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313/313 [03:18<00:00,  1.58it/s]"}}}},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":5441,"databundleVersionId":38425,"sourceType":"competition"}],"dockerImageVersionId":30786,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Visual Transformer with Linformer\n\nTraining Visual Transformer on *Dogs vs Cats Data*\n\n* Dogs vs. Cats Redux: Kernels Edition - https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition\n* Base Code - https://www.kaggle.com/reukki/pytorch-cnn-tutorial-with-cats-and-dogs/\n* Efficient Attention Implementation - https://github.com/lucidrains/vit-pytorch#efficient-attention","metadata":{"latex_metadata":{"author":"Aditya Mishra","title":"Visual Transformer | Cats&Dogs Edition","twitter":"@adi_myth"}}},{"cell_type":"code","source":"!pip -q install vit_pytorch linformer","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.128122Z","start_time":"2024-10-31T13:52:28.784225Z"},"id":"s_z7TuN_RIOK","execution":{"iopub.status.busy":"2024-10-31T14:11:54.782669Z","iopub.execute_input":"2024-10-31T14:11:54.783728Z","iopub.status.idle":"2024-10-31T14:14:24.495918Z","shell.execute_reply.started":"2024-10-31T14:11:54.783667Z","shell.execute_reply":"2024-10-31T14:14:24.494456Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Import Libraries","metadata":{"id":"IDT1Xwv9RZXb"}},{"cell_type":"code","source":"from __future__ import print_function\n\nimport glob\nfrom itertools import chain\nimport os\nimport random\nimport zipfile\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom linformer import Linformer\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom torch.optim.lr_scheduler import StepLR\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import datasets, transforms\nfrom tqdm.notebook import tqdm\n\nfrom vit_pytorch.efficient import ViT\n","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.136999Z","start_time":"2024-10-31T13:52:30.132128Z"},"id":"qq-e52uORIVg","execution":{"iopub.status.busy":"2024-10-31T14:04:05.683708Z","iopub.execute_input":"2024-10-31T14:04:05.684116Z","iopub.status.idle":"2024-10-31T14:04:09.838129Z","shell.execute_reply.started":"2024-10-31T14:04:05.684074Z","shell.execute_reply":"2024-10-31T14:04:09.834135Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(f\"Torch: {torch.__version__}\")","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.146731Z","start_time":"2024-10-31T13:52:30.143412Z"},"id":"pV-E0IFHRITw","outputId":"f4221b45-a2bf-479f-ecdb-8df9e836312a","execution":{"iopub.status.busy":"2024-10-31T14:04:58.13504Z","iopub.execute_input":"2024-10-31T14:04:58.135481Z","iopub.status.idle":"2024-10-31T14:04:58.141366Z","shell.execute_reply.started":"2024-10-31T14:04:58.135436Z","shell.execute_reply":"2024-10-31T14:04:58.140127Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Training settings\nbatch_size = 64\nepochs = 20\nlr = 3e-5\ngamma = 0.7\nseed = 42","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.154426Z","start_time":"2024-10-31T13:52:30.151272Z"},"id":"GEoNmg0aQVf9","execution":{"iopub.status.busy":"2024-10-31T14:04:09.841395Z","iopub.status.idle":"2024-10-31T14:04:09.842044Z","shell.execute_reply.started":"2024-10-31T14:04:09.841721Z","shell.execute_reply":"2024-10-31T14:04:09.841752Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def seed_everything(seed):\n    random.seed(seed)\n    os.environ['PYTHONHASHSEED'] = str(seed)\n    np.random.seed(seed)\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed(seed)\n    torch.cuda.manual_seed_all(seed)\n    torch.backends.cudnn.deterministic = True\n\nseed_everything(seed)","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.171209Z","start_time":"2024-10-31T13:52:30.164886Z"},"id":"mSO-6jwwlYzO","execution":{"iopub.status.busy":"2024-10-31T14:04:09.843978Z","iopub.status.idle":"2024-10-31T14:04:09.844596Z","shell.execute_reply.started":"2024-10-31T14:04:09.844282Z","shell.execute_reply":"2024-10-31T14:04:09.844314Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"device = 'cuda'","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.183389Z","start_time":"2024-10-31T13:52:30.180713Z"},"id":"ZS5Jp9SBRgQr","execution":{"iopub.status.busy":"2024-10-31T14:04:09.846503Z","iopub.status.idle":"2024-10-31T14:04:09.847171Z","shell.execute_reply.started":"2024-10-31T14:04:09.846812Z","shell.execute_reply":"2024-10-31T14:04:09.846843Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Load Data","metadata":{"id":"ZEIyZaYXRkZF"}},{"cell_type":"code","source":"os.makedirs('data', exist_ok=True)","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.191988Z","start_time":"2024-10-31T13:52:30.187993Z"},"id":"gj-ZY6eVRgZW","execution":{"iopub.status.busy":"2024-10-31T14:04:09.848476Z","iopub.status.idle":"2024-10-31T14:04:09.849048Z","shell.execute_reply.started":"2024-10-31T14:04:09.848765Z","shell.execute_reply":"2024-10-31T14:04:09.848795Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_dir = 'data/train'\ntest_dir = 'data/test'","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.199914Z","start_time":"2024-10-31T13:52:30.196704Z"},"id":"lvw64WGURgxK","execution":{"iopub.status.busy":"2024-10-31T14:04:09.850854Z","iopub.status.idle":"2024-10-31T14:04:09.851471Z","shell.execute_reply.started":"2024-10-31T14:04:09.851176Z","shell.execute_reply":"2024-10-31T14:04:09.851208Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"with zipfile.ZipFile('train.zip') as train_zip:\n    train_zip.extractall('data')\n    \nwith zipfile.ZipFile('test.zip') as test_zip:\n    test_zip.extractall('data')","metadata":{"id":"1hE3h70ZRg2g","ExecuteTime":{"end_time":"2024-10-31T13:58:01.925629Z","start_time":"2024-10-31T13:58:01.905174Z"},"execution":{"iopub.status.busy":"2024-10-31T14:04:09.853018Z","iopub.status.idle":"2024-10-31T14:04:09.853622Z","shell.execute_reply.started":"2024-10-31T14:04:09.853315Z","shell.execute_reply":"2024-10-31T14:04:09.853346Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_list = glob.glob(os.path.join(train_dir,'*.jpg'))\ntest_list = glob.glob(os.path.join(test_dir, '*.jpg'))","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:53:41.169543Z","start_time":"2024-10-31T13:53:41.16536Z"},"id":"FVD2SEjTRgXh","execution":{"iopub.status.busy":"2024-10-31T14:04:09.855586Z","iopub.status.idle":"2024-10-31T14:04:09.856205Z","shell.execute_reply.started":"2024-10-31T14:04:09.85587Z","shell.execute_reply":"2024-10-31T14:04:09.855901Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(f\"Train Data: {len(train_list)}\")\nprint(f\"Test Data: {len(test_list)}\")","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.23632Z","start_time":"2024-10-30T14:40:41.674919Z"},"id":"GwQ01kgtSExB","outputId":"50a9ce9b-39d0-4360-e227-cbd155be31fb","execution":{"iopub.status.busy":"2024-10-31T14:04:09.857649Z","iopub.status.idle":"2024-10-31T14:04:09.85808Z","shell.execute_reply.started":"2024-10-31T14:04:09.857885Z","shell.execute_reply":"2024-10-31T14:04:09.857907Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"labels = [path.split('/')[-1].split('.')