CopyTask.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Copy\n",
    "\n",
    "In this task, a sequence of bit vectors is provided to the model. The input sequence starts with a reserved start vector, then some random binary bit vectors, followed by a reserved stop vector. The model is expected to start reproducing the exact input bit vectors immediately after observing the stop vector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from util import *\n",
    "from dnc_lstm import DNC\n",
    "from dnc_ff import DNCFF\n",
    "from autograd import grad\n",
    "from autograd.misc.optimizers import rmsprop, adam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84c1a9fa50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf9cfcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84c1a8f390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def seq(seq_len, seq_width):\n",
    "    \"\"\"\n",
    "    Implements the copy task - section 4.1 from the NTM paper.\n",
    "    Returns inputs, outputs, and a mask for loss calculation\n",
    "    \"\"\"\n",
    "    rand_tile = np.random.randint(2, size=(seq_len, seq_width))\n",
    "    inputs = np.zeros((seq_len*2+3, seq_width+2))\n",
    "    inputs[0,1] = 1\n",
    "    inputs[seq_len+1,0] = 1\n",
    "    inputs[1:seq_len+1, 2:] = rand_tile\n",
    "    targets = np.zeros((seq_len*2+3, seq_width+1))\n",
    "    targets[-1,0] = 1\n",
    "    targets[seq_len+2:-1, 1:] = rand_tile\n",
    "    mask = np.zeros((seq_len*2+3, seq_width+1))\n",
    "    mask[seq_len+2:,:] = 1\n",
    "    return inputs, targets, mask\n",
    "\n",
    "def long_copy(seq_len, seq_width, repeat=4):\n",
    "    inputs, targets, masks = [], [], []\n",
    "    for i in range(repeat):\n",
    "        inpt, tar, mask = seq(seq_len, seq_width)\n",
    "        inputs.append(inpt)\n",
    "        targets.append(tar)\n",
    "        masks.append(mask)\n",
    "    inputs = np.vstack(inputs)\n",
    "    targets = np.vstack(targets)\n",
    "    masks = np.ones_like(targets) # np.vstack(masks)\n",
    "    return inputs, targets, masks\n",
    "\n",
    "# print seq(4, 4)\n",
    "for item in long_copy(4,4):\n",
    "    display(item.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training DNC...\n",
      "('Iteration', 0, 'Train loss:', 0.69503228167640196)\n",
      "Test loss:  0.694567429618\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf3ff6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bee8b650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be7c6150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bebefb10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 1000, 'Train loss:', 0.20447556280155266)\n",
      "Test loss:  0.200185461653\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bfa08bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8504609a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdf71910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdf71f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 2000, 'Train loss:', 0.18558648981293202)\n",
      "Test loss:  0.190224545893\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beb22290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bde97610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAACPtJREFUeJzt3X+MXFUZxvHvw/Z3S6z0B5K2WlASU40WuhIJhBCMBpBaTTCixvAHgYSUBKJGQZMGTUxEIkjESBAQRAQVUBuCUZQmamKgXWihpSoF10BTaWulhWC73fb1j3sK47Bz78y6nXN7+3ySSe/cc2f36duZd2fPnN6riMDMzJrlmNwBzMxs4rm5m5k1kJu7mVkDubmbmTWQm7uZWQO5uZuZNZCbu5lZA7m5m5k1kJu7mVkDTcr1jefOnRuLFy/O9e2POENDQ6Xjy5Yt61OSZiirp2vZO9dz4lS91oGdETGv6iB1c/oBSecCNwEDwG0R8c228anAj4BlwL+AT0XEcNnXHBwcjLVr15Z9z8pcR5Oqehw8eHDcjz0aHXNM519aDxw4UPrYo7GeVX2irJ5lz004OutZpot6DEXEYNVBldMykgaA7wHnAUuAT0ta0nbYJcC/I+JdwI3AdVVf18zMDp9u5txPA7ZExPMRMQLcB6xoO2YFcFfavh/4kPzj2Mwsm26a+wLghZb7L6Z9Yx4TEaPAbmBO+xeSdJmkdZLW7dixY3yJzcysUl9Xy0TErRExGBGD8+ZVfh5gZmbj1E1z3wosarm/MO0b8xhJk4C3UHywamZmGXSzFHItcLKkEyma+EXAZ9qOWQ1cDPwZuBB4NLpYhlN2SK4p+6rYK1eu7Di2YEH7bNX/2rlzZ8exstUG0MwVB9dff33p+PDwcOn4yMhIx7GyWgOMjo52HDsSawlw6aWXlo4vWdK+DuINe/fuLX1s1bLlJq7WWr58eel42exD1YqrOXPeNGv9uqrXelWvOKSyuUfEqKQrgN9QLIW8IyI2Sfo6sC4iVgO3A3dL2gLsovgBYGZmmXT1n5gi4mHg4bZ9q1q29wKfnNhoZmY2Xj79gJlZA7m5m5k1kJu7mVkDubmbmTWQm7uZWQNlO+Xvkeq1117rOFa1/nT//v0dx2bMmDHuTE01c+bM0vGyteoDAwMTHaf2qp5/06ZN6zhWtc697LnbVFXPv9mzZ3cc271790TH6ZnfuZuZNZCbu5lZA7m5m5k1kJu7mVkDdXMlpkWS1kh6RtImSVeOcczZknZLWp9uq8b6WmZm1h/drJYZBb4QEU9IOhYYkvRIRDzTdtwfI+KCiY9oZma96uaskNuAbWn7FUmbKa681N7ce3Ykngp01qxZHcemT59e+tj58+d3HKs6zWcTlS0lA9izZ0/peNm/xa5du8aV6UhWtfxzypQp4xrrZryJqvrTpEmd22dVLyh77ETpac5d0mLgFOCxMYZPl7RB0q8lvafD432ZPTOzPui6uUuaBTwAXBUR7W+pngDeERHvB74L/HKsr+HL7JmZ9UdXzV3SZIrGfk9EPNg+HhF7IuLVtP0wMFnS3AlNamZmXetmtYworrS0OSJu6HDM29JxSDotfV1fQ9XMLJNuZvXPAD4HPC1pfdr3FeDtABFxC8V1Uy+XNAr8B7iom2uompnZ4dHNapk/AaUfG0fEzcDNExXKzMz+P/4fqmZmDZT1lL9lMzd1XQM/derUjmNV64zL/r5lp69tqrJaQvXa6pGRkY5jdX3+HE5l6/6hvJ5Vpws+GlWd8rfsFMr79u0rfWw/6u1/UTOzBnJzNzNrIDd3M7MGcnM3M2sgN3czswZyczczayA3dzOzBlKuswRI2gH8o2XXXGBnljDlnKs3ztUb5+qNcxVn4K08rW625t5O0rqIGMydo51z9ca5euNcvXGu7nlaxsysgdzczcwaqE7N/dbcATpwrt44V2+cqzfO1aXazLmbmdnEqdM7dzMzmyBu7mZmDVSL5i7pXEl/lbRF0tW58xwiaVjS05LWS1qXMccdkrZL2tiy7zhJj0h6Nv351prkulbS1lSz9ZLOz5BrkaQ1kp6RtEnSlWl/1pqV5MpaM0nTJD0uaUPK9bW0/0RJj6XX5U8llZ9gv3+57pT095Z6Le1nrpZ8A5KelPRQup+1Xm8SEVlvwADwHHASMAXYACzJnStlGwbm1iDHWcCpwMaWfd8Crk7bVwPX1STXtcAXM9frBODUtH0s8DdgSe6aleTKWjOKy2jOStuTgceADwI/o7geMsAtwOU1yXUncGHO51jK9HngJ8BD6X7WerXf6vDO/TRgS0Q8HxEjwH3AisyZaiUi/gDsatu9Argrbd8FfLyvoeiYK7uI2BYRT6TtV4DNwAIy16wkV1ZReDXdnZxuAZwD3J/256hXp1zZSVoIfBS4Ld0XmevVrg7NfQHwQsv9F6nBEz4J4LeShiRdljtMm+MjYlva/idwfM4wba6Q9FSatun7dFErSYuBUyje9dWmZm25IHPN0hTDemA78AjFb9MvR8Sh6z9meV2254qIQ/X6RqrXjZLKr9d4eHwH+BJwMN2fQw3q1aoOzb3OzoyIU4HzgJWSzsodaCxR/B5Yi3c0wPeBdwJLgW3At3MFkTQLeAC4KiL2tI7lrNkYubLXLCIORMRSYCHFb9Pv7neGsbTnkvRe4BqKfB8AjgO+3M9Mki4AtkfEUD+/b6/q0Ny3Aota7i9M+7KLiK3pz+3ALyie9HXxkqQTANKf2zPnASAiXkovyIPAD8hUM0mTKRroPRHxYNqdvWZj5apLzVKWl4E1wOnAbEmT0lDW12VLrnPT9FZExD7gh/S/XmcAH5M0TDGNfA5wEzWqF9Sjua8FTk6fNE8BLgJWZ86EpJmSjj20DXwE2Fj+qL5aDVycti8GfpUxy+sONc/kE2SoWZr/vB3YHBE3tAxlrVmnXLlrJmmepNlpezrwYYrPA9YAF6bDctRrrFx/afkBLYp57b7WKyKuiYiFEbGYol89GhGfJXO93iT3J87pk+XzKVYOPAd8NXeelOkkipU7G4BNOXMB91L8ur6fYi7vEoo5vt8DzwK/A46rSa67gaeBpyia6QkZcp1JMeXyFLA+3c7PXbOSXFlrBrwPeDJ9/43AqrT/JOBxYAvwc2BqTXI9muq1EfgxaUVNjhtwNm+slslar/abTz9gZtZAdZiWMTOzCebmbmbWQG7uZmYN5OZuZtZAbu5mZg3k5m5m1kBu7mZmDfRfj79JIJIIgtUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be363f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be2aafd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 3000, 'Train loss:', 0.16040424927080391)\n",
