Customized_VAE.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Customized_VAE.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vx92cpJlYjFp",
        "colab_type": "code",
        "outputId": "70ab2d84-f224-4607-cbf1-a3a9e9940b49",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        }
      },
      "source": [
        "# Import Tensorflow 2.0\n",
        "%tensorflow_version 2.x\n",
        "import tensorflow as tf\n",
        "\n",
        "import IPython\n",
        "import functools\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from tqdm import tqdm\n",
        "\n",
        "# Download and import the MIT 6.S191 package\n",
        "!pip install mitdeeplearning\n",
        "import mitdeeplearning as mdl"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting mitdeeplearning\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/8b/3b/b9174b68dc10832356d02a2d83a64b43a24f1762c172754407d22fc8f960/mitdeeplearning-0.1.2.tar.gz (2.1MB)\n",
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            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from mitdeeplearning) (1.18.2)\n",
            "Requirement already satisfied: regex in /usr/local/lib/python3.6/dist-packages (from mitdeeplearning) (2019.12.20)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.6/dist-packages (from mitdeeplearning) (4.38.0)\n",
            "Requirement already satisfied: gym in /usr/local/lib/python3.6/dist-packages (from mitdeeplearning) (0.17.1)\n",
            "Requirement already satisfied: cloudpickle<1.4.0,>=1.2.0 in /usr/local/lib/python3.6/dist-packages (from gym->mitdeeplearning) (1.3.0)\n",
            "Requirement already satisfied: pyglet<=1.5.0,>=1.4.0 in /usr/local/lib/python3.6/dist-packages (from gym->mitdeeplearning) (1.5.0)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from gym->mitdeeplearning) (1.4.1)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from gym->mitdeeplearning) (1.12.0)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from pyglet<=1.5.0,>=1.4.0->gym->mitdeeplearning) (0.16.0)\n",
            "Building wheels for collected packages: mitdeeplearning\n",
            "  Building wheel for mitdeeplearning (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for mitdeeplearning: filename=mitdeeplearning-0.1.2-cp36-none-any.whl size=2114586 sha256=f25bceecfff4d9b9372b211cba2d87cc60b4cf1804cce97ba315acef4fb1306a\n",
            "  Stored in directory: /root/.cache/pip/wheels/27/e1/73/5f01c787621d8a3c857f59876c79e304b9b64db9ff5bd61b74\n",
            "Successfully built mitdeeplearning\n",
            "Installing collected packages: mitdeeplearning\n",
            "Successfully installed mitdeeplearning-0.1.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZwVeWfU7YobJ",
        "colab_type": "code",
        "outputId": "c94b6ec5-6ccc-4a63-a231-ab8f22298a4f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        }
      },
      "source": [
        "# Get the training data: both images from CelebA and ImageNet\n",
        "path_to_training_data = tf.keras.utils.get_file('train_face.h5', 'https://www.dropbox.com/s/l5iqduhe0gwxumq/train_face.h5?dl=1')\n",
        "# Instantiate a TrainingDatasetLoader using the downloaded dataset\n",
        "loader = mdl.lab2.TrainingDatasetLoader(path_to_training_data)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://www.dropbox.com/s/l5iqduhe0gwxumq/train_face.h5?dl=1\n",
            "1263894528/1263889489 [==============================] - 50s 0us/step\n",
            "Opening /root/.keras/datasets/train_face.h5\n",
            "Loading data into memory...\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zghuqqOdYqcI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "number_of_training_examples = loader.get_train_size()\n",
        "(images, labels) = loader.get_batch(100)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-m5i4ZazYsc6",
        "colab_type": "code",
        "outputId": "bfb9154a-9240-4ba2-85b6-79c79ed9249f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
        }
      },
      "source": [
        "### Examining the CelebA training dataset ###\n",
        "\n",
        "#@title Change the sliders to look at positive and negative training examples! { run: \"auto\" }\n",
        "\n",
        "face_images = images[np.where(labels==1)[0]]\n",
        "not_face_images = images[np.where(labels==0)[0]]\n",
        "\n",
        "idx_face = 23 #@param {type:\"slider\", min:0, max:50, step:1}\n",
        "idx_not_face = 9 #@param {type:\"slider\", min:0, max:50, step:1}\n",
        "\n",
        "plt.figure(figsize=(5,5))\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.imshow(face_images[idx_face])\n",