[0] for path in train_list]","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.23632Z","start_time":"2024-10-30T14:40:41.778632Z"},"id":"amKHFCu_iwQZ","execution":{"iopub.status.busy":"2024-10-31T14:04:09.859726Z","iopub.status.idle":"2024-10-31T14:04:09.860201Z","shell.execute_reply.started":"2024-10-31T14:04:09.860002Z","shell.execute_reply":"2024-10-31T14:04:09.860024Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Random Plots","metadata":{"id":"H4NdaHt7R-zP"}},{"cell_type":"code","source":"random_idx = np.random.randint(1, len(train_list), size=9)\nfig, axes = plt.subplots(3, 3, figsize=(16, 12))\n\nfor idx, ax in enumerate(axes.ravel()):\n    img = Image.open(train_list[idx])\n    ax.set_title(labels[idx])\n    ax.imshow(img)\n","metadata":{"ExecuteTime":{"end_time":"2024-10-31T13:52:30.23632Z","start_time":"2024-10-30T14:40:41.809981Z"},"id":"Fs8I30iIR6A1","outputId":"4102a4bb-a66e-4234-e51d-2e282ece1e43","execution":{"iopub.status.busy":"2024-10-31T14:04:09.861706Z","iopub.status.idle":"2024-10-31T14:04:09.862233Z","shell.execute_reply.started":"2024-10-31T14:04:09.862009Z","shell.execute_reply":"2024-10-31T14:04:09.862033Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Load Datasets","metadata":{"id":"b0JAXWWtSXpB"}},{"cell_type":"code","source":"class CatsDogsDataset(Dataset):\n    def __init__(self, file_list, transform=None):\n        self.file_list = file_list\n        self.transform = transform\n\n    def __len__(self):\n        self.filelength = len(self.file_list)\n        return self.filelength\n\n    def __getitem__(self, idx):\n        img_path = self.file_list[idx]\n        img = Image.open(img_path)\n        img_transformed = self.transform(img)\n\n        label = img_path.split(\"/\")[-1].split(\".\")[0]\n        label = 1 if label == \"dog\" else 0\n\n        return img_transformed, label\n","metadata":{"id":"Ds9yt5kHR56R","execution":{"iopub.status.busy":"2024-10-31T14:04:09.864377Z","iopub.status.idle":"2024-10-31T14:04:09.864878Z","shell.execute_reply.started":"2024-10-31T14:04:09.864651Z","shell.execute_reply":"2024-10-31T14:04:09.864674Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_data = CatsDogsDataset(train_list, transform=train_transforms) # type: ignore\nvalid_data = CatsDogsDataset(valid_list, transform=test_transforms)\ntest_data = CatsDogsDataset(test_list, transform=test_transforms)","metadata":{"id":"pC-D9a8xSZNd","execution":{"iopub.status.busy":"2024-10-31T14:04:09.866219Z","iopub.status.idle":"2024-10-31T14:04:09.866651Z","shell.execute_reply.started":"2024-10-31T14:04:09.866424Z","shell.execute_reply":"2024-10-31T14:04:09.866446Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_loader = DataLoader(dataset = train_data, batch_size=batch_size, shuffle=True )\nvalid_loader = DataLoader(dataset = valid_data, batch_size=batch_size, shuffle=True)\ntest_loader = DataLoader(dataset = test_data, batch_size=batch_size, shuffle=True)","metadata":{"id":"-mz9qUsLSZVU","execution":{"iopub.status.busy":"2024-10-31T14:04:09.86884Z","iopub.status.idle":"2024-10-31T14:04:09.869263Z","shell.execute_reply.started":"2024-10-31T14:04:09.869063Z","shell.execute_reply":"2024-10-31T14:04:09.869085Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(train_data), len(train_loader))","metadata":{"id":"JiIcaG1zSZLA","outputId":"bd4d6e91-6c28-4b42-f242-246250dc55f2","execution":{"iopub.status.busy":"2024-10-31T14:04:09.870647Z","iopub.status.idle":"2024-10-31T14:04:09.871062Z","shell.execute_reply.started":"2024-10-31T14:04:09.870856Z","shell.execute_reply":"2024-10-31T14:04:09.870887Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(valid_data), len(valid_loader))","metadata":{"id":"hLLq3UCRSZIo","outputId":"bc81dd28-197c-4c38-ecd1-7a8cc35d4703","execution":{"iopub.status.busy":"2024-10-31T14:04:09.872244Z","iopub.status.idle":"2024-10-31T14:04:09.872678Z","shell.execute_reply.started":"2024-10-31T14:04:09.872454Z","shell.execute_reply":"2024-10-31T14:04:09.872474Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Efficient