{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7LhpxluXAy0g"
      },
      "outputs": [],
      "source": [
        "!pip install transformers evaluate datasets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eBq4mm7cA4Cp"
      },
      "outputs": [],
      "source": [
        "import requests\n",
        "import torch\n",
        "from PIL import Image\n",
        "from transformers import *\n",
        "from tqdm import tqdm\n",
        "\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "JlLN5LTVA5eJ"
      },
      "outputs": [],
      "source": [
        "# the model name\n",
        "model_name = \"google/vit-base-patch16-224\"\n",
        "# load the image processor\n",
        "image_processor = ViTImageProcessor.from_pretrained(model_name)\n",
        "# loading the pre-trained model\n",
        "model = ViTForImageClassification.from_pretrained(model_name).to(device)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "B5z-Sqz4BiPQ"
      },
      "outputs": [],
      "source": [
        "import urllib.parse as parse\n",
        "import os\n",
        "\n",
        "# a function to determine whether a string is a URL or not\n",
        "def is_url(string):\n",
        "    try:\n",
        "        result = parse.urlparse(string)\n",
        "        return all([result.scheme, result.netloc, result.path])\n",
        "    except:\n",
        "        return False\n",
        "    \n",
        "# a function to load an image\n",
        "def load_image(image_path):\n",
        "    if is_url(image_path):\n",
        "        return Image.open(requests.get(image_path, stream=True).raw)\n",
        "    elif os.path.exists(image_path):\n",
        "        return Image.open(image_path)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "MgfKn08vByse"
      },
      "outputs": [],
      "source": [
        "def get_prediction(model, url_or_path):\n",
        "  # load the image\n",
        "  img = load_image(url_or_path)\n",
        "  # preprocessing the image\n",
        "  pixel_values = image_processor(img, return_tensors=\"pt\")[\"pixel_values\"].to(device)\n",
        "  # perform inference\n",
        "  output = model(pixel_values)\n",
        "  # get the label id and return the class name\n",
        "  return model.config.id2label[int(output.logits.softmax(dim=1).argmax())]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "q8n-To7RsyPx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "aa4a7cbb-7411-4822-f3b3-e383b6396809"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Indian elephant, Elephas maximus'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "get_prediction(model, \"http://images.cocodataset.org/test-stuff2017/000000000128.jpg\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Loading our Dataset"
      ],
      "metadata": {
        "id": "suO4z5NCDU8v"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392,
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          ]
        },
        "outputId": "0e11acb7-06a8-4c22-815f-446cae5c0e83"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/6.21k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "394913b4097b46a7984797f5d1deaaff"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading metadata:   0%|          | 0.00/5.56k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d6e7d1b10c7d4f5daa699d507c11f2d4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading readme:   0%|          | 0.00/10.3k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "df26988483374f13b3f5b5249885314e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading and preparing dataset food101/default to /root/.cache/huggingface/datasets/food101/default/0.0.0/7cebe41a80fb2da3f08fcbef769c8874073a86346f7fb96dc0847d4dfc318295...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/5.00G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "82acbc3424b14a3583b58739b556045e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data files:   0%|          | 0/2 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "27228900fcc64b8e976c7cf674365f5e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/1.47M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3a90127f102749d49dc707462fa1493c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/489k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c85eb3cb9e364d65bf81da8d8695384d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating train split:   0%|          | 0/75750 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "59228c17fb39460aa14997c501c4c528"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating validation split:   0%|          | 0/25250 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "0acd2ec0c2a64e2997230aee8d6b9ef3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset food101 downloaded and prepared to /root/.cache/huggingface/datasets/food101/default/0.0.0/7cebe41a80fb2da3f08fcbef769c8874073a86346f7fb96dc0847d4dfc318295. Subsequent calls will reuse this data.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/2 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "dfae6990fa884f9fa6f4c87c066ee755"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "# download & load the dataset\n",
        "ds = load_dataset(\"food101\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Loading a Custom Dataset using `ImageFolder`\n",
        "Run the three below cells to load a custom dataset (that's not in the Hub) using `ImageFolder`"
      ],
      "metadata": {
        "id": "H9ZcQf_HDXl6"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "kF0He2BQcBSG"
      },
      "outputs": [],
      "source": [
        "import requests\n",
        "from tqdm import tqdm\n",
