06_AE_NoisyAE.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Chay16/dataflowr-PlutonAI/blob/master/06_AE_NoisyAE.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G1w5n0W02uiH",
        "colab_type": "text"
      },
      "source": [
        "# Unsupervised learning with Autoencoder\n",
        "\n",
        "We first play with MNIST dataset and pieces of code seen during the course."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CFac0UPC2uiI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "import torch.optim as optim\n",
        "from torchvision import datasets, transforms\n",
        "\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s7XyL-JX2uiM",
        "colab_type": "text"
      },
      "source": [
        "## Loading MNIST"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9yAsJijZ2uiM",
        "colab_type": "code",
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          "height": 34
        },
        "outputId": "e11cb120-8737-40f4-b58b-3a878c29ddd7"
      },
      "source": [
        "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
        "\n",
        "print('Using gpu: %s ' % torch.cuda.is_available())"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Using gpu: True \n"
          ],
          "name": "stdout"
        }
      ]
    },
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      "source": [
        "# to be modified if not on colab\n",
        "root_dir = './data/MNIST/'\n",
        "train_loader = torch.utils.data.DataLoader(\n",
        "    datasets.MNIST(root_dir, train=True, download=True, transform=transforms.ToTensor()),\n",
        "    batch_size=256, shuffle=True)\n",
        "\n",
        "test_loader = torch.utils.data.DataLoader(\n",
        "    datasets.MNIST(root_dir, train=False, download=True, transform=transforms.ToTensor()),\n",
        "    batch_size=10, shuffle=False)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw/train-images-idx3-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
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        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/MNIST/raw/train-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw/train-labels-idx1-ubyte.gz\n"
          ],
          "name": "stdout"
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        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw/t10k-images-idx3-ubyte.gz\n"
          ],
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          },
          "metadata": {
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        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Extracting ./data/MNIST/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
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            ]
          },
          "metadata": {
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        },
        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw\n",
            "Processing...\n",
            "Done!\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/torch/csrc/utils/tensor_numpy.cpp:141: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s1M2kLzn2uiT",
        "colab_type": "text"
      },
      "source": [
        "## Helper Functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wugVCUrI2uiT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "c55c5122-aa01-4778-d5c1-82f6a7eaf5f7"
      },
      "source": [
        "def to_img(x):\n",
        "    x = x.cpu().data.numpy()\n",
        "    x = 0.5 * (x + 1)\n",
        "    x = np.clip(x, 0, 1)\n",
        "    x = x.reshape([-1, 28, 28])\n",
        "    return x\n",
        "\n",
        "def plot_reconstructions(model):\n",
        "    \"\"\"\n",
        "    Plot 10 reconstructions from the test set. The top row is the original\n",
        "    digits, the bottom is the decoder reconstruction.\n",
        "    The middle row is the encoded vector.\n",
        "    The encoder is called by model.encoder\n",
        "    The decoder is called by model.decoder\n",
