autoencoders_var.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9haJqZAjvWhv"
      },
      "source": [
        "Adaptado para ser utilizado em finalidade acadêmica por Bruno Menezes de:\n",
        "\n",
        "Deep Learning Models -- A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.\n",
        "- Author: Sebastian Raschka\n",
        "- GitHub Repository: https://github.com/rasbt/deeplearning-models"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AMPPGVipvWhz"
      },
      "source": [
        "# 05 -- Variational Autoencoder"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qieB2466vWh0"
      },
      "source": [
        "A simple variational autoencoder that compresses 768-pixel MNIST images down to a 15-pixel latent vector representation."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bfp_kZNZvWh1"
      },
      "source": [
        "## Imports"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "q_Klu0NRvWh1"
      },
      "outputs": [],
      "source": [
        "import time\n",
        "import numpy as np\n",
        "import torch\n",
        "import torch.nn.functional as F\n",
        "from torch.utils.data import DataLoader\n",
        "from torchvision import datasets\n",
        "from torchvision import transforms\n",
        "\n",
        "\n",
        "if torch.cuda.is_available():\n",
        "    torch.backends.cudnn.deterministic = True"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475,
          "referenced_widgets": [
            "6207c21a7373494799f19c6e54a03954",
            "e34c050f8d374c928aa13f2befbb0eab",
            "490cd4776ba14996918082fa8b2e977d",
            "f0cf9e7400aa40ab8c2e28a8d81aa956",
            "dfd8b2989c8c4cbca55145a778e27bde",
            "8141a41599aa4acbac909c4a65f7923c",
            "8666774ae39b45b2958ce08b62064394",
            "a1f3f753a38f481dad4b7140bba02c7c",
            "28492675799c4b0082d6088a03f9a8c4",
            "1d4a875c10b246fcbbaec0ceb83d0704",
            "e98940de978b466eb92cc58fa2dc62d1",
            "a403f74f46cb41c18ab462b73b408b27",
            "f269b4a518dd4524807341e6e3ad1790",
            "f57b9c6fec6e44b281615ffa2f094f6a",
            "7151a694cdeb45019ac570cbd96e15b0",
            "aac5762637e5466f86b24568cb9e5734",
            "ac128039a9504549b23977c0c511a987",
            "1cf555f5008941e48bc350a7bb29f609",
            "a621b3e9088e455493a7da17d6c5ddd8",
            "1b014a268b2a4b3bb2c2a31be32db98e",
            "413b05cfc82f4e308ce019c88d8fde79",
            "9e33cad7f595414aab11f0e30dfbf788",
            "285197313d734ca3967593eddf7ad08f",
            "612ae9dc40664b08b0e0995ad9ac6b88",
            "3bf7be7396ec460d9677fa039a19cd4f",
            "4e17fa62793344d884744fe7affa86e8",
            "7142a01641a54958a815391e043d990d",
            "0cf81e232b97431c831ce2484cbaa38c",
            "d0111506f49241a0a568719684393173",
            "8d365bc3a37744f7ab79b12c11440d70",
            "904467d8c7534decba617db7d522fd24",
            "29a5a904b0354529baab5f07eb255c73",
            "ef4c0aad69734e7cba25c9cf7881ca4e",
            "7f2d1249b36a48a5993b6f652cc058e0",
            "f6c430a047e2446592461e93502a515a",
            "a80e43df1c2e4bc0adf12f1d5b73afe2",
            "0d8a32e808fc403e844eeede9289ee2d",
            "2cc326deac81495c945ce55c8f6ff77e",
            "7d4b16d5bd644a049d5f1639c3cb9752",
            "b33765fbc4ce4406b39c81636b9dc680",
            "04c4c51f1fd64efa8d97e510f8568821",
            "e86f005672d844a7844172a31fe9c2ba",
            "e07dc21cb88e4a2e9c2588732b118ebe",
            "cd5159792bb44c44a4bea270044b9655"
          ]
        },
        "id": "VEPVjqbbvWh2",
        "outputId": "34c47c21-c986-4ec6-b5a8-03f58932e9a9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Device: cpu\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to data/MNIST/raw/train-images-idx3-ubyte.gz\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/9912422 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6207c21a7373494799f19c6e54a03954"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting data/MNIST/raw/train-images-idx3-ubyte.gz to data/MNIST/raw\n",
            "\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to data/MNIST/raw/train-labels-idx1-ubyte.gz\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/28881 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a403f74f46cb41c18ab462b73b408b27"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting data/MNIST/raw/train-labels-idx1-ubyte.gz to data/MNIST/raw\n",
            "\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to data/MNIST/raw/t10k-images-idx3-ubyte.gz\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/1648877 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "285197313d734ca3967593eddf7ad08f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting data/MNIST/raw/t10k-images-idx3-ubyte.gz to data/MNIST/raw\n",
            "\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to data/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/4542 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7f2d1249b36a48a5993b6f652cc058e0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting data/MNIST/raw/t10k-labels-idx1-ubyte.gz to data/MNIST/raw\n",
            "\n",
            "Image batch dimensions: torch.Size([128, 1, 28, 28])\n",
            "Image label dimensions: torch.Size([128])\n"
          ]
        }
      ],
      "source": [
        "##########################\n",
        "### SETTINGS\n",
        "##########################\n",
        "\n",
        "# Device\n",
        "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
        "print('Device:', device)\n",
        "\n",
        "# Hyperparameters\n",
        "random_seed = 0\n",
        "learning_rate = 0.001\n",
        "num_epochs = 50\n",
        "batch_size = 128\n",
        "\n",
        "# Architecture\n",
        "num_features = 784\n",
        "num_hidden_1 = 500\n",
        "num_latent = 15\n",
        "\n",
        "\n",
        "##########################\n",
        "### MNIST DATASET\n",
        "##########################\n",
        "\n",
        "# Note transforms.ToTensor() scales input images\n",
        "# to 0-1 range\n",
        "train_dataset = datasets.MNIST(root='data', \n",
        "                               train=True, \n",
        "                               transform=transforms.ToTensor(),\n",
        "                               download=True)\n",
        "\n",
        "test_dataset = datasets.MNIST(root='data', \n",
        "                              train=False, \n",
        "                              transform=transforms.ToTensor())\n",
        "\n",
        "\n",
        "train_loader = DataLoader(dataset=train_dataset, \n",
        "                          batch_size=batch_size, \n",
        "                          shuffle=True)\n",
        "\n",
        "test_loader = DataLoader(dataset=test_dataset, \n",
        "                         batch_size=batch_size, \n",
        "                         shuffle=False)\n",
        "\n",
        "# Checking the dataset\n",
        "for images, labels in train_loader:  \n",
        "    print('Image batch dimensions:', images.shape)\n",
        "    print('Image label dimensions:', labels.shape)\n",