        "plt.title(\"Face\"); plt.grid(False)\n",
        "\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.imshow(not_face_images[idx_not_face])"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f5c03894f60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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hl6fvmzb1AT88esR4OHDz+B3Gw02H9mg1Ls7NenFm5rwquZiy2fMxu+mze79JhFr1am6r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\nLteMZV+1UW3BwW/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mPOkVDq8d3+Lk9pkPJuQzSmVZTl7R1zi5Vlq+j0NzAjUO2cvutCvd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\nQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bJrAJfFOadlN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "\n",
        "n_filters = 12 # base number of convolutional filters\n",
        "\n",
        "'''Function to define a standard CNN model'''\n",
        "def make_standard_classifier(n_outputs=1):\n",
        "  Conv2D = functools.partial(tf.keras.layers.Conv2D, padding='same', activation='relu')\n",
        "  BatchNormalization = tf.keras.layers.BatchNormalization\n",
        "  Flatten = tf.keras.layers.Flatten\n",
        "  Dense = functools.partial(tf.keras.layers.Dense, activation='relu')\n",
        "\n",
        "  model = tf.keras.Sequential([\n",
        "    Conv2D(filters=1*n_filters, kernel_size=5,  strides=2),\n",
        "    BatchNormalization(),\n",
        "    \n",
        "    Conv2D(filters=2*n_filters, kernel_size=5,  strides=2),\n",
        "    BatchNormalization(),\n",
        "\n",
        "    Conv2D(filters=4*n_filters, kernel_size=3,  strides=2),\n",
        "    BatchNormalization(),\n",
        "\n",
        "    Conv2D(filters=6*n_filters, kernel_size=3,  strides=2),\n",
        "    BatchNormalization(),\n",
        "\n",
        "    Flatten(),\n",
        "    Dense(512),\n",
        "    Dense(n_outputs, activation=None),\n",
        "  ])\n",
        "  return model\n",
        "\n",
        "standard_classifier = make_standard_classifier()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Djn1gU4pasSu",
        "colab_type": "code",
        "outputId": "98647878-6020-4c9f-f0c0-850058508518",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        }
      },
      "source": [
        "### Train the standard CNN ###\n",
        "\n",
        "# Training hyperparameters\n",
        "batch_size = 32\n",
        "num_epochs = 2  # keep small to run faster\n",
        "learning_rate = 5e-4\n",
        "\n",
        "optimizer = tf.keras.optimizers.Adam(learning_rate) # define our optimizer\n",
        "loss_history = mdl.util.LossHistory(smoothing_factor=0.99) # to record loss evolution\n",
        "plotter = mdl.util.PeriodicPlotter(sec=2, scale='semilogy')\n",
        "if hasattr(tqdm, '_instances'): tqdm._instances.clear() # clear if it exists\n",
        "\n",
        "@tf.function\n",
        "def standard_train_step(x, y):\n",
        "  with tf.GradientTape() as tape:\n",
        "    # feed the images into the model\n",
        "    logits = standard_classifier(x) \n",
        "    # Compute the loss\n",
        "    loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=y, logits=logits)\n",
        "\n",
        "  # Backpropagation\n",
        "  grads = tape.gradient(loss, standard_classifier.trainable_variables)\n",
        "  optimizer.apply_gradients(zip(grads, standard_classifier.trainable_variables))\n",
        "  return loss\n",
        "\n",
        "# The training loop!\n",
        "for epoch in range(num_epochs):\n",
        "  for idx in tqdm(range(loader.get_train_size()//batch_size)):\n",
        "    # Grab a batch of training data and propagate through the network\n",
        "    x, y = loader.get_batch(batch_size)\n",
        "    loss = standard_train_step(x, y)\n",
        "\n",
        "    # Record the loss and plot the evolution of the loss as a function of training\n",
        "    loss_history.append(loss.numpy().mean())\n",
        "    plotter.plot(loss_history.get())"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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l6W+xfNdx/H7hFgy7/2s3XknXGI0NmQUTAZnaij+eh/dvPRNf3Gm8EK1/sjLF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\nQY6JgIgoyDEREBEFuf8Hz0p6ucgGObwAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 3434/3434 [00:27<00:00, 126.38it/s]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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l6W+xfNdx/H7hFgy7/2s3XknXGI0NmQUTAZnaij+eh/dvPRNf3Gm8EK1/sjLF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\nQY6JgIgoyDEREBEFuf8Hz0p6ucgGObwAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pJplzyPhascA",
