{"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":"markdown","source":"# [Sartorius - Cell Instance Segmentation](https://www.kaggle.com/c/petfinder-pawpularity-score)\n> Detect single neuronal cells in microscopy images\n\n![](https://storage.googleapis.com/kaggle-competitions/kaggle/30201/logos/header.png?t=2021-09-03-15-27-46)","metadata":{}},{"cell_type":"markdown","source":"# ⚽ Goal\n📌 The purpose of this notebook is to show how to achieve Good score even using **UNet**. \n\n📌 Even though the competition is about **Instance Segmentation** we can use **UNet** do **Semantic Segmentation** and then convert them to individual **Instances**.\n\n📌 Finally, we can use **UNet** with **Mask-RCNN** for Ensemble to further boost our score.\n\n<img src=\"https://i.stack.imgur.com/MEB9F.png\" width=800>","metadata":{}},{"cell_type":"markdown","source":"# 🚩 Version Info\n* `v17`: trying new augmentation variants\n    * normalization is off\n    * optical-distortion is off\n    * distortion prob=`0.25`\n    * rotation range=`90`\n    * coarse-dropout size is reduced to `img_size//20`\n    * clahe augmentation is added\n    * backbone: `efficientnet-b0`","metadata":{}},{"cell_type":"markdown","source":"# 📒 Notebooks\n📌 **UNet**:\n* Train: [[PyTorch] Sartorius: UNet Strikes Back [Train] 🔥](https://www.kaggle.com/awsaf49/pytorch-sartorius-unet-strikes-back-train/edit)\n* Infer: [[PyTorch] Sartorius: UNet Strikes Back [Infer] 🔥](https://www.kaggle.com/awsaf49/pytorch-sartorius-unet-strikes-back-infer/edit)\n\n📌 **Mask-RCNN**:\n* Train: [Sartorius: MMDetection [Train]](https://www.kaggle.com/awsaf49/sartorius-mmdetection-train)\n* Infer: [Sartorius: MMDetection [Infer]](https://www.kaggle.com/awsaf49/sartorius-mmdetection-infer)","metadata":{}},{"cell_type":"markdown","source":"## Please Upvote if you Find this Useful :)","metadata":{}},{"cell_type":"markdown","source":"# 🛠 Install Libraries","metadata":{}},{"cell_type":"code","source":"!pip install -q ../input/pytorch-segmentation-models-lib/pretrainedmodels-0.7.4/pretrainedmodels-0.7.4\n!pip install -q ../input/pytorch-segmentation-models-lib/efficientnet_pytorch-0.6.3/efficientnet_pytorch-0.6.3\n!pip install -q ../input/pytorch-segmentation-models-lib/timm-0.4.12-py3-none-any.whl\n!pip install -q ../input/pytorch-segmentation-models-lib/segmentation_models_pytorch-0.2.0-py3-none-any.whl\n!pip install -qU wandb","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-11-10T14:39:22.314795Z","iopub.execute_input":"2021-11-10T14:39:22.315116Z","iopub.status.idle":"2021-11-10T14:40:21.630757Z","shell.execute_reply.started":"2021-11-10T14:39:22.315032Z","shell.execute_reply":"2021-11-10T14:40:21.62976Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 📚 Import Libraries ","metadata":{}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\npd.options.plotting.backend = \"plotly\"\nimport random\nfrom glob import glob\nimport os, shutil\nfrom tqdm import tqdm\ntqdm.pandas()\nimport time\nimport copy\nimport joblib\nfrom collections import defaultdict\nimport gc\nfrom IPython import display as ipd\n\n# visualization\nimport cv2\nimport matplotlib.pyplot as plt\n\n# Sklearn\nfrom sklearn.model_selection import StratifiedKFold, KFold\n\n# PyTorch \nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torch.utils.data import Dataset, DataLoader\nfrom torch.cuda import amp\n\nimport timm\n\n# Albumentations for augmentations\nimport albumentations as A\nfrom albumentations.pytorch import ToTensorV2\n\n# For colored terminal text\nfrom colorama import Fore, Back, Style\nc_  = Fore.GREEN\nsr_ = Style.RESET_ALL\n\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\n# For descriptive error messages\nos.environ['CUDA_LAUNCH_BLOCKING'] = \"1\"","metadata":{"_kg_hide-input":false,"execution":{"iopub.status.busy":"2021-11-10T14:40:21.633645Z","iopub.execute_input":"2021-11-10T14:40:21.63402Z","iopub.status.idle":"2021-11-10T14:40:31.537973Z","shell.execute_reply.started":"2021-11-10T14:40:21.633972Z","shell.execute_reply":"2021-11-10T14:40:31.536847Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ⭐ WandB\n\n<img src=\"https://camo.githubusercontent.com/dd842f7b0be57140e68b2ab9cb007992acd131c48284eaf6b1aca758bfea358b/68747470733a2f2f692e696d6775722e636f6d2f52557469567a482e706e67\" width=\"400\" alt=\"Weights & Biases\" />\n\nWeights & Biases (W&B) is MLOps platform for tracking our experiemnts. We can use it to Build better models faster with experiment tracking, dataset versioning, and model management. Some of the cool features of **W&B**:\n\n* Track, compare, and visualize ML experiments\n* Get live metrics, terminal logs, and system stats streamed to the centralized dashboard.