        "\n",
        "def get_file(url):\n",
        "  response = requests.get(url, stream=True)\n",
        "  total_size = int(response.headers.get('content-length', 0))\n",
        "  filename = None\n",
        "  content_disposition = response.headers.get('content-disposition')\n",
        "  if content_disposition:\n",
        "      parts = content_disposition.split(';')\n",
        "      for part in parts:\n",
        "          if 'filename' in part:\n",
        "              filename = part.split('=')[1].strip('\"')\n",
        "  if not filename:\n",
        "      filename = os.path.basename(url)\n",
        "  block_size = 1024 # 1 Kibibyte\n",
        "  tqdm_bar = tqdm(total=total_size, unit='iB', unit_scale=True)\n",
        "  with open(filename, 'wb') as file:\n",
        "      for data in response.iter_content(block_size):\n",
        "          tqdm_bar.update(len(data))\n",
        "          file.write(data)\n",
        "  tqdm_bar.close()\n",
        "  print(f\"Downloaded {filename} ({total_size} bytes)\")\n",
        "  return filename"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HREIgilFbW_S",
        "outputId": "5df33354-ecd9-4b1a-dc54-fb9d7ab052c8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 865M/865M [00:47<00:00, 18.1MiB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloaded valid.zip (864538487 bytes)\n",
            "Extracting https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/valid.zip\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 5.74G/5.74G [05:39<00:00, 16.9MiB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloaded train.zip (5736557430 bytes)\n",
            "Extracting https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/train.zip\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 5.53G/5.53G [04:53<00:00, 18.9MiB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloaded test.zip (5528640507 bytes)\n",
            "Extracting https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/test.zip\n"
          ]
        }
      ],
      "source": [
        "import zipfile\n",
        "import os\n",
        "\n",
        "def download_and_extract_dataset():\n",
        "  # dataset from https://github.com/udacity/dermatologist-ai\n",
        "  # 5.3GB\n",
        "  train_url = \"https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/train.zip\"\n",
        "  # 824.5MB\n",
        "  valid_url = \"https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/valid.zip\"\n",
        "  # 5.1GB\n",
        "  test_url  = \"https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/test.zip\"\n",
        "  for i, download_link in enumerate([valid_url, train_url, test_url]):\n",
        "    data_dir = get_file(download_link)\n",
        "    print(\"Extracting\", download_link)\n",
        "    with zipfile.ZipFile(data_dir, \"r\") as z:\n",
        "      z.extractall(\"data\")\n",
        "    # remove the temp file\n",
        "    os.remove(data_dir)\n",
        "\n",
        "# comment the below line if you already downloaded the dataset\n",
        "download_and_extract_dataset()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "# load the custom dataset\n",
        "ds = load_dataset(\"imagefolder\", data_dir=\"data\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0,
          "referenced_widgets": [
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            "137a450619fc4630b7754d3539908288",
            "c00d60b00d2f4d22be325af0cb10b234",
            "c9518d498ce54f2c9bafde7914ddc51b",
            "ec62031c9a6240069a52da7354173622",
            "4706d251c340427ebb468e4d8a333031",
            "b799085f7ff84b4496a64587066d4645",
            "b3324a67f18449faaec765ea2248a6d8",
            "bd77d6d98d0249b3bc99c94d46e7d7a1",
            "8060cd481cdd4229878a871e9ae411d5",
            "5a2db2886a72478da3ec0b67f8e88c48",
            "a99e7f4228fb4a8e8589e30677ccde74",
            "c4f8b2b6f66c4108a12944505952c1ea",
            "c069ba18441347d2875a8c366b23c3ff",
            "0cafd43406ac46c6b307adb6c36746df",
            "42a4cd25bb6a46a9a3b4fe4b6da96eab",
            "c02ba744e0414508bc0e24e015c5ef57",
            "017d3b681a1248eeaac5787621356258",
            "83c008a35cb24407ae96ac46a6ca4c2a",
            "4895214231854f0ab17dc98a711772b3",
            "e34ff62351d8441593698b13d46bc18e",
            "a66a957b6c15453c8a525bcaf2f2a805",
            "f4bc4c6164624dcab5f8fe95e7ad5a31",
            "4171150fd5394d4989498ce951839a96",
            "4cfcbd9389734994997e4f0812f018c8",
            "6fd1258d4d374358ba261425b5260740",
            "a21b1102a4d842b394adba0a1e758a39",
            "27ab1ed3b5dd413991017b9fecc0903c"
          ]
        },
        "id": "LjzUza9MwBgz",
        "outputId": "9b33adf0-b7ec-42d6-9c3c-fc40b7107469"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Resolving data files:   0%|          | 0/2000 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "38389509624645cf977798472b81886c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Resolving data files:   0%|          | 0/600 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e9657262a4714ecf8884f6354f32c6a3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Resolving data files:   0%|          | 0/150 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b799085f7ff84b4496a64587066d4645"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:datasets.builder:Found cached dataset imagefolder (/root/.cache/huggingface/datasets/imagefolder/default-6fa39cb8bd2286d1/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/3 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "017d3b681a1248eeaac5787621356258"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Exploring the Data"
