ct2.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ts3o3A2ry1tX",
        "outputId": "a33d7cb9-43a2-40f3-8072-a7615087c240"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd \"/content/drive/MyDrive/A\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xQelcWIBy3Ke",
        "outputId": "cfa666a9-7f1f-49e6-98ec-5fce4857ab2a"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/A\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "VEEQV5z7MrGO"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "!pip3 install tensorflow\n",
        "!pip3 install nibabel\n",
        "!pip3 install scipy\n",
        "!pip3 install -r requirements.txt\n",
        "!pip3 install torchio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "2uDRE3YBypKh"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "import time\n",
        "import zipfile\n",
        "import numpy as np\n",
        "import nibabel as nib\n",
        "from tensorflow import keras\n",
        "from scipy import ndimage\n",
        "\n",
        "from torch.optim import Adam\n",
        "from torch import nn\n",
        "import generate_model\n",
        "import models.EfficientNet\n",
        "import torch\n",
        "from torch.utils.data import DataLoader\n",
        "import torchio as tio\n",
        "\n",
        "%matplotlib notebook\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "IE6wlXZhypKh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e7052b72-113e-4f85-e58a-07ac986b2833"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CT scans with normal lung tissue: 100\n",
            "CT scans with abnormal lung tissue: 100\n"
          ]
        }
      ],
      "source": [
        "# Download url of normal CT scans and abnormal scans.\n",
        "\n",
        "if not os.path.exists(\"CT-0.zip\"):\n",
        "  url = \"https://github.com/hasibzunair/3D-image-classification-tutorial/releases/download/v0.2/CT-0.zip\"\n",
        "  filename = os.path.join(os.getcwd(), \"CT-0.zip\")\n",
        "  keras.utils.get_file(filename, url)\n",
        "\n",
        "\n",
        "if not os.path.exists(\"CT-23.zip\"):\n",
        "  url = \"https://github.com/hasibzunair/3D-image-classification-tutorial/releases/download/v0.2/CT-23.zip\"\n",
        "  filename = os.path.join(os.getcwd(), \"CT-23.zip\")\n",
        "  keras.utils.get_file(filename, url)\n",
        "\n",
        "\n",
        "if not os.path.exists(\"./CTData\"):\n",
        "    os.makedirs(\"CTData\")\n",
        "\n",
        "    with zipfile.ZipFile(\"CT-0.zip\", \"r\") as z_fp:\n",
        "        z_fp.extractall(\"./CTData/\")\n",
        "\n",
        "    with zipfile.ZipFile(\"CT-23.zip\", \"r\") as z_fp:\n",
        "        z_fp.extractall(\"./CTData/\")\n",
        "\n",
        "\n",
        "normal_scan_paths = [\n",
        "    (os.path.join(os.getcwd(), \"CTData/CT-0\", x), 0)\n",
        "    for x in os.listdir(\"CTData/CT-0\")\n",
        "]\n",
        "\n",
        "abnormal_scan_paths = [\n",
        "    (os.path.join(os.getcwd(), \"CTData/CT-23\", x), 1)\n",
        "    for x in os.listdir(\"CTData/CT-23\")\n",
        "]\n",
        "\n",
        "print(\"CT scans with normal lung tissue: \" + str(len(normal_scan_paths)))\n",
        "print(\"CT scans with abnormal lung tissue: \" + str(len(abnormal_scan_paths)))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# both dataset should have equal samples.\n",
        "\n",
        "split = 0.7\n",
        "\n",
        "permutation = np.random.permutation(range(len(normal_scan_paths)))\n",
        "train = permutation[:int(len(normal_scan_paths) * split)]\n",
        "val = permutation[int(len(normal_scan_paths) * split):]\n",
        "\n",
        "train_subjects = []\n",
        "for i in train:\n",
        "  subject_path_n, label_n = normal_scan_paths[i]\n",
        "  subject_path_a, label_a = abnormal_scan_paths[i]\n",
        "\n",
        "  subject_n = tio.Subject(t1 = tio.ScalarImage(subject_path_n), label = label_n)\n",
        "  subject_a = tio.Subject(t1 = tio.ScalarImage(subject_path_a), label = label_a)\n",
        "\n",
        "  train_subjects.append(subject_n)\n",
        "  train_subjects.append(subject_a)\n",
        "\n",
        "\n",
        "\n",
        "val_subjects = []\n",
        "for i in val:\n",
        "  subject_path_n, label_n = normal_scan_paths[i]\n",
        "  subject_path_a, label_a = abnormal_scan_paths[i]\n",
        "\n",
        "  subject_n = tio.Subject(t1 = tio.ScalarImage(subject_path_n), label = label_n)\n",
        "  subject_a = tio.Subject(t1 = tio.ScalarImage(subject_path_a), label = label_a)\n",
        "\n",
        "  val_subjects.append(subject_n)\n",
        "  val_subjects.append(subject_a)"
      ],
      "metadata": {
        "id": "vuf8oRy7ZePW"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "normalize = tio.RescaleIntensity(out_min_max = (0, 1), in_min_max = (-1000, 400))\n",
        "resize = tio.Resize((128, 128, 64))\n",
        "affine = tio.OneOf({tio.RandomAffine(): 0.8 })\n",
        "\n",
        "train_transform = tio.Compose([normalize, resize, affine])\n",
        "val_transform = tio.Compose([normalize, resize])\n",
        "\n",
        "train_subjects_dataset = tio.SubjectsDataset(train_subjects, transform=train_transform)\n",
        "val_subjects_dataset = tio.SubjectsDataset(val_subjects, transform=val_transform)\n",
        "\n",
        "training_loader = DataLoader(train_subjects_dataset, shuffle=True, batch_size=4)\n",
        "validation_loader = DataLoader(val_subjects_dataset, batch_size=4)\n",
        "\n",
        "train_steps = len(training_loader.dataset) // 4\n",
        "val_steps = len(validation_loader.dataset) // 4"
      ],
      "metadata": {
        "id": "D_NI5ATcfYKg"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "gd_XZaXfypKm"
      },
      "outputs": [],
      "source": [
        "def train_model(epoch, model, device, lossFn, optimizer, history, mute = True):\n",
        "\tprint(\"[INFO] training the network...\")\n",
        "\tstartTime = time.time()\n",
        "\thistory[\"train_loss\"] = []\n",
        "\thistory[\"train_acc\"] = []\n",
        "\thistory[\"val_loss\"] = []\n",
        "\thistory[\"val_acc\"] = []\n",
        "\tfor e in range(0, epoch):\n",
        "\t\tmodel.train()\n",
        "\t\ttotalTrainLoss = 0\n",
        "\t\ttotalValLoss = 0\n",
        "\t\ttrainCorrect = 0\n",
        "\t\tvalCorrect = 0\n",
        "\t\tfor subjects_batch in training_loader:\n",
        "\t\t\tx = subjects_batch['t1'][tio.DATA].to(device)\n",
        "\t\t\ty = subjects_batch['label'].to(device)\n",
        "\t\t\toptimizer.zero_grad()\n",
        "\t\t\tpred = model(x)\n",
        "\t\t\tloss = lossFn(pred, y)\n",
        "\t\t\tloss.backward()\n",
        "\t\t\toptimizer.step()\n",
        "\t\t\ttotalTrainLoss += loss\n",
        "\t\t\ttrainCorrect += (pred.argmax(1) == y).type(torch.float).sum().item()\n",
        "\n",
        "\t\twith torch.no_grad():\n",
        "\t\t\tmodel.eval()\n",
        "\t\t\tfor subjects_batch in validation_loader:\n",
        "\t\t\t\tx = subjects_batch['t1'][tio.DATA].to(device)\n",
        "\t\t\t\ty = subjects_batch['label'].to(device)\n",
        "\t\t\t\tpred = model(x)\n",
        "\t\t\t\ttotalValLoss += lossFn(pred, y)\n",
        "\t\t\t\tvalCorrect += (pred.argmax(1) == y).type(torch.float).sum().item()\n",
        "\n",
        "\t\tavgTrainLoss = totalTrainLoss / train_steps\n",
        "\t\tavgValLoss = totalValLoss / val_steps\n",
        "\t\ttrainCorrect = trainCorrect / len(training_loader.dataset)\n",
        "\t\tvalCorrect = valCorrect / len(validation_loader.dataset)\n",
        "\t\thistory[\"train_loss\"].append(avgTrainLoss.cpu().detach().numpy())\n",
        "\t\thistory[\"train_acc\"].append(trainCorrect)\n",
        "\t\thistory[\"val_loss\"].append(avgValLoss.cpu().detach().numpy())\n",
        "\t\thistory[\"val_acc\"].append(valCorrect)\n",
        "\t\tif not mute:\n",
        "\t\t\tprint(\"[INFO] EPOCH: {}/{}\".format(e + 1, epoch))\n",
        "\t\t\tprint(\"Train loss: {:.6f}, Train accuracy: {:.4f}\".format(\n",
        "\t\t\t\tavgTrainLoss, trainCorrect))\n",
        "\t\t\tprint(\"Val loss: {:.6f}, Val accuracy: {:.4f}\\n\".format(\n",
        "\t\t\t\tavgValLoss, valCorrect))\n",
        "\tprint(\"[INFO] total time taken to train the model: {}s\".format(\n",
        "\t\tround(time.time() - startTime, 2)))\n",
        "\n",
        "def plot_history(history):\n",
        "\tfig, ax = plt.subplots(1, 2, figsize=(20, 3))\n",
        "\tax = ax.ravel()\n",
        "\tfor i, metric in enumerate([\"acc\", \"loss\"]):\n",
        "\t\t\tax[i].plot(history[\"train_\" + metric])\n",
        "\t\t\tax[i].plot(history[\"val_\" + metric])\n",
        "\t\t\tax[i].set_title(\"Model {}\".format(metric))\n",
        "\t\t\tax[i].set_xlabel(\"epochs\")\n",
        "\t\t\tax[i].set_ylabel(metric)\n",
        "\t\t\tax[i].legend([\"train\", \"val\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rdrPKiF1ypKm",
        "outputId": "b3b8caf7-7b5c-4ee3-f4f2-a93aa9b2bee7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[INFO] training the network...\n",
            "[INFO] EPOCH: 1/200\n",
            "Train loss: 0.875454, Train accuracy: 0.5071\n",
            "Val loss: 0.693485, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 2/200\n",
            "Train loss: 0.800749, Train accuracy: 0.4214\n",
            "Val loss: 0.694800, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 3/200\n",
            "Train loss: 0.727618, Train accuracy: 0.5429\n",
            "Val loss: 0.693163, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 4/200\n",
            "Train loss: 0.760523, Train accuracy: 0.4071\n",
            "Val loss: 0.699752, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 5/200\n",
            "Train loss: 0.736830, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 6/200\n",
            "Train loss: 0.756135, Train accuracy: 0.4429\n",
            "Val loss: 0.705288, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 7/200\n",
            "Train loss: 0.757724, Train accuracy: 0.4714\n",
            "Val loss: 0.693170, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 8/200\n",
            "Train loss: 0.732631, Train accuracy: 0.5429\n",
            "Val loss: 0.716309, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 9/200\n",
            "Train loss: 0.789131, Train accuracy: 0.4429\n",
            "Val loss: 0.693478, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 10/200\n",
            "Train loss: 0.735494, Train accuracy: 0.4643\n",
            "Val loss: 0.695242, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 11/200\n",
            "Train loss: 0.756052, Train accuracy: 0.5000\n",
            "Val loss: 0.696292, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 12/200\n",
            "Train loss: 0.713247, Train accuracy: 0.5214\n",
            "Val loss: 0.700806, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 13/200\n",
            "Train loss: 0.715047, Train accuracy: 0.5143\n",
            "Val loss: 0.693389, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 14/200\n",
            "Train loss: 0.725375, Train accuracy: 0.5071\n",
            "Val loss: 0.693408, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 15/200\n",
            "Train loss: 0.738070, Train accuracy: 0.5000\n",
            "Val loss: 0.693797, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 16/200\n",
            "Train loss: 0.736779, Train accuracy: 0.4714\n",
            "Val loss: 0.693646, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 17/200\n",
            "Train loss: 0.724975, Train accuracy: 0.4786\n",
            "Val loss: 0.693499, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 18/200\n",
            "Train loss: 0.734169, Train accuracy: 0.4429\n",
            "Val loss: 0.695974, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 19/200\n",
            "Train loss: 0.713562, Train accuracy: 0.5000\n",
            "Val loss: 0.705212, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 20/200\n",
            "Train loss: 0.709993, Train accuracy: 0.5071\n",
            "Val loss: 0.706331, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 21/200\n",
            "Train loss: 0.725319, Train accuracy: 0.5214\n",
            "Val loss: 0.694001, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 22/200\n",
            "Train loss: 0.729771, Train accuracy: 0.4857\n",
            "Val loss: 0.707976, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 23/200\n",
            "Train loss: 0.702001, Train accuracy: 0.5571\n",
            "Val loss: 1.687442, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 24/200\n",
            "Train loss: 0.730263, Train accuracy: 0.4929\n",
            "Val loss: 1.596817, Val accuracy: 0.4500\n",
            "\n",
            "[INFO] EPOCH: 25/200\n",
            "Train loss: 0.696630, Train accuracy: 0.5143\n",
            "Val loss: 0.729109, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 26/200\n",
            "Train loss: 0.697528, Train accuracy: 0.5286\n",
            "Val loss: 1.255297, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 27/200\n",
            "Train loss: 0.723885, Train accuracy: 0.4786\n",
            "Val loss: 0.726001, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 28/200\n",
            "Train loss: 0.695928, Train accuracy: 0.4929\n",
            "Val loss: 0.695884, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 29/200\n",
            "Train loss: 0.709539, Train accuracy: 0.5643\n",
            "Val loss: 0.698161, Val accuracy: 0.4000\n",
            "\n",
            "[INFO] EPOCH: 30/200\n",
            "Train loss: 0.700715, Train accuracy: 0.5357\n",
            "Val loss: 0.739433, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 31/200\n",
            "Train loss: 0.702604, Train accuracy: 0.5500\n",
            "Val loss: 0.711569, Val accuracy: 0.3500\n",
            "\n",
            "[INFO] EPOCH: 32/200\n",
            "Train loss: 0.712345, Train accuracy: 0.4786\n",
            "Val loss: 0.715030, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 33/200\n",
            "Train loss: 0.714941, Train accuracy: 0.4643\n",
            "Val loss: 0.705402, Val accuracy: 0.4833\n",
            "\n",
            "[INFO] EPOCH: 34/200\n",
            "Train loss: 0.696670, Train accuracy: 0.5857\n",
            "Val loss: 2.135496, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 35/200\n",
            "Train loss: 0.729172, Train accuracy: 0.5000\n",
            "Val loss: 1.114621, Val accuracy: 0.4167\n",
            "\n",
            "[INFO] EPOCH: 36/200\n",
            "Train loss: 0.680673, Train accuracy: 0.5929\n",
            "Val loss: 0.886349, Val accuracy: 0.5167\n",
            "\n",
            "[INFO] EPOCH: 37/200\n",
            "Train loss: 0.704111, Train accuracy: 0.5429\n",
            "Val loss: 0.687329, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 38/200\n",
            "Train loss: 0.711134, Train accuracy: 0.4643\n",
            "Val loss: 0.682660, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 39/200\n",
            "Train loss: 0.692109, Train accuracy: 0.5500\n",
            "Val loss: 0.650608, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 40/200\n",
            "Train loss: 0.631439, Train accuracy: 0.6429\n",
            "Val loss: 1.872861, Val accuracy: 0.5167\n",
            "\n",
            "[INFO] EPOCH: 41/200\n",
            "Train loss: 0.656283, Train accuracy: 0.6214\n",
            "Val loss: 0.755913, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 42/200\n",
            "Train loss: 0.669825, Train accuracy: 0.6357\n",
            "Val loss: 0.683398, Val accuracy: 0.4833\n",
            "\n",
            "[INFO] EPOCH: 43/200\n",
            "Train loss: 0.663194, Train accuracy: 0.6286\n",
            "Val loss: 0.692804, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 44/200\n",
            "Train loss: 0.670692, Train accuracy: 0.6643\n",
            "Val loss: 0.722173, Val accuracy: 0.5500\n",
            "\n",
            "[INFO] EPOCH: 45/200\n",
            "Train loss: 0.612735, Train accuracy: 0.6643\n",
            "Val loss: 0.726458, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 46/200\n",
            "Train loss: 0.683267, Train accuracy: 0.6286\n",
            "Val loss: 1.129577, Val accuracy: 0.6833\n",
            "\n",
            "[INFO] EPOCH: 47/200\n",
            "Train loss: 0.671515, Train accuracy: 0.6000\n",
            "Val loss: 0.684652, Val accuracy: 0.5500\n",
            "\n",
            "[INFO] EPOCH: 48/200\n",
            "Train loss: 0.645937, Train accuracy: 0.6143\n",
            "Val loss: 0.674564, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 49/200\n",
            "Train loss: 0.651517, Train accuracy: 0.6500\n",
            "Val loss: 0.711527, Val accuracy: 0.5167\n",
            "\n",
            "[INFO] EPOCH: 50/200\n",
            "Train loss: 0.647306, Train accuracy: 0.6357\n",
            "Val loss: 0.666684, Val accuracy: 0.6167\n",
            "\n",
            "[INFO] EPOCH: 51/200\n",
            "Train loss: 0.645650, Train accuracy: 0.6500\n",
            "Val loss: 2.024784, Val accuracy: 0.4667\n",
            "\n",
            "[INFO] EPOCH: 52/200\n",
            "Train loss: 0.626881, Train accuracy: 0.6429\n",
            "Val loss: 0.883807, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 53/200\n",
            "Train loss: 0.644360, Train accuracy: 0.6357\n",
            "Val loss: 1.004322, Val accuracy: 0.5500\n",
            "\n",
            "[INFO] EPOCH: 54/200\n",
            "Train loss: 0.650100, Train accuracy: 0.6643\n",
            "Val loss: 0.833627, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 55/200\n",
            "Train loss: 0.632117, Train accuracy: 0.6929\n",
            "Val loss: 0.623265, Val accuracy: 0.6500\n",
            "\n",
            "[INFO] EPOCH: 56/200\n",
            "Train loss: 0.622281, Train accuracy: 0.6857\n",
            "Val loss: 0.668013, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 57/200\n",
            "Train loss: 0.534558, Train accuracy: 0.7643\n",
            "Val loss: 0.717319, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 58/200\n",
            "Train loss: 0.653184, Train accuracy: 0.6071\n",
            "Val loss: 0.667163, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 59/200\n",
            "Train loss: 0.578032, Train accuracy: 0.7286\n",
            "Val loss: 0.664286, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 60/200\n",
            "Train loss: 0.609030, Train accuracy: 0.6929\n",
            "Val loss: 0.636316, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 61/200\n",
            "Train loss: 0.578882, Train accuracy: 0.7286\n",
            "Val loss: 0.678704, Val accuracy: 0.5500\n",
            "\n",
            "[INFO] EPOCH: 62/200\n",
            "Train loss: 0.599466, Train accuracy: 0.7071\n",
            "Val loss: 0.712257, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 63/200\n",