        "    \"\"\"\n",
        "    # encode then decode\n",
        "    data, _ = next(iter(test_loader))\n",
        "    data = data.view([-1, 784])\n",
        "    data.requires_grad = False\n",
        "    data = data.to(device)\n",
        "    true_imgs = data\n",
        "    encoded_imgs = model.encoder(data)\n",
        "    decoded_imgs = model.decoder(encoded_imgs)\n",
        "    \n",
        "    true_imgs = to_img(true_imgs)\n",
        "    decoded_imgs = to_img(decoded_imgs)\n",
        "    encoded_imgs = encoded_imgs.cpu().data.numpy()\n",
        "    \n",
        "    n = 10\n",
        "    plt.figure(figsize=(20, 4))\n",
        "    for i in range(n):\n",
        "        # display original\n",
        "        ax = plt.subplot(3, n, i + 1)\n",
        "        plt.imshow(true_imgs[i])\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "        \n",
        "        ax = plt.subplot(3, n, i + 1 + n)\n",
        "        plt.imshow(encoded_imgs[i].reshape(-1,4))\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "\n",
        "        # display reconstruction\n",
        "        ax = plt.subplot(3, n, i + 1 + n + n)\n",
        "        plt.imshow(decoded_imgs[i])\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "    \n",
        "    plt.show()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dRAI3MaO2uiW",
        "colab_type": "text"
      },
      "source": [
        "## Simple Auto-Encoder\n",
        "\n",
        "We'll start with the simplest autoencoder: a single, fully-connected layer as the encoder and decoder."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GApDwy6e2uiW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class AutoEncoder(nn.Module):\n",
        "    def __init__(self, input_dim, encoding_dim):\n",
        "        super(AutoEncoder, self).__init__()\n",
        "        self.encoder = nn.Linear(input_dim, encoding_dim)\n",
        "        self.decoder = nn.Linear(encoding_dim, input_dim)\n",
        "\n",
        "    def forward(self, x):\n",
        "        encoded = F.relu(self.encoder(x))\n",
        "        decoded = self.decoder(encoded)\n",
        "        return decoded"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oUbMKILV2uiZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "input_dim = 784\n",
        "encoding_dim = 64\n",
        "\n",
        "model = AutoEncoder(input_dim, encoding_dim)\n",
        "model = model.to(device)\n",
        "optimizer = optim.Adam(model.parameters())\n",
        "loss_fn = torch.nn.MSELoss()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZaNO1R_G2uid",
        "colab_type": "text"
      },
      "source": [
        "Why did we take 784 as input dimension?\n",
        "\n",
        "To find the learning rate, see the documentation for [Adam optimizer](https://pytorch.org/docs/stable/optim.html#torch.optim.Adam)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e3Zh8eQ_2uid",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def train_model(model,loss_fn,data_loader=None,epochs=1,optimizer=None):\n",
        "    model.train()\n",
        "    for epoch in range(epochs):\n",
        "        for batch_idx, (data, _) in enumerate(train_loader):\n",
        "            data = data.view([-1, 784]).to(device)\n",
        "            optimizer.zero_grad()\n",
        "            output = model(data)\n",
        "            loss = loss_fn(output, data)\n",
        "            loss.backward()\n",
        "            optimizer.step()\n",
        "            if batch_idx % 100 == 0:\n",
        "                print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
        "                    epoch, batch_idx * len(data), len(data_loader.dataset),\n",
        "                    100. * batch_idx / len(data_loader), loss.data.item()))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "dybe6kLJ2uig",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        },
        "outputId": "09d73644-0e06-4924-9bc7-34fc0107ead2"