      "Test loss:  0.193053658604\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf90fd90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf2d4910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beec2490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB9FJREFUeJzt3X+o3XUdx/Hnq/0q2sjmHTa21XUlxIqa220kiohRzCWtYNEqYn8IgiQoFTULhgVBBmmSkZiayywrf9SQRa02qCCm986735XTFjqWm5lOobKb7/74flaHr+eeH+vsfL778HrA4X5/3XNevLnnfc/9fD/3+1VEYGZmZXlV7gBmZjZ4bu5mZgVyczczK5Cbu5lZgdzczcwK5OZuZlYgN3czswK5uZuZFcjN3cysQDNzvfDIyEiMjo7mevkzzsTERMf9K1euHFKSMnSqp2vZP9dzcLq914FnImJBt4PUy+UHJK0GbgZmALdHxFdq++cA3wVWAn8FPhIRhzs959jYWIyPj3d9batI6rjfl5HoT6d6upb9cz0Hp9t7HZiIiLFuB3UdlpE0A/gmcBmwDPiopGW1w64A/hYRbwFuAm7o9rxmZnb69DLmvgo4FBFPRMRLwL3A2toxa4HNafk+4D3q4dePmZmdHr0090XAky3rT6VtbY+JiCngeeDs+hNJulLSuKTx48ePn1piMzPraqizZSLitogYi4ixBQu6ng8wM7NT1EtzPwIsaVlfnLa1PUbSTOB1VCdWzcwsg16mQj4CnCfpXKomvh74WO2YLcAG4HfAOmB7FHqKPNesgBLLeTpPy3Srl+vZH9dzeLrVstdcXZt7RExJuhr4OdVUyDsjYr+kLwHjEbEFuAO4W9Ih4FmqXwBmZpZJT//EFBFbga21bZtalv8BfHiw0czM7FT58gNmZgVyczczK5Cbu5lZgdzczcwK5OZuZlagbJf8PVOVOJ/XzMrjT+5mZgVyczczK5Cbu5lZgdzczcwK1MudmJZI2iHpgKT9kq5pc8wlkp6XNJkem9o9l5mZDUcvs2WmgE9HxC5J84AJSdsi4kDtuN9ExOWDj2hmZv3q5aqQR4GjafkFSQep7rxUb+5mA+Vpp8PjWvev6TXra8xd0ihwPrCzze4LJO2W9DNJb5vm+32bPTOzIei5uUuaC9wPXBsRJ2q7dwFvioh3At8AftLuOXybPTOz4eipuUuaRdXY74mIB+r7I+JERLyYlrcCsySNDDSpmZn1rJfZMqK609LBiLhxmmPekI5D0qr0vL6HqplZJr3MlrkQ+ASwV9Jk2vZ54I0AEXEr1X1Tr5I0BfwdWF/qPVTNzM4EvcyW+S3Q8Y6sEXELcMugQpmZ2f/H/6FqZlYgX/LXGiudxpmWR/4Gx7XuX7eanapB1dqf3M3MCuTmbmZWIDd3M7MCubmbmRXIzd3MrEBu7mZmBXJzNzMrkHLNX5V0HPhzy6YR4JksYTpzrv44V3+cqz/OVV2Bt+tldbM19zpJ4xExljtHnXP1x7n641z9ca7eeVjGzKxAbu5mZgVqUnO/LXeAaThXf5yrP87VH+fqUWPG3M3MbHCa9MndzMwGxM3dzKxAjWjuklZL+oOkQ5I25s5zkqTDkvZKmpQ0njHHnZKOSdrXsm2+pG2SHktfX9+QXNdLOpJqNilpTYZcSyTtkHRA0n5J16TtWWvWIVfWmkl6taSHJe1Oub6Ytp8raWd6X/5Q0uyG5LpL0p9a6rV8mLla8s2Q9Kikh9J61nq9QkRkfQAzgMeBpcBsYDewLHeulO0wMNKAHBcDK4B9Ldu+CmxMyxuBGxqS63rgM5nrtRBYkZbnAX8EluWuWYdcWWtGdRvNuWl5FrATeDfwI6r7IQPcClzVkFx3Aety/oylTJ8Cvg88lNaz1qv+aMIn91XAoYh4IiJeAu4F1mbO1CgR8Wvg2drmtcDmtLwZ+OBQQzFtruwi4mhE7ErLLwAHgUVkrlmHXFlF5cW0Ois9ArgUuC9tz1Gv6XJlJ2kx8H7g9rQuMterrgnNfRHwZMv6UzTgBz4J4BeSJiRdmTtMzTkRcTQt/wU4J2eYmqsl7UnDNkMfLmolaRQ4n+pTX2NqVssFmWuWhhgmgWPANqq/pp+LiKl0SJb3ZT1XRJys15dTvW6SNGfYuYCvA58FXk7rZ9OAerVqQnNvsosiYgVwGfBJSRfnDtROVH8HNuITDfAt4M3AcuAo8LVcQSTNBe4Hro2IE637ctasTa7sNYuIf0fEcmAx1V/Tbx12hnbquSS9HbiOKt+7gPnA54aZSdLlwLGImBjm6/arCc39CLCkZX1x2pZdRBxJX48BD1L90DfF05IWAqSvxzLnASAink5vyJeBb5OpZpJmUTXQeyLigbQ5e83a5WpKzVKW54AdwAXAWZJmpl1Z35ctuVan4a2IiH8C32H49boQ+ICkw1TDyJcCN9OgekEzmvsjwHnpTPNsYD2wJXMmJL1W0ryTy8D7gH2dv2uotgAb0vIG4KcZs/zXyeaZfIgMNUvjn3cAByPixpZdWWs2Xa7cNZO0QNJZafk1wHupzgfsANalw3LUq12u37f8ghbVuPZQ6xUR10XE4ogYpepX2yPi42Su1yvkPuOcziyvoZo58Djwhdx5UqalVDN3dgP7c+YCfkD15/q/qMbyrqAa4/sV8BjwS2B+Q3LdDewF9lA104UZcl1ENeSyB5hMjzW5a9YhV9aaAe8AHk2vvw/YlLYvBR4GDgE/BuY0JNf2VK99wPdIM2pyPIBL+N9smaz1qj98+QEzswI1YVjGzMwGzM3dzKxAbu5mZgVyczczK5Cbu5lZgdzczcwK5OZuZlag/wB4zRri9T7EHAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be6eb390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 4000, 'Train loss:', 0.17752186217965138)\n",
      "Test loss:  0.182103858928\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8509b570d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf6d6bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be23c9d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be67e390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 5000, 'Train loss:', 0.14417570901875074)\n",
      "Test loss:  0.176557909388\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bfa11e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be23b110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be3fb690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB9hJREFUeJzt3X+o3XUdx/Hnq+1uRRvpvMPG7uq6FGJFze02EkXEKOaSVrBoFbE/BEESlIqaBcOCIIM0yUhMzWWWlVoNWdRqgwpieu+82+62yqstdCw3M51CZTff/fH9rA5fzz0/tnPP53u/ez3gcL+/7jkv3rvnfc/9fL/7fBURmJlZvbwmdwAzM+s9N3czsxpyczczqyE3dzOzGnJzNzOrITd3M7MacnM3M6shN3czsxpyczczq6G5uV54cHAwhoeHc738rDM2NtZy/+rVq/uUpB5a1dO17J7r2Tvt3uvAsxGxuN1B6mT6AUlrgVuBOcCdEfGV0v75wHeB1cDfgI9ExOFWzzkyMhKjo6NtX9sKklru9zQS3WlVT9eye65n77R7rwNjETHS7qC2wzKS5gDfBK4AVgAflbSidNhVwN8j4nzgFuCmds9rZmYzp5Mx9zXAZEQ8GREvA/cD60vHrAe2puUHgPeog18/ZmY2Mzpp7kuBpxrWn07bmh4TEVPAC8A55SeSdLWkUUmjx48fP7XEZmbWVl+vlomIOyJiJCJGFi9uez7AzMxOUSfN/QiwrGF9KG1reoykucAbKE6smplZBp1cCvkocIGk8yia+EbgY6VjtgGbgN8DG4CdcQaeIp/J0wxnYDlnVB3rmfOKKtezd9o9b6d9pm1zj4gpSdcCv6C4FPLuiDgg6UvAaERsA+4C7pU0CTxH8QvAzMwy6eg/MUXEdmB7aduWhuV/Ah/ubTQzMztVnn7AzKyG3NzNzGrIzd3MrIbc3M3MasjN3cyshrJN+Ttbecqc3vFMl73les0e/ZhF05/czcxqyM3dzKyG3NzNzGrIzd3MrIY6uRPTMkm7JB2UdEDSdU2OuUzSC5LG02NLs+cyM7P+6ORqmSng0xGxR9JCYEzSjog4WDrutxFxZe8jmplZtzqZFfIocDQtvyjpEMWdl8rN3cwy8qWls0c//i26GnOXNAxcCOxusvsiSXsl/VzS26b5ft9mz8ysDzpu7pIWAA8C10fEidLuPcCbI+KdwDeAnzZ7Dt9mz8ysPzpq7pIGKBr7fRHxUHl/RJyIiJfS8nZgQNJgT5OamVnHOrlaRhR3WjoUETdPc8wb03FIWpOe1/dQNTPLpJOrZS4GPgHslzSetn0eeBNARNxOcd/UayRNAf8ANp6J91A1M6uKTq6W+R3Q8jR8RNwG3NarUGZmdnr8P1TNzGrIU/7arHU60y971NBO10xN/+0pf83MbFpu7mZmNeTmbmZWQ27uZmY15OZuZlZDbu5mZjXk5m5mVkPKdb2vpOPAXxo2DQLPZgnTmnN1x7m641zdca5iBt620+pma+5lkkYjYiR3jjLn6o5zdce5uuNcnfOwjJlZDbm5m5nVUJWa+x25A0zDubrjXN1xru44V4cqM+ZuZma9U6VP7mZm1iNu7mZmNVSJ5i5praQ/SpqUtDl3npMkHZa0X9K4pNGMOe6WdEzSRMO2RZJ2SHo8fT27IrlulHQk1Wxc0roMuZZJ2iXpoKQDkq5L27PWrEWurDWT9FpJj0jam3J9MW0/T9Lu9L78oaR5Fcl1j6Q/N9RrZT9zNeSbI+kxSQ+n9az1epWIyPoA5gBPAMuBecBeYEXuXCnbYWCwAjkuBVYBEw3bvgpsTsubgZsqkutG4DOZ67UEWJWWFwJ/AlbkrlmLXFlrRnEbzQVpeQDYDbwb+BHF/ZABbgeuqUiue4ANOX/GUqZPAd8HHk7rWetVflThk/saYDIinoyIl4H7gfWZM1VKRPwGeK60eT2wNS1vBT7Y11BMmyu7iDgaEXvS8ovAIWApmWvWIldWUXgprQ6kRwCXAw+k7TnqNV2u7CQNAe8H7kzrInO9yqrQ3JcCTzWsP00FfuCTAH4paUzS1bnDlJwbEUfT8l+Bc3OGKblW0r40bNP34aJGkoaBCyk+9VWmZqVckLlmaYhhHDgG7KD4a/r5iJhKh2R5X5ZzRcTJen051esWSfP7nQv4OvBZ4JW0fg4VqFejKjT3KrskIlYBVwCflHRp7kDNRPF3YCU+0QDfAt4CrASOAl/LFUTSAuBB4PqIONG4L2fNmuTKXrOI+E9ErASGKP6afmu/MzRTziXp7cANFPneBSwCPtfPTJKuBI5FxFg/X7dbVWjuR4BlDetDaVt2EXEkfT0G/ITih74qnpG0BCB9PZY5DwAR8Ux6Q74CfJtMNZM0QNFA74uIh9Lm7DVrlqsqNUtZngd2ARcBZ0mam3ZlfV825FqbhrciIv4FfIf+1+ti4AOSDlMMI18O3EqF6gXVaO6PAhekM83zgI3AtsyZkPR6SQtPLgPvAyZaf1dfbQM2peVNwM8yZvmfk80z+RAZapbGP+8CDkXEzQ27stZsuly5ayZpsaSz0vLrgPdSnA/YBWxIh+WoV7Ncf2j4BS2Kce2+1isiboiIoYgYpuhXOyPi42Su16vkPuOcziyvo7hy4AngC7nzpEzLKa7c2QscyJkL+AHFn+v/phjLu4pijO/XwOPAr4BFFcl1L7Af2EfRTJdkyHUJxZDLPmA8PdblrlmLXFlrBrwDeCy9/gSwJW1fDjwCTAI/BuZXJNfOVK8J4HukK2pyPIDL+P/VMlnrVX54+gEzsxqqwrCMmZn1mJu7mVkNubmbmdWQm7uZWQ25uZuZ1ZCbu5lZDbm5m5nV0H8B2vgX64Si3FsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be4e7190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 6000, 'Train loss:', 0.11092541794146663)\n",
      "Test loss:  0.130007251907\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf090bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdf2d210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be5aa4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bebc4510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 7000, 'Train loss:', 0.14557318135991709)\n",