            "Train loss: 0.634616, Train accuracy: 0.7071\n",
            "Val loss: 0.665739, Val accuracy: 0.6333\n",
            "\n",
            "[INFO] EPOCH: 64/200\n",
            "Train loss: 0.579580, Train accuracy: 0.7500\n",
            "Val loss: 0.844668, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 65/200\n",
            "Train loss: 0.635567, Train accuracy: 0.6357\n",
            "Val loss: 0.767210, Val accuracy: 0.4667\n",
            "\n",
            "[INFO] EPOCH: 66/200\n",
            "Train loss: 0.579199, Train accuracy: 0.6929\n",
            "Val loss: 0.632989, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 67/200\n",
            "Train loss: 0.620368, Train accuracy: 0.6786\n",
            "Val loss: 0.628513, Val accuracy: 0.6500\n",
            "\n",
            "[INFO] EPOCH: 68/200\n",
            "Train loss: 0.525042, Train accuracy: 0.7429\n",
            "Val loss: 0.640495, Val accuracy: 0.6167\n",
            "\n",
            "[INFO] EPOCH: 69/200\n",
            "Train loss: 0.645194, Train accuracy: 0.6571\n",
            "Val loss: 0.652466, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 70/200\n",
            "Train loss: 0.616760, Train accuracy: 0.6786\n",
            "Val loss: 0.706577, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 71/200\n",
            "Train loss: 0.541525, Train accuracy: 0.7643\n",
            "Val loss: 0.722482, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 72/200\n",
            "Train loss: 0.657210, Train accuracy: 0.6571\n",
            "Val loss: 0.763264, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 73/200\n",
            "Train loss: 0.662507, Train accuracy: 0.6286\n",
            "Val loss: 0.704682, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 74/200\n",
            "Train loss: 0.617256, Train accuracy: 0.6500\n",
            "Val loss: 0.689768, Val accuracy: 0.6167\n",
            "\n",
            "[INFO] EPOCH: 75/200\n",
            "Train loss: 0.628469, Train accuracy: 0.6643\n",
            "Val loss: 0.687863, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 76/200\n",
            "Train loss: 0.601784, Train accuracy: 0.6857\n",
            "Val loss: 0.696507, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 77/200\n",
            "Train loss: 0.548886, Train accuracy: 0.7214\n",
            "Val loss: 0.687362, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 78/200\n",
            "Train loss: 0.637578, Train accuracy: 0.6500\n",
            "Val loss: 0.706835, Val accuracy: 0.4667\n",
            "\n",
            "[INFO] EPOCH: 79/200\n",
            "Train loss: 0.631480, Train accuracy: 0.6786\n",
            "Val loss: 0.719421, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 80/200\n",
            "Train loss: 0.644682, Train accuracy: 0.6929\n",
            "Val loss: 0.739231, Val accuracy: 0.4500\n",
            "\n",
            "[INFO] EPOCH: 81/200\n",
            "Train loss: 0.577819, Train accuracy: 0.7429\n",
            "Val loss: 0.756840, Val accuracy: 0.4833\n",
            "\n",
            "[INFO] EPOCH: 82/200\n",
            "Train loss: 0.612294, Train accuracy: 0.7071\n",
            "Val loss: 0.680511, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 83/200\n",
            "Train loss: 0.630334, Train accuracy: 0.6714\n",
            "Val loss: 0.672866, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 84/200\n",
            "Train loss: 0.591619, Train accuracy: 0.7143\n",
            "Val loss: 0.710966, Val accuracy: 0.5167\n",
            "\n",
            "[INFO] EPOCH: 85/200\n",
            "Train loss: 0.632349, Train accuracy: 0.6643\n",
            "Val loss: 0.917392, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 86/200\n",
            "Train loss: 0.622797, Train accuracy: 0.6571\n",
            "Val loss: 1.562197, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 87/200\n",
            "Train loss: 0.604075, Train accuracy: 0.6786\n",
            "Val loss: 0.669820, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 88/200\n",
            "Train loss: 0.651180, Train accuracy: 0.6500\n",
            "Val loss: 0.663528, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 89/200\n",
            "Train loss: 0.593616, Train accuracy: 0.7429\n",
            "Val loss: 0.703027, Val accuracy: 0.3000\n",
            "\n",
            "[INFO] EPOCH: 90/200\n",
            "Train loss: 0.622436, Train accuracy: 0.6857\n",
            "Val loss: 0.588025, Val accuracy: 0.6667\n",
            "\n",
            "[INFO] EPOCH: 91/200\n",
            "Train loss: 0.700458, Train accuracy: 0.5714\n",
            "Val loss: 0.659295, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 92/200\n",
            "Train loss: 0.607894, Train accuracy: 0.7214\n",
            "Val loss: 0.869993, Val accuracy: 0.5833\n",
            "\n",
            "[INFO] EPOCH: 93/200\n",
            "Train loss: 0.583206, Train accuracy: 0.6857\n",
            "Val loss: 0.751224, Val accuracy: 0.6167\n",
            "\n",
            "[INFO] EPOCH: 94/200\n",
            "Train loss: 0.620114, Train accuracy: 0.6786\n",
            "Val loss: 0.690471, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 95/200\n",
            "Train loss: 0.538163, Train accuracy: 0.7357\n",
            "Val loss: 0.916322, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 96/200\n",
            "Train loss: 0.635849, Train accuracy: 0.6571\n",
            "Val loss: 0.638273, Val accuracy: 0.6167\n",
            "\n",
            "[INFO] EPOCH: 97/200\n",
            "Train loss: 0.525065, Train accuracy: 0.7571\n",
            "Val loss: 0.784922, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 98/200\n",
            "Train loss: 0.631455, Train accuracy: 0.7000\n",
            "Val loss: 0.712689, Val accuracy: 0.6167\n",
            "\n",
            "[INFO] EPOCH: 99/200\n",
            "Train loss: 0.572865, Train accuracy: 0.7071\n",
            "Val loss: 0.719855, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 100/200\n",
            "Train loss: 0.601076, Train accuracy: 0.7000\n",
            "Val loss: 0.686623, Val accuracy: 0.4833\n",
            "\n",
            "[INFO] EPOCH: 101/200\n",
            "Train loss: 0.567064, Train accuracy: 0.7429\n",
            "Val loss: 0.668956, Val accuracy: 0.6333\n",
            "\n",
            "[INFO] EPOCH: 102/200\n",
            "Train loss: 0.582409, Train accuracy: 0.7143\n",
            "Val loss: 0.730573, Val accuracy: 0.4833\n",
            "\n",
            "[INFO] EPOCH: 103/200\n",
            "Train loss: 0.534063, Train accuracy: 0.7714\n",
            "Val loss: 1.001945, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 104/200\n",
            "Train loss: 0.593828, Train accuracy: 0.6857\n",
            "Val loss: 0.709395, Val accuracy: 0.6000\n",
            "\n",
            "[INFO] EPOCH: 105/200\n",
            "Train loss: 0.546191, Train accuracy: 0.7786\n",
            "Val loss: 0.664745, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 106/200\n",
            "Train loss: 0.594407, Train accuracy: 0.6786\n",
            "Val loss: 0.674044, Val accuracy: 0.5500\n",
            "\n",
            "[INFO] EPOCH: 107/200\n",
            "Train loss: 0.613065, Train accuracy: 0.7214\n",
            "Val loss: 0.663679, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 108/200\n",
            "Train loss: 0.564769, Train accuracy: 0.7571\n",
            "Val loss: 0.710486, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 109/200\n",
            "Train loss: 0.560377, Train accuracy: 0.7429\n",
            "Val loss: 0.702963, Val accuracy: 0.5667\n",
            "\n",
            "[INFO] EPOCH: 110/200\n",
            "Train loss: 0.598565, Train accuracy: 0.7286\n",
            "Val loss: 0.727994, Val accuracy: 0.5333\n",
            "\n",
            "[INFO] EPOCH: 111/200\n",
            "Train loss: 0.521765, Train accuracy: 0.7643\n",
            "Val loss: 0.711390, Val accuracy: 0.6333\n",
            "\n",
            "[INFO] EPOCH: 112/200\n",
            "Train loss: 0.549636, Train accuracy: 0.7357\n",
            "Val loss: 0.754434, Val accuracy: 0.5167\n",
            "\n",
            "[INFO] EPOCH: 113/200\n",
            "Train loss: 0.535871, Train accuracy: 0.7500\n",
            "Val loss: 0.759353, Val accuracy: 0.6333\n",
            "\n",
            "[INFO] EPOCH: 114/200\n",
            "Train loss: 0.568559, Train accuracy: 0.7071\n",
            "Val loss: 0.661129, Val accuracy: 0.6167\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# EfficientNet b0\n",
        "model = models.EfficientNet.EfficientNet3D.from_name(\n",
        "            'efficientnet-b0', \n",
        "            override_params={'num_classes': 2}, \n",
        "            in_channels=1).cuda()\n",
        "lossFn = nn.CrossEntropyLoss()\n",
        "optimizer = Adam(model.parameters(), lr = 10e-4, weight_decay = 10e-5)\n",
        "history_0 = {}\n",
        "\n",
        "train_model(200, model, device, lossFn, optimizer, history_0, mute = False)\n",
        "plot_history(history_0)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# EfficientNet b0\n",
        "model = models.EfficientNet.EfficientNet3D.from_name(\n",
        "            'efficientnet-b0', \n",
        "            override_params={'num_classes': 2}, \n",
        "            in_channels=1).cuda()\n",
        "lossFn = nn.CrossEntropyLoss()\n",
        "optimizer = Adam(model.parameters(), lr = 10e-4, weight_decay = 5 * 10e-3)\n",
        "history_1 = {}\n",
        "\n",
        "train_model(200, model, device, lossFn, optimizer, history_1, mute = False)\n",
        "plot_history(history_1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "6GcAya9pR9S9",
        "outputId": "f5b3ebd6-44d5-46f2-f082-3789fb07d49d"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[INFO] training the network...\n",
            "[INFO] EPOCH: 1/200\n",
            "Train loss: 0.948143, Train accuracy: 0.4500\n",
            "Val loss: 0.694396, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 2/200\n",
            "Train loss: 0.776182, Train accuracy: 0.4714\n",
            "Val loss: 0.693220, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 3/200\n",
            "Train loss: 0.720956, Train accuracy: 0.4929\n",
            "Val loss: 0.693436, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 4/200\n",
            "Train loss: 0.732843, Train accuracy: 0.5143\n",
            "Val loss: 0.693369, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 5/200\n",
            "Train loss: 0.729529, Train accuracy: 0.5000\n",
            "Val loss: 0.693282, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 6/200\n",
            "Train loss: 0.728729, Train accuracy: 0.4929\n",
            "Val loss: 0.693877, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 7/200\n",
            "Train loss: 0.710280, Train accuracy: 0.5071\n",
            "Val loss: 0.693389, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 8/200\n",
            "Train loss: 0.705760, Train accuracy: 0.5071\n",
            "Val loss: 0.693227, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 9/200\n",
            "Train loss: 0.715116, Train accuracy: 0.4286\n",
            "Val loss: 0.693162, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 10/200\n",
            "Train loss: 0.706089, Train accuracy: 0.5000\n",
            "Val loss: 0.693446, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 11/200\n",
            "Train loss: 0.723879, Train accuracy: 0.4500\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 12/200\n",
            "Train loss: 0.706205, Train accuracy: 0.4500\n",
            "Val loss: 0.693365, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 13/200\n",
            "Train loss: 0.699698, Train accuracy: 0.5071\n",
            "Val loss: 0.693506, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 14/200\n",
            "Train loss: 0.699885, Train accuracy: 0.5643\n",
            "Val loss: 0.693184, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 15/200\n",
            "Train loss: 0.713166, Train accuracy: 0.4643\n",
            "Val loss: 0.693191, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 16/200\n",
            "Train loss: 0.700226, Train accuracy: 0.5071\n",
            "Val loss: 0.693315, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 17/200\n",
            "Train loss: 0.701578, Train accuracy: 0.5286\n",
            "Val loss: 0.693206, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 18/200\n",
            "Train loss: 0.697034, Train accuracy: 0.4857\n",
            "Val loss: 0.693187, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 19/200\n",
            "Train loss: 0.693562, Train accuracy: 0.5000\n",
            "Val loss: 0.693163, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 20/200\n",
            "Train loss: 0.693356, Train accuracy: 0.5000\n",
            "Val loss: 0.693193, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 21/200\n",
            "Train loss: 0.693353, Train accuracy: 0.5000\n",
            "Val loss: 0.693182, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 22/200\n",
            "Train loss: 0.693369, Train accuracy: 0.5000\n",
            "Val loss: 0.693210, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 23/200\n",
            "Train loss: 0.693518, Train accuracy: 0.5000\n",
            "Val loss: 0.693164, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 24/200\n",
            "Train loss: 0.693587, Train accuracy: 0.5000\n",
            "Val loss: 0.693187, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 25/200\n",
            "Train loss: 0.693270, Train accuracy: 0.5000\n",
            "Val loss: 0.693176, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 26/200\n",
            "Train loss: 0.693284, Train accuracy: 0.5000\n",
            "Val loss: 0.693160, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 27/200\n",
            "Train loss: 0.693339, Train accuracy: 0.5000\n",
            "Val loss: 0.693168, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 28/200\n",
            "Train loss: 0.693294, Train accuracy: 0.5000\n",
            "Val loss: 0.693163, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 29/200\n",
            "Train loss: 0.693272, Train accuracy: 0.5000\n",
            "Val loss: 0.693160, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 30/200\n",
            "Train loss: 0.693420, Train accuracy: 0.5000\n",
            "Val loss: 0.693153, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 31/200\n",
            "Train loss: 0.693346, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 32/200\n",
            "Train loss: 0.693336, Train accuracy: 0.4857\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 33/200\n",
            "Train loss: 0.693263, Train accuracy: 0.5000\n",
            "Val loss: 0.693156, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 34/200\n",
            "Train loss: 0.693283, Train accuracy: 0.5000\n",
            "Val loss: 0.693161, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 35/200\n",
            "Train loss: 0.693533, Train accuracy: 0.5000\n",
            "Val loss: 0.693163, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 36/200\n",
            "Train loss: 0.693249, Train accuracy: 0.5000\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 37/200\n",
            "Train loss: 0.693486, Train accuracy: 0.4071\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 38/200\n",
            "Train loss: 0.693575, Train accuracy: 0.5000\n",
            "Val loss: 0.693163, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 39/200\n",
            "Train loss: 0.693257, Train accuracy: 0.5000\n",
            "Val loss: 0.693159, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 40/200\n",
            "Train loss: 0.693249, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 41/200\n",
            "Train loss: 0.693304, Train accuracy: 0.4214\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 42/200\n",
            "Train loss: 0.693195, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 43/200\n",
            "Train loss: 0.693330, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 44/200\n",
            "Train loss: 0.693297, Train accuracy: 0.4214\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 45/200\n",
            "Train loss: 0.693215, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 46/200\n",
            "Train loss: 0.693322, Train accuracy: 0.5000\n",
            "Val loss: 0.693153, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 47/200\n",
            "Train loss: 0.693228, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 48/200\n",
            "Train loss: 0.693306, Train accuracy: 0.4571\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 49/200\n",
            "Train loss: 0.693246, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 50/200\n",
            "Train loss: 0.693331, Train accuracy: 0.4857\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 51/200\n",
            "Train loss: 0.693609, Train accuracy: 0.4714\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 52/200\n",
            "Train loss: 0.693230, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 53/200\n",
