1706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a69275b4", + "id": "52c8fb2e", "metadata": {}, "outputs": [], "source": [ @@ -1744,7 +1744,7 @@ }, { "cell_type": "markdown", - "id": "2cfec16b", + "id": "f294c563", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1753,7 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9b3103df", + "id": "a792d29f", "metadata": {}, "outputs": [], "source": [ @@ -1764,7 +1764,7 @@ }, { "cell_type": "markdown", - "id": "a8ddab2b", + "id": "e4400668", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1773,7 +1773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b749e2d3", + "id": "38b615ff", "metadata": { "lines_to_next_cell": 1 }, @@ -1789,7 +1789,7 @@ }, { "cell_type": "markdown", - "id": "33b18ff9", + "id": "6eef3ca6", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1800,7 +1800,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7fb1ba9d", + "id": "564550c8", "metadata": { "lines_to_next_cell": 1 }, @@ -1809,7 +1809,7 @@ "def apply_denoising(image, model):\n", " # add batch and channel dimensions\n", " image = torch.unsqueeze(torch.unsqueeze(image, 0), 0)\n", - " prediction = model(image.cuda())\n", + " prediction = model(image.to(device))\n", " # remove batch and channel dimensions before returning\n", " return prediction.detach().cpu()[0,0]" ] @@ -1817,7 +1817,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d0b2276", + "id": "c2f88bd6", "metadata": { "lines_to_next_cell": 1 }, @@ -1843,7 +1843,7 @@ }, { "cell_type": "markdown", - "id": "d64d4b73", + "id": "d94541f8", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1852,7 +1852,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d201b55f", + "id": "2f402794", "metadata": {}, "outputs": [], "source": [ @@ -1862,7 +1862,7 @@ }, { "cell_type": "markdown", - "id": "216613e6", + "id": "527a3789", "metadata": {}, "source": [ "

    \n", @@ -1873,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "3947715c", + "id": "09164156", "metadata": { "tags": [ "solution" @@ -1887,7 +1887,7 @@ }, { "cell_type": "markdown", - "id": "1b69380e", + "id": "c106b9be", "metadata": { "tags": [ "solution" @@ -1901,17 +1901,17 @@ }, { "cell_type": "markdown", - "id": "1e8bbf40", + "id": "ec2b36f5", "metadata": {}, "source": [ - "### Apply trained model on 'wrong' data \n", + "### Apply trained model on 'wrong' data\n", "\n", "Apply the denoising model trained above to some example _noisy_ images derived from the Fashion-MNIST dataset.\n" ] }, { "cell_type": "markdown", - "id": "ec89d5cf", + "id": "8194dcee", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1922,7 +1922,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e006bc77", + "id": "e613bf75", "metadata": {}, "outputs": [], "source": [ @@ -1943,7 +1943,7 @@ }, { "cell_type": "markdown", - "id": "d20560de", + "id": "324412bf", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1952,7 +1952,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2c0ffe7c", + "id": "8d094c79", "metadata": {}, "outputs": [], "source": [ @@ -1962,7 +1962,7 @@ }, { "cell_type": "markdown", - "id": "e0bc45a6", + "id": "38893a5f", "metadata": {}, "source": [ "

    \n", @@ -1973,7 +1973,7 @@ }, { "cell_type": "markdown", - "id": "0d240f0a", + "id": "57de716e", "metadata": { "tags": [ "solution" @@ -1987,7 +1987,7 @@ }, { "cell_type": "markdown", - "id": "16da4bf5", + "id": "c9f5e127", "metadata": { "tags": [ "solution" @@ -1996,12 +1996,12 @@ "source": [ "**5.2 Answer from 2023 Students:**\n", "\n", - "BAD! Some of them kind of look like numbers. " + "BAD! Some of them kind of look like numbers." ] }, { "cell_type": "markdown", - "id": "6d61dfab", + "id": "19f22363", "metadata": {}, "source": [ "

    \n", @@ -2012,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "67e12194", + "id": "38e5971d", "metadata": { "tags": [ "solution" @@ -2026,7 +2026,7 @@ }, { "cell_type": "markdown", - "id": "00ff2115", + "id": "70eb7e44", "metadata": { "tags": [ "solution" @@ -2041,7 +2041,7 @@ }, { "cell_type": "markdown", - "id": "e6483d98", + "id": "baaba56b", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2052,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "09e48578", + "id": "0dbacd4c", "metadata": {}, "outputs": [], "source": [ @@ -2089,7 +2089,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f080bc7", + "id": "d420fd52", "metadata": {}, "outputs": [], "source": [ @@ -2100,7 +2100,7 @@ { "cell_type": "code", "execution_count": null, - "id": "361df7de", + "id": "6d23b631", "metadata": {}, "outputs": [], "source": [ @@ -2110,7 +2110,7 @@ }, { "cell_type": "markdown", - "id": "f88adf9e", + "id": "121897cd", "metadata": {}, "source": [ "

    \n", @@ -2121,7 +2121,7 @@ }, { "cell_type": "markdown", - "id": "ceb7d13a", + "id": "d7d6e35c", "metadata": { "tags": [ "solution" @@ -2140,7 +2140,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ef8f51df", + "id": "227404b2", "metadata": {}, "outputs": [], "source": [ @@ -2177,7 +2177,7 @@ { "cell_type": "code", "execution_count": null, - "id": "34473ef0", + "id": "01e3e4dc", "metadata": {}, "outputs": [], "source": [ @@ -2188,7 +2188,7 @@ { "cell_type": "code", "execution_count": null, - "id": "65bffa85", + "id": "5df0f7a0", "metadata": {}, "outputs": [], "source": [ @@ -2198,7 +2198,7 @@ }, { "cell_type": "markdown", - "id": "388c8c72", + "id": "510edc26", "metadata": {}, "source": [ "

    \n", @@ -2209,7 +2209,7 @@ }, { "cell_type": "markdown", - "id": "38a1e793", + "id": "f1670840", "metadata": { "tags": [ "solution" @@ -2223,21 +2223,21 @@ }, { "cell_type": "markdown", - "id": "52244cd5", + "id": "21c20845", "metadata": {}, "source": [ "\n", "

    \n", " Checkpoint 5

    \n", "
      \n", - " Congrats on reaching the final checkpoint! Let us know on Element, and we'll discuss the questions once reaching critical mass.\n", + " Congrats on reaching the final checkpoint! Let us know on the course chat, and we'll discuss the questions once reaching critical mass.\n", "
    \n", "
    " ] }, { "cell_type": "markdown", - "id": "3af95611", + "id": "b7a1fa15", "metadata": {}, "source": [ "\n", @@ -2251,7 +2251,7 @@ }, { "cell_type": "markdown", - "id": "c0afb23d", + "id": "389a3851", "metadata": {}, "source": [] } From 98cd0a0fcfc27bce6bdbb161c218d40bec1c3dda Mon Sep 17 00:00:00 2001 From: Diane Adjavon Date: Mon, 19 Aug 2024 14:18:14 -0400 Subject: [PATCH 49/51] Add description of the model forgetting --- solution.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/solution.py b/solution.py index 1f5cac2..49a3567 100644 --- a/solution.py +++ b/solution.py @@ -1179,14 +1179,17 @@ def visualize_denoising(model, dataset, index): # %% [markdown] #

    # Task 5.4:

    -# How does the new denoiser perform compared to the one from the previous section? +# How does the new denoiser perform compared to the one from the previous section? Why? #
    # %% [markdown] tags=["solution"] # **5.4 Answer:** # # The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable). -# +# If you look more closely at the code, you'll notice that we haven't shuffled the data in our `DataLoader`. This means that every epoch the model will first train on all of the MNIST data, then on all of the FashinMNIST. +# The effect that we're seeing here, where it's performing worse of the MNIST data, points to an important lesson: Models Forget! +# If the model is trained for too long without any MNISt examples, as it is here, it begins to overwrite what it has learned about that data. +# %% [markdown] # ### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data # # We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below) From 65adfb3610e0b935330e7711d5bf50354e8dd849 Mon Sep 17 00:00:00 2001 From: adjavon Date: Mon, 19 Aug 2024 18:20:27 +0000 Subject: [PATCH 50/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 246 +++++++++++++++++++------------------ solution.ipynb | 324 +++++++++++++++++++++++++------------------------ 2 files changed, 295 insertions(+), 275 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index 6de2231..f05295e 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "400d2e03", + "id": "f4c5998d", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "394f293f", + "id": "400de6a4", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks.\n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "0734f242", + "id": "3baf2a90", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "b8c60ec0", + "id": "fac88ce5", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "1c8d915c", + "id": "12f7ca06", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9e3f7120", + "id": "2eaac11e", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "2b767ea4", + "id": "0fa59082", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "989ccfe9", + "id": "44f8cc97", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "91d01d2d", + "id": "fa4dbba7", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "7d34c3c8", + "id": "3afbd53b", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c3e01c63", + "id": "45d6aa77", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c8a299ee", + "id": "60351b4b", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "6ceb0857", + "id": "f2e929ca", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "cb572ae9", + "id": "2dbcf4b2", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "631a8c9e", + "id": "39ce6b99", "metadata": {}, "source": [ "## Part 1.2: Global Corruption of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "70a36235", + "id": "45f7b920", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "13873808", + "id": "20be6faf", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "35cbd7d7", + "id": "698581c8", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "34980b74", + "id": "69f364a2", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "59ed11fd", + "id": "a2e35eaf", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d20eb078", + "id": "e773f840", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "051c02ad", + "id": "d8c22dfb", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8.\n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4564cb56", + "id": "20d299d2", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b5a17a23", + "id": "6c9fc998", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "3262735f", + "id": "ae4eef7e", "metadata": {}, "source": [ "

    \n", @@ -328,7 +328,7 @@ }, { "cell_type": "markdown", - "id": "ad6b7873", + "id": "a90db194", "metadata": {}, "source": [ "\n", @@ -340,7 +340,7 @@ }, { "cell_type": "markdown", - "id": "43162d5f", + "id": "1f6d7182", "metadata": {}, "source": [ "\n", @@ -353,7 +353,7 @@ }, { "cell_type": "markdown", - "id": "26dc8c22", + "id": "613e4cd4", "metadata": {}, "source": [ "\n", @@ -371,7 +371,7 @@ }, { "cell_type": "markdown", - "id": "82c8ebea", + "id": "2fb5fede", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -382,7 +382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "112bc521", + "id": "cdcd46d5", "metadata": {}, "outputs": [], "source": [ @@ -396,7 +396,7 @@ }, { "cell_type": "markdown", - "id": "1b59e4b3", + "id": "c2cf6bfa", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -405,7 +405,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f988864", + "id": "98eddd14", "metadata": {}, "outputs": [], "source": [ @@ -430,7 +430,7 @@ }, { "cell_type": "markdown", - "id": "42a57b6b", + "id": "af0edd25", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -439,7 +439,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e52a71cf", + "id": "3deddbd3", "metadata": {}, "outputs": [], "source": [ @@ -458,7 +458,7 @@ }, { "cell_type": "markdown", - "id": "7f9f1305", + "id": "4ed7aa39", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -467,7 +467,7 @@ { "cell_type": "code", "execution_count": null, - "id": "094feafc", + "id": "43b0197b", "metadata": {}, "outputs": [], "source": [ @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "547c344a", + "id": "1ae683d2", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -504,7 +504,7 @@ { "cell_type": "code", "execution_count": null, - "id": "14c3e9a0", + "id": "081f197c", "metadata": {}, "outputs": [], "source": [ @@ -518,7 +518,7 @@ }, { "cell_type": "markdown", - "id": "caac6dfc", + "id": "597135be", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -527,7 +527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e302a996", + "id": "e32e286d", "metadata": {}, "outputs": [], "source": [ @@ -560,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "2aa1ae7d", + "id": "75895920", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -569,7 +569,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d2b3b3a", + "id": "7006b624", "metadata": {}, "outputs": [], "source": [ @@ -584,7 +584,7 @@ }, { "cell_type": "markdown", - "id": "1bcf5872", + "id": "4467a232", "metadata": {}, "source": [ "