        "    break"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7ghuqUjnvWh3"
      },
      "source": [
        "## Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "mH5fDTiWvWh4"
      },
      "outputs": [],
      "source": [
        "##########################\n",
        "### MODEL\n",
        "##########################\n",
        "\n",
        "class VariationalAutoencoder(torch.nn.Module):\n",
        "\n",
        "    def __init__(self, num_features, num_hidden_1, num_latent):\n",
        "        super(VariationalAutoencoder, self).__init__()\n",
        "        \n",
        "        ### ENCODER\n",
        "        self.hidden_1 = torch.nn.Linear(num_features, num_hidden_1)\n",
        "        self.z_mean = torch.nn.Linear(num_hidden_1, num_latent)\n",
        "        # in the original paper (Kingma & Welling 2015, we use\n",
        "        # have a z_mean and z_var, but the problem is that\n",
        "        # the z_var can be negative, which would cause issues\n",
        "        # in the log later. Hence we assume that latent vector\n",
        "        # has a z_mean and z_log_var component, and when we need\n",
        "        # the regular variance or std_dev, we simply use \n",
        "        # an exponential function\n",
        "        self.z_log_var = torch.nn.Linear(num_hidden_1, num_latent)\n",
        "        \n",
        "        \n",
        "        ### DECODER\n",
        "        self.linear_3 = torch.nn.Linear(num_latent, num_hidden_1)\n",
        "        self.linear_4 = torch.nn.Linear(num_hidden_1, num_features)\n",
        "\n",
        "    def reparameterize(self, z_mu, z_log_var):\n",
        "        # Sample epsilon from standard normal distribution\n",
        "        eps = torch.randn(z_mu.size(0), z_mu.size(1)).to(device)\n",
        "        # note that log(x^2) = 2*log(x); hence divide by 2 to get std_dev\n",
        "        # i.e., std_dev = exp(log(std_dev^2)/2) = exp(log(var)/2)\n",
        "        z = z_mu + eps * torch.exp(z_log_var/2.) \n",
        "        return z\n",
        "        \n",
        "    def encoder(self, features):\n",
        "        x = self.hidden_1(features)\n",
        "        x = F.leaky_relu(x, negative_slope=0.0001)\n",
        "        z_mean = self.z_mean(x)\n",
        "        z_log_var = self.z_log_var(x)\n",
        "        encoded = self.reparameterize(z_mean, z_log_var)\n",
        "        return z_mean, z_log_var, encoded\n",
        "    \n",
        "    def decoder(self, encoded):\n",
        "        x = self.linear_3(encoded)\n",
        "        x = F.leaky_relu(x, negative_slope=0.0001)\n",
        "        x = self.linear_4(x)\n",
        "        decoded = torch.sigmoid(x)\n",
        "        return decoded\n",
        "\n",
        "    def forward(self, features):\n",
        "        \n",
        "        z_mean, z_log_var, encoded = self.encoder(features)\n",
        "        decoded = self.decoder(encoded)\n",
        "        \n",
        "        return z_mean, z_log_var, encoded, decoded\n",
        "\n",
        "    \n",
        "torch.manual_seed(random_seed)\n",
        "model = VariationalAutoencoder(num_features,\n",
        "                               num_hidden_1,\n",
        "                               num_latent)\n",
        "model = model.to(device)\n",
        "    \n",
        "optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)  "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ziG76BL4vWh5"
      },
      "source": [
        "## Training"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a5eK4bq_vWh5",
        "outputId": "82d175c5-f653-4e2d-8414-d3357c8d32eb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 001/050 | Batch 000/469 | Cost: 70335.5078\n",
            "Epoch: 001/050 | Batch 050/469 | Cost: 26118.4375\n",
            "Epoch: 001/050 | Batch 100/469 | Cost: 22565.9512\n",
            "Epoch: 001/050 | Batch 150/469 | Cost: 20126.6484\n",
            "Epoch: 001/050 | Batch 200/469 | Cost: 18710.9805\n",
            "Epoch: 001/050 | Batch 250/469 | Cost: 18154.2129\n",
            "Epoch: 001/050 | Batch 300/469 | Cost: 17224.2812\n",
            "Epoch: 001/050 | Batch 350/469 | Cost: 16768.8633\n",
            "Epoch: 001/050 | Batch 400/469 | Cost: 16421.1699\n",
            "Epoch: 001/050 | Batch 450/469 | Cost: 16168.4414\n",
            "Time elapsed: 0.28 min\n",
            "Epoch: 002/050 | Batch 000/469 | Cost: 16473.6680\n",
            "Epoch: 002/050 | Batch 050/469 | Cost: 15622.6250\n",
            "Epoch: 002/050 | Batch 100/469 | Cost: 15482.7559\n",
            "Epoch: 002/050 | Batch 150/469 | Cost: 15896.6064\n",
            "Epoch: 002/050 | Batch 200/469 | Cost: 15834.4785\n",
            "Epoch: 002/050 | Batch 250/469 | Cost: 15044.4434\n",
            "Epoch: 002/050 | Batch 300/469 | Cost: 15187.6982\n",
            "Epoch: 002/050 | Batch 350/469 | Cost: 15196.2324\n",
            "Epoch: 002/050 | Batch 400/469 | Cost: 15100.6836\n",
            "Epoch: 002/050 | Batch 450/469 | Cost: 14559.2568\n",
            "Time elapsed: 0.56 min\n",
            "Epoch: 003/050 | Batch 000/469 | Cost: 15348.1934\n",
            "Epoch: 003/050 | Batch 050/469 | Cost: 14766.6475\n",
            "Epoch: 003/050 | Batch 100/469 | Cost: 15141.9180\n",
            "Epoch: 003/050 | Batch 150/469 | Cost: 14266.0156\n",
            "Epoch: 003/050 | Batch 200/469 | Cost: 14386.3867\n",
            "Epoch: 003/050 | Batch 250/469 | Cost: 14617.3828\n",
            "Epoch: 003/050 | Batch 300/469 | Cost: 14390.1025\n",
            "Epoch: 003/050 | Batch 350/469 | Cost: 14905.1104\n",
            "Epoch: 003/050 | Batch 400/469 | Cost: 14175.4199\n",
            "Epoch: 003/050 | Batch 450/469 | Cost: 13613.1299\n",
            "Time elapsed: 0.83 min\n",
            "Epoch: 004/050 | Batch 000/469 | Cost: 13864.5000\n",
            "Epoch: 004/050 | Batch 050/469 | Cost: 14560.8340\n",
            "Epoch: 004/050 | Batch 100/469 | Cost: 14108.6328\n",
            "Epoch: 004/050 | Batch 150/469 | Cost: 13906.4844\n",
            "Epoch: 004/050 | Batch 200/469 | Cost: 14264.0957\n",
            "Epoch: 004/050 | Batch 250/469 | Cost: 14946.4590\n",
            "Epoch: 004/050 | Batch 300/469 | Cost: 14025.7676\n",
            "Epoch: 004/050 | Batch 350/469 | Cost: 13800.6543\n",
            "Epoch: 004/050 | Batch 400/469 | Cost: 14233.3789\n",
            "Epoch: 004/050 | Batch 450/469 | Cost: 13871.7285\n",
            "Time elapsed: 1.10 min\n",
            "Epoch: 005/050 | Batch 000/469 | Cost: 14110.3008\n",
            "Epoch: 005/050 | Batch 050/469 | Cost: 13899.1172\n",
            "Epoch: 005/050 | Batch 100/469 | Cost: 14080.8486\n",
            "Epoch: 005/050 | Batch 150/469 | Cost: 14532.2686\n",
            "Epoch: 005/050 | Batch 200/469 | Cost: 13268.0996\n",
            "Epoch: 005/050 | Batch 250/469 | Cost: 13693.9473\n",
            "Epoch: 005/050 | Batch 300/469 | Cost: 14018.5186\n",
            "Epoch: 005/050 | Batch 350/469 | Cost: 14601.0215\n",
            "Epoch: 005/050 | Batch 400/469 | Cost: 14333.7441\n",
            "Epoch: 005/050 | Batch 450/469 | Cost: 14498.4355\n",
            "Time elapsed: 1.39 min\n",
            "Epoch: 006/050 | Batch 000/469 | Cost: 13558.9375\n",