\n* Explain how your model works, show graphs of how model versions improved, discuss bugs, and demonstrate progress towards milestones.","metadata":{}},{"cell_type":"code","source":"import wandb\n\ntry:\n    from kaggle_secrets import UserSecretsClient\n    user_secrets = UserSecretsClient()\n    api_key = user_secrets.get_secret(\"WANDB\")\n    wandb.login(key=api_key)\n    anonymous = None\nexcept:\n    anonymous = \"must\"\n    print('To use your W&B account,\\nGo to Add-ons -> Secrets and provide your W&B access token. Use the Label name as WANDB. \\nGet your W&B access token from here: https://wandb.ai/authorize')","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:31.539873Z","iopub.execute_input":"2021-11-10T14:40:31.540235Z","iopub.status.idle":"2021-11-10T14:40:33.893478Z","shell.execute_reply.started":"2021-11-10T14:40:31.540186Z","shell.execute_reply":"2021-11-10T14:40:33.892436Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ⚙️ Configuration ","metadata":{}},{"cell_type":"code","source":"class CFG:\n    seed          = 101\n    debug         = False # set debug=False for Full Training\n    exp_name      = 'Unet-effnetb2-512x512-aug2'\n    model_name    = 'Unet'\n    backbone      = 'efficientnet-b2'\n    train_bs      = 24\n    valid_bs      = 48\n    img_size      = [512, 512]\n    epochs        = 50\n    lr            = 5e-3\n    scheduler     = 'CosineAnnealingLR'\n    min_lr        = 1e-6\n    T_max         = int(100*6*1.8)\n    T_0           = 25\n    warmup_epochs = 0\n    wd            = 1e-6\n    n_accumulate  = 32//train_bs\n    n_fold        = 5\n    num_classes   = 1\n    device        = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n    competition   = 'sartorius'\n    _wandb_kernel = 'awsaf49'","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:33.896889Z","iopub.execute_input":"2021-11-10T14:40:33.89744Z","iopub.status.idle":"2021-11-10T14:40:33.960348Z","shell.execute_reply.started":"2021-11-10T14:40:33.897386Z","shell.execute_reply":"2021-11-10T14:40:33.958766Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ❗ Reproducibility","metadata":{}},{"cell_type":"code","source":"def set_seed(seed = 42):\n    '''Sets the seed of the entire notebook so results are the same every time we run.\n    This is for REPRODUCIBILITY.'''\n    np.random.seed(seed)\n    random.seed(seed)\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed(seed)\n    # When running on the CuDNN backend, two further options must be set\n    torch.backends.cudnn.deterministic = True\n    torch.backends.cudnn.benchmark = False\n    # Set a fixed value for the hash seed\n    os.environ['PYTHONHASHSEED'] = str(seed)\n    print('> SEEDING DONE')\n    \nset_seed(CFG.seed)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:33.962619Z","iopub.execute_input":"2021-11-10T14:40:33.963021Z","iopub.status.idle":"2021-11-10T14:40:33.980628Z","shell.execute_reply.started":"2021-11-10T14:40:33.962977Z","shell.execute_reply":"2021-11-10T14:40:33.979601Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 📖 Meta Data","metadata":{}},{"cell_type":"code","source":"BASE_PATH  = '/kaggle/input/sartorius-cell-instance-segmentation'\nBASE_PATH2 = '/kaggle/input/sartorius-binary-mask-dataset'","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:33.982262Z","iopub.execute_input":"2021-11-10T14:40:33.983165Z","iopub.status.idle":"2021-11-10T14:40:33.988609Z","shell.execute_reply.started":"2021-11-10T14:40:33.983119Z","shell.execute_reply":"2021-11-10T14:40:33.987503Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Train Data\ndf               = pd.read_csv(f'{BASE_PATH}/train.csv')\ndf['image_path'] = BASE_PATH + '/train/' + df['id'] + '.png'\ntmp_df           = df.drop_duplicates(subset=[\"id\", \"image_path\"]).reset_index(drop=True)\ntmp_df[\"annotation\"] = df.groupby(\"id\")[\"annotation\"].agg(list).reset_index(drop=True)\ndf               = tmp_df.copy()\ndf['mask_path']  = BASE_PATH2 + '/' + df['id'] + '.npy'\ndisplay(df.head(2))\n\n# Test Data\ntest_df       = pd.DataFrame(glob(BASE_PATH+'/test/*'), columns=['image_path'])\ntest_df['id'] = test_df.image_path.map(lambda x: x.split('/')[-1].split('.')