      "Test loss:  0.129975113026\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAABQCAYAAAA5pZ/mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB3BJREFUeJzt3V+IXHcZxvHvY0yq2EKNWUrIBreRggQpMTsGxVJUUNIoRqEXES96IQTEgiKiKYLUi4IK/umFKLHWFrXG/xhKQasNeNd21ibpplWb1pU2xO4GKdYba9rXi/NbO93Ozp7ZmTO/88s+Hxj2nLOze568u/PmzJl3zioiMDOzcrwmdwAzMxuOG7eZWWHcuM3MCuPGbWZWGDduM7PCuHGbmRXGjdvMrDBu3GZmhXHjNjMrzGub+Kbbtm2LmZmZJr71SObm5gZ+fnZ2dkJJLg2D6ulaDs/1HJ8SH+sLCwtcuHBBde6rOm95l7QfuB3YBNwREV8ZdP9OpxPdbrfO/idKGlwTv/1/OIPq6VoOz/UcnxIf651Oh263W6txr3mqRNIm4NvADcBu4GOSdo8W0czM1qvOOe59wNmIeCoiXgCOAQebjWVmZqup07h3AE/3rD+Ttr2CpMOSupK6S0tL48pnZmYrjG2qJCKORkQnIjpTU1Pj+rZmZrZCncZ9DtjZsz6dtpmZWQZ1GvfDwDWSrpa0BTgEHG82lpmZrWbNOe6IuCjpZuC3VOOAd0bEmUFfMzc318rRpjaOANXRxlrm3vd6tXlMzPUcnxJrOYxab8CJiPuA+xrOYmZmNfgt72ZmhXHjNjMrjBu3mVlh3LjNzArjxm1mVphGLus6OztLU1cHbOtoXJNG+XetNa41ihLrvVbmUepVYj1GlbOeG7EXLPMRt5lZYdy4zcwK48ZtZlYYN24zs8K4cZuZFcaN28ysMG7cZmaFaWSOexRNzh1fikat16B51434s7jU538nrcn3IGzkn5WPuM3MCuPGbWZWGDduM7PCuHGbmRXGjdvMrDBu3GZmhXHjNjMrTOvmuDfybOZ6+PrS4zXK7LDnjl9tlGtm+3rcq/MRt5lZYdy4zcwK48ZtZlYYN24zs8K4cZuZFcaN28ysMFnGAUcZ49nII0D9NDmC5vG2V/Pv33B82eBm1GrckhaA54EXgYsR0WkylJmZrW6YI+73RsSFxpKYmVktPsdtZlaYuo07gN9JmpN0uN8dJB2W1JXUXVpaGl9CMzN7hbqN+7qI2AvcAHxK0vUr7xARRyOiExGdqampsYY0M7OX1WrcEXEufVwEfg3sazKUmZmtbs3GLekNkq5YXgY+AMw3HczMzPpTjbnpXVRH2VBNodwTEbet8TVLwN/T6jagjdMozjW8tmZzruE413AmlevNEVHrPPOajXtUkrptnPt2ruG1NZtzDce5htPGXB4HNDMrjBu3mVlhJtG4j05gH+vhXMNrazbnGo5zDad1uRo/x21mZuPlUyVmZoVptHFL2i/pL5LOSjrS5L6GIWlB0qOSTkrqZsxxp6RFSfM927ZKul/SE+njG1uS61ZJ51LNTko6kCHXTkknJD0m6YykT6ftWWs2IFfWmkl6naSHJJ1Kub6ctl8t6cH0uPyppC0tyXWXpL/11GvPJHP15Nsk6RFJ96b1rPXqKyIauQGbgCeBXcAW4BSwu6n9DZltAdjWghzXA3uB+Z5tXwOOpOUjwFdbkutW4HOZ67Ud2JuWrwD+CuzOXbMBubLWDBBweVreDDwIvBP4GXAobf8u8MmW5LoLuDHn71jK9FngHuDetJ61Xv1uTR5x7wPORsRTEfECcAw42OD+ihMRfwT+uWLzQeDutHw38JGJhmLVXNlFxPmI+FNafh54HNhB5poNyJVVVP6dVjenWwDvA36Rtueo12q5spM0DXwQuCOti8z16qfJxr0DeLpn/Rla8MucrHm1w4yuiojzafkfwFU5w6xws6TT6VTKxE/h9JI0A7yd6mitNTVbkQsy1yw97T8JLAL3Uz0Lfi4iLqa7ZHlcrswVEcv1ui3V65uSLpt0LuBbwOeBl9L6m2hBvVbaqC9Ornm1wzaI6rlZK45EgO8AbwH2AOeBr+cKIuly4JfAZyLiX72fy1mzPrmy1ywiXoyIPcA01bPgt046Qz8rc0l6G3ALVb53AFuBL0wyk6QPAYsRMTfJ/a5Hk437HLCzZ306bcsu2n21w2clbQdIHxcz5wEgIp5ND7aXgO+RqWaSNlM1xx9HxK/S5uw165erLTVLWZ4DTgDvAq6UtPzXr7I+Lnty7U+nnCIi/gP8gMnX693Ah9OfajxGdYrkdlpUr2VNNu6HgWvSK7JbgEPA8Qb3V0sBVzs8DtyUlm8CfpMxy/8tN8bko2SoWTrf+H3g8Yj4Rs+nstZstVy5ayZpStKVafn1wPupzr+fAG5Md8tRr365/tzzn6+oziNPtF4RcUtETEfEDFW/eiAiPk7mevXV8KuzB6heYX8S+GLuV2JTpl1UEy6ngDM5cwE/oXoK/V+qc2efoDqn9gfgCeD3wNaW5Poh8ChwmqpRbs+Q6zqq0yCngZPpdiB3zQbkyloz4FrgkbT/eeBLafsu4CHgLPBz4LKW5Hog1Wse+BFp8iTHDXgPL0+VZK1Xv5vfOWlmVpiN+uKkmVmx3LjNzArjxm1mVhg3bjOzwrhxm5kVxo3bzKwwbtxmZoVx4zYzK8z/AEbaxWC6tA+2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf3238d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf2b3c10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beb78dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be7ae510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 8000, 'Train loss:', 0.10052498574417264)\n",
      "Test loss:  0.143378897624\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bfa5c610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be72cc90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be948b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf425dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 9000, 'Train loss:', 0.11996405182031056)\n",
      "Test loss:  0.138249116915\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf9b5bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf8f9bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be5c7c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be112850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 10000, 'Train loss:', 0.10403950256251225)\n",
      "Test loss:  0.0979447278123\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf090bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be981810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be6a4510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be3e0b50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 11000, 'Train loss:', 0.10559546127582657)\n",
      "Test loss:  0.0856181423907\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf3245d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB/JJREFUeJzt3X+o3XUdx/Hnq+1uRRvZvMPG7uq6EmJFze02EkXEKOaSVrBoFbE/BEESlIqaBcOCIIM0yUhMzWWWlVoNWdRqgwpieu+8+105baHj5mamU6hs+e6P72d1ODv3/Ng9O5+vH18PONzvr3vO677vOe97zvf7ud+vIgIzMyvLq3IHMDOz/nNzNzMrkJu7mVmB3NzNzArk5m5mViA3dzOzArm5m5kVyM3dzKxAbu5mZgWaneuBh4eHY3R0NNfDv+xMTEy0Xb9y5coBJSlDu3q6lr1zPfun02sdeDoiFnbaSN2cfkDSauBmYBZwe0R8pWn9XOC7wErgb8BHIuJwu/scGxuL8fHxjo9tFUlt1/s0Er1pV0/XsneuZ/90eq0DExEx1mmjjrtlJM0CvglcBiwDPippWdNmVwB/j4i3ADcBN3S6XzMzO3O62ee+CjgUEY9HxIvAvcDapm3WApvT9H3Ae9TFnx8zMzszumnui4EnGuafTMtabhMRJ4DngLOb70jSlZLGJY0fO3bs9BKbmVlHAx0tExG3RcRYRIwtXNjxeICZmZ2mbpr7EWBJw/xIWtZyG0mzgddRHVg1M7MMuhkK+TBwnqRzqZr4euBjTdtsATYAvwfWAduj0EPkuQ4llFjOnCOAXM/+KrGeMzGT30WnWnbbgzo294g4Ielq4BdUQyHvjIj9kr4EjEfEFuAO4G5Jh4BnqP4AmJlZJl39E1NEbAW2Ni3b1DD9T+DD/Y1mZmany6cfMDMrkJu7mVmB3NzNzArk5m5mViA3dzOzAmU75W+JZjI+1eOE7Uw7k/+jUeLzN9dY9X7V0u/czcwK5OZuZlYgN3czswK5uZuZFaibKzEtkbRD0gFJ+yVd02KbSyQ9J2ky3Ta1ui8zMxuMbkbLnAA+HRG7JM0HJiRti4gDTdv9NiIu739EMzPrVTdnhZwCptL085IOUl15qbm5vyKUOOSrRL6g+Kna/cyuV+9mMrR0EPXsaZ+7pFHgfGBni9UXSNot6eeS3jbN9/sye2ZmA9B1c5c0D7gfuDYijjet3gW8KSLeCXwD+Gmr+/Bl9szMBqOr5i5piKqx3xMRDzSvj4jjEfFCmt4KDEka7mtSMzPrWjejZUR1paWDEXHjNNu8IW2HpFXpfn0NVTOzTLoZLXMh8Algr6TJtOzzwBsBIuJWquumXiXpBPAPYH2p11A1M3s56Ga0zO+AtoeFI+IW4JZ+hTIzs5nxf6iamRXIp/ztI48V7s1M6+FTKA/OK/G5PZOfqVO9fMpfMzM7LW7uZmYFcnM3MyuQm7uZWYHc3M3MCuTmbmZWIDd3M7MCKdf4VEnHgL80LBoGns4Spj3n6o1z9ca5euNc1Rl4O55WN1tzbyZpPCLGcudo5ly9ca7eOFdvnKt73i1jZlYgN3czswLVqbnfljvANJyrN87VG+fqjXN1qTb73M3MrH/q9M7dzMz6xM3dzKxAtWjuklZL+qOkQ5I25s5zkqTDkvZKmpQ0njHHnZKOStrXsGyBpG2SHk1fX1+TXNdLOpJqNilpTYZcSyTtkHRA0n5J16TlWWvWJlfWmkl6taSHJO1Oub6Ylp8raWd6Xf5Q0pya5LpL0p8b6rV8kLka8s2S9IikB9N81nqdIiKy3oBZwGPAUmAOsBtYljtXynYYGK5BjouBFcC+hmVfBTam6Y3ADTXJdT3wmcz1WgSsSNPzgT8By3LXrE2urDWjuozmvDQ9BOwE3g38iOp6yAC3AlfVJNddwLqcz7GU6VPA94EH03zWejXf6vDOfRVwKCIej4gXgXuBtZkz1UpE/AZ4pmnxWmBzmt4MfHCgoZg2V3YRMRURu9L088BBYDGZa9YmV1ZReSHNDqVbAJcC96XlOeo1Xa7sJI0A7wduT/Mic72a1aG5LwaeaJh/kho84ZMAfilpQtKVucM0OSciptL0X4FzcoZpcrWkPWm3zcB3FzWSNAqcT/WurzY1a8oFmWuWdjFMAkeBbVSfpp+NiBNpkyyvy+ZcEXGyXl9O9bpJ0txB5wK+DnwWeCnNn00N6tWoDs29zi6KiBXAZcAnJV2cO1ArUX0OrMU7GuBbwJuB5cAU8LVcQSTNA+4Hro2I443rctasRa7sNYuI/0TEcmCE6tP0WwedoZXmXJLeDlxHle9dwALgc4PMJOly4GhETAzycXtVh+Z+BFjSMD+SlmUXEUfS16PAT6ie9HXxlKRFAOnr0cx5AIiIp9IL8iXg22SqmaQhqgZ6T0Q8kBZnr1mrXHWpWcryLLADuAA4S9LstCrr67Ih1+q0eysi4l/Adxh8vS4EPiDpMNVu5EuBm6lRvaAezf1h4Lx0pHkOsB7YkjkTkl4raf7JaeB9wL723zVQW4ANaXoD8LOMWf7nZPNMPkSGmqX9n3cAByPixoZVWWs2Xa7cNZO0UNJZafo1wHupjgfsANalzXLUq1WuPzT8gRbVfu2B1isirouIkYgYpepX2yPi42Su1ylyH3FOR5bXUI0ceAz4Qu48KdNSqpE7u4H9OXMBP6D6uP5vqn15V1Dt4/s18CjwK2BBTXLdDewF9lA100UZcl1EtctlDzCZbmty16xNrqw1A94BPJIefx+wKS1fCjwEHAJ+DMytSa7tqV77gO+RRtTkuAGX8P/RMlnr1Xzz6QfMzApUh90yZmbWZ27uZmYFcnM3MyuQm7uZWYHc3M3MCuTmbmZWIDd3M7MC/RcYmDjfGM/QswAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beec2490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be8ae710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf8f9bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 12000, 'Train loss:', 0.069732620396053643)\n",