            "Epoch: 006/050 | Batch 050/469 | Cost: 14186.2939\n",
            "Epoch: 006/050 | Batch 100/469 | Cost: 14015.7520\n",
            "Epoch: 006/050 | Batch 150/469 | Cost: 14149.1738\n",
            "Epoch: 006/050 | Batch 200/469 | Cost: 13424.0039\n",
            "Epoch: 006/050 | Batch 250/469 | Cost: 14455.1719\n",
            "Epoch: 006/050 | Batch 300/469 | Cost: 13789.8281\n",
            "Epoch: 006/050 | Batch 350/469 | Cost: 13995.2129\n",
            "Epoch: 006/050 | Batch 400/469 | Cost: 13821.4336\n",
            "Epoch: 006/050 | Batch 450/469 | Cost: 13744.0332\n",
            "Time elapsed: 1.67 min\n",
            "Epoch: 007/050 | Batch 000/469 | Cost: 14263.2832\n",
            "Epoch: 007/050 | Batch 050/469 | Cost: 13097.9785\n",
            "Epoch: 007/050 | Batch 100/469 | Cost: 13445.1846\n",
            "Epoch: 007/050 | Batch 150/469 | Cost: 13828.2988\n",
            "Epoch: 007/050 | Batch 200/469 | Cost: 13707.5244\n",
            "Epoch: 007/050 | Batch 250/469 | Cost: 13698.9639\n",
            "Epoch: 007/050 | Batch 300/469 | Cost: 13814.7656\n",
            "Epoch: 007/050 | Batch 350/469 | Cost: 13804.3760\n",
            "Epoch: 007/050 | Batch 400/469 | Cost: 14061.4453\n",
            "Epoch: 007/050 | Batch 450/469 | Cost: 13601.8477\n",
            "Time elapsed: 1.95 min\n",
            "Epoch: 008/050 | Batch 000/469 | Cost: 13429.9463\n",
            "Epoch: 008/050 | Batch 050/469 | Cost: 13416.8242\n",
            "Epoch: 008/050 | Batch 100/469 | Cost: 13110.3584\n",
            "Epoch: 008/050 | Batch 150/469 | Cost: 13584.4697\n",
            "Epoch: 008/050 | Batch 200/469 | Cost: 13180.5215\n",
            "Epoch: 008/050 | Batch 250/469 | Cost: 13413.4756\n",
            "Epoch: 008/050 | Batch 300/469 | Cost: 14018.8867\n",
            "Epoch: 008/050 | Batch 350/469 | Cost: 13948.0781\n",
            "Epoch: 008/050 | Batch 400/469 | Cost: 13960.2549\n",
            "Epoch: 008/050 | Batch 450/469 | Cost: 13777.9473\n",
            "Time elapsed: 2.22 min\n",
            "Epoch: 009/050 | Batch 000/469 | Cost: 13322.1465\n",
            "Epoch: 009/050 | Batch 050/469 | Cost: 13740.7363\n",
            "Epoch: 009/050 | Batch 100/469 | Cost: 13449.1152\n",
            "Epoch: 009/050 | Batch 150/469 | Cost: 13486.6504\n",
            "Epoch: 009/050 | Batch 200/469 | Cost: 13652.7598\n",
            "Epoch: 009/050 | Batch 250/469 | Cost: 13758.9219\n",
            "Epoch: 009/050 | Batch 300/469 | Cost: 13304.2344\n",
            "Epoch: 009/050 | Batch 350/469 | Cost: 13316.5977\n",
            "Epoch: 009/050 | Batch 400/469 | Cost: 13535.5420\n",
            "Epoch: 009/050 | Batch 450/469 | Cost: 13416.4385\n",
            "Time elapsed: 2.49 min\n",
            "Epoch: 010/050 | Batch 000/469 | Cost: 13651.2471\n",
            "Epoch: 010/050 | Batch 050/469 | Cost: 14373.1914\n",
            "Epoch: 010/050 | Batch 100/469 | Cost: 14008.9912\n",
            "Epoch: 010/050 | Batch 150/469 | Cost: 13498.1123\n",
            "Epoch: 010/050 | Batch 200/469 | Cost: 13651.9854\n",
            "Epoch: 010/050 | Batch 250/469 | Cost: 13269.7617\n",
            "Epoch: 010/050 | Batch 300/469 | Cost: 13909.3408\n",
            "Epoch: 010/050 | Batch 350/469 | Cost: 13314.0703\n",
            "Epoch: 010/050 | Batch 400/469 | Cost: 13796.5898\n",
            "Epoch: 010/050 | Batch 450/469 | Cost: 13399.3203\n",
            "Time elapsed: 2.76 min\n",
            "Epoch: 011/050 | Batch 000/469 | Cost: 13419.7539\n",
            "Epoch: 011/050 | Batch 050/469 | Cost: 13559.3828\n",
            "Epoch: 011/050 | Batch 100/469 | Cost: 13418.9766\n",
            "Epoch: 011/050 | Batch 150/469 | Cost: 13563.6299\n",
            "Epoch: 011/050 | Batch 200/469 | Cost: 13867.8701\n",
            "Epoch: 011/050 | Batch 250/469 | Cost: 13341.8672\n",
            "Epoch: 011/050 | Batch 300/469 | Cost: 13849.8643\n",
            "Epoch: 011/050 | Batch 350/469 | Cost: 13061.7432\n",
            "Epoch: 011/050 | Batch 400/469 | Cost: 13685.8516\n",
            "Epoch: 011/050 | Batch 450/469 | Cost: 14209.5811\n",
            "Time elapsed: 3.03 min\n",
            "Epoch: 012/050 | Batch 000/469 | Cost: 13200.7666\n",
            "Epoch: 012/050 | Batch 050/469 | Cost: 13192.1895\n",
            "Epoch: 012/050 | Batch 100/469 | Cost: 13333.8594\n",
            "Epoch: 012/050 | Batch 150/469 | Cost: 13114.3877\n",
            "Epoch: 012/050 | Batch 200/469 | Cost: 13517.7109\n",
            "Epoch: 012/050 | Batch 250/469 | Cost: 13975.7852\n",
            "Epoch: 012/050 | Batch 300/469 | Cost: 13604.1797\n",
            "Epoch: 012/050 | Batch 350/469 | Cost: 13507.8447\n",
            "Epoch: 012/050 | Batch 400/469 | Cost: 13381.6934\n",
            "Epoch: 012/050 | Batch 450/469 | Cost: 13554.4434\n",
            "Time elapsed: 3.30 min\n",
            "Epoch: 013/050 | Batch 000/469 | Cost: 13184.5244\n",
            "Epoch: 013/050 | Batch 050/469 | Cost: 13378.2344\n",
            "Epoch: 013/050 | Batch 100/469 | Cost: 12909.3164\n",
            "Epoch: 013/050 | Batch 150/469 | Cost: 13281.7754\n",
            "Epoch: 013/050 | Batch 200/469 | Cost: 13456.1885\n",
            "Epoch: 013/050 | Batch 250/469 | Cost: 13025.8291\n",
            "Epoch: 013/050 | Batch 300/469 | Cost: 13497.3711\n",
            "Epoch: 013/050 | Batch 350/469 | Cost: 13234.2646\n",
            "Epoch: 013/050 | Batch 400/469 | Cost: 13386.6133\n",
            "Epoch: 013/050 | Batch 450/469 | Cost: 12600.3730\n",
            "Time elapsed: 3.59 min\n",
            "Epoch: 014/050 | Batch 000/469 | Cost: 13154.1406\n",
            "Epoch: 014/050 | Batch 050/469 | Cost: 13490.4668\n",
            "Epoch: 014/050 | Batch 100/469 | Cost: 13515.7861\n",
            "Epoch: 014/050 | Batch 150/469 | Cost: 13116.3174\n",
            "Epoch: 014/050 | Batch 200/469 | Cost: 13531.2539\n",
            "Epoch: 014/050 | Batch 250/469 | Cost: 13246.2500\n",
            "Epoch: 014/050 | Batch 300/469 | Cost: 13220.2617\n",
            "Epoch: 014/050 | Batch 350/469 | Cost: 13416.8496\n",
            "Epoch: 014/050 | Batch 400/469 | Cost: 13778.4238\n",
            "Epoch: 014/050 | Batch 450/469 | Cost: 13673.2812\n",
            "Time elapsed: 3.91 min\n",
            "Epoch: 015/050 | Batch 000/469 | Cost: 13465.6484\n",
            "Epoch: 015/050 | Batch 050/469 | Cost: 13841.4326\n",
            "Epoch: 015/050 | Batch 100/469 | Cost: 13061.8574\n",
            "Epoch: 015/050 | Batch 150/469 | Cost: 12950.3994\n",
            "Epoch: 015/050 | Batch 200/469 | Cost: 13266.0312\n",
            "Epoch: 015/050 | Batch 250/469 | Cost: 13675.5293\n",
            "Epoch: 015/050 | Batch 300/469 | Cost: 13430.8193\n",
            "Epoch: 015/050 | Batch 350/469 | Cost: 13793.0762\n",
            "Epoch: 015/050 | Batch 400/469 | Cost: 13533.9717\n",
            "Epoch: 015/050 | Batch 450/469 | Cost: 13410.7559\n",
            "Time elapsed: 4.24 min\n",
            "Epoch: 016/050 | Batch 000/469 | Cost: 13660.2959\n",
            "Epoch: 016/050 | Batch 050/469 | Cost: 13430.5098\n",
            "Epoch: 016/050 | Batch 100/469 | Cost: 13617.3281\n",
            "Epoch: 016/050 | Batch 150/469 | Cost: 13533.3828\n",
            "Epoch: 016/050 | Batch 200/469 | Cost: 13733.6943\n",