      ],
      "metadata": {
        "id": "QVjb_p9kDr5Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ds"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dX_ABF25z-_w",
        "outputId": "9842bde2-9aec-45c3-a9f4-bd8c76a34f58"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatasetDict({\n",
              "    train: Dataset({\n",
              "        features: ['image', 'label'],\n",
              "        num_rows: 75750\n",
              "    })\n",
              "    validation: Dataset({\n",
              "        features: ['image', 'label'],\n",
              "        num_rows: 25250\n",
              "    })\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "MgxqXVVrITqO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "11bb4f17-9700-427e-c7fd-cba027ec71b4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ClassLabel(names=['apple_pie', 'baby_back_ribs', 'baklava', 'beef_carpaccio', 'beef_tartare', 'beet_salad', 'beignets', 'bibimbap', 'bread_pudding', 'breakfast_burrito', 'bruschetta', 'caesar_salad', 'cannoli', 'caprese_salad', 'carrot_cake', 'ceviche', 'cheesecake', 'cheese_plate', 'chicken_curry', 'chicken_quesadilla', 'chicken_wings', 'chocolate_cake', 'chocolate_mousse', 'churros', 'clam_chowder', 'club_sandwich', 'crab_cakes', 'creme_brulee', 'croque_madame', 'cup_cakes', 'deviled_eggs', 'donuts', 'dumplings', 'edamame', 'eggs_benedict', 'escargots', 'falafel', 'filet_mignon', 'fish_and_chips', 'foie_gras', 'french_fries', 'french_onion_soup', 'french_toast', 'fried_calamari', 'fried_rice', 'frozen_yogurt', 'garlic_bread', 'gnocchi', 'greek_salad', 'grilled_cheese_sandwich', 'grilled_salmon', 'guacamole', 'gyoza', 'hamburger', 'hot_and_sour_soup', 'hot_dog', 'huevos_rancheros', 'hummus', 'ice_cream', 'lasagna', 'lobster_bisque', 'lobster_roll_sandwich', 'macaroni_and_cheese', 'macarons', 'miso_soup', 'mussels', 'nachos', 'omelette', 'onion_rings', 'oysters', 'pad_thai', 'paella', 'pancakes', 'panna_cotta', 'peking_duck', 'pho', 'pizza', 'pork_chop', 'poutine', 'prime_rib', 'pulled_pork_sandwich', 'ramen', 'ravioli', 'red_velvet_cake', 'risotto', 'samosa', 'sashimi', 'scallops', 'seaweed_salad', 'shrimp_and_grits', 'spaghetti_bolognese', 'spaghetti_carbonara', 'spring_rolls', 'steak', 'strawberry_shortcake', 'sushi', 'tacos', 'takoyaki', 'tiramisu', 'tuna_tartare', 'waffles'], id=None)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "labels = ds[\"train\"].features[\"label\"]\n",
        "labels"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "ozNlqVN3IgnR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "b74c1570-de7c-4843-8ede-fe5e877468cb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'beignets'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "labels.int2str(ds[\"train\"][532][\"label\"])"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def show_image_grid(dataset, split, grid_size=(4,4)):\n",
        "    # Select random images from the given split\n",
        "    indices = random.sample(range(len(dataset[split])), grid_size[0]*grid_size[1])\n",
        "    images = [dataset[split][i][\"image\"] for i in indices]\n",
        "    labels = [dataset[split][i][\"label\"] for i in indices]\n",
        "    \n",
        "    # Display the images in a grid\n",
        "    fig, axes = plt.subplots(nrows=grid_size[0], ncols=grid_size[1], figsize=(8,8))\n",
        "    for i, ax in enumerate(axes.flat):\n",
        "        ax.imshow(images[i])\n",
        "        ax.axis('off')\n",
        "        ax.set_title(ds[\"train\"].features[\"label\"].int2str(labels[i]))\n",
        "    \n",
        "    plt.show()"
      ],
      "metadata": {
        "id": "FEV3yejjE7GV"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "show_image_grid(ds, \"train\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "id": "YwU_YpNYE8af",
        "outputId": "43b98331-a68f-439f-e6e1-6292402ae1cc"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 16 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Preprocessing the Data"
      ],
      "metadata": {
        "id": "W8jdhJCQKCOA"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "9x5QuhV8IwXB"
      },
      "outputs": [],
      "source": [
        "def transform(examples):\n",
        "  # convert all images to RGB format, then preprocessing it\n",
        "  # using our image processor\n",
        "  inputs = image_processor([img.convert(\"RGB\") for img in examples[\"image\"]], return_tensors=\"pt\")\n",
        "  # we also shouldn't forget about the labels\n",
        "  inputs[\"labels\"] = examples[\"label\"]\n",
        "  return inputs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "vY7oXLDZJBaX"
      },
      "outputs": [],
      "source": [
        "# use the with_transform() method to apply the transform to the dataset on the fly during training\n",
        "dataset = ds.with_transform(transform)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "WbWrF63YQdsE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0e4c0b60-e9c1-48c8-d755-88d6d8cfb150"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "torch.Size([3, 224, 224])\n",
            "6\n"
          ]
        }
      ],
      "source": [
        "for item in dataset[\"train\"]:\n",
        "  print(item[\"pixel_values\"].shape)\n",
        "  print(item[\"labels\"])\n",
        "  break"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "CnrUwcqwKTOV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe094d75-c537-48e7-bfc9-38b8df4db9fa"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['apple_pie',\n",
              " 'baby_back_ribs',\n",
              " 'baklava',\n",