      "Test loss:  0.0737735605445\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bedceb10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bee85490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be4e93d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be0f2390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 13000, 'Train loss:', 0.066272415557329975)\n",
      "Test loss:  0.0815225803656\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf090bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf6d6490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be27d2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf324150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 14000, 'Train loss:', 0.062694513964887705)\n",
      "Test loss:  0.0755212599197\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8504609a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be2ba550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be3278d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84becf48d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 15000, 'Train loss:', 0.050168430672524134)\n",
      "Test loss:  0.0389464332453\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf56b090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bee83750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be0accd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf41c150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 16000, 'Train loss:', 0.086057955441826595)\n",
      "Test loss:  0.0244324111134\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf324150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bde9b2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be0cc510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be900350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 17000, 'Train loss:', 0.053465910442757739)\n",
      "Test loss:  0.0161677333003\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf3238d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84befa31d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84befe33d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf41be50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 18000, 'Train loss:', 0.022383144886887821)\n",
      "Test loss:  0.0151489134439\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf9b5bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf2b3d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be244110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdf9f950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 19000, 'Train loss:', 0.0046921082402188339)\n",
      "Test loss:  0.00701083138029\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf919250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be46d7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf037f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be5eb4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 20000, 'Train loss:', 0.0018783159200929374)\n",
      "Test loss:  0.00209154667423\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf037790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be9ddb50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be705d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bef7f950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 21000, 'Train loss:', 0.00048287279118242298)\n",
      "Test loss:  0.000998385477596\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bedceb10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdebbc90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be4a1690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB/BJREFUeJzt3X+o3XUdx/Hnq+1uRRvpvMPG7uq6FGJFze02EkXEKOaSVrBoFbE/BEESlIqaBcOCIIM0yUhMzWWWlVoNWdRqgwpieu+82+62yqstdNy8M9MpVLZ898f3szp9d+75sXt2Pt++ez3gcL+/7jkv3tzzvud+vp/7/SoiMDOzenlV7gBmZtZ7bu5mZjXk5m5mVkNu7mZmNeTmbmZWQ27uZmY15OZuZlZDbu5mZjXk5m5mVkNzc73w4OBgDA8P53r5/ztjY2Mt969evbpPSeqhVT1dy+65nr3T7r0OPBsRi9sdpE4uPyBpLXArMAe4MyK+VNo/H/g2sBr4C/ChiDjc6jlHRkZidHS07WtbQVLL/b6MRHda1dO17J7r2Tvt3uvAWESMtDuo7bCMpDnA14ErgBXAhyWtKB12FfDXiDgfuAW4qd3zmpnZ6dPJmPsaYDIinoyIl4H7gfWlY9YDW9PyA8C71MGvHzMzOz06ae5Lgaca1p9O25oeExHHgReAc8pPJOlqSaOSRo8ePXpqic3MrK2+zpaJiDsiYiQiRhYvbns+wMzMTlEnzf0IsKxhfShta3qMpLnA6yhOrJqZWQadTIV8FLhA0nkUTXwj8JHSMduATcBvgQ3AzvAp8pPMZkaBy9lbdaznbGZUzXY2Vh3r2c7pOq3Yrpadvm7b5h4RxyVdC/yMYirk3RFxQNIXgNGI2AbcBdwraRJ4juIXgJmZZdLRPzFFxHZge2nbloblvwMf7G00MzM7Vb78gJlZDbm5m5nVkJu7mVkNubmbmdWQm7uZWQ1lu+Sv2em80qWvonkyX+6pOvrx8+dP7mZmNeTmbmZWQ27uZmY15OZuZlZDndyJaZmkXZIOSjog6bomx1wm6QVJ4+mxpdlzmZlZf3QyW+Y48MmI2CNpITAmaUdEHCwd9+uIuLL3Ec3MrFudXBVyCphKyy9KOkRx56Vycz/j5bzk6pnIU/v+1+mcOnomyjVVt1fv9a7G3CUNAxcCu5vsvkjSXkk/lfSWGb7ft9kzM+uDjpu7pAXAg8D1EXGstHsP8MaIeDvwNeDHzZ7Dt9kzM+uPjpq7pAGKxn5fRDxU3h8RxyLipbS8HRiQNNjTpGZm1rFOZsuI4k5LhyLi5hmOeX06Dklr0vP6HqpmZpl0MlvmYuBjwH5J42nbZ4E3AETE7RT3Tb1G0nHgb8BG30PVzCyfTmbL/AZoedo4Im4DbutVKDMzmx3/h6qZWQ35kr89NJuRKI9i9ZbrebJ+zK2uk3Y1qfr/BviTu5lZDbm5m5nVkJu7mVkNubmbmdWQm7uZWQ25uZuZ1ZCbu5lZDSnX/FZJR4E/NWwaBJ7NEqY15+qOc3XHubrjXMUVeNteVjdbcy+TNBoRI7lzlDlXd5yrO87VHefqnIdlzMxqyM3dzKyGqtTc78gdYAbO1R3n6o5zdce5OlSZMXczM+udKn1yNzOzHnFzNzOroUo0d0lrJf1e0qSkzbnznCDpsKT9ksYljWbMcbekaUkTDdsWSdoh6fH09eyK5LpR0pFUs3FJ6zLkWiZpl6SDkg5Iui5tz1qzFrmy1kzSqyU9ImlvyvX5tP08SbvT+/L7kuZVJNc9kv7YUK+V/czVkG+OpMckPZzWs9brJBGR9QHMAZ4AlgPzgL3Aity5UrbDwGAFclwKrAImGrZ9GdicljcDN1Uk143ApzLXawmwKi0vBP4ArMhdsxa5staM4jaaC9LyALAbeCfwA4r7IQPcDlxTkVz3ABty/oylTJ8Avgs8nNaz1qv8qMIn9zXAZEQ8GREvA/cD6zNnqpSI+BXwXGnzemBrWt4KvL+voZgxV3YRMRURe9Lyi8AhYCmZa9YiV1ZReCmtDqRHAJcDD6TtOeo1U67sJA0B7wXuTOsic73KqtDclwJPNaw/TQV+4JMAfi5pTNLVucOUnBsRU2n5z8C5OcOUXCtpXxq26ftwUSNJw8CFFJ/6KlOzUi7IXLM0xDAOTAM7KP6afj4ijqdDsrwvy7ki4kS9vpjqdYuk+f3OBXwV+DTwSlo/hwrUq1EVmnuVXRIRq4ArgI9LujR3oGai+DuwEp9ogG8AbwJWAlPAV3IFkbQAeBC4PiKONe7LWbMmubLXLCL+FRErgSGKv6bf3O8MzZRzSXorcANFvncAi4DP9DOTpCuB6YgY6+frdqsKzf0IsKxhfShtyy4ijqSv08CPKH7oq+IZSUsA0tfpzHkAiIhn0hvyFeCbZKqZpAGKBnpfRDyUNmevWbNcValZyvI8sAu4CDhL0ty0K+v7siHX2jS8FRHxD+Bb9L9eFwPvk3SYYhj5cuBWKlQvqEZzfxS4IJ1pngdsBLZlzoSk10paeGIZeA8w0fq7+mobsCktbwJ+kjHLf5xonskHyFCzNP55F3AoIm5u2JW1ZjPlyl0zSYslnZWWXwO8m+J8wC5gQzosR72a5fpdwy9oUYxr97VeEXFDRAxFxDBFv9oZER8lc71OkvuMczqzvI5i5sATwOdy50mZllPM3NkLHMiZC/gexZ/r/6QYy7uKYozvl8DjwC+ARRXJdS+wH9hH0UyXZMh1CcWQyz5gPD3W5a5Zi1xZawa8DXgsvf4EsCVtXw48AkwCPwTmVyTXzlSvCeA7pBk1OR7AZfx3tkzWepUfvvyAmVkNVWFYxszMeszN3cyshtzczcxqyM3dzKyG3NzNzGrIzd3MrIbc3M3MaujfMcks6O2quG4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be19b0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 22000, 'Train loss:', 0.00094048433725986273)\n",