    \n", @@ -595,7 +595,7 @@ }, { "cell_type": "markdown", - "id": "1529ab82", + "id": "e6853659", "metadata": {}, "source": [ "

    \n", @@ -606,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "c5daa29d", + "id": "786976e5", "metadata": {}, "source": [ "

    \n", @@ -617,7 +617,7 @@ }, { "cell_type": "markdown", - "id": "0cef3ffb", + "id": "b151cf85", "metadata": {}, "source": [ "

    \n", @@ -629,7 +629,7 @@ }, { "cell_type": "markdown", - "id": "26e74550", + "id": "046f2d98", "metadata": {}, "source": [ "

    \n", @@ -644,7 +644,7 @@ }, { "cell_type": "markdown", - "id": "f8f40037", + "id": "efb66b32", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -657,7 +657,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59344f6a", + "id": "67a73dc1", "metadata": {}, "outputs": [], "source": [ @@ -679,7 +679,7 @@ }, { "cell_type": "markdown", - "id": "87a707d4", + "id": "eaa7a921", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -688,7 +688,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5a8569d3", + "id": "92257da3", "metadata": {}, "outputs": [], "source": [ @@ -700,7 +700,7 @@ }, { "cell_type": "markdown", - "id": "590238a5", + "id": "b7426171", "metadata": {}, "source": [ "We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -709,7 +709,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8637c217", + "id": "994b40c0", "metadata": { "lines_to_next_cell": 1 }, @@ -764,7 +764,7 @@ }, { "cell_type": "markdown", - "id": "227322ac", + "id": "a1321ccd", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -773,7 +773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3a970ea0", + "id": "348d2b4d", "metadata": {}, "outputs": [], "source": [ @@ -785,7 +785,7 @@ }, { "cell_type": "markdown", - "id": "d32fc6d1", + "id": "19651455", "metadata": {}, "source": [ "

    \n", @@ -796,7 +796,7 @@ }, { "cell_type": "markdown", - "id": "6e643061", + "id": "651dfee3", "metadata": {}, "source": [ "

    \n", @@ -807,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "2dfde11d", + "id": "6d40345f", "metadata": {}, "source": [ "

    \n", @@ -818,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "0e819c67", + "id": "e17b0677", "metadata": {}, "source": [ "

    \n", @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "10de39bb", + "id": "04ca2bfa", "metadata": {}, "source": [ "

    \n", @@ -841,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "86e2c33e", + "id": "8cf32682", "metadata": {}, "source": [ "

    \n", @@ -856,7 +856,7 @@ }, { "cell_type": "markdown", - "id": "1a124f4a", + "id": "afbe6a03", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "991c9adb", + "id": "b290da92", "metadata": {}, "source": [ "\n", @@ -875,7 +875,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9c7dd3ca", + "id": "896bdba0", "metadata": {}, "outputs": [], "source": [ @@ -908,7 +908,7 @@ }, { "cell_type": "markdown", - "id": "7610d0ff", + "id": "b549928d", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -917,7 +917,7 @@ { "cell_type": "code", "execution_count": null, - "id": "857a5cec", + "id": "8827a868", "metadata": {}, "outputs": [], "source": [ @@ -956,7 +956,7 @@ }, { "cell_type": "markdown", - "id": "f5089370", + "id": "f39ba38b", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens.\n", @@ -967,7 +967,7 @@ { "cell_type": "code", "execution_count": null, - "id": "67d2539a", + "id": "eadea48c", "metadata": {}, "outputs": [], "source": [ @@ -977,7 +977,7 @@ }, { "cell_type": "markdown", - "id": "4ac77606", + "id": "b5599149", "metadata": {}, "source": [ "

    \n", @@ -988,7 +988,7 @@ }, { "cell_type": "markdown", - "id": "2b3203e1", + "id": "09cd4b31", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -997,7 +997,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0878fa69", + "id": "004c2744", "metadata": {}, "outputs": [], "source": [ @@ -1007,7 +1007,7 @@ }, { "cell_type": "markdown", - "id": "21fb3bcb", + "id": "10f6e82a", "metadata": {}, "source": [ "

    \n", @@ -1018,7 +1018,7 @@ }, { "cell_type": "markdown", - "id": "10fd930e", + "id": "5f1a65c7", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1027,7 +1027,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4cd9057a", + "id": "c20db2dc", "metadata": {}, "outputs": [], "source": [ @@ -1039,7 +1039,7 @@ }, { "cell_type": "markdown", - "id": "53abc3bb", + "id": "db17eead", "metadata": {}, "source": [ "

    \n", @@ -1050,7 +1050,7 @@ }, { "cell_type": "markdown", - "id": "ee45ee7e", + "id": "30a9b553", "metadata": {}, "source": [ "

    \n", @@ -1061,7 +1061,7 @@ }, { "cell_type": "markdown", - "id": "41a824a7", + "id": "335772f7", "metadata": {}, "source": [ "

    \n", @@ -1074,7 +1074,7 @@ }, { "cell_type": "markdown", - "id": "91dddcdc", + "id": "8af404b4", "metadata": {}, "source": [ "

    \n", @@ -1088,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "9feabbd4", + "id": "9295ffc7", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1100,7 +1100,7 @@ }, { "cell_type": "markdown", - "id": "d48569a6", + "id": "7cbf3b1a", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1109,7 +1109,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d79ed624", + "id": "1a3769ac", "metadata": {}, "outputs": [], "source": [ @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "63aca81c", + "id": "3a3a8139", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1131,7 +1131,7 @@ { "cell_type": "code", "execution_count": null, - "id": "268eb42f", + "id": "36f20530", "metadata": {}, "outputs": [], "source": [ @@ -1160,7 +1160,7 @@ }, { "cell_type": "markdown", - "id": "783d702b", + "id": "8622949e", "metadata": {}, "source": [ "### UNet model\n", @@ -1170,7 +1170,7 @@ }, { "cell_type": "markdown", - "id": "f114069b", + "id": "9ab55c00", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1179,7 +1179,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8d0a5ab3", + "id": "66bd1d56", "metadata": {}, "outputs": [], "source": [ @@ -1227,7 +1227,7 @@ }, { "cell_type": "markdown", - "id": "3f3c87f9", + "id": "6d20945b", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1236,7 +1236,7 @@ { "cell_type": "code", "execution_count": null, - "id": "52c8fb2e", + "id": "827d2f32", "metadata": {}, "outputs": [], "source": [ @@ -1274,7 +1274,7 @@ }, { "cell_type": "markdown", - "id": "f294c563", + "id": "3a0153a5", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1283,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a792d29f", + "id": "716b936f", "metadata": {}, "outputs": [], "source": [ @@ -1294,7 +1294,7 @@ }, { "cell_type": "markdown", - "id": "e4400668", + "id": "b24bdfbd", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1303,7 +1303,7 @@ { "cell_type": "code", "execution_count": null, - "id": "38b615ff", + "id": "bc71bff7", "metadata": { "lines_to_next_cell": 1 }, @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "6eef3ca6", + "id": "2b474711", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1330,7 +1330,7 @@ { "cell_type": "code", "execution_count": null, - "id": "564550c8", + "id": "e1d20e0b", "metadata": { "lines_to_next_cell": 1 }, @@ -1347,7 +1347,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c2f88bd6", + "id": "4b77f687", "metadata": { "lines_to_next_cell": 1 }, @@ -1373,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "d94541f8", + "id": "b5eb2c28", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1382,7 +1382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f402794", + "id": "3a1d22bd", "metadata": {}, "outputs": [], "source": [ @@ -1392,7 +1392,7 @@ }, { "cell_type": "markdown", - "id": "527a3789", + "id": "29912374", "metadata": {}, "source": [ "

    \n", @@ -1403,7 +1403,7 @@ }, { "cell_type": "markdown", - "id": "ec2b36f5", + "id": "8a598bb3", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data\n", @@ -1413,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "8194dcee", + "id": "4b63fc64", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1424,7 +1424,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e613bf75", + "id": "d03b2297", "metadata": {}, "outputs": [], "source": [ @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "324412bf", + "id": "31d01ee1", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1454,7 +1454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8d094c79", + "id": "aab3b99c", "metadata": {}, "outputs": [], "source": [ @@ -1464,7 +1464,7 @@ }, { "cell_type": "markdown", - "id": "38893a5f", + "id": "e12f3a1d", "metadata": {}, "source": [ "

    \n", @@ -1475,7 +1475,7 @@ }, { "cell_type": "markdown", - "id": "19f22363", + "id": "3c296abe", "metadata": {}, "source": [ "

    \n", @@ -1486,7 +1486,7 @@ }, { "cell_type": "markdown", - "id": "baaba56b", + "id": "749d2d87", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1497,7 +1497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0dbacd4c", + "id": "e52a2f68", "metadata": {}, "outputs": [], "source": [ @@ -1534,7 +1534,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d420fd52", + "id": "76324612", "metadata": {}, "outputs": [], "source": [ @@ -1545,7 +1545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d23b631", + "id": "1544565a", "metadata": {}, "outputs": [], "source": [ @@ -1555,19 +1555,29 @@ }, { "cell_type": "markdown", - "id": "121897cd", + "id": "d2646697", "metadata": {}, "source": [ "

    \n", " Task 5.4:

    \n", - "How does the new denoiser perform compared to the one from the previous section?\n", + "How does the new denoiser perform compared to the one from the previous section? Why?\n", "
    " ] }, + { + "cell_type": "markdown", + "id": "4f02d520", + "metadata": {}, + "source": [ + "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", + "\n", + "We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below)" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "227404b2", + "id": "fb070c5c", "metadata": {}, "outputs": [], "source": [ @@ -1604,7 +1614,7 @@ { "cell_type": "code", "execution_count": null, - "id": "01e3e4dc", + "id": "2cfefa77", "metadata": {}, "outputs": [], "source": [ @@ -1615,7 +1625,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5df0f7a0", + "id": "56718c41", "metadata": {}, "outputs": [], "source": [ @@ -1625,7 +1635,7 @@ }, { "cell_type": "markdown", - "id": "510edc26", + "id": "df6234dd", "metadata": {}, "source": [ "

