Demo_Variational_Autoencoders.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Demo - VAEs - Variational Auto Encoders\n",
        "\n",
        "# Data Saturday BH\n",
        "\n",
        "Dr. Ahirton Lopes\n",
        "\n",
        "* Introdução\n",
        "\n",
        "Os Variational Autoencoders (VAEs) são um tipo de rede neural generativa que aprende a representar dados em um espaço latente de menor dimensão. Essa representação latente pode ser utilizada para gerar novos dados que se assemelham aos dados de treinamento. No contexto da moda, VAEs podem ser empregados para criar novos designs de roupas a partir de um conjunto de exemplos existentes.\n",
        "\n",
        "* O Dataset Fashion MNIST\n",
        "\n",
        "O Fashion MNIST é um dataset composto por 70.000 imagens em preto e branco de 28x28 pixels, representando 10 categorias diferentes de roupas. Ele é frequentemente utilizado como um ponto de partida para experimentos em aprendizado de máquina, pois é mais desafiador que o dataset MNIST original (dígitos escritos à mão)."
      ],
      "metadata": {
        "id": "Z-Qa3twPlpHR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "* O que são Variational Autoencoders?\n",
        "\n",
        "Encoder: A primeira parte de um VAE, que mapeia as imagens de entrada para um espaço latente.\n",
        "\n",
        "Espaço Latente: Um espaço de menor dimensão onde cada ponto representa uma possível imagem.\n",
        "\n",
        "Decoder: A segunda parte de um VAE, que mapeia os pontos do espaço latente de volta para imagens.\n",
        "Por que usar VAEs?\n",
        "\n",
        "Geração de Novos Dados: VAEs podem gerar novas imagens que se assemelham aos dados de treinamento, mas não são cópias exatas.\n",
        "\n",
        "Inferência: VAEs podem ser usados para inferir propriedades latentes dos dados, como o estilo ou a categoria de uma imagem.\n",
        "\n",
        "Interpolação: É possível interpolar entre dois pontos no espaço latente para criar novas imagens que são uma mistura dos dois pontos originais."
      ],
      "metadata": {
        "id": "oqDvX-3rGRj1"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "R1NzQtVnk9tZ"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "import tensorflow as tf\n",
        "import os\n",
        "import random"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oh9UakY4k9te"
      },
      "outputs": [],
      "source": [
        "# Use randomseed para resultados mais consistentes\n",
        "SEED = 42\n",
        "os.environ['PYTHONHASHSEED']=str(SEED)\n",
        "os.environ['TF_CUDNN_DETERMINISTIC'] = '1'  # flag presente no tf 2.0+\n",
        "random.seed(SEED)\n",
        "np.random.seed(SEED)\n",
        "tf.random.set_seed(SEED)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zO3_r_0wk9tj",
        "outputId": "82da33a9-c70f-49bc-eae0-eba9613d70bf"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n",
            "\u001b[1m29515/29515\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n",
            "\u001b[1m26421880/26421880\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n",
            "\u001b[1m5148/5148\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n",
            "\u001b[1m4422102/4422102\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 0us/step\n",
            "(60000, 28, 28)\n",
            "(10000, 28, 28)\n"
          ]
        }
      ],
      "source": [
        "from tensorflow.keras.datasets import fashion_mnist\n",
        "\n",
        "\n",
        "(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()\n",
        "print(x_train.shape)\n",
        "print(x_test.shape)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JUJHILpjk9tf"
      },
      "source": [
        "<h2>Available Labels/Classes in Fashion Mnist dataset</h2>\n",
        "\n",
        "<table align=\"left\">\n",
        "<thead>\n",
        "<tr>\n",
        "<th align=\"center\">Label</th>\n",
        "<th>Description</th>\n",
        "</tr>\n",
        "</thead>\n",
        "<tbody>\n",
        "<tr>\n",
        "<td align=\"center\">0</td>\n",
        "<td>T-shirt/top</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">1</td>\n",
        "<td>Trouser</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">2</td>\n",
        "<td>Pullover</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">3</td>\n",
        "<td>Dress</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">4</td>\n",
        "<td>Coat</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">5</td>\n",
        "<td>Sandal</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">6</td>\n",
        "<td>Shirt</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">7</td>\n",
        "<td>Sneaker</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">8</td>\n",
        "<td>Bag</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td align=\"center\">9</td>\n",
        "<td>Ankle boot</td>\n",
        "</tr>\n",
        "</tbody>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 643
        },
        "id": "CpzPJyCrk9tl",