        "colab_type": "code",
        "outputId": "8835dae2-b316-4628-b198-bb957d6026b3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "### Evaluation of standard CNN ###\n",
        "\n",
        "# TRAINING DATA\n",
        "# Evaluate on a subset of CelebA+Imagenet\n",
        "(batch_x, batch_y) = loader.get_batch(5000)\n",
        "y_pred_standard = tf.round(tf.nn.sigmoid(standard_classifier.predict(batch_x)))\n",
        "acc_standard = tf.reduce_mean(tf.cast(tf.equal(batch_y, y_pred_standard), tf.float32))\n",
        "\n",
        "print(\"Standard CNN accuracy on (potentially biased) training set: {:.4f}\".format(acc_standard.numpy()))"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Standard CNN accuracy on (potentially biased) training set: 0.9954\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VUJrBOvfaskV",
        "colab_type": "code",
        "outputId": "dbe6eeef-1298-4e8e-8ed3-59df58b49831",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        }
      },
      "source": [
        "### Load test dataset and plot examples ###\n",
        "\n",
        "test_faces = mdl.lab2.get_test_faces()\n",
        "keys = [\"Light Female\", \"Light Male\", \"Dark Female\", \"Dark Male\"]\n",
        "for group, key in zip(test_faces,keys): \n",
        "  plt.figure(figsize=(5,5))\n",
        "  plt.imshow(np.hstack(group))\n",
        "  plt.title(key, fontsize=15)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Gcnx2m2YxJ4WA0jovGinSHJ1QzeaI0tgmYtuWlCLWD0QSQ7dnsZyxWq0Ybc4w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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1wwFgiVFJy9657pHhbHnE8vQmzXSKq6p/sQ5nXOVQU5VD6ECXGqaopMJgctas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\nnX2i7f8Dd1aRmpWROwsAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AnQfHPP/iLRbLOcVkg3e/7WnGswnH8yOuPfNbfOrTn0YXR2zWNU0IzHePEFOw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8kQI3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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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l4l2bxm4zFk3LonMs2oRTRQGTaXIRohJ8azG9RQyiCD4SYl9tEANFntFZs4IC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\nkDu2Yzu2t7UdB7ljO7Zje1vb/wfKUNnUSB2jiAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lk86YFnCa6qa",
        "colab_type": "code",
        "outputId": "87cfe285-3a3d-4795-d44c-bb2be3f1e6fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "### Evaluate the standard CNN on the test data ### \n",
        "\n",
        "standard_classifier_logits = [standard_classifier(np.array(x, dtype=np.float32)) for x in test_faces]\n",
        "standard_classifier_probs = tf.squeeze(tf.sigmoid(standard_classifier_logits))\n",
        "\n",
        "# Plot the prediction accuracies per demographic\n",
        "xx = range(len(keys))\n",
        "yy = standard_classifier_probs.numpy().mean(1)\n",
        "plt.bar(xx, yy)\n",
        "plt.xticks(xx, keys)\n",
        "plt.ylim(max(0,yy.min()-yy.ptp()/2.), yy.max()+yy.ptp()/2.)\n",
        "plt.title(\"Standard classifier predictions\");"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a3mytjuVYyf7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def vae_loss_function(x, x_recon, mu, logsigma, kl_weight=0.0005):\n",
        "  latent_loss = 0.5 * tf.reduce_sum(tf.exp(logsigma) + tf.square(mu) - 1.0 - logsigma, axis=1)\n",
        "  reconstruction_loss = tf.reduce_mean(tf.abs(x-x_recon), axis=(1,2,3))\n",
        "  vae_loss = kl_weight * latent_loss + reconstruction_loss \n",
        "  return vae_loss\n",
        "\n",
        "def sampling(z_mean, z_logsigma):\n",
        "  batch, latent_dim = z_mean.shape\n",
        "  epsilon = tf.random.normal(shape=(batch, latent_dim))\n",
        "  z = z_mean + tf.math.exp(0.5 * z_logsigma) * epsilon\n",
        "  return z\n",
        "def debiasing_loss_function(x, x_pred, y, y_logit, mu, logsigma):\n",
        "  vae_loss = vae_loss_function(x, x_pred, mu, logsigma)\n",
        "  classification_loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=y, logits=y_logit)\n",
        "  face_indicator = tf.cast(tf.equal(y, 1), tf.float32)\n",
        "  total_loss = tf.reduce_mean(\n",
        "      classification_loss + \n",
        "      face_indicator * vae_loss\n",
        "  )\n",
        "  return total_loss, classification_loss\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I46xVM99Z755",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "n_filters = 12 # base number of convolutional filters, same as standard CNN\n",
        "latent_dim = 500 # number of latent variables\n",
        "\n",
        "def make_face_decoder_network():\n",
