MixMatch_v3.ipynb

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  "cells": [
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      "cell_type": "code",
      "metadata": {
        "id": "1HdPUmwf4M-4"
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      "source": [
        "# from google.colab import drive\n",
        "# drive.mount('/content/gdrive', force_remount= True)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AziIsuVg4X4W"
      },
      "source": [
        "from __future__ import print_function, division\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "from torch.optim import lr_scheduler\n",
        "import numpy as np\n",
        "import torchvision\n",
        "from torchvision import datasets, models, transforms\n",
        "import matplotlib.pyplot as plt\n",
        "import time\n",
        "import os\n",
        "import copy\n",
        "\n",
        "plt.ion()   # interactive mode"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "va2Mxic-yRlU"
      },
      "source": [
        "def displayImages(images, title1=\"Original\", title2=\"Augmented\", labels=None, augmented_images=None):\n",
        "    class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer',\n",
        "                   'dog', 'frog', 'horse', 'ship', 'truck']\n",
        "\n",
        "    fig = plt.figure(figsize=(images.shape[0], images.shape[0]))\n",
        "    for i in range(images.shape[0]):\n",
        "        plt.subplot(5, 5, i + 1)\n",
        "        plt.xticks([])\n",
        "        plt.yticks([])\n",
        "        plt.grid(False)\n",
        "        plt.imshow(images[i], cmap=plt.cm.binary)\n",
        "        if labels is not None:\n",
        "            plt.xlabel(class_names[int(labels[i])])\n",
        "    fig.suptitle(title1, fontsize=16)\n",
        "\n",
        "    if augmented_images is not None:\n",
        "        fig2 = plt.figure(2, figsize=(augmented_images.shape[0], augmented_images.shape[0]))\n",
        "        for i in range(augmented_images.shape[0]):\n",
        "            plt.subplot(5, 5, i + 1)\n",
        "            plt.xticks([])\n",
        "            plt.yticks([])\n",
        "            plt.grid(False)\n",
        "            plt.imshow(augmented_images[i], cmap=plt.cm.binary)\n",
        "            if labels is not None:\n",
        "                plt.xlabel(class_names[int(labels[i])])\n",
        "        fig2.suptitle(title2, fontsize=16)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def split_indexes(n_classes, n_labeled_per_class, n_validation, labels):\n",
        "    labels = np.array(labels)\n",
        "    train_labeled_indexes = []\n",
        "    train_unlabeled_indexes = []\n",
        "    validation_indexes = []\n",
        "\n",
        "    for i in range(n_classes):\n",
        "        indexes = np.where(labels == i)[0]\n",
        "        np.random.shuffle(indexes)\n",
        "\n",
        "        train_labeled_indexes.extend(indexes[:n_labeled_per_class])\n",
        "        train_unlabeled_indexes.extend(indexes[n_labeled_per_class:-n_validation])\n",
        "        validation_indexes.extend(indexes[-n_validation:])\n",
        "\n",
        "    np.random.shuffle(train_unlabeled_indexes)\n",
        "    np.random.shuffle(train_labeled_indexes)\n",
        "    np.random.shuffle(validation_indexes)\n",
        "\n",
        "    return train_labeled_indexes, train_unlabeled_indexes, validation_indexes\n",
        "\n",
        "\n",
        "def to_tensor_dim(x, source='NHWC', target='NCHW'):\n",
        "    return x.transpose([source.index(d) for d in target])\n",
        "\n",
        "\n",
        "def normalise(X):\n",
        "    mean = np.mean(X, axis=(0, 1, 2))\n",
        "    std = np.std(X, axis=(0, 1, 2))\n",
        "    X, mean, std = [np.array(a, np.float32) for a in (X, mean, std)]\n",
        "    X -= mean\n",
        "    X *= 1.0 / std\n",
        "    return X\n",
        "\n",
        "\n",
        "def random_flip(x):\n",
        "    if np.random.rand() < 0.6:\n",
        "        x = x[:, ::-1, :]\n",
        "    return x.copy()\n",
        "\n",
        "\n",
        "def pad(x, border=4):\n",
        "    return np.pad(x, [(border, border), (border, border), (0, 0)], mode='reflect')\n",
        "\n",
        "\n",
        "def pad_and_crop(x, output_size=(32, 32)):\n",
        "    x = pad(x, 4)\n",
        "    h, w = x.shape[:-1]\n",
        "    new_h, new_w = output_size\n",
        "\n",
        "    top = np.random.randint(0, h - new_h)\n",
        "    left = np.random.randint(0, w - new_w)\n",
        "\n",
        "    x = x[top: top + new_h, left: left + new_w, :]\n",
        "\n",
        "    return x\n",
        "\n",
        "\n",