            "Train loss: 0.693278, Train accuracy: 0.4857\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-11-3ef09fac2b31>\u001b[0m in \u001b[0;36m<cell line: 10>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0mhistory_1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mtrain_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlossFn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptimizer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhistory_1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmute\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m \u001b[0mplot_history\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhistory_1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-8-5932a2608526>\u001b[0m in \u001b[0;36mtrain_model\u001b[0;34m(epoch, model, device, lossFn, optimizer, history, mute)\u001b[0m\n\u001b[1;32m     12\u001b[0m                 \u001b[0mtrainCorrect\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m                 \u001b[0mvalCorrect\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m                 \u001b[0;32mfor\u001b[0m \u001b[0msubjects_batch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtraining_loader\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m                         \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msubjects_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m't1'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDATA\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m                         \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msubjects_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'label'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    632\u001b[0m                 \u001b[0;31m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    633\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[call-arg]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 634\u001b[0;31m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_next_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    635\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_yielded\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    636\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dataset_kind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0m_DatasetKind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mIterable\u001b[0m \u001b[0;32mand\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    676\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_next_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    677\u001b[0m         \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_next_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# may raise StopIteration\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 678\u001b[0;31m         \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dataset_fetcher\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfetch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# may raise StopIteration\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    679\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pin_memory\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    680\u001b[0m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpin_memory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpin_memory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pin_memory_device\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py\u001b[0m in \u001b[0;36mfetch\u001b[0;34m(self, possibly_batched_index)\u001b[0m\n\u001b[1;32m     49\u001b[0m                 \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getitems__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m                 \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midx\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0midx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     49\u001b[0m                 \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getitems__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m                 \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midx\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0midx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/data/dataset.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, index)\u001b[0m\n\u001b[1;32m     97\u001b[0m         \u001b[0;31m# Apply transform (this is usually the bottleneck)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     98\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_transform\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 99\u001b[0;31m             \u001b[0msubject\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    100\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0msubject\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    101\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/transform.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    156\u001b[0m             \u001b[0msubject\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'raise'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ignore'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 158\u001b[0;31m             \u001b[0mtransformed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    159\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeep\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimage\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mimages_to_keep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/augmentation/composition.py\u001b[0m in \u001b[0;36mapply_transform\u001b[0;34m(self, subject)\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mapply_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubject\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mSubject\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mSubject\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mtransform\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransforms\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m             \u001b[0msubject\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[assignment]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0msubject\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/transform.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    156\u001b[0m             \u001b[0msubject\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'raise'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ignore'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 158\u001b[0;31m             \u001b[0mtransformed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    159\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeep\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimage\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mimages_to_keep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/augmentation/composition.py\u001b[0m in \u001b[0;36mapply_transform\u001b[0;34m(self, subject)\u001b[0m\n\u001b[1;32m    115\u001b[0m         \u001b[0mtransforms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransforms_dict\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    116\u001b[0m         \u001b[0mtransform\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtransforms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 117\u001b[0;31m         \u001b[0mtransformed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    118\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mtransformed\u001b[0m  \u001b[0;31m# type: ignore[return-value]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    119\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/transform.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    156\u001b[0m             \u001b[0msubject\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'raise'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ignore'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 158\u001b[0;31m             \u001b[0mtransformed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    159\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeep\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimage\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mimages_to_keep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/augmentation/spatial/random_affine.py\u001b[0m in \u001b[0;36mapply_transform\u001b[0;34m(self, subject)\u001b[0m\n\u001b[1;32m    177\u001b[0m         }\n\u001b[1;32m    178\u001b[0m         \u001b[0mtransform\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAffine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_include_exclude\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marguments\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 179\u001b[0;31m         \u001b[0mtransformed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    180\u001b[0m         \u001b[0;32massert\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtransformed\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    181\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mtransformed\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/transform.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    156\u001b[0m             \u001b[0msubject\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrstate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'raise'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'ignore'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 158\u001b[0;31m             \u001b[0mtransformed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    159\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeep\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimage\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mimages_to_keep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/augmentation/spatial/random_affine.py\u001b[0m in \u001b[0;36mapply_transform\u001b[0;34m(self, subject)\u001b[0m\n\u001b[1;32m    383\u001b[0m                         \u001b[0;32massert\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdefault_pad_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mNumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    384\u001b[0m                         \u001b[0mdefault_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdefault_pad_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 385\u001b[0;31m                 transformed_tensor = self.apply_affine_transform(\n\u001b[0m\u001b[1;32m    386\u001b[0m                     \u001b[0msitk_image\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    387\u001b[0m                     \u001b[0mtransform\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/torchio/transforms/augmentation/spatial/random_affine.py\u001b[0m in \u001b[0;36mapply_affine_transform\u001b[0;34m(self, sitk_image, transform, interpolation, default_value)\u001b[0m\n\u001b[1;32m    408\u001b[0m         \u001b[0mresampler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSetOutputPixelType\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msitk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msitkFloat32\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    409\u001b[0m         \u001b[0mresampler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSetTransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 410\u001b[0;31m         \u001b[0mresampled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresampler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mExecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfloating\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    411\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    412\u001b[0m         \u001b[0mnp_array\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msitk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGetArrayFromImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresampled\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.9/dist-packages/SimpleITK/SimpleITK.py\u001b[0m in \u001b[0;36mExecute\u001b[0;34m(self, image1)\u001b[0m\n\u001b[1;32m  49590\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m  49591\u001b[0m         \"\"\"\n\u001b[0;32m> 49592\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_SimpleITK\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mResampleImageFilter_Execute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimage1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m  49593\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m  49594\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mSetReferenceImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrefImage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# EfficientNet b0\n",
        "model = models.EfficientNet.EfficientNet3D.from_name(\n",
        "            'efficientnet-b0', \n",
        "            override_params={'num_classes': 2}, \n",
        "            in_channels=1).cuda()\n",
        "lossFn = nn.CrossEntropyLoss()\n",
        "optimizer = Adam(model.parameters(), lr = 10e-4, weight_decay = 5 * 10e-3)\n",
        "history_2 = {}\n",
        "\n",
        "train_model(200, model, device, lossFn, optimizer, history_2, mute = False)\n",
        "plot_history(history_2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "OiUGRxb55jsX",
        "outputId": "79698bd8-e19d-48e4-9ee7-b440772f37cc"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[INFO] training the network...\n",
            "[INFO] EPOCH: 1/200\n",
            "Train loss: 0.843385, Train accuracy: 0.5357\n",
            "Val loss: 0.693164, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 2/200\n",
            "Train loss: 0.858637, Train accuracy: 0.4571\n",
            "Val loss: 0.693329, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 3/200\n",
            "Train loss: 0.754451, Train accuracy: 0.5214\n",
            "Val loss: 0.693239, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 4/200\n",
            "Train loss: 0.732336, Train accuracy: 0.4714\n",
            "Val loss: 0.693155, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 5/200\n",
            "Train loss: 0.725894, Train accuracy: 0.4786\n",
            "Val loss: 0.693831, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 6/200\n",
            "Train loss: 0.713575, Train accuracy: 0.4714\n",
            "Val loss: 0.693174, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 7/200\n",
            "Train loss: 0.727987, Train accuracy: 0.4500\n",
            "Val loss: 0.693327, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 8/200\n",
            "Train loss: 0.708684, Train accuracy: 0.5071\n",
            "Val loss: 0.693157, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 9/200\n",
            "Train loss: 0.729885, Train accuracy: 0.4214\n",
            "Val loss: 0.693198, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 10/200\n",
            "Train loss: 0.706968, Train accuracy: 0.5071\n",
            "Val loss: 0.693164, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 11/200\n",
            "Train loss: 0.681973, Train accuracy: 0.5571\n",
            "Val loss: 0.693179, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 12/200\n",
            "Train loss: 0.714666, Train accuracy: 0.5214\n",
            "Val loss: 0.693271, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 13/200\n",
            "Train loss: 0.702036, Train accuracy: 0.5357\n",
            "Val loss: 0.693205, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 14/200\n",
            "Train loss: 0.700167, Train accuracy: 0.4500\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 15/200\n",
            "Train loss: 0.708588, Train accuracy: 0.4857\n",
            "Val loss: 0.693186, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 16/200\n",
            "Train loss: 0.694253, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 17/200\n",
            "Train loss: 0.693348, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 18/200\n",
            "Train loss: 0.693458, Train accuracy: 0.4643\n",
            "Val loss: 0.693159, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 19/200\n",
            "Train loss: 0.693286, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 20/200\n",
            "Train loss: 0.693296, Train accuracy: 0.5000\n",
            "Val loss: 0.693159, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 21/200\n",
            "Train loss: 0.693504, Train accuracy: 0.4286\n",
            "Val loss: 0.693161, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 22/200\n",
            "Train loss: 0.693620, Train accuracy: 0.5000\n",
            "Val loss: 0.693187, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 23/200\n",
            "Train loss: 0.693206, Train accuracy: 0.5000\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 24/200\n",
            "Train loss: 0.693318, Train accuracy: 0.5000\n",
            "Val loss: 0.693162, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 25/200\n",
            "Train loss: 0.693408, Train accuracy: 0.4500\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 26/200\n",
            "Train loss: 0.693404, Train accuracy: 0.5000\n",
            "Val loss: 0.693154, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 27/200\n",
            "Train loss: 0.693761, Train accuracy: 0.4000\n",
            "Val loss: 0.693162, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 28/200\n",
            "Train loss: 0.693299, Train accuracy: 0.5000\n",
            "Val loss: 0.693153, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 29/200\n",
            "Train loss: 0.693298, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 30/200\n",
            "Train loss: 0.693551, Train accuracy: 0.4000\n",
            "Val loss: 0.693154, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 31/200\n",
            "Train loss: 0.693269, Train accuracy: 0.5000\n",
            "Val loss: 0.693156, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 32/200\n",
            "Train loss: 0.693486, Train accuracy: 0.5000\n",
            "Val loss: 0.693154, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 33/200\n",
            "Train loss: 0.693307, Train accuracy: 0.5000\n",
            "Val loss: 0.693155, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 34/200\n",
            "Train loss: 0.693320, Train accuracy: 0.5000\n",
            "Val loss: 0.693157, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 35/200\n",
            "Train loss: 0.693400, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 36/200\n",
            "Train loss: 0.693302, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 37/200\n",
            "Train loss: 0.693249, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 38/200\n",
            "Train loss: 0.693319, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 39/200\n",
            "Train loss: 0.693362, Train accuracy: 0.5000\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 40/200\n",
            "Train loss: 0.693313, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 41/200\n",
            "Train loss: 0.693160, Train accuracy: 0.4929\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 42/200\n",
            "Train loss: 0.693369, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 43/200\n",
            "Train loss: 0.693566, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 44/200\n",
            "Train loss: 0.693340, Train accuracy: 0.4857\n",
            "Val loss: 0.693155, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 45/200\n",
            "Train loss: 0.693417, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 46/200\n",
            "Train loss: 0.693246, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 47/200\n",
            "Train loss: 0.693361, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 48/200\n",
            "Train loss: 0.693235, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 49/200\n",
            "Train loss: 0.693376, Train accuracy: 0.4000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 50/200\n",
            "Train loss: 0.693313, Train accuracy: 0.4214\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 51/200\n",
            "Train loss: 0.693241, Train accuracy: 0.4857\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 52/200\n",
            "Train loss: 0.693349, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 53/200\n",
            "Train loss: 0.693256, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 54/200\n",
            "Train loss: 0.693268, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 55/200\n",
            "Train loss: 0.693488, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 56/200\n",
            "Train loss: 0.693191, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 57/200\n",
            "Train loss: 0.693253, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 58/200\n",
            "Train loss: 0.693272, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 59/200\n",
            "Train loss: 0.693256, Train accuracy: 0.4857\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 60/200\n",