        "outputId": "7b537f3e-74d9-41f6-99f4-92ceacb264bd"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x900 with 9 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(9, 9))\n",
        "\n",
        "# Escolhendo 9 amostras de 60K disponíveis no conjunto de treino\n",
        "rndSamples = np.random.choice(60000, 9)\n",
        "\n",
        "for i in range(9):\n",
        "    plt.subplot(3,3,i+1)\n",
        "    plt.imshow(x_train[rndSamples[i]], cmap=\"Greys_r\")\n",
        "    plt.axis('off')\n",
        "\n",
        "plt.show();"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aboBC-krk9tn"
      },
      "outputs": [],
      "source": [
        "dataset = np.concatenate([x_train, x_test], axis=0)\n",
        "# Converte imagens de 28x28 para 28x28x1 como camadas convolucionais esperam 3 canais\n",
        "dataset = np.expand_dims(dataset, -1).astype(\"float32\") / 255"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cmq1-2gzk9tp"
      },
      "outputs": [],
      "source": [
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "\n",
        "\n",
        "# Crie uma camada de amostragem onde definimos a reparametrização\n",
        "class SamplingLayer(layers.Layer):\n",
        "  \"\"\"Reparameterization Trick z = mu + sigma * epsilon\"\"\"\n",
        "\n",
        "  def call(self, inputs):\n",
        "    zMean, zLogVar = inputs\n",
        "    batch = tf.shape(zMean)[0]\n",
        "    dim = tf.shape(zMean)[1]\n",
        "    epsilon = tf.keras.backend.random_normal(shape=(batch, dim))\n",
        "    return zMean + tf.exp(0.5 * zLogVar) * epsilon"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "id": "eMH3U9lRk9tr",
        "outputId": "95d1bd4d-8092-4c39-f877-ea7ca12cadb9"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1mModel: \"encoder\"\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"encoder\"</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
              "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)             \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m       Param #\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mConnected to          \u001b[0m\u001b[1m \u001b[0m┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
              "│ input_layer (\u001b[38;5;33mInputLayer\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m1\u001b[0m)      │              \u001b[38;5;34m0\u001b[0m │ -                      │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ sequential (\u001b[38;5;33mSequential\u001b[0m)   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m)            │        \u001b[38;5;34m878,144\u001b[0m │ input_layer[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]      │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ z_mean (\u001b[38;5;33mDense\u001b[0m)            │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2\u001b[0m)              │            \u001b[38;5;34m514\u001b[0m │ sequential[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]       │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ z_log_var (\u001b[38;5;33mDense\u001b[0m)         │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2\u001b[0m)              │            \u001b[38;5;34m514\u001b[0m │ sequential[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]       │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ sampling_layer            │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2\u001b[0m)              │              \u001b[38;5;34m0\u001b[0m │ z_mean[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m],          │\n",
              "│ (\u001b[38;5;33mSamplingLayer\u001b[0m)           │                        │                │ z_log_var[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]        │\n",
              "└───────────────────────────┴────────────────────────┴────────────────┴────────────────────────┘\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
              "┃<span style=\"font-weight: bold\"> Layer (type)              </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">        Param # </span>┃<span style=\"font-weight: bold\"> Connected to           </span>┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
              "│ input_layer (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">InputLayer</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)      │              <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ -                      │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ sequential (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Sequential</span>)   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">878,144</span> │ input_layer[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]      │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ z_mean (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)            │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">514</span> │ sequential[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]       │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ z_log_var (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)         │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">514</span> │ sequential[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]       │\n",