        "def augment(X, K=1):\n",
        "\n",
        "    # X_augmented = X\n",
        "    # for k in range(K-1):\n",
        "    #   X_augmented.hstack(X)\n",
        "    X_augmented = np.zeros(([K]+list(X.shape)))\n",
        "\n",
        "    # print(\"after hstack\", X_augmented.shape)\n",
        "    for k in range(K):\n",
        "      for i in range(X_augmented[k].shape[0]):\n",
        "            x = X[i, :]\n",
        "            x = pad_and_crop(x)\n",
        "            X_augmented[k, i, :] = random_flip(x)\n",
        "    return X_augmented\n",
        "\n",
        "\n",
        "def load_and_augment_data(dataset_name, model_params):\n",
        "    \"\"\"\n",
        "    From datasets.CIFAR10:\n",
        "        dataset.data: the image as numpy array, shape: (50000, 32, 32, 3)\n",
        "        dataset.targets: labels of the images as list, len: 50000\n",
        "    :return:\n",
        "        augmented_labeled_X: the tensor of augmented labeled images (K=1),\n",
        "                             size: (n_labeled_per_class * n_classes , 32, 32, 3)\n",
        "        augmented_unlabeled_X: the tensor of augmented unlabeled images (K=2),\n",
        "                             size: ((N/10 - n_labeled_per_class - n_validation) * n_classes * K , 32, 32, 3)\n",
        "        train_labeled_targets: the tensor of labeled targets,\n",
        "                             size = n_labeled_per_class * n_classes\n",
        "        train_unlabeled_targets: the tensor of unlabeled targets,\n",
        "                             size = (N/10 - n_labeled_per_class - n_validation) * n_classes\n",
        "    \"\"\"\n",
        "\n",
        "    # Step 1: Set the model's hyperparameters\n",
        "    n_classes = model_params[\"n_classes\"]\n",
        "    n_labeled_per_class = model_params[\"n_labeled_per_class\"]\n",
        "    n_validation = model_params[\"n_validation\"]\n",
        "    K = model_params[\"K\"]\n",
        "\n",
        "    # Step 2: Load the dataset\n",
        "    if dataset_name == 'CIFAR10':\n",
        "        dataset = datasets.CIFAR10(root=\"./datasets\", train=True, download=True)\n",
        "    elif dataset_name == 'SLT10':\n",
        "        dataset = datasets.STL10(root=\"./datasets\", download=True)\n",
        "    else:\n",
        "        raise ValueError(\"Invalid dataset name\")\n",
        "\n",
        "    # Step 3: Split the indexes\n",
        "    train_labeled_indexes, train_unlabeled_indexes, validation_indexes = \\\n",
        "        split_indexes(n_classes, n_labeled_per_class, n_validation, dataset.targets)\n",
        "\n",
        "    # Step 4: Attract the images for training, validation\n",
        "    train_labeled_images = np.take(dataset.data, train_labeled_indexes, axis=0)\n",
        "    train_unlabeled_images = np.take(dataset.data, train_unlabeled_indexes, axis=0)\n",
        "    target_array = np.asarray(dataset.targets)\n",
        "    train_labeled_targets = np.take(target_array, train_labeled_indexes, axis=0)\n",
        "    train_unlabeled_targets = np.take(target_array, train_unlabeled_indexes, axis=0)\n",
        "    validation_images = np.take(dataset.data, validation_indexes, axis=0)\n",
        "    validation_targets = np.take(target_array, validation_indexes, axis=0)\n",
        "\n",
        "    # Step 5: Normalise the datasets\n",
        "    train_labeled_images = normalise(train_labeled_images)\n",
        "    train_unlabeled_images = normalise(train_unlabeled_images)\n",
        "\n",
        "    # Step 6: Augment training images\n",
        "    print(\"shape\",train_unlabeled_images.shape )\n",
        "\n",
        "    augmented_labeled_X = augment(train_labeled_images, K=1)\n",
        "    augmented_unlabeled_X = augment(train_unlabeled_images, K=K)\n",
        "    \n",
        "    print(\"shape after\", augmented_unlabeled_X.shape )\n",
        "    \n",
        "    # Take a look at some of the augmented images\n",
        "    # displayImages(train_labeled_images[:10], title1=\"Original-Labeled\", title2=\"Augmented-Labeled\",\n",
        "    #               augmented_images=augmented_labeled_X[:10], labels=train_labeled_targets[:10])\n",
        "    # n_unlabeled = train_unlabeled_images.shape[0]\n",
        "    # displayImages(train_unlabeled_images[:10], title1=\"Original-Unlabeled\", title2=\"Augmented-Unlabeled\",\n",
        "    #               augmented_images=augmented_unlabeled_X[:10], labels=train_unlabeled_targets[:10])\n",
        "    # displayImages(augmented_unlabeled_X[:10], title1=\"Augmented-Unlabeled1\", title2=\"Augmented-Unlabeled2\",\n",
        "    #               augmented_images=augmented_unlabeled_X[n_unlabeled:10+n_unlabeled],\n",