            "Train loss: 0.693337, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 61/200\n",
            "Train loss: 0.693256, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 62/200\n",
            "Train loss: 0.693424, Train accuracy: 0.4571\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 63/200\n",
            "Train loss: 0.693458, Train accuracy: 0.4571\n",
            "Val loss: 0.693153, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 64/200\n",
            "Train loss: 0.693261, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 65/200\n",
            "Train loss: 0.693192, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 66/200\n",
            "Train loss: 0.693293, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 67/200\n",
            "Train loss: 0.693286, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 68/200\n",
            "Train loss: 0.693480, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 69/200\n",
            "Train loss: 0.693256, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 70/200\n",
            "Train loss: 0.693249, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 71/200\n",
            "Train loss: 0.693392, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 72/200\n",
            "Train loss: 0.693308, Train accuracy: 0.5000\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 73/200\n",
            "Train loss: 0.693218, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 74/200\n",
            "Train loss: 0.693306, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 75/200\n",
            "Train loss: 0.693258, Train accuracy: 0.4429\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 76/200\n",
            "Train loss: 0.693265, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 77/200\n",
            "Train loss: 0.693253, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 78/200\n",
            "Train loss: 0.693202, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 79/200\n",
            "Train loss: 0.693508, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 80/200\n",
            "Train loss: 0.693231, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 81/200\n",
            "Train loss: 0.693349, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 82/200\n",
            "Train loss: 0.693240, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 83/200\n",
            "Train loss: 0.693418, Train accuracy: 0.4857\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 84/200\n",
            "Train loss: 0.693320, Train accuracy: 0.4714\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 85/200\n",
            "Train loss: 0.693177, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 86/200\n",
            "Train loss: 0.693339, Train accuracy: 0.4143\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 87/200\n",
            "Train loss: 0.693240, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 88/200\n",
            "Train loss: 0.693303, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 89/200\n",
            "Train loss: 0.693289, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 90/200\n",
            "Train loss: 0.693500, Train accuracy: 0.4857\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 91/200\n",
            "Train loss: 0.693321, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 92/200\n",
            "Train loss: 0.693277, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 93/200\n",
            "Train loss: 0.693285, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 94/200\n",
            "Train loss: 0.693292, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 95/200\n",
            "Train loss: 0.693884, Train accuracy: 0.4143\n",
            "Val loss: 0.693160, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 96/200\n",
            "Train loss: 0.693161, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 97/200\n",
            "Train loss: 0.693205, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 98/200\n",
            "Train loss: 0.693235, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 99/200\n",
            "Train loss: 0.693288, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 100/200\n",
            "Train loss: 0.693267, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 101/200\n",
            "Train loss: 0.693448, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 102/200\n",
            "Train loss: 0.693288, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 103/200\n",
            "Train loss: 0.693315, Train accuracy: 0.4571\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 104/200\n",
            "Train loss: 0.693472, Train accuracy: 0.4143\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 105/200\n",
            "Train loss: 0.693213, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 106/200\n",
            "Train loss: 0.693256, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 107/200\n",
            "Train loss: 0.693291, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 108/200\n",
            "Train loss: 0.693274, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 109/200\n",
            "Train loss: 0.693268, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 110/200\n",
            "Train loss: 0.693217, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 111/200\n",
            "Train loss: 0.693334, Train accuracy: 0.4143\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 112/200\n",
            "Train loss: 0.693239, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 113/200\n",
            "Train loss: 0.693194, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 114/200\n",
            "Train loss: 0.693335, Train accuracy: 0.4571\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 115/200\n",
            "Train loss: 0.693652, Train accuracy: 0.4429\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 116/200\n",
            "Train loss: 0.693282, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 117/200\n",
            "Train loss: 0.693278, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 118/200\n",
            "Train loss: 0.693306, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 119/200\n",
            "Train loss: 0.693234, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 120/200\n",
            "Train loss: 0.693235, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 121/200\n",
            "Train loss: 0.693281, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 122/200\n",
            "Train loss: 0.693344, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 123/200\n",
            "Train loss: 0.693262, Train accuracy: 0.3857\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 124/200\n",
            "Train loss: 0.693214, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 125/200\n",
            "Train loss: 0.693287, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 126/200\n",
            "Train loss: 0.693201, Train accuracy: 0.4857\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 127/200\n",
            "Train loss: 0.693330, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 128/200\n",
            "Train loss: 0.693543, Train accuracy: 0.4143\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 129/200\n",
            "Train loss: 0.693345, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 130/200\n",
            "Train loss: 0.693292, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 131/200\n",
            "Train loss: 0.693403, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 132/200\n",
            "Train loss: 0.693314, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 133/200\n",
            "Train loss: 0.693288, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 134/200\n",
            "Train loss: 0.693235, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 135/200\n",
            "Train loss: 0.693222, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 136/200\n",
            "Train loss: 0.693192, Train accuracy: 0.4857\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 137/200\n",
            "Train loss: 0.693451, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 138/200\n",
            "Train loss: 0.693240, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 139/200\n",
            "Train loss: 0.693262, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 140/200\n",
            "Train loss: 0.693497, Train accuracy: 0.4286\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 141/200\n",
            "Train loss: 0.693319, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 142/200\n",
            "Train loss: 0.693348, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 143/200\n",
            "Train loss: 0.693273, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 144/200\n",
            "Train loss: 0.693317, Train accuracy: 0.4143\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 145/200\n",
            "Train loss: 0.693507, Train accuracy: 0.4143\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 146/200\n",
            "Train loss: 0.693571, Train accuracy: 0.4714\n",
            "Val loss: 0.693152, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 147/200\n",
            "Train loss: 0.693221, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 148/200\n",
            "Train loss: 0.693319, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 149/200\n",
            "Train loss: 0.693288, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 150/200\n",
            "Train loss: 0.693233, Train accuracy: 0.5000\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 151/200\n",
            "Train loss: 0.693381, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 152/200\n",
            "Train loss: 0.693346, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 153/200\n",
            "Train loss: 0.693207, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 154/200\n",
            "Train loss: 0.693388, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 155/200\n",
            "Train loss: 0.693219, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 156/200\n",
            "Train loss: 0.693362, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 157/200\n",
            "Train loss: 0.693288, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 158/200\n",
            "Train loss: 0.693406, Train accuracy: 0.4571\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 159/200\n",
            "Train loss: 0.693378, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 160/200\n",
            "Train loss: 0.693199, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 161/200\n",
            "Train loss: 0.693195, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 162/200\n",
            "Train loss: 0.693304, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 163/200\n",
            "Train loss: 0.693422, Train accuracy: 0.4714\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 164/200\n",
            "Train loss: 0.693334, Train accuracy: 0.4857\n",
            "Val loss: 0.693149, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 165/200\n",
            "Train loss: 0.693248, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 166/200\n",
            "Train loss: 0.693206, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 167/200\n",
            "Train loss: 0.693236, Train accuracy: 0.4714\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 168/200\n",
            "Train loss: 0.693381, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 169/200\n",
            "Train loss: 0.693205, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 170/200\n",
            "Train loss: 0.693229, Train accuracy: 0.4143\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 171/200\n",
            "Train loss: 0.693362, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 172/200\n",
            "Train loss: 0.693253, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 173/200\n",
            "Train loss: 0.693292, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 174/200\n",
            "Train loss: 0.693419, Train accuracy: 0.4571\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 175/200\n",
            "Train loss: 0.693329, Train accuracy: 0.5000\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 176/200\n",
            "Train loss: 0.693214, Train accuracy: 0.5000\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 177/200\n",
            "Train loss: 0.693236, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 178/200\n",
            "Train loss: 0.693289, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 179/200\n",
            "Train loss: 0.693219, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 180/200\n",
            "Train loss: 0.693295, Train accuracy: 0.4571\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 181/200\n",
            "Train loss: 0.693232, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 182/200\n",
            "Train loss: 0.693262, Train accuracy: 0.4571\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 183/200\n",
            "Train loss: 0.693248, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 184/200\n",
            "Train loss: 0.693342, Train accuracy: 0.4714\n",
            "Val loss: 0.693151, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 185/200\n",
            "Train loss: 0.693233, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 186/200\n",
            "Train loss: 0.693219, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 187/200\n",
            "Train loss: 0.693295, Train accuracy: 0.4857\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 188/200\n",
            "Train loss: 0.693187, Train accuracy: 0.4286\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 189/200\n",
            "Train loss: 0.693336, Train accuracy: 0.5000\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 190/200\n",
            "Train loss: 0.693227, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 191/200\n",
            "Train loss: 0.693279, Train accuracy: 0.4429\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 192/200\n",
            "Train loss: 0.693389, Train accuracy: 0.3571\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 193/200\n",
            "Train loss: 0.693247, Train accuracy: 0.4429\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 194/200\n",
            "Train loss: 0.693215, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 195/200\n",
            "Train loss: 0.693376, Train accuracy: 0.4714\n",
            "Val loss: 0.693150, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 196/200\n",
            "Train loss: 0.693255, Train accuracy: 0.5000\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 197/200\n",
            "Train loss: 0.693281, Train accuracy: 0.4714\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 198/200\n",
            "Train loss: 0.693458, Train accuracy: 0.4857\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 199/200\n",
            "Train loss: 0.693236, Train accuracy: 0.4286\n",
            "Val loss: 0.693148, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] EPOCH: 200/200\n",
            "Train loss: 0.693266, Train accuracy: 0.4571\n",
            "Val loss: 0.693147, Val accuracy: 0.5000\n",
            "\n",
            "[INFO] total time taken to train the model: 27881.87s\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "/* Put everything inside the global mpl namespace */\n",
              "/* global mpl */\n",
              "window.mpl = {};\n",
              "\n",
              "mpl.get_websocket_type = function () {\n",
              "    if (typeof WebSocket !== 'undefined') {\n",
              "        return WebSocket;\n",
              "    } else if (typeof MozWebSocket !== 'undefined') {\n",
              "        return MozWebSocket;\n",
              "    } else {\n",
              "        alert(\n",
              "            'Your browser does not have WebSocket support. ' +\n",
              "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
              "                'Firefox 4 and 5 are also supported but you ' +\n",
              "                'have to enable WebSockets in about:config.'\n",
              "        );\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
              "    this.id = figure_id;\n",
              "\n",
              "    this.ws = websocket;\n",
              "\n",
              "    this.supports_binary = this.ws.binaryType !== undefined;\n",
              "\n",
              "    if (!this.supports_binary) {\n",
              "        var warnings = document.getElementById('mpl-warnings');\n",
              "        if (warnings) {\n",
              "            warnings.style.display = 'block';\n",
              "            warnings.textContent =\n",
              "                'This browser does not support binary websocket messages. ' +\n",
              "                'Performance may be slow.';\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.imageObj = new Image();\n",
              "\n",
              "    this.context = undefined;\n",
              "    this.message = undefined;\n",
              "    this.canvas = undefined;\n",
              "    this.rubberband_canvas = undefined;\n",
              "    this.rubberband_context = undefined;\n",
              "    this.format_dropdown = undefined;\n",
              "\n",
              "    this.image_mode = 'full';\n",
              "\n",
              "    this.root = document.createElement('div');\n",
              "    this.root.setAttribute('style', 'display: inline-block');\n",
              "    this._root_extra_style(this.root);\n",
              "\n",
              "    parent_element.appendChild(this.root);\n",
              "\n",
              "    this._init_header(this);\n",
              "    this._init_canvas(this);\n",
              "    this._init_toolbar(this);\n",
              "\n",
              "    var fig = this;\n",
              "\n",
              "    this.waiting = false;\n",
              "\n",
              "    this.ws.onopen = function () {\n",
              "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
              "        fig.send_message('send_image_mode', {});\n",
              "        if (fig.ratio !== 1) {\n",
              "            fig.send_message('set_device_pixel_ratio', {\n",
              "                device_pixel_ratio: fig.ratio,\n",
              "            });\n",
              "        }\n",
              "        fig.send_message('refresh', {});\n",
              "    };\n",
              "\n",
              "    this.imageObj.onload = function () {\n",
              "        if (fig.image_mode === 'full') {\n",
              "            // Full images could contain transparency (where diff images\n",
              "            // almost always do), so we need to clear the canvas so that\n",
              "            // there is no ghosting.\n",
              "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
              "        }\n",
              "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
              "    };\n",