    \n", @@ -1636,7 +1646,7 @@ }, { "cell_type": "markdown", - "id": "21c20845", + "id": "dbe9b728", "metadata": {}, "source": [ "\n", @@ -1650,7 +1660,7 @@ }, { "cell_type": "markdown", - "id": "b7a1fa15", + "id": "b69ac817", "metadata": {}, "source": [ "\n", @@ -1664,7 +1674,7 @@ }, { "cell_type": "markdown", - "id": "389a3851", + "id": "b682aed4", "metadata": {}, "source": [] } diff --git a/solution.ipynb b/solution.ipynb index 5c1fe6e..11e9d64 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "400d2e03", + "id": "f4c5998d", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "394f293f", + "id": "400de6a4", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks.\n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "0734f242", + "id": "3baf2a90", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "b8c60ec0", + "id": "fac88ce5", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "1c8d915c", + "id": "12f7ca06", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9e3f7120", + "id": "2eaac11e", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "2b767ea4", + "id": "0fa59082", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "989ccfe9", + "id": "44f8cc97", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "91d01d2d", + "id": "fa4dbba7", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "7d34c3c8", + "id": "3afbd53b", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c3e01c63", + "id": "45d6aa77", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c8a299ee", + "id": "60351b4b", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "6ceb0857", + "id": "f2e929ca", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "60fae5a8", + "id": "f7652227", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "1dbe0c7b", + "id": "58ebc7b2", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "cb572ae9", + "id": "2dbcf4b2", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "196a2407", + "id": "4bad6d7c", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "93b462a2", + "id": "69cccf93", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "631a8c9e", + "id": "39ce6b99", "metadata": {}, "source": [ "## Part 1.2: Global Corruption of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "70a36235", + "id": "45f7b920", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "13873808", + "id": "20be6faf", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "35cbd7d7", + "id": "698581c8", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "34980b74", + "id": "69f364a2", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "59ed11fd", + "id": "a2e35eaf", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d20eb078", + "id": "e773f840", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "051c02ad", + "id": "d8c22dfb", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8.\n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4564cb56", + "id": "20d299d2", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "b5a17a23", + "id": "6c9fc998", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "3262735f", + "id": "ae4eef7e", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "ee831b57", + "id": "8160ab25", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "aae0a4e4", + "id": "b46002b6", "metadata": { "tags": [ "solution" @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "ad6b7873", + "id": "a90db194", "metadata": {}, "source": [ "\n", @@ -454,7 +454,7 @@ }, { "cell_type": "markdown", - "id": "c3a25477", + "id": "c61d96bd", "metadata": { "tags": [ "solution" @@ -468,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "df788018", + "id": "78a448b1", "metadata": { "tags": [ "solution" @@ -482,7 +482,7 @@ }, { "cell_type": "markdown", - "id": "43162d5f", + "id": "1f6d7182", "metadata": {}, "source": [ "\n", @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "26dc8c22", + "id": "613e4cd4", "metadata": {}, "source": [ "\n", @@ -513,7 +513,7 @@ }, { "cell_type": "markdown", - "id": "82c8ebea", + "id": "2fb5fede", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -524,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "112bc521", + "id": "cdcd46d5", "metadata": {}, "outputs": [], "source": [ @@ -538,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "1b59e4b3", + "id": "c2cf6bfa", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -547,7 +547,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f988864", + "id": "98eddd14", "metadata": {}, "outputs": [], "source": [ @@ -572,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "42a57b6b", + "id": "af0edd25", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -581,7 +581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e52a71cf", + "id": "3deddbd3", "metadata": {}, "outputs": [], "source": [ @@ -600,7 +600,7 @@ }, { "cell_type": "markdown", - "id": "7f9f1305", + "id": "4ed7aa39", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -609,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "094feafc", + "id": "43b0197b", "metadata": {}, "outputs": [], "source": [ @@ -637,7 +637,7 @@ }, { "cell_type": "markdown", - "id": "547c344a", + "id": "1ae683d2", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -646,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "14c3e9a0", + "id": "081f197c", "metadata": {}, "outputs": [], "source": [ @@ -660,7 +660,7 @@ }, { "cell_type": "markdown", - "id": "caac6dfc", + "id": "597135be", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -669,7 +669,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e302a996", + "id": "e32e286d", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "2aa1ae7d", + "id": "75895920", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -711,7 +711,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d2b3b3a", + "id": "7006b624", "metadata": {}, "outputs": [], "source": [ @@ -726,7 +726,7 @@ }, { "cell_type": "markdown", - "id": "1bcf5872", + "id": "4467a232", "metadata": {}, "source": [ "

    \n", @@ -737,7 +737,7 @@ }, { "cell_type": "markdown", - "id": "eec7a9fb", + "id": "12a2ca82", "metadata": { "tags": [ "solution" @@ -751,7 +751,7 @@ }, { "cell_type": "markdown", - "id": "dea0439e", + "id": "97aab178", "metadata": { "tags": [ "solution" @@ -765,7 +765,7 @@ }, { "cell_type": "markdown", - "id": "1529ab82", + "id": "e6853659", "metadata": {}, "source": [ "

    \n", @@ -776,7 +776,7 @@ }, { "cell_type": "markdown", - "id": "7174819f", + "id": "ee00919f", "metadata": { "tags": [ "solution" @@ -790,7 +790,7 @@ }, { "cell_type": "markdown", - "id": "f7c519b0", + "id": "0899155c", "metadata": { "tags": [ "solution" @@ -804,7 +804,7 @@ }, { "cell_type": "markdown", - "id": "c5daa29d", + "id": "786976e5", "metadata": {}, "source": [ "

    \n", @@ -815,7 +815,7 @@ }, { "cell_type": "markdown", - "id": "d04daf83", + "id": "d6a8c3a7", "metadata": { "tags": [ "solution" @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "77e456c6", + "id": "1417f3e1", "metadata": { "tags": [ "solution" @@ -843,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "0cef3ffb", + "id": "b151cf85", "metadata": {}, "source": [ "

    \n", @@ -855,7 +855,7 @@ }, { "cell_type": "markdown", - "id": "26e74550", + "id": "046f2d98", "metadata": {}, "source": [ "

    \n", @@ -870,7 +870,7 @@ }, { "cell_type": "markdown", - "id": "f8f40037", + "id": "efb66b32", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -883,7 +883,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59344f6a", + "id": "67a73dc1", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "87a707d4", + "id": "eaa7a921", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5a8569d3", + "id": "92257da3", "metadata": {}, "outputs": [], "source": [ @@ -926,7 +926,7 @@ }, { "cell_type": "markdown", - "id": "590238a5", + "id": "b7426171", "metadata": {}, "source": [ "We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -935,7 +935,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8637c217", + "id": "994b40c0", "metadata": { "lines_to_next_cell": 1 }, @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "227322ac", + "id": "a1321ccd", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -999,7 +999,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3a970ea0", + "id": "348d2b4d", "metadata": {}, "outputs": [], "source": [ @@ -1011,7 +1011,7 @@ }, { "cell_type": "markdown", - "id": "d32fc6d1", + "id": "19651455", "metadata": {}, "source": [ "

    \n", @@ -1022,7 +1022,7 @@ }, { "cell_type": "markdown", - "id": "0602367e", + "id": "c4766bc4", "metadata": { "tags": [ "solution" @@ -1036,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "7ec26f86", + "id": "41c92b6c", "metadata": { "tags": [ "solution" @@ -1051,7 +1051,7 @@ }, { "cell_type": "markdown", - "id": "6e643061", + "id": "651dfee3", "metadata": {}, "source": [ "

    \n", @@ -1062,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "6a059155", + "id": "f59acfa9", "metadata": { "tags": [ "solution" @@ -1076,7 +1076,7 @@ }, { "cell_type": "markdown", - "id": "aee6531e", + "id": "354500fc", "metadata": { "tags": [ "solution" @@ -1090,7 +1090,7 @@ }, { "cell_type": "markdown", - "id": "2dfde11d", + "id": "6d40345f", "metadata": {}, "source": [ "

    \n", @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "1309299f", + "id": "348ae3e8", "metadata": { "tags": [ "solution" @@ -1115,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "cccf38c7", + "id": "a714df43", "metadata": { "tags": [ "solution" @@ -1132,7 +1132,7 @@ }, { "cell_type": "markdown", - "id": "0e819c67", + "id": "e17b0677", "metadata": {}, "source": [ "

    \n", @@ -1143,7 +1143,7 @@ }, { "cell_type": "markdown", - "id": "cde7da50", + "id": "2fe8a46f", "metadata": { "tags": [ "solution" @@ -1157,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "6a25c456", + "id": "32f1c657", "metadata": { "tags": [ "solution" @@ -1177,7 +1177,7 @@ }, { "cell_type": "markdown", - "id": "10de39bb", + "id": "04ca2bfa", "metadata": {}, "source": [ "

    \n", @@ -1189,7 +1189,7 @@ }, { "cell_type": "markdown", - "id": "86e2c33e", + "id": "8cf32682", "metadata": {}, "source": [ "

    \n", @@ -1204,7 +1204,7 @@ }, { "cell_type": "markdown", - "id": "1a124f4a", + "id": "afbe6a03", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1213,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "991c9adb", + "id": "b290da92", "metadata": {}, "source": [ "\n", @@ -1223,7 +1223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9c7dd3ca", + "id": "896bdba0", "metadata": {}, "outputs": [], "source": [ @@ -1256,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "7610d0ff", + "id": "b549928d", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1265,7 +1265,7 @@ { "cell_type": "code", "execution_count": null, - "id": "857a5cec", + "id": "8827a868", "metadata": {}, "outputs": [], "source": [ @@ -1304,7 +1304,7 @@ }, { "cell_type": "markdown", - "id": "f5089370", + "id": "f39ba38b", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens.\n", @@ -1315,7 +1315,7 @@ { "cell_type": "code", "execution_count": null, - "id": "67d2539a", + "id": "eadea48c", "metadata": {}, "outputs": [], "source": [ @@ -1325,7 +1325,7 @@ }, { "cell_type": "markdown", - "id": "4ac77606", + "id": "b5599149", "metadata": {}, "source": [ "

    \n", @@ -1336,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "eefc1b8f", + "id": "fa8ddd38", "metadata": { "tags": [ "solution" @@ -1350,7 +1350,7 @@ }, { "cell_type": "markdown", - "id": "dea4b18b", + "id": "9261ba02", "metadata": { "tags": [ "solution" @@ -1365,7 +1365,7 @@ }, { "cell_type": "markdown", - "id": "2b3203e1", + "id": "09cd4b31", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1374,7 +1374,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0878fa69", + "id": "004c2744", "metadata": {}, "outputs": [], "source": [ @@ -1384,7 +1384,7 @@ }, { "cell_type": "markdown", - "id": "21fb3bcb", + "id": "10f6e82a", "metadata": {}, "source": [ "