        "    #               labels=train_unlabeled_targets[:10])\n",
        "\n",
        "    # Step 7: Change the dimension of np.array in oder for it to work in torch\n",
        "    augmented_labeled_X = to_tensor_dim(augmented_labeled_X.reshape(train_labeled_images.shape))\n",
        "\n",
        "    augmented_unlabeled_X_zeros = np.zeros(([K]+[augmented_unlabeled_X.shape[1]] + list(augmented_labeled_X.shape[1:])))\n",
        "    #print(\"augmented_unlabeled_X_zeros\", augmented_unlabeled_X_zeros.shape)\n",
        "    for k in range(K):\n",
        "      unlabeled_shape = augmented_unlabeled_X[k].reshape(train_unlabeled_images.shape)\n",
        "      #print(\"unlabeled_shape\", unlabeled_shape)\n",
        "      augmented_unlabeled_X_zeros[k] = to_tensor_dim(unlabeled_shape)\n",
        "    validation_images = to_tensor_dim(validation_images)\n",
        "    \n",
        "    return torch.from_numpy(augmented_labeled_X), torch.from_numpy(augmented_unlabeled_X_zeros), \\\n",
        "           torch.from_numpy(train_labeled_targets), torch.from_numpy(train_unlabeled_targets), \\\n",
        "           torch.from_numpy(validation_images), torch.from_numpy(validation_targets)\n"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uVktFDszObih"
      },
      "source": [
        "# Defining Model Parameters and obtaining train and val sets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219,
          "referenced_widgets": [
            "b284816c8c1c45e7a7c444205f540446",
            "2274d4bbecbb426d8358036bb4ca9019",
            "58316e2ffbb7468d9a808dce3e6cbd89",
            "79fae45e0256472795cb618427e3142e",
            "eda1fd7d2a9b48a19bd9a45b8e6a01c4",
            "7fe7db39c0e64ebe9d88612bbbc167ab",
            "df6cb6b9634a4f5887092fa831f23f1d",
            "80fdf5f9933d499b8898ae2208e4ac98"
          ]
        },
        "id": "4t_9ML18yasD",
        "outputId": "eb2e2237-0887-4b62-d7cf-2f860c09da8c"
      },
      "source": [
        "model_params = {\n",
        "    \"n_classes\": 10,\n",
        "    \"n_labeled_per_class\": 3000,\n",
        "    \"n_validation\": 500,\n",
        "    \"K\": 2\n",
        "}\n",
        "augmented_labeled_X, augmented_unlabeled_X, train_labeled_targets, train_unlabeled_targets, \\\n",
        "    validation_images, validation_targets = load_and_augment_data('CIFAR10', model_params)\n",
        "\n",
        "print(augmented_labeled_X.size())\n",
        "print(augmented_unlabeled_X.size())\n",
        "print(train_labeled_targets.size())\n",
        "print(train_unlabeled_targets.size())\n",
        "\n",
        "\n",
        "# Half the number of labeled data TODO:check this!\n",
        "n_labeled = augmented_labeled_X.size()[0]\n",
        "new_n = int(n_labeled/2)\n",
        "augmented_labeled_X = augmented_labeled_X[:new_n]\n",
        "print(f\"New length: {augmented_labeled_X.size()}\")\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to ./datasets/cifar-10-python.tar.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "b284816c8c1c45e7a7c444205f540446",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=170498071.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Extracting ./datasets/cifar-10-python.tar.gz to ./datasets\n",
            "shape (15000, 32, 32, 3)\n",
            "shape after (2, 15000, 32, 32, 3)\n",
            "torch.Size([30000, 3, 32, 32])\n",
            "torch.Size([2, 15000, 3, 32, 32])\n",
            "torch.Size([30000])\n",
            "torch.Size([15000])\n",
            "New length: torch.Size([15000, 3, 32, 32])\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pbp2lWcuJYmV"
      },
      "source": [
        "# Splitting data into Batches"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pok_bZgUJxco"
      },
      "source": [
        "batch_size = 10"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZX6c1XbUJkA2"
      },
      "source": [
        "## Splitting labelled data\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ttYoAOvqk1ot"
      },
      "source": [
        "permutation = torch.randperm(augmented_labeled_X.size()[0])\n",
        "labeled_batches = []\n",
        "for i in range(0,augmented_labeled_X.size()[0], batch_size):\n",
        "        indices = permutation[i:i+batch_size]\n",
        "        batch_x, batch_y = augmented_labeled_X[indices], train_labeled_targets[indices]\n",
        "        labeled_batches.append((batch_x, batch_y))"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cn5yUae9Jua8"
      },
      "source": [
        "# Splitting unlabelled data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VMO1gm-wItV9"
      },
      "source": [
        "#Splitting unlabelled into batches\n",
        "k_unlabeled_batches = []\n",