              " 'beef_carpaccio',\n",
              " 'beef_tartare',\n",
              " 'beet_salad',\n",
              " 'beignets',\n",
              " 'bibimbap',\n",
              " 'bread_pudding',\n",
              " 'breakfast_burrito',\n",
              " 'bruschetta',\n",
              " 'caesar_salad',\n",
              " 'cannoli',\n",
              " 'caprese_salad',\n",
              " 'carrot_cake',\n",
              " 'ceviche',\n",
              " 'cheesecake',\n",
              " 'cheese_plate',\n",
              " 'chicken_curry',\n",
              " 'chicken_quesadilla',\n",
              " 'chicken_wings',\n",
              " 'chocolate_cake',\n",
              " 'chocolate_mousse',\n",
              " 'churros',\n",
              " 'clam_chowder',\n",
              " 'club_sandwich',\n",
              " 'crab_cakes',\n",
              " 'creme_brulee',\n",
              " 'croque_madame',\n",
              " 'cup_cakes',\n",
              " 'deviled_eggs',\n",
              " 'donuts',\n",
              " 'dumplings',\n",
              " 'edamame',\n",
              " 'eggs_benedict',\n",
              " 'escargots',\n",
              " 'falafel',\n",
              " 'filet_mignon',\n",
              " 'fish_and_chips',\n",
              " 'foie_gras',\n",
              " 'french_fries',\n",
              " 'french_onion_soup',\n",
              " 'french_toast',\n",
              " 'fried_calamari',\n",
              " 'fried_rice',\n",
              " 'frozen_yogurt',\n",
              " 'garlic_bread',\n",
              " 'gnocchi',\n",
              " 'greek_salad',\n",
              " 'grilled_cheese_sandwich',\n",
              " 'grilled_salmon',\n",
              " 'guacamole',\n",
              " 'gyoza',\n",
              " 'hamburger',\n",
              " 'hot_and_sour_soup',\n",
              " 'hot_dog',\n",
              " 'huevos_rancheros',\n",
              " 'hummus',\n",
              " 'ice_cream',\n",
              " 'lasagna',\n",
              " 'lobster_bisque',\n",
              " 'lobster_roll_sandwich',\n",
              " 'macaroni_and_cheese',\n",
              " 'macarons',\n",
              " 'miso_soup',\n",
              " 'mussels',\n",
              " 'nachos',\n",
              " 'omelette',\n",
              " 'onion_rings',\n",
              " 'oysters',\n",
              " 'pad_thai',\n",
              " 'paella',\n",
              " 'pancakes',\n",
              " 'panna_cotta',\n",
              " 'peking_duck',\n",
              " 'pho',\n",
              " 'pizza',\n",
              " 'pork_chop',\n",
              " 'poutine',\n",
              " 'prime_rib',\n",
              " 'pulled_pork_sandwich',\n",
              " 'ramen',\n",
              " 'ravioli',\n",
              " 'red_velvet_cake',\n",
              " 'risotto',\n",
              " 'samosa',\n",
              " 'sashimi',\n",
              " 'scallops',\n",
              " 'seaweed_salad',\n",
              " 'shrimp_and_grits',\n",
              " 'spaghetti_bolognese',\n",
              " 'spaghetti_carbonara',\n",
              " 'spring_rolls',\n",
              " 'steak',\n",
              " 'strawberry_shortcake',\n",
              " 'sushi',\n",
              " 'tacos',\n",
              " 'takoyaki',\n",
              " 'tiramisu',\n",
              " 'tuna_tartare',\n",
              " 'waffles']"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "# extract the labels for our dataset\n",
        "labels = ds[\"train\"].features[\"label\"].names\n",
        "labels"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "ZUukexdrJGob"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "\n",
        "def collate_fn(batch):\n",
        "  return {\n",
        "      \"pixel_values\": torch.stack([x[\"pixel_values\"] for x in batch]),\n",
        "      \"labels\": torch.tensor([x[\"labels\"] for x in batch]),\n",
        "  }"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Defining the Metrics"
      ],
      "metadata": {
        "id": "mNT_iBYyKGAE"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "crXIbHCeJYFs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81,
          "referenced_widgets": [
            "a6f5330da3834963b3a47f9f9bb6a657",
            "9a0cee1fc0644c768a1e7cfc7bb65469",
            "c303a871150b40cf9209fc3f6da02e7d",
            "9422c52eef304328a65551949c4eb982",
            "7834179cb085439c96b265e34ca19309",
            "2e7a21ab2dfc4858bd7d43451b16a179",
            "9e3e30be4469468d8451dc6761d16bf6",
            "343707c48e984b26a09c4adc25a510a5",
            "444820c45f1241c59d0f7d1082e4c8d7",
            "1933b7094ac4474abc1f48605ca4e0c4",
            "db1683f3d8f44d4797dbc2a0f808bd2a",
            "40eaac98a5b642b28298028de5b0a8f0",
            "9185dd3b67964f1191210a7b104c4a88",
            "5280d259979548ae9b302d3bfd06a1bd",
            "1aa0c864c04d42329974b10668dd5eb7",
            "a2699e131c4448d5bcc890f1f0c22c63",
            "f40b643bece248458e3373e19f456325",
            "dcf80cee15294d12aa9f5f2648a95028",
            "1d0d738bddde42df9c434fe77f5c0307",
            "c8aeb58e12b8427bb547022d7076a38b",
            "04e02d2b23c149389db0cb519880b175",
            "0f67af90cad747b99865abef12dd16a9"
          ]
        },
        "outputId": "43655744-224f-43bd-ebc1-846a1ca66b81"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/4.20k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a6f5330da3834963b3a47f9f9bb6a657"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/6.77k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "40eaac98a5b642b28298028de5b0a8f0"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from evaluate import load\n",
