modelspractice.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyNLezvWiyurOg80daGK/Y91"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "8PzaP2WrEzz9"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "import torchvision\n",
        "\n",
        "import torchvision.datasets as datasets\n",
        "import torchvision.transforms as transforms\n",
        "\n",
        "import pathlib\n",
        "\n",
        "data_dir = pathlib.Path(\"petdata/\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_data = datasets.OxfordIIITPet(root=data_dir,\n",
        "                                    split=\"trainval\",\n",
        "                                    download=\"True\")\n",
        "\n",
        "test_data = datasets.OxfordIIITPet(root=data_dir,\n",
        "                                   split=\"test\",\n",
        "                                   download=\"True\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HOA7mMa8E6ry",
        "outputId": "1db1a9e5-b0ac-406a-f474-70c5297465e6"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://thor.robots.ox.ac.uk/datasets/pets/images.tar.gz to petdata/oxford-iiit-pet/images.tar.gz\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 791918971/791918971 [00:26<00:00, 29727871.66it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting petdata/oxford-iiit-pet/images.tar.gz to petdata/oxford-iiit-pet\n",
            "Downloading https://thor.robots.ox.ac.uk/datasets/pets/annotations.tar.gz to petdata/oxford-iiit-pet/annotations.tar.gz\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 19173078/19173078 [00:01<00:00, 16356823.54it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting petdata/oxford-iiit-pet/annotations.tar.gz to petdata/oxford-iiit-pet\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_data.classes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p6kxhmlEU5X2",
        "outputId": "7ea1a415-8202-496b-c454-7e679c17f1fa"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Abyssinian',\n",
              " 'American Bulldog',\n",
              " 'American Pit Bull Terrier',\n",
              " 'Basset Hound',\n",
              " 'Beagle',\n",
              " 'Bengal',\n",
              " 'Birman',\n",
              " 'Bombay',\n",
              " 'Boxer',\n",
              " 'British Shorthair',\n",
              " 'Chihuahua',\n",
              " 'Egyptian Mau',\n",
              " 'English Cocker Spaniel',\n",
              " 'English Setter',\n",
              " 'German Shorthaired',\n",
              " 'Great Pyrenees',\n",
              " 'Havanese',\n",
              " 'Japanese Chin',\n",
              " 'Keeshond',\n",
              " 'Leonberger',\n",
              " 'Maine Coon',\n",
              " 'Miniature Pinscher',\n",
              " 'Newfoundland',\n",
              " 'Persian',\n",
              " 'Pomeranian',\n",
              " 'Pug',\n",
              " 'Ragdoll',\n",
              " 'Russian Blue',\n",
              " 'Saint Bernard',\n",
              " 'Samoyed',\n",
              " 'Scottish Terrier',\n",
              " 'Shiba Inu',\n",
              " 'Siamese',\n",
              " 'Sphynx',\n",
              " 'Staffordshire Bull Terrier',\n",
              " 'Wheaten Terrier',\n",
              " 'Yorkshire Terrier']"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "\n",
        "image_path = data_dir / \"oxford-iiit-pet\" / \"images\"\n",
        "target_classes = [\"Abyssinian\", \"beagle\", \"boxer\", \"Ragdoll\"]\n",
        "\n",
        "def get_subset(image_path=image_path,\n",
        "               data_splits=[\"trainval\", \"test\"],\n",
        "               target_classes=target_classes,\n",
        "               amount=0.2):\n",
        "  label_splits = {}\n",
        "\n",
        "  for data_split in data_splits:\n",
        "    print(f\"Creating image split for: {data_split}\")\n",
        "    label_path = data_dir / \"oxford-iiit-pet\" / \"annotations\" / f\"{data_split}.txt\"\n",
        "    with open(label_path, \"r\") as f:\n",
        "      labels = [line.strip(\"\\n\") for line in f.readlines() if line.split(\"_\")[0] in target_classes]\n",
        "\n",
        "    #if data_split == \"test\":\n",
        "      #num_to_sample = round(amount*len(labels))\n",
        "    #else:\n",
        "      #num_to_sample = round(amount*2*len(labels))\n",
        "    print(f\"Getting {len(labels)} images for {data_split}...\")\n",
        "    #sampled_images = random.sample(labels, k=num_to_sample)\n",
        "\n",
        "    image_paths = [pathlib.Path(str(image_path / str(sample_image)).split(\" \")[0] + \".jpg\") for sample_image in labels]\n",
        "    label_splits[data_split] = image_paths\n",
        "  return label_splits\n",
        "\n",
        "label_splits = get_subset()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4zuvdPGsGjwP",
        "outputId": "bb866945-039d-449a-f936-dca5eecb9344"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Creating image split for: trainval\n",
            "Getting 400 images for trainval...\n",
            "Creating image split for: test\n",
            "Getting 397 images for test...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "label_splits[\"trainval\"][:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VlF6Y3zlK98k",
        "outputId": "861db6d3-e977-48f6-eab4-441de34232d2"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_100.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_101.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_102.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_103.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_104.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_105.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_106.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_107.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_108.jpg'),\n",
              " PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_109.jpg')]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target_dir_name = \"petdata/dog_and_cat\"\n",
        "target_dir = pathlib.Path(target_dir_name)\n",
        "target_dir.mkdir(parents=True, exist_ok=True)\n"
      ],
      "metadata": {
        "id": "bjPHju7_29DQ"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "img_path = label_splits[\"trainval\"][0]\n",
        "img_path.name, img_path.parent.stem"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k1i8Krlk46_5",
        "outputId": "2ec92077-c4a7-43a5-ddb8-4e7f7b560d95"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('Abyssinian_100.jpg', 'images')"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "str(img_path.name).split(\" \")[0].split(\"_\")[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "ghWeTgOE__Ut",
        "outputId": "76cb8ea2-bc5e-43a8-b8e4-52d6f6981834"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Abyssinian'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "img_path"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9frmC7HfCGyH",
        "outputId": "2329f091-42bb-44b3-d680-f6bea0f9325a"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PosixPath('petdata/oxford-iiit-pet/images/Abyssinian_100.jpg')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dest_dir_test = target_dir / \"train\" / str(img_path.name).split(\"_\")[0] / img_path.name\n",