        "for k in range(augmented_unlabeled_X.size()[0]):\n",
        "  permutation = torch.randperm(augmented_unlabeled_X.size()[1])\n",
        "  unlabeled_batches = []\n",
        "  for i in range(0, augmented_unlabeled_X.size()[1], batch_size):\n",
        "          indices = permutation[i:i+batch_size]\n",
        "          batch = augmented_unlabeled_X[k][indices]\n",
        "          unlabeled_batches.append(batch)\n",
        "  k_unlabeled_batches.append(unlabeled_batches)\n"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0c5_MqEolyPr",
        "outputId": "f4c83223-6e66-4079-fa2a-ae2428630833"
      },
      "source": [
        "k_unlabeled_batches[0][0].size()\n"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([10, 3, 32, 32])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9vhi_NtWR3UQ"
      },
      "source": [
        "K_unlabeled_batches is a tuple of shape [k, num_batches, batch_size, 3, 32, 32]\n",
        "where k is the number of augmentations."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "okMxCrpwOTfa"
      },
      "source": [
        "# Defining Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GY3wObVfFWXW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 83,
          "referenced_widgets": [
            "43d3ec45caa54986b07cf11abba1685d",
            "d654d895c18f434497cd8fc0bc38f8d9",
            "2034dbb285294114af29426b682f257c",
            "413b53dd16f14ba3a4e5706dd82e7c51",
            "55e7e86789f54a9aa7248855b8608d2d",
            "dfeba9dbcd164326b978040372632e6a",
            "9d5de4fc6b8845999de4902e0e02afcf",
            "a38f8c97b7724442bb256a48cf947aba"
          ]
        },
        "outputId": "edc7712d-d38b-484f-c75d-c2093e3a6876"
      },
      "source": [
        "classes = ('plane', 'car', 'bird', 'cat',\n",
        "           'deer', 'dog', 'frog', 'horse', 'ship', 'truck')\n",
        "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
        "\n",
        "model_ft = models.resnet18(pretrained=True)\n",
        "num_ftrs = model_ft.fc.in_features\n",
        "# Here the size of each output sample is set to 2.\n",
        "# Alternatively, it can be generalized to nn.Linear(num_ftrs, len(class_names)).\n",
        "model_ft.fc = nn.Linear(num_ftrs, len(classes))\n",
        "\n",
        "model_ft = model_ft.to(device)\n",
        "\n",
        "criterion = nn.CrossEntropyLoss()\n",
        "\n",
        "# Observe that all parameters are being optimized\n",
        "optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\n",
        "\n",
        "# Decay LR by a factor of 0.1 every 7 epochs\n",
        "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: \"https://download.pytorch.org/models/resnet18-5c106cde.pth\" to /root/.cache/torch/hub/checkpoints/resnet18-5c106cde.pth\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "43d3ec45caa54986b07cf11abba1685d",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=46827520.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lHjp1npZFjyz"
      },
      "source": [
        "def label_guessing(model, data):\n",
        "   return model(data)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NoVTPmq4SVon"
      },
      "source": [
        "# Example use of label_guessing function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NDaNW_EYQiEe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "14abc365-63b8-4e39-b767-6c48c2d64ed0"
      },
      "source": [
        "guesses = label_guessing(model_ft, k_unlabeled_batches[0][0].float().to(device))\n",
        "print(f\"shape: {guesses.shape}\")\n",
        "print(guesses)\n",
        "\n"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "shape: torch.Size([10, 10])\n",
            "tensor([[-1.2789, -0.5869, -0.0888,  1.7029, -2.6441, -1.3944,  0.9974,  2.3822,\n",
            "          1.1978,  0.1573],\n",
            "        [-0.1398,  0.0064,  0.4604,  0.3415, -0.7673,  1.3372,  1.4283,  0.1526,\n",
            "          1.1103,  0.7259],\n",
            "        [-0.0276, -0.7054, -0.6044,  0.3507, -0.2867, -1.2972, -0.0840,  1.6870,\n",
            "          0.4973, -0.5207],\n",
            "        [ 0.7743, -0.2185, -0.5104, -0.1310, -1.0116, -1.0090,  2.2560, -0.0497,\n",
            "          0.1744,  0.0392],\n",
            "        [ 0.6033, -0.3544,  0.9827,  0.8817, -0.7490, -0.3838,  1.3908,  0.5579,\n",
            "          0.1137,  1.3341],\n",
            "        [ 0.1961,  0.1221, -0.2273,  0.0891, -0.8502, -1.3683,  1.8759,  0.4580,\n",
            "          0.3588,  0.8689],\n",
            "        [-0.8054,  0.0316,  0.9166,  0.6161, -1.2150,  0.3562,  3.0396,  2.2617,\n",
            "          0.6982,  1.0428],\n",