        "import numpy as np\n",
        "\n",
        "# load the accuracy and f1 metrics from the evaluate module\n",
        "accuracy = load(\"accuracy\")\n",
        "f1 = load(\"f1\")\n",
        "\n",
        "def compute_metrics(eval_pred):\n",
        "  # compute the accuracy and f1 scores & return them\n",
        "  accuracy_score = accuracy.compute(predictions=np.argmax(eval_pred.predictions, axis=1), references=eval_pred.label_ids)\n",
        "  f1_score = f1.compute(predictions=np.argmax(eval_pred.predictions, axis=1), references=eval_pred.label_ids, average=\"macro\")\n",
        "  return {**accuracy_score, **f1_score}"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Training the Model"
      ],
      "metadata": {
        "id": "2WNJaZeYKJZH"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "U1MmFNVLKw_2"
      },
      "outputs": [],
      "source": [
        "# load the ViT model\n",
        "model = ViTForImageClassification.from_pretrained(\n",
        "    model_name,\n",
        "    num_labels=len(labels),\n",
        "    id2label={str(i): c for i, c in enumerate(labels)},\n",
        "    label2id={c: str(i) for i, c in enumerate(labels)},\n",
        "    ignore_mismatched_sizes=True,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "RNnG1GUUK7nj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6390cd94-ad97-4413-f85c-5bc823e2a8ff"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "PyTorch: setting up devices\n"
          ]
        }
      ],
      "source": [
        "from transformers import TrainingArguments\n",
        "\n",
        "training_args = TrainingArguments(\n",
        "  output_dir=\"./vit-base-food\", # output directory\n",
        "  # output_dir=\"./vit-base-skin-cancer\",\n",
        "  per_device_train_batch_size=32, # batch size per device during training\n",
        "  evaluation_strategy=\"steps\",    # evaluation strategy to adopt during training\n",
        "  num_train_epochs=3,             # total number of training epochs\n",
        "  # fp16=True,                    # use mixed precision\n",
        "  save_steps=1000,                # number of update steps before saving checkpoint\n",
        "  eval_steps=1000,                # number of update steps before evaluating\n",
        "  logging_steps=1000,             # number of update steps before logging\n",
        "  # save_steps=50,\n",
        "  # eval_steps=50,\n",
        "  # logging_steps=50,\n",
        "  save_total_limit=2,             # limit the total amount of checkpoints on disk\n",
        "  remove_unused_columns=False,    # remove unused columns from the dataset\n",
        "  push_to_hub=False,              # do not push the model to the hub\n",
        "  report_to='tensorboard',        # report metrics to tensorboard\n",
        "  load_best_model_at_end=True,    # load the best model at the end of training\n",
        ")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "3n8Cv48_QKzr"
      },
      "outputs": [],
      "source": [
        "from transformers import Trainer\n",
        "\n",
        "trainer = Trainer(\n",
        "    model=model,                        # the instantiated 🤗 Transformers model to be trained\n",
        "    args=training_args,                 # training arguments, defined above\n",
        "    data_collator=collate_fn,           # the data collator that will be used for batching\n",
        "    compute_metrics=compute_metrics,    # the metrics function that will be used for evaluation\n",
        "    train_dataset=dataset[\"train\"],     # training dataset\n",
        "    eval_dataset=dataset[\"validation\"], # evaluation dataset\n",
        "    tokenizer=image_processor,          # the processor that will be used for preprocessing the images\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "wUUoQyh-QPED",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "eb399913-48db-4af9-b8a9-ec4bc67adc0a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.9/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
            "  warnings.warn(\n",
            "***** Running training *****\n",
            "  Num examples = 75750\n",
            "  Num Epochs = 3\n",
            "  Instantaneous batch size per device = 32\n",
            "  Total train batch size (w. parallel, distributed & accumulation) = 32\n",
            "  Gradient Accumulation steps = 1\n",
            "  Total optimization steps = 7104\n",
            "  Number of trainable parameters = 85876325\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='7104' max='7104' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [7104/7104 3:46:15, Epoch 3/3]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Step</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>F1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1000</td>\n",
              "      <td>1.440300</td>\n",
              "      <td>0.582373</td>\n",
              "      <td>0.853149</td>\n",
              "      <td>0.852764</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2000</td>\n",
              "      <td>0.703100</td>\n",
              "      <td>0.453642</td>\n",
              "      <td>0.878297</td>\n",
              "      <td>0.878230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3000</td>\n",
              "      <td>0.434700</td>\n",
              "      <td>0.409464</td>\n",
              "      <td>0.886455</td>\n",
              "      <td>0.886492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4000</td>\n",
              "      <td>0.310100</td>\n",
              "      <td>0.394801</td>\n",
              "      <td>0.889188</td>\n",