        "dest_dir_test, dest_dir_test.parent"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CDicp0I7BOcH",
        "outputId": "3eb3c8fe-5ef9-455f-eb0d-413b36d672da"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(PosixPath('petdata/dog_and_cat/train/Abyssinian/Abyssinian_100.jpg'),\n",
              " PosixPath('petdata/dog_and_cat/train/Abyssinian'))"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import shutil\n",
        "\n",
        "for label_split in label_splits.keys():\n",
        "  for image_path in label_splits[str(label_split)]:\n",
        "    dest_dir = target_dir / label_split / str(image_path.name).split(\"_\")[0] / image_path.name\n",
        "    if not dest_dir.parent.is_dir():\n",
        "      dest_dir.parent.mkdir(parents=True, exist_ok=True)\n",
        "    print(f\"[INFO] Copying {image_path} to {dest_dir}...\")\n",
        "    shutil.copy2(image_path, dest_dir)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CqxvHV8O4NHQ",
        "outputId": "3038a23c-7ab6-47c0-aa78-d92db278ad98"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_100.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_100.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_101.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_101.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_102.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_102.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_103.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_103.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_104.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_104.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_105.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_105.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_106.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_106.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_107.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_107.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_108.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_108.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_109.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_109.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_10.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_10.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_110.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_110.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_111.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_111.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_112.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_112.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_113.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_113.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_114.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_114.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_115.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_115.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_116.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_116.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_117.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_117.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_118.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_118.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_119.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_119.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_11.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_11.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_120.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_120.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_121.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_121.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_122.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_122.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_123.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_123.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_124.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_124.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_125.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_125.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_126.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_126.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_127.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_127.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_128.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_128.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_129.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_129.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_12.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_12.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_130.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_130.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_131.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_131.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_132.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_132.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_133.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_133.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_134.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_134.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_135.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_135.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_136.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_136.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_137.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_137.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_138.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_138.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_139.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_139.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_13.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_13.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_140.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_140.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_141.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_141.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_142.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_142.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_143.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_143.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_144.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_144.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Abyssinian_145.jpg to petdata/dog_and_cat/trainval/Abyssinian/Abyssinian_145.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_100.jpg to petdata/dog_and_cat/trainval/beagle/beagle_100.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_101.jpg to petdata/dog_and_cat/trainval/beagle/beagle_101.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_102.jpg to petdata/dog_and_cat/trainval/beagle/beagle_102.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_103.jpg to petdata/dog_and_cat/trainval/beagle/beagle_103.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_104.jpg to petdata/dog_and_cat/trainval/beagle/beagle_104.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_105.jpg to petdata/dog_and_cat/trainval/beagle/beagle_105.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_107.jpg to petdata/dog_and_cat/trainval/beagle/beagle_107.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_108.jpg to petdata/dog_and_cat/trainval/beagle/beagle_108.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_109.jpg to petdata/dog_and_cat/trainval/beagle/beagle_109.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_10.jpg to petdata/dog_and_cat/trainval/beagle/beagle_10.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_110.jpg to petdata/dog_and_cat/trainval/beagle/beagle_110.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/beagle_111.jpg to petdata/dog_and_cat/trainval/beagle/beagle_111.jpg...\n",