            "        [ 0.5101, -1.1070,  0.5907,  0.9323, -0.5980, -0.9324, -0.5306,  1.8763,\n",
            "          1.9642,  1.2228],\n",
            "        [-0.9229, -1.2849, -0.3821,  0.7601, -0.8083, -1.5911, -0.1905, -0.8115,\n",
            "          0.7612,  1.3981],\n",
            "        [ 0.3853, -1.7102,  0.3686,  2.3023, -0.2958, -0.5422,  1.3300,  0.3969,\n",
            "          0.8286,  0.6760]], device='cuda:0', grad_fn=<AddmmBackward>)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D7PlDRsg-AWl"
      },
      "source": [
        "def guess_and_sharpen(augmented_unlabeled_X1, augmented_unlabeled_X2, T=0.5):\n",
        "    \"\"\"\n",
        "    Assume:\n",
        "      label_guesses: a list of K guesses\n",
        "    \"\"\"\n",
        "    guess1 = label_guessing(model_ft, augmented_unlabeled_X1.float().to(device))\n",
        "    guess2 = label_guessing(model_ft, augmented_unlabeled_X2.float().to(device))\n",
        "\n",
        "    # Compute the average predictions across all augmentations\n",
        "    p = (torch.softmax(guess1, dim=1) + torch.softmax(guess2, dim=1)) / 2\n",
        "\n",
        "    # Sharpen\n",
        "    pt = p**(1/T)\n",
        "    targets_u = pt/pt.sum(dim=1, keepdim=True)\n",
        "    targets_u = targets_u.detach()\n",
        "\n",
        "    return targets_u\n",
        "\n",
        "\n",
        "def mixup(X_hat, data_U1, data_U2, targets_U, alpha):\n",
        "    data_X = X_hat[0].float().to(device)\n",
        "    targets_X = X_hat[1]\n",
        "\n",
        "    targets_X = torch.nn.functional.one_hot(targets_X, num_classes=10).float().to(device)\n",
        "\n",
        "    batch_size = data_X.size(0)\n",
        "\n",
        "    # Form W\n",
        "    all_data = torch.cat([data_X, data_U1.float().to(device), data_U2.float().to(device)], dim=0)\n",
        "    all_targets = torch.cat([targets_X, targets_U, targets_U], dim=0)\n",
        "\n",
        "    idx = torch.randperm(all_data.size(0))\n",
        "    W_data = all_data[idx]\n",
        "    W_targets = all_targets[idx]\n",
        "\n",
        "    # Mix it up\n",
        "    lamda = np.random.beta(alpha, alpha)\n",
        "    lamda = max(lamda, 1 - lamda)\n",
        "\n",
        "    data_prime = lamda * all_data + (1-lamda) * W_data\n",
        "    targets_prime = lamda * all_targets + (1-lamda) * W_targets\n",
        "\n",
        "    return data_prime, targets_prime\n"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "63xD9oiGctPI"
      },
      "source": [
        "def train(labeled_batches, k_unlabeled_batches):\n",
        "    # Step 1: Input of the function (Raghav)\n",
        "      # labeled_batches: List, size: n_batches, each elem: tuple of X(tensor) and targets(tensor)\n",
        "      # k_unlabeled_batches: [k, num_batches, batch_size, 3, 32, 32] where k is the number of augmentations.\n",
        "\n",
        "    n_batches = len(labeled_batches)\n",
        "    alpha = 0.75\n",
        "\n",
        "    # Step 2: For loop\n",
        "    for i in range(n_batches):\n",
        "        targets_u = guess_and_sharpen(k_unlabeled_batches[0][i], k_unlabeled_batches[1][i])\n",
        "        data_prime, targets_prime = mixup(labeled_batches[i], k_unlabeled_batches[0][i], k_unlabeled_batches[1][i], targets_u, alpha) \n",
        "\n",
        "        print(f\"data_prime size: {data_prime.size()}\")\n",
        "        print(f\"targets_prime size: {targets_prime.size()}\")\n",
        "        \n",
        "        # data_prime: labeled + u1 + u2, size(3*batch_size, 3, 32, 32)\n",
        "        # targets_prime: labeled + u1 + u2, size(3*batch_size, 10)\n",
        "\n",
        "        # Step3: Set the model\n",
        "\n",
        "\n"
      ],
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cJlZcOFTdb25",
        "outputId": "b74d4931-0f73-4f4f-cac9-0faa16e2d5d9"
      },
      "source": [
        "train(labeled_batches, k_unlabeled_batches)"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n",
            "data_prime size: torch.Size([30, 3, 32, 32])\n",
            "targets_prime size: torch.Size([30, 10])\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z2KIoCSgRpD8"
      },
      "source": [
        "#Example Train function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8puyYVxCRn_q"
      },
      "source": [
        "def train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n",
        "    since = time.time()\n",
        "\n",
        "    best_model_wts = copy.deepcopy(model.state_dict())\n",
        "    best_acc = 0.0\n",
        "\n",
        "    for epoch in range(num_epochs):\n",
        "        print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
        "        print('-' * 10)\n",
        "\n",