      "Test loss:  0.000602215834154\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf919250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf6d6650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAACDNJREFUeJzt3X+o3XUdx/Hna3d3K7aRzTtsbKurJcSKmtttJIqIUcwlrWDRKmJ/CIIkKBU1C4YFQQZpkpGYmsssK3/UkEWtNqggpvfOu9+V0xY6lpuZTkflbnv3x/ezOpyd+z3n7J6dz9fvXg843O+ve85rb855n3M/57PvVxGBmZnVy7TcAczMrPfc3M3MasjN3cyshtzczcxqyM3dzKyG3NzNzGrIzd3MrIbc3M3MasjN3cyshqbneuChoaEYHh7O9fCvOWNjY6X7ly1b1qck9VBWT9eye65n77R7rQPPR8S8dgepk9MPSFoB3AYMAHdFxNea9s8Evg8sA/4OfCwiDpTd58jISIyOjrZ9bCtIKt3v00h0p6yermX3XM/eafdaB8YiYqTdQW2HZSQNAN8GrgQWAx+XtLjpsKuBf0TE24BbgZvb3a+ZmZ05nYy5Lwf2R8TTEfEq8ACwqumYVcCGtPwg8D518PZjZmZnRifNfQHwTMP6s2lby2MiYgJ4CTi3+Y4kXSNpVNLokSNHTi+xmZm11dfZMhFxZ0SMRMTIvHltvw8wM7PT1ElzPwgsalhfmLa1PEbSdOANFF+smplZBp1MhXwcuFDS+RRNfA3wiaZjNgJrgT8Aq4EtcRZ+RT5tWvl7ZVlJ2pWrjuWc6tcyU6lJHevZTtnz88SJE6W/69lapxocHJx03/Hjx0/7ftvVstPXTdvmHhETkq4DfkkxFfKeiNgj6SvAaERsBO4G7pO0H3iB4g3AzMwy6eg/MUXEJmBT07b1Dcv/Aj7a22hmZna6fPoBM7MacnM3M6shN3czsxpyczczqyE3dzOzGsp2yt86ajdXuIznEffW9OnlT+2JiYk+JamOsufnwMBAH5PUQ9lc9iq8nv3J3cyshtzczcxqyM3dzKyG3NzNzGqokysxLZK0VdJeSXskXd/imMslvSRpPN3Wt7ovMzPrj05my0wAn42I7ZLmAGOSNkfE3qbjfhcRV/U+opmZdauTs0IeAg6l5Zcl7aO48lJzc7c2fOXB/jkbpzq2M5WLWM+aNavXcV7zplLPqZx+uVNdjblLGgYuAra12H2xpB2SfiHpHZP8vi+zZ2bWBx03d0mzgYeAGyLiaNPu7cBbIuLdwLeAn7W6D19mz8ysPzpq7pIGKRr7/RHxcPP+iDgaEa+k5U3AoKShniY1M7OOdTJbRhRXWtoXEbdMcsyb0nFIWp7u19dQNTPLpJPZMpcAnwJ2SRpP274IvBkgIu6guG7qtZImgH8Ca87Ga6iamVVFJ7Nlfg+UTvOIiNuB23sVyszMpsb/Q9XMrIZ8yt8uTWVua5mzcRTrTP6bq3DK1To5duxY7giVU/YcanfKaZ/y18zMToubu5lZDbm5m5nVkJu7mVkNubmbmdWQm7uZWQ25uZuZ1ZByzfeVdAT4a8OmIeD5LGHKOVd3nKs7ztUd5yrOwNv2tLrZmnszSaMRMZI7RzPn6o5zdce5uuNcnfOwjJlZDbm5m5nVUJWa+525A0zCubrjXN1xru44V4cqM+ZuZma9U6VP7mZm1iNu7mZmNVSJ5i5phaQ/SdovaV3uPCdJOiBpl6RxSaMZc9wj6bCk3Q3b5kraLOnJ9PONFcl1k6SDqWbjklZmyLVI0lZJeyXtkXR92p61ZiW5stZM0uskPSZpR8r15bT9fEnb0uvyx5JmVCTXvZL+0lCvJf3M1ZBvQNITkh5N61nrdYqIyHoDBoCngAuAGcAOYHHuXCnbAWCoAjkuA5YCuxu2fR1Yl5bXATdXJNdNwOcy12s+sDQtzwH+DCzOXbOSXFlrRnEZzdlpeRDYBrwX+AnF9ZAB7gCurUiue4HVOZ9jKdNngB8Cj6b1rPVqvlXhk/tyYH9EPB0RrwIPAKsyZ6qUiPgt8ELT5lXAhrS8AfhwX0Mxaa7sIuJQRGxPyy8D+4AFZK5ZSa6sovBKWh1MtwCuAB5M23PUa7Jc2UlaCHwQuCuti8z1alaF5r4AeKZh/Vkq8IRPAviVpDFJ1+QO0+S8iDiUlv8GnJczTJPrJO1MwzZ9Hy5qJGkYuIjiU19lataUCzLXLA0xjAOHgc0Uf02/GBET6ZAsr8vmXBFxsl5fTfW6VdLMfucCvgl8HjiR1s+lAvVqVIXmXmWXRsRS4Erg05Iuyx2olSj+DqzEJxrgO8BbgSXAIeAbuYJImg08BNwQEUcb9+WsWYtc2WsWEf+JiCXAQoq/pt/e7wytNOeS9E7gRop87wHmAl/oZyZJVwGHI2Ksn4/brSo094PAoob1hWlbdhFxMP08DDxC8aSviuckzQdIPw9nzgNARDyXXpAngO+SqWaSBika6P0R8XDanL1mrXJVpWYpy4vAVuBi4BxJJ6/0nPV12ZBrRRreioj4N/A9+l+vS4APSTpAMYx8BXAbFaoXVKO5Pw5cmL5pngGsATZmzoSkWZLmnFwGPgDsLv+tvtoIrE3La4GfZ8zyPyebZ/IRMtQsjX/eDeyLiFsadmWt2WS5ctdM0jxJ56Tl1wPvp/g+YCuwOh2Wo16tcv2x4Q1aFOPafa1XRNwYEQsjYpiiX22JiE+SuV6nyP2Nc/pmeSXFzIGngC/lzpMyXUAxc2cHsCdnLuBHFH+uH6cYy7uaYozvN8CTwK+BuRXJdR+wC9hJ0UznZ8h1KcWQy05gPN1W5q5ZSa6sNQPeBTyRHn83sD5tvwB4DNgP/BSYWZFcW1K9dgM/IM2oyXEDLuf/s2Wy1qv55tMPmJnVUBWGZczMrMfc3M3MasjN3cyshtzczcxqyM3dzKyG3NzNzGrIzd3MrIb+C8IrPtN4sXlHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be03a1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf428810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 23000, 'Train loss:', 8.8263015313110648e-05)\n",
      "Test loss:  0.000131177881181\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84c1a8f550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be4292d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf32ea50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be42f450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 24000, 'Train loss:', 0.00015255513164378902)\n",
      "Test loss:  0.000129075379753\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf950410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB+1JREFUeJzt3X+o3XUdx/Hnq+1uRRvpvMPG7uq6FGJFze02EkXEKOaSVrBoFbE/BEESlIqaBcOCIIM0yUhMzWWWlVoNWdRqgwpieu+82+62yqstdCzvzHQKld1898f3szp8Pff82D07n+++ez3gcL+/7jmvvXfO+57z/X7O96uIwMzM6uU1uQOYmVnvubmbmdWQm7uZWQ25uZuZ1ZCbu5lZDbm5m5nVkJu7mVkNubmbmdWQm7uZWQ3NzfXAg4ODMTw8nOvhTztjY2Mt169evbpPSeqhVT1dy+65nr3T7rUOPBsRi9ttpE5OPyBpLXArMAe4MyK+Ulo/H/gusBr4G/CRiDjc6j5HRkZidHS07WNbQVLL9T6NRHda1dO17J7r2TvtXuvAWESMtNuo7W4ZSXOAbwJXACuAj0paUdrsKuDvEXE+cAtwU7v7NTOzU6eTfe5rgMmIeDIiXgbuB9aXtlkPbE3TDwDvUQd/fszM7NTopLkvBZ5qmH86LWu6TURMAy8A55TvSNLVkkYljR47duzkEpuZWVt9HS0TEXdExEhEjCxe3PZ4gJmZnaROmvsRYFnD/FBa1nQbSXOBN1AcWDUzsww6GQr5KHCBpPMomvhG4GOlbbYBm4DfAxuAnVHTQ+SzOZTQqiQeDdNbZ2I9T+Vhrnb1OhPrear+ze3ut9P/57bNPSKmJV0L/IJiKOTdEXFA0peA0YjYBtwF3CtpEniO4g+AmZll0tGXmCJiO7C9tGxLw/Q/gQ/3NpqZmZ0sn37AzKyG3NzNzGrIzd3MrIbc3M3MasjN3cyshrKd8vd0lWtsax3NdhyxT1/Undl8z+JM/N7AbFShXn7nbmZWQ27uZmY15OZuZlZDbu5mZjXUyZWYlknaJemgpAOSrmuyzWWSXpA0nm5bmt2XmZn1RyejZaaBT0fEHkkLgTFJOyLiYGm730bElb2PaGZm3erkrJBHgaNp+kVJhyiuvFRu7maW0WyGjnooY/10tc9d0jBwIbC7yeqLJO2V9HNJb5vh932ZPTOzPui4uUtaADwIXB8Rx0ur9wBvjoh3At8AftrsPnyZPTOz/uiouUsaoGjs90XEQ+X1EXE8Il5K09uBAUmDPU1qZmYd62S0jCiutHQoIm6eYZs3pu2QtCbdr6+hamaWSSejZS4GPgHslzSeln0eeBNARNxOcd3UayRNA/8ANtb1GqpmZqeDTkbL/A5oeRaciLgNuK1XoczMbHb8DVUzsxryKX8rogqnCK0an9K3f2Zb6zPx+Vl1fuduZlZDbu5mZjXk5m5mVkNu7mZmNeTmbmZWQ27uZmY15OZuZlZDyjU+VdIx4C8NiwaBZ7OEac25uuNc3XGu7jhXcQbetqfVzdbcyySNRsRI7hxlztUd5+qOc3XHuTrn3TJmZjXk5m5mVkNVau535A4wA+fqjnN1x7m641wdqsw+dzMz650qvXM3M7MecXM3M6uhSjR3SWsl/VHSpKTNufOcIOmwpP2SxiWNZsxxt6QpSRMNyxZJ2iHp8fTz7IrkulHSkVSzcUnrMuRaJmmXpIOSDki6Li3PWrMWubLWTNJrJT0iaW/K9cW0/DxJu9Pr8oeS5lUk1z2S/txQr5X9zNWQb46kxyQ9nOaz1utVIiLrDZgDPAEsB+YBe4EVuXOlbIeBwQrkuBRYBUw0LPsqsDlNbwZuqkiuG4HPZK7XEmBVml4I/AlYkbtmLXJlrRnFZTQXpOkBYDfwbuBHFNdDBrgduKYiue4BNuR8jqVMnwK+Dzyc5rPWq3yrwjv3NcBkRDwZES8D9wPrM2eqlIj4DfBcafF6YGua3gp8sK+hmDFXdhFxNCL2pOkXgUPAUjLXrEWurKLwUpodSLcALgceSMtz1GumXNlJGgLeD9yZ5kXmepVVobkvBZ5qmH+aCjzhkwB+KWlM0tW5w5ScGxFH0/RfgXNzhim5VtK+tNum77uLGkkaBi6keNdXmZqVckHmmqVdDOPAFLCD4tP08xExnTbJ8ros54qIE/X6cqrXLZLm9zsX8HXgs8Araf4cKlCvRlVo7lV2SUSsAq4APinp0tyBmonic2Al3tEA3wLeAqwEjgJfyxVE0gLgQeD6iDjeuC5nzZrkyl6ziPhPRKwEhig+Tb+13xmaKeeS9HbgBop87wIWAZ/rZyZJVwJTETHWz8ftVhWa+xFgWcP8UFqWXUQcST+ngJ9QPOmr4hlJSwDSz6nMeQCIiGfSC/IV4NtkqpmkAYoGel9EPJQWZ69Zs1xVqVnK8jywC7gIOEvS3LQq6+uyIdfatHsrIuJfwHfof70uBj4g6TDFbuTLgVupUL2gGs39UeCCdKR5HrAR2JY5E5JeL2nhiWngfcBE69/qq23ApjS9CfhZxiz/c6J5Jh8iQ83S/s+7gEMRcXPDqqw1mylX7ppJWizprDT9OuC9FMcDdgEb0mY56tUs1x8a/kCLYr92X+sVETdExFBEDFP0q50R8XEy1+tVch9xTkeW11GMHHgC+ELuPCnTcoqRO3uBAzlzAT+g+Lj+b4p9eVdR7OP7NfA48CtgUUVy3QvsB/ZRNNMlGXJdQrHLZR8wnm7rctesRa6sNQPeATyWHn8C2JKWLwceASaBHwPzK5JrZ6rXBPA90oiaHDfgMv4/WiZrvco3n37AzKyGqrBbxszMeszN3cyshtzczcxqyM3dzKyG3NzNzGrIzd3MrIbc3M3Maui/SuAj7pjoqLUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf41bb90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be467450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beb75b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 25000, 'Train loss:', 6.5967315210683808e-05)\n",
      "Test loss:  6.29166109358e-05\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84c1a8f550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be82d190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be4c5d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf2b3550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 26000, 'Train loss:', 3.6827546092938995e-05)\n",