              "├───────────────────────────┼────────────────────────┼────────────────┼────────────────────────┤\n",
              "│ sampling_layer            │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2</span>)              │              <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ z_mean[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>],          │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">SamplingLayer</span>)           │                        │                │ z_log_var[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]        │\n",
              "└───────────────────────────┴────────────────────────┴────────────────┴────────────────────────┘\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m879,172\u001b[0m (3.35 MB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">879,172</span> (3.35 MB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m879,172\u001b[0m (3.35 MB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">879,172</span> (3.35 MB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "def buildEncoder(latentDim, encoderInputs):\n",
        "\n",
        "# Dado um batch de imagens, o bloco convolucional extrai os recursos\n",
        "  l1 = keras.models.Sequential([\n",
        "    layers.Conv2D(128, 3, activation=\"relu\", strides=2, padding=\"same\"),\n",
        "    layers.Conv2D(64, 3, activation=\"relu\", strides=2, padding=\"same\"),\n",
        "    layers.Flatten(),\n",
        "    layers.Dense(256, activation=\"relu\")\n",
        "  ])\n",
        "\n",
        "#passa as entradas pelo bloco convolucional\n",
        "  x = l1(encoderInputs)\n",
        "\n",
        "# uma camada dedicada para aprender a média em paralelo\n",
        "  zMean = layers.Dense(latentDim, name=\"z_mean\")(x)\n",
        "\n",
        "# uma camada dedicada para aprender a variação em paralelo\n",
        "  zLogVar = layers.Dense(latentDim, name=\"z_log_var\")(x)\n",
        "\n",
        "# agora o truque de reparametrização para encontrar z como definido por média e variância\n",
        "  z = SamplingLayer()([zMean, zLogVar])\n",
        "\n",
        "  return keras.Model(encoderInputs, [zMean, zLogVar, z], name=\"encoder\")\n",
        "\n",
        "\n",
        "# aciona a função para realmente construir o modelo\n",
        "encoderInputs = keras.Input(shape=(28, 28, 1))\n",
        "encoder = buildEncoder(2, encoderInputs)\n",
        "encoder.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 251
        },
        "id": "EUkCB_o6k9ts",
        "outputId": "7c2f7eea-230a-45f4-bb22-d7121948bd07"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
            "  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1mModel: \"decoder\"\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"decoder\"</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
              "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                        \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape               \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m        Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
              "│ input_layer_2 (\u001b[38;5;33mInputLayer\u001b[0m)           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2\u001b[0m)                   │               \u001b[38;5;34m0\u001b[0m │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ sequential_1 (\u001b[38;5;33mSequential\u001b[0m)            │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m1\u001b[0m)           │         \u001b[38;5;34m157,633\u001b[0m │\n",
              "└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
              "┃<span style=\"font-weight: bold\"> Layer (type)                         </span>┃<span style=\"font-weight: bold\"> Output Shape                </span>┃<span style=\"font-weight: bold\">         Param # </span>┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
              "│ input_layer_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">InputLayer</span>)           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2</span>)                   │               <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ sequential_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Sequential</span>)            │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">28</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)           │         <span style=\"color: #00af00; text-decoration-color: #00af00\">157,633</span> │\n",
              "└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m157,633\u001b[0m (615.75 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">157,633</span> (615.75 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m157,633\u001b[0m (615.75 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">157,633</span> (615.75 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "def buildDecoder(latentInputs):\n",