        "  # Functionally define the different layer types we will use\n",
        "  Conv2DTranspose = functools.partial(tf.keras.layers.Conv2DTranspose, padding='same', activation='relu')\n",
        "  BatchNormalization = tf.keras.layers.BatchNormalization\n",
        "  Flatten = tf.keras.layers.Flatten\n",
        "  Dense = functools.partial(tf.keras.layers.Dense, activation='relu')\n",
        "  Reshape = tf.keras.layers.Reshape\n",
        "\n",
        "  # Build the decoder network using the Sequential API\n",
        "  decoder = tf.keras.Sequential([\n",
        "    # Transform to pre-convolutional generation\n",
        "    Dense(units=4*4*6*n_filters),  # 4x4 feature maps (with 6N occurances)\n",
        "    Reshape(target_shape=(4, 4, 6*n_filters)),\n",
        "\n",
        "    # Upscaling convolutions (inverse of encoder)\n",
        "    Conv2DTranspose(filters=4*n_filters, kernel_size=3,  strides=2),\n",
        "    Conv2DTranspose(filters=2*n_filters, kernel_size=3,  strides=2),\n",
        "    Conv2DTranspose(filters=1*n_filters, kernel_size=5,  strides=2),\n",
        "    Conv2DTranspose(filters=3, kernel_size=5,  strides=2),\n",
        "  ])\n",
        "\n",
        "  return decoder"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hTf8ygCVZ-9O",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "### Defining and creating the DB-VAE ###\n",
        "\n",
        "class DB_VAE(tf.keras.Model):\n",
        "  def __init__(self, latent_dim):\n",
        "    super(DB_VAE, self).__init__()\n",
        "    self.latent_dim = latent_dim\n",
        "\n",
        "    # Define the number of outputs for the encoder. Recall that we have \n",
        "    # `latent_dim` latent variables, as well as a supervised output for the \n",
        "    # classification.\n",
        "    num_encoder_dims = 2*self.latent_dim + 1\n",
        "\n",
        "    self.encoder = make_standard_classifier(num_encoder_dims)\n",
        "    self.decoder = make_face_decoder_network()\n",
        "\n",
        "  # function to feed images into encoder, encode the latent space, and output\n",
        "  #   classification probability \n",
        "  def encode(self, x):\n",
        "    # encoder output\n",
        "    encoder_output = self.encoder(x)\n",
        "\n",
        "    # classification prediction\n",
        "    y_logit = tf.expand_dims(encoder_output[:, 0], -1)\n",
        "    # latent variable distribution parameters\n",
        "    z_mean = encoder_output[:, 1:self.latent_dim+1] \n",
        "    z_logsigma = encoder_output[:, self.latent_dim+1:]\n",
        "\n",
        "    return y_logit, z_mean, z_logsigma\n",
        "\n",
        "  # VAE reparameterization: given a mean and logsigma, sample latent variables\n",
        "  def reparameterize(self, z_mean, z_logsigma):\n",
        "    # TODO: call the sampling function defined above\n",
        "    z = sampling(z_mean, z_logsigma)\n",
        "    # z = # TODO\n",
        "    return z\n",
        "\n",
        "  # Decode the latent space and output reconstruction\n",
        "  def decode(self, z):\n",
        "    # TODO: use the decoder to output the reconstruction\n",
        "    reconstruction = self.decoder(z)\n",
        "    # reconstruction = # TODO\n",
        "    return reconstruction\n",
        "\n",
        "  # The call function will be used to pass inputs x through the core VAE\n",
        "  def call(self, x): \n",
        "    # Encode input to a prediction and latent space\n",
        "    y_logit, z_mean, z_logsigma = self.encode(x)\n",
        "\n",
        "    # TODO: reparameterization\n",
        "    z = self.reparameterize(z_mean, z_logsigma)\n",
        "    # z = # TODO\n",
        "\n",
        "    # TODO: reconstruction\n",
        "    recon = self.decode(z)\n",
        "    # recon = # TODO\n",
        "    return y_logit, z_mean, z_logsigma, recon\n",
        "\n",
        "  # Predict face or not face logit for given input x\n",
        "  def predict(self, x):\n",
        "    y_logit, z_mean, z_logsigma = self.encode(x)\n",
        "    return y_logit\n",
        "\n",
        "dbvae = DB_VAE(latent_dim)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NHqP_c1jaA63",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Function to return the means for an input image batch\n",
        "def get_latent_mu(images, dbvae, batch_size=1024):\n",
        "  N = images.shape[0]\n",
        "  mu = np.zeros((N, latent_dim))\n",
        "  for start_ind in range(0, N, batch_size):\n",
        "    end_ind = min(start_ind+batch_size, N+1)\n",
        "    batch = (images[start_ind:end_ind]).astype(np.float32)/255.\n",