              "      <td>0.888990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5000</td>\n",
              "      <td>0.245100</td>\n",
              "      <td>0.383308</td>\n",
              "      <td>0.895168</td>\n",
              "      <td>0.895035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6000</td>\n",
              "      <td>0.115700</td>\n",
              "      <td>0.379927</td>\n",
              "      <td>0.896515</td>\n",
              "      <td>0.896743</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7000</td>\n",
              "      <td>0.108100</td>\n",
              "      <td>0.376985</td>\n",
              "      <td>0.898059</td>\n",
              "      <td>0.898311</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-1000\n",
            "Configuration saved in ./vit-base-food/checkpoint-1000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-1000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-1000/preprocessor_config.json\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-2000\n",
            "Configuration saved in ./vit-base-food/checkpoint-2000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-2000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-2000/preprocessor_config.json\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-3000\n",
            "Configuration saved in ./vit-base-food/checkpoint-3000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-3000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-3000/preprocessor_config.json\n",
            "Deleting older checkpoint [vit-base-food/checkpoint-1000] due to args.save_total_limit\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-4000\n",
            "Configuration saved in ./vit-base-food/checkpoint-4000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-4000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-4000/preprocessor_config.json\n",
            "Deleting older checkpoint [vit-base-food/checkpoint-2000] due to args.save_total_limit\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-5000\n",
            "Configuration saved in ./vit-base-food/checkpoint-5000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-5000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-5000/preprocessor_config.json\n",
            "Deleting older checkpoint [vit-base-food/checkpoint-3000] due to args.save_total_limit\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-6000\n",
            "Configuration saved in ./vit-base-food/checkpoint-6000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-6000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-6000/preprocessor_config.json\n",
            "Deleting older checkpoint [vit-base-food/checkpoint-4000] due to args.save_total_limit\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n",
            "Saving model checkpoint to ./vit-base-food/checkpoint-7000\n",
            "Configuration saved in ./vit-base-food/checkpoint-7000/config.json\n",
            "Model weights saved in ./vit-base-food/checkpoint-7000/pytorch_model.bin\n",
            "Image processor saved in ./vit-base-food/checkpoint-7000/preprocessor_config.json\n",
            "Deleting older checkpoint [vit-base-food/checkpoint-5000] due to args.save_total_limit\n",
            "\n",
            "\n",
            "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
            "\n",
            "\n",
            "Loading best model from ./vit-base-food/checkpoint-7000 (score: 0.37698468565940857).\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainOutput(global_step=7104, training_loss=0.47385838654664186, metrics={'train_runtime': 13577.408, 'train_samples_per_second': 16.737, 'train_steps_per_second': 0.523, 'total_flos': 1.76256801415296e+19, 'train_loss': 0.47385838654664186, 'epoch': 3.0})"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "# start training\n",
        "trainer.train()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "akZ0-H5YQSuJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 211
        },
        "outputId": "85b9cf1b-3fca-47ed-b4fe-5de2839e8cd5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "***** Running Evaluation *****\n",
            "  Num examples = 25250\n",
            "  Batch size = 8\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='3157' max='3157' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [3157/3157 08:06]\n",
              "    </div>\n",
              "    "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'eval_loss': 0.37698468565940857,\n",
              " 'eval_accuracy': 0.8980594059405941,\n",
              " 'eval_f1': 0.8983106653355424,\n",
              " 'eval_runtime': 487.0104,\n",
              " 'eval_samples_per_second': 51.847,\n",
              " 'eval_steps_per_second': 6.482,\n",
              " 'epoch': 3.0}"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "# trainer.evaluate(dataset[\"test\"])\n",
        "trainer.evaluate()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wAZFCk5Gd1p0"
      },
      "outputs": [],
      "source": [
        "# start tensorboard\n",
        "# %load_ext tensorboard\n",
        "%reload_ext tensorboard\n",
        "%tensorboard --logdir ./vit-base-food/runs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H_SsuMpFafPe"
      },
      "source": [
        "## Alternatively: Training using PyTorch Loop\n",
        "Run the two below cells to fine-tune using a regular PyTorch loop if you want."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "C29idUGDd2yW"
      },
      "outputs": [],
      "source": [
        "# Training loop\n",
        "from torch.utils.tensorboard import SummaryWriter\n",
        "from torch.optim import AdamW\n",