    \n", @@ -1395,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "b2b83581", + "id": "37ee01b8", "metadata": { "tags": [ "solution" @@ -1409,7 +1409,7 @@ }, { "cell_type": "markdown", - "id": "b6a36c08", + "id": "eef4cb3d", "metadata": { "tags": [ "solution" @@ -1427,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "10fd930e", + "id": "5f1a65c7", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1436,7 +1436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4cd9057a", + "id": "c20db2dc", "metadata": {}, "outputs": [], "source": [ @@ -1448,7 +1448,7 @@ }, { "cell_type": "markdown", - "id": "53abc3bb", + "id": "db17eead", "metadata": {}, "source": [ "

    \n", @@ -1459,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "0c0b5970", + "id": "6c3eaa25", "metadata": { "tags": [ "solution" @@ -1473,7 +1473,7 @@ }, { "cell_type": "markdown", - "id": "a4e568c7", + "id": "5cf16cd9", "metadata": { "tags": [ "solution" @@ -1490,7 +1490,7 @@ }, { "cell_type": "markdown", - "id": "ee45ee7e", + "id": "30a9b553", "metadata": {}, "source": [ "

    \n", @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "75a5866f", + "id": "dea4299b", "metadata": { "tags": [ "solution" @@ -1515,7 +1515,7 @@ }, { "cell_type": "markdown", - "id": "765f74c6", + "id": "c144e90d", "metadata": { "tags": [ "solution" @@ -1531,7 +1531,7 @@ }, { "cell_type": "markdown", - "id": "41a824a7", + "id": "335772f7", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "91dddcdc", + "id": "8af404b4", "metadata": {}, "source": [ "

    \n", @@ -1558,7 +1558,7 @@ }, { "cell_type": "markdown", - "id": "9feabbd4", + "id": "9295ffc7", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1570,7 +1570,7 @@ }, { "cell_type": "markdown", - "id": "d48569a6", + "id": "7cbf3b1a", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1579,7 +1579,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d79ed624", + "id": "1a3769ac", "metadata": {}, "outputs": [], "source": [ @@ -1592,7 +1592,7 @@ }, { "cell_type": "markdown", - "id": "63aca81c", + "id": "3a3a8139", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1601,7 +1601,7 @@ { "cell_type": "code", "execution_count": null, - "id": "268eb42f", + "id": "36f20530", "metadata": {}, "outputs": [], "source": [ @@ -1630,7 +1630,7 @@ }, { "cell_type": "markdown", - "id": "783d702b", + "id": "8622949e", "metadata": {}, "source": [ "### UNet model\n", @@ -1640,7 +1640,7 @@ }, { "cell_type": "markdown", - "id": "f114069b", + "id": "9ab55c00", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1649,7 +1649,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8d0a5ab3", + "id": "66bd1d56", "metadata": {}, "outputs": [], "source": [ @@ -1697,7 +1697,7 @@ }, { "cell_type": "markdown", - "id": "3f3c87f9", + "id": "6d20945b", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1706,7 +1706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "52c8fb2e", + "id": "827d2f32", "metadata": {}, "outputs": [], "source": [ @@ -1744,7 +1744,7 @@ }, { "cell_type": "markdown", - "id": "f294c563", + "id": "3a0153a5", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1753,7 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a792d29f", + "id": "716b936f", "metadata": {}, "outputs": [], "source": [ @@ -1764,7 +1764,7 @@ }, { "cell_type": "markdown", - "id": "e4400668", + "id": "b24bdfbd", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1773,7 +1773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "38b615ff", + "id": "bc71bff7", "metadata": { "lines_to_next_cell": 1 }, @@ -1789,7 +1789,7 @@ }, { "cell_type": "markdown", - "id": "6eef3ca6", + "id": "2b474711", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1800,7 +1800,7 @@ { "cell_type": "code", "execution_count": null, - "id": "564550c8", + "id": "e1d20e0b", "metadata": { "lines_to_next_cell": 1 }, @@ -1817,7 +1817,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c2f88bd6", + "id": "4b77f687", "metadata": { "lines_to_next_cell": 1 }, @@ -1843,7 +1843,7 @@ }, { "cell_type": "markdown", - "id": "d94541f8", + "id": "b5eb2c28", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1852,7 +1852,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2f402794", + "id": "3a1d22bd", "metadata": {}, "outputs": [], "source": [ @@ -1862,7 +1862,7 @@ }, { "cell_type": "markdown", - "id": "527a3789", + "id": "29912374", "metadata": {}, "source": [ "

    \n", @@ -1873,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "09164156", + "id": "cf8ec03e", "metadata": { "tags": [ "solution" @@ -1887,7 +1887,7 @@ }, { "cell_type": "markdown", - "id": "c106b9be", + "id": "bde4066d", "metadata": { "tags": [ "solution" @@ -1901,7 +1901,7 @@ }, { "cell_type": "markdown", - "id": "ec2b36f5", + "id": "8a598bb3", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data\n", @@ -1911,7 +1911,7 @@ }, { "cell_type": "markdown", - "id": "8194dcee", + "id": "4b63fc64", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1922,7 +1922,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e613bf75", + "id": "d03b2297", "metadata": {}, "outputs": [], "source": [ @@ -1943,7 +1943,7 @@ }, { "cell_type": "markdown", - "id": "324412bf", + "id": "31d01ee1", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1952,7 +1952,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8d094c79", + "id": "aab3b99c", "metadata": {}, "outputs": [], "source": [ @@ -1962,7 +1962,7 @@ }, { "cell_type": "markdown", - "id": "38893a5f", + "id": "e12f3a1d", "metadata": {}, "source": [ "

    \n", @@ -1973,7 +1973,7 @@ }, { "cell_type": "markdown", - "id": "57de716e", + "id": "61bade0f", "metadata": { "tags": [ "solution" @@ -1987,7 +1987,7 @@ }, { "cell_type": "markdown", - "id": "c9f5e127", + "id": "f32a2e94", "metadata": { "tags": [ "solution" @@ -2001,7 +2001,7 @@ }, { "cell_type": "markdown", - "id": "19f22363", + "id": "3c296abe", "metadata": {}, "source": [ "

    \n", @@ -2012,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "38e5971d", + "id": "aa8db1dd", "metadata": { "tags": [ "solution" @@ -2026,7 +2026,7 @@ }, { "cell_type": "markdown", - "id": "70eb7e44", + "id": "697b36bf", "metadata": { "tags": [ "solution" @@ -2041,7 +2041,7 @@ }, { "cell_type": "markdown", - "id": "baaba56b", + "id": "749d2d87", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2052,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0dbacd4c", + "id": "e52a2f68", "metadata": {}, "outputs": [], "source": [ @@ -2089,7 +2089,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d420fd52", + "id": "76324612", "metadata": {}, "outputs": [], "source": [ @@ -2100,7 +2100,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6d23b631", + "id": "1544565a", "metadata": {}, "outputs": [], "source": [ @@ -2110,19 +2110,20 @@ }, { "cell_type": "markdown", - "id": "121897cd", + "id": "d2646697", "metadata": {}, "source": [ "

    \n", " Task 5.4:

    \n", - "How does the new denoiser perform compared to the one from the previous section?\n", + "How does the new denoiser perform compared to the one from the previous section? Why?\n", "
    " ] }, { "cell_type": "markdown", - "id": "d7d6e35c", + "id": "9508a7c1", "metadata": { + "lines_to_next_cell": 0, "tags": [ "solution" ] @@ -2131,7 +2132,16 @@ "**5.4 Answer:**\n", "\n", "The new denoiser has been trained on both MNIST and FashionMNIST, and as a result, it no longer insist on reshaping objects from the FashionMNIST dataset into digits. However, it seems to be performing slightly worse on the original MNIST (some of the digits are hardly recognisable).\n", - "\n", + "If you look more closely at the code, you'll notice that we haven't shuffled the data in our `DataLoader`. This means that every epoch the model will first train on all of the MNIST data, then on all of the FashinMNIST.\n", + "The effect that we're seeing here, where it's performing worse of the MNIST data, points to an important lesson: Models Forget!\n", + "If the model is trained for too long without any MNISt examples, as it is here, it begins to overwrite what it has learned about that data." + ] + }, + { + "cell_type": "markdown", + "id": "4f02d520", + "metadata": {}, + "source": [ "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", "\n", "We previously performed the training sequentially on the MNIST data first then followed by the FashionMNIST data. Now, we ask for the training data to be shuffled and observe the impact on performance. (noe the `shuffle=True` in the lines below)" @@ -2140,7 +2150,7 @@ { "cell_type": "code", "execution_count": null, - "id": "227404b2", + "id": "fb070c5c", "metadata": {}, "outputs": [], "source": [ @@ -2177,7 +2187,7 @@ { "cell_type": "code", "execution_count": null, - "id": "01e3e4dc", + "id": "2cfefa77", "metadata": {}, "outputs": [], "source": [ @@ -2188,7 +2198,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5df0f7a0", + "id": "56718c41", "metadata": {}, "outputs": [], "source": [ @@ -2198,7 +2208,7 @@ }, { "cell_type": "markdown", - "id": "510edc26", + "id": "df6234dd", "metadata": {}, "source": [ "

    \n", @@ -2209,7 +2219,7 @@ }, { "cell_type": "markdown", - "id": "f1670840", + "id": "7e149cd8", "metadata": { "tags": [ "solution" @@ -2223,7 +2233,7 @@ }, { "cell_type": "markdown", - "id": "21c20845", + "id": "dbe9b728", "metadata": {}, "source": [ "\n", @@ -2237,7 +2247,7 @@ }, { "cell_type": "markdown", - "id": "b7a1fa15", + "id": "b69ac817", "metadata": {}, "source": [ "\n", @@ -2251,7 +2261,7 @@ }, { "cell_type": "markdown", - "id": "389a3851", + "id": "b682aed4", "metadata": {}, "source": [] } From f7963b79402a04b1b7ec6d3f027ae7bb6ef05503 Mon Sep 17 00:00:00 2001 From: afoix Date: Mon, 19 Aug 2024 23:46:27 +0000 Subject: [PATCH 51/51] Commit from GitHub Actions (Build Notebooks) --- exercise.ipynb | 236 ++++++++++++++++++------------------- solution.ipynb | 312 ++++++++++++++++++++++++------------------------- 2 files changed, 274 insertions(+), 274 deletions(-) diff --git a/exercise.ipynb b/exercise.ipynb index f05295e..e5cda35 100644 --- a/exercise.ipynb +++ b/exercise.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "f4c5998d", + "id": "ad68ff94", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "400de6a4", + "id": "c0f0735a", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks.\n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "3baf2a90", + "id": "5619f37d", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "fac88ce5", + "id": "aba193c5", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "12f7ca06", + "id": "c1cf118b", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2eaac11e", + "id": "c29ae4dc", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "0fa59082", + "id": "1bb942ea", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "44f8cc97", + "id": "32077360", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fa4dbba7", + "id": "1adbc5ee", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "3afbd53b", + "id": "dd092467", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45d6aa77", + "id": "5d779046", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "60351b4b", + "id": "9eae44bc", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "f2e929ca", + "id": "1242b7da", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "2dbcf4b2", + "id": "586be487", "metadata": {}, "source": [ "