              "\n",
              "    this.imageObj.onunload = function () {\n",
              "        fig.ws.close();\n",
              "    };\n",
              "\n",
              "    this.ws.onmessage = this._make_on_message_function(this);\n",
              "\n",
              "    this.ondownload = ondownload;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_header = function () {\n",
              "    var titlebar = document.createElement('div');\n",
              "    titlebar.classList =\n",
              "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
              "    var titletext = document.createElement('div');\n",
              "    titletext.classList = 'ui-dialog-title';\n",
              "    titletext.setAttribute(\n",
              "        'style',\n",
              "        'width: 100%; text-align: center; padding: 3px;'\n",
              "    );\n",
              "    titlebar.appendChild(titletext);\n",
              "    this.root.appendChild(titlebar);\n",
              "    this.header = titletext;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._init_canvas = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
              "    canvas_div.setAttribute('tabindex', '0');\n",
              "    canvas_div.setAttribute(\n",
              "        'style',\n",
              "        'border: 1px solid #ddd;' +\n",
              "            'box-sizing: content-box;' +\n",
              "            'clear: both;' +\n",
              "            'min-height: 1px;' +\n",
              "            'min-width: 1px;' +\n",
              "            'outline: 0;' +\n",
              "            'overflow: hidden;' +\n",
              "            'position: relative;' +\n",
              "            'resize: both;' +\n",
              "            'z-index: 2;'\n",
              "    );\n",
              "\n",
              "    function on_keyboard_event_closure(name) {\n",
              "        return function (event) {\n",
              "            return fig.key_event(event, name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'keydown',\n",
              "        on_keyboard_event_closure('key_press')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'keyup',\n",
              "        on_keyboard_event_closure('key_release')\n",
              "    );\n",
              "\n",
              "    this._canvas_extra_style(canvas_div);\n",
              "    this.root.appendChild(canvas_div);\n",
              "\n",
              "    var canvas = (this.canvas = document.createElement('canvas'));\n",
              "    canvas.classList.add('mpl-canvas');\n",
              "    canvas.setAttribute(\n",
              "        'style',\n",
              "        'box-sizing: content-box;' +\n",
              "            'pointer-events: none;' +\n",
              "            'position: relative;' +\n",
              "            'z-index: 0;'\n",
              "    );\n",
              "\n",
              "    this.context = canvas.getContext('2d');\n",
              "\n",
              "    var backingStore =\n",
              "        this.context.backingStorePixelRatio ||\n",
              "        this.context.webkitBackingStorePixelRatio ||\n",
              "        this.context.mozBackingStorePixelRatio ||\n",
              "        this.context.msBackingStorePixelRatio ||\n",
              "        this.context.oBackingStorePixelRatio ||\n",
              "        this.context.backingStorePixelRatio ||\n",
              "        1;\n",
              "\n",
              "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
              "\n",
              "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
              "        'canvas'\n",
              "    ));\n",
              "    rubberband_canvas.setAttribute(\n",
              "        'style',\n",
              "        'box-sizing: content-box;' +\n",
              "            'left: 0;' +\n",
              "            'pointer-events: none;' +\n",
              "            'position: absolute;' +\n",
              "            'top: 0;' +\n",
              "            'z-index: 1;'\n",
              "    );\n",
              "\n",
              "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
              "    if (this.ResizeObserver === undefined) {\n",
              "        if (window.ResizeObserver !== undefined) {\n",
              "            this.ResizeObserver = window.ResizeObserver;\n",
              "        } else {\n",
              "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
              "            this.ResizeObserver = obs.ResizeObserver;\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
              "        var nentries = entries.length;\n",
              "        for (var i = 0; i < nentries; i++) {\n",
              "            var entry = entries[i];\n",
              "            var width, height;\n",
              "            if (entry.contentBoxSize) {\n",
              "                if (entry.contentBoxSize instanceof Array) {\n",
              "                    // Chrome 84 implements new version of spec.\n",
              "                    width = entry.contentBoxSize[0].inlineSize;\n",
              "                    height = entry.contentBoxSize[0].blockSize;\n",
              "                } else {\n",
              "                    // Firefox implements old version of spec.\n",
              "                    width = entry.contentBoxSize.inlineSize;\n",
              "                    height = entry.contentBoxSize.blockSize;\n",
              "                }\n",
              "            } else {\n",
              "                // Chrome <84 implements even older version of spec.\n",
              "                width = entry.contentRect.width;\n",
              "                height = entry.contentRect.height;\n",
              "            }\n",
              "\n",
              "            // Keep the size of the canvas and rubber band canvas in sync with\n",
              "            // the canvas container.\n",
              "            if (entry.devicePixelContentBoxSize) {\n",
              "                // Chrome 84 implements new version of spec.\n",
              "                canvas.setAttribute(\n",
              "                    'width',\n",
              "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
              "                );\n",
              "                canvas.setAttribute(\n",
              "                    'height',\n",
              "                    entry.devicePixelContentBoxSize[0].blockSize\n",
              "                );\n",
              "            } else {\n",
              "                canvas.setAttribute('width', width * fig.ratio);\n",
              "                canvas.setAttribute('height', height * fig.ratio);\n",
              "            }\n",
              "            /* This rescales the canvas back to display pixels, so that it\n",
              "             * appears correct on HiDPI screens. */\n",
              "            canvas.style.width = width + 'px';\n",
              "            canvas.style.height = height + 'px';\n",
              "\n",
              "            rubberband_canvas.setAttribute('width', width);\n",
              "            rubberband_canvas.setAttribute('height', height);\n",
              "\n",
              "            // And update the size in Python. We ignore the initial 0/0 size\n",
              "            // that occurs as the element is placed into the DOM, which should\n",
              "            // otherwise not happen due to the minimum size styling.\n",
              "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
              "                fig.request_resize(width, height);\n",
              "            }\n",
              "        }\n",
              "    });\n",
              "    this.resizeObserverInstance.observe(canvas_div);\n",
              "\n",
              "    function on_mouse_event_closure(name) {\n",
              "        /* User Agent sniffing is bad, but WebKit is busted:\n",
              "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
              "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
              "         * The worst that happens here is that they get an extra browser\n",
              "         * selection when dragging, if this check fails to catch them.\n",
              "         */\n",
              "        var UA = navigator.userAgent;\n",
              "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
              "        if(isWebKit) {\n",
              "            return function (event) {\n",
              "                /* This prevents the web browser from automatically changing to\n",
              "                 * the text insertion cursor when the button is pressed. We\n",
              "                 * want to control all of the cursor setting manually through\n",
              "                 * the 'cursor' event from matplotlib */\n",
              "                event.preventDefault()\n",
              "                return fig.mouse_event(event, name);\n",
              "            };\n",
              "        } else {\n",
              "            return function (event) {\n",
              "                return fig.mouse_event(event, name);\n",
              "            };\n",
              "        }\n",
              "    }\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'mousedown',\n",
              "        on_mouse_event_closure('button_press')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseup',\n",
              "        on_mouse_event_closure('button_release')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'dblclick',\n",
              "        on_mouse_event_closure('dblclick')\n",
              "    );\n",
              "    // Throttle sequential mouse events to 1 every 20ms.\n",
              "    canvas_div.addEventListener(\n",
              "        'mousemove',\n",
              "        on_mouse_event_closure('motion_notify')\n",
              "    );\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseenter',\n",
              "        on_mouse_event_closure('figure_enter')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseleave',\n",
              "        on_mouse_event_closure('figure_leave')\n",
              "    );\n",
              "\n",
              "    canvas_div.addEventListener('wheel', function (event) {\n",
              "        if (event.deltaY < 0) {\n",
              "            event.step = 1;\n",
              "        } else {\n",
              "            event.step = -1;\n",
              "        }\n",
              "        on_mouse_event_closure('scroll')(event);\n",
              "    });\n",
              "\n",
              "    canvas_div.appendChild(canvas);\n",
              "    canvas_div.appendChild(rubberband_canvas);\n",
              "\n",
              "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
              "    this.rubberband_context.strokeStyle = '#000000';\n",
              "\n",
              "    this._resize_canvas = function (width, height, forward) {\n",
              "        if (forward) {\n",
              "            canvas_div.style.width = width + 'px';\n",
              "            canvas_div.style.height = height + 'px';\n",
              "        }\n",
              "    };\n",
              "\n",
              "    // Disable right mouse context menu.\n",
              "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
              "        event.preventDefault();\n",
              "        return false;\n",
              "    });\n",
              "\n",
              "    function set_focus() {\n",
              "        canvas.focus();\n",
              "        canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    window.setTimeout(set_focus, 100);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'mpl-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'mpl-button-group';\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'mpl-button-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        var button = (fig.buttons[name] = document.createElement('button'));\n",
              "        button.classList = 'mpl-widget';\n",
              "        button.setAttribute('role', 'button');\n",
              "        button.setAttribute('aria-disabled', 'false');\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "\n",
              "        var icon_img = document.createElement('img');\n",
              "        icon_img.src = '_images/' + image + '.png';\n",
              "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
              "        icon_img.alt = tooltip;\n",
              "        button.appendChild(icon_img);\n",
              "\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    var fmt_picker = document.createElement('select');\n",
              "    fmt_picker.classList = 'mpl-widget';\n",
              "    toolbar.appendChild(fmt_picker);\n",
              "    this.format_dropdown = fmt_picker;\n",
              "\n",
              "    for (var ind in mpl.extensions) {\n",
              "        var fmt = mpl.extensions[ind];\n",
              "        var option = document.createElement('option');\n",
              "        option.selected = fmt === mpl.default_extension;\n",
              "        option.innerHTML = fmt;\n",
              "        fmt_picker.appendChild(option);\n",
              "    }\n",
              "\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
              "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
              "    // which will in turn request a refresh of the image.\n",
              "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_message = function (type, properties) {\n",
              "    properties['type'] = type;\n",
              "    properties['figure_id'] = this.id;\n",
              "    this.ws.send(JSON.stringify(properties));\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_draw_message = function () {\n",
              "    if (!this.waiting) {\n",
              "        this.waiting = true;\n",
              "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    var format_dropdown = fig.format_dropdown;\n",
              "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
              "    fig.ondownload(fig, format);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
              "    var size = msg['size'];\n",
              "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
              "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
              "        fig.send_message('refresh', {});\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
              "    var x0 = msg['x0'] / fig.ratio;\n",
              "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
              "    var x1 = msg['x1'] / fig.ratio;\n",
              "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
              "    x0 = Math.floor(x0) + 0.5;\n",
              "    y0 = Math.floor(y0) + 0.5;\n",
              "    x1 = Math.floor(x1) + 0.5;\n",
              "    y1 = Math.floor(y1) + 0.5;\n",
              "    var min_x = Math.min(x0, x1);\n",
              "    var min_y = Math.min(y0, y1);\n",
              "    var width = Math.abs(x1 - x0);\n",
              "    var height = Math.abs(y1 - y0);\n",
              "\n",
              "    fig.rubberband_context.clearRect(\n",
              "        0,\n",
              "        0,\n",
              "        fig.canvas.width / fig.ratio,\n",
              "        fig.canvas.height / fig.ratio\n",
              "    );\n",
              "\n",
              "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
              "    // Updates the figure title.\n",
              "    fig.header.textContent = msg['label'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
              "    fig.canvas_div.style.cursor = msg['cursor'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
              "    fig.message.textContent = msg['message'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
              "    // Request the server to send over a new figure.\n",
              "    fig.send_draw_message();\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
              "    fig.image_mode = msg['mode'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
              "    for (var key in msg) {\n",
              "        if (!(key in fig.buttons)) {\n",
              "            continue;\n",
              "        }\n",
              "        fig.buttons[key].disabled = !msg[key];\n",
              "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
              "    if (msg['mode'] === 'PAN') {\n",
              "        fig.buttons['Pan'].classList.add('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    } else if (msg['mode'] === 'ZOOM') {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.add('active');\n",
              "    } else {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Called whenever the canvas gets updated.\n",
              "    this.send_message('ack', {});\n",
              "};\n",
              "\n",
              "// A function to construct a web socket function for onmessage handling.\n",
              "// Called in the figure constructor.\n",
              "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
              "    return function socket_on_message(evt) {\n",
              "        if (evt.data instanceof Blob) {\n",
              "            var img = evt.data;\n",
              "            if (img.type !== 'image/png') {\n",
              "                /* FIXME: We get \"Resource interpreted as Image but\n",
              "                 * transferred with MIME type text/plain:\" errors on\n",
              "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
              "                 * to be part of the websocket stream */\n",
              "                img.type = 'image/png';\n",
              "            }\n",
              "\n",
              "            /* Free the memory for the previous frames */\n",
              "            if (fig.imageObj.src) {\n",
              "                (window.URL || window.webkitURL).revokeObjectURL(\n",
              "                    fig.imageObj.src\n",
              "                );\n",
              "            }\n",
              "\n",
              "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
              "                img\n",
              "            );\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        } else if (\n",
              "            typeof evt.data === 'string' &&\n",
              "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
              "        ) {\n",
              "            fig.imageObj.src = evt.data;\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        var msg = JSON.parse(evt.data);\n",
              "        var msg_type = msg['type'];\n",
              "\n",