        "        # Each epoch has a training and validation phase\n",
        "        for phase in ['train']:\n",
        "            if phase == 'train':\n",
        "                model.train()  # Set model to training mode\n",
        "            else:\n",
        "                model.eval()   # Set model to evaluate mode\n",
        "\n",
        "            running_loss = 0.0\n",
        "            running_corrects = 0\n",
        "\n",
        "            # Iterate over data.\n",
        "            for inputs, labels in dataloaders[phase]:\n",
        "                inputs = inputs.to(device)\n",
        "                labels = labels.to(device)\n",
        "\n",
        "                # zero the parameter gradients\n",
        "                optimizer.zero_grad()\n",
        "\n",
        "                # forward\n",
        "                # track history if only in train\n",
        "                #import pdb; pdb.set_trace()\n",
        "                with torch.set_grad_enabled(phase == 'train'):\n",
        "                    outputs = model(inputs)\n",
        "                    #print(outputs.shape)\n",
        "                    _, preds = torch.max(outputs, 1)\n",
        "                    loss = criterion(outputs, labels)\n",
        "\n",
        "                    # backward + optimize only if in training phase\n",
        "                    if phase == 'train':\n",
        "                        loss.backward()\n",
        "                        optimizer.step()\n",
        "\n",
        "                # statistics\n",
        "                running_loss += loss.item() * inputs.size(0)\n",
        "                running_corrects += torch.sum(preds == labels.data)\n",
        "            if phase == 'train':\n",
        "                scheduler.step()\n",
        "\n",
        "            epoch_loss = running_loss / 50000\n",
        "            epoch_acc = running_corrects.double() / 50000\n",
        "            print('{} Loss: {:.4f} Acc: {:.4f}'.format(\n",
        "                phase, epoch_loss, epoch_acc))\n",
        "\n",
        "            # deep copy the model\n",
        "            if phase == 'val' and epoch_acc > best_acc:\n",
        "                best_acc = epoch_acc\n",
        "                best_model_wts = copy.deepcopy(model.state_dict())\n",
        "\n",
        "        print()\n",
        "\n",
        "    time_elapsed = time.time() - since\n",
        "    print('Training complete in {:.0f}m {:.0f}s'.format(\n",
        "        time_elapsed // 60, time_elapsed % 60))\n",
        "    print('Best val Acc: {:4f}'.format(best_acc))\n",
        "\n",
        "    # load best model weights\n",
        "    model.load_state_dict(best_model_wts)\n",
        "    return model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O8uTe8SKRxRb"
      },
      "source": [
        "model_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n",
        "                       num_epochs=2)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tPSoU3xYzGPD"
      },
      "source": [
        "# import torch.utils.data as data\n",
        "# batch_size = 10\n",
        "# labeled_trainloader = load((augmented_labeled_X, train_labeled_targets), batch_size=batch_size, shuffle=True, num_workers=0, drop_last=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NbxUeMgiRwrl"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pqBkDdjS-c9Y"
      },
      "source": [
        "# labeled_trainloader"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q20cZv5yC8H8"
      },
      "source": [
        "# labeled_train_iter = iter(labeled_trainloader)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HajD3KshC98p"
      },
      "source": [
        "# inputs_x, targets_x = labeled_train_iter.next()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mPSME6c5yzb-"
      },
      "source": [
        "# def mix_match(x_batch, y_batch)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vZiPAa-7zFTu"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fma7aqeC9ioS"
      },
      "source": [
        "# def train_val_split(labels, n_labeled_per_class):\n",
        "#     labels = np.array(labels)\n",
        "#     train_labeled_idxs = []\n",
        "#     train_unlabeled_idxs = []\n",
        "#     val_idxs = []\n",
        "\n",
        "#     for i in range(10):\n",
        "#         idxs = np.where(labels == i)[0]\n",
        "#         np.random.shuffle(idxs)\n",
        "#         train_labeled_idxs.extend(idxs[:n_labeled_per_class])\n",
        "#         train_unlabeled_idxs.extend(idxs[n_labeled_per_class:-500])\n",
        "#         val_idxs.extend(idxs[-500:])\n",
        "#     np.random.shuffle(train_labeled_idxs)\n",
