{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yWDWIilQYyjO",
        "outputId": "a7089fac-eda7-4620-fffb-e15612144972"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: kaggle in /usr/local/lib/python3.11/dist-packages (1.7.4.5)\n",
            "Requirement already satisfied: bleach in /usr/local/lib/python3.11/dist-packages (from kaggle) (6.2.0)\n",
            "Requirement already satisfied: certifi>=14.05.14 in /usr/local/lib/python3.11/dist-packages (from kaggle) (2025.4.26)\n",
            "Requirement already satisfied: charset-normalizer in /usr/local/lib/python3.11/dist-packages (from kaggle) (3.4.2)\n",
            "Requirement already satisfied: idna in /usr/local/lib/python3.11/dist-packages (from kaggle) (3.10)\n",
            "Requirement already satisfied: protobuf in /usr/local/lib/python3.11/dist-packages (from kaggle) (5.29.4)\n",
            "Requirement already satisfied: python-dateutil>=2.5.3 in /usr/local/lib/python3.11/dist-packages (from kaggle) (2.9.0.post0)\n",
            "Requirement already satisfied: python-slugify in /usr/local/lib/python3.11/dist-packages (from kaggle) (8.0.4)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from kaggle) (2.32.3)\n",
            "Requirement already satisfied: setuptools>=21.0.0 in /usr/local/lib/python3.11/dist-packages (from kaggle) (75.2.0)\n",
            "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.11/dist-packages (from kaggle) (1.17.0)\n",
            "Requirement already satisfied: text-unidecode in /usr/local/lib/python3.11/dist-packages (from kaggle) (1.3)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from kaggle) (4.67.1)\n",
            "Requirement already satisfied: urllib3>=1.15.1 in /usr/local/lib/python3.11/dist-packages (from kaggle) (2.4.0)\n",
            "Requirement already satisfied: webencodings in /usr/local/lib/python3.11/dist-packages (from kaggle) (0.5.1)\n"
          ]
        }
      ],
      "source": [
        "!pip install kaggle"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JFhEGzBpcf1A",
        "outputId": "24c19e3b-00fc-43a7-d5fa-143278b01a44"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!mkdir -p ~/.kaggle\n",
        "!cp kaggle.json ~/.kaggle/\n",
        "!chmod 600 ~/.kaggle/kaggle.json\n",
        "#confguring the kaggle.json path"
      ],
      "metadata": {
        "id": "mVF9xpgLZXlE"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#downloading dataset through api\n",
        "!kaggle competitions download -c cifar-10"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XGiMW13XaeFE",
        "outputId": "8d667609-4082-465e-9a17-6370b2104a0d"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading cifar-10.zip to /content\n",
            " 94% 669M/715M [00:07<00:00, 70.1MB/s]\n",
            "100% 715M/715M [00:07<00:00, 98.3MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "30HfMliQakkZ",
        "outputId": "29e7f72e-09d5-41d0-bc5b-f46d65b71f3c"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cifar-10.zip  drive  kaggle.json  sample_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#we need to extract the compressed file using zipfile library\n",
        "from zipfile import ZipFile\n",
        "dataset = '/content/cifar-10.zip'\n",
        "\n",
        "with ZipFile(dataset,'r') as zip:\n",
        "  zip.extractall()\n",
        "  print('The dataset is extracted')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qxsIc_Rha5-I",
        "outputId": "c02ed73f-a871-4839-8e7b-4ec3bda43d29"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The dataset is extracted\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "msDaGVpKa-8P",
        "outputId": "e0c2763e-f4c9-4274-d552-70d66627bc35"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cifar-10.zip  kaggle.json  sampleSubmission.csv  train.7z\n",
            "drive\t      sample_data  test.7z\t\t trainLabels.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install py7zr\n",
        "#to extract 7z files"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FwetScrMbd-i",
        "outputId": "c525fb35-644a-4d7b-8d88-730ad51fe9da"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting py7zr\n",
            "  Downloading py7zr-1.0.0-py3-none-any.whl.metadata (17 kB)\n",
            "Collecting texttable (from py7zr)\n",
            "  Downloading texttable-1.7.0-py2.py3-none-any.whl.metadata (9.8 kB)\n",
            "Requirement already satisfied: pycryptodomex>=3.20.0 in /usr/local/lib/python3.11/dist-packages (from py7zr) (3.23.0)\n",
            "Collecting brotli>=1.1.0 (from py7zr)\n",
            "  Downloading Brotli-1.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.5 kB)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from py7zr) (5.9.5)\n",
            "Collecting pyzstd>=0.16.1 (from py7zr)\n",
            "  Downloading pyzstd-0.17.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.5 kB)\n",
            "Collecting pyppmd<1.3.0,>=1.1.0 (from py7zr)\n",
            "  Downloading pyppmd-1.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.4 kB)\n",
            "Collecting pybcj<1.1.0,>=1.0.0 (from py7zr)\n",
            "  Downloading pybcj-1.0.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.7 kB)\n",
            "Collecting multivolumefile>=0.2.3 (from py7zr)\n",
            "  Downloading multivolumefile-0.2.3-py3-none-any.whl.metadata (6.3 kB)\n",
            "Collecting inflate64<1.1.0,>=1.0.0 (from py7zr)\n",
            "  Downloading inflate64-1.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.4 kB)\n",
            "Requirement already satisfied: typing-extensions>=4.13.2 in /usr/local/lib/python3.11/dist-packages (from pyzstd>=0.16.1->py7zr) (4.13.2)\n",
            "Downloading py7zr-1.0.0-py3-none-any.whl (69 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.7/69.7 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading Brotli-1.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB)\n",
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            "\u001b[?25hDownloading inflate64-1.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (96 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m96.4/96.4 kB\u001b[0m \u001b[31m9.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading multivolumefile-0.2.3-py3-none-any.whl (17 kB)\n",
            "Downloading pybcj-1.0.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (50 kB)\n",
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            "\u001b[?25hDownloading pyppmd-1.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (141 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m141.3/141.3 kB\u001b[0m \u001b[31m15.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyzstd-0.17.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (412 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m412.9/412.9 kB\u001b[0m \u001b[31m37.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading texttable-1.7.0-py2.py3-none-any.whl (10 kB)\n",
            "Installing collected packages: texttable, brotli, pyzstd, pyppmd, pybcj, multivolumefile, inflate64, py7zr\n",
            "Successfully installed brotli-1.1.0 inflate64-1.0.3 multivolumefile-0.2.3 py7zr-1.0.0 pybcj-1.0.6 pyppmd-1.2.0 pyzstd-0.17.0 texttable-1.7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import py7zr\n",
        "\n",
        "archive=py7zr.SevenZipFile('/content/train.7z','r')\n",
        "archive.extractall()\n",
        "print('The dataset is extracted')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UrCcZ37qbr7R",
        "outputId": "30b8ce99-8d0f-499f-c803-3529a9243ee6"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The dataset is extracted\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ujyekwaFb-RL",
        "outputId": "252bad97-51ec-4362-d181-1cc715a4791f"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cifar-10.zip  kaggle.json  sampleSubmission.csv  train\t   trainLabels.csv\n",
            "drive\t      sample_data  test.7z\t\t train.7z\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from PIL import Image\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.image as mpimg\n",
        "from sklearn.model_selection import train_test_split"
      ],
      "metadata": {
        "id": "KNlxbj0gcGHz"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "filename=os.listdir('/content/train')\n",
        "#to explore the file train"
      ],
      "metadata": {
        "id": "CNtNTWrec7o1"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "type(filename)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jcr0a2d0hwC4",
        "outputId": "67106657-9c32-466c-e9f7-83e73232d8d8"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(filename)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xZLJkBRohzIC",
        "outputId": "acc910ab-51e2-4cd5-d97d-206b7aad1f39"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "50000"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#test has 10000 train jas 50000 data"
      ],
      "metadata": {
        "id": "hUCEJbLNh3Q1"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(filename[:5])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cMNwFBJIiDWM",
        "outputId": "11944044-6f46-4277-a898-a87cc2ef9358"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['45155.png', '15916.png', '48284.png', '7697.png', '6308.png']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Labels processing"
      ],
      "metadata": {
        "id": "-0x0Z2J-iSt9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "labels=pd.read_csv('/content/trainLabels.csv')"
      ],
      "metadata": {
