Torchdreams_playground.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/meefs/art/blob/master/Torchdreams_playground.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "metadata": {
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      "source": [
        "**Install  torch-dreams**\n",
        "\n",
        "instructions from Nerdy Rodent - https://www.youtube.com/watch?v=gXfu2jUvHmQ"
      ]
    },
    {
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        "pip install"
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        "!pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html\n",
        "!pip install torch-dreams imageio imageio-ffmpeg matplotlib"
      ],
      "execution_count": 2,
      "outputs": [
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            "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
            "Collecting torch==1.8.1+cu111\n",
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            "\u001b[K     |█████████████▌                  | 834.1 MB 1.3 MB/s eta 0:14:18tcmalloc: large alloc 1147494400 bytes == 0x563a4b8d4000 @  0x7f3da5229615 0x563a126bb4cc 0x563a1279b47a 0x563a126be2ed 0x563a127afe1d 0x563a12731e99 0x563a1272c9ee 0x563a126bfbda 0x563a12731d00 0x563a1272c9ee 0x563a126bfbda 0x563a1272e737 0x563a127b0c66 0x563a1272ddaf 0x563a127b0c66 0x563a1272ddaf 0x563a127b0c66 0x563a1272ddaf 0x563a126c0039 0x563a12703409 0x563a126bec52 0x563a12731c25 0x563a1272c9ee 0x563a126bfbda 0x563a1272e737 0x563a1272c9ee 0x563a126bfbda 0x563a1272d915 0x563a126bfafa 0x563a1272dc0d 0x563a1272c9ee\n",
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            "\u001b[K     |████████████████████████████████| 1982.2 MB 1.1 MB/s eta 0:00:01tcmalloc: large alloc 1982177280 bytes == 0x563b054a6000 @  0x7f3da52281e7 0x563a126f1067 0x563a126bb4cc 0x563a1279b47a 0x563a126be2ed 0x563a127afe1d 0x563a12731e99 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a126bfafa 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272e737 0x563a1272c9ee 0x563a126bfbda 0x563a1272e737 0x563a1272c9ee\n",
            "tcmalloc: large alloc 2477727744 bytes == 0x563b7b700000 @  0x7f3da5229615 0x563a126bb4cc 0x563a1279b47a 0x563a126be2ed 0x563a127afe1d 0x563a12731e99 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272dc0d 0x563a126bfafa 0x563a1272dc0d 0x563a1272c9ee 0x563a126bfbda 0x563a1272e737 0x563a1272c9ee 0x563a126bfbda 0x563a1272e737 0x563a1272c9ee 0x563a126c0271\n",
            "\u001b[K     |████████████████████████████████| 1982.2 MB 2.3 kB/s \n",
            "\u001b[?25hCollecting torchvision==0.9.1+cu111\n",
            "  Downloading https://download.pytorch.org/whl/cu111/torchvision-0.9.1%2Bcu111-cp37-cp37m-linux_x86_64.whl (17.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 17.6 MB 1.2 MB/s \n",
            "\u001b[?25hCollecting torchaudio==0.8.1\n",
            "  Downloading torchaudio-0.8.1-cp37-cp37m-manylinux1_x86_64.whl (1.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.9 MB 8.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torch==1.8.1+cu111) (1.19.5)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.8.1+cu111) (3.7.4.3)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision==0.9.1+cu111) (7.1.2)\n",
            "Installing collected packages: torch, torchvision, torchaudio\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 1.9.0+cu111\n",
            "    Uninstalling torch-1.9.0+cu111:\n",
            "      Successfully uninstalled torch-1.9.0+cu111\n",
            "  Attempting uninstall: torchvision\n",
            "    Found existing installation: torchvision 0.10.0+cu111\n",
            "    Uninstalling torchvision-0.10.0+cu111:\n",
            "      Successfully uninstalled torchvision-0.10.0+cu111\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchtext 0.10.0 requires torch==1.9.0, but you have torch 1.8.1+cu111 which is incompatible.\u001b[0m\n",
            "Successfully installed torch-1.8.1+cu111 torchaudio-0.8.1 torchvision-0.9.1+cu111\n",
            "Collecting torch-dreams\n",
            "  Downloading torch_dreams-2.3.1-py3-none-any.whl (21 kB)\n",
            "Requirement already satisfied: imageio in /usr/local/lib/python3.7/dist-packages (2.4.1)\n",
            "Collecting imageio-ffmpeg\n",
            "  Downloading imageio_ffmpeg-0.4.5-py3-none-manylinux2010_x86_64.whl (26.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 26.9 MB 1.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (3.2.2)\n",
            "Requirement already satisfied: torch>=1.8.0 in /usr/local/lib/python3.7/dist-packages (from torch-dreams) (1.8.1+cu111)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from torch-dreams) (4.62.3)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torch-dreams) (1.19.5)\n",
            "Requirement already satisfied: mkl in /usr/local/lib/python3.7/dist-packages (from torch-dreams) (2019.0)\n",
            "Requirement already satisfied: torchvision>=0.8.1 in /usr/local/lib/python3.7/dist-packages (from torch-dreams) (0.9.1+cu111)\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (from torch-dreams) (4.1.2.30)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.8.0->torch-dreams) (3.7.4.3)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision>=0.8.1->torch-dreams) (7.1.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib) (0.10.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib) (2.4.7)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib) (1.3.2)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib) (2.8.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from cycler>=0.10->matplotlib) (1.15.0)\n",
            "Requirement already satisfied: intel-openmp in /usr/local/lib/python3.7/dist-packages (from mkl->torch-dreams) (2021.4.0)\n",
            "Installing collected packages: torch-dreams, imageio-ffmpeg\n",
            "Successfully installed imageio-ffmpeg-0.4.5 torch-dreams-2.3.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "96M-wMV0uiLW"
      },
      "source": [
        "Create a directory to save scripts & images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZGADaH43ro-5"
      },
      "source": [
        "!mkdir torch-dreams ## create /content/torch-dreams\n",
        "\n",
        "!cd torch-dreams\n",
        "\n",
        "!pwd ##print the current working directory"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L5OFsqQPxtQ5"