    \n", @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "39ce6b99", + "id": "2ad4f801", "metadata": {}, "source": [ "## Part 1.2: Global Corruption of data\n", @@ -204,7 +204,7 @@ }, { "cell_type": "markdown", - "id": "45f7b920", + "id": "0749a9f6", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -213,7 +213,7 @@ { "cell_type": "code", "execution_count": null, - "id": "20be6faf", + "id": "19c5869e", "metadata": {}, "outputs": [], "source": [ @@ -224,7 +224,7 @@ }, { "cell_type": "markdown", - "id": "698581c8", + "id": "46e255ca", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -233,7 +233,7 @@ { "cell_type": "code", "execution_count": null, - "id": "69f364a2", + "id": "823060ce", "metadata": {}, "outputs": [], "source": [ @@ -249,7 +249,7 @@ }, { "cell_type": "markdown", - "id": "a2e35eaf", + "id": "c09f310e", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -258,7 +258,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e773f840", + "id": "5264fb24", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "d8c22dfb", + "id": "d0235c57", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8.\n", @@ -279,7 +279,7 @@ { "cell_type": "code", "execution_count": null, - "id": "20d299d2", + "id": "bf580bd0", "metadata": {}, "outputs": [], "source": [ @@ -295,7 +295,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6c9fc998", + "id": "dc053eb0", "metadata": {}, "outputs": [], "source": [ @@ -317,7 +317,7 @@ }, { "cell_type": "markdown", - "id": "ae4eef7e", + "id": "66a4eb68", "metadata": {}, "source": [ "

    \n", @@ -328,7 +328,7 @@ }, { "cell_type": "markdown", - "id": "a90db194", + "id": "ea13603f", "metadata": {}, "source": [ "\n", @@ -340,7 +340,7 @@ }, { "cell_type": "markdown", - "id": "1f6d7182", + "id": "5a17ff4d", "metadata": {}, "source": [ "\n", @@ -353,7 +353,7 @@ }, { "cell_type": "markdown", - "id": "613e4cd4", + "id": "e6cb618a", "metadata": {}, "source": [ "\n", @@ -371,7 +371,7 @@ }, { "cell_type": "markdown", - "id": "2fb5fede", + "id": "8cb597ed", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -382,7 +382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cdcd46d5", + "id": "0a677906", "metadata": {}, "outputs": [], "source": [ @@ -396,7 +396,7 @@ }, { "cell_type": "markdown", - "id": "c2cf6bfa", + "id": "d76c4b98", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -405,7 +405,7 @@ { "cell_type": "code", "execution_count": null, - "id": "98eddd14", + "id": "7d448ce4", "metadata": {}, "outputs": [], "source": [ @@ -430,7 +430,7 @@ }, { "cell_type": "markdown", - "id": "af0edd25", + "id": "855c4b61", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -439,7 +439,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3deddbd3", + "id": "8a2d97a2", "metadata": {}, "outputs": [], "source": [ @@ -458,7 +458,7 @@ }, { "cell_type": "markdown", - "id": "4ed7aa39", + "id": "441c4d04", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -467,7 +467,7 @@ { "cell_type": "code", "execution_count": null, - "id": "43b0197b", + "id": "28d546e4", "metadata": {}, "outputs": [], "source": [ @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "1ae683d2", + "id": "9eb196cd", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -504,7 +504,7 @@ { "cell_type": "code", "execution_count": null, - "id": "081f197c", + "id": "133a85ba", "metadata": {}, "outputs": [], "source": [ @@ -518,7 +518,7 @@ }, { "cell_type": "markdown", - "id": "597135be", + "id": "90762c28", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -527,7 +527,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e32e286d", + "id": "a949ffda", "metadata": {}, "outputs": [], "source": [ @@ -560,7 +560,7 @@ }, { "cell_type": "markdown", - "id": "75895920", + "id": "96bc28fd", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -569,7 +569,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7006b624", + "id": "29093a14", "metadata": {}, "outputs": [], "source": [ @@ -584,7 +584,7 @@ }, { "cell_type": "markdown", - "id": "4467a232", + "id": "c7dddc4b", "metadata": {}, "source": [ "

    \n", @@ -595,7 +595,7 @@ }, { "cell_type": "markdown", - "id": "e6853659", + "id": "b20df043", "metadata": {}, "source": [ "

    \n", @@ -606,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "786976e5", + "id": "94551ca6", "metadata": {}, "source": [ "

    \n", @@ -617,7 +617,7 @@ }, { "cell_type": "markdown", - "id": "b151cf85", + "id": "edcc38e3", "metadata": {}, "source": [ "

    \n", @@ -629,7 +629,7 @@ }, { "cell_type": "markdown", - "id": "046f2d98", + "id": "ba7ae77b", "metadata": {}, "source": [ "

    \n", @@ -644,7 +644,7 @@ }, { "cell_type": "markdown", - "id": "efb66b32", + "id": "e0afcf03", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -657,7 +657,7 @@ { "cell_type": "code", "execution_count": null, - "id": "67a73dc1", + "id": "2c8432f0", "metadata": {}, "outputs": [], "source": [ @@ -679,7 +679,7 @@ }, { "cell_type": "markdown", - "id": "eaa7a921", + "id": "dac0d3bd", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -688,7 +688,7 @@ { "cell_type": "code", "execution_count": null, - "id": "92257da3", + "id": "c6438d2e", "metadata": {}, "outputs": [], "source": [ @@ -700,7 +700,7 @@ }, { "cell_type": "markdown", - "id": "b7426171", + "id": "f6ec7c0d", "metadata": {}, "source": [ "We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -709,7 +709,7 @@ { "cell_type": "code", "execution_count": null, - "id": "994b40c0", + "id": "ada1daff", "metadata": { "lines_to_next_cell": 1 }, @@ -764,7 +764,7 @@ }, { "cell_type": "markdown", - "id": "a1321ccd", + "id": "1c841eaa", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -773,7 +773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "348d2b4d", + "id": "073a89a2", "metadata": {}, "outputs": [], "source": [ @@ -785,7 +785,7 @@ }, { "cell_type": "markdown", - "id": "19651455", + "id": "267208ff", "metadata": {}, "source": [ "

    \n", @@ -796,7 +796,7 @@ }, { "cell_type": "markdown", - "id": "651dfee3", + "id": "82d1cba3", "metadata": {}, "source": [ "

    \n", @@ -807,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "6d40345f", + "id": "dd6ca1dd", "metadata": {}, "source": [ "

    \n", @@ -818,7 +818,7 @@ }, { "cell_type": "markdown", - "id": "e17b0677", + "id": "c231d586", "metadata": {}, "source": [ "

    \n", @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "04ca2bfa", + "id": "a676ba72", "metadata": {}, "source": [ "

    \n", @@ -841,7 +841,7 @@ }, { "cell_type": "markdown", - "id": "8cf32682", + "id": "e9a5583c", "metadata": {}, "source": [ "

    \n", @@ -856,7 +856,7 @@ }, { "cell_type": "markdown", - "id": "afbe6a03", + "id": "c30d4df6", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -865,7 +865,7 @@ }, { "cell_type": "markdown", - "id": "b290da92", + "id": "2784e751", "metadata": {}, "source": [ "\n", @@ -875,7 +875,7 @@ { "cell_type": "code", "execution_count": null, - "id": "896bdba0", + "id": "7403b38f", "metadata": {}, "outputs": [], "source": [ @@ -908,7 +908,7 @@ }, { "cell_type": "markdown", - "id": "b549928d", + "id": "3f1881d0", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -917,7 +917,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8827a868", + "id": "1ef66e49", "metadata": {}, "outputs": [], "source": [ @@ -956,7 +956,7 @@ }, { "cell_type": "markdown", - "id": "f39ba38b", + "id": "3587e26e", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens.\n", @@ -967,7 +967,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eadea48c", + "id": "3a141027", "metadata": {}, "outputs": [], "source": [ @@ -977,7 +977,7 @@ }, { "cell_type": "markdown", - "id": "b5599149", + "id": "09f0b17b", "metadata": {}, "source": [ "

    \n", @@ -988,7 +988,7 @@ }, { "cell_type": "markdown", - "id": "09cd4b31", + "id": "e886ceb9", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -997,7 +997,7 @@ { "cell_type": "code", "execution_count": null, - "id": "004c2744", + "id": "5d8fe87c", "metadata": {}, "outputs": [], "source": [ @@ -1007,7 +1007,7 @@ }, { "cell_type": "markdown", - "id": "10f6e82a", + "id": "63f51d95", "metadata": {}, "source": [ "

    \n", @@ -1018,7 +1018,7 @@ }, { "cell_type": "markdown", - "id": "5f1a65c7", + "id": "d84b50f2", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1027,7 +1027,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c20db2dc", + "id": "1f2524bc", "metadata": {}, "outputs": [], "source": [ @@ -1039,7 +1039,7 @@ }, { "cell_type": "markdown", - "id": "db17eead", + "id": "162b2791", "metadata": {}, "source": [ "

    \n", @@ -1050,7 +1050,7 @@ }, { "cell_type": "markdown", - "id": "30a9b553", + "id": "693673e7", "metadata": {}, "source": [ "

    \n", @@ -1061,7 +1061,7 @@ }, { "cell_type": "markdown", - "id": "335772f7", + "id": "07ffa5c9", "metadata": {}, "source": [ "

    \n", @@ -1074,7 +1074,7 @@ }, { "cell_type": "markdown", - "id": "8af404b4", + "id": "e2b3e006", "metadata": {}, "source": [ "