        "id": "fiydq2F4iVqf"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(labels)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c0y4OWZ8ibuI",
        "outputId": "9579f5f6-ca81-4418-90fa-657a85aed934"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "          id       label\n",
            "0          1        frog\n",
            "1          2       truck\n",
            "2          3       truck\n",
            "3          4        deer\n",
            "4          5  automobile\n",
            "...      ...         ...\n",
            "49995  49996        bird\n",
            "49996  49997        frog\n",
            "49997  49998       truck\n",
            "49998  49999  automobile\n",
            "49999  50000  automobile\n",
            "\n",
            "[50000 rows x 2 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FMHtRa1YiePt",
        "outputId": "d87502fa-15a2-4eb5-81c1-65784a1ab150"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50000, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df=labels"
      ],
      "metadata": {
        "id": "oovJqMjKipoK"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['id']==45155]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "KROKKESOi9du",
        "outputId": "6272c25b-d073-4817-c0ba-d74c758d683c"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          id  label\n",
              "45154  45155  truck"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-deb50734-bc63-43f1-9f47-e602e4d9e703\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>45154</th>\n",
              "      <td>45155</td>\n",
              "      <td>truck</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-deb50734-bc63-43f1-9f47-e602e4d9e703')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-deb50734-bc63-43f1-9f47-e602e4d9e703 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-deb50734-bc63-43f1-9f47-e602e4d9e703');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[df['id']==45155]\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 45155,\n        \"max\": 45155,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          45155\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"truck\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['label'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "qBh6N5ubjayT",
        "outputId": "a20aa9ff-7fdd-4ceb-bac3-66450d971ed5"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "label\n",
              "frog          5000\n",
              "truck         5000\n",
              "deer          5000\n",
              "automobile    5000\n",
              "bird          5000\n",
              "horse         5000\n",
              "ship          5000\n",
              "cat           5000\n",
              "dog           5000\n",
              "airplane      5000\n",
              "Name: count, dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>label</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>frog</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>truck</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>deer</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>automobile</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bird</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>horse</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ship</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cat</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dog</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>airplane</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels_dict={'frog':0,'truck':1,'deer':2,'automobile':3,'bird':4,'horse':5,'ship':6,'cat':7,'dog':8,'airplane':9}"
      ],
      "metadata": {
        "id": "8NLQPIpzkOmo"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "labels=[labels_dict[i] for i in df['label']]"
      ],
      "metadata": {
        "id": "lLSZo6uQktFh"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "labels[0:5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C4vDfkFclQ7F",
        "outputId": "aa8f0cad-6c6e-49b9-c9f0-c0274b14db2d"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0, 1, 1, 2, 3]"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#handling images\n",
        "import cv2\n",
        "from google.colab.patches import cv2_imshow\n",
        "img=cv2.imread('/content/train/7796.png')  #to numpy"
      ],
      "metadata": {
        "id": "m1xHDAcDlWIT"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cv2_imshow(img)  # converts numpy to image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49
        },
        "id": "QSez-vHPm-wR",
        "outputId": "1409b62b-6e7c-47cf-e6fe-fa7914b7c14c"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=32x32>"
            ],
            "image/png": "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\n",
            "image/jpeg": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['id']==7796]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "RPNrF8ihnRId",
        "outputId": "6c97f1be-9365-4dc2-9902-3f1cadb26b21"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id label\n",
              "7795  7796  frog"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-67287dfb-bbf5-40e1-bc72-f5788a91341e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7795</th>\n",
              "      <td>7796</td>\n",
              "      <td>frog</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-67287dfb-bbf5-40e1-bc72-f5788a91341e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-67287dfb-bbf5-40e1-bc72-f5788a91341e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-67287dfb-bbf5-40e1-bc72-f5788a91341e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[df['id']==7796]\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 7796,\n        \"max\": 7796,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7796\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"frog\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "id_ls=list(df['id'])"
      ],
      "metadata": {
        "id": "MwwP0Lornoga"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Image Processing"
      ],
      "metadata": {
        "id": "W3zm4tsAoFuF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train_data_folder='/content/train/' #adding forward slashes to access images in it"
      ],
      "metadata": {
        "id": "hN98skuFoKWB"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data=[]\n",
        "\n",
        "for id in id_ls:\n",
        "\n",
        "  image=Image.open(train_data_folder+str(id)+'.png')  #read using pillow\n",
        "  image=np.array(image)  #converting to numpy array\n",
        "  data.append(image)"
      ],
      "metadata": {
        "id": "xQvKfiyPonDy"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hew3DGcqpwJU",
        "outputId": "6588e379-a75e-4760-e4ea-1e2f1ed2c798"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "50000"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(data[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qNvWP6ahrn1E",
        "outputId": "ee747cfd-26c2-47a4-84ae-974412791a2a"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data[0].shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VyBfvYHnrrLR",
        "outputId": "aa508f48-cfee-411f-ef26-06457146d5cd"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(32, 32, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#32- height 32- width 3-color channel\n",
        "#grey scale image HxW, rgb(color) scale image HxWxn\n",
        "#n- red,green,blue  so it uses 3 32x32 matrices"
      ],
      "metadata": {
        "id": "dtL7Ww0vr2CR"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "zjP-upA7sWIy",
        "outputId": "a7b94c84-0aac-45f3-b900-427bb08837a0"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[ 59,  62,  63],\n",
              "        [ 43,  46,  45],\n",
              "        [ 50,  48,  43],\n",
              "        ...,\n",
              "        [158, 132, 108],\n",
              "        [152, 125, 102],\n",
              "        [148, 124, 103]],\n",
              "\n",
              "       [[ 16,  20,  20],\n",
              "        [  0,   0,   0],\n",
              "        [ 18,   8,   0],\n",
              "        ...,\n",
              "        [123,  88,  55],\n",
              "        [119,  83,  50],\n",
              "        [122,  87,  57]],\n",
              "\n",
              "       [[ 25,  24,  21],\n",
              "        [ 16,   7,   0],\n",
              "        [ 49,  27,   8],\n",
              "        ...,\n",
              "        [118,  84,  50],\n",
              "        [120,  84,  50],\n",
              "        [109,  73,  42]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[208, 170,  96],\n",
              "        [201, 153,  34],\n",
              "        [198, 161,  26],\n",
              "        ...,\n",
              "        [160, 133,  70],\n",
              "        [ 56,  31,   7],\n",
              "        [ 53,  34,  20]],\n",
              "\n",
              "       [[180, 139,  96],\n",
              "        [173, 123,  42],\n",
              "        [186, 144,  30],\n",
              "        ...,\n",
              "        [184, 148,  94],\n",
              "        [ 97,  62,  34],\n",
              "        [ 83,  53,  34]],\n",
              "\n",
              "       [[177, 144, 116],\n",
              "        [168, 129,  94],\n",
              "        [179, 142,  87],\n",
              "        ...,\n",
              "        [216, 184, 140],\n",
              "        [151, 118,  84],\n",
              "        [123,  92,  72]]], dtype=uint8)"
            ],