            "Epoch: 016/050 | Batch 250/469 | Cost: 13103.6680\n",
            "Epoch: 016/050 | Batch 300/469 | Cost: 13210.9023\n",
            "Epoch: 016/050 | Batch 350/469 | Cost: 13661.7227\n",
            "Epoch: 016/050 | Batch 400/469 | Cost: 13121.8496\n",
            "Epoch: 016/050 | Batch 450/469 | Cost: 13054.5908\n",
            "Time elapsed: 4.51 min\n",
            "Epoch: 017/050 | Batch 000/469 | Cost: 12997.8799\n",
            "Epoch: 017/050 | Batch 050/469 | Cost: 12992.8613\n",
            "Epoch: 017/050 | Batch 100/469 | Cost: 13467.3096\n",
            "Epoch: 017/050 | Batch 150/469 | Cost: 13082.2891\n",
            "Epoch: 017/050 | Batch 200/469 | Cost: 13073.2129\n",
            "Epoch: 017/050 | Batch 250/469 | Cost: 13498.1172\n",
            "Epoch: 017/050 | Batch 300/469 | Cost: 13853.6895\n",
            "Epoch: 017/050 | Batch 350/469 | Cost: 13239.6504\n",
            "Epoch: 017/050 | Batch 400/469 | Cost: 12880.7832\n",
            "Epoch: 017/050 | Batch 450/469 | Cost: 13019.1777\n",
            "Time elapsed: 4.79 min\n",
            "Epoch: 018/050 | Batch 000/469 | Cost: 13025.5566\n",
            "Epoch: 018/050 | Batch 050/469 | Cost: 14039.7354\n",
            "Epoch: 018/050 | Batch 100/469 | Cost: 13732.3887\n",
            "Epoch: 018/050 | Batch 150/469 | Cost: 13593.4102\n",
            "Epoch: 018/050 | Batch 200/469 | Cost: 13056.6465\n",
            "Epoch: 018/050 | Batch 250/469 | Cost: 13256.8125\n",
            "Epoch: 018/050 | Batch 300/469 | Cost: 13300.9229\n",
            "Epoch: 018/050 | Batch 350/469 | Cost: 13401.8926\n",
            "Epoch: 018/050 | Batch 400/469 | Cost: 13272.0566\n",
            "Epoch: 018/050 | Batch 450/469 | Cost: 13192.5762\n",
            "Time elapsed: 5.06 min\n",
            "Epoch: 019/050 | Batch 000/469 | Cost: 13202.0850\n",
            "Epoch: 019/050 | Batch 050/469 | Cost: 13164.4336\n",
            "Epoch: 019/050 | Batch 100/469 | Cost: 13807.8750\n",
            "Epoch: 019/050 | Batch 150/469 | Cost: 13284.7285\n",
            "Epoch: 019/050 | Batch 200/469 | Cost: 12978.9639\n",
            "Epoch: 019/050 | Batch 250/469 | Cost: 13200.9219\n",
            "Epoch: 019/050 | Batch 300/469 | Cost: 13448.0996\n",
            "Epoch: 019/050 | Batch 350/469 | Cost: 12774.8184\n",
            "Epoch: 019/050 | Batch 400/469 | Cost: 13360.3965\n",
            "Epoch: 019/050 | Batch 450/469 | Cost: 13329.7422\n",
            "Time elapsed: 5.33 min\n",
            "Epoch: 020/050 | Batch 000/469 | Cost: 13335.3418\n",
            "Epoch: 020/050 | Batch 050/469 | Cost: 13727.9033\n",
            "Epoch: 020/050 | Batch 100/469 | Cost: 13953.4473\n",
            "Epoch: 020/050 | Batch 150/469 | Cost: 13414.0576\n",
            "Epoch: 020/050 | Batch 200/469 | Cost: 13104.2197\n",
            "Epoch: 020/050 | Batch 250/469 | Cost: 13527.5859\n",
            "Epoch: 020/050 | Batch 300/469 | Cost: 13532.0107\n",
            "Epoch: 020/050 | Batch 350/469 | Cost: 13432.0010\n",
            "Epoch: 020/050 | Batch 400/469 | Cost: 13528.2324\n",
            "Epoch: 020/050 | Batch 450/469 | Cost: 13433.4814\n",
            "Time elapsed: 5.60 min\n",
            "Epoch: 021/050 | Batch 000/469 | Cost: 13634.6240\n",
            "Epoch: 021/050 | Batch 050/469 | Cost: 13440.2637\n",
            "Epoch: 021/050 | Batch 100/469 | Cost: 13711.1035\n",
            "Epoch: 021/050 | Batch 150/469 | Cost: 13038.6680\n",
            "Epoch: 021/050 | Batch 200/469 | Cost: 12951.3828\n",
            "Epoch: 021/050 | Batch 250/469 | Cost: 12408.7832\n",
            "Epoch: 021/050 | Batch 300/469 | Cost: 13617.5605\n",
            "Epoch: 021/050 | Batch 350/469 | Cost: 13049.3906\n",
            "Epoch: 021/050 | Batch 400/469 | Cost: 13303.7891\n",
            "Epoch: 021/050 | Batch 450/469 | Cost: 13467.8730\n",
            "Time elapsed: 5.87 min\n",
            "Epoch: 022/050 | Batch 000/469 | Cost: 13738.9199\n",
            "Epoch: 022/050 | Batch 050/469 | Cost: 13114.4277\n",
            "Epoch: 022/050 | Batch 100/469 | Cost: 13300.0078\n",
            "Epoch: 022/050 | Batch 150/469 | Cost: 12400.8574\n",
            "Epoch: 022/050 | Batch 200/469 | Cost: 13239.4424\n",
            "Epoch: 022/050 | Batch 250/469 | Cost: 12657.8184\n",
            "Epoch: 022/050 | Batch 300/469 | Cost: 12823.7588\n",
            "Epoch: 022/050 | Batch 350/469 | Cost: 13288.3047\n",
            "Epoch: 022/050 | Batch 400/469 | Cost: 13375.6992\n",
            "Epoch: 022/050 | Batch 450/469 | Cost: 13121.5957\n",
            "Time elapsed: 6.15 min\n",
            "Epoch: 023/050 | Batch 000/469 | Cost: 13129.0762\n",
            "Epoch: 023/050 | Batch 050/469 | Cost: 13121.4766\n",
            "Epoch: 023/050 | Batch 100/469 | Cost: 13363.5850\n",
            "Epoch: 023/050 | Batch 150/469 | Cost: 13244.4102\n",
            "Epoch: 023/050 | Batch 200/469 | Cost: 12998.6162\n",
            "Epoch: 023/050 | Batch 250/469 | Cost: 13602.0469\n",
            "Epoch: 023/050 | Batch 300/469 | Cost: 12591.9453\n",
            "Epoch: 023/050 | Batch 350/469 | Cost: 13046.7422\n",
            "Epoch: 023/050 | Batch 400/469 | Cost: 12894.0557\n",
            "Epoch: 023/050 | Batch 450/469 | Cost: 13573.4473\n",
            "Time elapsed: 6.43 min\n",
            "Epoch: 024/050 | Batch 000/469 | Cost: 13196.1152\n",
            "Epoch: 024/050 | Batch 050/469 | Cost: 13399.2480\n",
            "Epoch: 024/050 | Batch 100/469 | Cost: 13001.0059\n",
            "Epoch: 024/050 | Batch 150/469 | Cost: 13264.8809\n",
            "Epoch: 024/050 | Batch 200/469 | Cost: 12803.7061\n",
            "Epoch: 024/050 | Batch 250/469 | Cost: 13218.7969\n",
            "Epoch: 024/050 | Batch 300/469 | Cost: 12806.3223\n",
            "Epoch: 024/050 | Batch 350/469 | Cost: 13245.3379\n",
            "Epoch: 024/050 | Batch 400/469 | Cost: 13084.0918\n",
            "Epoch: 024/050 | Batch 450/469 | Cost: 12912.0000\n",
            "Time elapsed: 6.70 min\n",
            "Epoch: 025/050 | Batch 000/469 | Cost: 13255.4492\n",
            "Epoch: 025/050 | Batch 050/469 | Cost: 13017.9395\n",
            "Epoch: 025/050 | Batch 100/469 | Cost: 13056.4775\n",
            "Epoch: 025/050 | Batch 150/469 | Cost: 12865.7881\n",
            "Epoch: 025/050 | Batch 200/469 | Cost: 13383.4795\n",
            "Epoch: 025/050 | Batch 250/469 | Cost: 12876.3496\n",
            "Epoch: 025/050 | Batch 300/469 | Cost: 13533.5977\n",
            "Epoch: 025/050 | Batch 350/469 | Cost: 12935.4688\n",
            "Epoch: 025/050 | Batch 400/469 | Cost: 13144.0898\n",
            "Epoch: 025/050 | Batch 450/469 | Cost: 13563.7090\n",
            "Time elapsed: 6.97 min\n",
            "Epoch: 026/050 | Batch 000/469 | Cost: 13234.9375\n",
            "Epoch: 026/050 | Batch 050/469 | Cost: 13384.4180\n",
            "Epoch: 026/050 | Batch 100/469 | Cost: 13253.5088\n",
            "Epoch: 026/050 | Batch 150/469 | Cost: 12927.1953\n",
            "Epoch: 026/050 | Batch 200/469 | Cost: 13375.1660\n",
            "Epoch: 026/050 | Batch 250/469 | Cost: 12774.5693\n",
            "Epoch: 026/050 | Batch 300/469 | Cost: 13110.7510\n",
            "Epoch: 026/050 | Batch 350/469 | Cost: 12989.7354\n",