        "    _, batch_mu, _ = dbvae.encode(batch)\n",
        "    mu[start_ind:end_ind] = batch_mu\n",
        "  return mu"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C6bLcVOwbF1U",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "\n",
        "### Resampling algorithm for DB-VAE ###\n",
        "\n",
        "'''Function that recomputes the sampling probabilities for images within a batch\n",
        "      based on how they distribute across the training data'''\n",
        "def get_training_sample_probabilities(images, dbvae, bins=10, smoothing_fac=0.001): \n",
        "    print(\"Recomputing the sampling probabilities\")\n",
        "    \n",
        "    # TODO: run the input batch and get the latent variable means\n",
        "    mu = get_latent_mu(images, dbvae)\n",
        "    # mu = get_latent_mu('''TODO''') # TODO\n",
        "\n",
        "    # sampling probabilities for the images\n",
        "    training_sample_p = np.zeros(mu.shape[0])\n",
        "    \n",
        "    # consider the distribution for each latent variable \n",
        "    for i in range(latent_dim):\n",
        "      \n",
        "        latent_distribution = mu[:,i]\n",
        "        # generate a histogram of the latent distribution\n",
        "        hist_density, bin_edges =  np.histogram(latent_distribution, density=True, bins=bins)\n",
        "\n",
        "        # find which latent bin every data sample falls in \n",
        "        bin_edges[0] = -float('inf')\n",
        "        bin_edges[-1] = float('inf')\n",
        "        \n",
        "        # TODO: call the digitize function to find which bins in the latent distribution \n",
        "        #    every data sample falls in to\n",
        "        # https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.digitize.html\n",
        "        bin_idx = np.digitize(latent_distribution, bin_edges)\n",
        "        # bin_idx = np.digitize('''TODO''', '''TODO''') # TODO\n",
        "\n",
        "        # smooth the density function\n",
        "        hist_smoothed_density = hist_density + smoothing_fac\n",
        "        hist_smoothed_density = hist_smoothed_density / np.sum(hist_smoothed_density)\n",
        "\n",
        "        # invert the density function \n",
        "        p = 1.0/(hist_smoothed_density[bin_idx-1])\n",
        "        \n",
        "        # TODO: normalize all probabilities\n",
        "        p = p / np.sum(p)\n",
        "        # p = # TODO\n",
        "        \n",
        "        # TODO: update sampling probabilities by considering whether the newly\n",
        "        #     computed p is greater than the existing sampling probabilities.\n",
        "        training_sample_p = np.maximum(p, training_sample_p)\n",
        "        # training_sample_p = # TODO\n",
        "        \n",
        "    # final normalization\n",
        "    training_sample_p /= np.sum(training_sample_p)\n",
        "\n",
        "    return training_sample_p"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AUrU5UH5bJyo",
        "colab_type": "code",
        "outputId": "371128e5-d3ea-48c2-dc77-1f840e7f2349",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "### Training the DB-VAE ###\n",
        "import IPython\n",
        "# Hyperparameters\n",
        "batch_size = 16\n",
        "learning_rate = 5e-5\n",
        "latent_dim = 100\n",
        "\n",
        "# DB-VAE needs slightly more epochs to train since its more complex than \n",
        "# the standard classifier so we use 6 instead of 2\n",
        "num_epochs = 20 \n",
        "\n",
        "# instantiate a new DB-VAE model and optimizer\n",
        "dbvae = DB_VAE(100)\n",
        "optimizer = tf.keras.optimizers.Adam(learning_rate)\n",
        "\n",
        "# To define the training operation, we will use tf.function which is a powerful tool \n",
        "#   that lets us turn a Python function into a TensorFlow computation graph.\n",
        "@tf.function\n",
        "def debiasing_train_step(x, y):\n",
        "\n",
        "  with tf.GradientTape() as tape:\n",
        "    # Feed input x into dbvae. Note that this is using the DB_VAE call function!\n",
        "    y_logit, z_mean, z_logsigma, x_recon = dbvae(x)\n",
        "\n",
        "    '''TODO: call the DB_VAE loss function to compute the loss'''\n",
        "    loss, class_loss = debiasing_loss_function(x, x_recon, y, y_logit, z_mean, z_logsigma)\n",
        "    # loss, class_loss = debiasing_loss_function('''TODO arguments''') # TODO\n",
        "  \n",
        "  '''TODO: use the GradientTape.gradient method to compute the gradients.\n",
        "     Hint: this is with respect to the trainable_variables of the dbvae.'''\n",