            "text/html": [
              "<style>\n",
              "      .ndarray_repr .ndarray_raw_data {\n",
              "        display: none;\n",
              "      }\n",
              "      .ndarray_repr.show_array .ndarray_raw_data {\n",
              "        display: block;\n",
              "      }\n",
              "      .ndarray_repr.show_array .ndarray_image_preview {\n",
              "        display: none;\n",
              "      }\n",
              "      </style>\n",
              "      <div id=\"id-06a08a7e-24e6-4621-a1ec-8a41edf7319e\" class=\"ndarray_repr\"><pre>ndarray (32, 32, 3) <button style=\"padding: 0 2px;\">show data</button></pre><img src=\"data:image/png;base64,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\" class=\"ndarray_image_preview\" /><pre class=\"ndarray_raw_data\">array([[[ 59,  62,  63],\n",
              "        [ 43,  46,  45],\n",
              "        [ 50,  48,  43],\n",
              "        ...,\n",
              "        [158, 132, 108],\n",
              "        [152, 125, 102],\n",
              "        [148, 124, 103]],\n",
              "\n",
              "       [[ 16,  20,  20],\n",
              "        [  0,   0,   0],\n",
              "        [ 18,   8,   0],\n",
              "        ...,\n",
              "        [123,  88,  55],\n",
              "        [119,  83,  50],\n",
              "        [122,  87,  57]],\n",
              "\n",
              "       [[ 25,  24,  21],\n",
              "        [ 16,   7,   0],\n",
              "        [ 49,  27,   8],\n",
              "        ...,\n",
              "        [118,  84,  50],\n",
              "        [120,  84,  50],\n",
              "        [109,  73,  42]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[208, 170,  96],\n",
              "        [201, 153,  34],\n",
              "        [198, 161,  26],\n",
              "        ...,\n",
              "        [160, 133,  70],\n",
              "        [ 56,  31,   7],\n",
              "        [ 53,  34,  20]],\n",
              "\n",
              "       [[180, 139,  96],\n",
              "        [173, 123,  42],\n",
              "        [186, 144,  30],\n",
              "        ...,\n",
              "        [184, 148,  94],\n",
              "        [ 97,  62,  34],\n",
              "        [ 83,  53,  34]],\n",
              "\n",
              "       [[177, 144, 116],\n",
              "        [168, 129,  94],\n",
              "        [179, 142,  87],\n",
              "        ...,\n",
              "        [216, 184, 140],\n",
              "        [151, 118,  84],\n",
              "        [123,  92,  72]]], dtype=uint8)</pre></div><script>\n",
              "      (() => {\n",
              "      const titles = ['show data', 'hide data'];\n",
              "      let index = 0\n",
              "      document.querySelector('#id-06a08a7e-24e6-4621-a1ec-8a41edf7319e button').onclick = (e) => {\n",
              "        document.querySelector('#id-06a08a7e-24e6-4621-a1ec-8a41edf7319e').classList.toggle('show_array');\n",
              "        index = (++index) % 2;\n",
              "        document.querySelector('#id-06a08a7e-24e6-4621-a1ec-8a41edf7319e button').textContent = titles[index];\n",
              "        e.preventDefault();\n",
              "        e.stopPropagation();\n",
              "      }\n",
              "      })();\n",
              "    </script>"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#0 in all 3- black    255 in all 3-white\n",
        "#we also need to ensure all images are of same shape if not resize it"
      ],
      "metadata": {
        "id": "iSdLOFQwsX2a"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#convert images(list) and labels(list) to numpy arrays\n",
        "\n",
        "X=np.array(data)\n",
        "Y=np.array(labels)\n",
        "print(type(X))\n",
        "print(type(Y))\n",
        "print(X.shape)\n",
        "print(Y.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pFmsdNTosoGI",
        "outputId": "002df5d6-72e0-46ad-b6a3-d96693d7705e"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'numpy.ndarray'>\n",
            "<class 'numpy.ndarray'>\n",
            "(50000, 32, 32, 3)\n",
            "(50000,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Train and Test Split"
      ],
      "metadata": {
        "id": "rFfyfHittega"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x_train,x_test,y_train,y_test=train_test_split(X,Y,test_size=0.2,random_state=2)"
      ],
      "metadata": {
        "id": "2CoeM1pstn8S"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(x_train.shape)\n",
        "print(x_test.shape)\n",
        "print(y_train.shape)\n",
        "print(y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g12RPgg4twCO",
        "outputId": "c1cbcc03-5521-43d3-a133-6e14c69f03d2"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(40000, 32, 32, 3)\n",
            "(10000, 32, 32, 3)\n",
            "(40000,)\n",
            "(10000,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#converting array from 0 to 255 ---> 0 to 1\n",
        "#we are going to do scaling down the pixel value(helps in increasing the performance of neural network)"
      ],
      "metadata": {
        "id": "2eYf8MAVukwl"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#scaling down\n",
        "#normalization\n",
        "x_train_scaled=x_train/255\n",
        "x_test_scaled=x_test/255"
      ],
      "metadata": {
        "id": "eTF6mK7bu7Nf"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train_scaled[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0DO3wu76vNHU",
        "outputId": "dca9b2d8-faee-4488-cdf0-58cbab5a55c6"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[0.81960784, 0.82352941, 0.79607843],\n",
              "        [0.83529412, 0.83921569, 0.81960784],\n",
              "        [0.85490196, 0.85882353, 0.84313725],\n",
              "        ...,\n",
              "        [0.49803922, 0.29019608, 0.15294118],\n",
              "        [0.47843137, 0.26666667, 0.1372549 ],\n",
              "        [0.45490196, 0.24705882, 0.1254902 ]],\n",
              "\n",
              "       [[0.82352941, 0.82352941, 0.79215686],\n",
              "        [0.83529412, 0.83921569, 0.81176471],\n",
              "        [0.85490196, 0.8627451 , 0.83921569],\n",
              "        ...,\n",
              "        [0.48627451, 0.2745098 , 0.1372549 ],\n",
              "        [0.4745098 , 0.2627451 , 0.12941176],\n",
              "        [0.48235294, 0.27058824, 0.14117647]],\n",
              "\n",
              "       [[0.80784314, 0.80392157, 0.76470588],\n",
              "        [0.81960784, 0.81960784, 0.79215686],\n",
              "        [0.83529412, 0.84313725, 0.81960784],\n",
              "        ...,\n",
              "        [0.48627451, 0.2745098 , 0.14509804],\n",
              "        [0.51372549, 0.30196078, 0.16470588],\n",
              "        [0.51372549, 0.30588235, 0.16078431]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[0.49803922, 0.42352941, 0.38039216],\n",
              "        [0.54117647, 0.47843137, 0.43137255],\n",
              "        [0.55294118, 0.49803922, 0.4627451 ],\n",
              "        ...,\n",
              "        [0.61960784, 0.58431373, 0.5254902 ],\n",
              "        [0.63137255, 0.61176471, 0.59215686],\n",
              "        [0.53333333, 0.5372549 , 0.58039216]],\n",
              "\n",
              "       [[0.56862745, 0.50980392, 0.46666667],\n",
              "        [0.58039216, 0.52941176, 0.50196078],\n",
              "        [0.53333333, 0.49803922, 0.50196078],\n",
              "        ...,\n",
              "        [0.68627451, 0.68235294, 0.6745098 ],\n",
              "        [0.62745098, 0.63137255, 0.66666667],\n",
              "        [0.56078431, 0.58039216, 0.64313725]],\n",
              "\n",
              "       [[0.54117647, 0.50196078, 0.48235294],\n",
              "        [0.54901961, 0.51764706, 0.53333333],\n",
              "        [0.53333333, 0.51372549, 0.54901961],\n",
              "        ...,\n",
              "        [0.58823529, 0.60392157, 0.6627451 ],\n",
              "        [0.56862745, 0.58431373, 0.65098039],\n",
              "        [0.54901961, 0.56862745, 0.63921569]]])"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Neural Network Building**"
      ],
      "metadata": {
        "id": "4uh_hOfBvl1C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow import keras"
      ],
      "metadata": {
        "id": "RBFOYTItvw6L"
      },
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "n=10\n",
        "# no.of classes\n",
        "# input --> hidden --> output\n",
        "\n",
        "model=keras.Sequential([\n",
        "    keras.layers.Flatten(input_shape=(32,32,3)), #converted to 1d vector\n",
        "    keras.layers.Dense(128,activation='relu'),    #hidden layer with 128(2^7) neurons\n",
        "    keras.layers.Dense(64,activation='relu'),    #hidden layer with 64(2^6) neurons\n",
        "    keras.layers.Dense(n,activation='softmax'),  #as we are having more than 2 classes\n",
        "])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7N4Frwciwf07",
        "outputId": "652a6cc9-4b4e-4161-aa42-a318f30853d9"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/keras/src/layers/reshaping/flatten.py:37: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
            "  super().__init__(**kwargs)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(optimizer='adam',\n",