              "        // Call the  \"handle_{type}\" callback, which takes\n",
              "        // the figure and JSON message as its only arguments.\n",
              "        try {\n",
              "            var callback = fig['handle_' + msg_type];\n",
              "        } catch (e) {\n",
              "            console.log(\n",
              "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
              "                msg\n",
              "            );\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        if (callback) {\n",
              "            try {\n",
              "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
              "                callback(fig, msg);\n",
              "            } catch (e) {\n",
              "                console.log(\n",
              "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
              "                    e,\n",
              "                    e.stack,\n",
              "                    msg\n",
              "                );\n",
              "            }\n",
              "        }\n",
              "    };\n",
              "};\n",
              "\n",
              "function getModifiers(event) {\n",
              "    var mods = [];\n",
              "    if (event.ctrlKey) {\n",
              "        mods.push('ctrl');\n",
              "    }\n",
              "    if (event.altKey) {\n",
              "        mods.push('alt');\n",
              "    }\n",
              "    if (event.shiftKey) {\n",
              "        mods.push('shift');\n",
              "    }\n",
              "    if (event.metaKey) {\n",
              "        mods.push('meta');\n",
              "    }\n",
              "    return mods;\n",
              "}\n",
              "\n",
              "/*\n",
              " * return a copy of an object with only non-object keys\n",
              " * we need this to avoid circular references\n",
              " * https://stackoverflow.com/a/24161582/3208463\n",
              " */\n",
              "function simpleKeys(original) {\n",
              "    return Object.keys(original).reduce(function (obj, key) {\n",
              "        if (typeof original[key] !== 'object') {\n",
              "            obj[key] = original[key];\n",
              "        }\n",
              "        return obj;\n",
              "    }, {});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.mouse_event = function (event, name) {\n",
              "    if (name === 'button_press') {\n",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    // from https://stackoverflow.com/q/1114465\n",
              "    var boundingRect = this.canvas.getBoundingClientRect();\n",
              "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
              "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
              "\n",
              "    this.send_message(name, {\n",
              "        x: x,\n",
              "        y: y,\n",
              "        button: event.button,\n",
              "        step: event.step,\n",
              "        modifiers: getModifiers(event),\n",
              "        guiEvent: simpleKeys(event),\n",
              "    });\n",
              "\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
              "    // Handle any extra behaviour associated with a key event\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.key_event = function (event, name) {\n",
              "    // Prevent repeat events\n",
              "    if (name === 'key_press') {\n",
              "        if (event.key === this._key) {\n",
              "            return;\n",
              "        } else {\n",
              "            this._key = event.key;\n",
              "        }\n",
              "    }\n",
              "    if (name === 'key_release') {\n",
              "        this._key = null;\n",
              "    }\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.key !== 'Control') {\n",
              "        value += 'ctrl+';\n",
              "    }\n",
              "    else if (event.altKey && event.key !== 'Alt') {\n",
              "        value += 'alt+';\n",
              "    }\n",
              "    else if (event.shiftKey && event.key !== 'Shift') {\n",
              "        value += 'shift+';\n",
              "    }\n",
              "\n",
              "    value += 'k' + event.key;\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
              "    if (name === 'download') {\n",
              "        this.handle_save(this, null);\n",
              "    } else {\n",
              "        this.send_message('toolbar_button', { name: name });\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
              "    this.message.textContent = tooltip;\n",
              "};\n",
              "\n",
              "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
              "// prettier-ignore\n",
              "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
              "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
              "\n",
              "mpl.default_extension = \"png\";/* global mpl */\n",
              "\n",
              "var comm_websocket_adapter = function (comm) {\n",
              "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
              "    // object with the appropriate methods. Currently this is a non binary\n",
              "    // socket, so there is still some room for performance tuning.\n",
              "    var ws = {};\n",
              "\n",
              "    ws.binaryType = comm.kernel.ws.binaryType;\n",
              "    ws.readyState = comm.kernel.ws.readyState;\n",
              "    function updateReadyState(_event) {\n",
              "        if (comm.kernel.ws) {\n",
              "            ws.readyState = comm.kernel.ws.readyState;\n",
              "        } else {\n",
              "            ws.readyState = 3; // Closed state.\n",
              "        }\n",
              "    }\n",
              "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
              "\n",
              "    ws.close = function () {\n",
              "        comm.close();\n",
              "    };\n",
              "    ws.send = function (m) {\n",
              "        //console.log('sending', m);\n",
              "        comm.send(m);\n",
              "    };\n",
              "    // Register the callback with on_msg.\n",
              "    comm.on_msg(function (msg) {\n",
              "        //console.log('receiving', msg['content']['data'], msg);\n",
              "        var data = msg['content']['data'];\n",
              "        if (data['blob'] !== undefined) {\n",
              "            data = {\n",
              "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
              "            };\n",
              "        }\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(data);\n",
              "    });\n",
              "    return ws;\n",
              "};\n",
              "\n",
              "mpl.mpl_figure_comm = function (comm, msg) {\n",
              "    // This is the function which gets called when the mpl process\n",
              "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
              "\n",
              "    var id = msg.content.data.id;\n",
              "    // Get hold of the div created by the display call when the Comm\n",
              "    // socket was opened in Python.\n",
              "    var element = document.getElementById(id);\n",
              "    var ws_proxy = comm_websocket_adapter(comm);\n",
              "\n",
              "    function ondownload(figure, _format) {\n",
              "        window.open(figure.canvas.toDataURL());\n",
              "    }\n",
              "\n",
              "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
              "\n",
              "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
              "    // web socket which is closed, not our websocket->open comm proxy.\n",
              "    ws_proxy.onopen();\n",
              "\n",
              "    fig.parent_element = element;\n",
              "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
              "    if (!fig.cell_info) {\n",
              "        console.error('Failed to find cell for figure', id, fig);\n",
              "        return;\n",
              "    }\n",
              "    fig.cell_info[0].output_area.element.on(\n",
              "        'cleared',\n",
              "        { fig: fig },\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
              "    var width = fig.canvas.width / fig.ratio;\n",
              "    fig.cell_info[0].output_area.element.off(\n",
              "        'cleared',\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
              "\n",
              "    // Update the output cell to use the data from the current canvas.\n",
              "    fig.push_to_output();\n",
              "    var dataURL = fig.canvas.toDataURL();\n",
              "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
              "    // the notebook keyboard shortcuts fail.\n",
              "    IPython.keyboard_manager.enable();\n",
              "    fig.parent_element.innerHTML =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "    fig.close_ws(fig, msg);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
              "    fig.send_message('closing', msg);\n",
              "    // fig.ws.close()\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
              "    // Turn the data on the canvas into data in the output cell.\n",
              "    var width = this.canvas.width / this.ratio;\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Tell IPython that the notebook contents must change.\n",
              "    IPython.notebook.set_dirty(true);\n",
              "    this.send_message('ack', {});\n",
              "    var fig = this;\n",
              "    // Wait a second, then push the new image to the DOM so\n",
              "    // that it is saved nicely (might be nice to debounce this).\n",
              "    setTimeout(function () {\n",
              "        fig.push_to_output();\n",
              "    }, 1000);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'btn-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'btn-group';\n",
              "    var button;\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'btn-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        button = fig.buttons[name] = document.createElement('button');\n",
              "        button.classList = 'btn btn-default';\n",
              "        button.href = '#';\n",
              "        button.title = name;\n",
              "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    // Add the status bar.\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message pull-right';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "\n",
              "    // Add the close button to the window.\n",
              "    var buttongrp = document.createElement('div');\n",
              "    buttongrp.classList = 'btn-group inline pull-right';\n",
              "    button = document.createElement('button');\n",
              "    button.classList = 'btn btn-mini btn-primary';\n",
              "    button.href = '#';\n",
              "    button.title = 'Stop Interaction';\n",
              "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
              "    button.addEventListener('click', function (_evt) {\n",
              "        fig.handle_close(fig, {});\n",
              "    });\n",
              "    button.addEventListener(\n",
              "        'mouseover',\n",
              "        on_mouseover_closure('Stop Interaction')\n",
              "    );\n",
              "    buttongrp.appendChild(button);\n",
              "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
              "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
              "    var fig = event.data.fig;\n",
              "    if (event.target !== this) {\n",
              "        // Ignore bubbled events from children.\n",
              "        return;\n",
              "    }\n",
              "    fig.close_ws(fig, {});\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (el) {\n",
              "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
              "    // this is important to make the div 'focusable\n",
              "    el.setAttribute('tabindex', 0);\n",
              "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
              "    // off when our div gets focus\n",
              "\n",
              "    // location in version 3\n",
              "    if (IPython.notebook.keyboard_manager) {\n",
              "        IPython.notebook.keyboard_manager.register_events(el);\n",
              "    } else {\n",
              "        // location in version 2\n",
              "        IPython.keyboard_manager.register_events(el);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
              "    // Check for shift+enter\n",
              "    if (event.shiftKey && event.which === 13) {\n",
              "        this.canvas_div.blur();\n",
              "        // select the cell after this one\n",
              "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
              "        IPython.notebook.select(index + 1);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    fig.ondownload(fig, null);\n",
              "};\n",
              "\n",
              "mpl.find_output_cell = function (html_output) {\n",
              "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
              "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
              "    // IPython event is triggered only after the cells have been serialised, which for\n",
              "    // our purposes (turning an active figure into a static one), is too late.\n",
              "    var cells = IPython.notebook.get_cells();\n",
              "    var ncells = cells.length;\n",
              "    for (var i = 0; i < ncells; i++) {\n",
              "        var cell = cells[i];\n",
              "        if (cell.cell_type === 'code') {\n",
              "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
              "                var data = cell.output_area.outputs[j];\n",
              "                if (data.data) {\n",
              "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
              "                    data = data.data;\n",
              "                }\n",
              "                if (data['text/html'] === html_output) {\n",
              "                    return [cell, data, j];\n",
              "                }\n",
              "            }\n",
              "        }\n",
              "    }\n",
              "};\n",
              "\n",
              "// Register the function which deals with the matplotlib target/channel.\n",
              "// The kernel may be null if the page has been refreshed.\n",
              "if (IPython.notebook.kernel !== null) {\n",
              "    IPython.notebook.kernel.comm_manager.register_target(\n",
              "        'matplotlib',\n",
              "        mpl.mpl_figure_comm\n",
              "    );\n",
              "}\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div id='018c2558-dc61-4a7e-aa05-6c2752701282'></div>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_history(history):\n",
        "\tfig, ax = plt.subplots(1, 2, figsize=(20, 3))\n",
        "\tax = ax.ravel()\n",
        "\tfor i, metric in enumerate([\"acc\", \"loss\"]):\n",
        "\t\t\tax[i].plot(history[\"train_\" + metric])\n",
        "\t\t\tax[i].plot(history[\"val_\" + metric])\n",
        "\t\t\tax[i].set_title(\"Model {}\".format(metric))\n",
        "\t\t\tax[i].set_xlabel(\"epochs\")\n",
        "\t\t\tax[i].set_ylabel(metric)\n",
        "\t\t\tax[i].legend([\"train\", \"val\"])\n",
        "   \n",
        "plot_history(history_2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "nzRJNyYI0vqQ",
        "outputId": "3b505e9e-31dd-4163-b68e-137e52e6691e"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "/* Put everything inside the global mpl namespace */\n",
              "/* global mpl */\n",
              "window.mpl = {};\n",
              "\n",
              "mpl.get_websocket_type = function () {\n",
              "    if (typeof WebSocket !== 'undefined') {\n",
              "        return WebSocket;\n",
              "    } else if (typeof MozWebSocket !== 'undefined') {\n",
              "        return MozWebSocket;\n",
              "    } else {\n",
              "        alert(\n",
              "            'Your browser does not have WebSocket support. ' +\n",
              "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
              "                'Firefox 4 and 5 are also supported but you ' +\n",
              "                'have to enable WebSockets in about:config.'\n",
              "        );\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
              "    this.id = figure_id;\n",
              "\n",
              "    this.ws = websocket;\n",
              "\n",
              "    this.supports_binary = this.ws.binaryType !== undefined;\n",
              "\n",
              "    if (!this.supports_binary) {\n",
              "        var warnings = document.getElementById('mpl-warnings');\n",
              "        if (warnings) {\n",
              "            warnings.style.display = 'block';\n",
              "            warnings.textContent =\n",
              "                'This browser does not support binary websocket messages. ' +\n",
              "                'Performance may be slow.';\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.imageObj = new Image();\n",
              "\n",
              "    this.context = undefined;\n",
              "    this.message = undefined;\n",
              "    this.canvas = undefined;\n",
              "    this.rubberband_canvas = undefined;\n",
              "    this.rubberband_context = undefined;\n",
              "    this.format_dropdown = undefined;\n",
              "\n",
              "    this.image_mode = 'full';\n",
              "\n",
              "    this.root = document.createElement('div');\n",
              "    this.root.setAttribute('style', 'display: inline-block');\n",
              "    this._root_extra_style(this.root);\n",
              "\n",
              "    parent_element.appendChild(this.root);\n",
              "\n",
              "    this._init_header(this);\n",
              "    this._init_canvas(this);\n",
              "    this._init_toolbar(this);\n",
              "\n",
              "    var fig = this;\n",
              "\n",
              "    this.waiting = false;\n",
              "\n",
              "    this.ws.onopen = function () {\n",
              "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
              "        fig.send_message('send_image_mode', {});\n",
              "        if (fig.ratio !== 1) {\n",
              "            fig.send_message('set_device_pixel_ratio', {\n",