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            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_94.jpg to petdata/dog_and_cat/test/boxer/boxer_94.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_95.jpg to petdata/dog_and_cat/test/boxer/boxer_95.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_96.jpg to petdata/dog_and_cat/test/boxer/boxer_96.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_97.jpg to petdata/dog_and_cat/test/boxer/boxer_97.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_98.jpg to petdata/dog_and_cat/test/boxer/boxer_98.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_99.jpg to petdata/dog_and_cat/test/boxer/boxer_99.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/boxer_9.jpg to petdata/dog_and_cat/test/boxer/boxer_9.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_203.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_203.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_204.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_204.jpg...\n",
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            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_208.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_208.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_20.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_20.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_210.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_210.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_219.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_219.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_224.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_224.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_227.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_227.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_228.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_228.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_234.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_234.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_235.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_235.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_245.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_245.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_24.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_24.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_250.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_250.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_252.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_252.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_254.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_254.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_255.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_255.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_257.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_257.jpg...\n",
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            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_25.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_25.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_260.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_260.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_261.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_261.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_262.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_262.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_263.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_263.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_264.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_264.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_265.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_265.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_26.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_26.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_27.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_27.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_29.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_29.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_2.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_2.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_30.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_30.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_31.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_31.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_32.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_32.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_33.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_33.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_34.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_34.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_35.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_35.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_36.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_36.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_37.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_37.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_3.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_3.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_40.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_40.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_41.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_41.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_42.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_42.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_43.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_43.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_44.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_44.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_45.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_45.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_47.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_47.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_48.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_48.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_49.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_49.