    \n", @@ -1088,7 +1088,7 @@ }, { "cell_type": "markdown", - "id": "9295ffc7", + "id": "d9c75351", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1100,7 +1100,7 @@ }, { "cell_type": "markdown", - "id": "7cbf3b1a", + "id": "3c96a7d4", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1109,7 +1109,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1a3769ac", + "id": "7eb143be", "metadata": {}, "outputs": [], "source": [ @@ -1122,7 +1122,7 @@ }, { "cell_type": "markdown", - "id": "3a3a8139", + "id": "420f2eb7", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1131,7 +1131,7 @@ { "cell_type": "code", "execution_count": null, - "id": "36f20530", + "id": "0c9ba2bc", "metadata": {}, "outputs": [], "source": [ @@ -1160,7 +1160,7 @@ }, { "cell_type": "markdown", - "id": "8622949e", + "id": "3aa422bb", "metadata": {}, "source": [ "### UNet model\n", @@ -1170,7 +1170,7 @@ }, { "cell_type": "markdown", - "id": "9ab55c00", + "id": "ce6e4ffe", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1179,7 +1179,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66bd1d56", + "id": "22e3196a", "metadata": {}, "outputs": [], "source": [ @@ -1227,7 +1227,7 @@ }, { "cell_type": "markdown", - "id": "6d20945b", + "id": "afdc53ce", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1236,7 +1236,7 @@ { "cell_type": "code", "execution_count": null, - "id": "827d2f32", + "id": "98818e5f", "metadata": {}, "outputs": [], "source": [ @@ -1274,7 +1274,7 @@ }, { "cell_type": "markdown", - "id": "3a0153a5", + "id": "851ee8bc", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1283,7 +1283,7 @@ { "cell_type": "code", "execution_count": null, - "id": "716b936f", + "id": "e75e5250", "metadata": {}, "outputs": [], "source": [ @@ -1294,7 +1294,7 @@ }, { "cell_type": "markdown", - "id": "b24bdfbd", + "id": "3b123c83", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1303,7 +1303,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bc71bff7", + "id": "649578f4", "metadata": { "lines_to_next_cell": 1 }, @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "2b474711", + "id": "31ee6225", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1330,7 +1330,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e1d20e0b", + "id": "aeada78c", "metadata": { "lines_to_next_cell": 1 }, @@ -1347,7 +1347,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4b77f687", + "id": "04b85210", "metadata": { "lines_to_next_cell": 1 }, @@ -1373,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "b5eb2c28", + "id": "999110e1", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1382,7 +1382,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3a1d22bd", + "id": "48932965", "metadata": {}, "outputs": [], "source": [ @@ -1392,7 +1392,7 @@ }, { "cell_type": "markdown", - "id": "29912374", + "id": "a88faa07", "metadata": {}, "source": [ "

    \n", @@ -1403,7 +1403,7 @@ }, { "cell_type": "markdown", - "id": "8a598bb3", + "id": "933c7ac9", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data\n", @@ -1413,7 +1413,7 @@ }, { "cell_type": "markdown", - "id": "4b63fc64", + "id": "5b4369e0", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1424,7 +1424,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d03b2297", + "id": "5e57d385", "metadata": {}, "outputs": [], "source": [ @@ -1445,7 +1445,7 @@ }, { "cell_type": "markdown", - "id": "31d01ee1", + "id": "b36c6e41", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1454,7 +1454,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aab3b99c", + "id": "6744e360", "metadata": {}, "outputs": [], "source": [ @@ -1464,7 +1464,7 @@ }, { "cell_type": "markdown", - "id": "e12f3a1d", + "id": "971da0c3", "metadata": {}, "source": [ "

    \n", @@ -1475,7 +1475,7 @@ }, { "cell_type": "markdown", - "id": "3c296abe", + "id": "1df30b46", "metadata": {}, "source": [ "

    \n", @@ -1486,7 +1486,7 @@ }, { "cell_type": "markdown", - "id": "749d2d87", + "id": "835030fd", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -1497,7 +1497,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e52a2f68", + "id": "c7cc9bb3", "metadata": {}, "outputs": [], "source": [ @@ -1534,7 +1534,7 @@ { "cell_type": "code", "execution_count": null, - "id": "76324612", + "id": "46edff16", "metadata": {}, "outputs": [], "source": [ @@ -1545,7 +1545,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1544565a", + "id": "2dac72fa", "metadata": {}, "outputs": [], "source": [ @@ -1555,7 +1555,7 @@ }, { "cell_type": "markdown", - "id": "d2646697", + "id": "288c6764", "metadata": {}, "source": [ "

    \n", @@ -1566,7 +1566,7 @@ }, { "cell_type": "markdown", - "id": "4f02d520", + "id": "a9694e46", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", @@ -1577,7 +1577,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fb070c5c", + "id": "ae52c3d0", "metadata": {}, "outputs": [], "source": [ @@ -1614,7 +1614,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2cfefa77", + "id": "f71a710b", "metadata": {}, "outputs": [], "source": [ @@ -1625,7 +1625,7 @@ { "cell_type": "code", "execution_count": null, - "id": "56718c41", + "id": "52a67bf2", "metadata": {}, "outputs": [], "source": [ @@ -1635,7 +1635,7 @@ }, { "cell_type": "markdown", - "id": "df6234dd", + "id": "b8fe50cf", "metadata": {}, "source": [ "

    \n", @@ -1646,7 +1646,7 @@ }, { "cell_type": "markdown", - "id": "dbe9b728", + "id": "ec448985", "metadata": {}, "source": [ "\n", @@ -1660,7 +1660,7 @@ }, { "cell_type": "markdown", - "id": "b69ac817", + "id": "33838105", "metadata": {}, "source": [ "\n", @@ -1674,7 +1674,7 @@ }, { "cell_type": "markdown", - "id": "b682aed4", + "id": "eee21f1e", "metadata": {}, "source": [] } diff --git a/solution.ipynb b/solution.ipynb index 11e9d64..fa15474 100644 --- a/solution.ipynb +++ b/solution.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "f4c5998d", + "id": "ad68ff94", "metadata": {}, "source": [ "# Exercise 7: Failure Modes And Limits of Deep Learning" @@ -10,7 +10,7 @@ }, { "cell_type": "markdown", - "id": "400de6a4", + "id": "c0f0735a", "metadata": {}, "source": [ "In the following exercise, we explore the failure modes and limits of neural networks.\n", @@ -23,7 +23,7 @@ }, { "cell_type": "markdown", - "id": "3baf2a90", + "id": "5619f37d", "metadata": {}, "source": [ "\n", @@ -44,7 +44,7 @@ }, { "cell_type": "markdown", - "id": "fac88ce5", + "id": "aba193c5", "metadata": {}, "source": [ "### Acknowledgements\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "12f7ca06", + "id": "c1cf118b", "metadata": {}, "source": [ "### Data Loading\n", @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2eaac11e", + "id": "c29ae4dc", "metadata": {}, "outputs": [], "source": [ @@ -90,7 +90,7 @@ }, { "cell_type": "markdown", - "id": "0fa59082", + "id": "1bb942ea", "metadata": {}, "source": [ "### Part 1: Preparation of a Tainted Dataset\n", @@ -101,7 +101,7 @@ { "cell_type": "code", "execution_count": null, - "id": "44f8cc97", + "id": "32077360", "metadata": {}, "outputs": [], "source": [ @@ -115,7 +115,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fa4dbba7", + "id": "1adbc5ee", "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "markdown", - "id": "3afbd53b", + "id": "dd092467", "metadata": {}, "source": [ "## Part 1.1: Local Corruption of Data\n", @@ -137,7 +137,7 @@ { "cell_type": "code", "execution_count": null, - "id": "45d6aa77", + "id": "5d779046", "metadata": {}, "outputs": [], "source": [ @@ -149,7 +149,7 @@ { "cell_type": "code", "execution_count": null, - "id": "60351b4b", + "id": "9eae44bc", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "f2e929ca", + "id": "1242b7da", "metadata": {}, "source": [ "

    \n", @@ -183,7 +183,7 @@ }, { "cell_type": "markdown", - "id": "f7652227", + "id": "73add44b", "metadata": { "tags": [ "solution" @@ -199,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "58ebc7b2", + "id": "35e8819c", "metadata": { "tags": [ "solution" @@ -215,7 +215,7 @@ }, { "cell_type": "markdown", - "id": "2dbcf4b2", + "id": "586be487", "metadata": {}, "source": [ "

    \n", @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "4bad6d7c", + "id": "5b6c8072", "metadata": { "tags": [ "solution" @@ -240,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "69cccf93", + "id": "d55321f4", "metadata": { "tags": [ "solution" @@ -261,7 +261,7 @@ }, { "cell_type": "markdown", - "id": "39ce6b99", + "id": "2ad4f801", "metadata": {}, "source": [ "## Part 1.2: Global Corruption of data\n", @@ -271,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "45f7b920", + "id": "0749a9f6", "metadata": {}, "source": [ "You may have noticed that the images are stored as arrays of integers. First we cast them to float to be able to add textures easily without integer wrapping issues." @@ -280,7 +280,7 @@ { "cell_type": "code", "execution_count": null, - "id": "20be6faf", + "id": "19c5869e", "metadata": {}, "outputs": [], "source": [ @@ -291,7 +291,7 @@ }, { "cell_type": "markdown", - "id": "698581c8", + "id": "46e255ca", "metadata": {}, "source": [ "Then we create the grid texture and visualize it." @@ -300,7 +300,7 @@ { "cell_type": "code", "execution_count": null, - "id": "69f364a2", + "id": "823060ce", "metadata": {}, "outputs": [], "source": [ @@ -316,7 +316,7 @@ }, { "cell_type": "markdown", - "id": "a2e35eaf", + "id": "c09f310e", "metadata": {}, "source": [ "Next we add the texture to all 4s in the train and test set." @@ -325,7 +325,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e773f840", + "id": "5264fb24", "metadata": {}, "outputs": [], "source": [ @@ -336,7 +336,7 @@ }, { "cell_type": "markdown", - "id": "d8c22dfb", + "id": "d0235c57", "metadata": {}, "source": [ "After adding the texture, we have to make sure the values are between 0 and 255 and then cast back to uint8.\n", @@ -346,7 +346,7 @@ { "cell_type": "code", "execution_count": null, - "id": "20d299d2", + "id": "bf580bd0", "metadata": {}, "outputs": [], "source": [ @@ -362,7 +362,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6c9fc998", + "id": "dc053eb0", "metadata": {}, "outputs": [], "source": [ @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "ae4eef7e", + "id": "66a4eb68", "metadata": {}, "source": [ "