Attention","metadata":{"id":"TF9yMaRrSvmv"}},{"cell_type":"markdown","source":"### Linformer","metadata":{"id":"XED_6UFASx9r"}},{"cell_type":"code","source":"efficient_transformer = Linformer(\n    dim=128,\n    seq_len=49+1,  # 7x7 patches + 1 cls-token\n    depth=12,\n    heads=8,\n    k=64\n)","metadata":{"id":"EZ6KeBfgSnwg","execution":{"iopub.status.busy":"2024-10-31T14:04:09.874319Z","iopub.status.idle":"2024-10-31T14:04:09.874768Z","shell.execute_reply.started":"2024-10-31T14:04:09.874522Z","shell.execute_reply":"2024-10-31T14:04:09.874568Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Visual Transformer","metadata":{"id":"8VCgoZBvovkx"}},{"cell_type":"code","source":"model = ViT(\n    dim=128,\n    image_size=224,\n    patch_size=32,\n    num_classes=2,\n    transformer=efficient_transformer,\n    channels=3,\n).to(device)","metadata":{"id":"rFmQvrLXSntZ","execution":{"iopub.status.busy":"2024-10-31T14:04:09.875935Z","iopub.status.idle":"2024-10-31T14:04:09.876418Z","shell.execute_reply.started":"2024-10-31T14:04:09.87616Z","shell.execute_reply":"2024-10-31T14:04:09.87623Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Training","metadata":{"id":"4u5YZG1eozIv"}},{"cell_type":"code","source":"# loss function\ncriterion = nn.CrossEntropyLoss()\n# optimizer\noptimizer = optim.Adam(model.parameters(), lr=lr)\n# scheduler\nscheduler = StepLR(optimizer, step_size=1, gamma=gamma)","metadata":{"id":"2Go1icggSnrB","execution":{"iopub.status.busy":"2024-10-31T14:04:09.8783Z","iopub.status.idle":"2024-10-31T14:04:09.878751Z","shell.execute_reply.started":"2024-10-31T14:04:09.878515Z","shell.execute_reply":"2024-10-31T14:04:09.878555Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for epoch in range(epochs):\n    epoch_loss = 0\n    epoch_accuracy = 0\n\n    for data, label in tqdm(train_loader):\n        data = data.to(device)\n        label = label.to(device)\n\n        output = model(data)\n        loss = criterion(output, label)\n\n        optimizer.zero_grad()\n        loss.backward()\n        optimizer.step()\n\n        acc = (output.argmax(dim=1) == label).float().mean()\n        epoch_accuracy += acc / len(train_loader)\n        epoch_loss += loss / len(train_loader)\n\n    with torch.no_grad():\n        epoch_val_accuracy = 0\n        epoch_val_loss = 0\n        for data, label in valid_loader:\n            data = data.to(device)\n            label = label.to(device)\n\n            val_output = model(data)\n            val_loss = criterion(val_output, label)\n\n            acc = (val_output.argmax(dim=1) == label).float().mean()\n            epoch_val_accuracy += acc / len(valid_loader)\n            epoch_val_loss += val_loss / len(valid_loader)\n\n    print(\n        f\"Epoch : {epoch+1} - loss : {epoch_loss:.4f} - acc: {epoch_accuracy:.4f} - val_loss : {epoch_val_loss:.4f} - val_acc: {epoch_val_accuracy:.4f}\\n\"\n    )\n","metadata":{"id":"KDBDOcxeU1eR","outputId":"ef6d4d62-e705-4490-90a7-85036ff6ce62","execution":{"iopub.status.busy":"2024-10-31T14:04:09.880779Z","iopub.status.idle":"2024-10-31T14:04:09.881213Z","shell.execute_reply.started":"2024-10-31T14:04:09.880998Z","shell.execute_reply":"2024-10-31T14:04:09.881019Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"id":"kl7r45-FUmfC"},"execution_count":null,"outputs":[]}]}