[0])\n\ndisplay(test_df.head(2))","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:33.990301Z","iopub.execute_input":"2021-11-10T14:40:33.999181Z","iopub.status.idle":"2021-11-10T14:40:34.685628Z","shell.execute_reply.started":"2021-11-10T14:40:33.991959Z","shell.execute_reply":"2021-11-10T14:40:34.6847Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Class Distribution","metadata":{}},{"cell_type":"code","source":"df.cell_type.value_counts().plot.bar()","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:34.687049Z","iopub.execute_input":"2021-11-10T14:40:34.687367Z","iopub.status.idle":"2021-11-10T14:40:37.89853Z","shell.execute_reply.started":"2021-11-10T14:40:34.687321Z","shell.execute_reply":"2021-11-10T14:40:37.897526Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 📁 Create Folds","metadata":{}},{"cell_type":"code","source":"skf = StratifiedKFold(n_splits=CFG.n_fold, shuffle=True, random_state=CFG.seed)\nfor fold, (train_idx, val_idx) in enumerate(skf.split(df, df[\"cell_type\"])):\n    df.loc[val_idx, 'fold'] = fold\ndisplay(df.groupby(['fold'])['id'].count())","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:37.900447Z","iopub.execute_input":"2021-11-10T14:40:37.900787Z","iopub.status.idle":"2021-11-10T14:40:37.924428Z","shell.execute_reply.started":"2021-11-10T14:40:37.900744Z","shell.execute_reply":"2021-11-10T14:40:37.923315Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🍚 Dataset","metadata":{}},{"cell_type":"code","source":"class BuildDataset(torch.utils.data.Dataset):\n    def __init__(self, df, transforms=None):\n        self.df = df\n        self.img_paths  = df['image_path'].values\n        try: # if there is no mask then only send images --> test data\n            self.msk_paths  = df['mask_path'].values\n        except:\n            self.msk_paths  = None\n        self.transforms = transforms\n        \n    def __len__(self):\n        return len(self.df)\n    \n    def __getitem__(self, index):\n        img_path = self.img_paths[index]\n        img      = cv2.imread(img_path)\n        img      = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n        if self.msk_paths is not None:\n            msk_path = self.msk_paths[index]\n            msk      = np.load(msk_path)\n            if self.transforms:\n                data = self.transforms(image=img, mask=msk)\n                img  = data['image']\n                msk  = data['mask']\n            msk      = np.expand_dims(msk, axis=0) # output_shape: (batch_size, 1, img_size, img_size)\n            return img, msk\n        else:\n            if self.transforms:\n                data = self.transforms(image=img)\n                img  = data['image']\n            return img","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:40:37.928026Z","iopub.execute_input":"2021-11-10T14:40:37.928448Z","iopub.status.idle":"2021-11-10T14:40:37.939817Z","shell.execute_reply.started":"2021-11-10T14:40:37.928402Z","shell.execute_reply":"2021-11-10T14:40:37.93846Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🌈 Augmentations","metadata":{}},{"cell_type":"code","source":"data_transforms = {\n    \"train\": A.Compose([\n        A.Resize(*CFG.img_size),\n#         A.Normalize(\n#                 mean=[0.485, 0.456, 0.406], \n#                 std=[0.229, 0.224, 0.225], \n#                 max_pixel_value=255.0, \n#                 p=1.0,\n#             ),\n        A.CLAHE(p=0.35),\n        A.ColorJitter(p=0.5),\n        A.HorizontalFlip(p=0.5),\n        A.VerticalFlip(p=0.5),\n        