            "Epoch: 026/050 | Batch 400/469 | Cost: 12764.6719\n",
            "Epoch: 026/050 | Batch 450/469 | Cost: 13519.3555\n",
            "Time elapsed: 7.24 min\n",
            "Epoch: 027/050 | Batch 000/469 | Cost: 12865.8496\n",
            "Epoch: 027/050 | Batch 050/469 | Cost: 12814.8145\n",
            "Epoch: 027/050 | Batch 100/469 | Cost: 13143.4258\n",
            "Epoch: 027/050 | Batch 150/469 | Cost: 13794.2549\n",
            "Epoch: 027/050 | Batch 200/469 | Cost: 12752.4121\n",
            "Epoch: 027/050 | Batch 250/469 | Cost: 13332.6484\n",
            "Epoch: 027/050 | Batch 300/469 | Cost: 12991.1045\n",
            "Epoch: 027/050 | Batch 350/469 | Cost: 12997.2773\n",
            "Epoch: 027/050 | Batch 400/469 | Cost: 13135.0801\n",
            "Epoch: 027/050 | Batch 450/469 | Cost: 12922.8418\n",
            "Time elapsed: 7.51 min\n",
            "Epoch: 028/050 | Batch 000/469 | Cost: 12414.3135\n",
            "Epoch: 028/050 | Batch 050/469 | Cost: 13445.2988\n",
            "Epoch: 028/050 | Batch 100/469 | Cost: 12563.7422\n",
            "Epoch: 028/050 | Batch 150/469 | Cost: 12992.1162\n",
            "Epoch: 028/050 | Batch 200/469 | Cost: 13300.3037\n",
            "Epoch: 028/050 | Batch 250/469 | Cost: 13377.2979\n",
            "Epoch: 028/050 | Batch 300/469 | Cost: 13089.3633\n",
            "Epoch: 028/050 | Batch 350/469 | Cost: 12966.3223\n",
            "Epoch: 028/050 | Batch 400/469 | Cost: 12525.9180\n",
            "Epoch: 028/050 | Batch 450/469 | Cost: 12623.4678\n",
            "Time elapsed: 7.78 min\n",
            "Epoch: 029/050 | Batch 000/469 | Cost: 12944.4355\n",
            "Epoch: 029/050 | Batch 050/469 | Cost: 13227.8926\n",
            "Epoch: 029/050 | Batch 100/469 | Cost: 13211.7324\n",
            "Epoch: 029/050 | Batch 150/469 | Cost: 12724.7305\n",
            "Epoch: 029/050 | Batch 200/469 | Cost: 13074.8242\n",
            "Epoch: 029/050 | Batch 250/469 | Cost: 12926.3623\n",
            "Epoch: 029/050 | Batch 300/469 | Cost: 13525.8857\n",
            "Epoch: 029/050 | Batch 350/469 | Cost: 13105.4180\n",
            "Epoch: 029/050 | Batch 400/469 | Cost: 12968.2568\n",
            "Epoch: 029/050 | Batch 450/469 | Cost: 13169.3340\n",
            "Time elapsed: 8.05 min\n",
            "Epoch: 030/050 | Batch 000/469 | Cost: 13008.7148\n",
            "Epoch: 030/050 | Batch 050/469 | Cost: 12859.0303\n",
            "Epoch: 030/050 | Batch 100/469 | Cost: 13047.5430\n",
            "Epoch: 030/050 | Batch 150/469 | Cost: 12975.2676\n",
            "Epoch: 030/050 | Batch 200/469 | Cost: 12377.1895\n",
            "Epoch: 030/050 | Batch 250/469 | Cost: 13486.9727\n",
            "Epoch: 030/050 | Batch 300/469 | Cost: 13298.4707\n",
            "Epoch: 030/050 | Batch 350/469 | Cost: 12897.1904\n",
            "Epoch: 030/050 | Batch 400/469 | Cost: 12861.9395\n",
            "Epoch: 030/050 | Batch 450/469 | Cost: 13095.9395\n",
            "Time elapsed: 8.32 min\n",
            "Epoch: 031/050 | Batch 000/469 | Cost: 12385.8945\n",
            "Epoch: 031/050 | Batch 050/469 | Cost: 13189.1211\n",
            "Epoch: 031/050 | Batch 100/469 | Cost: 13038.8887\n",
            "Epoch: 031/050 | Batch 150/469 | Cost: 13986.4414\n",
            "Epoch: 031/050 | Batch 200/469 | Cost: 12588.1611\n",
            "Epoch: 031/050 | Batch 250/469 | Cost: 13464.8027\n",
            "Epoch: 031/050 | Batch 300/469 | Cost: 12572.1719\n",
            "Epoch: 031/050 | Batch 350/469 | Cost: 13355.6582\n",
            "Epoch: 031/050 | Batch 400/469 | Cost: 12926.3223\n",
            "Epoch: 031/050 | Batch 450/469 | Cost: 13422.5781\n",
            "Time elapsed: 8.59 min\n",
            "Epoch: 032/050 | Batch 000/469 | Cost: 12778.6719\n",
            "Epoch: 032/050 | Batch 050/469 | Cost: 13234.0508\n",
            "Epoch: 032/050 | Batch 100/469 | Cost: 12950.5039\n",
            "Epoch: 032/050 | Batch 150/469 | Cost: 13391.9502\n",
            "Epoch: 032/050 | Batch 200/469 | Cost: 13007.1172\n",
            "Epoch: 032/050 | Batch 250/469 | Cost: 13175.2051\n",
            "Epoch: 032/050 | Batch 300/469 | Cost: 13233.7812\n",
            "Epoch: 032/050 | Batch 350/469 | Cost: 12689.7588\n",
            "Epoch: 032/050 | Batch 400/469 | Cost: 12834.5967\n",
            "Epoch: 032/050 | Batch 450/469 | Cost: 12923.6006\n",
            "Time elapsed: 8.87 min\n",
            "Epoch: 033/050 | Batch 000/469 | Cost: 12902.7139\n",
            "Epoch: 033/050 | Batch 050/469 | Cost: 12958.1865\n",
            "Epoch: 033/050 | Batch 100/469 | Cost: 13152.6396\n",
            "Epoch: 033/050 | Batch 150/469 | Cost: 12891.6270\n",
            "Epoch: 033/050 | Batch 200/469 | Cost: 13575.1064\n",
            "Epoch: 033/050 | Batch 250/469 | Cost: 13240.3301\n",
            "Epoch: 033/050 | Batch 300/469 | Cost: 13412.7939\n",
            "Epoch: 033/050 | Batch 350/469 | Cost: 12935.6934\n",
            "Epoch: 033/050 | Batch 400/469 | Cost: 13073.6758\n",
            "Epoch: 033/050 | Batch 450/469 | Cost: 13389.8086\n",
            "Time elapsed: 9.15 min\n",
            "Epoch: 034/050 | Batch 000/469 | Cost: 12970.7822\n",
            "Epoch: 034/050 | Batch 050/469 | Cost: 12797.8350\n",
            "Epoch: 034/050 | Batch 100/469 | Cost: 13757.2266\n",
            "Epoch: 034/050 | Batch 150/469 | Cost: 13206.4600\n",
            "Epoch: 034/050 | Batch 200/469 | Cost: 13410.0195\n",
            "Epoch: 034/050 | Batch 250/469 | Cost: 13574.5801\n",
            "Epoch: 034/050 | Batch 300/469 | Cost: 13388.7656\n",
            "Epoch: 034/050 | Batch 350/469 | Cost: 12712.1553\n",
            "Epoch: 034/050 | Batch 400/469 | Cost: 13310.3027\n",
            "Epoch: 034/050 | Batch 450/469 | Cost: 13348.0146\n",
            "Time elapsed: 9.42 min\n",
            "Epoch: 035/050 | Batch 000/469 | Cost: 13100.9570\n",
            "Epoch: 035/050 | Batch 050/469 | Cost: 12898.1602\n",
            "Epoch: 035/050 | Batch 100/469 | Cost: 13032.1367\n",
            "Epoch: 035/050 | Batch 150/469 | Cost: 12808.9141\n",
            "Epoch: 035/050 | Batch 200/469 | Cost: 12812.3535\n",
            "Epoch: 035/050 | Batch 250/469 | Cost: 13465.8311\n",
            "Epoch: 035/050 | Batch 300/469 | Cost: 12663.4590\n",
            "Epoch: 035/050 | Batch 350/469 | Cost: 12546.4482\n",
            "Epoch: 035/050 | Batch 400/469 | Cost: 12838.5254\n",
            "Epoch: 035/050 | Batch 450/469 | Cost: 13492.3350\n",
            "Time elapsed: 9.69 min\n",
            "Epoch: 036/050 | Batch 000/469 | Cost: 13047.3359\n",
            "Epoch: 036/050 | Batch 050/469 | Cost: 13466.8125\n",
            "Epoch: 036/050 | Batch 100/469 | Cost: 12779.1572\n",
            "Epoch: 036/050 | Batch 150/469 | Cost: 12937.6348\n",
            "Epoch: 036/050 | Batch 200/469 | Cost: 12978.7646\n",
            "Epoch: 036/050 | Batch 250/469 | Cost: 13218.2207\n",
            "Epoch: 036/050 | Batch 300/469 | Cost: 12845.1670\n",
            "Epoch: 036/050 | Batch 350/469 | Cost: 12636.0283\n",
            "Epoch: 036/050 | Batch 400/469 | Cost: 12963.1152\n",
            "Epoch: 036/050 | Batch 450/469 | Cost: 13118.2764\n",
            "Time elapsed: 9.96 min\n",
            "Epoch: 037/050 | Batch 000/469 | Cost: 12925.6816\n",