        "\n",
        "  l1 = keras.models.Sequential([\n",
        "    layers.Dense(7*7*64, activation=\"relu\", input_shape=(latentInputs.shape[1],)),\n",
        "    layers.Reshape((7,7,64)),\n",
        "    layers.Conv2DTranspose(128, 3, activation=\"relu\", strides=2, padding=\"same\"),\n",
        "    layers.Conv2DTranspose(64, 3, activation=\"relu\", strides=2, padding=\"same\"),\n",
        "    layers.Conv2DTranspose(1, 3, activation=\"sigmoid\", padding=\"same\")\n",
        "  ])\n",
        "\n",
        "  return keras.Model(latentInputs, l1(latentInputs), name=\"decoder\")\n",
        "\n",
        "# construindo o modelo real\n",
        "latentInputs = keras.Input(shape=(2,))\n",
        "decoder = buildDecoder(latentInputs)\n",
        "decoder.summary()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_B6pv8igk9tu"
      },
      "source": [
        "## Funções de perda (loss)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "C8JblcfMk9tu"
      },
      "outputs": [],
      "source": [
        "# A função de primeira perda é a perda de reconstrução, que penaliza imagens que não sejam semelhantes às imagens originais.\n",
        "\n",
        "def reconstructionLoss(data, reconstructed):\n",
        "  return tf.reduce_mean(\n",
        "      tf.reduce_sum(\n",
        "          keras.losses.binary_crossentropy(data, reconstructed),\n",
        "          axis=(1, 2)\n",
        "      )\n",
        "  )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fiN-wrmfk9tw"
      },
      "outputs": [],
      "source": [
        "# Função de perda de divergência de Kullback-Liebler que penaliza o modelo se ele aprender\n",
        "# uma distribuição de probabilidade \"z\" diferente da distribuição de probabilidade original dos dados \"X\".\n",
        "\n",
        "def klDivergenceLoss(zMean, zLogVar):\n",
        "  return tf.reduce_mean(\n",
        "      tf.reduce_sum(\n",
        "          -0.5 * (1 + zLogVar - tf.square(zMean) - tf.exp(zLogVar)),\n",
        "          axis=1\n",
        "      )\n",
        "  )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QPAl6tHgk9tx"
      },
      "outputs": [],
      "source": [
        "# Agora vamos combiná-los na função de perda total\n",
        "\n",
        "def calcTotalLoss(data, reconstructed, zMean, zLogVar):\n",
        "  loss1 = reconstructionLoss(data, reconstructed)\n",
        "  loss2 = klDivergenceLoss(zMean, zLogVar)\n",
        "  klWeight = 3.0\n",
        "  return  loss1, loss2, loss1 + klWeight * loss2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HG9zQjQMk9ty"
      },
      "outputs": [],
      "source": [
        "# Como estamos usando uma função de perda personalizada em mu e sigma, precisamos substituir como a perda é calculada.\n",
        "# Precisamos comparar X_original e X_reconstructed ao mesmo tempo enquanto calculamos a perda de Kullback-Liebler (KL).\n",
        "\n",
        "class VAE(keras.Model):\n",
        "  def __init__(self, encoder, decoder, **kwargs):\n",
        "    super(VAE, self).__init__(**kwargs)\n",
        "    self.encoder = encoder\n",
        "    self.decoder = decoder\n",
        "    # registra a perda total como uma métrica observável no histórico de treinamento do modelo\n",
        "    self.totalLossTracker = keras.metrics.Mean(name=\"total_loss\")\n",
        "    self.ceLossTracker = keras.metrics.Mean(name=\"ce_loss\")\n",
        "    self.klLossTracker = keras.metrics.Mean(name=\"kl_loss\")\n",
        "\n",
        "  # Todas sendo métricas observáveis\n",
        "  @property\n",
        "  def metrics(self):\n",
        "    return [\n",
        "        self.totalLossTracker,\n",
        "        self.ceLossTracker,\n",
        "        self.klLossTracker\n",
        "    ]\n",
        "\n",
        "  # Agora calcule a perda + calcule os gradientes + atualize os pesos\n",
        "  def train_step(self, data):\n",
        "    # A fita de gradiente é uma gravação de todos os gradientes para o treinável\n",
        "    # pesos que precisam ser atualizados\n",
        "    with tf.GradientTape() as tape:\n",
        "\n",
        " # caminho para frente\n",
        "        zMean, zLogVar, z = self.encoder(data)\n",
        "        reconstruction = self.decoder(z)\n",
        "        ceLoss, klLoss, totalLoss = calcTotalLoss(data, reconstruction, zMean, zLogVar)\n",
        "\n",
        " # caminho para trás\n",
        "\n",
        "    grads = tape.gradient(totalLoss, self.trainable_weights)\n",
        "    self.optimizer.apply_gradients(zip(grads, self.trainable_weights))\n",
        "\n",
        "# acompanhando a perda\n",
        "\n",
        "    self.totalLossTracker.update_state(totalLoss)\n",
        "    self.ceLossTracker.update_state(ceLoss)\n",
        "    self.klLossTracker.update_state(klLoss)\n",
        "\n",
        "# retorna a perda do objeto histórico\n",
        "\n",
        "    return {\n",
        "        \"total_loss\": self.totalLossTracker.result(),\n",
        "        \"ce_loss\": self.ceLossTracker.result(),\n",
