{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"!pip install einops","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:21.781849Z","iopub.execute_input":"2022-05-02T11:51:21.782133Z","iopub.status.idle":"2022-05-02T11:51:32.691005Z","shell.execute_reply.started":"2022-05-02T11:51:21.782094Z","shell.execute_reply":"2022-05-02T11:51:32.690142Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import torch\nfrom torch import nn\n\nfrom einops import rearrange, repeat\nfrom einops.layers.torch import Rearrange","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:32.693498Z","iopub.execute_input":"2022-05-02T11:51:32.693795Z","iopub.status.idle":"2022-05-02T11:51:34.376892Z","shell.execute_reply.started":"2022-05-02T11:51:32.693740Z","shell.execute_reply":"2022-05-02T11:51:34.375953Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def pair(t):\n    return t if isinstance(t, tuple) else (t, t)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.381196Z","iopub.execute_input":"2022-05-02T11:51:34.381528Z","iopub.status.idle":"2022-05-02T11:51:34.389346Z","shell.execute_reply.started":"2022-05-02T11:51:34.381492Z","shell.execute_reply":"2022-05-02T11:51:34.388569Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class PreNorm(nn.Module):\n    def __init__(self, dim, fn):\n        super().__init__()\n        self.norm = nn.LayerNorm(dim)\n        self.fn = fn\n    def forward(self, x, **kwargs):\n        return self.fn(self.norm(x), **kwargs)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.394738Z","iopub.execute_input":"2022-05-02T11:51:34.397172Z","iopub.status.idle":"2022-05-02T11:51:34.404433Z","shell.execute_reply.started":"2022-05-02T11:51:34.397132Z","shell.execute_reply":"2022-05-02T11:51:34.403597Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class FeedForward(nn.Module):\n    def __init__(self, dim, hidden_dim, dropout = 0.):\n        super().__init__()\n        self.net = nn.Sequential(\n            nn.Linear(dim, hidden_dim),\n            nn.GELU(),\n            nn.Dropout(dropout),\n            nn.Linear(hidden_dim, dim),\n            nn.Dropout(dropout)\n        )\n    def forward(self, x):\n        return self.net(x)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.408717Z","iopub.execute_input":"2022-05-02T11:51:34.411106Z","iopub.status.idle":"2022-05-02T11:51:34.419881Z","shell.execute_reply.started":"2022-05-02T11:51:34.411069Z","shell.execute_reply":"2022-05-02T11:51:34.418806Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class Attention(nn.Module):\n    def __init__(self, dim, heads = 8, dim_head = 64, dropout = 0.):\n        super().__init__()\n        inner_dim = dim_head *  heads\n        project_out = not (heads == 1 and dim_head == dim)\n\n        self.heads = heads\n        self.scale = dim_head ** -0.5\n\n        self.attend = nn.Softmax(dim = -1)\n        self.to_qkv = nn.Linear(dim, inner_dim * 3, bias = False)\n\n        self.to_out = nn.Sequential(\n            nn.Linear(inner_dim, dim),\n            nn.Dropout(dropout)\n        ) if project_out else nn.Identity()\n\n    def forward(self, x):\n        #返回三个元组\n        qkv = self.to_qkv(x).chunk(3, dim = -1)\n        # X = X.reshape(X.shape[0], X.shape[1], num_heads, -1)\n        # X = X.permute(0, 2, 1, 3)\n        q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h = self.heads), qkv)\n\n        dots = torch.matmul(q, k.transpose(-1, -2)) * self.scale\n\n        attn = self.attend(dots)\n\n        out = torch.matmul(attn, v)\n        # X = X.reshape(-1, num_heads, X.shape[1], X.shape[2])\n        # X = X.permute(0, 2, 1, 3)\n        # X.reshape(X.shape[0], X.shape[1], -1)\n        out = rearrange(out, 'b h n d -> b n (h d)')\n        return self.to_out(out)\n","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.424292Z","iopub.execute_input":"2022-05-02T11:51:34.426844Z","iopub.status.idle":"2022-05-02T11:51:34.440806Z","shell.execute_reply.started":"2022-05-02T11:51:34.426805Z","shell.execute_reply":"2022-05-02T11:51:34.440156Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"'''\nx = nn.Parameter(torch.randn(1, 2, 10))\n\nto_qkv = nn.Linear(10, 3 * 6, bias = False)\n#返回三个元组\nqkv = to_qkv(x).chunk(3, dim = -1)\nq, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h = 3), qkv)\n\nqkv[1], qkv[1].shape\n\noutputs : \n    (tensor([[[ 0.7575,  0.4202,  0.3702,  0.2388,  0.2091, -0.0606],\n              [ 0.0393,  0.3073, -0.9259,  0.2085,  0.6273, -0.5488]]],\n                grad_fn=<SplitBackward>),\n    torch.Size([1, 2, 6]))\n\nq.shape, k\n\noutputs : \n        (torch.Size([1, 3, 2, 2]),\n        tensor([[[[ 0.7575,  0.4202],\n               [ 0.0393,  0.3073]],\n \n              [[ 0.3702,  0.2388],\n               [-0.9259,  0.2085]],\n \n              [[ 0.2091, -0.0606],\n               [ 0.6273, -0.5488]]]], grad_fn=<ViewBackward>))\n               \ndots = torch.matmul(q, k.transpose(-1, -2))\ndots, dots.shape\n\noutputs : \n    (tensor([[[[-0.2935, -0.0989],\n              [ 0.0588,  0.0918]],\n \n             [[-0.4660,  0.8755],\n              [-0.4306,  1.0743]],\n \n             [[-0.0404, -0.2811],\n             [-0.1492, -0.4611]]]], grad_fn=<UnsafeViewBackward>),\ntorch.Size([1, 3, 2, 2]))\n'''","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.445685Z","iopub.execute_input":"2022-05-02T11:51:34.448208Z","iopub.status.idle":"2022-05-02T11:51:34.463339Z","shell.execute_reply.started":"2022-05-02T11:51:34.448170Z","shell.execute_reply":"2022-05-02T11:51:34.462616Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"![image.png](attachment:117bf5d0-ba6f-4f3b-b495-75274fa24810.png)","metadata":{},"attachments":{"117bf5d0-ba6f-4f3b-b495-75274fa24810.png":{"image/png":"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"}}},{"cell_type":"code","source":"class Transformer(nn.Module):\n    def __init__(self, dim, depth, heads, dim_head, mlp_dim, dropout = 0.):\n        super().__init__()\n        self.layers = nn.ModuleList([])\n        for _ in range(depth):\n            self.layers.append(nn.ModuleList([\n                PreNorm(dim, Attention(dim, heads = heads, dim_head = dim_head, dropout = dropout)),\n                PreNorm(dim, FeedForward(dim, mlp_dim, dropout = dropout))\n            ]))\n    def forward(self, x):\n        for attn, ff in self.layers:\n            x = attn(x) + x\n            x = ff(x) + x\n        return x","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.468367Z","iopub.execute_input":"2022-05-02T11:51:34.470592Z","iopub.status.idle":"2022-05-02T11:51:34.480631Z","shell.execute_reply.started":"2022-05-02T11:51:34.470552Z","shell.execute_reply":"2022-05-02T11:51:34.480048Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"![image.png](attachment:d116e2e5-a281-43f1-916b-a0ed17e895cb.png)","metadata":{},"attachments":{"d116e2e5-a281-43f1-916b-a0ed17e895cb.png":{"image/png":"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"}}},{"cell_type":"code","source":"class ViT(nn.Module):\n    def __init__(self, *, image_size, patch_size, num_classes, dim, depth, heads, mlp_dim, pool = 'cls', channels = 3, dim_head = 64, dropout = 0., emb_dropout = 0.):\n        super().__init__()\n        image_height, image_width = pair(image_size)\n        patch_height, patch_width = pair(patch_size)\n\n        assert image_height % patch_height == 0 and image_width % patch_width == 0, 'Image dimensions must be divisible by the patch size.'