      },
      "source": [
        "train_model(model, loss_fn, data_loader=train_loader, epochs=10, optimizer=optimizer)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train Epoch: 0 [0/60000 (0%)]\tLoss: 0.124655\n",
            "Train Epoch: 0 [25600/60000 (43%)]\tLoss: 0.046309\n",
            "Train Epoch: 0 [51200/60000 (85%)]\tLoss: 0.031571\n",
            "Train Epoch: 1 [0/60000 (0%)]\tLoss: 0.030374\n",
            "Train Epoch: 1 [25600/60000 (43%)]\tLoss: 0.025613\n",
            "Train Epoch: 1 [51200/60000 (85%)]\tLoss: 0.022501\n",
            "Train Epoch: 2 [0/60000 (0%)]\tLoss: 0.022306\n",
            "Train Epoch: 2 [25600/60000 (43%)]\tLoss: 0.019670\n",
            "Train Epoch: 2 [51200/60000 (85%)]\tLoss: 0.018690\n",
            "Train Epoch: 3 [0/60000 (0%)]\tLoss: 0.018267\n",
            "Train Epoch: 3 [25600/60000 (43%)]\tLoss: 0.018283\n",
            "Train Epoch: 3 [51200/60000 (85%)]\tLoss: 0.017572\n",
            "Train Epoch: 4 [0/60000 (0%)]\tLoss: 0.017365\n",
            "Train Epoch: 4 [25600/60000 (43%)]\tLoss: 0.016401\n",
            "Train Epoch: 4 [51200/60000 (85%)]\tLoss: 0.017780\n",
            "Train Epoch: 5 [0/60000 (0%)]\tLoss: 0.018329\n",
            "Train Epoch: 5 [25600/60000 (43%)]\tLoss: 0.017864\n",
            "Train Epoch: 5 [51200/60000 (85%)]\tLoss: 0.017786\n",
            "Train Epoch: 6 [0/60000 (0%)]\tLoss: 0.016799\n",
            "Train Epoch: 6 [25600/60000 (43%)]\tLoss: 0.017083\n",
            "Train Epoch: 6 [51200/60000 (85%)]\tLoss: 0.017452\n",
            "Train Epoch: 7 [0/60000 (0%)]\tLoss: 0.016579\n",
            "Train Epoch: 7 [25600/60000 (43%)]\tLoss: 0.016839\n",
            "Train Epoch: 7 [51200/60000 (85%)]\tLoss: 0.016437\n",
            "Train Epoch: 8 [0/60000 (0%)]\tLoss: 0.017283\n",
            "Train Epoch: 8 [25600/60000 (43%)]\tLoss: 0.017357\n",
            "Train Epoch: 8 [51200/60000 (85%)]\tLoss: 0.016777\n",
            "Train Epoch: 9 [0/60000 (0%)]\tLoss: 0.017148\n",
            "Train Epoch: 9 [25600/60000 (43%)]\tLoss: 0.016857\n",
            "Train Epoch: 9 [51200/60000 (85%)]\tLoss: 0.016956\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NOPJgAUh2uij",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "outputId": "7cb7e4af-71cb-4fb1-829b-25e733221de8"
      },
      "source": [
        "plot_reconstructions(model)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x288 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xhCiHP7P2uil",
        "colab_type": "text"
      },
      "source": [
        "## 1. Exercise: Stacked Autoencoder\n",
        "\n",
        "Now you will code an autoencoder where both the encoder and the decoder are multilayer perceptron (MLP). You can take for the encoder a first hidden layer with dimension 128, a second one with dimension 64 and then the code of dimension 32. For the decoder, you can take the same sequence of dimensions in reverse order."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SrTmxg7z2uim",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class DeepAutoEncoder(nn.Module):\n",
        "    def __init__(self, input_dim, encoding_dim):\n",
        "        super(DeepAutoEncoder, self).__init__()\n",
        "        #\n",
        "        # your code here\n",
        "        self.encoder = nn.Sequential(\n",
        "            nn.Linear(input_dim, 128),\n",
        "            nn.ReLU(True),\n",
        "            nn.Linear(128, 64),\n",
        "            nn.ReLU(True), \n",
        "            nn.Linear(64, encoding_dim), \n",
        "            nn.ReLU(True),\n",
        "        )\n",
        "        self.decoder = nn.Sequential(\n",
        "            nn.Linear(encoding_dim, 64),\n",
        "            nn.ReLU(True),\n",
        "            nn.Linear(64, 128),\n",
        "            nn.ReLU(True), \n",
        "            nn.Linear(128, input_dim),\n",
        "        )\n",
        "        #\n",
        "        \n",