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_4.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_4.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_51.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_51.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_52.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_52.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_53.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_53.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_54.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_54.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_56.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_56.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_57.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_57.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_58.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_58.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_59.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_59.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_5.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_5.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_60.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_60.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_62.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_62.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_63.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_63.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_64.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_64.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_67.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_67.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_68.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_68.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_69.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_69.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_6.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_6.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_71.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_71.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_72.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_72.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_73.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_73.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_74.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_74.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_75.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_75.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_76.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_76.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_77.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_77.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_78.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_78.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_79.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_79.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_7.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_7.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_80.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_80.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_81.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_81.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_82.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_82.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_83.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_83.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_84.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_84.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_85.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_85.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_86.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_86.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_87.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_87.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_88.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_88.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_89.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_89.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_8.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_8.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_90.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_90.jpg...\n",
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            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_93.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_93.jpg...\n",
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            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_96.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_96.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_97.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_97.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_98.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_98.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_99.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_99.jpg...\n",
            "[INFO] Copying petdata/oxford-iiit-pet/images/Ragdoll_9.jpg to petdata/dog_and_cat/test/Ragdoll/Ragdoll_9.jpg...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "\n",
        "def walk_through_dir(dir_path):\n",
        "  for dirpath, dirnames, filenames in os.walk(dir_path):\n",
        "    print(f\"There {len(dirnames)} directories and {len(filenames)} images in {dirpath}\")\n",
        "\n",
        "walk_through_dir(target_dir)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LKXPuxkoLZv5",
        "outputId": "de240928-bb09-4bf6-cf31-bb78299becc1"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "There 2 directories and 0 images in petdata/dog_and_cat\n",
            "There 4 directories and 0 images in petdata/dog_and_cat/trainval\n",
            "There 0 directories and 100 images in petdata/dog_and_cat/trainval/boxer\n",
            "There 0 directories and 100 images in petdata/dog_and_cat/trainval/Ragdoll\n",
            "There 0 directories and 100 images in petdata/dog_and_cat/trainval/beagle\n",
            "There 0 directories and 100 images in petdata/dog_and_cat/trainval/Abyssinian\n",
            "There 4 directories and 0 images in petdata/dog_and_cat/test\n",
            "There 0 directories and 99 images in petdata/dog_and_cat/test/boxer\n",
            "There 0 directories and 100 images in petdata/dog_and_cat/test/Ragdoll\n",
            "There 0 directories and 100 images in petdata/dog_and_cat/test/beagle\n",
            "There 0 directories and 98 images in petdata/dog_and_cat/test/Abyssinian\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "zip_file_name = data_dir / \"dog_and_cat_imgs\"\n",
        "shutil.make_archive(zip_file_name,\n",
        "                    format=\"zip\",\n",
        "                    root_dir=target_dir)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "PFFwGs1cNscN",