        "              loss='sparse_categorical_crossentropy',\n",
        "              metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "tm_CDpGTyAm8"
      },
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#training neural network\n",
        "model.fit(x_train_scaled,y_train,validation_split=0.1,epochs=10)\n",
        "#in each epochs(forward and backward) it tries to update the weight"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vIPPXRKkycLG",
        "outputId": "b1cb64f4-4482-4154-f58c-65c8dc89f165"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 3ms/step - accuracy: 0.2570 - loss: 2.0316 - val_accuracy: 0.3750 - val_loss: 1.7393\n",
            "Epoch 2/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 3ms/step - accuracy: 0.3684 - loss: 1.7624 - val_accuracy: 0.3963 - val_loss: 1.6567\n",
            "Epoch 3/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 2ms/step - accuracy: 0.3936 - loss: 1.6823 - val_accuracy: 0.3902 - val_loss: 1.6545\n",
            "Epoch 4/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 2ms/step - accuracy: 0.4164 - loss: 1.6310 - val_accuracy: 0.4053 - val_loss: 1.6388\n",
            "Epoch 5/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 3ms/step - accuracy: 0.4280 - loss: 1.5945 - val_accuracy: 0.4205 - val_loss: 1.5858\n",
            "Epoch 6/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 3ms/step - accuracy: 0.4356 - loss: 1.5720 - val_accuracy: 0.4117 - val_loss: 1.6074\n",
            "Epoch 7/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 3ms/step - accuracy: 0.4368 - loss: 1.5543 - val_accuracy: 0.4285 - val_loss: 1.5667\n",
            "Epoch 8/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 3ms/step - accuracy: 0.4445 - loss: 1.5494 - val_accuracy: 0.4283 - val_loss: 1.5767\n",
            "Epoch 9/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 3ms/step - accuracy: 0.4531 - loss: 1.5234 - val_accuracy: 0.4333 - val_loss: 1.5658\n",
            "Epoch 10/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 3ms/step - accuracy: 0.4551 - loss: 1.5230 - val_accuracy: 0.4302 - val_loss: 1.5814\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.history.History at 0x7dfbc2ded9d0>"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#loss - difference between true and predicted value"
      ],
      "metadata": {
        "id": "IR03CLUBzD0s"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#as we see that we can't get good accuracy\n",
        "#we use transfer learning(trained for an another similar dataset earlier)"
      ],
      "metadata": {
        "id": "qbaxxlXjzVWI"
      },
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **ResNet50**"
      ],
      "metadata": {
        "id": "j2KFJCmJ0Cr8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras import Sequential,models,layers\n",
        "#layers\n",
        "from tensorflow.keras.layers import Dense, Dropout,Flatten\n",
        "from tensorflow.keras.layers import BatchNormalization\n",
        "#models\n",
        "from tensorflow.keras.models import load_model\n",
        "from tensorflow.keras.models import Model\n",
        "\n",
        "from tensorflow.keras.applications.resnet50 import ResNet50\n",
        "from tensorflow.keras import optimizers"
      ],
      "metadata": {
        "id": "uIzgZbvM0GW6"
      },
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "convolutional_based = ResNet50(weights='imagenet',include_top=False,input_shape=(256,256,3))\n",
        "#imagenet - image data base with 14 million image dataset\n",
        "#and now we are going to use those weights that we got while they trained imagenet\n",
        "#cifar-10 is similar to imagenet so we are using it\n",
        "#include_top=False - to remove the output layer. we need to use ours\n",
        "#these layers used apart from input,hidden,output becoz it can capture the information from image better"
      ],
      "metadata": {
        "id": "JvH8hEPb09R8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "afaa9a4b-527d-40ad-b2e8-440c09c289b7"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "\u001b[1m94765736/94765736\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "convolutional_based.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "1QU1-IAr37z0",
        "outputId": "3fe7cda5-b5a8-4197-b226-e59827b1d6a2"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1mModel: \"resnet50\"\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"resnet50\"</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓\n",
              "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape     \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m   Param #\u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mConnected to     \u001b[0m\u001b[1m \u001b[0m┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩\n",
              "│ input_layer_1       │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m256\u001b[0m,  │          \u001b[38;5;34m0\u001b[0m │ -                 │\n",
              "│ (\u001b[38;5;33mInputLayer\u001b[0m)        │ \u001b[38;5;34m3\u001b[0m)                │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_pad           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m262\u001b[0m, \u001b[38;5;34m262\u001b[0m,  │          \u001b[38;5;34m0\u001b[0m │ input_layer_1[\u001b[38;5;34m0\u001b[0m]… │\n",
              "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m)     │ \u001b[38;5;34m3\u001b[0m)                │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_conv (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m,  │      \u001b[38;5;34m9,472\u001b[0m │ conv1_pad[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]   │\n",
              "│                     │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_bn            │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m,  │        \u001b[38;5;34m256\u001b[0m │ conv1_conv[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]  │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_relu          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m,  │          \u001b[38;5;34m0\u001b[0m │ conv1_bn[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]    │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ pool1_pad           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m130\u001b[0m, \u001b[38;5;34m130\u001b[0m,  │          \u001b[38;5;34m0\u001b[0m │ conv1_relu[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]  │\n",
              "│ (\u001b[38;5;33mZeroPadding2D\u001b[0m)     │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ pool1_pool          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ pool1_pad[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]   │\n",
              "│ (\u001b[38;5;33mMaxPooling2D\u001b[0m)      │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │      \u001b[38;5;34m4,160\u001b[0m │ pool1_pool[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]  │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │        \u001b[38;5;34m256\u001b[0m │ conv2_block1_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block1_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m36,928\u001b[0m │ conv2_block1_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │        \u001b[38;5;34m256\u001b[0m │ conv2_block1_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block1_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_0_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m16,640\u001b[0m │ pool1_pool[\u001b[38;5;34m0\u001b[0m][\u001b[38;5;34m0\u001b[0m]  │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m16,640\u001b[0m │ conv2_block1_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_0_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv2_block1_0_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv2_block1_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block1_0_b… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m256\u001b[0m)              │            │ conv2_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block1_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m16,448\u001b[0m │ conv2_block1_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │        \u001b[38;5;34m256\u001b[0m │ conv2_block2_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block2_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m36,928\u001b[0m │ conv2_block2_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │        \u001b[38;5;34m256\u001b[0m │ conv2_block2_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block2_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m16,640\u001b[0m │ conv2_block2_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv2_block2_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block1_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m256\u001b[0m)              │            │ conv2_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block2_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m16,448\u001b[0m │ conv2_block2_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │        \u001b[38;5;34m256\u001b[0m │ conv2_block3_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block3_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m36,928\u001b[0m │ conv2_block3_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │        \u001b[38;5;34m256\u001b[0m │ conv2_block3_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block3_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m64\u001b[0m)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │     \u001b[38;5;34m16,640\u001b[0m │ conv2_block3_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv2_block3_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block2_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m256\u001b[0m)              │            │ conv2_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv2_block3_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m32,896\u001b[0m │ conv2_block3_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block1_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block1_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │    \u001b[38;5;34m147,584\u001b[0m │ conv3_block1_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block1_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block1_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_0_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │    \u001b[38;5;34m131,584\u001b[0m │ conv2_block3_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m66,048\u001b[0m │ conv3_block1_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_0_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │      \u001b[38;5;34m2,048\u001b[0m │ conv3_block1_0_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │      \u001b[38;5;34m2,048\u001b[0m │ conv3_block1_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block1_0_b… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m512\u001b[0m)              │            │ conv3_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block1_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m65,664\u001b[0m │ conv3_block1_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block2_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block2_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │    \u001b[38;5;34m147,584\u001b[0m │ conv3_block2_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block2_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block2_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m66,048\u001b[0m │ conv3_block2_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │      \u001b[38;5;34m2,048\u001b[0m │ conv3_block2_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block1_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m512\u001b[0m)              │            │ conv3_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block2_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m65,664\u001b[0m │ conv3_block2_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block3_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block3_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │    \u001b[38;5;34m147,584\u001b[0m │ conv3_block3_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block3_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block3_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m66,048\u001b[0m │ conv3_block3_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │      \u001b[38;5;34m2,048\u001b[0m │ conv3_block3_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block2_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m512\u001b[0m)              │            │ conv3_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block3_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m65,664\u001b[0m │ conv3_block3_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block4_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block4_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │    \u001b[38;5;34m147,584\u001b[0m │ conv3_block4_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │        \u001b[38;5;34m512\u001b[0m │ conv3_block4_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block4_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m128\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │     \u001b[38;5;34m66,048\u001b[0m │ conv3_block4_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │      \u001b[38;5;34m2,048\u001b[0m │ conv3_block4_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block3_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m512\u001b[0m)              │            │ conv3_block4_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv3_block4_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m512\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m131,328\u001b[0m │ conv3_block4_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block1_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block1_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m590,080\u001b[0m │ conv4_block1_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block1_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block1_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_0_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m525,312\u001b[0m │ conv3_block4_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m263,168\u001b[0m │ conv4_block1_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_0_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block1_0_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block1_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block1_0_b… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m1024\u001b[0m)             │            │ conv4_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block1_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m262,400\u001b[0m │ conv4_block1_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block2_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block2_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m590,080\u001b[0m │ conv4_block2_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block2_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block2_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m263,168\u001b[0m │ conv4_block2_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block2_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block1_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m1024\u001b[0m)             │            │ conv4_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block2_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m262,400\u001b[0m │ conv4_block2_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block3_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block3_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m590,080\u001b[0m │ conv4_block3_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block3_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block3_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m263,168\u001b[0m │ conv4_block3_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block3_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block2_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m1024\u001b[0m)             │            │ conv4_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block3_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m262,400\u001b[0m │ conv4_block3_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block4_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block4_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m590,080\u001b[0m │ conv4_block4_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block4_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block4_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m263,168\u001b[0m │ conv4_block4_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block4_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block3_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m1024\u001b[0m)             │            │ conv4_block4_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block4_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m262,400\u001b[0m │ conv4_block4_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block5_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block5_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m590,080\u001b[0m │ conv4_block5_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block5_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block5_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m263,168\u001b[0m │ conv4_block5_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block5_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block4_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m1024\u001b[0m)             │            │ conv4_block5_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block5_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m262,400\u001b[0m │ conv4_block5_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block6_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block6_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m590,080\u001b[0m │ conv4_block6_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m1,024\u001b[0m │ conv4_block6_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block6_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m256\u001b[0m)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │    \u001b[38;5;34m263,168\u001b[0m │ conv4_block6_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │      \u001b[38;5;34m4,096\u001b[0m │ conv4_block6_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block5_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m1024\u001b[0m)             │            │ conv4_block6_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m,    │          \u001b[38;5;34m0\u001b[0m │ conv4_block6_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m1024\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │    \u001b[38;5;34m524,800\u001b[0m │ conv4_block6_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │      \u001b[38;5;34m2,048\u001b[0m │ conv5_block1_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │          \u001b[38;5;34m0\u001b[0m │ conv5_block1_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │  \u001b[38;5;34m2,359,808\u001b[0m │ conv5_block1_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │      \u001b[38;5;34m2,048\u001b[0m │ conv5_block1_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │          \u001b[38;5;34m0\u001b[0m │ conv5_block1_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_0_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │  \u001b[38;5;34m2,099,200\u001b[0m │ conv4_block6_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │  \u001b[38;5;34m1,050,624\u001b[0m │ conv5_block1_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_0_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │      \u001b[38;5;34m8,192\u001b[0m │ conv5_block1_0_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │      \u001b[38;5;34m8,192\u001b[0m │ conv5_block1_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │          \u001b[38;5;34m0\u001b[0m │ conv5_block1_0_b… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m2048\u001b[0m)             │            │ conv5_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │          \u001b[38;5;34m0\u001b[0m │ conv5_block1_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │  \u001b[38;5;34m1,049,088\u001b[0m │ conv5_block1_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │      \u001b[38;5;34m2,048\u001b[0m │ conv5_block2_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │          \u001b[38;5;34m0\u001b[0m │ conv5_block2_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │  \u001b[38;5;34m2,359,808\u001b[0m │ conv5_block2_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │      \u001b[38;5;34m2,048\u001b[0m │ conv5_block2_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │          \u001b[38;5;34m0\u001b[0m │ conv5_block2_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │  \u001b[38;5;34m1,050,624\u001b[0m │ conv5_block2_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │      \u001b[38;5;34m8,192\u001b[0m │ conv5_block2_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │          \u001b[38;5;34m0\u001b[0m │ conv5_block1_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m2048\u001b[0m)             │            │ conv5_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │          \u001b[38;5;34m0\u001b[0m │ conv5_block2_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_1_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │  \u001b[38;5;34m1,049,088\u001b[0m │ conv5_block2_out… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_1_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │      \u001b[38;5;34m2,048\u001b[0m │ conv5_block3_1_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_1_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │          \u001b[38;5;34m0\u001b[0m │ conv5_block3_1_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_2_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │  \u001b[38;5;34m2,359,808\u001b[0m │ conv5_block3_1_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_2_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │      \u001b[38;5;34m2,048\u001b[0m │ conv5_block3_2_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_2_relu │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m512\u001b[0m) │          \u001b[38;5;34m0\u001b[0m │ conv5_block3_2_b… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_3_conv │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │  \u001b[38;5;34m1,050,624\u001b[0m │ conv5_block3_2_r… │\n",
              "│ (\u001b[38;5;33mConv2D\u001b[0m)            │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_3_bn   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │      \u001b[38;5;34m8,192\u001b[0m │ conv5_block3_3_c… │\n",
              "│ (\u001b[38;5;33mBatchNormalizatio…\u001b[0m │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_add    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │          \u001b[38;5;34m0\u001b[0m │ conv5_block2_out… │\n",
              "│ (\u001b[38;5;33mAdd\u001b[0m)               │ \u001b[38;5;34m2048\u001b[0m)             │            │ conv5_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_out    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8\u001b[0m, \u001b[38;5;34m8\u001b[0m,      │          \u001b[38;5;34m0\u001b[0m │ conv5_block3_add… │\n",
              "│ (\u001b[38;5;33mActivation\u001b[0m)        │ \u001b[38;5;34m2048\u001b[0m)             │            │                   │\n",
              "└─────────────────────┴───────────────────┴────────────┴───────────────────┘\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓\n",
              "┃<span style=\"font-weight: bold\"> Layer (type)        </span>┃<span style=\"font-weight: bold\"> Output Shape      </span>┃<span style=\"font-weight: bold\">    Param # </span>┃<span style=\"font-weight: bold\"> Connected to      </span>┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩\n",
              "│ input_layer_1       │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>,  │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ -                 │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">InputLayer</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)                │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_pad           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">262</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">262</span>,  │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ input_layer_1[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">ZeroPadding2D</span>)     │ <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)                │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_conv (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>,  │      <span style=\"color: #00af00; text-decoration-color: #00af00\">9,472</span> │ conv1_pad[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]   │\n",
              "│                     │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_bn            │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>,  │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv1_conv[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]  │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv1_relu          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>,  │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv1_bn[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]    │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ pool1_pad           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">130</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">130</span>,  │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv1_relu[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]  │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">ZeroPadding2D</span>)     │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ pool1_pool          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ pool1_pad[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]   │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)      │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,160</span> │ pool1_pool[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]  │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv2_block1_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block1_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">36,928</span> │ conv2_block1_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv2_block1_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block1_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_0_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">16,640</span> │ pool1_pool[<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>][<span style=\"color: #00af00; text-decoration-color: #00af00\">0</span>]  │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">16,640</span> │ conv2_block1_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_0_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv2_block1_0_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv2_block1_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block1_0_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │ conv2_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block1_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block1_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">16,448</span> │ conv2_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv2_block2_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block2_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">36,928</span> │ conv2_block2_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv2_block2_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block2_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">16,640</span> │ conv2_block2_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv2_block2_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │ conv2_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block2_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block2_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">16,448</span> │ conv2_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv2_block3_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block3_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">36,928</span> │ conv2_block3_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │ conv2_block3_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block3_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)               │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">16,640</span> │ conv2_block3_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv2_block3_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │ conv2_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv2_block3_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv2_block3_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">32,896</span> │ conv2_block3_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block1_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block1_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">147,584</span> │ conv3_block1_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block1_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block1_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_0_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">131,584</span> │ conv2_block3_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">66,048</span> │ conv3_block1_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_0_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv3_block1_0_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv3_block1_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block1_0_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │ conv3_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block1_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block1_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">65,664</span> │ conv3_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block2_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block2_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">147,584</span> │ conv3_block2_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block2_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block2_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">66,048</span> │ conv3_block2_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv3_block2_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │ conv3_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block2_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block2_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">65,664</span> │ conv3_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block3_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block3_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">147,584</span> │ conv3_block3_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block3_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block3_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">66,048</span> │ conv3_block3_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv3_block3_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │ conv3_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block3_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block3_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">65,664</span> │ conv3_block3_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block4_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block4_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">147,584</span> │ conv3_block4_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │ conv3_block4_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block4_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │     <span style=\"color: #00af00; text-decoration-color: #00af00\">66,048</span> │ conv3_block4_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv3_block4_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block3_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │ conv3_block4_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv3_block4_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv3_block4_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">131,328</span> │ conv3_block4_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block1_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block1_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │ conv4_block1_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block1_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block1_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_0_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">525,312</span> │ conv3_block4_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">263,168</span> │ conv4_block1_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_0_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block1_0_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block1_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block1_0_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │ conv4_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block1_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block1_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">262,400</span> │ conv4_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block2_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block2_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │ conv4_block2_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block2_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block2_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">263,168</span> │ conv4_block2_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block2_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │ conv4_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block2_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block2_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">262,400</span> │ conv4_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block3_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block3_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │ conv4_block3_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block3_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block3_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">263,168</span> │ conv4_block3_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block3_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │ conv4_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block3_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block3_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">262,400</span> │ conv4_block3_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block4_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block4_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │ conv4_block4_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block4_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block4_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">263,168</span> │ conv4_block4_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block4_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block3_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │ conv4_block4_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block4_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block4_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">262,400</span> │ conv4_block4_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block5_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block5_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │ conv4_block5_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block5_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block5_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">263,168</span> │ conv4_block5_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block5_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block4_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │ conv4_block5_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block5_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block5_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">262,400</span> │ conv4_block5_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block6_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block6_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │ conv4_block6_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │ conv4_block6_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block6_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)              │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │    <span style=\"color: #00af00; text-decoration-color: #00af00\">263,168</span> │ conv4_block6_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │      <span style=\"color: #00af00; text-decoration-color: #00af00\">4,096</span> │ conv4_block6_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block5_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │ conv4_block6_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv4_block6_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>,    │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv4_block6_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">1024</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │    <span style=\"color: #00af00; text-decoration-color: #00af00\">524,800</span> │ conv4_block6_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv5_block1_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block1_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │  <span style=\"color: #00af00; text-decoration-color: #00af00\">2,359,808</span> │ conv5_block1_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv5_block1_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block1_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_0_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │  <span style=\"color: #00af00; text-decoration-color: #00af00\">2,099,200</span> │ conv4_block6_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │  <span style=\"color: #00af00; text-decoration-color: #00af00\">1,050,624</span> │ conv5_block1_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_0_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │      <span style=\"color: #00af00; text-decoration-color: #00af00\">8,192</span> │ conv5_block1_0_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │      <span style=\"color: #00af00; text-decoration-color: #00af00\">8,192</span> │ conv5_block1_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block1_0_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │ conv5_block1_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block1_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block1_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │  <span style=\"color: #00af00; text-decoration-color: #00af00\">1,049,088</span> │ conv5_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv5_block2_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block2_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │  <span style=\"color: #00af00; text-decoration-color: #00af00\">2,359,808</span> │ conv5_block2_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv5_block2_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block2_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │  <span style=\"color: #00af00; text-decoration-color: #00af00\">1,050,624</span> │ conv5_block2_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │      <span style=\"color: #00af00; text-decoration-color: #00af00\">8,192</span> │ conv5_block2_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block1_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │ conv5_block2_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block2_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block2_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_1_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │  <span style=\"color: #00af00; text-decoration-color: #00af00\">1,049,088</span> │ conv5_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_1_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv5_block3_1_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_1_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block3_1_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_2_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │  <span style=\"color: #00af00; text-decoration-color: #00af00\">2,359,808</span> │ conv5_block3_1_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_2_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │      <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │ conv5_block3_2_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_2_relu │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>) │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block3_2_b… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │                   │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_3_conv │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │  <span style=\"color: #00af00; text-decoration-color: #00af00\">1,050,624</span> │ conv5_block3_2_r… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)            │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_3_bn   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │      <span style=\"color: #00af00; text-decoration-color: #00af00\">8,192</span> │ conv5_block3_3_c… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalizatio…</span> │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_add    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block2_out… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Add</span>)               │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │ conv5_block3_3_b… │\n",
              "├─────────────────────┼───────────────────┼────────────┼───────────────────┤\n",
              "│ conv5_block3_out    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8</span>,      │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │ conv5_block3_add… │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Activation</span>)        │ <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)             │            │                   │\n",
              "└─────────────────────┴───────────────────┴────────────┴───────────────────┘\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m23,587,712\u001b[0m (89.98 MB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> (89.98 MB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m23,534,592\u001b[0m (89.78 MB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">23,534,592</span> (89.78 MB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m53,120\u001b[0m (207.50 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">53,120</span> (207.50 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "no_of_classes=10\n",
        "model=models.Sequential()\n",
        "model.add(layers.UpSampling2D((2,2)))\n",
        "model.add(layers.UpSampling2D((2,2)))\n",
        "model.add(layers.UpSampling2D((2,2)))\n",
        "model.add(convolutional_based)\n",
        "model.add(layers.GlobalAveragePooling2D())\n",
        "model.add(layers.BatchNormalization())\n",
        "\n",
        "model.add(layers.Dense(128,activation='relu'))\n",
        "model.add(layers.Dropout(0.5))\n",
        "model.add(layers.BatchNormalization())\n",
        "\n",
        "model.add(layers.Dense(64,activation='relu'))\n",
        "model.add(layers.Dropout(0.5))\n",
        "model.add(layers.BatchNormalization())\n",
        "\n",
        "model.add(layers.Dense(no_of_classes,activation='softmax'))"
      ],
      "metadata": {
        "id": "i9pvxtOp4BR1"
      },
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#upsampling - converting 32x32 to 256x256\n",
        "#32x2x2x2=256 as resnet uses 256x256 as input shape\n",
        "\n",
        "#batchnorm not needed if we already used norm but batchnorm improved efficiency most of the time\n",
        "#batchnorm makes sure each time the values are normalized after processing in each layer\n",
        "\n",
        "#dropout- to avoid overfitting\n",
        "#During training, a fraction of neurons (typically 20-50%) are randomly dropped out, meaning their outputs are set to zero"
      ],
      "metadata": {
        "id": "4JVICUos5XXB"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(optimizer=optimizers.RMSprop(learning_rate=2e-5),\n",
        "              loss='sparse_categorical_crossentropy',\n",
        "              metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "r83gzwyB9Gbh"
      },
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "history = model.fit(x_train_scaled, y_train, validation_split=0.1, epochs=10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LSheWvZc-mrm",
        "outputId": "c2296bb5-a764-4b2f-ebc5-c0bf1bec27cc"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m430s\u001b[0m 339ms/step - accuracy: 0.2521 - loss: 2.3072 - val_accuracy: 0.7582 - val_loss: 0.8734\n",
            "Epoch 2/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m419s\u001b[0m 341ms/step - accuracy: 0.6782 - loss: 1.0655 - val_accuracy: 0.8960 - val_loss: 0.4392\n",
            "Epoch 3/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m432s\u001b[0m 333ms/step - accuracy: 0.8161 - loss: 0.7139 - val_accuracy: 0.9155 - val_loss: 0.3324\n",
            "Epoch 4/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m395s\u001b[0m 345ms/step - accuracy: 0.8814 - loss: 0.5422 - val_accuracy: 0.9275 - val_loss: 0.2748\n",
            "Epoch 5/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m437s\u001b[0m 341ms/step - accuracy: 0.9222 - loss: 0.4087 - val_accuracy: 0.9295 - val_loss: 0.2533\n",
            "Epoch 6/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m441s\u001b[0m 340ms/step - accuracy: 0.9448 - loss: 0.3228 - val_accuracy: 0.9312 - val_loss: 0.2564\n",
            "Epoch 7/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m433s\u001b[0m 332ms/step - accuracy: 0.9585 - loss: 0.2605 - val_accuracy: 0.9315 - val_loss: 0.2485\n",
            "Epoch 8/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m387s\u001b[0m 344ms/step - accuracy: 0.9686 - loss: 0.2127 - val_accuracy: 0.9290 - val_loss: 0.2534\n",
            "Epoch 9/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m443s\u001b[0m 345ms/step - accuracy: 0.9758 - loss: 0.1840 - val_accuracy: 0.9325 - val_loss: 0.2455\n",
            "Epoch 10/10\n",
            "\u001b[1m1125/1125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m440s\u001b[0m 343ms/step - accuracy: 0.9810 - loss: 0.1557 - val_accuracy: 0.9360 - val_loss: 0.2404\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "h = history\n",
        "\n",
        "# plot the loss value\n",
        "plt.plot(h.history['loss'], label='train loss')\n",
        "plt.plot(h.history['val_loss'], label='validation loss')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "\n",
        "# plot the accuracy value\n",
        "plt.plot(h.history['accuracy'], label='train accuracy')\n",
        "plt.plot(h.history['val_accuracy'], label='validation accuracy')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 843
        },
        "id": "-2dH7TlNA2om",
        "outputId": "16611da6-6da3-49c6-e9c4-e9fa9ffcaf2b"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loss, accuracy = model.evaluate(x_test_scaled, y_test)\n",
        "print('Test Accuracy =', accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tM7WfZkbUW6s",
        "outputId": "6d64124c-ecb2-474a-c8db-7f3c1bf61618"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m38s\u001b[0m 108ms/step - accuracy: 0.9319 - loss: 0.2646\n",
            "Test Accuracy = 0.9336000084877014\n"
          ]
        }
      ]
    }
  ]
}