        "    def forward(self, x):\n",
        "        #\n",
        "        # your code here\n",
        "        encoded = self.encoder(x)\n",
        "        decoded = self.decoder(encoded)\n",
        "        \n",
        "        return decoded\n",
        "        #"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bm_n3sI92uiq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "input_dim = 784\n",
        "encoding_dim = 32\n",
        "\n",
        "model = DeepAutoEncoder(input_dim, encoding_dim)\n",
        "model = model.to(device)\n",
        "optimizer = optim.Adam(model.parameters())\n",
        "loss_fn = torch.nn.MSELoss()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "8VNi4vtk2uit",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        },
        "outputId": "8d7dbec6-0b48-41f8-e991-71b0e14c8dbf"
      },
      "source": [
        "train_model(model, loss_fn,data_loader=train_loader,epochs=10,optimizer=optimizer)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train Epoch: 0 [0/60000 (0%)]\tLoss: 0.115357\n",
            "Train Epoch: 0 [25600/60000 (43%)]\tLoss: 0.049786\n",
            "Train Epoch: 0 [51200/60000 (85%)]\tLoss: 0.036796\n",
            "Train Epoch: 1 [0/60000 (0%)]\tLoss: 0.034610\n",
            "Train Epoch: 1 [25600/60000 (43%)]\tLoss: 0.030025\n",
            "Train Epoch: 1 [51200/60000 (85%)]\tLoss: 0.028142\n",
            "Train Epoch: 2 [0/60000 (0%)]\tLoss: 0.026009\n",
            "Train Epoch: 2 [25600/60000 (43%)]\tLoss: 0.024164\n",
            "Train Epoch: 2 [51200/60000 (85%)]\tLoss: 0.023409\n",
            "Train Epoch: 3 [0/60000 (0%)]\tLoss: 0.024333\n",
            "Train Epoch: 3 [25600/60000 (43%)]\tLoss: 0.023156\n",
            "Train Epoch: 3 [51200/60000 (85%)]\tLoss: 0.022704\n",
            "Train Epoch: 4 [0/60000 (0%)]\tLoss: 0.022691\n",
            "Train Epoch: 4 [25600/60000 (43%)]\tLoss: 0.021351\n",
            "Train Epoch: 4 [51200/60000 (85%)]\tLoss: 0.021424\n",
            "Train Epoch: 5 [0/60000 (0%)]\tLoss: 0.021141\n",
            "Train Epoch: 5 [25600/60000 (43%)]\tLoss: 0.020195\n",
            "Train Epoch: 5 [51200/60000 (85%)]\tLoss: 0.019983\n",
            "Train Epoch: 6 [0/60000 (0%)]\tLoss: 0.019795\n",
            "Train Epoch: 6 [25600/60000 (43%)]\tLoss: 0.020016\n",
            "Train Epoch: 6 [51200/60000 (85%)]\tLoss: 0.019530\n",
            "Train Epoch: 7 [0/60000 (0%)]\tLoss: 0.020278\n",
            "Train Epoch: 7 [25600/60000 (43%)]\tLoss: 0.019000\n",
            "Train Epoch: 7 [51200/60000 (85%)]\tLoss: 0.019027\n",
            "Train Epoch: 8 [0/60000 (0%)]\tLoss: 0.019761\n",
            "Train Epoch: 8 [25600/60000 (43%)]\tLoss: 0.017496\n",
            "Train Epoch: 8 [51200/60000 (85%)]\tLoss: 0.017504\n",
            "Train Epoch: 9 [0/60000 (0%)]\tLoss: 0.018086\n",
            "Train Epoch: 9 [25600/60000 (43%)]\tLoss: 0.018229\n",
            "Train Epoch: 9 [51200/60000 (85%)]\tLoss: 0.017502\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nraDkOnC2uiv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "outputId": "c5afc0ec-49f0-4ebb-c6ba-2b77566e89a7"
      },
      "source": [
        "plot_reconstructions(model)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x288 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XIWLi9Ps2uix",
        "colab_type": "text"
      },
      "source": [
        "Replace the `MSELoss` with a `BCEWithLogitsLoss` for each pixel. Note the unusual use of `BCEWithLogitsLoss`! You can have a look at the definition of [Cross Entropy](https://en.wikipedia.org/wiki/Cross_entropy)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6so26rh-c37a",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        },
        "outputId": "4e0b3993-4abb-4d58-e9d2-1d8ada8f9a97"
      },
      "source": [
        "input_dim = 784\n",
        "encoding_dim = 32\n",
        "\n",
        "model = DeepAutoEncoder(input_dim, encoding_dim)\n",
        "model = model.to(device)\n",