\n\n        num_patches = (image_height // patch_height) * (image_width // patch_width)\n        patch_dim = channels * patch_height * patch_width\n        assert pool in {'cls', 'mean'}, 'pool type must be either cls (cls token) or mean (mean pooling)'\n\n        self.to_patch_embedding = nn.Sequential(\n            Rearrange('b c (h p1) (w p2) -> b (h w) (p1 p2 c)', p1 = patch_height, p2 = patch_width),\n            nn.Linear(patch_dim, dim),\n        )\n\n        self.pos_embedding = nn.Parameter(torch.randn(1, num_patches + 1, dim))\n        self.cls_token = nn.Parameter(torch.randn(1, 1, dim))\n        self.dropout = nn.Dropout(emb_dropout)\n\n        self.transformer = Transformer(dim, depth, heads, dim_head, mlp_dim, dropout)\n\n        self.pool = pool\n        self.to_latent = nn.Identity()\n\n        self.mlp_head = nn.Sequential(\n            nn.LayerNorm(dim),\n            nn.Linear(dim, num_classes)\n        )\n\n    def forward(self, img):\n        x = self.to_patch_embedding(img)\n        b, n, _ = x.shape\n\n        cls_tokens = repeat(self.cls_token, '() n d -> b n d', b = b)\n        x = torch.cat((cls_tokens, x), dim=1)\n        x += self.pos_embedding[:, :(n + 1)]\n        x = self.dropout(x)\n\n        x = self.transformer(x)\n\n        x = x.mean(dim = 1) if self.pool == 'mean' else x[:, 0]\n\n        x = self.to_latent(x)\n        return self.mlp_head(x)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.482612Z","iopub.execute_input":"2022-05-02T11:51:34.482912Z","iopub.status.idle":"2022-05-02T11:51:34.509377Z","shell.execute_reply.started":"2022-05-02T11:51:34.482875Z","shell.execute_reply":"2022-05-02T11:51:34.508674Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# !pip -q install vit_pytorch linformer ","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.515765Z","iopub.execute_input":"2022-05-02T11:51:34.518188Z","iopub.status.idle":"2022-05-02T11:51:34.523588Z","shell.execute_reply.started":"2022-05-02T11:51:34.518078Z","shell.execute_reply":"2022-05-02T11:51:34.522788Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# !pip uninstall torchvision\n# !pip install torchvision","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.526452Z","iopub.execute_input":"2022-05-02T11:51:34.526810Z","iopub.status.idle":"2022-05-02T11:51:34.534157Z","shell.execute_reply.started":"2022-05-02T11:51:34.526773Z","shell.execute_reply":"2022-05-02T11:51:34.533295Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"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\n# from 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\n# from vit_pytorch.efficient import ViT","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:34.535381Z","iopub.execute_input":"2022-05-02T11:51:34.536556Z","iopub.status.idle":"2022-05-02T11:51:35.696497Z","shell.execute_reply.started":"2022-05-02T11:51:34.536508Z","shell.execute_reply":"2022-05-02T11:51:35.695763Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(f\"Torch: {torch.__version__}\") ","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.698641Z","iopub.execute_input":"2022-05-02T11:51:35.699059Z","iopub.status.idle":"2022-05-02T11:51:35.704153Z","shell.execute_reply.started":"2022-05-02T11:51:35.699022Z","shell.execute_reply":"2022-05-02T11:51:35.703332Z"},"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":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.705621Z","iopub.execute_input":"2022-05-02T11:51:35.706447Z","iopub.status.idle":"2022-05-02T11:51:35.713333Z","shell.execute_reply.started":"2022-05-02T11:51:35.706397Z","shell.execute_reply":"2022-05-02T11:51:35.712509Z"},"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":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.714841Z","iopub.execute_input":"2022-05-02T11:51:35.715280Z","iopub.status.idle":"2022-05-02T11:51:35.725350Z","shell.execute_reply.started":"2022-05-02T11:51:35.715244Z","shell.execute_reply":"2022-05-02T11:51:35.724556Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#device = 'cuda'\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.726712Z","iopub.execute_input":"2022-05-02T11:51:35.727257Z","iopub.status.idle":"2022-05-02T11:51:35.786849Z","shell.execute_reply.started":"2022-05-02T11:51:35.727220Z","shell.execute_reply":"2022-05-02T11:51:35.786066Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# train_dir = '/kaggle/input/dogs-vs-cats-redux-kernels-edition/train.zip'\n# test_dir = '/kaggle/input/dogs-vs-cats-redux-kernels-edition/test.zip'","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.788293Z","iopub.execute_input":"2022-05-02T11:51:35.788547Z","iopub.status.idle":"2022-05-02T11:51:35.798174Z","shell.execute_reply.started":"2022-05-02T11:51:35.788510Z","shell.execute_reply":"2022-05-02T11:51:35.797427Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_dir = '/kaggle/input/dogsvscatsreduxkernelsedition/train/train'\ntest_dir = '/kaggle/input/dogsvscatsreduxkernelsedition/test/test'","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.800789Z","iopub.execute_input":"2022-05-02T11:51:35.801421Z","iopub.status.idle":"2022-05-02T11:51:35.807205Z","shell.execute_reply.started":"2022-05-02T11:51:35.801383Z","shell.execute_reply":"2022-05-02T11:51:35.806494Z"},"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":{"execution":{"iopub.status.busy":"2022-05-02T11:51:35.809349Z","iopub.execute_input":"2022-05-02T11:51:35.810037Z","iopub.status.idle":"2022-05-02T11:51:36.707502Z","shell.execute_reply.started":"2022-05-02T11:51:35.809999Z","shell.execute_reply":"2022-05-02T11:51:36.706735Z"},"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":{"execution":{"iopub.status.busy":"2022-05-02T11:51:36.709103Z","iopub.execute_input":"2022-05-02T11:51:36.709358Z","iopub.status.idle":"2022-05-02T11:51:36.714957Z","shell.execute_reply.started":"2022-05-02T11:51:36.709324Z","shell.execute_reply":"2022-05-02T11:51:36.714244Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"labels = [path.split('/')[-1].split('.')[0] for path in train_list] ","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:36.716458Z","iopub.execute_input":"2022-05-02T11:51:36.717033Z","iopub.status.idle":"2022-05-02T11:51:36.740939Z","shell.execute_reply.started":"2022-05-02T11:51:36.716968Z","shell.execute_reply":"2022-05-02T11:51:36.740033Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"len(labels), len(train_list)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:36.742448Z","iopub.execute_input":"2022-05-02T11:51:36.742797Z","iopub.status.idle":"2022-05-02T11:51:36.753109Z","shell.execute_reply.started":"2022-05-02T11:51:36.742759Z","shell.execute_reply":"2022-05-02T11:51:36.752160Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#  Random Plots","metadata":{}},{"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)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:36.754613Z","iopub.execute_input":"2022-05-02T11:51:36.755160Z","iopub.status.idle":"2022-05-02T11:51:38.252118Z","shell.execute_reply.started":"2022-05-02T11:51:36.755123Z","shell.execute_reply":"2022-05-02T11:51:38.249824Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#stratify是为了保持split前类的分布\ntrain_list, valid_list = train_test_split(train_list, \n                                          test_size=0.2,\n                                          stratify=labels,\n                                          random_state=seed)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.253101Z","iopub.execute_input":"2022-05-02T11:51:38.253349Z","iopub.status.idle":"2022-05-02T11:51:38.293086Z","shell.execute_reply.started":"2022-05-02T11:51:38.253310Z","shell.execute_reply":"2022-05-02T11:51:38.292376Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(f\"Train Data: {len(train_list)}\")\nprint(f\"Validation Data: {len(valid_list)}\")\nprint(f\"Test Data: {len(test_list)}\")","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.294216Z","iopub.execute_input":"2022-05-02T11:51:38.294538Z","iopub.status.idle":"2022-05-02T11:51:38.300861Z","shell.execute_reply.started":"2022-05-02T11:51:38.294495Z","shell.execute_reply":"2022-05-02T11:51:38.300157Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(f\"Train Data: {len(train_list)}\")\nprint(f\"Validation Data: {len(valid_list)}\")\nprint(f\"Test Data: {len(test_list)}\")","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.302261Z","iopub.execute_input":"2022-05-02T11:51:38.302739Z","iopub.status.idle":"2022-05-02T11:51:38.312610Z","shell.execute_reply.started":"2022-05-02T11:51:38.302705Z","shell.execute_reply":"2022-05-02T11:51:38.311846Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Image Augumentation","metadata":{}},{"cell_type":"code","source":"train_transforms = transforms.Compose(\n    [\n        transforms.Resize((224, 224)),\n        transforms.RandomResizedCrop(224),\n        #以给定的概率随机水平旋转给定的PIL的图像，默认为0.5\n        transforms.RandomHorizontalFlip(),\n        transforms.ToTensor(),\n    ]\n)\n\nval_transforms = transforms.Compose(\n    [\n        transforms.Resize(256),\n        transforms.CenterCrop(224),\n        transforms.ToTensor(),\n    ]\n)\n\n\ntest_transforms = transforms.Compose(\n    [\n        transforms.Resize(256),\n        transforms.CenterCrop(224),\n        transforms.ToTensor(),\n    ]\n)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.314063Z","iopub.execute_input":"2022-05-02T11:51:38.314313Z","iopub.status.idle":"2022-05-02T11:51:38.321974Z","shell.execute_reply.started":"2022-05-02T11:51:38.314281Z","shell.execute_reply":"2022-05-02T11:51:38.321113Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Load Datasets\n","metadata":{}},{"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":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.326516Z","iopub.execute_input":"2022-05-02T11:51:38.326702Z","iopub.status.idle":"2022-05-02T11:51:38.335709Z","shell.execute_reply.started":"2022-05-02T11:51:38.326680Z","shell.execute_reply":"2022-05-02T11:51:38.334999Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_data = CatsDogsDataset(train_list, transform=train_transforms)\nvalid_data = CatsDogsDataset(valid_list, transform=test_transforms)\ntest_data = CatsDogsDataset(test_list, transform=test_transforms)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.337268Z","iopub.execute_input":"2022-05-02T11:51:38.338022Z","iopub.status.idle":"2022-05-02T11:51:38.342896Z","shell.execute_reply.started":"2022-05-02T11:51:38.337971Z","shell.execute_reply":"2022-05-02T11:51:38.342197Z"},"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)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.344258Z","iopub.execute_input":"2022-05-02T11:51:38.344564Z","iopub.status.idle":"2022-05-02T11:51:38.352883Z","shell.execute_reply.started":"2022-05-02T11:51:38.344530Z","shell.execute_reply":"2022-05-02T11:51:38.352046Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(train_data), len(train_loader)) ","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.354294Z","iopub.execute_input":"2022-05-02T11:51:38.354546Z","iopub.status.idle":"2022-05-02T11:51:38.367051Z","shell.execute_reply.started":"2022-05-02T11:51:38.354514Z","shell.execute_reply":"2022-05-02T11:51:38.365912Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(valid_data), len(valid_loader)) ","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.368466Z","iopub.execute_input":"2022-05-02T11:51:38.369080Z","iopub.status.idle":"2022-05-02T11:51:38.376777Z","shell.execute_reply.started":"2022-05-02T11:51:38.369043Z","shell.execute_reply":"2022-05-02T11:51:38.375916Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model = ViT(\n    dim=768,\n    image_size=224,\n    patch_size=16,\n    num_classes=2,\n    depth=7,\n    channels=3,\n    heads=12,\n    mlp_dim=768,\n    dropout=0.1,\n).to(device)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:38.378228Z","iopub.execute_input":"2022-05-02T11:51:38.378793Z","iopub.status.idle":"2022-05-02T11:51:41.536371Z","shell.execute_reply.started":"2022-05-02T11:51:38.378676Z","shell.execute_reply":"2022-05-02T11:51:41.535445Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Training","metadata":{}},{"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":{"execution":{"iopub.status.busy":"2022-05-02T11:51:41.541214Z","iopub.execute_input":"2022-05-02T11:51:41.541767Z","iopub.status.idle":"2022-05-02T11:51:41.552553Z","shell.execute_reply.started":"2022-05-02T11:51:41.541715Z","shell.execute_reply":"2022-05-02T11:51:41.551587Z"},"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    )","metadata":{"execution":{"iopub.status.busy":"2022-05-02T11:51:41.558239Z","iopub.execute_input":"2022-05-02T11:51:41.558801Z","iopub.status.idle":"2022-05-02T12:57:07.734525Z","shell.execute_reply.started":"2022-05-02T11:51:41.558754Z","shell.execute_reply":"2022-05-02T12:57:07.733789Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dog_probs = []\nmodel.eval()\nwith torch.no_grad():\n    for idx, x in enumerate(test_loader):\n        data, fileid = x\n        data = data.to(device)\n#         print(data.shape)\n#         print(fileid)\n#         print(idx)\n#         print(range(idx*64+1, (idx+1)*64+1))\n        preds = model(data)\n        preds_list = F.softmax(preds, dim=1)[:, 1].tolist()\n        dog_probs += list(zip(range(idx*64+1, (idx+1)*64+1), preds_list))","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:57:07.735711Z","iopub.execute_input":"2022-05-02T12:57:07.736917Z","iopub.status.idle":"2022-05-02T12:59:44.146151Z","shell.execute_reply.started":"2022-05-02T12:57:07.736878Z","shell.execute_reply":"2022-05-02T12:59:44.145370Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dog_probs.sort(key = lambda x : int(x[0]))\ndog_probs","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:59:44.147692Z","iopub.execute_input":"2022-05-02T12:59:44.147962Z","iopub.status.idle":"2022-05-02T12:59:44.199788Z","shell.execute_reply.started":"2022-05-02T12:59:44.147927Z","shell.execute_reply":"2022-05-02T12:59:44.199064Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"idx = list(map(lambda x: x[0],dog_probs))\nprob = list(map(lambda x: x[1],dog_probs))","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:59:44.201124Z","iopub.execute_input":"2022-05-02T12:59:44.201367Z","iopub.status.idle":"2022-05-02T12:59:44.208527Z","shell.execute_reply.started":"2022-05-02T12:59:44.201335Z","shell.execute_reply":"2022-05-02T12:59:44.207705Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission = pd.DataFrame({'id':idx,'label':prob})","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:59:44.210152Z","iopub.execute_input":"2022-05-02T12:59:44.210435Z","iopub.status.idle":"2022-05-02T12:59:44.227277Z","shell.execute_reply.started":"2022-05-02T12:59:44.210388Z","shell.execute_reply":"2022-05-02T12:59:44.226531Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:59:44.228320Z","iopub.execute_input":"2022-05-02T12:59:44.228558Z","iopub.status.idle":"2022-05-02T12:59:44.253384Z","shell.execute_reply.started":"2022-05-02T12:59:44.228527Z","shell.execute_reply":"2022-05-02T12:59:44.252531Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission.to_csv('result.csv',index=False)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:59:44.254801Z","iopub.execute_input":"2022-05-02T12:59:44.255163Z","iopub.status.idle":"2022-05-02T12:59:44.304326Z","shell.execute_reply.started":"2022-05-02T12:59:44.255124Z","shell.execute_reply":"2022-05-02T12:59:44.303604Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import random\n\nid_list = []\nclass_ = {0: 'cat', 1: 'dog'}\n\nfig, axes = plt.subplots(2, 5, figsize=(20, 12), facecolor='w')\n\nfor ax in axes.ravel():\n    \n    i = random.choice(submission['id'].values)\n    \n    label = submission.loc[submission['id'] == i, 'label'].values[0]\n    if label > 0.5:\n        label = 1\n    else:\n        label = 0\n        \n    img_path = os.path.join(test_dir, '{}.jpg'.format(i))\n    img = Image.open(img_path)\n    \n    ax.set_title(class_[label])\n    ax.imshow(img)","metadata":{"execution":{"iopub.status.busy":"2022-05-02T12:59:44.305581Z","iopub.execute_input":"2022-05-02T12:59:44.305864Z","iopub.status.idle":"2022-05-02T12:59:45.885125Z","shell.execute_reply.started":"2022-05-02T12:59:44.305826Z","shell.execute_reply":"2022-05-02T12:59:45.881369Z"},"trusted":true},"execution_count":null,"outputs":[]}]}