              "                device_pixel_ratio: fig.ratio,\n",
              "            });\n",
              "        }\n",
              "        fig.send_message('refresh', {});\n",
              "    };\n",
              "\n",
              "    this.imageObj.onload = function () {\n",
              "        if (fig.image_mode === 'full') {\n",
              "            // Full images could contain transparency (where diff images\n",
              "            // almost always do), so we need to clear the canvas so that\n",
              "            // there is no ghosting.\n",
              "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
              "        }\n",
              "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
              "    };\n",
              "\n",
              "    this.imageObj.onunload = function () {\n",
              "        fig.ws.close();\n",
              "    };\n",
              "\n",
              "    this.ws.onmessage = this._make_on_message_function(this);\n",
              "\n",
              "    this.ondownload = ondownload;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_header = function () {\n",
              "    var titlebar = document.createElement('div');\n",
              "    titlebar.classList =\n",
              "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
              "    var titletext = document.createElement('div');\n",
              "    titletext.classList = 'ui-dialog-title';\n",
              "    titletext.setAttribute(\n",
              "        'style',\n",
              "        'width: 100%; text-align: center; padding: 3px;'\n",
              "    );\n",
              "    titlebar.appendChild(titletext);\n",
              "    this.root.appendChild(titlebar);\n",
              "    this.header = titletext;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
              "\n",
              "mpl.figure.prototype._init_canvas = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
              "    canvas_div.setAttribute('tabindex', '0');\n",
              "    canvas_div.setAttribute(\n",
              "        'style',\n",
              "        'border: 1px solid #ddd;' +\n",
              "            'box-sizing: content-box;' +\n",
              "            'clear: both;' +\n",
              "            'min-height: 1px;' +\n",
              "            'min-width: 1px;' +\n",
              "            'outline: 0;' +\n",
              "            'overflow: hidden;' +\n",
              "            'position: relative;' +\n",
              "            'resize: both;' +\n",
              "            'z-index: 2;'\n",
              "    );\n",
              "\n",
              "    function on_keyboard_event_closure(name) {\n",
              "        return function (event) {\n",
              "            return fig.key_event(event, name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'keydown',\n",
              "        on_keyboard_event_closure('key_press')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'keyup',\n",
              "        on_keyboard_event_closure('key_release')\n",
              "    );\n",
              "\n",
              "    this._canvas_extra_style(canvas_div);\n",
              "    this.root.appendChild(canvas_div);\n",
              "\n",
              "    var canvas = (this.canvas = document.createElement('canvas'));\n",
              "    canvas.classList.add('mpl-canvas');\n",
              "    canvas.setAttribute(\n",
              "        'style',\n",
              "        'box-sizing: content-box;' +\n",
              "            'pointer-events: none;' +\n",
              "            'position: relative;' +\n",
              "            'z-index: 0;'\n",
              "    );\n",
              "\n",
              "    this.context = canvas.getContext('2d');\n",
              "\n",
              "    var backingStore =\n",
              "        this.context.backingStorePixelRatio ||\n",
              "        this.context.webkitBackingStorePixelRatio ||\n",
              "        this.context.mozBackingStorePixelRatio ||\n",
              "        this.context.msBackingStorePixelRatio ||\n",
              "        this.context.oBackingStorePixelRatio ||\n",
              "        this.context.backingStorePixelRatio ||\n",
              "        1;\n",
              "\n",
              "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
              "\n",
              "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
              "        'canvas'\n",
              "    ));\n",
              "    rubberband_canvas.setAttribute(\n",
              "        'style',\n",
              "        'box-sizing: content-box;' +\n",
              "            'left: 0;' +\n",
              "            'pointer-events: none;' +\n",
              "            'position: absolute;' +\n",
              "            'top: 0;' +\n",
              "            'z-index: 1;'\n",
              "    );\n",
              "\n",
              "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
              "    if (this.ResizeObserver === undefined) {\n",
              "        if (window.ResizeObserver !== undefined) {\n",
              "            this.ResizeObserver = window.ResizeObserver;\n",
              "        } else {\n",
              "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
              "            this.ResizeObserver = obs.ResizeObserver;\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
              "        var nentries = entries.length;\n",
              "        for (var i = 0; i < nentries; i++) {\n",
              "            var entry = entries[i];\n",
              "            var width, height;\n",
              "            if (entry.contentBoxSize) {\n",
              "                if (entry.contentBoxSize instanceof Array) {\n",
              "                    // Chrome 84 implements new version of spec.\n",
              "                    width = entry.contentBoxSize[0].inlineSize;\n",
              "                    height = entry.contentBoxSize[0].blockSize;\n",
              "                } else {\n",
              "                    // Firefox implements old version of spec.\n",
              "                    width = entry.contentBoxSize.inlineSize;\n",
              "                    height = entry.contentBoxSize.blockSize;\n",
              "                }\n",
              "            } else {\n",
              "                // Chrome <84 implements even older version of spec.\n",
              "                width = entry.contentRect.width;\n",
              "                height = entry.contentRect.height;\n",
              "            }\n",
              "\n",
              "            // Keep the size of the canvas and rubber band canvas in sync with\n",
              "            // the canvas container.\n",
              "            if (entry.devicePixelContentBoxSize) {\n",
              "                // Chrome 84 implements new version of spec.\n",
              "                canvas.setAttribute(\n",
              "                    'width',\n",
              "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
              "                );\n",
              "                canvas.setAttribute(\n",
              "                    'height',\n",
              "                    entry.devicePixelContentBoxSize[0].blockSize\n",
              "                );\n",
              "            } else {\n",
              "                canvas.setAttribute('width', width * fig.ratio);\n",
              "                canvas.setAttribute('height', height * fig.ratio);\n",
              "            }\n",
              "            /* This rescales the canvas back to display pixels, so that it\n",
              "             * appears correct on HiDPI screens. */\n",
              "            canvas.style.width = width + 'px';\n",
              "            canvas.style.height = height + 'px';\n",
              "\n",
              "            rubberband_canvas.setAttribute('width', width);\n",
              "            rubberband_canvas.setAttribute('height', height);\n",
              "\n",
              "            // And update the size in Python. We ignore the initial 0/0 size\n",
              "            // that occurs as the element is placed into the DOM, which should\n",
              "            // otherwise not happen due to the minimum size styling.\n",
              "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
              "                fig.request_resize(width, height);\n",
              "            }\n",
              "        }\n",
              "    });\n",
              "    this.resizeObserverInstance.observe(canvas_div);\n",
              "\n",
              "    function on_mouse_event_closure(name) {\n",
              "        /* User Agent sniffing is bad, but WebKit is busted:\n",
              "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
              "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
              "         * The worst that happens here is that they get an extra browser\n",
              "         * selection when dragging, if this check fails to catch them.\n",
              "         */\n",
              "        var UA = navigator.userAgent;\n",
              "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
              "        if(isWebKit) {\n",
              "            return function (event) {\n",
              "                /* This prevents the web browser from automatically changing to\n",
              "                 * the text insertion cursor when the button is pressed. We\n",
              "                 * want to control all of the cursor setting manually through\n",
              "                 * the 'cursor' event from matplotlib */\n",
              "                event.preventDefault()\n",
              "                return fig.mouse_event(event, name);\n",
              "            };\n",
              "        } else {\n",
              "            return function (event) {\n",
              "                return fig.mouse_event(event, name);\n",
              "            };\n",
              "        }\n",
              "    }\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'mousedown',\n",
              "        on_mouse_event_closure('button_press')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseup',\n",
              "        on_mouse_event_closure('button_release')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'dblclick',\n",
              "        on_mouse_event_closure('dblclick')\n",
              "    );\n",
              "    // Throttle sequential mouse events to 1 every 20ms.\n",
              "    canvas_div.addEventListener(\n",
              "        'mousemove',\n",
              "        on_mouse_event_closure('motion_notify')\n",
              "    );\n",
              "\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseenter',\n",
              "        on_mouse_event_closure('figure_enter')\n",
              "    );\n",
              "    canvas_div.addEventListener(\n",
              "        'mouseleave',\n",
              "        on_mouse_event_closure('figure_leave')\n",
              "    );\n",
              "\n",
              "    canvas_div.addEventListener('wheel', function (event) {\n",
              "        if (event.deltaY < 0) {\n",
              "            event.step = 1;\n",
              "        } else {\n",
              "            event.step = -1;\n",
              "        }\n",
              "        on_mouse_event_closure('scroll')(event);\n",
              "    });\n",
              "\n",
              "    canvas_div.appendChild(canvas);\n",
              "    canvas_div.appendChild(rubberband_canvas);\n",
              "\n",
              "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
              "    this.rubberband_context.strokeStyle = '#000000';\n",
              "\n",
              "    this._resize_canvas = function (width, height, forward) {\n",
              "        if (forward) {\n",
              "            canvas_div.style.width = width + 'px';\n",
              "            canvas_div.style.height = height + 'px';\n",
              "        }\n",
              "    };\n",
              "\n",
              "    // Disable right mouse context menu.\n",
              "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
              "        event.preventDefault();\n",
              "        return false;\n",
              "    });\n",
              "\n",
              "    function set_focus() {\n",
              "        canvas.focus();\n",
              "        canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    window.setTimeout(set_focus, 100);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'mpl-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'mpl-button-group';\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'mpl-button-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        var button = (fig.buttons[name] = document.createElement('button'));\n",
              "        button.classList = 'mpl-widget';\n",
              "        button.setAttribute('role', 'button');\n",
              "        button.setAttribute('aria-disabled', 'false');\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "\n",
              "        var icon_img = document.createElement('img');\n",
              "        icon_img.src = '_images/' + image + '.png';\n",
              "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
              "        icon_img.alt = tooltip;\n",
              "        button.appendChild(icon_img);\n",
              "\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    var fmt_picker = document.createElement('select');\n",
              "    fmt_picker.classList = 'mpl-widget';\n",
              "    toolbar.appendChild(fmt_picker);\n",
              "    this.format_dropdown = fmt_picker;\n",
              "\n",
              "    for (var ind in mpl.extensions) {\n",
              "        var fmt = mpl.extensions[ind];\n",
              "        var option = document.createElement('option');\n",
              "        option.selected = fmt === mpl.default_extension;\n",
              "        option.innerHTML = fmt;\n",
              "        fmt_picker.appendChild(option);\n",
              "    }\n",
              "\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
              "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
              "    // which will in turn request a refresh of the image.\n",
              "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_message = function (type, properties) {\n",
              "    properties['type'] = type;\n",
              "    properties['figure_id'] = this.id;\n",
              "    this.ws.send(JSON.stringify(properties));\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.send_draw_message = function () {\n",
              "    if (!this.waiting) {\n",
              "        this.waiting = true;\n",
              "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    var format_dropdown = fig.format_dropdown;\n",
              "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
              "    fig.ondownload(fig, format);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
              "    var size = msg['size'];\n",
              "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
              "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
              "        fig.send_message('refresh', {});\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
              "    var x0 = msg['x0'] / fig.ratio;\n",
              "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
              "    var x1 = msg['x1'] / fig.ratio;\n",
              "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
              "    x0 = Math.floor(x0) + 0.5;\n",
              "    y0 = Math.floor(y0) + 0.5;\n",
              "    x1 = Math.floor(x1) + 0.5;\n",
              "    y1 = Math.floor(y1) + 0.5;\n",
              "    var min_x = Math.min(x0, x1);\n",
              "    var min_y = Math.min(y0, y1);\n",
              "    var width = Math.abs(x1 - x0);\n",
              "    var height = Math.abs(y1 - y0);\n",
              "\n",
              "    fig.rubberband_context.clearRect(\n",
              "        0,\n",
              "        0,\n",
              "        fig.canvas.width / fig.ratio,\n",
              "        fig.canvas.height / fig.ratio\n",
              "    );\n",
              "\n",
              "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
              "    // Updates the figure title.\n",
              "    fig.header.textContent = msg['label'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
              "    fig.canvas_div.style.cursor = msg['cursor'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
              "    fig.message.textContent = msg['message'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
              "    // Request the server to send over a new figure.\n",
              "    fig.send_draw_message();\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
              "    fig.image_mode = msg['mode'];\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
              "    for (var key in msg) {\n",
              "        if (!(key in fig.buttons)) {\n",
              "            continue;\n",
              "        }\n",
              "        fig.buttons[key].disabled = !msg[key];\n",
              "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
              "    if (msg['mode'] === 'PAN') {\n",
              "        fig.buttons['Pan'].classList.add('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    } else if (msg['mode'] === 'ZOOM') {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.add('active');\n",
              "    } else {\n",
              "        fig.buttons['Pan'].classList.remove('active');\n",
              "        fig.buttons['Zoom'].classList.remove('active');\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Called whenever the canvas gets updated.\n",
              "    this.send_message('ack', {});\n",
              "};\n",
              "\n",
              "// A function to construct a web socket function for onmessage handling.\n",
              "// Called in the figure constructor.\n",
              "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
              "    return function socket_on_message(evt) {\n",
              "        if (evt.data instanceof Blob) {\n",
              "            var img = evt.data;\n",
              "            if (img.type !== 'image/png') {\n",
              "                /* FIXME: We get \"Resource interpreted as Image but\n",
              "                 * transferred with MIME type text/plain:\" errors on\n",
              "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
              "                 * to be part of the websocket stream */\n",
              "                img.type = 'image/png';\n",