            "Epoch: 037/050 | Batch 050/469 | Cost: 13007.9004\n",
            "Epoch: 037/050 | Batch 100/469 | Cost: 13166.5938\n",
            "Epoch: 037/050 | Batch 150/469 | Cost: 12694.0615\n",
            "Epoch: 037/050 | Batch 200/469 | Cost: 13251.0625\n",
            "Epoch: 037/050 | Batch 250/469 | Cost: 13334.0508\n",
            "Epoch: 037/050 | Batch 300/469 | Cost: 13123.9414\n",
            "Epoch: 037/050 | Batch 350/469 | Cost: 12696.5635\n",
            "Epoch: 037/050 | Batch 400/469 | Cost: 12948.7891\n",
            "Epoch: 037/050 | Batch 450/469 | Cost: 13050.7949\n",
            "Time elapsed: 10.23 min\n",
            "Epoch: 038/050 | Batch 000/469 | Cost: 13238.6738\n",
            "Epoch: 038/050 | Batch 050/469 | Cost: 12981.1836\n",
            "Epoch: 038/050 | Batch 100/469 | Cost: 12743.1016\n",
            "Epoch: 038/050 | Batch 150/469 | Cost: 12756.9600\n",
            "Epoch: 038/050 | Batch 200/469 | Cost: 12966.2266\n",
            "Epoch: 038/050 | Batch 250/469 | Cost: 12689.9102\n",
            "Epoch: 038/050 | Batch 300/469 | Cost: 12412.8115\n",
            "Epoch: 038/050 | Batch 350/469 | Cost: 12911.0303\n",
            "Epoch: 038/050 | Batch 400/469 | Cost: 12375.1270\n",
            "Epoch: 038/050 | Batch 450/469 | Cost: 12899.7803\n",
            "Time elapsed: 10.51 min\n",
            "Epoch: 039/050 | Batch 000/469 | Cost: 13009.2754\n",
            "Epoch: 039/050 | Batch 050/469 | Cost: 13035.1035\n",
            "Epoch: 039/050 | Batch 100/469 | Cost: 12799.4639\n",
            "Epoch: 039/050 | Batch 150/469 | Cost: 13304.0176\n",
            "Epoch: 039/050 | Batch 200/469 | Cost: 12774.5742\n",
            "Epoch: 039/050 | Batch 250/469 | Cost: 12729.7529\n",
            "Epoch: 039/050 | Batch 300/469 | Cost: 13337.5957\n",
            "Epoch: 039/050 | Batch 350/469 | Cost: 12708.4570\n",
            "Epoch: 039/050 | Batch 400/469 | Cost: 13192.1826\n",
            "Epoch: 039/050 | Batch 450/469 | Cost: 12682.2451\n",
            "Time elapsed: 10.78 min\n",
            "Epoch: 040/050 | Batch 000/469 | Cost: 13438.7520\n",
            "Epoch: 040/050 | Batch 050/469 | Cost: 12659.3945\n",
            "Epoch: 040/050 | Batch 100/469 | Cost: 12738.7881\n",
            "Epoch: 040/050 | Batch 150/469 | Cost: 12662.0781\n",
            "Epoch: 040/050 | Batch 200/469 | Cost: 13093.8320\n",
            "Epoch: 040/050 | Batch 250/469 | Cost: 13136.1074\n",
            "Epoch: 040/050 | Batch 300/469 | Cost: 13218.9688\n",
            "Epoch: 040/050 | Batch 350/469 | Cost: 13168.8447\n",
            "Epoch: 040/050 | Batch 400/469 | Cost: 12922.6494\n",
            "Epoch: 040/050 | Batch 450/469 | Cost: 13159.8213\n",
            "Time elapsed: 11.05 min\n",
            "Epoch: 041/050 | Batch 000/469 | Cost: 12396.8662\n",
            "Epoch: 041/050 | Batch 050/469 | Cost: 12762.4150\n",
            "Epoch: 041/050 | Batch 100/469 | Cost: 13361.5811\n",
            "Epoch: 041/050 | Batch 150/469 | Cost: 13519.0547\n",
            "Epoch: 041/050 | Batch 200/469 | Cost: 12891.8174\n",
            "Epoch: 041/050 | Batch 250/469 | Cost: 12949.2715\n",
            "Epoch: 041/050 | Batch 300/469 | Cost: 13171.1484\n",
            "Epoch: 041/050 | Batch 350/469 | Cost: 13096.2988\n",
            "Epoch: 041/050 | Batch 400/469 | Cost: 13043.2354\n",
            "Epoch: 041/050 | Batch 450/469 | Cost: 12825.7617\n",
            "Time elapsed: 11.34 min\n",
            "Epoch: 042/050 | Batch 000/469 | Cost: 12950.8477\n",
            "Epoch: 042/050 | Batch 050/469 | Cost: 13129.1230\n",
            "Epoch: 042/050 | Batch 100/469 | Cost: 13083.8477\n",
            "Epoch: 042/050 | Batch 150/469 | Cost: 12563.1729\n",
            "Epoch: 042/050 | Batch 200/469 | Cost: 12931.5547\n",
            "Epoch: 042/050 | Batch 250/469 | Cost: 12739.3418\n",
            "Epoch: 042/050 | Batch 300/469 | Cost: 13419.0195\n",
            "Epoch: 042/050 | Batch 350/469 | Cost: 12937.1973\n",
            "Epoch: 042/050 | Batch 400/469 | Cost: 12840.3438\n",
            "Epoch: 042/050 | Batch 450/469 | Cost: 12964.3574\n",
            "Time elapsed: 11.62 min\n",
            "Epoch: 043/050 | Batch 000/469 | Cost: 12575.6777\n",
            "Epoch: 043/050 | Batch 050/469 | Cost: 13371.2949\n",
            "Epoch: 043/050 | Batch 100/469 | Cost: 12790.6387\n",
            "Epoch: 043/050 | Batch 150/469 | Cost: 13087.4238\n",
            "Epoch: 043/050 | Batch 200/469 | Cost: 13100.4648\n",
            "Epoch: 043/050 | Batch 250/469 | Cost: 12704.0898\n",
            "Epoch: 043/050 | Batch 300/469 | Cost: 13381.4648\n",
            "Epoch: 043/050 | Batch 350/469 | Cost: 12874.1211\n",
            "Epoch: 043/050 | Batch 400/469 | Cost: 12735.6543\n",
            "Epoch: 043/050 | Batch 450/469 | Cost: 12979.6074\n",
            "Time elapsed: 11.90 min\n",
            "Epoch: 044/050 | Batch 000/469 | Cost: 13053.7549\n",
            "Epoch: 044/050 | Batch 050/469 | Cost: 12381.4238\n",
            "Epoch: 044/050 | Batch 100/469 | Cost: 12949.8193\n",
            "Epoch: 044/050 | Batch 150/469 | Cost: 13492.9355\n",
            "Epoch: 044/050 | Batch 200/469 | Cost: 12846.3545\n",
            "Epoch: 044/050 | Batch 250/469 | Cost: 12937.9629\n",
            "Epoch: 044/050 | Batch 300/469 | Cost: 12927.0381\n",
            "Epoch: 044/050 | Batch 350/469 | Cost: 13059.9355\n",
            "Epoch: 044/050 | Batch 400/469 | Cost: 12804.2803\n",
            "Epoch: 044/050 | Batch 450/469 | Cost: 12420.2207\n",
            "Time elapsed: 12.18 min\n",
            "Epoch: 045/050 | Batch 000/469 | Cost: 13485.7148\n",
            "Epoch: 045/050 | Batch 050/469 | Cost: 13024.1992\n",
            "Epoch: 045/050 | Batch 100/469 | Cost: 12896.5176\n",
            "Epoch: 045/050 | Batch 150/469 | Cost: 13212.3799\n",
            "Epoch: 045/050 | Batch 200/469 | Cost: 13033.3936\n",
            "Epoch: 045/050 | Batch 250/469 | Cost: 13078.7041\n",
            "Epoch: 045/050 | Batch 300/469 | Cost: 12709.6738\n",
            "Epoch: 045/050 | Batch 350/469 | Cost: 13061.2188\n",
            "Epoch: 045/050 | Batch 400/469 | Cost: 12698.5898\n",
            "Epoch: 045/050 | Batch 450/469 | Cost: 12951.4707\n",
            "Time elapsed: 12.45 min\n",
            "Epoch: 046/050 | Batch 000/469 | Cost: 12499.7559\n",
            "Epoch: 046/050 | Batch 050/469 | Cost: 12336.2852\n",
            "Epoch: 046/050 | Batch 100/469 | Cost: 13036.8428\n",
            "Epoch: 046/050 | Batch 150/469 | Cost: 13263.4404\n",
            "Epoch: 046/050 | Batch 200/469 | Cost: 13086.6953\n",
            "Epoch: 046/050 | Batch 250/469 | Cost: 13301.6084\n",
            "Epoch: 046/050 | Batch 300/469 | Cost: 13404.0059\n",
            "Epoch: 046/050 | Batch 350/469 | Cost: 13076.0527\n",
            "Epoch: 046/050 | Batch 400/469 | Cost: 12452.7939\n",
            "Epoch: 046/050 | Batch 450/469 | Cost: 12906.3535\n",
            "Time elapsed: 12.74 min\n",
            "Epoch: 047/050 | Batch 000/469 | Cost: 12803.2451\n",
            "Epoch: 047/050 | Batch 050/469 | Cost: 12293.2354\n",
            "Epoch: 047/050 | Batch 100/469 | Cost: 13313.5811\n",
            "Epoch: 047/050 | Batch 150/469 | Cost: 13096.8955\n",