        "optimizer = optim.Adam(model.parameters())\n",
        "loss_fn = torch.nn.BCEWithLogitsLoss()\n",
        "\n",
        "train_model(model, loss_fn,data_loader=train_loader,epochs=10,optimizer=optimizer)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train Epoch: 0 [0/60000 (0%)]\tLoss: 0.694675\n",
            "Train Epoch: 0 [25600/60000 (43%)]\tLoss: 0.258323\n",
            "Train Epoch: 0 [51200/60000 (85%)]\tLoss: 0.245227\n",
            "Train Epoch: 1 [0/60000 (0%)]\tLoss: 0.234705\n",
            "Train Epoch: 1 [25600/60000 (43%)]\tLoss: 0.218493\n",
            "Train Epoch: 1 [51200/60000 (85%)]\tLoss: 0.193358\n",
            "Train Epoch: 2 [0/60000 (0%)]\tLoss: 0.187576\n",
            "Train Epoch: 2 [25600/60000 (43%)]\tLoss: 0.166909\n",
            "Train Epoch: 2 [51200/60000 (85%)]\tLoss: 0.160064\n",
            "Train Epoch: 3 [0/60000 (0%)]\tLoss: 0.163467\n",
            "Train Epoch: 3 [25600/60000 (43%)]\tLoss: 0.156074\n",
            "Train Epoch: 3 [51200/60000 (85%)]\tLoss: 0.148047\n",
            "Train Epoch: 4 [0/60000 (0%)]\tLoss: 0.144214\n",
            "Train Epoch: 4 [25600/60000 (43%)]\tLoss: 0.149295\n",
            "Train Epoch: 4 [51200/60000 (85%)]\tLoss: 0.140440\n",
            "Train Epoch: 5 [0/60000 (0%)]\tLoss: 0.140575\n",
            "Train Epoch: 5 [25600/60000 (43%)]\tLoss: 0.139713\n",
            "Train Epoch: 5 [51200/60000 (85%)]\tLoss: 0.133479\n",
            "Train Epoch: 6 [0/60000 (0%)]\tLoss: 0.134737\n",
            "Train Epoch: 6 [25600/60000 (43%)]\tLoss: 0.136135\n",
            "Train Epoch: 6 [51200/60000 (85%)]\tLoss: 0.134200\n",
            "Train Epoch: 7 [0/60000 (0%)]\tLoss: 0.133798\n",
            "Train Epoch: 7 [25600/60000 (43%)]\tLoss: 0.130751\n",
            "Train Epoch: 7 [51200/60000 (85%)]\tLoss: 0.124880\n",
            "Train Epoch: 8 [0/60000 (0%)]\tLoss: 0.127582\n",
            "Train Epoch: 8 [25600/60000 (43%)]\tLoss: 0.123284\n",
            "Train Epoch: 8 [51200/60000 (85%)]\tLoss: 0.128581\n",
            "Train Epoch: 9 [0/60000 (0%)]\tLoss: 0.123181\n",
            "Train Epoch: 9 [25600/60000 (43%)]\tLoss: 0.122425\n",
            "Train Epoch: 9 [51200/60000 (85%)]\tLoss: 0.122924\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MpjKFk85dLud",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "outputId": "1f3871ee-41af-4f5f-b6b6-2089db38261a"
      },
      "source": [
        "plot_reconstructions(model)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x288 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9S8qgLsO2uix",
        "colab_type": "text"
      },
      "source": [
        "## 2. Optional\n",
        "\n",
        "At this stage, you can code the interpolation described in the lesson to obtain:\n",
        "\n",
        "![](https://raw.githubusercontent.com/mlelarge/dataflowr-slides/master/PlutonAI/images/lesson6/interp_AE.png)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9VCJLQXE2ujS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 125
        },
        "outputId": "cb9b2e8f-03e8-41bd-b84d-9377699243a4"
      },
      "source": [
        "N_img = 10\n",
        "\n",
        "alphas = np.linspace(0,1,N_img)\n",
        "images, labels = next(iter(train_loader))\n",
        "image_2 = images[labels == 2][0]\n",
        "image_9 = images[labels == 9][0]\n",
        "\n",
        "encoded_2 = model.encoder(image_2.view([-1, 784]).to(device))\n",
        "encoded_9 = model.encoder(image_9.view([-1, 784]).to(device))\n",
        "\n",
        "plt.figure(figsize=(20, 10))\n",
        "\n",
        "\n",
        "for i in range(N_img):\n",
        "    alpha = alphas[i]\n",
        "    encoded = (1 - alpha) * encoded_2 + alpha * encoded_9\n",
        "    decoded = model.decoder(encoded)\n",
        "    interpolation = to_img(decoded)[0]\n",
        "\n",
        "    ax = plt.subplot(1, N_img, i+1)\n",
        "    plt.imshow(interpolation)\n",
        "    plt.gray()\n",
        "    ax.get_xaxis().set_visible(False)\n",