        "        \"kl_loss\": self.klLossTracker.result()\n",
        "    }"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bR-0p50Ok9ty"
      },
      "source": [
        "## Treinando o modelo"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fON4Z63rk9tz",
        "outputId": "c5b96e22-0b87-4022-fed1-5ba25d45917f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m15s\u001b[0m 17ms/step - ce_loss: 351.4058 - kl_loss: 2.7772 - total_loss: 359.7373\n",
            "Epoch 2/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 13ms/step - ce_loss: 266.0986 - kl_loss: 4.5256 - total_loss: 279.6754\n",
            "Epoch 3/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 13ms/step - ce_loss: 262.1526 - kl_loss: 4.6852 - total_loss: 276.2082\n",
            "Epoch 4/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 13ms/step - ce_loss: 260.1123 - kl_loss: 4.7780 - total_loss: 274.4464\n",
            "Epoch 5/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 258.8289 - kl_loss: 4.8356 - total_loss: 273.3358\n",
            "Epoch 6/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 258.1751 - kl_loss: 4.8849 - total_loss: 272.8300\n",
            "Epoch 7/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 257.2513 - kl_loss: 4.9348 - total_loss: 272.0557\n",
            "Epoch 8/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 13ms/step - ce_loss: 256.5034 - kl_loss: 4.9636 - total_loss: 271.3943\n",
            "Epoch 9/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 255.8089 - kl_loss: 4.9951 - total_loss: 270.7945\n",
            "Epoch 10/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 255.4658 - kl_loss: 5.0180 - total_loss: 270.5197\n",
            "Epoch 11/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 254.8939 - kl_loss: 5.0470 - total_loss: 270.0350\n",
            "Epoch 12/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 254.6113 - kl_loss: 5.0600 - total_loss: 269.7913\n",
            "Epoch 13/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 254.3129 - kl_loss: 5.0866 - total_loss: 269.5728\n",
            "Epoch 14/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 253.9343 - kl_loss: 5.0897 - total_loss: 269.2035\n",
            "Epoch 15/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 253.6600 - kl_loss: 5.0910 - total_loss: 268.9331\n",
            "Epoch 16/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 253.3016 - kl_loss: 5.1355 - total_loss: 268.7081\n",
            "Epoch 17/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 252.9858 - kl_loss: 5.1517 - total_loss: 268.4409\n",
            "Epoch 18/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 252.6887 - kl_loss: 5.1668 - total_loss: 268.1890\n",
            "Epoch 19/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 252.6684 - kl_loss: 5.1718 - total_loss: 268.1838\n",
            "Epoch 20/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 14ms/step - ce_loss: 252.3252 - kl_loss: 5.1858 - total_loss: 267.8826\n",
            "Epoch 21/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 252.1830 - kl_loss: 5.1868 - total_loss: 267.7437\n",
            "Epoch 22/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 252.0085 - kl_loss: 5.1986 - total_loss: 267.6044\n",
            "Epoch 23/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 251.8351 - kl_loss: 5.2183 - total_loss: 267.4901\n",
            "Epoch 24/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 251.6126 - kl_loss: 5.2093 - total_loss: 267.2406\n",
            "Epoch 25/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 251.7966 - kl_loss: 5.2159 - total_loss: 267.4442\n",
            "Epoch 26/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 251.6664 - kl_loss: 5.2290 - total_loss: 267.3532\n",
            "Epoch 27/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 14ms/step - ce_loss: 251.2979 - kl_loss: 5.2411 - total_loss: 267.0211\n",
            "Epoch 28/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 251.1205 - kl_loss: 5.2469 - total_loss: 266.8613\n",
            "Epoch 29/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 251.1400 - kl_loss: 5.2411 - total_loss: 266.8632\n",
            "Epoch 30/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 250.8496 - kl_loss: 5.2564 - total_loss: 266.6188\n",
            "Epoch 31/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step - ce_loss: 250.7921 - kl_loss: 5.2652 - total_loss: 266.5874\n",
            "Epoch 32/32\n",
            "\u001b[1m547/547\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 14ms/step - ce_loss: 250.6008 - kl_loss: 5.2634 - total_loss: 266.3910\n"
          ]
        }
      ],
      "source": [
        "vae = VAE(encoder, decoder)\n",
        "vae.compile(optimizer=keras.optimizers.Adam(learning_rate=0.001))\n",
        "history = vae.fit(dataset, epochs=32, batch_size=128)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eAykBihvk9t0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 574
        },