        "outputId": "468b0226-1c9a-4b73-84f4-969645b06f03"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/petdata/dog_and_cat_imgs.zip'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_dir = data_dir / \"dog_and_cat\" / \"trainval\"\n",
        "test_dir = data_dir / \"dog_and_cat\" / \"test\"\n",
        "\n",
        "train_dir, test_dir"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CyeZ-njD9TSK",
        "outputId": "efcf5d2c-c77f-4601-da4b-41a60865f584"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(PosixPath('petdata/dog_and_cat/trainval'),\n",
              " PosixPath('petdata/dog_and_cat/test'))"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
      ],
      "metadata": {
        "id": "hKR2BFy5VHjH"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_transform = transforms.Compose([\n",
        "    transforms.Resize(size=(224, 224)),\n",
        "    transforms.TrivialAugmentWide(num_magnitude_bins=31),\n",
        "    transforms.ToTensor()\n",
        "])\n",
        "\n",
        "test_transform = transforms.Compose([\n",
        "    transforms.Resize(size=(224, 224)),\n",
        "    transforms.ToTensor()\n",
        "])"
      ],
      "metadata": {
        "id": "rHLr3F5Y_l_a"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "training_data = datasets.ImageFolder(root=train_dir,\n",
        "                                     transform=train_transform,\n",
        "                                     target_transform=None)\n",
        "\n",
        "testing_data = datasets.ImageFolder(root=test_dir,\n",
        "                                    transform=test_transform,\n",
        "                                    target_transform=None)\n",
        "\n",
        "training_data, testing_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R1Ay9qud_QvB",
        "outputId": "d4703780-a8be-4c03-b0a7-eb03c0440a41"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(Dataset ImageFolder\n",
              "     Number of datapoints: 400\n",
              "     Root location: petdata/dog_and_cat/trainval\n",
              "     StandardTransform\n",
              " Transform: Compose(\n",
              "                Resize(size=(224, 224), interpolation=bilinear, max_size=None, antialias=warn)\n",
              "                TrivialAugmentWide(num_magnitude_bins=31, interpolation=InterpolationMode.NEAREST, fill=None)\n",
              "                ToTensor()\n",
              "            ),\n",
              " Dataset ImageFolder\n",
              "     Number of datapoints: 397\n",
              "     Root location: petdata/dog_and_cat/test\n",
              "     StandardTransform\n",
              " Transform: Compose(\n",
              "                Resize(size=(224, 224), interpolation=bilinear, max_size=None, antialias=warn)\n",
              "                ToTensor()\n",
              "            ))"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from torch.utils.data import DataLoader\n",
        "\n",
        "train_dataloader = DataLoader(dataset=training_data,\n",
        "                              batch_size=32,\n",
        "                              shuffle=True)\n",
        "\n",
        "test_dataloader = DataLoader(dataset=testing_data,\n",
        "                             batch_size=32,\n",
        "                             shuffle=False)\n",
        "\n",
        "train_dataloader, test_dataloader"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7BEhGRMfCEr8",
        "outputId": "ee6e3dff-67b2-4034-8806-aef601baa298"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<torch.utils.data.dataloader.DataLoader at 0x7f63a04c6da0>,\n",
              " <torch.utils.data.dataloader.DataLoader at 0x7f63a04c6ad0>)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "imgs, labels = next(iter(train_dataloader))\n",
        "img, label = imgs[0], labels[0]\n",
        "\n",
        "img.shape, label.shape\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W0egZmhRDNPp",
        "outputId": "74fe975b-d8f5-4068-eb27-08ef8bbad6b2"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(torch.Size([3, 224, 224]), torch.Size([]))"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class_names = training_data.classes"
      ],
      "metadata": {
        "id": "AK9JMKQ4Eh_q"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "figure = plt.figure(figsize=(7, 7))\n",
        "for i in range(1, 9):\n",
        "  imgs, labels = next(iter(train_dataloader))\n",
        "  img, label = imgs[0], labels[0]\n",
        "  plt.subplot(3, 3, i)\n",
        "  plt.imshow(img.permute(1, 2, 0))\n",
        "  plt.title(f\"Class: {class_names[label]}\")\n",
        "  plt.axis(False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 598
        },
        "id": "TrpctcLpCkaX",
        "outputId": "d47bc440-8c2f-41eb-c1b5-8d7c09de3820"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x700 with 8 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from torch import nn"
      ],
      "metadata": {
        "id": "rwz4DnI7HiA7"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class VGG16(nn.Module):\n",
        "    def __init__(self, input_shape:int, output_shape:int):\n",
        "        super().__init__()\n",
        "        self.conv_block_1 = nn.Sequential(\n",
        "            nn.Conv2d(in_channels=input_shape, out_channels=64, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size=2, stride=2)\n",
        "        )\n",
        "        self.conv_block_2 = nn.Sequential(\n",
        "            nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=128, out_channels=128, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size=2, stride=2)\n",
        "        )\n",
        "        self.conv_block_3 = nn.Sequential(\n",
        "            nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=256, out_channels=256, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=256, out_channels=256, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size=2, stride=2)\n",
        "        )\n",
        "        self.conv_block_4 = nn.Sequential(\n",
        "            nn.Conv2d(in_channels=256, out_channels=512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=512, out_channels=512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=512, out_channels=512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size=2, stride=2)\n",
        "        )\n",
        "        self.conv_block_5 = nn.Sequential(\n",
        "            nn.Conv2d(in_channels=512, out_channels=512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=512, out_channels=512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.Conv2d(in_channels=512, out_channels=512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size=2, stride=2)\n",
        "        )\n",
        "        self.linear_layer = nn.Sequential(\n",
        "            nn.Flatten(),\n",
        "            nn.Linear(in_features=512*7*7, out_features=4096),\n",
        "            nn.ReLU(),\n",
        "            nn.Linear(in_features=4096, out_features=4096),\n",
        "            nn.ReLU()\n",
        "        )\n",
        "        self.classifier = nn.Linear(in_features=4096, out_features=output_shape)\n",
        "\n",
        "    def forward(self, x):\n",
        "      x =  self.conv_block_1(x)\n",
        "      x =  self.conv_block_2(x)\n",