A.ShiftScaleRotate(shift_limit=0.0625, scale_limit=0.1, rotate_limit=90, p=0.5),\n        A.OneOf([\n            A.GridDistortion(num_steps=5, distort_limit=0.05, p=1.0),\n#             A.OpticalDistortion(distort_limit=0.05, shift_limit=0.05, p=1.0),\n            A.ElasticTransform(alpha=1, sigma=50, alpha_affine=50, p=1.0)\n        ], p=0.25),\n        A.CoarseDropout(max_holes=8, max_height=CFG.img_size[0]//20, max_width=CFG.img_size[1]//20,\n                         min_holes=5, fill_value=0, mask_fill_value=0, p=0.5),\n        ToTensorV2()], p=1.0),\n    \n    \"valid\": A.Compose([\n        A.Resize(*CFG.img_size),\n#         A.Normalize(\n#                 mean=[0.485, 0.456, 0.406], \n#                 std=[0.229, 0.224, 0.225], \n#                 max_pixel_value=255.0, \n#                 p=1.0\n#             ),\n        ToTensorV2()], p=1.0)\n}","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-11-10T14:48:43.287551Z","iopub.execute_input":"2021-11-10T14:48:43.288335Z","iopub.status.idle":"2021-11-10T14:48:43.298997Z","shell.execute_reply.started":"2021-11-10T14:48:43.288298Z","shell.execute_reply":"2021-11-10T14:48:43.297406Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🍰 DataLoader","metadata":{}},{"cell_type":"code","source":"def prepare_loaders(fold):\n    train_df = df[df.fold != fold].reset_index(drop=True)\n    valid_df = df[df.fold == fold].reset_index(drop=True)\n    \n    train_dataset = BuildDataset(train_df, transforms=data_transforms['train'])\n    valid_dataset = BuildDataset(valid_df, transforms=data_transforms['valid'])\n\n    train_loader = DataLoader(train_dataset, batch_size=CFG.train_bs, \n                              num_workers=4, shuffle=True, pin_memory=True, drop_last=True)\n    valid_loader = DataLoader(valid_dataset, batch_size=CFG.valid_bs, \n                              num_workers=4, shuffle=False, pin_memory=True)\n    \n    return train_loader, valid_loader\n","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:48:44.343108Z","iopub.execute_input":"2021-11-10T14:48:44.343925Z","iopub.status.idle":"2021-11-10T14:48:44.351098Z","shell.execute_reply.started":"2021-11-10T14:48:44.343872Z","shell.execute_reply":"2021-11-10T14:48:44.35006Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_loader, valid_loader = prepare_loaders(fold=0)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:48:45.116026Z","iopub.execute_input":"2021-11-10T14:48:45.116821Z","iopub.status.idle":"2021-11-10T14:48:45.127435Z","shell.execute_reply.started":"2021-11-10T14:48:45.116784Z","shell.execute_reply":"2021-11-10T14:48:45.126442Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"imgs, msks = next(iter(train_loader))\nimgs = imgs.permute((0, 2, 3, 1))\nmsks = msks.permute((0, 2, 3, 1))\nimgs.size(), msks.size()","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:48:46.030782Z","iopub.execute_input":"2021-11-10T14:48:46.031468Z","iopub.status.idle":"2021-11-10T14:48:56.905728Z","shell.execute_reply.started":"2021-11-10T14:48:46.031431Z","shell.execute_reply":"2021-11-10T14:48:56.904654Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 📈 Visualization","metadata":{}},{"cell_type":"code","source":"def plot_batch(imgs, msks, size=3):\n    for idx in range(size):\n        plt.figure(figsize=(4*3, 5))\n\n        plt.subplot(1, 3, 1); plt.imshow(imgs[idx])\n        plt.title('image', fontsize=15)\n        plt.axis('OFF')\n\n        plt.subplot(1, 3, 2); plt.imshow(msks[idx])\n        plt.title('mask', fontsize=15)\n        plt.axis('OFF')\n\n        plt.subplot(1, 3, 3); plt.imshow(imgs[idx]); plt.imshow(msks[idx], alpha=0.3)\n        plt.title('overlay', fontsize=15)\n        plt.axis('OFF')\n        \n        plt.tight_layout()\n        plt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2021-11-10T14:49:02.265829Z","iopub.execute_input":"2021-11-10T14:49:02.266152Z","iopub.status.idle":"2021-11-10T14:49:02.277403Z","shell.execute_reply.started":"2021-11-10T14:49:02.26612Z","shell.execute_reply":"2021-11-10T14:49:02.274922Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plot_batch(imgs, msks, size=3)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:50:55.636644Z","iopub.execute_input":"2021-11-10T14:50:55.636996Z","iopub.status.idle":"2021-11-10T14:50:57.022012Z","shell.execute_reply.started":"2021-11-10T14:50:55.636963Z","shell.execute_reply":"2021-11-10T14:50:57.021097Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 