        "#     np.random.shuffle(train_unlabeled_idxs)\n",
        "#     np.random.shuffle(val_idxs)\n",
        "\n",
        "#     return train_labeled_idxs, train_unlabeled_idxs, val_idxs"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0q6ebyri97fk"
      },
      "source": [
        "# class CIFAR10_labeled(torchvision.datasets.CIFAR10):\n",
        "\n",
        "#     def __init__(self, root, indexs=None, train=True,\n",
        "#                  transform=None, target_transform=None,\n",
        "#                  download=False):\n",
        "#         super(CIFAR10_labeled, self).__init__(root, train=train,\n",
        "#                  transform=transform, target_transform=target_transform,\n",
        "#                  download=download)\n",
        "#         if indexs is not None:\n",
        "#             self.data = self.data[indexs]\n",
        "#             self.targets = np.array(self.targets)[indexs]\n",
        "#         self.data = transpose(normalise(self.data))\n",
        "\n",
        "#     def __getitem__(self, index):\n",
        "#         \"\"\"\n",
        "#         Args:\n",
        "#             index (int): Index\n",
        "#         Returns:\n",
        "#             tuple: (image, target) where target is index of the target class.\n",
        "#         \"\"\"\n",
        "#         img, target = self.data[index], self.targets[index]\n",
        "\n",
        "#         if self.transform is not None:\n",
        "#             img = self.transform(img)\n",
        "\n",
        "#         if self.target_transform is not None:\n",
        "#             target = self.target_transform(target)\n",
        "\n",
        "#         return img, target\n",
        "    \n",
        "\n",
        "# class CIFAR10_unlabeled(CIFAR10_labeled):\n",
        "\n",
        "#     def __init__(self, root, indexs, train=True,\n",
        "#                  transform=None, target_transform=None,\n",
        "#                  download=False):\n",
        "#         super(CIFAR10_unlabeled, self).__init__(root, indexs, train=train,\n",
        "#                  transform=transform, target_transform=target_transform,\n",
        "#                  download=download)\n",
        "#         self.targets = np.array([-1 for i in range(len(self.targets))])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dG_EAv26-kRT"
      },
      "source": [
        "# def normalise(x, mean=cifar10_mean, std=cifar10_std):\n",
        "#     x, mean, std = [np.array(a, np.float32) for a in (x, mean, std)]\n",
        "#     x -= mean*255\n",
        "#     x *= 1.0/(255*std)\n",
        "#     return x\n",
        "\n",
        "# def transpose(x, source='NHWC', target='NCHW'):\n",
        "#     return x.transpose([source.index(d) for d in target]) \n",
        "\n",
        "# def pad(x, border=4):\n",
        "#     return np.pad(x, [(0, 0), (border, border), (border, border)], mode='reflect')\n",
        "\n",
        "# class RandomPadandCrop(object):\n",
        "#     \"\"\"Crop randomly the image.\n",
        "#     Args:\n",
        "#         output_size (tuple or int): Desired output size. If int, square crop\n",
        "#             is made.\n",
        "#     \"\"\"\n",
        "\n",
        "#     def __init__(self, output_size):\n",
        "#         assert isinstance(output_size, (int, tuple))\n",
        "#         if isinstance(output_size, int):\n",
        "#             self.output_size = (output_size, output_size)\n",
        "#         else:\n",
        "#             assert len(output_size) == 2\n",
        "#             self.output_size = output_size\n",
        "\n",
        "#     def __call__(self, x):\n",
        "#         x = pad(x, 4)\n",
        "\n",
        "#         h, w = x.shape[1:]\n",
        "#         new_h, new_w = self.output_size\n",
        "\n",
        "#         top = np.random.randint(0, h - new_h)\n",
        "#         left = np.random.randint(0, w - new_w)\n",
        "\n",
        "#         x = x[:, top: top + new_h, left: left + new_w]\n",
        "\n",
        "#         return x\n",
        "\n",
        "# class RandomFlip(object):\n",
        "#     \"\"\"Flip randomly the image.\n",
        "#     \"\"\"\n",
        "#     def __call__(self, x):\n",
        "#         if np.random.rand() < 0.5:\n",
        "#             x = x[:, :, ::-1]\n",
        "\n",
        "#         return x.copy()\n",
        "\n",
        "# class GaussianNoise(object):\n",
        "#     \"\"\"Add gaussian noise to the image.\n",
        "#     \"\"\"\n",
        "#     def __call__(self, x):\n",
        "#         c, h, w = x.shape\n",
        "#         x += np.random.randn(c, h, w) * 0.15\n",