        "      x =  self.conv_block_3(x)\n",
        "      x =  self.conv_block_4(x)\n",
        "      x =  self.conv_block_5(x)\n",
        "      #print(f\"Shape after the 5 conv blocks: {x.shape}\")\n",
        "      x = self.linear_layer(x)\n",
        "      #print(f\"Shape after linear_layer: {x.shape}\")\n",
        "      x = self.classifier(x)\n",
        "      #print(f\"Shape after classifier: {x.shape}\")\n",
        "      return x"
      ],
      "metadata": {
        "id": "3JFF-dSAHZMN"
      },
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model = VGG16(input_shape=3, output_shape=4).to(device)"
      ],
      "metadata": {
        "id": "Sedlu_OOIXnf"
      },
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "example_img, example_label = next(iter(train_dataloader))\n",
        "\n",
        "model.eval()\n",
        "with torch.inference_mode():\n",
        "  pred = model(example_img.to(device))\n",
        "  print(pred)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3RsynjTEIK8P",
        "outputId": "7d249830-3716-49b1-ebfd-47546bcef0e5"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043],\n",
            "        [ 0.0060,  0.0058, -0.0118,  0.0043]], device='cuda:0')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def train_step(model:nn.Module, train_dataloader:torch.utils.data.DataLoader, loss_fn:nn.Module, optimizer:torch.optim.Optimizer, accuracy_fn, device:torch.device=device):\n",
        "  model.train()\n",
        "  train_loss, train_acc = 0, 0\n",
        "  for X, y in train_dataloader:\n",
        "    X, y = X.to(device), y.to(device)\n",
        "    pred = model(X)\n",
        "    loss = loss_fn(pred, y)\n",
        "    train_loss += loss\n",
        "    train_acc += accuracy_fn(y, torch.argmax(pred, dim=1))\n",
        "    optimizer.zero_grad()\n",
        "    loss.backward()\n",
        "    optimizer.step()\n",
        "\n",
        "  train_loss /= len(train_dataloader)\n",
        "  train_acc /= len(train_dataloader)\n",
        "  return train_loss, train_acc*100\n",
        "\n",
        "def test_step(model:nn.Module, test_dataloader:torch.utils.data.DataLoader, loss_fn:nn.Module, accuracy_fn, device:torch.device=device):\n",
        "  model.eval()\n",
        "  test_loss, test_acc = 0, 0\n",
        "  with torch.inference_mode():\n",
        "    for X, y in test_dataloader:\n",
        "      X, y = X.to(device), y.to(device)\n",
        "      pred = model(X)\n",
        "      test_loss += loss_fn(pred, y)\n",
        "      test_acc += accuracy_fn(y, torch.argmax(pred, dim=1))\n",
        "\n",
        "    test_loss /= len(test_dataloader)\n",
        "    test_acc /= len(test_dataloader)\n",
        "    return test_loss, test_acc*100\n"
      ],
      "metadata": {
        "id": "G_oRutIhU1SE"
      },
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def train(model:nn.Module, num_epochs:int, train_dataloader:torch.utils.data.DataLoader, test_dataloader:torch.utils.data.DataLoader, loss_fn:nn.Module, optimizer:torch.optim.Optimizer,\n",
        "          accuracy_fn, device:torch.device=device):\n",
        "  model.to(device)\n",
        "  perf_dict = {}\n",
        "  for epoch in range(num_epochs):\n",
        "    train_loss, train_acc = train_step(model=model, train_dataloader=train_dataloader, loss_fn=loss_fn, optimizer=optimizer, accuracy_fn=accuracy_fn)\n",
        "    test_loss, test_acc = test_step(model=model, test_dataloader=test_dataloader, loss_fn=loss_fn, accuracy_fn=accuracy_fn)\n",
        "\n",
        "    print(f\"Epoch: {epoch}\\nTrain loss: {train_loss} | Train acc: {train_acc} | Test loss: {test_loss} | Test acc: {test_acc}\")\n",
        "\n",
        "  perf_dict[\"train_loss\"] = train_loss\n",
        "  perf_dict[\"test_loss\"] = test_loss\n",
        "  perf_dict[\"train_acc\"] = train_acc\n",
        "  perf_dict[\"test_acc\"] = test_acc\n",
        "  return perf_dict\n",
        "\n",
        ""
      ],
      "metadata": {
        "id": "j4poXKeXXJV-"
      },
      "execution_count": 66,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install torchmetrics"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fQu1ByXzOUAu",
        "outputId": "0f0f45fa-2a17-4390-edb4-11ff88bbf7cc"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: torchmetrics in /usr/local/lib/python3.10/dist-packages (0.11.4)\n",
            "Requirement already satisfied: numpy>=1.17.2 in /usr/local/lib/python3.10/dist-packages (from torchmetrics) (1.22.4)\n",
            "Requirement already satisfied: torch>=1.8.1 in /usr/local/lib/python3.10/dist-packages (from torchmetrics) (2.0.1+cu118)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from torchmetrics) (23.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.1->torchmetrics) (3.12.2)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.1->torchmetrics) (4.6.3)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.1->torchmetrics) (1.11.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.1->torchmetrics) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.1->torchmetrics) (3.1.2)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.1->torchmetrics) (2.0.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.8.1->torchmetrics) (3.25.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.8.1->torchmetrics) (16.0.6)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.8.1->torchmetrics) (2.1.3)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.8.1->torchmetrics) (1.3.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from torchmetrics import Accuracy\n",
        "optimizer = torch.optim.SGD(params=model.parameters(), lr=0.1)\n",
        "loss_fn = nn.CrossEntropyLoss()\n",
        "accuracy_fn = Accuracy(task=\"multiclass\", num_classes=4).to(device)\n"
      ],
      "metadata": {
        "id": "h6Z6lkaeNw1N"
      },
      "execution_count": 68,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_results = train(model=model, num_epochs=20, train_dataloader=train_dataloader, test_dataloader=test_dataloader, loss_fn=loss_fn, optimizer=optimizer, accuracy_fn=accuracy_fn)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MaBy4kGWY9Qe",
        "outputId": "77578d2b-c8cc-41b0-e5cd-3bb045a15040"
      },
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 0\n",
            "Train loss: 1.3873839378356934 | Train acc: 23.798078536987305 | Test loss: 1.3864364624023438 | Test acc: 23.557693481445312\n",
            "Epoch: 1\n",
            "Train loss: 1.387146234512329 | Train acc: 24.038461685180664 | Test loss: 1.3860777616500854 | Test acc: 23.557693481445312\n",
            "Epoch: 2\n",
            "Train loss: 1.3874155282974243 | Train acc: 23.798078536987305 | Test loss: 1.3861984014511108 | Test acc: 24.038461685180664\n",
            "Epoch: 3\n",
            "Train loss: 1.387532353401184 | Train acc: 23.557693481445312 | Test loss: 1.3861546516418457 | Test acc: 28.365385055541992\n",
            "Epoch: 4\n",
            "Train loss: 1.3875067234039307 | Train acc: 22.355770111083984 | Test loss: 1.3858882188796997 | Test acc: 28.365385055541992\n",
            "Epoch: 5\n",
            "Train loss: 1.387463092803955 | Train acc: 24.51923179626465 | Test loss: 1.3865152597427368 | Test acc: 24.038461685180664\n",