        "  grads = tape.gradient(loss, dbvae.trainable_variables)\n",
        "  # grads = tape.gradient('''TODO''', '''TODO''') # TODO\n",
        "\n",
        "  # apply gradients to variables\n",
        "  optimizer.apply_gradients(zip(grads, dbvae.trainable_variables))\n",
        "  return loss\n",
        "\n",
        "# get training faces from data loader\n",
        "all_faces = loader.get_all_train_faces()\n",
        "\n",
        "if hasattr(tqdm, '_instances'): tqdm._instances.clear() # clear if it exists\n",
        "\n",
        "# The training loop -- outer loop iterates over the number of epochs\n",
        "for i in range(num_epochs):\n",
        "\n",
        "  IPython.display.clear_output(wait=True)\n",
        "  print(\"Starting epoch {}/{}\".format(i+1, num_epochs))\n",
        "\n",
        "  # Recompute data sampling proabilities\n",
        "  '''TODO: recompute the sampling probabilities for debiasing'''\n",
        "  p_faces = get_training_sample_probabilities(all_faces, dbvae)\n",
        "  # p_faces = get_training_sample_probabilities('''TODO''', '''TODO''') # TODO\n",
        "  \n",
        "  # get a batch of training data and compute the training step\n",
        "  for j in tqdm(range(loader.get_train_size() // batch_size)):\n",
        "    # load a batch of data\n",
        "    (x, y) = loader.get_batch(batch_size, p_pos=p_faces)\n",
        "    # loss optimization\n",
        "    loss = debiasing_train_step(x, y)\n",
        "    \n",
        "    # plot the progress every 200 steps\n",
        "    if j % 500 == 0: \n",
        "      mdl.util.plot_sample(x, y, dbvae)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Starting epoch 20/20\n",
            "Recomputing the sampling probabilities\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\r  0%|          | 0/6869 [00:00<?, ?it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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2wdlmSxXqUhDNEEOYsqgSnYSUkZQRIwzDyJgD2+0WqgVd3z/4kplc2FTgMGqxDowoRjMi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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "  7%|▋         | 488/6869 [00:03<00:38, 165.97it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/ype+8lWGmEgusLO3x//9R/+C9370vrnUk4f4jJXIyjtmPort4H6hkzp/SAFn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\ny/8PQEWdIzPgkPUAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 14%|█▍        | 987/6869 [00:06<00:36, 159.87it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1klErzPPM48tL7j96VAcnfAxR1eourgu3YtddgSjCvNBAxnlmmhO5FNrgKhmv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\nGYmFCJiQAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 22%|██▏       | 1492/6869 [00:09<00:31, 170.77it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jVhTNM6UmvDcYDRgtHDYbGHr6RYeRHkqizhOa58aWEIGaES0susDJyvPkqrDd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\n8ieBt4E/8dEvpfyV//6v8N5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            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 29%|██▉       | 1988/6869 [00:12<00:28, 172.37it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SGKZCKYXVNDCMGWt7xgfOS3duMZvzzsVDXk9KW5Zr/OQJRYAiwpATm6Fw+2TiZFqHRVKh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\nlhslupGnlhslupGnlhslupGnlv8PbZaiLlXwtocAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 36%|███▌      | 2483/6869 [00:15<00:26, 165.51it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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KjejqMCOjU9vEvbPo+nAP3KS1Tk5Ol47qgHdHcmQU1jopFYxKmntkJLWiFJ4c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\notfy0vL/A7keNfhfN829AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 44%|████▎     | 2998/6869 [00:18<00:22, 171.14it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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K54cEWrmRJkYKcH56Rr/bIqmGexUjNp6UDdRY7C954cXnuX/3A9anZ7z39lt8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\n9v8DXyDBVF8fltcAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 51%|█████     | 3498/6869 [00:22<00:20, 