📦 Model\n","metadata":{}},{"cell_type":"markdown","source":"## UNet\n\n<img src=\"https://miro.medium.com/max/875/1*f7YOaE4TWubwaFF7Z1fzNw.png\" width=\"600\">\n\n📌 **Pros**:\n* Performs well even with smaller data\n* Can be used with `imagenet` pretrain models\n\n📌 **Cons**:\n* Struggles with **edge** cases\n* Semantic Difference in **Skip Connection**","metadata":{}},{"cell_type":"code","source":"import segmentation_models_pytorch as smp\n\ndef build_model():\n    model = smp.Unet(\n        encoder_name=CFG.backbone,      # choose encoder, e.g. mobilenet_v2 or efficientnet-b7\n        encoder_weights=\"imagenet\",     # use `imagenet` pre-trained weights for encoder initialization\n        in_channels=3,                  # model input channels (1 for gray-scale images, 3 for RGB, etc.)\n        classes=CFG.num_classes,        # model output channels (number of classes in your dataset)\n        activation=None,\n    )\n    model.to(CFG.device)\n    return model\n\ndef load_model(path):\n    model = build_model()\n    model.load_state_dict(torch.load(path))\n    model.eval()\n    return model","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:51:41.896393Z","iopub.execute_input":"2021-11-10T14:51:41.897201Z","iopub.status.idle":"2021-11-10T14:51:43.724061Z","shell.execute_reply.started":"2021-11-10T14:51:41.897163Z","shell.execute_reply":"2021-11-10T14:51:43.723103Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# test\nimg = torch.randn(1, 3, *CFG.img_size).to(CFG.device)\nimg = (img - img.min())/(img.max() - img.min())\nmodel = build_model()\nmodel(img)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:51:43.726043Z","iopub.execute_input":"2021-11-10T14:51:43.726784Z","iopub.status.idle":"2021-11-10T14:51:50.840864Z","shell.execute_reply.started":"2021-11-10T14:51:43.72675Z","shell.execute_reply":"2021-11-10T14:51:50.839893Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🔧 Loss Function","metadata":{}},{"cell_type":"code","source":"JaccardLoss = smp.losses.JaccardLoss(mode='binary')\nJaccard     = smp.losses.JaccardLoss(mode='binary', from_logits=False)\nDice        = smp.losses.DiceLoss(mode='binary', from_logits=False)\nBCELoss     = smp.losses.SoftBCEWithLogitsLoss()\n\ndef criterion(y_pred, y_true):\n    return JaccardLoss(y_pred, y_true)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:15.877305Z","iopub.execute_input":"2021-11-10T14:59:15.877663Z","iopub.status.idle":"2021-11-10T14:59:17.16209Z","shell.execute_reply.started":"2021-11-10T14:59:15.877564Z","shell.execute_reply":"2021-11-10T14:59:17.161115Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🚄 Training Function","metadata":{}},{"cell_type":"code","source":"def train_one_epoch(model, optimizer, scheduler, dataloader, device, epoch):\n    model.train()\n    scaler = amp.GradScaler()\n    \n    dataset_size = 0\n    running_loss = 0.0\n    \n    pbar = tqdm(enumerate(dataloader), total=len(dataloader), desc='Train ')\n    for step, (images, masks) in pbar:         \n        images = images.to(device, dtype=torch.float)\n        masks  = masks.to(device, dtype=torch.float)\n        \n        batch_size = images.size(0)\n        \n        with amp.autocast(enabled=True):\n            y_pred = model(images)\n            loss   = criterion(y_pred, masks)\n            loss   = loss / CFG.n_accumulate\n            \n        scaler.scale(loss).backward()\n    \n        if (step + 1) % CFG.n_accumulate == 0:\n            scaler.step(optimizer)\n            scaler.update()\n\n            # zero the parameter gradients\n            optimizer.zero_grad()\n\n            if scheduler is not None:\n                scheduler.step()\n                \n        running_loss += (loss.item() * batch_size)\n        dataset_size += batch_size\n        \n        epoch_loss = running_loss / dataset_size\n        \n        mem = torch.cuda.memory_reserved() / 1E9 if torch.cuda.is_available() else 0\n        \n        pbar.set_postfix(train_loss=f'{epoch_loss:0.4f}',\n                        lr=optimizer.param_groups[0]['lr'],\n                        gpu_memory=f'{mem:0.2f} GB')\n    torch.cuda.empty_cache()\n    gc.collect()\n    \n    return epoch_loss","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:17.164858Z","iopub.execute_input":"2021-11-10T14:59:17.165448Z","iopub.status.idle":"2021-11-10T14:59:18.421179Z","shell.execute_reply.started":"2021-11-10T14:59:17.165384Z","shell.execute_reply":"2021-11-10T14:59:18.420155Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 👀 Validation Function","metadata":{}},{"cell_type":"code","source":"@torch.no_grad()\ndef valid_one_epoch(model, dataloader, device, epoch):\n    model.eval()\n    \n    dataset_size = 0\n    running_loss = 0.0\n    \n    TARGETS = []\n    PREDS   = []\n    \n    pbar = tqdm(enumerate(dataloader), total=len(dataloader), desc='Valid ')\n    for step, (images, masks) in pbar:        \n        images  = images.to(device, dtype=torch.float)\n        masks   = masks.to(device, dtype=torch.float)\n        \n        batch_size = images.size(0)\n        \n        y_pred  = model(images)\n        loss    = criterion(y_pred, masks)\n        \n        running_loss += (loss.item() * batch_size)\n        dataset_size += batch_size\n        \n        epoch_loss = running_loss / dataset_size\n        \n        PREDS.append(nn.Sigmoid()(y_pred))\n        TARGETS.append(masks)\n        \n        mem = torch.cuda.memory_reserved() / 1E9 if torch.cuda.is_available() else 0\n        \n        pbar.set_postfix(valid_loss=f'{epoch_loss:0.4f}',\n                        lr=optimizer.param_groups[0]['lr'],\n                        gpu_memory=f'{mem:0.2f} GB')\n    \n    TARGETS = torch.cat(TARGETS,dim=0).to(torch.float32)\n    PREDS   = (torch.cat(PREDS, dim=0)>0.5).to(torch.float32)\n    val_dice    = 1. - Dice(TARGETS, PREDS).cpu().detach().numpy()\n    val_jaccard = 1. - Jaccard(TARGETS, PREDS).cpu().detach().numpy()\n    val_scores  = [val_dice, val_jaccard]\n    torch.cuda.empty_cache()\n    gc.collect()\n    \n    return epoch_loss, val_scores","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:18.423189Z","iopub.execute_input":"2021-11-10T14:59:18.423877Z","iopub.status.idle":"2021-11-10T14:59:19.637279Z","shell.execute_reply.started":"2021-11-10T14:59:18.423828Z","shell.execute_reply":"2021-11-10T14:59:19.636321Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🏃 Run Training","metadata":{}},{"cell_type":"code","source":"def run_training(model, optimizer, scheduler, device, num_epochs):\n    # To automatically log gradients\n    wandb.watch(model, log_freq=100)\n    \n    if torch.cuda.is_available():\n        print(\"cuda: {}\\n\".format(torch.cuda.get_device_name()))\n    \n    start = time.time()\n    best_model_wts = copy.deepcopy(model.state_dict())\n    best_dice  = -np.inf\n    best_epoch = -1\n    history = defaultdict(list)\n    \n    for epoch in range(1, num_epochs + 1): \n        gc.collect()\n        print(f'Epoch {epoch}/{num_epochs}', end='')\n        train_loss = train_one_epoch(model, optimizer, scheduler, \n                                           dataloader=train_loader, \n                                           device=CFG.device, epoch=epoch)\n        \n        val_loss, val_scores = valid_one_epoch(model, valid_loader, \n                                                         device=CFG.device, \n                                                         epoch=epoch)\n        val_dice, val_jaccard = val_scores\n    \n        history['Train Loss'].append(train_loss)\n        history['Valid Loss'].append(val_loss)\n        history['Valid Dice'].append(val_dice)\n        history['Valid Jaccard'].append(val_jaccard)\n        \n        # Log the metrics\n        wandb.log({\"Train Loss\": train_loss, \n                   \"Valid Loss\": val_loss,\n                   \"Valid Dice\": val_dice,\n                   \"Valid Jaccard\": val_jaccard,\n                   \"LR\":scheduler.get_last_lr()[0]})\n        \n        print(f'Valid Dice: {val_dice:0.4f} | Valid Jaccard: {val_jaccard:0.4f}')\n        \n        # deep copy the model\n        if val_dice >= best_dice:\n            print(f\"{c_}Valid Dice Improved ({best_dice:0.4f} ---> {val_dice:0.4f})\")\n            best_dice    = val_dice\n            best_jaccard = val_jaccard\n            best_epoch   = epoch\n            run.summary[\"Best Dice\"]    = best_dice\n            run.summary[\"Best Jaccard\"] = best_jaccard\n            run.summary[\"Best Epoch\"]   = best_epoch\n            best_model_wts = copy.deepcopy(model.state_dict())\n            PATH = f\"best_epoch-{fold:02d}.bin\"\n            torch.save(model.state_dict(), PATH)\n            # Save a model file from the current directory\n            wandb.save(PATH)\n            print(f\"Model Saved{sr_}\")\n            \n        last_model_wts = copy.deepcopy(model.state_dict())\n        PATH = f\"last_epoch-{fold:02d}.bin\"\n        torch.save(model.state_dict(), PATH)\n            \n        print(); print()\n    \n    end = time.time()\n    time_elapsed = end - start\n    print('Training complete in {:.0f}h {:.0f}m {:.0f}s'.format(\n        time_elapsed // 3600, (time_elapsed % 3600) // 60, (time_elapsed % 3600) % 60))\n    print(\"Best Score: {:.4f}\".format(best_dice))\n    \n    # load best model weights\n    model.load_state_dict(best_model_wts)\n    \n    return model, history","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:19.639645Z","iopub.execute_input":"2021-11-10T14:59:19.64003Z","iopub.status.idle":"2021-11-10T14:59:20.993645Z","shell.execute_reply.started":"2021-11-10T14:59:19.639984Z","shell.execute_reply":"2021-11-10T14:59:20.992406Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🔍 Optimizer\n\n<img src=\"https://mlfromscratch.com/content/images/2019/12/saddle.gif\" width=500>","metadata":{}},{"cell_type":"code","source":"optimizer = optim.Adam(model.parameters(), lr=CFG.lr, weight_decay=CFG.wd)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:20.998116Z","iopub.execute_input":"2021-11-10T14:59:20.998363Z","iopub.status.idle":"2021-11-10T14:59:22.361485Z","shell.execute_reply.started":"2021-11-10T14:59:20.998331Z","shell.execute_reply":"2021-11-10T14:59:22.360442Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ⚓ Scheduler\n* **CosineAnnealingWarmRestarts**:\n\n<img src=\"https://user-images.githubusercontent.com/20135989/68026469-cccc5200-fcea-11e9-9399-11e4a5a5eae3.png\" width=500>\n\n* **CosineAnnealingLR**:\n\n<img src=\"https://www.researchgate.net/publication/343341777/figure/fig1/AS:919348742979584@1596201229282/The-cosine-annealing-leaning-rate-in-different-Tmax.png\" width=500>\n\n* **ReduceLROnPlateau**:\n\n<img src=\"https://miro.medium.com/max/1400/1*L6Dq6AgpWwjRNzmJ8EsEVA.png\" width=500>\n\n* **ExponentialLR**:\n\n<img src=\"https://miro.medium.com/max/1400/1*CgioTtU7G7mL202dL7CVfg.png\" width=500>","metadata":{}},{"cell_type":"code","source":"def fetch_scheduler(optimizer):\n    if CFG.scheduler == 'CosineAnnealingLR':\n        scheduler = lr_scheduler.CosineAnnealingLR(optimizer,T_max=CFG.T_max, \n                                                   eta_min=CFG.min_lr)\n    elif CFG.scheduler == 'CosineAnnealingWarmRestarts':\n        scheduler = lr_scheduler.CosineAnnealingWarmRestarts(optimizer,T_0=CFG.T_0, \n                                                             eta_min=CFG.min_lr)\n    elif CFG.scheduler == 'ReduceLROnPlateau':\n        scheduler = lr_scheduler.ReduceLROnPlateau(optimizer,\n                                                   mode='min',\n                                                   factor=0.1,\n                                                   patience=7,\n                                                   threshold=0.0001,\n                                                   min_lr=CFG.min_lr,)\n    elif CFG.scheduer == 'ExponentialLR':\n        scheduler = lr_scheduler.ExponentialLR(optimizer, gamma=0.85)\n    elif CFG.scheduler == None:\n        return None\n        \n    return