        "outputId": "2bb4bdcc-7cca-46de-e580-518006087dae"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x900 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(10, 9))\n",
        "plt.plot(history.history.get('total_loss'), label=\"total loss\")\n",
        "plt.plot(history.history.get('ce_loss'), label=\"reconstruction loss\")\n",
        "plt.plot(history.history.get('kl_loss'), label=\"KL loss\")\n",
        "plt.legend();"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "N9YhgCVWk9t2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 577
        },
        "outputId": "80178bc6-ff11-42e6-8921-4bb17f1b016b"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x900 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Vamos ampliar a perda de KL para que possamos ver melhor\n",
        "\n",
        "plt.figure(figsize=(10, 9))\n",
        "plt.plot(history.history.get('kl_loss'), label=\"KL loss\")\n",
        "plt.legend();"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PomB6hK3k9t2"
      },
      "source": [
        "# Resultados\n",
        "\n",
        "Após treinar o modelo, podemos gerar novas imagens amostrando pontos aleatórios do espaço latente e passando-os pelo decoder. Podemos também visualizar o espaço latente em 2D para entender como as diferentes classes de roupas estão distribuídas.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5faUa2zUk9t3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "outputId": "2ca5cc56-060a-451c-bc36-278880d78432"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m4/4\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 153ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2800x2800 with 100 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ],
      "source": [
        "z = np.random.normal(loc=0, scale=4, size=(100,2))\n",
        "synth = vae.decoder.predict(z)\n",
        "\n",
        "plt.figure(figsize=(28,28))\n",
        "\n",
        "for i in range(100):\n",
        "    plt.subplot(10,10,i+1)\n",
        "    plt.imshow(synth[i].reshape((28,28)), cmap=\"Greys_r\")\n",
        "    plt.axis('off')\n",
        "\n",
        "plt.show();"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1o_dAHK9k9t4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6d0b62a1-ee84-42b5-c4e7-a4958f345263"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(1, 28, 28, 1)\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 498ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 235ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.4089772 , 0.30041736]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "# Mapearemos uma imagem de uma categoria através do codificador e observaremos a saída.\n",
        "# Em seguida, usaremos essas saídas para instruir condicionalmente o decodificador a amostrar de uma categoria específica.\n",
        "\n",
        "idx = 1280 # arbitrariamente\n",
        "batch = np.expand_dims(x_train[idx], axis=0)\n",
        "batchOfImages = np.expand_dims(batch, axis=-1).astype(\"float32\") / 255\n",
        "print(batchOfImages.shape)\n",
        "\n",
        "# obtém z(mu,sigma) para a imagem dada\n",
        "_, _, z = vae.encoder.predict(batchOfImages)\n",
        "\n",
        "# agora reconstrua uma imagem semelhante\n",
        "synth = vae.decoder.predict([z])\n",
        "\n",
        "z"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QGpnMCoOk9t7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "8d57b7b5-be25-4523-b2fb-7cced210e779"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2800x2800 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(28, 28))\n",
        "\n",
        "# imagem original\n",
        "plt.subplot(1,2,1)\n",
        "plt.axis('off')\n",
        "plt.imshow(x_train[idx], cmap=\"Greys_r\")\n",
        "\n",
        "# imagem reconstruída\n",
        "plt.subplot(1,2,2)\n",
        "plt.axis('off')\n",
        "plt.imshow(synth[0].reshape((28,28)), cmap=\"Greys_r\")\n",
        "plt.show();"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 647
        },
        "id": "y3XAuCcck9t7",
        "outputId": "ac486b2c-0ec7-40dc-9a5a-c1c341872f84"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:tensorflow:5 out of the last 7 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x799b3a2856c0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m2188/2188\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "\"\"\"\n",
        "O VAE pode ser usado no aprendizado não supervisionado de texto grande ou corpus de imagens não rotuladas de modo a agrupar as amostras em categorias\n",
        "\"\"\"\n",
        "\n",
        "labels = np.concatenate([y_train, y_test], axis=0)\n",
        "meu, _, _ = vae.encoder.predict(dataset)\n",
        "plt.figure(figsize=(12, 10))\n",
        "plt.scatter(meu[:, 0], meu[:, 1], c=labels)\n",
        "plt.colorbar()\n",
        "plt.xlabel(\"meu[0]\")\n",
        "plt.ylabel(\"meu[1]\")\n",
        "plt.show();"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.5"
    },
    "colab": {
      "provenance": []
    },
    "accelerator": "GPU"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}