      "Test loss:  6.82096027567e-05\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf090bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be47f4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be1b04d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be7b9b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 27000, 'Train loss:', 1.2918744256982638e-05)\n",
      "Test loss:  1.77243605277e-05\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf1531d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be56df90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beec25d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf400150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 28000, 'Train loss:', 6.6593330006635175e-06)\n",
      "Test loss:  9.44151063918e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf32ea50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be10a8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be0a1fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be1389d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 29000, 'Train loss:', 2.6060735464989976e-06)\n",
      "Test loss:  8.9897315418e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf9b5bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84beb53790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf6f2950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdfdfd90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 30000, 'Train loss:', 1.0908505965737594e-05)\n",
      "Test loss:  4.10975439528e-05\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bfa08bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdfd7cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bde3a0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84befa5690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 31000, 'Train loss:', 2.8042850044549844e-06)\n",
      "Test loss:  9.840787786e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf9b5bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be26ff90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bde520d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf129650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 32000, 'Train loss:', 3.6665245328339632e-06)\n",
      "Test loss:  6.80431375536e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf8f9bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be1a58d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be57a1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB/RJREFUeJzt3W2IXGcZxvH/ZbKJYoI13VBDNrqNFiSKpskaLC2lVJQ0FqMQMSqSD4VCsdCioqlCqIJgBVuLFUtta2OtVm2rhhLRaAIqSNrddPOudlsjbVi7qbVNC2qNvf1wnuhwMjsv2dl5Tk6uHwx73mbm2ntn7p0959lzFBGYmVm9vCp3ADMz6z03dzOzGnJzNzOrITd3M7MacnM3M6shN3czsxpyczczqyE3dzOzGnJzNzOrobm5nnhwcDCGh4dzPf0ZZ2xsrOX61atX9ylJPbSqp2vZPdezd9q914FnI2Jxu43UyekHJK0FbgXmAHdGxFdK6+cD3wVWA38DPhIRR1o95sjISIyOjrZ9bitIarnep5HoTqt6upbdcz17p917HRiLiJF2G7XdLSNpDvBN4ApgBfBRSStKm10F/D0i3gLcAtzU7nHNzGz2dLLPfQ0wERFPRsTLwP3A+tI264GtafoB4D3q4NePmZnNjk6a+1LgqYb5p9OypttExAngBeDc8gNJulrSqKTRY8eOnV5iMzNrq6+jZSLijogYiYiRxYvbHg8wM7PT1ElzPwosa5gfSsuabiNpLvA6igOrZmaWQSdDIR8FLpB0PkUT3wh8rLTNNmAT8HtgA7AzanqIfCaHElqVxKNhTjVbte5k/ZloNut1Nr4+Z/I9z+S+M/1ZnNS2uUfECUnXAr+gGAp5d0QclPQlYDQitgF3AfdKmgCeo/gFYGZmmXT0T0wRsR3YXlq2pWH6n8CHexvNzMxOl08/YGZWQ27uZmY15OZuZlZDbu5mZjXk5m5mVkPZTvl7NvLpdiynOo5Fn029Gm/e7X179XPyJ3czsxpyczczqyE3dzOzGnJzNzOroU6uxLRM0i5JhyQdlHRdk20uk/SCpPF029LssczMrD86GS1zAvh0ROyRtBAYk7QjIg6VtvttRFzZ+4hmZtatTs4KOQlMpukXJR2muPJSubmf9TzUrLdmUs+z8RS1dfyeqmw2X5+90NU+d0nDwIXA7iarL5K0V9LPJb1tmvv7MntmZn3QcXOXtAB4ELg+Io6XVu8B3hQR7wS+Afy02WP4MntmZv3RUXOXNEDR2O+LiIfK6yPieES8lKa3AwOSBnua1MzMOtbJaBlRXGnpcETcPM02b0jbIWlNelxfQ9XMLJNORstcDHwC2C9pPC37PPBGgIi4neK6qddIOgH8A9hY12uompmdCToZLfM7oOWh3Yi4DbitV6HMzGxm/B+qZmY15FP+9tDZOLZ6Jlyv3vIppaujCq9tf3I3M6shN3czsxpyczczqyE3dzOzGnJzNzOrITd3M7MacnM3M6sh5RpLLOkY8JeGRYPAs1nCtOZc3XGu7jhXd5yrOANv29PqZmvuZZJGI2Ikd44y5+qOc3XHubrjXJ3zbhkzsxpyczczq6EqNfc7cgeYhnN1x7m641zdca4OVWafu5mZ9U6VPrmbmVmPuLmbmdVQJZq7pLWS/ihpQtLm3HlOknRE0n5J45JGM+a4W9KUpAMNyxZJ2iHp8fT19RXJdaOko6lm45LWZci1TNIuSYckHZR0XVqetWYtcmWtmaRXS3pE0t6U64tp+fmSdqf35Q8lzatIrnsk/bmhXiv7mash3xxJj0l6OM1nrdcpIiLrDZgDPAEsB+YBe4EVuXOlbEeAwQrkuBRYBRxoWPZVYHOa3gzcVJFcNwKfyVyvJcCqNL0Q+BOwInfNWuTKWjOKy2guSNMDwG7g3cCPKK6HDHA7cE1Fct0DbMj5GkuZPgV8H3g4zWetV/lWhU/ua4CJiHgyIl4G7gfWZ85UKRHxG+C50uL1wNY0vRX4YF9DMW2u7CJiMiL2pOkXgcPAUjLXrEWurKLwUpodSLcALgceSMtz1Gu6XNlJGgLeD9yZ5kXmepVVobkvBZ5qmH+aCrzgkwB+KWlM0tW5w5ScFxGTafqvwHk5w5RcK2lf2m3T991FjSQNAxdSfOqrTM1KuSBzzdIuhnFgCthB8df08xFxIm2S5X1ZzhURJ+v15VSvWyTN73cu4OvAZ4FX0vy5VKBejarQ3KvskohYBVwBfFLSpbkDNRPF34GV+EQDfAt4M7ASmAS+liuIpAXAg8D1EXG8cV3OmjXJlb1mEfGfiFgJDFH8Nf3WfmdoppxL0tuBGyjyvQtYBHyun5kkXQlMRcRYP5+3W1Vo7keBZQ3zQ2lZdhFxNH2dAn5C8aKvimckLQFIX6cy5wEgIp5Jb8hXgG+TqWaSBiga6H0R8VBanL1mzXJVpWYpy/PALuAi4BxJc9OqrO/Lhlxr0+6tiIh/Ad+h//W6GPiApCMUu5EvB26lQvWCajT3R4EL0pHmecBGYFvmTEh6raSFJ6eB9wEHWt+rr7YBm9L0JuBnGbP8z8nmmXyIDDVL+z/vAg5HxM0Nq7LWbLpcuWsmabGkc9L0a4D3UhwP2AVsSJvlqFezXH9o+AUtiv3afa1XRNwQEUMRMUzRr3ZGxMfJXK9T5D7inI4sr6MYOfAE8IXceVKm5RQjd/YCB3PmAn5A8ef6vyn25V1FsY/v18DjwK+ARRXJdS+wH9hH0UyXZMh1CcUul33AeLqty12zFrmy1gx4B/BYev4DwJa0fDnwCDAB/BiYX5FcO1O9DgDfI42oyXEDLuP/o2Wy1qt88+kHzMxqqAq7ZczMrMfc3M3MasjN3cyshtzczcxqyM3dzKyG3NzNzGrIzd3MrIb+C4hHLOu9vuVeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be18c9d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 33000, 'Train loss:', 1.7890252060145159e-06)\n",
      "Test loss:  2.4769043043e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAABQCAYAAAA5pZ/mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB3VJREFUeJzt3V+IXGcdxvHvY0yq2EKNu5SQDW4jBQlSYnYMiqWooKRRjEIvIl70QgiIhYqIpghSLwqt4J9eiBJrbVFr/I+hFLTagHdtZ22Sbtpq07rShtjdIMV6Y0378+K8a6fb2fmTmTPveXefDwx7zpnZPc/+MueXM++8c1YRgZmZleMNuQOYmdlw3LjNzArjxm1mVhg3bjOzwrhxm5kVxo3bzKwwbtxmZoVx4zYzK4wbt5lZYd5Yxw+dmpqK2dnZOn70SObn53vePzc3N6Ek60OverqWw3M9x6fEY31xcZHz589rkMdqkI+8S9oH3AFsAu6MiNt6Pb7VakW73R5k/xMl9a6JP/4/nF71dC2H53qOT4nHeqvVot1uD9S4+w6VSNoEfAe4DtgFfErSrtEimpnZxRpkjHsvcCYinomIl4CjwIF6Y5mZ2VoGadzbgWc71p9L215D0iFJbUnt5eXlceUzM7NVxjarJCKOREQrIlrT09Pj+rFmZrbKII37LLCjY30mbTMzswwGadyPAFdJulLSFuAgcKzeWGZmtpa+87gj4oKkG4HfUU0HvCsiTvf6nvn5+UZObWriFKBBNLGWufd9sZo8Tcz1HJ8SazmMgT6AExH3A/fXnMXMzAbgj7ybmRXGjdvMrDBu3GZmhXHjNjMrjBu3mVlharms69zcHL2uDtjU6W1NNUpN+k3Xqmu/TTXq7zRKPfspsd79Mo9yrDd1qmET+IzbzKwwbtxmZoVx4zYzK4wbt5lZYdy4zcwK48ZtZlYYN24zs8LUMo+7H89LHp9R5xWvx5rk4lq+nmtSD59xm5kVxo3bzKwwbtxmZoVx4zYzK4wbt5lZYdy4zcwK48ZtZlaYLPO467qm8UacM7oRf+c6jfLc9Jz616vz+uUbmc+4zcwK48ZtZlYYN24zs8K4cZuZFcaN28ysMG7cZmaFWVeXde039Wg9Trfqp87pWOuxnv1+p171XI/1qNMote53/3r/txiocUtaBF4EXgYuRESrzlBmZra2Yc64PxgR52tLYmZmA/EYt5lZYQZt3AH8XtK8pEPdHiDpkKS2pPby8vL4EpqZ2WsM2riviYg9wHXA5yRdu/oBEXEkIloR0Zqenh5rSDMze9VAjTsizqavS8BvgL11hjIzs7X1bdyS3iLpspVl4CPAQt3BzMysOw0wl3In1Vk2VLNQ7o2IW/t8zzLw97Q6BTRxNopzDa+p2ZxrOM41nEnlentEDDTO3Ldxj0pSu4nzvp1reE3N5lzDca7hNDGXpwOamRXGjdvMrDCTaNxHJrCPi+Fcw2tqNucajnMNp3G5ah/jNjOz8fJQiZlZYWpt3JL2SfqLpDOSDte5r2FIWpT0mKQTktoZc9wlaUnSQse2rZIekPRU+vrWhuS6RdLZVLMTkvZnyLVD0nFJj0s6LemmtD1rzXrkylozSW+S9LCkkynX19L2KyU9lI7Ln0na0pBcd0v6W0e9dk8yV0e+TZIelXRfWs9ar64iopYbsAl4GtgJbAFOArvq2t+Q2RaBqQbkuBbYAyx0bPs6cDgtHwZub0iuW4AvZq7XNmBPWr4M+CuwK3fNeuTKWjNAwKVpeTPwEPBe4OfAwbT9e8BnG5LrbuD6nM+xlOkLwL3AfWk9a7263eo8494LnImIZyLiJeAocKDG/RUnIv4E/HPV5gPAPWn5HuATEw3Fmrmyi4hzEfHntPwi8ASwncw165Erq6j8O61uTrcAPgT8Mm3PUa+1cmUnaQb4KHBnWheZ69VNnY17O/Bsx/pzNODJnPS92mFGV0TEubT8D+CKnGFWuVHSqTSUMvEhnE6SZoF3U52tNaZmq3JB5pqll/0ngCXgAapXwS9ExIX0kCzH5epcEbFSr1tTvb4l6ZJJ5wK+DXwJeCWtv40G1Gu1jfrmZN+rHTZBVK/NGnEmAnwXeAewGzgHfCNXEEmXAr8CPh8R/+q8L2fNuuTKXrOIeDkidgMzVK+C3znpDN2sziXpXcDNVPneA2wFvjzJTJI+BixFxPwk93sx6mzcZ4EdHeszaVt20eyrHT4vaRtA+rqUOQ8AEfF8OtheAb5PpppJ2kzVHH8SEb9Om7PXrFuuptQsZXkBOA68D7hc0spfv8p6XHbk2peGnCIi/gP8kMnX6/3Ax9OfajxKNURyBw2q14o6G/cjwFXpHdktwEHgWI37G0gBVzs8BtyQlm8Afpsxy/+tNMbkk2SoWRpv/AHwRER8s+OurDVbK1fumkmalnR5Wn4z8GGq8ffjwPXpYTnq1S3Xkx3/+YpqHHmi9YqImyNiJiJmqfrVgxHxaTLXq6ua353dT/UO+9PAV3K/E5sy7aSa4XISOJ0zF/BTqpfQ/6UaO/sM1ZjaH4GngD8AWxuS60fAY8Apqka5LUOua6iGQU4BJ9Jtf+6a9ciVtWbA1cCjaf8LwFfT9p3Aw8AZ4BfAJQ3J9WCq1wLwY9LMkxw34AO8Oqska7263fzJSTOzwmzUNyfNzIrlxm1mVhg3bjOzwrhxm5kVxo3bzKwwbtxmZoVx4zYzK4wbt5lZYf4Hw8S8YPkghtsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf0900d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf941a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be963b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdf9d910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 34000, 'Train loss:', 5.254897544995045e-06)\n",
      "Test loss:  8.77572552988e-07\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8509b570d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be791a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be11f610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB/1JREFUeJzt3X+o3XUdx/Hnq/0q2sjmHTa21XUlxIqa220kiohRzCWtYNEqYn8IgiQoFTULhgVBBmmSkZiayywrtRqyqNUGFcT03nm33W2VV1voWN6Z6RQqW7774/tZHc/OPT927z2f7z6+HnC43+/3fO85r713zvue+/l+7veriMDMzMryqtwBzMxs+rm5m5kVyM3dzKxAbu5mZgVyczczK5Cbu5lZgdzczcwK5OZuZlYgN3czswLNzvXEAwMDMTg4mOvpzzgjIyNt71+9enWfkpShXT1dy965ntOn03sdeDoiFnXaSd2cfkDSWuBmYBZwe0R8pen+ecB3gdXA34CPRMThdo85NDQUw8PDHZ/bKpLa3u/TSPSmXT1dy965ntOn03sdGImIoU47dRyWkTQL+CZwGbAC+KikFU27XQH8PSLeAtwE3NDpcc3MbOZ0M+a+BhiPiMcj4kXgXmB90z7rga1p+T7gPerix4+Zmc2Mbpr7EuCJhvUn07aW+0TECeA54OzmB5J0paRhScPHjh07vcRmZtZRX2fLRMRtETEUEUOLFnU8HmBmZqepm+Z+BFjWsL40bWu5j6TZwOuoDqyamVkG3UyFfBg4T9K5VE18I/Cxpn22AZuA3wMbgJ1R6CHymTqU0KlcJZZzJmcAeXbRqWbyMFiJ9ZzKa2gq39uplt3+P3Zs7hFxQtLVwC+opkLeGREHJH0JGI6IbcAdwN2SxoFnqH4AmJlZJl39EVNEbAe2N23b0rD8T+DD0xvNzMxOl08/YGZWIDd3M7MCubmbmRXIzd3MrEBu7mZmBcp2yt8z1VTmttrLzeTc6BLnXef0SqznTP6b+3EWTX9yNzMrkJu7mVmB3NzNzArk5m5mVqBursS0TNIuSQclHZB0TYt9LpH0nKTRdNvS6rHMzKw/upktcwL4dETskbQAGJG0IyIONu3324i4fPojmplZr7o5K+RR4Ghafl7SIaorLzU3d7OeTPW0vFOZevpKnNrXzlRrXWI9z/R/c09j7pIGgfOB3S3uvkDSXkk/l/S2Sb7fl9kzM+uDrpu7pPnA/cC1EXG86e49wJsi4p3AN4CftnoMX2bPzKw/umrukuZQNfZ7IuKB5vsj4nhEvJCWtwNzJA1Ma1IzM+taN7NlRHWlpUMRceMk+7wh7YekNelxfQ1VM7NMupktcyHwCWC/pNG07fPAGwEi4laq66ZeJekE8A9gY6nXUDUzOxN0M1vmd0Dbw8YRcQtwy3SFMjOzqfFfqJqZFcin/O0jj1S93EzOrfbpl22qzvT3qz+5m5kVyM3dzKxAbu5mZgVyczczK5Cbu5lZgdzczcwK5OZuZlYg5ZrLKekY8JeGTQPA01nCtOdcvXGu3jhXb5yrOgNvx9PqZmvuzSQNR8RQ7hzNnKs3ztUb5+qNc3XPwzJmZgVyczczK1CdmvttuQNMwrl641y9ca7eOFeXajPmbmZm06dOn9zNzGyauLmbmRWoFs1d0lpJf5Q0Lmlz7jwnSTosab+kUUnDGXPcKWlC0ljDtoWSdkh6NH19fU1yXS/pSKrZqKR1GXItk7RL0kFJByRdk7ZnrVmbXFlrJunVkh6StDfl+mLafq6k3el9+UNJc2uS6y5Jf26o18p+5mrIN0vSI5IeTOtZ63WKiMh6A2YBjwHLgbnAXmBF7lwp22FgoAY5LgZWAWMN274KbE7Lm4EbapLreuAzmeu1GFiVlhcAfwJW5K5Zm1xZa0Z1Gc35aXkOsBt4N/AjqushA9wKXFWTXHcBG3K+xlKmTwHfBx5M61nr1Xyrwyf3NcB4RDweES8C9wLrM2eqlYj4DfBM0+b1wNa0vBX4YF9DMWmu7CLiaETsScvPA4eAJWSuWZtcWUXlhbQ6J90CuBS4L23PUa/JcmUnaSnwfuD2tC4y16tZHZr7EuCJhvUnqcELPgngl5JGJF2ZO0yTcyLiaFr+K3BOzjBNrpa0Lw3b9H24qJGkQeB8qk99talZUy7IXLM0xDAKTAA7qH6bfjYiTqRdsrwvm3NFxMl6fTnV6yZJ8/qdC/g68FngpbR+NjWoV6M6NPc6uygiVgGXAZ+UdHHuQK1E9XtgLT7RAN8C3gysBI4CX8sVRNJ84H7g2og43nhfzpq1yJW9ZhHxn4hYCSyl+m36rf3O0EpzLklvB66jyvcuYCHwuX5mknQ5MBERI/183l7VobkfAZY1rC9N27KLiCPp6wTwE6oXfV08JWkxQPo6kTkPABHxVHpDvgR8m0w1kzSHqoHeExEPpM3Za9YqV11qlrI8C+wCLgDOkjQ73ZX1fdmQa20a3oqI+BfwHfpfrwuBD0g6TDWMfClwMzWqF9SjuT8MnJeONM8FNgLbMmdC0mslLTi5DLwPGGv/XX21DdiUljcBP8uY5X9ONs/kQ2SoWRr/vAM4FBE3NtyVtWaT5cpdM0mLJJ2Vll8DvJfqeMAuYEPaLUe9WuX6Q8MPaFGNa/e1XhFxXUQsjYhBqn61MyI+TuZ6nSL3Eed0ZHkd1cyBx4Av5M6TMi2nmrmzFziQMxfwA6pf1/9NNZZ3BdUY36+BR4FfAQtrkutuYD+wj6qZLs6Q6yKqIZd9wGi6rctdsza5stYMeAfwSHr+MWBL2r4ceAgYB34MzKtJrp2pXmPA90gzanLcgEv4/2yZrPVqvvn0A2ZmBarDsIyZmU0zN3czswK5uZuZFcjN3cysQG7uZmYFcnM3MyuQm7uZWYH+C4grNdzw3JEwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf0593d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 35000, 'Train loss:', 7.4899145793856002e-07)\n",
      "Test loss:  7.33481845092e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf323450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be231250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf323450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAABICAYAAAANm7UyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB+hJREFUeJzt3X+o3XUdx/Hnq+1uRRvpvMPG7uq6FGJFze02EkXEKOaSVrBoFbE/BEESlIqaBcOCIIM0yUhMzWWWlVoNWdRqgwpieu+8+115tYWO5Z2ZTqGy5bs/vp/V6btzz4/dc8/n2/e+HnC4318757U397zvuZ/v536/igjMzKxeXpU7gJmZ9Z6bu5lZDbm5m5nVkJu7mVkNubmbmdWQm7uZWQ25uZuZ1ZCbu5lZDbm5m5nV0NxcLzw4OBjDw8O5Xv7/ztjYWMv9q1ev7lOSemhVT9eye65n77R7rwPPRsTidgepk8sPSFoL3ArMAe6MiC+V9s8Hvg2sBv4CfCgijrR6zpGRkRgdHW372laQ1HK/LyPRnVb1dC2753r2Trv3OjAWESPtDmo7LCNpDvB14ApgBfBhSStKh10F/DUizgduAW5q97xmZjZzOhlzXwNMRMSTEfEycD+wvnTMemBrWn4AeJc6+PFjZmYzo5PmvhR4qmH96bSt6TERcRJ4ATin/ESSrpY0Kmn0+PHjZ5bYzMza6utsmYi4IyJGImJk8eK25wPMzOwMddLcjwLLGtaH0ramx0iaC7yO4sSqmZll0MlUyEeBCySdR9HENwIfKR2zDdgE/BbYAOyMWXiKfDozWjwbpnvTmaHhev6v6X7/uZ69066WnZ7ObNvcI+KkpGuBn1FMhbw7Ig5K+gIwGhHbgLuAeyVNAM9R/AAwM7NMOvojpojYDmwvbdvSsPx34IO9jWZmZmfKlx8wM6shN3czsxpyczczqyE3dzOzGnJzNzOroWyX/J2NfLmd7rheVlf9uIqmP7mbmdWQm7uZWQ25uZuZ1ZCbu5lZDXVyJ6ZlknZJOiTpoKTrmhxzmaQXJI2nx5Zmz2VmZv3RyWyZk8AnI2KPpIXAmKQdEXGodNyvI+LK3kc0M7NudXJVyGPAsbT8oqTDFHdeKjd3s56azqVPZ+MllGfy/zwb69nOdKbq9qNeXY25SxoGLgR2N9l9kaS9kn4q6S1T/HvfZs/MrA86bu6SFgAPAtdHxInS7j3AGyPi7cDXgB83ew7fZs/MrD86au6SBiga+30R8VB5f0SciIiX0vJ2YEDSYE+TmplZxzqZLSOKOy0djoibpzjm9ek4JK1Jz+t7qJqZZdLJbJmLgY8B+yWNp22fBd4AEBG3U9w39RpJJ4G/ARtn4z1UzcyqopPZMr8BWp4WjojbgNt6FcrMzKbHf6FqZlZDvuSvZTOTc6dn46jgdP4uwE43k/PYfclfMzM7I27uZmY15OZuZlZDbu5mZjXk5m5mVkNu7mZmNeTmbmZWQ8o1H1jSceBPDZsGgWezhGnNubrjXN1xru44V3EF3raX1c3W3MskjUbESO4cZc7VHefqjnN1x7k652EZM7MacnM3M6uhKjX3O3IHmIJzdce5uuNc3XGuDlVmzN3MzHqnSp/czcysR9zczcxqqBLNXdJaSb+XNCFpc+48p0g6Imm/pHFJoxlz3C1pUtKBhm2LJO2Q9Hj6enZFct0o6Wiq2bikdRlyLZO0S9IhSQclXZe2Z61Zi1xZaybp1ZIekbQ35fp82n6epN3pffl9SfMqkuseSX9sqNfKfuZqyDdH0mOSHk7rWet1mojI+gDmAE8Ay4F5wF5gRe5cKdsRYLACOS4FVgEHGrZ9GdicljcDN1Uk143ApzLXawmwKi0vBP4ArMhdsxa5staM4jaaC9LyALAbeCfwA4r7IQPcDlxTkVz3ABtyfo+lTJ8Avgs8nNaz1qv8qMIn9zXAREQ8GREvA/cD6zNnqpSI+BXwXGnzemBrWt4KvL+voZgyV3YRcSwi9qTlF4HDwFIy16xFrqyi8FJaHUiPAC4HHkjbc9RrqlzZSRoC3gvcmdZF5nqVVaG5LwWealh/mgp8wycB/FzSmKSrc4cpOTcijqXlPwPn5gxTcq2kfWnYpu/DRY0kDQMXUnzqq0zNSrkgc83SEMM4MAnsoPht+vmIOJkOyfK+LOeKiFP1+mKq1y2S5vc7F/BV4NPAK2n9HCpQr0ZVaO5VdklErAKuAD4u6dLcgZqJ4vfASnyiAb4BvAlYCRwDvpIriKQFwIPA9RFxonFfzpo1yZW9ZhHxr4hYCQxR/Db95n5naKacS9JbgRso8r0DWAR8pp+ZJF0JTEbEWD9ft1tVaO5HgWUN60NpW3YRcTR9nQR+RPFNXxXPSFoCkL5OZs4DQEQ8k96QrwDfJFPNJA1QNND7IuKhtDl7zZrlqkrNUpbngV3ARcBZkuamXVnflw251qbhrYiIfwDfov/1uhh4n6QjFMPIlwO3UqF6QTWa+6PABelM8zxgI7AtcyYkvVbSwlPLwHuAA63/VV9tAzal5U3ATzJm+Y9TzTP5ABlqlsY/7wIOR8TNDbuy1myqXLlrJmmxpLPS8muAd1OcD9gFbEiH5ahXs1y/a/gBLYpx7b7WKyJuiIihiBim6Fc7I+KjZK7XaXKfcU5nltdRzBx4Avhc7jwp03KKmTt7gYM5cwHfo/h1/Z8UY3lXUYzx/RJ4HPgFsKgiue4F9gP7KJrpkgy5LqEYctkHjKfHutw1a5Era82AtwGPpdc/AGxJ25cDjwATwA+B+RXJtTPV6wDwHdKMmhwP4DL+O1sma73KD19+wMyshqowLGNmZj3m5m5mVkNu7mZmNeTmbmZWQ27uZmY15OZuZlZDbu5mZjX0b7ZEJvE+kXexAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be22b210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Iteration', 36000, 'Train loss:', 5.5867157310606901e-07)\n",