        "#         return x\n",
        "\n",
        "# class ToTensor(object):\n",
        "#     \"\"\"Transform the image to tensor.\n",
        "#     \"\"\"\n",
        "#     def __call__(self, x):\n",
        "#         x = torch.from_numpy(x)\n",
        "#         return x"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2a19u2L65mzg"
      },
      "source": [
        "# def get_cifar10(root, n_labeled,\n",
        "#                  transform_train=None, transform_val=None,\n",
        "#                  download=True):\n",
        "\n",
        "#     base_dataset = torchvision.datasets.CIFAR10(root, train=True, download=download)\n",
        "#     train_labeled_idxs, train_unlabeled_idxs, val_idxs = train_val_split(base_dataset.targets, int(n_labeled/10))\n",
        "\n",
        "#     train_labeled_dataset = CIFAR10_labeled(root, train_labeled_idxs, train=True, transform=transform_train)\n",
        "#     train_unlabeled_dataset = CIFAR10_unlabeled(root, train_unlabeled_idxs, train=True, transform=TransformTwice(transform_train))\n",
        "#     val_dataset = CIFAR10_labeled(root, val_idxs, train=True, transform=transform_val, download=True)\n",
        "#     test_dataset = CIFAR10_labeled(root, train=False, transform=transform_val, download=True)\n",
        "\n",
        "#     print (f\"#Labeled: {len(train_labeled_idxs)} #Unlabeled: {len(train_unlabeled_idxs)} #Val: {len(val_idxs)}\")\n",
        "#     return train_labeled_dataset, train_unlabeled_dataset, val_dataset, test_dataset"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0_Rf8CR66I3-"
      },
      "source": [
        "# %cd /content/gdrive/MyDrive/"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eVr5iu0e_85l"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DR6RurC76TkG"
      },
      "source": [
        "# %mkdir DLDS_Data"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aIwOu3qE_i3b"
      },
      "source": [
        "# X = datasets.CIFAR10(root='/content/gdrive/MyDrive/DLDS_Data', train=True, download=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XsShVQF86ZmV"
      },
      "source": [
        "# # n_labeled = 100\n",
        "# # train_labeled_dataset, train_unlabeled_dataset, val_dataset, test_dataset = get_cifar10(\"/DLDS_Data\", n_labeled)\n",
        "\n",
        "# data_dir = '/content/gdrive/MyDrive/DLDS_Data'\n",
        "# # image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
        "# #                                           data_transforms[x])\n",
        "# #                   for x in ['train', 'val']}\n",
        "# # dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,\n",
        "# #                                              shuffle=True, num_workers=4)\n",
        "# #               for x in ['train', 'val']}\n",
        "\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DhpTM2QdBQTu"
      },
      "source": [
        "# transform = transforms.Compose(\n",
        "#     [transforms.ToTensor(),\n",
        "#      transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])\n",
        "\n",
        "# batch_size = 4\n",
        "\n",
        "# trainset = torchvision.datasets.CIFAR10(root=data_dir , train=True,\n",
        "#                                         download=True, transform=transform)\n",
        "# trainloader = torch.utils.data.DataLoader(trainset, batch_size=batch_size,\n",
        "#                                           shuffle=True, num_workers=2)\n",
        "\n",
        "# testset = torchvision.datasets.CIFAR10(root=data_dir , train=False,\n",
        "#                                        download=True, transform=transform)\n",
        "# testloader = torch.utils.data.DataLoader(testset, batch_size=batch_size,\n",
        "#                                          shuffle=False, num_workers=2)\n",
        "\n",
        "# classes = ('plane', 'car', 'bird', 'cat',\n",
        "#            'deer', 'dog', 'frog', 'horse', 'ship', 'truck')\n",
        "\n",
        "# dataloaders = {\"train\": trainloader}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-gHRMa3UJytW"
      },
      "source": [
        "# trainloader"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uq95SB7GDE6z"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fq7eEuUF8U-U"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nuS7KiCv8bEE"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DmwPhC-M8cQ4"
      },
      "source": [
        "import tensorflow as tf\n",
        "tf.test.gpu_device_name()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-tBeB-FyHidw"
      },
      "source": [
        "torch.cuda.is_available()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2IQL5M-XHnl9"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}