      },
      "source": [
        "Some examples...\n",
        " "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "6b0c48e442bc4f1582fef8243072423e",
            "431fe7e7a3ce4cdf8f5c0e59a80cf4f1",
            "437918522fd448bb80ee98eb61181fe0",
            "28b0c41b3a53468aadf4c1dde632f06e",
            "c9fbe492bb964342a2f600336ae7f2de",
            "30fac98747da4aaa9cba2488f0afeb1b",
            "e07ce8d625c646e491ca3aadc80d56c5",
            "38bd65bb72ba4074b060f50a206eda1e",
            "988b5dab79a04248b31e48ce7109bb6b",
            "7d42493f832a40d89ae2220afe8176b2",
            "433cfd1315634d0e8d8710bcb881738b"
          ]
        },
        "id": "4a6rK7H_xsqN",
        "outputId": "b59fb457-04aa-42ec-faf3-b658cb70861b"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import torchvision.models as models\n",
        "from torch_dreams.dreamer import dreamer\n",
        "\n",
        "model = models.inception_v3(pretrained=True)\n",
        "dreamy_boi = dreamer(model, device = 'cuda')\n",
        "\n",
        "# Print the model\n",
        "print(model)\n",
        "\n",
        "image_param = dreamy_boi.render(\n",
        "    layers = [model.Mixed_5c],\n",
        ")\n",
        "\n",
        "plt.imshow(image_param)\n",
        "plt.show()\n"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading: \"https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth\" to /root/.cache/torch/hub/checkpoints/inception_v3_google-1a9a5a14.pth\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "6b0c48e442bc4f1582fef8243072423e",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0.00/104M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Inception3(\n",
            "  (Conv2d_1a_3x3): BasicConv2d(\n",
            "    (conv): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
            "    (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  )\n",
            "  (Conv2d_2a_3x3): BasicConv2d(\n",
            "    (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), bias=False)\n",
            "    (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  )\n",
            "  (Conv2d_2b_3x3): BasicConv2d(\n",
            "    (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "    (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  )\n",
            "  (maxpool1): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (Conv2d_3b_1x1): BasicConv2d(\n",
            "    (conv): Conv2d(64, 80, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "    (bn): BatchNorm2d(80, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  )\n",
            "  (Conv2d_4a_3x3): BasicConv2d(\n",
            "    (conv): Conv2d(80, 192, kernel_size=(3, 3), stride=(1, 1), bias=False)\n",
            "    (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  )\n",
            "  (maxpool2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (Mixed_5b): InceptionA(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch5x5_1): BasicConv2d(\n",
            "      (conv): Conv2d(192, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch5x5_2): BasicConv2d(\n",
            "      (conv): Conv2d(48, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(192, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_5c): InceptionA(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch5x5_1): BasicConv2d(\n",
            "      (conv): Conv2d(256, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch5x5_2): BasicConv2d(\n",
            "      (conv): Conv2d(48, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_5d): InceptionA(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch5x5_1): BasicConv2d(\n",
            "      (conv): Conv2d(288, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch5x5_2): BasicConv2d(\n",
            "      (conv): Conv2d(48, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_6a): InceptionB(\n",
            "    (branch3x3): BasicConv2d(\n",
            "      (conv): Conv2d(288, 384, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_6b): InceptionC(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_2): BasicConv2d(\n",
            "      (conv): Conv2d(128, 128, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_3): BasicConv2d(\n",
            "      (conv): Conv2d(128, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(128, 128, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(128, 128, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_4): BasicConv2d(\n",
            "      (conv): Conv2d(128, 128, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_5): BasicConv2d(\n",
            "      (conv): Conv2d(128, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_6c): InceptionC(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_2): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_3): BasicConv2d(\n",
            "      (conv): Conv2d(160, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_4): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_5): BasicConv2d(\n",
            "      (conv): Conv2d(160, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_6d): InceptionC(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_2): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_3): BasicConv2d(\n",
            "      (conv): Conv2d(160, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_4): BasicConv2d(\n",
            "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_5): BasicConv2d(\n",
            "      (conv): Conv2d(160, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_6e): InceptionC(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_2): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7_3): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_3): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_4): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7dbl_5): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (AuxLogits): InceptionAux(\n",
            "    (conv0): BasicConv2d(\n",
            "      (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (conv1): BasicConv2d(\n",
            "      (conv): Conv2d(128, 768, kernel_size=(5, 5), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(768, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (fc): Linear(in_features=768, out_features=1000, bias=True)\n",