164.98it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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nm9nojM7wfL/rySXXMjoboYsE1yF4VqsjVusjHjw4Z7/vEeeJoamyEy01lCuz\nRtlIRckmXGz2vPGt97m/HfjBl18lW2bcbnHicAGaxRPIY/lQDlJbla1+eaaMplyF8blArpHGnCFO\nMaogLaPklNE0UdJESQVTrQI1NZwq4sssda1bXTkMeXBzM6MqPtSPWg7Ie54oaSANA8NuZL+f2O5H\ndlNhKkpWpcwt3zb3zn2cfQ+2s7kcdQ5FmfJUcaAyMmXwxVG0qSrEqUeix7WR4jx53sOh0Pc70phJ\nQ3UoHzxeApqUZtXQxQXeNzTNguXyiM1uS0qF1TLMvTs2Yyuuir+0OlExuPvggsvNBnOeYtA0LZPs\nECd4ceSUHnu9BxL/IMqv2eoBlsjodSTKhJxQF3FSiV6dh33ZoSu35Dq7qNT8yjuHTPk6Dy76YWuR\nd3WCgzibp4RU8NLNCkdyxlKhTIk0JtKUyKmQS74mgrMBJoRH5IDPPLFuYos3Q6JHnTHmRCpCMUe2\niaSOXCY0DVgasN5B8ITFEnEVNe77PWipCy+K964OTPARFyLiPYvTE8qDczrnOFp0XF2d0489p+50\n7kAVskEpPdmUfRrZ58Rm7Ll/ecGuH/GLlgd373J0vASryLXzzEj4E6xaasmNcN20WPX2NWqUeVvL\nOePcVCtNFESu8ym7Hox1mBRXJbVYbYiZRdm1lUi4nlN06I41CqpV661qWEmkaSJNiSlNTCkxpkwq\ndi1DMerkkGKfIMTazGialjwNDLkOU9JcGPPEmAQfHcHqN8AplH5CtZ7IJo0oxq7f4aNnvVpxNQmu\nqToZCR7FmKaJ4Ec0jYy7Da0oZdzRNo7zy3OOTo5ZtB3OmCuUglrCBEYt9CnzzvvvU1C81EER4zCh\naWLRdIhU1P2x10ztllCd9c5ac40p14R+DBnvM8Fnip9mYe7sLiLoHAWccxTv8XMg02KoHKLp4fzq\nrBqoowMl1MFeVTVaK8CsBUpB08gw9ux3e7abnu1+YBhybdN2tQvHUVWRNf/8eHu2UhAnWMmzQH9G\nQ32g4BhLoZ3bf8ZpIjDSxBYrjjwWio4UU3x0rJYLzDIn6wX9esE7b3+LB9OImvHSCy8Tidx//32G\n3Z7L7YZ33n+Pt+9+wJ85OSJpwiWIOERz7TwZe8wcpVQy8s69K4rWKRmGQ/OhLceRc6mg3BNYtkIq\ngSlrFeSlzJgKY1ZimaORZrQkcnbzaBmbt6ODU1USV5wh3ubestondlCz2aG/zLvqigLOHKaKUJN5\nNGG5UHLtZtmNA5e7LVfbHZuhpy8JtTrNTaUqIsN3gvYQkTeBDXW0QDazL4nIDeC/Bz4LvAn8VTM7\nf8TrYAKr1Zo07BlLZh0jJorHIo8AAA7LSURBVDZ/W+sJTSmh9LWlyA+oFwiedtkRw7L2jc+w/+2z\nG0z7Ha+//nUU4c7773P3vXvcfuFF3n3nbd557y0uNpe88tnXODo+Yhh7JCdEAmnfk/sdKU3sdoUx\nJc6vNmz2A+/2CTducBc7vHP81Odfoij85tfeZ5gK1ClxZ49a86FB0KzMwONBMzTPAbJCMaVYodgE\nuU7u8AJCQFys7UFQsSOp80XUpBKkfCj2A+boNI+wOfSnWdVLax6hZLRkchoZx4H90HO123G527Ef\nJ9JUcy4TNwsID7Lej1/jk0Siv2Bm9z5y/8vAr5vZL85Dwb8M/CcPewGZaY8QA/2+sO8HTpanOFeV\ndTq3qiiGt4KVkWxUpLrpEKeUMpCnTIiVZwJ45dVPcXbjBkWN3XbPG994k9/+3d9hGke8j3z2s5/j\n05/7NMfrI8ZhwPkMeIbdljLVySOb3Y79YLx35wFjrlrqT926wXLRcNRGgnN845373Dzq+NHXbvPL\nv/EHm8dZswFTNrxXuqIVLpg/VKwmwgdUu1gdTqpaKkJtNRE2pHZpUIllF2uzvaggM+A4n+Fr1Lq+\nVAUwzRTKTJvkqQ69SBNDP7Dbbtlsd+z6nj4VktUhW1jVfl9PLHnIGp9mO/t54Gfn//93wP/xqBOK\ngA+e7X6LopxfXXLjZE27aHHRzwObaquvREF8bdERb2gZsRKYNOM0IFZwvsU5zzQlluszxHmOT+Ho\n5Bb7vmd3dUXa7zk6OsYiXN6/IgSHiZDKQB4GSk7s9hO7PnG1N+6cX9ZJUAglJ6LvECmE4LlzuePP\n/9AL5Nq9ex/4y49as5mRSiaUKoNNs4Z5HkCEoybDGSNY1VuZFopmrAjiHOoE8BVhr1wEruicJNdc\nx6A6pZbaGDe35Ne5FIparexMKy00pIl+Gtn2Pft+YOgTKecZE5J5MotcT1d7WCh6XCcy4H+TOrzv\nb8wjdl80s0NT+vvAi3/SEz8603m9aPDBk0sG77jcXNFPtzlaLOtwSVFUKlPuvOADiHcoME0JZV/D\nrPckn0gu0zVLjpZHpGSVuHWOs/WCdTuiq1N2Dy4Yp4ntdoAsbK52eC8cL5eIa5DgmCyTJXK13/Le\nnQfkUmuRDy633NvuefGk4/OvnjGmTJCMEw+QgM88as1tcOg8xi7lTCmFAjPwJ6jUZkU7TEYznTtT\nC1KM7AQp4FQoztehnEqFOqxOL8m5zhgy1QoLUHB+3hYDiD+0aCeKZZLluRpLDFNhyJmxZLJK7Zat\ne+d1JNLv0KS0f8bM3hGRF4BfE5F/9NFfmpnJx0yH/OhM59unK2PmcMygHwfOL684Xq5ZNJHoA8Wq\nqs5chQF88GhWSskMu8TFgytUjeVyjS8essP7hpSMNGUWiyXHR2v6Yc/V+Tk6Jlz0lAAX+yu2/ZZX\nX3uFtlmQcYyDsk/KUIy751dc7QZi0/LZrmHVCmqZ1+/uuHnSHVZ0iET1ziPWvG6DpaK47GZaQZlS\nrhzVTC3Eg/JL6gcv1LI860zJ5IpYYw4pOif6cx+fVQQ9lzrNpOQEzohdwDmhbR0u1ArLealbZanT\nQKZiDCnTT8qYlJTKPOhhhiNmgf7DGHx4TCcys3fm2zsi8neolyf4QEReNrP3RORl4M5jvBDFMlOa\n6lQQjDv37nO8WNHFSNd1dR6OzOjxPOOwirrgG19/nTff+CZWhLZZcOLWRA0E39E2S05OzrjXn3PX\nCuPUk1Nic7mBIFyVnnubB3zhn/hhXnv1NfrdhpQLQ1I2+8TlbuT1N96sKgMfCCETfQUBXzhtudoN\ntNExjBNdEwHi46zZMKZSkCQMTtgNI9v9wNGqZdE1tDnSmAKK5xChap6TkjGWTOpHcj+Rs6JjhlzJ\nYznonXKmTBNTHmskEgito4mRbt2yWLV0i0iRCoNkVcasDCmzGzL7MTFOhSEXkimGJ1BzWCfg7Slz\nIhFZAc7MNvP//yXgPwP+F+DfB35xvv3lR73WofJy88iYGBruPzjnaLFmvVwRguPkqM6dHlOhtdoL\nJd7Rtg0/+Wd+kh/5wo/x1jffRYonbZSonkW3pmRBdU5Ec+YktkxloF1HimRaF3ntMy/wmR/6Abxk\nEGWcEg8u9wzqefede1ycbxiGidAE1scrzCZGHbm/UT7/8pLbR4Fv3dvyY6/dArgJ/K1HrdkMxqxA\nJjpj10/s+ol+TKQxUxa18qmA6Zx5zGihoEipFV0qmXE/UPqEZKvNCITat5dG0jSSpxHVhInRD0K7\niMR2Fru5DhMja2Yyox8n9sNYt7Jc6Euu1xywOmLMxCFW4QX/HRhB/CLwd2aJZAD+lpn9ryLyFeB/\nEJH/APgm8FcffUIr+942LarQuMhVNv7wW2/jQkT9K+ADJ25R5RlTAqs8kQtCG1vado1Yx/vv3qcM\nI8OQ0JL53Oe+wK1bL3HxwV3Kvifve8b9jsvtfTbjJQFjuQwU7dnurtj3iSkbxRznFxu++rWvoaac\nHB9B8PzeH76PagaBF04DL5y0nHWO3/7DHX/vq3cBjqlfoEesGXIpODGmDEMu7JOyGxO7cWIxTizG\nSG4akvdE8bWtB6HxgdA5GhdITUNqWsoqIRm8CzhxUISSm/oztBTJ9TwDYRlZrpa0bYMLjiGP9MPA\n1dWOi6sd9zcj9/vMxVgYClW7NQtdTA2RSnRXF3qKliEzewP4iT/h8fvAv/Co53/UVJU0JZqmpaRC\nMEeIkQ/u3GEqdbSbE8V7Y7WM7KcM3hOdYMUQlwniWR0veQnHZbPh/gcP2E8b3r//LhIFH6FZR9QG\n0tAzuh05jKyOOtZna/CezW6kH41hUPox86233uZqs8XFBd2iY7Fs+VFOGcYLTk8XRF/f3wM//lLt\n6/+V3737dTN7jH7qmjgXNZIa4+xAl9uBNgSaWDXTMR4aGj3OHIGay4TgCK6h8Z7JOSwVKIbgkVKH\nQVTi2mHeo24emSeCbxvissOFQCnKfkxcbfZcXFxy/3zHg8sNF5uBbZ8ZCmSrOF7V8tW8dL52w0NX\n+MwJ2P1+T9O2KMpm6OswAyfcvfeAr33j64QIMRourGnlmOKbykBbYcwJCbUojq1xemuJD3B5tWPT\nX7J/a8eqW1D6AXJCdcQfO24uT1ker0nOGEpCxTEVRzLPe3fO+cab72BSrzpUSuHi4oL9dkPbOrw6\nKIUiWieGiCNPj0/AAnXgODCpMebCfhi42hmNN9ogdFFoo8d5TzFHY5U9FyLiIYjDN55gEfOekue+\neStoqXiToJg/XC0JYhdxscG3kYIxjBPjfmC73XGx6XlwteXiYsN2V0HfXCrgW6VGtbvlMJn/4Wqi\n74ETbbdb2q6rPFSYEIXj02Me3L/Hg/Nz3vjD19G8I+kruGULocH5hhgDMg9aCM7hWqUJntP2iOao\nYb8fK9ahI91ZQ6TB0dGu6hBRXO3UGKc6skVFePv9u/zmb3+VD+6dU8zRBkg5cXV5ThuERWywXOrw\nico8VCFcfjInQm2+xlG5pj32g7ANnlU7sF7E2vUR4rVYTFBoIPpYKysTXNNgwZCkSKpdME6Noh4s\n1EtMOWpEb6rUOBvkokwpset7zi+33H+w4cHFjsvdSD/V9u2DZKji3XVr80odyv7woSDPnoA9DEco\nMRCbwDhO9dobiwYrE32/473338U5Be/Ic/g+Wq1oY6zcjyjirV50pwhtiIR1wyqDpkLXRRpXB0E5\nr/RjnRCrpRA00e8Hzi9G/uCNr/HOe+8ylQpwBlOmvseJsOiaOlAz6TyPQZimjAu1HefxTeYLs9Ss\nQqly2XHKtbOkHVm2kcbHCuhofa/K9DgCoTZ9eo/YfNmFYEicL0HhEi5moKkjiX2lKurlG8BUSZoZ\npsx2O/LgwY6796+4f7VjsxvYj/VKBBVjdNcDPgXma4YcptB+vH1vnCglkv/wUgExCDG4+Wo/gZwS\n9+7cqfjQMFH6AXnhRcLJEc4J2TJt9PgYCBJZuAi+QYsgtTkBy7nOBJob98SNTPsteRrZXG146633\nuHv3LbKOjBP4JrDvB8ZxpA1yfQUgUqlMvwhWFJkHTD2JFdx8fYy6DY250CQYQ2LfT+zagdbX2dWB\neTSf1Ut4WdPUC98cLrflI84gqECjxIUhJVFpzXmkn+W6bi3YVMhZGcaJy6sNF1dbLjZ7Lvc9+yEz\nTMpUT1Ald+cvjKOey2uJwEPsmQ/+TGni8vISsTVt41EVMKVrIp7aNnx2vETTxOW9e+iY6C+3eBUC\ncHSyrCNP3Ew2OiO0kdh0VRVgdXzL1PeUacI04H1XpZ4KJWfO79/hzgdvMU1b6vUx/JznVCrBe4+W\nCi1AHe2izoixoe26mRZ5TJMq8fdSR9xRDNOqMy8JUlb6Udn6BG6iiR0uFMRlmnnbUgeNc1UvJR5x\nAecdFiAoSMmzpKVWgaVkMomSE33O9JPQD0Y/ar26EqG+DnV4lrp6TAIfkr+zKNILj/zSfNsXEv52\nTEQ2wNee2Rs+ud0C7j3yr6p9xsxuP+qP/hSt+WPX+6wT66+Z2Zee8Xs+tonIb34Xju9P/ZqfrPfl\nuT23P8GeO9Fze2p71k70S8/4/Z7UvhvH96d+zc80sX5ufzrt+Xb23J7anjvRc3tqe2ZOJCJ/SUS+\nJiKvz8L+76mJyJsi8nsi8tsi8pvzYzdE5NdE5A/m27OnfI/vjzVfdwd8F3+oY6G/Afwg0AC/A3zx\nWbz3Q47pTeDWH3vsvwK+PP//y8B/+XzNj/55VpHop4HXzewNM5uAv03tFvmk2c9TO1eYb//yU7zW\n982an5UTvQq89ZH7b8+PfS/t0MHyW3N3BjxmB8tj2vfNmp/9MPRPjn3bHSz/GNt3Zc3PKhK9A7z2\nkfufmh/7npl9pIMF+CMdLACP3cHy8fZ9s+Zn5URfofau/4CINMBfo3aLfE9MRFYicnT4P7WD5R/y\nYQcLPGYHy0Ps+2fNz7Ay+Dng69SK5T/9HlcpP0itln4H+P3D8VDbgH4d+APg7wI3nq/50T/PaY/n\n9tT2HLF+bk9tz53ouT21PXei5/bU9tyJnttT23Mnem5Pbc+d6Lk9tT13ouf21Pb/ARuDkxUiOug5\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 58%|█████▊    | 3995/6869 [00:25<00:17, 167.94it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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RZNpglCJTGhUFIkpClEhlIMBsbw/vLRsbm8wXFd61lOWc8fIKVZ3AaIv57M4X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\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 65%|██████▌   | 4486/6869 [00:28<00:14, 166.65it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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mwLJvuH18zJ1ly+6w59f/0W/yme/9Hv7I934Pp8dHHG2WtHWFNQbnSl5lkoIqYQqknMkp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\ngg==\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 73%|███████▎  | 4999/6869 [00:31<00:11, 168.55it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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4+YJawzNPX2E0Gt87O7uvCGCsBSN4DCRIkj/tRhWIqIIVi7UW7wyFd1R1rrJmTcnWeMTW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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 80%|███████▉  | 5488/6869 [00:34<00:08, 165.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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yGs00F0rJNWlfRAKqlfT2cfbMc6JSIGpiNo5WPOMwcrW/5LA15K1yc3MD7xpy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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 87%|████████▋ | 5996/6869 [00:37<00:05, 164.58it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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b9HzOkfOcVCta3YJYLZj63zbiSKuzOWKuWtC6+J5NC9M0shunZomWxjt3GOFD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\nYrlUokt5YrlUokt5YrlUokt5Yvn/ASWLEKDYM24/AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            " 94%|█████████▍| 6486/6869 [00:40<00:02, 171.05it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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d7BQLOWZKLKRhopRK9BpDxAE2JWLcsVx1dQqJdfXzVFPpzgJGHKCUkhE1M9VC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\nuydoM3AAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 144x72 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 6869/6869 [00:43<00:00, 158.55it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FdcjcyI2bdpv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "outputId": "23171cef-6585-4db0-eef5-bd98e351ffb1"
      },
      "source": [
        "dbvae_logits = [dbvae.predict(np.array(x, dtype=np.float32)) for x in test_faces]\n",
        "dbvae_probs = tf.squeeze(tf.sigmoid(dbvae_logits))\n",
        "\n",
        "xx = np.arange(len(keys))\n",
        "plt.bar(xx, standard_classifier_probs.numpy().mean(1), width=0.2, label=\"Standard CNN\")\n",
        "plt.bar(xx+0.2, dbvae_probs.numpy().mean(1), width=0.2, label=\"DB-VAE\")\n",
        "plt.xticks(xx, keys); \n",
        "plt.title(\"Network predictions on test dataset\")\n",
        "plt.ylabel(\"Probability\"); plt.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\");\n"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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YQHKEXq4pQH9JB5Ik/POA8wuFEbGW5Pa/he1MAq5y0jczM8tOo0P9EbENmCtp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\n5YgTv5mZWY448ZuZmeWIE7+ZmVmO/H/BqPEm2qLHYwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}