            "Epoch: 047/050 | Batch 200/469 | Cost: 12834.1211\n",
            "Epoch: 047/050 | Batch 250/469 | Cost: 13387.9775\n",
            "Epoch: 047/050 | Batch 300/469 | Cost: 12604.8896\n",
            "Epoch: 047/050 | Batch 350/469 | Cost: 13099.5928\n",
            "Epoch: 047/050 | Batch 400/469 | Cost: 12792.5078\n",
            "Epoch: 047/050 | Batch 450/469 | Cost: 13057.0693\n",
            "Time elapsed: 13.02 min\n",
            "Epoch: 048/050 | Batch 000/469 | Cost: 12864.2246\n",
            "Epoch: 048/050 | Batch 050/469 | Cost: 13114.0205\n",
            "Epoch: 048/050 | Batch 100/469 | Cost: 13159.2832\n",
            "Epoch: 048/050 | Batch 150/469 | Cost: 13445.4814\n",
            "Epoch: 048/050 | Batch 200/469 | Cost: 12692.9824\n",
            "Epoch: 048/050 | Batch 250/469 | Cost: 12473.5293\n",
            "Epoch: 048/050 | Batch 300/469 | Cost: 12694.9258\n",
            "Epoch: 048/050 | Batch 350/469 | Cost: 12650.0361\n",
            "Epoch: 048/050 | Batch 400/469 | Cost: 13358.6758\n",
            "Epoch: 048/050 | Batch 450/469 | Cost: 13147.1543\n",
            "Time elapsed: 13.30 min\n",
            "Epoch: 049/050 | Batch 000/469 | Cost: 12731.0078\n",
            "Epoch: 049/050 | Batch 050/469 | Cost: 12367.3818\n",
            "Epoch: 049/050 | Batch 100/469 | Cost: 12793.0586\n",
            "Epoch: 049/050 | Batch 150/469 | Cost: 13402.4785\n",
            "Epoch: 049/050 | Batch 200/469 | Cost: 13381.2422\n",
            "Epoch: 049/050 | Batch 250/469 | Cost: 12706.5791\n",
            "Epoch: 049/050 | Batch 300/469 | Cost: 13157.0234\n",
            "Epoch: 049/050 | Batch 350/469 | Cost: 12984.4336\n",
            "Epoch: 049/050 | Batch 400/469 | Cost: 13317.1660\n",
            "Epoch: 049/050 | Batch 450/469 | Cost: 13248.0508\n",
            "Time elapsed: 13.58 min\n",
            "Epoch: 050/050 | Batch 000/469 | Cost: 12776.3633\n",
            "Epoch: 050/050 | Batch 050/469 | Cost: 12830.2715\n",
            "Epoch: 050/050 | Batch 100/469 | Cost: 12358.5977\n",
            "Epoch: 050/050 | Batch 150/469 | Cost: 13409.3203\n",
            "Epoch: 050/050 | Batch 200/469 | Cost: 12998.4268\n",
            "Epoch: 050/050 | Batch 250/469 | Cost: 13520.4170\n",
            "Epoch: 050/050 | Batch 300/469 | Cost: 12749.2002\n",
            "Epoch: 050/050 | Batch 350/469 | Cost: 12690.4648\n",
            "Epoch: 050/050 | Batch 400/469 | Cost: 13226.1523\n",
            "Epoch: 050/050 | Batch 450/469 | Cost: 13155.6641\n",
            "Time elapsed: 13.87 min\n",
            "Total Training Time: 13.87 min\n"
          ]
        }
      ],
      "source": [
        "start_time = time.time()\n",
        "for epoch in range(num_epochs):\n",
        "    for batch_idx, (features, targets) in enumerate(train_loader):\n",
        "        \n",
        "        # don't need labels, only the images (features)\n",
        "        features = features.view(-1, 28*28).to(device)\n",
        "\n",
        "        ### FORWARD AND BACK PROP\n",
        "        z_mean, z_log_var, encoded, decoded = model(features)\n",
        "\n",
        "        # cost = reconstruction loss + Kullback-Leibler divergence\n",
        "        kl_divergence = (0.5 * (z_mean**2 + \n",
        "                                torch.exp(z_log_var) - z_log_var - 1)).sum()\n",
        "        pixelwise_bce = F.binary_cross_entropy(decoded, features, reduction='sum')\n",
        "        cost = kl_divergence + pixelwise_bce\n",
        "        \n",
        "        optimizer.zero_grad()\n",
        "        cost.backward()\n",
        "        \n",
        "        ### UPDATE MODEL PARAMETERS\n",
        "        optimizer.step()\n",
        "        \n",
        "        ### LOGGING\n",
        "        if not batch_idx % 50:\n",
        "            print ('Epoch: %03d/%03d | Batch %03d/%03d | Cost: %.4f' \n",
        "                   %(epoch+1, num_epochs, batch_idx, \n",
        "                     len(train_loader), cost))\n",
        "            \n",
        "    print('Time elapsed: %.2f min' % ((time.time() - start_time)/60))\n",
        "    \n",
        "print('Total Training Time: %.2f min' % ((time.time() - start_time)/60))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_6DS0bD2vWh6"
      },
      "source": [
        "# Evaluation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oG9LigjdvWh6"
      },
      "source": [
        "### Reconstruction"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "id": "kFB0XKp_vWh6",
        "outputId": "a954d304-96b4-4f89-eb6f-190a9176d506"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x180 with 30 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "##########################\n",
        "### VISUALIZATION\n",
        "##########################\n",
        "\n",
        "n_images = 15\n",
        "image_width = 28\n",
        "\n",
        "fig, axes = plt.subplots(nrows=2, ncols=n_images, \n",
        "                         sharex=True, sharey=True, figsize=(20, 2.5))\n",
        "orig_images = features[:n_images]\n",
        "decoded_images = decoded[:n_images]\n",
        "\n",
        "for i in range(n_images):\n",
        "    for ax, img in zip(axes, [orig_images, decoded_images]):\n",
        "        curr_img = img[i].detach().to(torch.device('cpu'))\n",
        "        ax[i].imshow(curr_img.view((image_width, image_width)), cmap='binary')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q6w46StJvWh7"
      },
      "source": [
        "### Generate new images"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 827
        },
        "id": "tMyAqDKCvWh7",
        "outputId": "93f8538a-e3fe-47b5-92dc-bbd0dbefae4e"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x180 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "for i in range(10):\n",
        "\n",
        "    ##########################\n",
        "    ### RANDOM SAMPLE\n",
        "    ##########################    \n",
        "    \n",
        "    n_images = 10\n",
        "    rand_features = torch.randn(n_images, num_latent).to(device)\n",
        "    new_images = model.decoder(rand_features)\n",
        "\n",
        "    ##########################\n",
        "    ### VISUALIZATION\n",
        "    ##########################\n",
        "\n",
        "    image_width = 28\n",
        "\n",
        "    fig, axes = plt.subplots(nrows=1, ncols=n_images, figsize=(10, 2.5), sharey=True)\n",
        "    decoded_images = new_images[:n_images]\n",
        "\n",
        "    for ax, img in zip(axes, decoded_images):\n",
        "        curr_img = img.detach().to(torch.device('cpu'))\n",
        "        ax.imshow(curr_img.view((image_width, image_width)), cmap='binary')\n",
        "        \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": "3.7.3"
    },
    "toc": {
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": false,
      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
      "toc_cell": false,
      "toc_position": {},
      "toc_section_display": true,
      "toc_window_display": false
    },
    "colab": {
      "provenance": []
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "6207c21a7373494799f19c6e54a03954": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_e34c050f8d374c928aa13f2befbb0eab",