        "from torch.utils.data import DataLoader\n",
        "\n",
        "batch_size = 32\n",
        "\n",
        "train_dataset_loader = DataLoader(dataset[\"train\"], collate_fn=collate_fn, batch_size=batch_size, shuffle=True)\n",
        "valid_dataset_loader = DataLoader(dataset[\"validation\"], collate_fn=collate_fn, batch_size=batch_size, shuffle=True)\n",
        "\n",
        "# define the optimizer\n",
        "optimizer = AdamW(model.parameters(), lr=1e-5)\n",
        "\n",
        "log_dir = \"./image-classification/tensorboard\"\n",
        "summary_writer = SummaryWriter(log_dir=log_dir)\n",
        "\n",
        "num_epochs = 3\n",
        "model = model.to(device)\n",
        "# print some statistics before training\n",
        "# number of training steps\n",
        "n_train_steps = num_epochs * len(train_dataset_loader)\n",
        "# number of validation steps\n",
        "n_valid_steps = len(valid_dataset_loader)\n",
        "# current training step\n",
        "current_step = 0\n",
        "# logging, eval & save steps\n",
        "save_steps = 1000\n",
        "\n",
        "def compute_metrics(eval_pred):\n",
        "  accuracy_score = accuracy.compute(predictions=eval_pred.predictions, references=eval_pred.label_ids)\n",
        "  f1_score = f1.compute(predictions=eval_pred.predictions, references=eval_pred.label_ids, average=\"macro\")\n",
        "  return {**accuracy_score, **f1_score}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2v6dNtUcd7-G"
      },
      "outputs": [],
      "source": [
        "for epoch in range(num_epochs):\n",
        "    # set the model to training mode\n",
        "    model.train()\n",
        "    # initialize the training loss\n",
        "    train_loss = 0\n",
        "    # initialize the progress bar\n",
        "    progress_bar = tqdm(range(current_step, n_train_steps), \"Training\", dynamic_ncols=True, ncols=80)\n",
        "    for batch in train_dataset_loader:\n",
        "      if (current_step+1) % save_steps == 0:\n",
        "        ### evaluation code ###\n",
        "        # evaluate on the validation set\n",
        "        # if the current step is a multiple of the save steps\n",
        "        print()\n",
        "        print(f\"Validation at step {current_step}...\")\n",
        "        print()\n",
        "        # set the model to evaluation mode\n",
        "        model.eval()\n",
        "        # initialize our lists that store the predictions and the labels\n",
        "        predictions, labels = [], []\n",
        "        # initialize the validation loss\n",
        "        valid_loss = 0\n",
        "        for batch in valid_dataset_loader:\n",
        "            # get the batch\n",
        "            pixel_values = batch[\"pixel_values\"].to(device)\n",
        "            label_ids = batch[\"labels\"].to(device)\n",
        "            # forward pass\n",
        "            outputs = model(pixel_values=pixel_values, labels=label_ids)\n",
        "            # get the loss\n",
        "            loss = outputs.loss\n",
        "            valid_loss += loss.item()\n",
        "            # free the GPU memory\n",
        "            logits = outputs.logits.detach().cpu()\n",
        "            # add the predictions to the list\n",
        "            predictions.extend(logits.argmax(dim=-1).tolist())\n",
        "            # add the labels to the list\n",
        "            labels.extend(label_ids.tolist())\n",
        "        # make the EvalPrediction object that the compute_metrics function expects\n",
        "        eval_prediction = EvalPrediction(predictions=predictions, label_ids=labels)\n",
        "        # compute the metrics\n",
        "        metrics = compute_metrics(eval_prediction)\n",
        "        # print the stats\n",
        "        print()\n",
        "        print(f\"Epoch: {epoch}, Step: {current_step}, Train Loss: {train_loss / save_steps:.4f}, \" + \n",
        "              f\"Valid Loss: {valid_loss / n_valid_steps:.4f}, Accuracy: {metrics['accuracy']}, \" +\n",
        "              f\"F1 Score: {metrics['f1']}\")\n",
        "        print()\n",
        "        # log the metrics\n",
        "        summary_writer.add_scalar(\"valid_loss\", valid_loss / n_valid_steps, global_step=current_step)\n",
        "        summary_writer.add_scalar(\"accuracy\", metrics[\"accuracy\"], global_step=current_step)\n",
        "        summary_writer.add_scalar(\"f1\", metrics[\"f1\"], global_step=current_step)\n",
        "        # save the model\n",
        "        model.save_pretrained(f\"./vit-base-food/checkpoint-{current_step}\")\n",
        "        image_processor.save_pretrained(f\"./vit-base-food/checkpoint-{current_step}\")\n",
        "        # get the model back to train mode\n",
        "        model.train()\n",
        "        # reset the train and valid loss\n",
        "        train_loss, valid_loss = 0, 0\n",
        "      ### training code below ###\n",
        "      # get the batch & convert to tensor\n",
        "      pixel_values = batch[\"pixel_values\"].to(device)\n",
        "      labels = batch[\"labels\"].to(device)\n",
        "      # forward pass\n",
        "      outputs = model(pixel_values=pixel_values, labels=labels)\n",
        "      # get the loss\n",
        "      loss = outputs.loss\n",
        "      # backward pass\n",
        "      loss.backward()\n",
        "      # update the weights\n",
        "      optimizer.step()\n",
        "      # zero the gradients\n",
        "      optimizer.zero_grad()\n",
        "      # log the loss\n",
        "      loss_v = loss.item()\n",
        "      train_loss += loss_v\n",