            "Epoch: 6\n",
            "Train loss: 1.3875831365585327 | Train acc: 23.07692527770996 | Test loss: 1.386430025100708 | Test acc: 24.038461685180664\n",
            "Epoch: 7\n",
            "Train loss: 1.387951135635376 | Train acc: 20.432693481445312 | Test loss: 1.3861507177352905 | Test acc: 23.557693481445312\n",
            "Epoch: 8\n",
            "Train loss: 1.3875184059143066 | Train acc: 22.836538314819336 | Test loss: 1.3867580890655518 | Test acc: 23.557693481445312\n",
            "Epoch: 9\n",
            "Train loss: 1.3875607252120972 | Train acc: 23.31730842590332 | Test loss: 1.3870726823806763 | Test acc: 23.557693481445312\n",
            "Epoch: 10\n",
            "Train loss: 1.3873512744903564 | Train acc: 21.39423179626465 | Test loss: 1.3871369361877441 | Test acc: 24.038461685180664\n",
            "Epoch: 11\n",
            "Train loss: 1.3876724243164062 | Train acc: 23.798078536987305 | Test loss: 1.3869729042053223 | Test acc: 23.557693481445312\n",
            "Epoch: 12\n",
            "Train loss: 1.387268304824829 | Train acc: 24.75961685180664 | Test loss: 1.3866432905197144 | Test acc: 24.038461685180664\n",
            "Epoch: 13\n",
            "Train loss: 1.3880128860473633 | Train acc: 23.07692527770996 | Test loss: 1.386963129043579 | Test acc: 23.557693481445312\n",
            "Epoch: 14\n",
            "Train loss: 1.387734293937683 | Train acc: 22.596155166625977 | Test loss: 1.387215495109558 | Test acc: 24.038461685180664\n",
            "Epoch: 15\n",
            "Train loss: 1.3880376815795898 | Train acc: 24.278846740722656 | Test loss: 1.3863128423690796 | Test acc: 24.038461685180664\n",
            "Epoch: 16\n",
            "Train loss: 1.3873577117919922 | Train acc: 24.278846740722656 | Test loss: 1.3867590427398682 | Test acc: 23.557693481445312\n",
            "Epoch: 17\n",
            "Train loss: 1.3871532678604126 | Train acc: 23.31730842590332 | Test loss: 1.3873084783554077 | Test acc: 24.038461685180664\n",
            "Epoch: 18\n",
            "Train loss: 1.387891411781311 | Train acc: 23.31730842590332 | Test loss: 1.3881269693374634 | Test acc: 24.038461685180664\n",
            "Epoch: 19\n",
            "Train loss: 1.3879022598266602 | Train acc: 23.798078536987305 | Test loss: 1.386673927307129 | Test acc: 24.038461685180664\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class TinyVGG(nn.Module):\n",
        "    def __init__(self, input_shape: int, hidden_units: int, output_shape: int):\n",
        "        super().__init__()\n",
        "        self.conv_block_1 = nn.Sequential(nn.Conv2d(in_channels=input_shape, out_channels=hidden_units, kernel_size=3, stride=1, padding=0),\n",
        "                                     nn.ReLU(),\n",
        "                                     nn.Conv2d(in_channels=hidden_units, out_channels=hidden_units, kernel_size=3, stride=1, padding=0),\n",
        "                                     nn.ReLU(),\n",
        "                                     nn.MaxPool2d(kernel_size=2, stride=2))\n",
        "        self.conv_block_2 = nn.Sequential(nn.Conv2d(in_channels=hidden_units, out_channels=hidden_units, kernel_size=3, stride=1, padding=0),\n",
        "                                     nn.ReLU(),\n",
        "                                     nn.Conv2d(in_channels=hidden_units, out_channels=hidden_units, kernel_size=3, stride=1, padding=0),\n",
        "                                     nn.ReLU(),\n",
        "                                     nn.MaxPool2d(kernel_size=2, stride=2))\n",
        "        self.classifier = nn.Sequential(nn.Flatten(),\n",
        "                                        nn.Linear(in_features=28090, out_features=output_shape))\n",
        "\n",
        "    def forward(self, x):\n",
        "        x = self.conv_block_1(x)\n",
        "        #print(x.shape)\n",
        "        x = self.conv_block_2(x)\n",
        "        #print(x.shape)\n",
        "        x = self.classifier(x)\n",
        "        #print(x.shape)\n",
        "        return x\n",
        "        #return self.classifier(self.conv_block_2(self.conv_block_1(x))) -> benefits from OPERATOR FUSION (speeds up gpu computations) -> check 'Making deep learning to brrrr article'"
      ],
      "metadata": {
        "id": "jz8mE7BpSaPE"
      },
      "execution_count": 88,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_1 = TinyVGG(input_shape=3, hidden_units=10, output_shape=4)"
      ],
      "metadata": {
        "id": "i8lUA1g_Scb7"
      },
      "execution_count": 89,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "optimizer_0 = torch.optim.SGD(params=model_1.parameters(), lr=0.005)"
      ],
      "metadata": {
        "id": "oqYOQJdzZMaq"
      },
      "execution_count": 90,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_1_results = train(model=model_1, num_epochs=5, train_dataloader=train_dataloader, test_dataloader=test_dataloader, loss_fn=loss_fn, optimizer=optimizer_0, accuracy_fn=accuracy_fn)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EqjP_LxFUMkl",
        "outputId": "53a23646-f08a-4a8f-a049-8319865e07ef"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 0\n",
            "Train loss: 1.393426537513733 | Train acc: 23.557693481445312 | Test loss: 1.39060640335083 | Test acc: 24.038461685180664\n",
            "Epoch: 1\n",
            "Train loss: 1.39248526096344 | Train acc: 22.596155166625977 | Test loss: 1.3830375671386719 | Test acc: 28.365385055541992\n",
            "Epoch: 2\n",
            "Train loss: 1.3915163278579712 | Train acc: 20.673078536987305 | Test loss: 1.3842917680740356 | Test acc: 28.365385055541992\n",
            "Epoch: 3\n",
            "Train loss: 1.3926254510879517 | Train acc: 24.278846740722656 | Test loss: 1.3876571655273438 | Test acc: 23.557693481445312\n",
            "Epoch: 4\n",
            "Train loss: 1.3908452987670898 | Train acc: 23.07692527770996 | Test loss: 1.38547682762146 | Test acc: 24.038461685180664\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#taken from https://blog.paperspace.com/vgg-from-scratch-pytorch/\n",
        "\n",
        "class VGG16_1(nn.Module):\n",
        "    def __init__(self, num_classes=4):\n",
        "        super(VGG16_1, self).__init__()\n",
        "        self.layer1 = nn.Sequential(\n",
        "            nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(64),\n",
        "            nn.ReLU())\n",
        "        self.layer2 = nn.Sequential(\n",
        "            nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(64),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size = 2, stride = 2))\n",
        "        self.layer3 = nn.Sequential(\n",
        "            nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(128),\n",
        "            nn.ReLU())\n",
        "        self.layer4 = nn.Sequential(\n",
        "            nn.Conv2d(128, 128, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(128),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size = 2, stride = 2))\n",
        "        self.layer5 = nn.Sequential(\n",
        "            nn.Conv2d(128, 256, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(256),\n",