scheduler","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:22.365454Z","iopub.execute_input":"2021-11-10T14:59:22.369618Z","iopub.status.idle":"2021-11-10T14:59:23.594669Z","shell.execute_reply.started":"2021-11-10T14:59:22.369583Z","shell.execute_reply":"2021-11-10T14:59:23.593628Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"scheduler = fetch_scheduler(optimizer)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T14:59:23.599765Z","iopub.execute_input":"2021-11-10T14:59:23.602829Z","iopub.status.idle":"2021-11-10T14:59:24.922907Z","shell.execute_reply.started":"2021-11-10T14:59:23.602793Z","shell.execute_reply":"2021-11-10T14:59:24.921952Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 🚅 Training","metadata":{}},{"cell_type":"code","source":"for fold in range(CFG.n_fold):\n    print(f'#'*15)\n    print(f'### Fold: {fold}')\n    print(f'#'*15)\n    run = wandb.init(project='sartorius-public', \n                     config={k:v for k, v in dict(vars(CFG)).items() if '__' not in k},\n                     anonymous='must',\n                     name=f\"fold-{fold}|dim-{CFG.img_size}|model-{CFG.model_name}\",\n                     group=CFG.exp_name,\n                    )\n    train_loader, valid_loader = prepare_loaders(fold=fold)\n    model     = build_model()\n    optimizer = optim.Adam(model.parameters(), lr=CFG.lr, weight_decay=CFG.wd)\n    scheduler = fetch_scheduler(optimizer)\n    model, history = run_training(model, optimizer, scheduler,\n                                  device=CFG.device,\n                                  num_epochs=CFG.epochs if not CFG.debug else 2)\n    run.finish()\n    display(ipd.IFrame(run.url, width=1000, height=720))","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-11-10T14:59:24.92591Z","iopub.execute_input":"2021-11-10T14:59:24.926239Z","iopub.status.idle":"2021-11-10T15:02:35.836824Z","shell.execute_reply.started":"2021-11-10T14:59:24.926193Z","shell.execute_reply":"2021-11-10T15:02:35.835235Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ✨ Overview\n\n![image.png](attachment:312fcb5e-4c91-4800-b273-82c80a6c4db7.png)","metadata":{},"attachments":{"312fcb5e-4c91-4800-b273-82c80a6c4db7.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"# 🔭 Prediction","metadata":{}},{"cell_type":"code","source":"test_dataset = BuildDataset(test_df, transforms=data_transforms['valid'])\ntest_loader  = DataLoader(test_dataset, batch_size=3, \n                          num_workers=4, shuffle=False, pin_memory=True)\nimgs = next(iter(test_loader))\nimgs = imgs.to(CFG.device, dtype=torch.float)\n\npreds = []\nfor fold in range(CFG.n_fold):\n    model = load_model(f\"best_epoch-{fold:02d}.bin\")\n    with torch.no_grad():\n        pred = model(imgs)\n        pred = nn.Sigmoid()(pred)\n    preds.append(pred)\n    \nimgs  = imgs.permute((0,2,3,1)).cpu().detach()\npreds = torch.mean(torch.stack(preds, dim=0), dim=0).permute((0,2,3,1)).cpu().detach()","metadata":{"execution":{"iopub.status.busy":"2021-11-10T15:03:53.434003Z","iopub.execute_input":"2021-11-10T15:03:53.434311Z","iopub.status.idle":"2021-11-10T15:03:54.219481Z","shell.execute_reply.started":"2021-11-10T15:03:53.434276Z","shell.execute_reply":"2021-11-10T15:03:54.218334Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plot_batch(imgs/255.0, preds)","metadata":{"execution":{"iopub.status.busy":"2021-11-10T15:03:54.222788Z","iopub.execute_input":"2021-11-10T15:03:54.223039Z","iopub.status.idle":"2021-11-10T15:03:55.600302Z","shell.execute_reply.started":"2021-11-10T15:03:54.223007Z","shell.execute_reply":"2021-11-10T15:03:55.59934Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# ✂️ Remove Files","metadata":{}},{"cell_type":"code","source":"!rm -r ./wandb","metadata":{"execution":{"iopub.status.busy":"2021-11-08T18:17:38.800846Z","iopub.status.idle":"2021-11-08T18:17:38.801478Z","shell.execute_reply.started":"2021-11-08T18:17:38.801224Z","shell.execute_reply":"2021-11-08T18:17:38.801247Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 💡 Reference\n* [[Pytorch] Hybrid Swin Transformer + CNN](https://www.kaggle.com/debarshichanda/pytorch-hybrid-swin-transformer-cnn) by @debarshichanda","metadata":{}}]}