        "      # increment the step\n",
        "      current_step += 1\n",
        "      progress_bar.update(1)\n",
        "      # log the training loss\n",
        "      summary_writer.add_scalar(\"train_loss\", loss_v, global_step=current_step)\n",
        "        "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Performing Inference"
      ],
      "metadata": {
        "id": "5nyMP4VRC_dG"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nuOoflvoen7E"
      },
      "outputs": [],
      "source": [
        "# load the best model, change the checkpoint number to the best checkpoint\n",
        "# if the last checkpoint is the best, then ignore this cell\n",
        "best_checkpoint = 7000\n",
        "# best_checkpoint = 150\n",
        "model = ViTForImageClassification.from_pretrained(f\"./vit-base-food/checkpoint-{best_checkpoint}\").to(device)\n",
        "# model = ViTForImageClassification.from_pretrained(f\"./vit-base-skin-cancer/checkpoint-{best_checkpoint}\").to(device)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "PwI6sf8PPReE",
        "outputId": "851ba75d-374c-483f-8e32-2fd38de848f0"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'sushi'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ],
      "source": [
        "get_prediction(model, \"https://images.pexels.com/photos/858496/pexels-photo-858496.jpeg?auto=compress&cs=tinysrgb&w=600&lazy=load\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "pkmjg6hGQ6DZ"
      },
      "outputs": [],
      "source": [
        "def get_prediction_probs(model, url_or_path, num_classes=3):\n",
        "    # load the image\n",
        "    img = load_image(url_or_path)\n",
        "    # preprocessing the image\n",
        "    pixel_values = image_processor(img, return_tensors=\"pt\")[\"pixel_values\"].to(device)\n",
        "    # perform inference\n",
        "    output = model(pixel_values)\n",
        "    # get the top k classes and probabilities\n",
        "    probs, indices = torch.topk(output.logits.softmax(dim=1), k=num_classes)\n",
        "    # get the class labels\n",
        "    id2label = model.config.id2label\n",
        "    classes = [id2label[idx.item()] for idx in indices[0]]\n",
        "    # convert the probabilities to a list\n",
        "    probs = probs.squeeze().tolist()\n",
        "    # create a dictionary with the class names and probabilities\n",
        "    results = dict(zip(classes, probs))\n",
        "    return results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N0pFDs9CRhqX",
        "outputId": "18f4cc0b-86fe-4575-c7d4-82b832938b56"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'greek_salad': 0.9658474326133728,\n",
              " 'caesar_salad': 0.019217027351260185,\n",
              " 'beet_salad': 0.008294313214719296}"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "# example 1\n",
        "get_prediction_probs(model, \"https://images.pexels.com/photos/406152/pexels-photo-406152.jpeg?auto=compress&cs=tinysrgb&w=600\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "urU-gg-gRjkN",
        "outputId": "6ff8b804-beea-4136-988d-2eb40c732205"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'grilled_cheese_sandwich': 0.9855711460113525,\n",
              " 'waffles': 0.0030371786560863256,\n",
              " 'club_sandwich': 0.0017941497499123216}"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "# example 2\n",
        "get_prediction_probs(model, \"https://images.pexels.com/photos/920220/pexels-photo-920220.jpeg?auto=compress&cs=tinysrgb&w=600\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nHtsyIRLV-3A",
        "outputId": "bbba9101-6884-4b2b-b7c6-eba4e70fbe10"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'donuts': 0.9919546246528625,\n",
              " 'cup_cakes': 0.0018467127811163664,\n",
              " 'beignets': 0.0009919782169163227}"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "# example 3\n",
        "get_prediction_probs(model, \"https://images.pexels.com/photos/3338681/pexels-photo-3338681.jpeg?auto=compress&cs=tinysrgb&w=600\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qbO_d45dXtwh",
        "outputId": "ef11eaab-abc9-4519-957e-fbb057d07c8e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'deviled_eggs': 0.9846165180206299,\n",
              " 'caprese_salad': 0.0012617064639925957,\n",
              " 'ravioli': 0.001060450915247202,\n",
              " 'beet_salad': 0.0008713295101188123,\n",
              " 'scallops': 0.0005976424436084926,\n",
              " 'gnocchi': 0.0005376451299525797,\n",
              " 'fried_calamari': 0.0005195785779505968,\n",
              " 'caesar_salad': 0.0003912363899871707,\n",
              " 'samosa': 0.0003842405858449638,\n",
              " 'dumplings': 0.00036707069375552237}"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ],
      "source": [
        "# example 4\n",
        "get_prediction_probs(model, \"https://images.pexels.com/photos/806457/pexels-photo-806457.jpeg?auto=compress&cs=tinysrgb&w=600\", num_classes=10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "id": "NAhzhcbhXyYA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "98b811a4-b43f-4c87-b7c2-fcc678281157"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'fried_rice': 0.8101670145988464,\n",
              " 'paella': 0.06818010658025742,\n",
              " 'steak': 0.015688087791204453}"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ],
      "source": [
        "get_prediction_probs(model, \"https://images.pexels.com/photos/1624487/pexels-photo-1624487.jpeg?auto=compress&cs=tinysrgb&w=600\")"
      ]
    }
  ],
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