            "  )\n",
            "  (Mixed_7a): InceptionD(\n",
            "    (branch3x3_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_2): BasicConv2d(\n",
            "      (conv): Conv2d(192, 320, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7x3_1): BasicConv2d(\n",
            "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7x3_2): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7x3_3): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch7x7x3_4): BasicConv2d(\n",
            "      (conv): Conv2d(192, 192, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_7b): InceptionE(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(1280, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_1): BasicConv2d(\n",
            "      (conv): Conv2d(1280, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_2a): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_2b): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(1280, 448, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(448, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3a): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3b): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(1280, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (Mixed_7c): InceptionE(\n",
            "    (branch1x1): BasicConv2d(\n",
            "      (conv): Conv2d(2048, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_1): BasicConv2d(\n",
            "      (conv): Conv2d(2048, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_2a): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3_2b): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_1): BasicConv2d(\n",
            "      (conv): Conv2d(2048, 448, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_2): BasicConv2d(\n",
            "      (conv): Conv2d(448, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3a): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch3x3dbl_3b): BasicConv2d(\n",
            "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
            "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "    (branch_pool): BasicConv2d(\n",
            "      (conv): Conv2d(2048, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
            "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
            "    )\n",
            "  )\n",
            "  (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n",
            "  (dropout): Dropout(p=0.5, inplace=False)\n",
            "  (fc): Linear(in_features=2048, out_features=1000, bias=True)\n",
            ")\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 120/120 [00:04<00:00, 28.66it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x-OBxJN-0Opf"
      },
      "source": [
        "Not so minimal example...\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s55iu49l0Rbd"
      },
      "source": [
        "model = models.inception_v3(pretrained=True)\n",
        "dreamy_boi = dreamer(model, device = 'cuda', quiet = False)\n",
        "\n",
        "image_param = dreamy_boi.render(\n",
        "    layers = [model.Mixed_5b],\n",
        "    width = 256,\n",
        "    height = 256,\n",
        "    iters = 150,\n",
        "    lr = 9e-3,\n",
        "    rotate_degrees = 15,\n",
        "    scale_max = 1.2,\n",
        "    scale_min =  0.5,\n",
        "    translate_x = 0.2,\n",
        "    translate_y = 0.2,\n",
        "    custom_func = None,\n",
        "    weight_decay = 1e-2,\n",
        "    grad_clip = 1.,\n",
        ")\n",
        "\n",
        "plt.imshow(image_param)\n",
        "plt.show()\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZZL6Jy7p0rP3"
      },
      "source": [
        "Visualizing individual channels"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "VtsTorJl0uiY",
        "outputId": "e67f6efa-c32c-4a4b-a8f4-b11e6375d6e6"
      },
      "source": [
        "model = models.inception_v3(pretrained=True)\n",
        "dreamy_boi = dreamer(model, device = 'cuda')\n",
        "\n",
        "layers_to_use = [model.Mixed_6b.branch1x1.conv]\n",
        "\n",
        "def make_custom_func(layer_number = 0, channel_number= 0): \n",
        "    def custom_func(layer_outputs):\n",
        "        loss = layer_outputs[layer_number][channel_number].mean()\n",
        "        return -loss\n",
        "    return custom_func\n",
        "\n",
        "my_custom_func = make_custom_func(layer_number= 0, channel_number = 119)\n",
        "\n",
        "image_param = dreamy_boi.render(\n",
        "    layers = layers_to_use,\n",
        "    custom_func = my_custom_func,\n",
        ")\n",
        "plt.imshow(image_param)\n",
        "plt.show()\n"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 120/120 [00:03<00:00, 34.41it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U6cjOmPE5CbS"
      },
      "source": [
        "**Caricatures**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "id": "Qum50y0N5HP8",
        "outputId": "0200bac0-f4a9-4ce2-e0bb-a93c8dc0d82f"
      },
      "source": [
        "model = models.googlenet(pretrained = True)\n",
        "dreamy_boi = dreamer(model = model, quiet= False, device= 'cuda')\n",
        "\n",
        "image_param = dreamy_boi.caricature(\n",
        "    input_tensor = image_tensor, \n",
        "    layers = [model.inception4c],   ## feel free to append more layers for more interesting caricatures \n",
        "    power= 1.2,                     ## higher -> more \"exaggerated\" features\n",
        ")\n",
        "\n",
        "plt.imshow(image_param)\n",
        "plt.show()\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-7cbf7b65288a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgooglenet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpretrained\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mdreamy_boi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdreamer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mquiet\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;34m'cuda'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m image_param = dreamy_boi.caricature(\n\u001b[1;32m      5\u001b[0m     \u001b[0minput_tensor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimage_tensor\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'models' is not defined"
          ]
        }
      ]
    }
  ]
}