        "    ax.get_yaxis().set_visible(False)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1440x720 with 10 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z3sm7Pi62ujU",
        "colab_type": "text"
      },
      "source": [
        "# 3. Exercise: Implement a denoising AE:\n",
        "\n",
        "\n",
        "Use previous code and with minimal modifications, transform your AE in a denoising AE. Now, you first apply some noise to your input and try to recover the original data at the output. For the noise, you can add some random noise or erase some of the pixels. In this last case, you should obtain something like: \n",
        "\n",
        "![](https://raw.githubusercontent.com/mlelarge/dataflowr-slides/master/PlutonAI/images/lesson6/denoising_AE.png)\n",
        "\n",
        "The first line corresponds to the original digit, the second line to the noisy version of the digit given as input to your network, the third line is the associated code amd the last line is the denoised digit obtained by your decoder from the code."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "isYFcQFS2ujU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# You need first to modify the training process by adding noise to your data\n",
        "# Hint if you want to erase pixels: https://stackoverflow.com/questions/49216615/is-there-an-efficient-way-to-create-a-random-bit-mask-in-pytorch\n",
        "def train_denoiser(model,loss_fn,data_loader=None,epochs=1,optimizer=None, noise=0.1):\n",
        "    model.train()\n",
        "    for epoch in range(epochs):\n",
        "      for batch_idx, (data, _) in enumerate(train_loader):\n",
        "        #\n",
        "        # your code here to create the noisy_data\n",
        "        data = data.to(device)\n",
        "        noisy_data = data + noise*torch.randn(data.size()).to(device)\n",
        "        data = data.view([-1,784])\n",
        "        noisy_data = noisy_data.view([-1, 784])\n",
        "\n",
        "        #\n",
        "        optimizer.zero_grad()\n",
        "        output = model(noisy_data)\n",
        "        loss = loss_fn(output, data)\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "            \n",
        "        if batch_idx % 100 == 0:\n",
        "            print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
        "                epoch, batch_idx * len(data), len(data_loader.dataset),\n",
        "                100. * batch_idx / len(data_loader), loss.data.item()))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EBkQbfVl2ujX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "input_dim = 784\n",
        "encoding_dim = 32\n",
        "\n",
        "model = DeepAutoEncoder(input_dim, encoding_dim)\n",
        "model = model.to(device)\n",
        "optimizer = optim.Adam(model.parameters())\n",
        "loss_fn = torch.nn.BCEWithLogitsLoss()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KlYqlT822ujZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        },
        "outputId": "6b838969-2bac-4e07-c919-98b59d6781c6"
      },
      "source": [
        "train_denoiser(model, loss_fn,data_loader=train_loader,epochs=10,optimizer=optimizer, noise=0.8)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train Epoch: 0 [0/60000 (0%)]\tLoss: 0.694136\n",
            "Train Epoch: 0 [25600/60000 (43%)]\tLoss: 0.257474\n",
            "Train Epoch: 0 [51200/60000 (85%)]\tLoss: 0.237771\n",
            "Train Epoch: 1 [0/60000 (0%)]\tLoss: 0.240704\n",
            "Train Epoch: 1 [25600/60000 (43%)]\tLoss: 0.221645\n",
            "Train Epoch: 1 [51200/60000 (85%)]\tLoss: 0.206718\n",
            "Train Epoch: 2 [0/60000 (0%)]\tLoss: 0.192641\n",
            "Train Epoch: 2 [25600/60000 (43%)]\tLoss: 0.195448\n",
            "Train Epoch: 2 [51200/60000 (85%)]\tLoss: 0.185199\n",
            "Train Epoch: 3 [0/60000 (0%)]\tLoss: 0.181221\n",
            "Train Epoch: 3 [25600/60000 (43%)]\tLoss: 0.182353\n",