      "Test loss:  2.20816537399e-06\n",
      "Input\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAABQCAYAAAA5pZ/mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAB1ZJREFUeJzt3V+IXGcdxvHvY0yq2EKNu5SQDW4jBQmlxOwYFEtRQUmjGIVeRHrRCyFQWlBENEWQelGogn96IUqstUWt8T+GUtBqA961nbVJurFq07rShtjdIMV6Y5v258V5107X2dkzu3PmPW/2+cCw55yZnfPsjz2/PfPOO2cVEZiZWTnekDuAmZkNx43bzKwwbtxmZoVx4zYzK4wbt5lZYdy4zcwK48ZtZlYYN24zs8K4cZuZFeaNTTzpxMRETE9PN/HU6zI7Ozvw/pmZmTEluTgMqqdrOTzXc3RKPNbn5+c5f/686jxWdT7yLmkfcBewCbg7Iu4c9PhOpxPdbrfO/sdKGlwTf/x/OIPq6VoOz/UcnRKP9U6nQ7fbrdW4Vx0qkbQJ+BZwPbAL+KSkXeuLaGZma1VnjHsvcCYinomIl4CjwIFmY5mZ2UrqNO7twLM968+lba8j6ZCkrqTu4uLiqPKZmdkyI5tVEhFHIqITEZ3JyclRPa2ZmS1Tp3GfBXb0rE+lbWZmlkGdxv0YcJWkKyVtAQ4Cx5qNZWZmK1l1HndEXJB0K/AbqumA90TE6UHfMzs728qpTW2cAlRHG2uZe99r1eZpYq7n6JRYy2HU+gBORDwIPNhwFjMzq8EfeTczK4wbt5lZYdy4zcwK48ZtZlYYN24zs8I0clnXmZkZ1np1wNWmFw1ysU4BavLn2mj1Xi3zRqvHeq2nnhuxXqPiM24zs8K4cZuZFcaN28ysMG7cZmaFceM2MyuMG7eZWWHcuM3MCtPIPG67OHie7f8bVJO2XuI0p/X8zJ5TvzKfcZuZFcaN28ysMG7cZmaFceM2MyuMG7eZWWHcuM3MCuPGbWZWmOLmcXse7XBcE7OLj8+4zcwK48ZtZlYYN24zs8K4cZuZFcaN28ysMG7cZmaFyTIdcNAUtfVMT9uIU9vWO93Pl84cnfXW2vW0umo1bknzwIvAK8CFiOg0GcrMzFY2zBn3ByLifGNJzMysFo9xm5kVpm7jDuC3kmYlHer3AEmHJHUldRcXF0eX0MzMXqdu4742IvYA1wO3SLpu+QMi4khEdCKiMzk5OdKQZmb2mlqNOyLOpq8LwK+AvU2GMjOzla3auCW9RdJlS8vAh4G5poOZmVl/qjH3dCfVWTZUs1Duj4g7VvmeReDvaXUCaONsFOcaXluzOddwnGs448r19oioNc68auNeL0ndNs77dq7htTWbcw3HuYbTxlyeDmhmVhg3bjOzwoyjcR8Zwz7WwrmG19ZszjUc5xpO63I1PsZtZmaj5aESM7PCNNq4Je2T9BdJZyQdbnJfw5A0L+kJSSckdTPmuEfSgqS5nm1bJT0k6an09a0tyXW7pLOpZick7c+Qa4ek45L+JOm0pE+n7VlrNiBX1ppJepOkRyWdTLm+nLZfKemRdFz+RNKWluS6V9Lfeuq1e5y5evJtkvS4pAfSetZ69RURjdyATcDTwE5gC3AS2NXU/obMNg9MtCDHdcAeYK5n21eBw2n5MPCVluS6Hfhc5nptA/ak5cuAvwK7ctdsQK6sNQMEXJqWNwOPAO8BfgocTNu/A9zcklz3Ajfk/B1LmT4L3A88kNaz1qvfrckz7r3AmYh4JiJeAo4CBxrcX3Ei4g/AP5dtPgDcl5bvAz4+1lCsmCu7iDgXEX9Myy8CTwLbyVyzAbmyisq/0+rmdAvgg8DP0/Yc9VopV3aSpoCPAHendZG5Xv002bi3A8/2rD9HC36Zk1WvdpjRFRFxLi3/A7giZ5hlbpV0Kg2ljH0Ip5ekaeBdVGdrranZslyQuWbpZf8JYAF4iOpV8AsRcSE9JMtxuTxXRCzV645Ur29IumTcuYBvAp8HXk3rb6MF9Vpuo745uerVDtsgqtdmrTgTAb4NvAPYDZwDvpYriKRLgV8An4mIf/Xel7NmfXJlr1lEvBIRu4EpqlfB7xx3hn6W55J0NXAbVb53A1uBL4wzk6SPAgsRMTvO/a5Fk437LLCjZ30qbcsu2n21w+clbQNIXxcy5wEgIp5PB9urwHfJVDNJm6ma448i4pdpc/aa9cvVlpqlLC8Ax4H3ApdLWvrvV1mPy55c+9KQU0TEf4DvM/56vQ/4WPpXjUephkjuokX1WtJk434MuCq9I7sFOAgca3B/tRRwtcNjwE1p+Sbg1xmz/M9SY0w+QYaapfHG7wFPRsTXe+7KWrOVcuWumaRJSZen5TcDH6Iafz8O3JAelqNe/XL9ueePr6jGkcdar4i4LSKmImKaql89HBE3krlefTX87ux+qnfYnwa+mPud2JRpJ9UMl5PA6Zy5gB9TvYR+mWrs7FNUY2q/B54CfgdsbUmuHwBPAKeoGuW2DLmupRoGOQWcSLf9uWs2IFfWmgHXAI+n/c8BX0rbdwKPAmeAnwGXtCTXw6lec8APSTNPctyA9/ParJKs9ep38ycnzcwKs1HfnDQzK5Ybt5lZYdy4zcwK48ZtZlYYN24zs8K4cZuZFcaN28ysMG7cZmaF+S8xh7ZXcv04MwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bf950410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be0fe3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84be4ef4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f84bdfc5a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Testing recurrent DNC\n",
    "\n",
    "def loss_fn(pred, target, mask):\n",
    "    pred = sigmoid(pred)\n",
    "    one = np.ones_like(pred)\n",
    "    epsilon = 1.e-20 # to prevent log(0)\n",
    "    a = target * np.log(pred + epsilon)\n",
    "    b = (one - target) * np.log(one - pred + epsilon)\n",
    "    return np.mean(- (a + b) * mask)\n",
    "\n",
    "seq_len, seq_wid = 4, 4\n",
    "\n",
    "# dnc = DNCFF(input_size=seq_wid+2, output_size=seq_wid+1, hidden_size=32, R=2, N=64, W=4)\n",
    "dnc = DNC(input_size=seq_wid+2, output_size=seq_wid+1, hidden_size=32, R=2, N=64, W=8)\n",
    "dnc_params = dnc._init_params()\n",
    "\n",
    "def print_training_prediction(params, iters):\n",
    "    \n",
    "    inputs, targets, mask = long_copy(seq_len, seq_wid)\n",
    "    result = []\n",
    "    dnc = DNC(input_size=seq_wid+2, output_size=seq_wid+1, hidden_size=32, R=2, N=64, W=8)\n",
    "    for t in range(inputs.shape[0]):\n",
    "        out = dnc.step_forward(params, inputs[np.newaxis, t])\n",
    "        result.append(out)\n",
    "    result = np.concatenate(result, axis=0)\n",
    "    loss = loss_fn(result, targets, mask)\n",
    "    print \"Test loss: \", loss\n",
    "    print \"Input\"\n",
    "    display(inputs.T)\n",
    "    print \"Target\"\n",
    "    display(targets.T)\n",
    "    print \"Predicted\"\n",
    "    display((sigmoid(result)).T)\n",
    "    display(np.around((sigmoid(result) * mask), decimals=0).astype('int').T)\n",
    "    \n",
    "    # Saving Model Check Points\n",
    "    save_pickle(params, './ckpt/copy/Iter_%d_Loss_%.6f.pkl' % (iters, loss))\n",
    "\n",
    "    \n",
    "def training_loss(params, iters):\n",
    "    inputs, targets, mask = long_copy(seq_len, seq_wid)\n",
    "    result = []\n",
    "    dnc = DNC(input_size=seq_wid+2, output_size=seq_wid+1, hidden_size=32, R=2, N=64, W=8)\n",
    "    for t in range(inputs.shape[0]):\n",
    "        out = dnc.step_forward(params, inputs[np.newaxis, t])\n",
    "        result.append(out)\n",
    "    result = np.concatenate(result, axis=0)\n",
    "    return loss_fn(result, targets, mask) \n",
    "\n",
    "def callback(weights, iters, gradient):\n",
    "    if iters % 1000 == 0:\n",
    "        print(\"Iteration\", iters, \"Train loss:\", training_loss(weights, 0))\n",
    "        print_training_prediction(weights, iters)\n",
    "\n",
    "# Build gradient of loss function using autograd.\n",
    "training_loss_grad = grad(training_loss)\n",
    "\n",
    "print(\"Training DNC...\")\n",
    "# trained_params = adam(training_loss_grad, dnc_params, step_size=0.001,\n",
    "#                       num_iters=100000, callback=callback)\n",
    "trained_params = rmsprop(training_loss_grad, dnc_params, step_size=0.001,\n",
    "                      num_iters=100000, callback=callback)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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