        "            nn.ReLU())\n",
        "        self.layer6 = nn.Sequential(\n",
        "            nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(256),\n",
        "            nn.ReLU())\n",
        "        self.layer7 = nn.Sequential(\n",
        "            nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(256),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size = 2, stride = 2))\n",
        "        self.layer8 = nn.Sequential(\n",
        "            nn.Conv2d(256, 512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(512),\n",
        "            nn.ReLU())\n",
        "        self.layer9 = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(512),\n",
        "            nn.ReLU())\n",
        "        self.layer10 = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(512),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size = 2, stride = 2))\n",
        "        self.layer11 = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(512),\n",
        "            nn.ReLU())\n",
        "        self.layer12 = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(512),\n",
        "            nn.ReLU())\n",
        "        self.layer13 = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1),\n",
        "            nn.BatchNorm2d(512),\n",
        "            nn.ReLU(),\n",
        "            nn.MaxPool2d(kernel_size = 2, stride = 2))\n",
        "        self.fc = nn.Sequential(\n",
        "            nn.Dropout(0.5),\n",
        "            nn.Linear(7*7*512, 4096),\n",
        "            nn.ReLU())\n",
        "        self.fc1 = nn.Sequential(\n",
        "            nn.Dropout(0.5),\n",
        "            nn.Linear(4096, 4096),\n",
        "            nn.ReLU())\n",
        "        self.fc2= nn.Sequential(\n",
        "            nn.Linear(4096, num_classes))\n",
        "\n",
        "    def forward(self, x):\n",
        "        out = self.layer1(x)\n",
        "        out = self.layer2(out)\n",
        "        out = self.layer3(out)\n",
        "        out = self.layer4(out)\n",
        "        out = self.layer5(out)\n",
        "        out = self.layer6(out)\n",
        "        out = self.layer7(out)\n",
        "        out = self.layer8(out)\n",
        "        out = self.layer9(out)\n",
        "        out = self.layer10(out)\n",
        "        out = self.layer11(out)\n",
        "        out = self.layer12(out)\n",
        "        out = self.layer13(out)\n",
        "        out = out.reshape(out.size(0), -1)\n",
        "        out = self.fc(out)\n",
        "        out = self.fc1(out)\n",
        "        out = self.fc2(out)\n",
        "        return out"
      ],
      "metadata": {
        "id": "ouyDxw9pU20W"
      },
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_2 = VGG16_1()"
      ],
      "metadata": {
        "id": "3Sgu6yjYWR0B"
      },
      "execution_count": 93,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "optimizer_1 = torch.optim.SGD(model_2.parameters(), lr=0.005, weight_decay = 0.005, momentum = 0.9)"
      ],
      "metadata": {
        "id": "Tz3VBWIqZBG3"
      },
      "execution_count": 94,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_2_results = train(model=model_2, num_epochs=20, train_dataloader=train_dataloader, test_dataloader=test_dataloader, loss_fn=loss_fn, optimizer=optimizer_1, accuracy_fn=accuracy_fn)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ANkgTZCuWh20",
        "outputId": "eabdc826-ae39-4e4b-c007-da6472344b4f"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 0\n",
            "Train loss: 1.469868540763855 | Train acc: 26.442306518554688 | Test loss: 20.016233444213867 | Test acc: 28.365385055541992\n",
            "Epoch: 1\n",
            "Train loss: 1.5788103342056274 | Train acc: 32.69231033325195 | Test loss: 6.716953277587891 | Test acc: 28.846153259277344\n",
            "Epoch: 2\n",
            "Train loss: 1.5124802589416504 | Train acc: 34.13461685180664 | Test loss: 1.3646878004074097 | Test acc: 30.824705123901367\n",
            "Epoch: 3\n",
            "Train loss: 1.2425695657730103 | Train acc: 43.26923370361328 | Test loss: 1.246212363243103 | Test acc: 42.93639373779297\n",
            "Epoch: 4\n",
            "Train loss: 1.1466971635818481 | Train acc: 47.59615707397461 | Test loss: 1.2748689651489258 | Test acc: 44.933433532714844\n",
            "Epoch: 5\n",
            "Train loss: 1.2286722660064697 | Train acc: 47.83654022216797 | Test loss: 1.2158459424972534 | Test acc: 43.56509017944336\n",
            "Epoch: 6\n",
            "Train loss: 1.1964771747589111 | Train acc: 49.75961685180664 | Test loss: 1.1375747919082642 | Test acc: 49.94452667236328\n",
            "Epoch: 7\n",
            "Train loss: 1.1047861576080322 | Train acc: 51.68269348144531 | Test loss: 1.0829076766967773 | Test acc: 55.69526672363281\n",
            "Epoch: 8\n",
            "Train loss: 1.0864824056625366 | Train acc: 53.365386962890625 | Test loss: 1.0213812589645386 | Test acc: 56.323970794677734\n",
            "Epoch: 9\n",
            "Train loss: 1.0096523761749268 | Train acc: 57.93269348144531 | Test loss: 1.2067512273788452 | Test acc: 53.328407287597656\n",
            "Epoch: 10\n",
            "Train loss: 1.0622494220733643 | Train acc: 53.125 | Test loss: 1.1848664283752441 | Test acc: 51.83062744140625\n",
            "Epoch: 11\n",
            "Train loss: 0.9759219884872437 | Train acc: 57.69230651855469 | Test loss: 0.9894790053367615 | Test acc: 56.58284378051758\n",
            "Epoch: 12\n",
            "Train loss: 1.0050513744354248 | Train acc: 57.451927185058594 | Test loss: 1.0145292282104492 | Test acc: 53.30990982055664\n",
            "Epoch: 13\n",
            "Train loss: 0.9842706322669983 | Train acc: 57.69230651855469 | Test loss: 1.0144147872924805 | Test acc: 53.95709991455078\n",
            "Epoch: 14\n",
            "Train loss: 0.9671334624290466 | Train acc: 58.89423370361328 | Test loss: 0.9777206778526306 | Test acc: 57.28550720214844\n",
            "Epoch: 15\n",
            "Train loss: 0.9251955151557922 | Train acc: 61.5384635925293 | Test loss: 0.9270422458648682 | Test acc: 60.521453857421875\n",
            "Epoch: 16\n",
            "Train loss: 0.9714013934135437 | Train acc: 60.33654022216797 | Test loss: 0.9240899085998535 | Test acc: 59.800296783447266\n",
            "Epoch: 17\n",
            "Train loss: 0.9087665677070618 | Train acc: 62.259620666503906 | Test loss: 1.0581128597259521 | Test acc: 54.4008903503418\n",
            "Epoch: 18\n",
            "Train loss: 0.8932859897613525 | Train acc: 62.259620666503906 | Test loss: 1.1204591989517212 | Test acc: 54.16050720214844\n",
            "Epoch: 19\n",
            "Train loss: 0.8878512978553772 | Train acc: 61.77885055541992 | Test loss: 0.9915058612823486 | Test acc: 61.6863899230957\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Note to self: learn more about Dropout layers, BatchNorm2d, weight_decay and momentum in optimizer because damn that accuracy is a lot better\n",
        "#also your testing and trainval splits are almost 50/50 probably not good"
      ],
      "metadata": {
        "id": "3XE4HQ7ybIUQ"
      },
      "execution_count": 98,
      "outputs": []
    }
  ]
}