    \n", @@ -395,7 +395,7 @@ }, { "cell_type": "markdown", - "id": "8160ab25", + "id": "1783f875", "metadata": { "tags": [ "solution" @@ -413,7 +413,7 @@ }, { "cell_type": "markdown", - "id": "b46002b6", + "id": "9adb2396", "metadata": { "tags": [ "solution" @@ -442,7 +442,7 @@ }, { "cell_type": "markdown", - "id": "a90db194", + "id": "ea13603f", "metadata": {}, "source": [ "\n", @@ -454,7 +454,7 @@ }, { "cell_type": "markdown", - "id": "c61d96bd", + "id": "2dc8d655", "metadata": { "tags": [ "solution" @@ -468,7 +468,7 @@ }, { "cell_type": "markdown", - "id": "78a448b1", + "id": "239d45dc", "metadata": { "tags": [ "solution" @@ -482,7 +482,7 @@ }, { "cell_type": "markdown", - "id": "1f6d7182", + "id": "5a17ff4d", "metadata": {}, "source": [ "\n", @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "613e4cd4", + "id": "e6cb618a", "metadata": {}, "source": [ "\n", @@ -513,7 +513,7 @@ }, { "cell_type": "markdown", - "id": "2fb5fede", + "id": "8cb597ed", "metadata": {}, "source": [ "### Part 2: Create and Train an Image Classification Neural Network on Clean and Tainted Data\n", @@ -524,7 +524,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cdcd46d5", + "id": "0a677906", "metadata": {}, "outputs": [], "source": [ @@ -538,7 +538,7 @@ }, { "cell_type": "markdown", - "id": "c2cf6bfa", + "id": "d76c4b98", "metadata": {}, "source": [ "Now we will train the neural network. A training function is provided below - this should be familiar, but make sure you look it over and understand what is happening in the training loop." @@ -547,7 +547,7 @@ { "cell_type": "code", "execution_count": null, - "id": "98eddd14", + "id": "7d448ce4", "metadata": {}, "outputs": [], "source": [ @@ -572,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "af0edd25", + "id": "855c4b61", "metadata": {}, "source": [ "We have to choose hyperparameters for our model. We have selected to train for two epochs, with a batch size of 64 for training and 1000 for testing. We are using the cross entropy loss, a standard multi-class classification loss." @@ -581,7 +581,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3deddbd3", + "id": "8a2d97a2", "metadata": {}, "outputs": [], "source": [ @@ -600,7 +600,7 @@ }, { "cell_type": "markdown", - "id": "4ed7aa39", + "id": "441c4d04", "metadata": {}, "source": [ "Next we initialize a clean model, and a tainted model. We want to have reproducible results, so we set the initial weights with a specific random seed. The seed number does not matter, just that it is the same!" @@ -609,7 +609,7 @@ { "cell_type": "code", "execution_count": null, - "id": "43b0197b", + "id": "28d546e4", "metadata": {}, "outputs": [], "source": [ @@ -637,7 +637,7 @@ }, { "cell_type": "markdown", - "id": "1ae683d2", + "id": "9eb196cd", "metadata": {}, "source": [ "Next we initialize the clean and tainted dataloaders, again with a specific random seed for reproducibility." @@ -646,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "081f197c", + "id": "133a85ba", "metadata": {}, "outputs": [], "source": [ @@ -660,7 +660,7 @@ }, { "cell_type": "markdown", - "id": "597135be", + "id": "90762c28", "metadata": {}, "source": [ "Now it is time to train the neural networks! We are storing the training loss history for each model so we can visualize it later." @@ -669,7 +669,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e32e286d", + "id": "a949ffda", "metadata": {}, "outputs": [], "source": [ @@ -702,7 +702,7 @@ }, { "cell_type": "markdown", - "id": "75895920", + "id": "96bc28fd", "metadata": {}, "source": [ "Now we visualize the loss history for the clean and tainted models." @@ -711,7 +711,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7006b624", + "id": "29093a14", "metadata": {}, "outputs": [], "source": [ @@ -726,7 +726,7 @@ }, { "cell_type": "markdown", - "id": "4467a232", + "id": "c7dddc4b", "metadata": {}, "source": [ "

    \n", @@ -737,7 +737,7 @@ }, { "cell_type": "markdown", - "id": "12a2ca82", + "id": "dbf8c34e", "metadata": { "tags": [ "solution" @@ -751,7 +751,7 @@ }, { "cell_type": "markdown", - "id": "97aab178", + "id": "d1e6912d", "metadata": { "tags": [ "solution" @@ -765,7 +765,7 @@ }, { "cell_type": "markdown", - "id": "e6853659", + "id": "b20df043", "metadata": {}, "source": [ "

    \n", @@ -776,7 +776,7 @@ }, { "cell_type": "markdown", - "id": "ee00919f", + "id": "fb4e94d9", "metadata": { "tags": [ "solution" @@ -790,7 +790,7 @@ }, { "cell_type": "markdown", - "id": "0899155c", + "id": "5dac1f8d", "metadata": { "tags": [ "solution" @@ -804,7 +804,7 @@ }, { "cell_type": "markdown", - "id": "786976e5", + "id": "94551ca6", "metadata": {}, "source": [ "

    \n", @@ -815,7 +815,7 @@ }, { "cell_type": "markdown", - "id": "d6a8c3a7", + "id": "e0a63648", "metadata": { "tags": [ "solution" @@ -829,7 +829,7 @@ }, { "cell_type": "markdown", - "id": "1417f3e1", + "id": "774a4d5b", "metadata": { "tags": [ "solution" @@ -843,7 +843,7 @@ }, { "cell_type": "markdown", - "id": "b151cf85", + "id": "edcc38e3", "metadata": {}, "source": [ "

    \n", @@ -855,7 +855,7 @@ }, { "cell_type": "markdown", - "id": "046f2d98", + "id": "ba7ae77b", "metadata": {}, "source": [ "

    \n", @@ -870,7 +870,7 @@ }, { "cell_type": "markdown", - "id": "efb66b32", + "id": "e0afcf03", "metadata": {}, "source": [ "### Part 3: Examining the Results of the Clean and Tainted Networks\n", @@ -883,7 +883,7 @@ { "cell_type": "code", "execution_count": null, - "id": "67a73dc1", + "id": "2c8432f0", "metadata": {}, "outputs": [], "source": [ @@ -905,7 +905,7 @@ }, { "cell_type": "markdown", - "id": "eaa7a921", + "id": "dac0d3bd", "metadata": {}, "source": [ "Now we call the predict method with the clean and tainted models on the clean and tainted datasets." @@ -914,7 +914,7 @@ { "cell_type": "code", "execution_count": null, - "id": "92257da3", + "id": "c6438d2e", "metadata": {}, "outputs": [], "source": [ @@ -926,7 +926,7 @@ }, { "cell_type": "markdown", - "id": "b7426171", + "id": "f6ec7c0d", "metadata": {}, "source": [ "We can investigate the results using the confusion matrix, which you should recall from the Introduction to Machine Learning exercise. The function in the cell below will create a nicely annotated confusion matrix." @@ -935,7 +935,7 @@ { "cell_type": "code", "execution_count": null, - "id": "994b40c0", + "id": "ada1daff", "metadata": { "lines_to_next_cell": 1 }, @@ -990,7 +990,7 @@ }, { "cell_type": "markdown", - "id": "a1321ccd", + "id": "1c841eaa", "metadata": {}, "source": [ "Now we will generate confusion matrices for each model/data combination. Take your time and try and interpret these, and then try and answer the questions below." @@ -999,7 +999,7 @@ { "cell_type": "code", "execution_count": null, - "id": "348d2b4d", + "id": "073a89a2", "metadata": {}, "outputs": [], "source": [ @@ -1011,7 +1011,7 @@ }, { "cell_type": "markdown", - "id": "19651455", + "id": "267208ff", "metadata": {}, "source": [ "

    \n", @@ -1022,7 +1022,7 @@ }, { "cell_type": "markdown", - "id": "c4766bc4", + "id": "29690755", "metadata": { "tags": [ "solution" @@ -1036,7 +1036,7 @@ }, { "cell_type": "markdown", - "id": "41c92b6c", + "id": "ba56b808", "metadata": { "tags": [ "solution" @@ -1051,7 +1051,7 @@ }, { "cell_type": "markdown", - "id": "651dfee3", + "id": "82d1cba3", "metadata": {}, "source": [ "

    \n", @@ -1062,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "f59acfa9", + "id": "cc035f15", "metadata": { "tags": [ "solution" @@ -1076,7 +1076,7 @@ }, { "cell_type": "markdown", - "id": "354500fc", + "id": "0aafabb4", "metadata": { "tags": [ "solution" @@ -1090,7 +1090,7 @@ }, { "cell_type": "markdown", - "id": "6d40345f", + "id": "dd6ca1dd", "metadata": {}, "source": [ "

    \n", @@ -1101,7 +1101,7 @@ }, { "cell_type": "markdown", - "id": "348ae3e8", + "id": "5550a081", "metadata": { "tags": [ "solution" @@ -1115,7 +1115,7 @@ }, { "cell_type": "markdown", - "id": "a714df43", + "id": "ce131527", "metadata": { "tags": [ "solution" @@ -1132,7 +1132,7 @@ }, { "cell_type": "markdown", - "id": "e17b0677", + "id": "c231d586", "metadata": {}, "source": [ "

    \n", @@ -1143,7 +1143,7 @@ }, { "cell_type": "markdown", - "id": "2fe8a46f", + "id": "751a2905", "metadata": { "tags": [ "solution" @@ -1157,7 +1157,7 @@ }, { "cell_type": "markdown", - "id": "32f1c657", + "id": "52c169b9", "metadata": { "tags": [ "solution" @@ -1177,7 +1177,7 @@ }, { "cell_type": "markdown", - "id": "04ca2bfa", + "id": "a676ba72", "metadata": {}, "source": [ "

    \n", @@ -1189,7 +1189,7 @@ }, { "cell_type": "markdown", - "id": "8cf32682", + "id": "e9a5583c", "metadata": {}, "source": [ "

    \n", @@ -1204,7 +1204,7 @@ }, { "cell_type": "markdown", - "id": "afbe6a03", + "id": "c30d4df6", "metadata": {}, "source": [ "### Part 4: Interpretation with Integrated Gradients\n", @@ -1213,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "b290da92", + "id": "2784e751", "metadata": {}, "source": [ "\n", @@ -1223,7 +1223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "896bdba0", + "id": "7403b38f", "metadata": {}, "outputs": [], "source": [ @@ -1256,7 +1256,7 @@ }, { "cell_type": "markdown", - "id": "b549928d", + "id": "3f1881d0", "metadata": {}, "source": [ "Next we provide a function to visualize the output of integrated gradients, using the function above to actually run the algorithm." @@ -1265,7 +1265,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8827a868", + "id": "1ef66e49", "metadata": {}, "outputs": [], "source": [ @@ -1304,7 +1304,7 @@ }, { "cell_type": "markdown", - "id": "f39ba38b", + "id": "3587e26e", "metadata": {}, "source": [ "To start examining the results, we will call the `visualize_integrated_gradients` with the tainted and clean models on the tainted and clean sevens.\n", @@ -1315,7 +1315,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eadea48c", + "id": "3a141027", "metadata": {}, "outputs": [], "source": [ @@ -1325,7 +1325,7 @@ }, { "cell_type": "markdown", - "id": "b5599149", + "id": "09f0b17b", "metadata": {}, "source": [ "

    \n", @@ -1336,7 +1336,7 @@ }, { "cell_type": "markdown", - "id": "fa8ddd38", + "id": "43a466fa", "metadata": { "tags": [ "solution" @@ -1350,7 +1350,7 @@ }, { "cell_type": "markdown", - "id": "9261ba02", + "id": "53e3d16c", "metadata": { "tags": [ "solution" @@ -1365,7 +1365,7 @@ }, { "cell_type": "markdown", - "id": "09cd4b31", + "id": "e886ceb9", "metadata": {}, "source": [ "Now let's look at the attention of the tainted model!" @@ -1374,7 +1374,7 @@ { "cell_type": "code", "execution_count": null, - "id": "004c2744", + "id": "5d8fe87c", "metadata": {}, "outputs": [], "source": [ @@ -1384,7 +1384,7 @@ }, { "cell_type": "markdown", - "id": "10f6e82a", + "id": "63f51d95", "metadata": {}, "source": [ "