            "Train Epoch: 3 [51200/60000 (85%)]\tLoss: 0.168338\n",
            "Train Epoch: 4 [0/60000 (0%)]\tLoss: 0.165421\n",
            "Train Epoch: 4 [25600/60000 (43%)]\tLoss: 0.169033\n",
            "Train Epoch: 4 [51200/60000 (85%)]\tLoss: 0.164105\n",
            "Train Epoch: 5 [0/60000 (0%)]\tLoss: 0.167376\n",
            "Train Epoch: 5 [25600/60000 (43%)]\tLoss: 0.168398\n",
            "Train Epoch: 5 [51200/60000 (85%)]\tLoss: 0.167432\n",
            "Train Epoch: 6 [0/60000 (0%)]\tLoss: 0.163653\n",
            "Train Epoch: 6 [25600/60000 (43%)]\tLoss: 0.159213\n",
            "Train Epoch: 6 [51200/60000 (85%)]\tLoss: 0.152680\n",
            "Train Epoch: 7 [0/60000 (0%)]\tLoss: 0.157847\n",
            "Train Epoch: 7 [25600/60000 (43%)]\tLoss: 0.156232\n",
            "Train Epoch: 7 [51200/60000 (85%)]\tLoss: 0.156578\n",
            "Train Epoch: 8 [0/60000 (0%)]\tLoss: 0.153268\n",
            "Train Epoch: 8 [25600/60000 (43%)]\tLoss: 0.157379\n",
            "Train Epoch: 8 [51200/60000 (85%)]\tLoss: 0.150285\n",
            "Train Epoch: 9 [0/60000 (0%)]\tLoss: 0.151722\n",
            "Train Epoch: 9 [25600/60000 (43%)]\tLoss: 0.151464\n",
            "Train Epoch: 9 [51200/60000 (85%)]\tLoss: 0.151403\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LGixZVJF2ujW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Now you need to modify the plot function\n",
        "def plot_denoising(model, noise=0.1):\n",
        "    \"\"\"\n",
        "    Plot 10 reconstructions from the test set. The top row is the original\n",
        "    digits, , the second row is the noisy digits, \n",
        "    the third row is the encoded vector and\n",
        "    the bottom is the decoder reconstruction.\n",
        "    \"\"\"\n",
        "    # encode then decode\n",
        "    data, _ = next(iter(test_loader))\n",
        "    #\n",
        "    # your code here to compute\n",
        "    # noisy_data\n",
        "    # encoded_imgs\n",
        "    # decoded_imgs\n",
        "    noisy_data = data.to(device) + noise*torch.randn(data.size()).to(device)\n",
        "    noisy_data = noisy_data.view([-1,784])\n",
        "    encoded_imgs = model.encoder(noisy_data)\n",
        "    decoded_imgs = model.decoder(encoded_imgs)\n",
        "    #\n",
        "    true_imgs = to_img(data)\n",
        "    noisy_imgs = to_img(noisy_data)\n",
        "    decoded_imgs = to_img(decoded_imgs)\n",
        "    encoded_imgs = encoded_imgs.cpu().data.numpy()\n",
        "    \n",
        "    n = 10\n",
        "    plt.figure(figsize=(20, 4))\n",
        "    for i in range(n):\n",
        "        # display original\n",
        "        ax = plt.subplot(4, n, i + 1)\n",
        "        plt.imshow(true_imgs[i])\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "        \n",
        "        # display corrupted original\n",
        "        ax = plt.subplot(4, n, i + 1 +n)\n",
        "        plt.imshow(noisy_imgs[i])\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "        \n",
        "        # display code\n",
        "        ax = plt.subplot(4, n, i + 1 + 2*n)\n",
        "        plt.imshow(encoded_imgs[i].reshape(-1,4))\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "\n",
        "        # display reconstruction\n",
        "        ax = plt.subplot(4, n, i + 1 +  3*n)\n",
        "        plt.imshow(decoded_imgs[i])\n",
        "        plt.gray()\n",
        "        ax.get_xaxis().set_visible(False)\n",
        "        ax.get_yaxis().set_visible(False)\n",
        "    \n",
        "    plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RFLDJ6f_2ujb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 252
        },
        "outputId": "7a7aac16-c009-4184-c9b5-43c9cc1f8459"
      },
      "source": [
        "plot_denoising(model, noise=0.8)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x288 with 40 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ddKvatCh2ujn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}