              "IPY_MODEL_490cd4776ba14996918082fa8b2e977d",
              "IPY_MODEL_f0cf9e7400aa40ab8c2e28a8d81aa956"
            ],
            "layout": "IPY_MODEL_dfd8b2989c8c4cbca55145a778e27bde"
          }
        },
        "e34c050f8d374c928aa13f2befbb0eab": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_8141a41599aa4acbac909c4a65f7923c",
            "placeholder": "​",
            "style": "IPY_MODEL_8666774ae39b45b2958ce08b62064394",
            "value": "100%"
          }
        },
        "490cd4776ba14996918082fa8b2e977d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a1f3f753a38f481dad4b7140bba02c7c",
            "max": 9912422,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_28492675799c4b0082d6088a03f9a8c4",
            "value": 9912422
          }
        },
        "f0cf9e7400aa40ab8c2e28a8d81aa956": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1d4a875c10b246fcbbaec0ceb83d0704",
            "placeholder": "​",
            "style": "IPY_MODEL_e98940de978b466eb92cc58fa2dc62d1",
            "value": " 9912422/9912422 [00:00&lt;00:00, 69701744.17it/s]"
          }
        },
        "dfd8b2989c8c4cbca55145a778e27bde": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8141a41599aa4acbac909c4a65f7923c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8666774ae39b45b2958ce08b62064394": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a1f3f753a38f481dad4b7140bba02c7c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "28492675799c4b0082d6088a03f9a8c4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "1d4a875c10b246fcbbaec0ceb83d0704": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e98940de978b466eb92cc58fa2dc62d1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a403f74f46cb41c18ab462b73b408b27": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_f269b4a518dd4524807341e6e3ad1790",
              "IPY_MODEL_f57b9c6fec6e44b281615ffa2f094f6a",
              "IPY_MODEL_7151a694cdeb45019ac570cbd96e15b0"
            ],
            "layout": "IPY_MODEL_aac5762637e5466f86b24568cb9e5734"
          }
        },
        "f269b4a518dd4524807341e6e3ad1790": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ac128039a9504549b23977c0c511a987",
            "placeholder": "​",
            "style": "IPY_MODEL_1cf555f5008941e48bc350a7bb29f609",
            "value": "100%"
          }
        },
        "f57b9c6fec6e44b281615ffa2f094f6a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a621b3e9088e455493a7da17d6c5ddd8",
            "max": 28881,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_1b014a268b2a4b3bb2c2a31be32db98e",
            "value": 28881
          }
        },
        "7151a694cdeb45019ac570cbd96e15b0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_413b05cfc82f4e308ce019c88d8fde79",
            "placeholder": "​",
            "style": "IPY_MODEL_9e33cad7f595414aab11f0e30dfbf788",
            "value": " 28881/28881 [00:00&lt;00:00, 1029059.12it/s]"
          }
        },
        "aac5762637e5466f86b24568cb9e5734": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ac128039a9504549b23977c0c511a987": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1cf555f5008941e48bc350a7bb29f609": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a621b3e9088e455493a7da17d6c5ddd8": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1b014a268b2a4b3bb2c2a31be32db98e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "413b05cfc82f4e308ce019c88d8fde79": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "9e33cad7f595414aab11f0e30dfbf788": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "285197313d734ca3967593eddf7ad08f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_612ae9dc40664b08b0e0995ad9ac6b88",
              "IPY_MODEL_3bf7be7396ec460d9677fa039a19cd4f",
              "IPY_MODEL_4e17fa62793344d884744fe7affa86e8"
            ],
            "layout": "IPY_MODEL_7142a01641a54958a815391e043d990d"
          }
        },
        "612ae9dc40664b08b0e0995ad9ac6b88": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_0cf81e232b97431c831ce2484cbaa38c",
            "placeholder": "​",
            "style": "IPY_MODEL_d0111506f49241a0a568719684393173",
            "value": "100%"
          }
        },
        "3bf7be7396ec460d9677fa039a19cd4f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_8d365bc3a37744f7ab79b12c11440d70",
            "max": 1648877,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_904467d8c7534decba617db7d522fd24",
            "value": 1648877
          }
        },
        "4e17fa62793344d884744fe7affa86e8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_29a5a904b0354529baab5f07eb255c73",
            "placeholder": "​",
            "style": "IPY_MODEL_ef4c0aad69734e7cba25c9cf7881ca4e",
            "value": " 1648877/1648877 [00:00&lt;00:00, 43479764.85it/s]"
          }
        },
        "7142a01641a54958a815391e043d990d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "0cf81e232b97431c831ce2484cbaa38c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "d0111506f49241a0a568719684393173": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "8d365bc3a37744f7ab79b12c11440d70": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "904467d8c7534decba617db7d522fd24": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "29a5a904b0354529baab5f07eb255c73": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ef4c0aad69734e7cba25c9cf7881ca4e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "7f2d1249b36a48a5993b6f652cc058e0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_f6c430a047e2446592461e93502a515a",
              "IPY_MODEL_a80e43df1c2e4bc0adf12f1d5b73afe2",
              "IPY_MODEL_0d8a32e808fc403e844eeede9289ee2d"
            ],
            "layout": "IPY_MODEL_2cc326deac81495c945ce55c8f6ff77e"
          }
        },
        "f6c430a047e2446592461e93502a515a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_7d4b16d5bd644a049d5f1639c3cb9752",
            "placeholder": "​",
            "style": "IPY_MODEL_b33765fbc4ce4406b39c81636b9dc680",
            "value": "100%"
          }
        },
        "a80e43df1c2e4bc0adf12f1d5b73afe2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_04c4c51f1fd64efa8d97e510f8568821",
            "max": 4542,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_e86f005672d844a7844172a31fe9c2ba",
            "value": 4542
          }
        },
        "0d8a32e808fc403e844eeede9289ee2d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e07dc21cb88e4a2e9c2588732b118ebe",
            "placeholder": "​",
            "style": "IPY_MODEL_cd5159792bb44c44a4bea270044b9655",
            "value": " 4542/4542 [00:00&lt;00:00, 113882.72it/s]"
          }
        },
        "2cc326deac81495c945ce55c8f6ff77e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7d4b16d5bd644a049d5f1639c3cb9752": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b33765fbc4ce4406b39c81636b9dc680": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "04c4c51f1fd64efa8d97e510f8568821": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e86f005672d844a7844172a31fe9c2ba": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "e07dc21cb88e4a2e9c2588732b118ebe": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "cd5159792bb44c44a4bea270044b9655": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}