    \n", @@ -1395,7 +1395,7 @@ }, { "cell_type": "markdown", - "id": "37ee01b8", + "id": "96f968ca", "metadata": { "tags": [ "solution" @@ -1409,7 +1409,7 @@ }, { "cell_type": "markdown", - "id": "eef4cb3d", + "id": "98ffa814", "metadata": { "tags": [ "solution" @@ -1427,7 +1427,7 @@ }, { "cell_type": "markdown", - "id": "5f1a65c7", + "id": "d84b50f2", "metadata": {}, "source": [ "Now let's look at the regions of the image that Integrated Gradients highlights as important for classifying fours in the clean and tainted models." @@ -1436,7 +1436,7 @@ { "cell_type": "code", "execution_count": null, - "id": "c20db2dc", + "id": "1f2524bc", "metadata": {}, "outputs": [], "source": [ @@ -1448,7 +1448,7 @@ }, { "cell_type": "markdown", - "id": "db17eead", + "id": "162b2791", "metadata": {}, "source": [ "

    \n", @@ -1459,7 +1459,7 @@ }, { "cell_type": "markdown", - "id": "6c3eaa25", + "id": "19e8eaa9", "metadata": { "tags": [ "solution" @@ -1473,7 +1473,7 @@ }, { "cell_type": "markdown", - "id": "5cf16cd9", + "id": "f382878c", "metadata": { "tags": [ "solution" @@ -1490,7 +1490,7 @@ }, { "cell_type": "markdown", - "id": "30a9b553", + "id": "693673e7", "metadata": {}, "source": [ "

    \n", @@ -1501,7 +1501,7 @@ }, { "cell_type": "markdown", - "id": "dea4299b", + "id": "2e00c171", "metadata": { "tags": [ "solution" @@ -1515,7 +1515,7 @@ }, { "cell_type": "markdown", - "id": "c144e90d", + "id": "15827a8b", "metadata": { "tags": [ "solution" @@ -1531,7 +1531,7 @@ }, { "cell_type": "markdown", - "id": "335772f7", + "id": "07ffa5c9", "metadata": {}, "source": [ "

    \n", @@ -1544,7 +1544,7 @@ }, { "cell_type": "markdown", - "id": "8af404b4", + "id": "e2b3e006", "metadata": {}, "source": [ "

    \n", @@ -1558,7 +1558,7 @@ }, { "cell_type": "markdown", - "id": "9295ffc7", + "id": "d9c75351", "metadata": {}, "source": [ "## Part 5: Importance of using the right training data\n", @@ -1570,7 +1570,7 @@ }, { "cell_type": "markdown", - "id": "7cbf3b1a", + "id": "3c96a7d4", "metadata": {}, "source": [ "First, we will write a function to add noise to the MNIST dataset, so that we can train a model to denoise it." @@ -1579,7 +1579,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1a3769ac", + "id": "7eb143be", "metadata": {}, "outputs": [], "source": [ @@ -1592,7 +1592,7 @@ }, { "cell_type": "markdown", - "id": "3a3a8139", + "id": "420f2eb7", "metadata": {}, "source": [ "Next we will visualize a couple MNIST examples with and without noise." @@ -1601,7 +1601,7 @@ { "cell_type": "code", "execution_count": null, - "id": "36f20530", + "id": "0c9ba2bc", "metadata": {}, "outputs": [], "source": [ @@ -1630,7 +1630,7 @@ }, { "cell_type": "markdown", - "id": "8622949e", + "id": "3aa422bb", "metadata": {}, "source": [ "### UNet model\n", @@ -1640,7 +1640,7 @@ }, { "cell_type": "markdown", - "id": "9ab55c00", + "id": "ce6e4ffe", "metadata": {}, "source": [ "The training loop code is also provided here. It is similar to the code used to train the image classification model previously, but look it over to make sure there are no surprises." @@ -1649,7 +1649,7 @@ { "cell_type": "code", "execution_count": null, - "id": "66bd1d56", + "id": "22e3196a", "metadata": {}, "outputs": [], "source": [ @@ -1697,7 +1697,7 @@ }, { "cell_type": "markdown", - "id": "6d20945b", + "id": "afdc53ce", "metadata": {}, "source": [ "Here we choose hyperparameters and initialize the model and data loaders." @@ -1706,7 +1706,7 @@ { "cell_type": "code", "execution_count": null, - "id": "827d2f32", + "id": "98818e5f", "metadata": {}, "outputs": [], "source": [ @@ -1744,7 +1744,7 @@ }, { "cell_type": "markdown", - "id": "3a0153a5", + "id": "851ee8bc", "metadata": {}, "source": [ "Finally, we run the training loop!" @@ -1753,7 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "id": "716b936f", + "id": "e75e5250", "metadata": {}, "outputs": [], "source": [ @@ -1764,7 +1764,7 @@ }, { "cell_type": "markdown", - "id": "b24bdfbd", + "id": "3b123c83", "metadata": {}, "source": [ "As before, we will visualize the training loss. If all went correctly, it should decrease from around 1.0 to less than 0.2." @@ -1773,7 +1773,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bc71bff7", + "id": "649578f4", "metadata": { "lines_to_next_cell": 1 }, @@ -1789,7 +1789,7 @@ }, { "cell_type": "markdown", - "id": "2b474711", + "id": "31ee6225", "metadata": {}, "source": [ "### Check denoising performance\n", @@ -1800,7 +1800,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e1d20e0b", + "id": "aeada78c", "metadata": { "lines_to_next_cell": 1 }, @@ -1817,7 +1817,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4b77f687", + "id": "04b85210", "metadata": { "lines_to_next_cell": 1 }, @@ -1843,7 +1843,7 @@ }, { "cell_type": "markdown", - "id": "b5eb2c28", + "id": "999110e1", "metadata": {}, "source": [ "We pick 8 images to show:" @@ -1852,7 +1852,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3a1d22bd", + "id": "48932965", "metadata": {}, "outputs": [], "source": [ @@ -1862,7 +1862,7 @@ }, { "cell_type": "markdown", - "id": "29912374", + "id": "a88faa07", "metadata": {}, "source": [ "

    \n", @@ -1873,7 +1873,7 @@ }, { "cell_type": "markdown", - "id": "cf8ec03e", + "id": "c559a605", "metadata": { "tags": [ "solution" @@ -1887,7 +1887,7 @@ }, { "cell_type": "markdown", - "id": "bde4066d", + "id": "3419188a", "metadata": { "tags": [ "solution" @@ -1901,7 +1901,7 @@ }, { "cell_type": "markdown", - "id": "8a598bb3", + "id": "933c7ac9", "metadata": {}, "source": [ "### Apply trained model on 'wrong' data\n", @@ -1911,7 +1911,7 @@ }, { "cell_type": "markdown", - "id": "4b63fc64", + "id": "5b4369e0", "metadata": {}, "source": [ "### Load the Fashion MNIST dataset\n", @@ -1922,7 +1922,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d03b2297", + "id": "5e57d385", "metadata": {}, "outputs": [], "source": [ @@ -1943,7 +1943,7 @@ }, { "cell_type": "markdown", - "id": "31d01ee1", + "id": "b36c6e41", "metadata": {}, "source": [ "Next we apply the denoising model we trained on the MNIST data to FashionMNIST, and visualize the results." @@ -1952,7 +1952,7 @@ { "cell_type": "code", "execution_count": null, - "id": "aab3b99c", + "id": "6744e360", "metadata": {}, "outputs": [], "source": [ @@ -1962,7 +1962,7 @@ }, { "cell_type": "markdown", - "id": "e12f3a1d", + "id": "971da0c3", "metadata": {}, "source": [ "

    \n", @@ -1973,7 +1973,7 @@ }, { "cell_type": "markdown", - "id": "61bade0f", + "id": "bbc529ed", "metadata": { "tags": [ "solution" @@ -1987,7 +1987,7 @@ }, { "cell_type": "markdown", - "id": "f32a2e94", + "id": "13941a06", "metadata": { "tags": [ "solution" @@ -2001,7 +2001,7 @@ }, { "cell_type": "markdown", - "id": "3c296abe", + "id": "1df30b46", "metadata": {}, "source": [ "

    \n", @@ -2012,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "aa8db1dd", + "id": "43fc08eb", "metadata": { "tags": [ "solution" @@ -2026,7 +2026,7 @@ }, { "cell_type": "markdown", - "id": "697b36bf", + "id": "43e047c9", "metadata": { "tags": [ "solution" @@ -2041,7 +2041,7 @@ }, { "cell_type": "markdown", - "id": "749d2d87", + "id": "835030fd", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST\n", @@ -2052,7 +2052,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e52a2f68", + "id": "c7cc9bb3", "metadata": {}, "outputs": [], "source": [ @@ -2089,7 +2089,7 @@ { "cell_type": "code", "execution_count": null, - "id": "76324612", + "id": "46edff16", "metadata": {}, "outputs": [], "source": [ @@ -2100,7 +2100,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1544565a", + "id": "2dac72fa", "metadata": {}, "outputs": [], "source": [ @@ -2110,7 +2110,7 @@ }, { "cell_type": "markdown", - "id": "d2646697", + "id": "288c6764", "metadata": {}, "source": [ "

    \n", @@ -2121,7 +2121,7 @@ }, { "cell_type": "markdown", - "id": "9508a7c1", + "id": "433162e3", "metadata": { "lines_to_next_cell": 0, "tags": [ @@ -2139,7 +2139,7 @@ }, { "cell_type": "markdown", - "id": "4f02d520", + "id": "a9694e46", "metadata": {}, "source": [ "### Train the denoiser on both MNIST and FashionMNIST, shuffling the training data\n", @@ -2150,7 +2150,7 @@ { "cell_type": "code", "execution_count": null, - "id": "fb070c5c", + "id": "ae52c3d0", "metadata": {}, "outputs": [], "source": [ @@ -2187,7 +2187,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2cfefa77", + "id": "f71a710b", "metadata": {}, "outputs": [], "source": [ @@ -2198,7 +2198,7 @@ { "cell_type": "code", "execution_count": null, - "id": "56718c41", + "id": "52a67bf2", "metadata": {}, "outputs": [], "source": [ @@ -2208,7 +2208,7 @@ }, { "cell_type": "markdown", - "id": "df6234dd", + "id": "b8fe50cf", "metadata": {}, "source": [ "

    \n", @@ -2219,7 +2219,7 @@ }, { "cell_type": "markdown", - "id": "7e149cd8", + "id": "23c0b50d", "metadata": { "tags": [ "solution" @@ -2233,7 +2233,7 @@ }, { "cell_type": "markdown", - "id": "dbe9b728", + "id": "ec448985", "metadata": {}, "source": [ "\n", @@ -2247,7 +2247,7 @@ }, { "cell_type": "markdown", - "id": "b69ac817", + "id": "33838105", "metadata": {}, "source": [ "\n", @@ -2261,7 +2261,7 @@ }, { "cell_type": "markdown", - "id": "b682aed4", + "id": "eee21f1e", "metadata": {}, "source": [] }