              "            }\n",
              "\n",
              "            /* Free the memory for the previous frames */\n",
              "            if (fig.imageObj.src) {\n",
              "                (window.URL || window.webkitURL).revokeObjectURL(\n",
              "                    fig.imageObj.src\n",
              "                );\n",
              "            }\n",
              "\n",
              "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
              "                img\n",
              "            );\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        } else if (\n",
              "            typeof evt.data === 'string' &&\n",
              "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
              "        ) {\n",
              "            fig.imageObj.src = evt.data;\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        var msg = JSON.parse(evt.data);\n",
              "        var msg_type = msg['type'];\n",
              "\n",
              "        // Call the  \"handle_{type}\" callback, which takes\n",
              "        // the figure and JSON message as its only arguments.\n",
              "        try {\n",
              "            var callback = fig['handle_' + msg_type];\n",
              "        } catch (e) {\n",
              "            console.log(\n",
              "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
              "                msg\n",
              "            );\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        if (callback) {\n",
              "            try {\n",
              "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
              "                callback(fig, msg);\n",
              "            } catch (e) {\n",
              "                console.log(\n",
              "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
              "                    e,\n",
              "                    e.stack,\n",
              "                    msg\n",
              "                );\n",
              "            }\n",
              "        }\n",
              "    };\n",
              "};\n",
              "\n",
              "function getModifiers(event) {\n",
              "    var mods = [];\n",
              "    if (event.ctrlKey) {\n",
              "        mods.push('ctrl');\n",
              "    }\n",
              "    if (event.altKey) {\n",
              "        mods.push('alt');\n",
              "    }\n",
              "    if (event.shiftKey) {\n",
              "        mods.push('shift');\n",
              "    }\n",
              "    if (event.metaKey) {\n",
              "        mods.push('meta');\n",
              "    }\n",
              "    return mods;\n",
              "}\n",
              "\n",
              "/*\n",
              " * return a copy of an object with only non-object keys\n",
              " * we need this to avoid circular references\n",
              " * https://stackoverflow.com/a/24161582/3208463\n",
              " */\n",
              "function simpleKeys(original) {\n",
              "    return Object.keys(original).reduce(function (obj, key) {\n",
              "        if (typeof original[key] !== 'object') {\n",
              "            obj[key] = original[key];\n",
              "        }\n",
              "        return obj;\n",
              "    }, {});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.mouse_event = function (event, name) {\n",
              "    if (name === 'button_press') {\n",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    // from https://stackoverflow.com/q/1114465\n",
              "    var boundingRect = this.canvas.getBoundingClientRect();\n",
              "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
              "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
              "\n",
              "    this.send_message(name, {\n",
              "        x: x,\n",
              "        y: y,\n",
              "        button: event.button,\n",
              "        step: event.step,\n",
              "        modifiers: getModifiers(event),\n",
              "        guiEvent: simpleKeys(event),\n",
              "    });\n",
              "\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
              "    // Handle any extra behaviour associated with a key event\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.key_event = function (event, name) {\n",
              "    // Prevent repeat events\n",
              "    if (name === 'key_press') {\n",
              "        if (event.key === this._key) {\n",
              "            return;\n",
              "        } else {\n",
              "            this._key = event.key;\n",
              "        }\n",
              "    }\n",
              "    if (name === 'key_release') {\n",
              "        this._key = null;\n",
              "    }\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.key !== 'Control') {\n",
              "        value += 'ctrl+';\n",
              "    }\n",
              "    else if (event.altKey && event.key !== 'Alt') {\n",
              "        value += 'alt+';\n",
              "    }\n",
              "    else if (event.shiftKey && event.key !== 'Shift') {\n",
              "        value += 'shift+';\n",
              "    }\n",
              "\n",
              "    value += 'k' + event.key;\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
              "    return false;\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
              "    if (name === 'download') {\n",
              "        this.handle_save(this, null);\n",
              "    } else {\n",
              "        this.send_message('toolbar_button', { name: name });\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
              "    this.message.textContent = tooltip;\n",
              "};\n",
              "\n",
              "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
              "// prettier-ignore\n",
              "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
              "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
              "\n",
              "mpl.default_extension = \"png\";/* global mpl */\n",
              "\n",
              "var comm_websocket_adapter = function (comm) {\n",
              "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
              "    // object with the appropriate methods. Currently this is a non binary\n",
              "    // socket, so there is still some room for performance tuning.\n",
              "    var ws = {};\n",
              "\n",
              "    ws.binaryType = comm.kernel.ws.binaryType;\n",
              "    ws.readyState = comm.kernel.ws.readyState;\n",
              "    function updateReadyState(_event) {\n",
              "        if (comm.kernel.ws) {\n",
              "            ws.readyState = comm.kernel.ws.readyState;\n",
              "        } else {\n",
              "            ws.readyState = 3; // Closed state.\n",
              "        }\n",
              "    }\n",
              "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
              "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
              "\n",
              "    ws.close = function () {\n",
              "        comm.close();\n",
              "    };\n",
              "    ws.send = function (m) {\n",
              "        //console.log('sending', m);\n",
              "        comm.send(m);\n",
              "    };\n",
              "    // Register the callback with on_msg.\n",
              "    comm.on_msg(function (msg) {\n",
              "        //console.log('receiving', msg['content']['data'], msg);\n",
              "        var data = msg['content']['data'];\n",
              "        if (data['blob'] !== undefined) {\n",
              "            data = {\n",
              "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
              "            };\n",
              "        }\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(data);\n",
              "    });\n",
              "    return ws;\n",
              "};\n",
              "\n",
              "mpl.mpl_figure_comm = function (comm, msg) {\n",
              "    // This is the function which gets called when the mpl process\n",
              "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
              "\n",
              "    var id = msg.content.data.id;\n",
              "    // Get hold of the div created by the display call when the Comm\n",
              "    // socket was opened in Python.\n",
              "    var element = document.getElementById(id);\n",
              "    var ws_proxy = comm_websocket_adapter(comm);\n",
              "\n",
              "    function ondownload(figure, _format) {\n",
              "        window.open(figure.canvas.toDataURL());\n",
              "    }\n",
              "\n",
              "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
              "\n",
              "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
              "    // web socket which is closed, not our websocket->open comm proxy.\n",
              "    ws_proxy.onopen();\n",
              "\n",
              "    fig.parent_element = element;\n",
              "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
              "    if (!fig.cell_info) {\n",
              "        console.error('Failed to find cell for figure', id, fig);\n",
              "        return;\n",
              "    }\n",
              "    fig.cell_info[0].output_area.element.on(\n",
              "        'cleared',\n",
              "        { fig: fig },\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
              "    var width = fig.canvas.width / fig.ratio;\n",
              "    fig.cell_info[0].output_area.element.off(\n",
              "        'cleared',\n",
              "        fig._remove_fig_handler\n",
              "    );\n",
              "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
              "\n",
              "    // Update the output cell to use the data from the current canvas.\n",
              "    fig.push_to_output();\n",
              "    var dataURL = fig.canvas.toDataURL();\n",
              "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
              "    // the notebook keyboard shortcuts fail.\n",
              "    IPython.keyboard_manager.enable();\n",
              "    fig.parent_element.innerHTML =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "    fig.close_ws(fig, msg);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
              "    fig.send_message('closing', msg);\n",
              "    // fig.ws.close()\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
              "    // Turn the data on the canvas into data in the output cell.\n",
              "    var width = this.canvas.width / this.ratio;\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] =\n",
              "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function () {\n",
              "    // Tell IPython that the notebook contents must change.\n",
              "    IPython.notebook.set_dirty(true);\n",
              "    this.send_message('ack', {});\n",
              "    var fig = this;\n",
              "    // Wait a second, then push the new image to the DOM so\n",
              "    // that it is saved nicely (might be nice to debounce this).\n",
              "    setTimeout(function () {\n",
              "        fig.push_to_output();\n",
              "    }, 1000);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function () {\n",
              "    var fig = this;\n",
              "\n",
              "    var toolbar = document.createElement('div');\n",
              "    toolbar.classList = 'btn-toolbar';\n",
              "    this.root.appendChild(toolbar);\n",
              "\n",
              "    function on_click_closure(name) {\n",
              "        return function (_event) {\n",
              "            return fig.toolbar_button_onclick(name);\n",
              "        };\n",
              "    }\n",
              "\n",
              "    function on_mouseover_closure(tooltip) {\n",
              "        return function (event) {\n",
              "            if (!event.currentTarget.disabled) {\n",
              "                return fig.toolbar_button_onmouseover(tooltip);\n",
              "            }\n",
              "        };\n",
              "    }\n",
              "\n",
              "    fig.buttons = {};\n",
              "    var buttonGroup = document.createElement('div');\n",
              "    buttonGroup.classList = 'btn-group';\n",
              "    var button;\n",
              "    for (var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            /* Instead of a spacer, we start a new button group. */\n",
              "            if (buttonGroup.hasChildNodes()) {\n",
              "                toolbar.appendChild(buttonGroup);\n",
              "            }\n",
              "            buttonGroup = document.createElement('div');\n",
              "            buttonGroup.classList = 'btn-group';\n",
              "            continue;\n",
              "        }\n",
              "\n",
              "        button = fig.buttons[name] = document.createElement('button');\n",
              "        button.classList = 'btn btn-default';\n",
              "        button.href = '#';\n",
              "        button.title = name;\n",
              "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
              "        button.addEventListener('click', on_click_closure(method_name));\n",
              "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
              "        buttonGroup.appendChild(button);\n",
              "    }\n",
              "\n",
              "    if (buttonGroup.hasChildNodes()) {\n",
              "        toolbar.appendChild(buttonGroup);\n",
              "    }\n",
              "\n",
              "    // Add the status bar.\n",
              "    var status_bar = document.createElement('span');\n",
              "    status_bar.classList = 'mpl-message pull-right';\n",
              "    toolbar.appendChild(status_bar);\n",
              "    this.message = status_bar;\n",
              "\n",
              "    // Add the close button to the window.\n",
              "    var buttongrp = document.createElement('div');\n",
              "    buttongrp.classList = 'btn-group inline pull-right';\n",
              "    button = document.createElement('button');\n",
              "    button.classList = 'btn btn-mini btn-primary';\n",
              "    button.href = '#';\n",
              "    button.title = 'Stop Interaction';\n",
              "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
              "    button.addEventListener('click', function (_evt) {\n",
              "        fig.handle_close(fig, {});\n",
              "    });\n",
              "    button.addEventListener(\n",
              "        'mouseover',\n",
              "        on_mouseover_closure('Stop Interaction')\n",
              "    );\n",
              "    buttongrp.appendChild(button);\n",
              "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
              "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
              "    var fig = event.data.fig;\n",
              "    if (event.target !== this) {\n",
              "        // Ignore bubbled events from children.\n",
              "        return;\n",
              "    }\n",
              "    fig.close_ws(fig, {});\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function (el) {\n",
              "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
              "    // this is important to make the div 'focusable\n",
              "    el.setAttribute('tabindex', 0);\n",
              "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
              "    // off when our div gets focus\n",
              "\n",
              "    // location in version 3\n",
              "    if (IPython.notebook.keyboard_manager) {\n",
              "        IPython.notebook.keyboard_manager.register_events(el);\n",
              "    } else {\n",
              "        // location in version 2\n",
              "        IPython.keyboard_manager.register_events(el);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
              "    // Check for shift+enter\n",
              "    if (event.shiftKey && event.which === 13) {\n",
              "        this.canvas_div.blur();\n",
              "        // select the cell after this one\n",
              "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
              "        IPython.notebook.select(index + 1);\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
              "    fig.ondownload(fig, null);\n",
              "};\n",
              "\n",
              "mpl.find_output_cell = function (html_output) {\n",
              "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
              "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
              "    // IPython event is triggered only after the cells have been serialised, which for\n",
              "    // our purposes (turning an active figure into a static one), is too late.\n",
              "    var cells = IPython.notebook.get_cells();\n",
              "    var ncells = cells.length;\n",
              "    for (var i = 0; i < ncells; i++) {\n",
              "        var cell = cells[i];\n",
              "        if (cell.cell_type === 'code') {\n",
              "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
              "                var data = cell.output_area.outputs[j];\n",
              "                if (data.data) {\n",
              "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
              "                    data = data.data;\n",
              "                }\n",
              "                if (data['text/html'] === html_output) {\n",
              "                    return [cell, data, j];\n",
              "                }\n",
              "            }\n",
              "        }\n",
              "    }\n",
              "};\n",
              "\n",
              "// Register the function which deals with the matplotlib target/channel.\n",
              "// The kernel may be null if the page has been refreshed.\n",
              "if (IPython.notebook.kernel !== null) {\n",
              "    IPython.notebook.kernel.comm_manager.register_target(\n",
              "        'matplotlib',\n",
              "        mpl.mpl_figure_comm\n",
              "    );\n",
              "}\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div id='7a2d4115-8832-46a9-8bd3-97e54b0fa3f3'></div>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1f8vxk3WypKn"
      },
      "outputs": [],
      "source": [
        "# !jupyter nbconvert --to script ct.ipynb"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "V100"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.1"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}