contrail-net-vision.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"from utils_directory_tree_generator import get_directory_tree\n\ntree_generator = get_directory_tree(\n    start_path='/kaggle/input',\n    max_depth=5,\n    include_files=True,\n    sort_by='type',\n    reverse=False,\n    max_items=5\n)\nfor line in tree_generator:\n    print(line)","metadata":{"execution":{"iopub.status.busy":"2023-08-06T16:44:47.952368Z","iopub.execute_input":"2023-08-06T16:44:47.952815Z","iopub.status.idle":"2023-08-06T16:45:04.084348Z","shell.execute_reply.started":"2023-08-06T16:44:47.952777Z","shell.execute_reply":"2023-08-06T16:45:04.081777Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"input\n    google-research-identify-contrails-reduce-global-warming\n        validation\n            3687499407028137410\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n            6558861185867890815\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n            7355354609194882312\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n            7547747455642200110\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n        test\n            1002653297254493116\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n            1000834164244036115\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n        train\n            1284412112608546821\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n            7457695218848685981\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n            836236084461732921\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n            7829917977180135058\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n        validation_metadata.json\ninput\n    google-research-identify-contrails-reduce-global-warming\n        validation\n            3687499407028137410\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n            6558861185867890815\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n            7355354609194882312\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n            7547747455642200110\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n            5456834089979970017\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n        test\n            1002653297254493116\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n            1000834164244036115\n                band_10.npy\n                band_14.npy\n                band_15.npy\n                band_16.npy\n                band_08.npy\n        train\n            1284412112608546821\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n                band_16.npy\n            7457695218848685981\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n                band_16.npy\n            836236084461732921\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n                band_16.npy\n            7829917977180135058\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n                band_16.npy\n            5319255125658459358\n                band_10.npy\n                band_14.npy\n                human_individual_masks.npy\n                band_15.npy\n                band_16.npy\n        validation_metadata.json\n        train_metadata.json\n","output_type":"stream"}]},{"cell_type":"code","source":"! pip install -q segmentation-models-pytorch --upgrade","metadata":{"execution":{"iopub.status.busy":"2023-08-06T16:45:04.086834Z","iopub.execute_input":"2023-08-06T16:45:04.087246Z","iopub.status.idle":"2023-08-06T16:45:15.615362Z","shell.execute_reply.started":"2023-08-06T16:45:04.087210Z","shell.execute_reply":"2023-08-06T16:45:15.613670Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"import segmentation_models_pytorch\nprint(segmentation_models_pytorch.__version__)\n","metadata":{"execution":{"iopub.status.busy":"2023-08-06T16:45:15.617219Z","iopub.execute_input":"2023-08-06T16:45:15.618218Z","iopub.status.idle":"2023-08-06T16:45:15.624767Z","shell.execute_reply.started":"2023-08-06T16:45:15.618176Z","shell.execute_reply":"2023-08-06T16:45:15.623431Z"},"trusted":true},"execution_count":7,"outputs":[{"name":"stdout","text":"0.3.3\n","output_type":"stream"}]},{"cell_type":"code","source":"import os\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.optim import Adam\nfrom torch.nn import BCEWithLogitsLoss\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision.transforms import Compose, Lambda, Resize, RandomAffine, ColorJitter\nfrom torch.nn.functional import pad\nfrom PIL import Image\nfrom utils_contrails_loss_functions import DiceLoss, FocalLoss\nimport segmentation_models_pytorch as smp\nimport pytorch_lightning as pl\n\n# Dataset paths\ntrain_data_path = \"/kaggle/input/google-research-identify-contrails-reduce-global-warming/train\"\nval_data_path = \"/kaggle/input/google-research-identify-contrails-reduce-global-warming/validation\"\ntest_data_path = \"/kaggle/input/google-research-identify-contrails-reduce-global-warming/test\"\n\n\n# Data Loader\nclass ContrailDataset(Dataset):\n    def __init__(self, root_dir, transform=None):\n        self.root_dir = root_dir\n        self.transform = transform\n        self.record_dirs = [os.path.join(root_dir, d) for d in os.listdir(root_dir) if os.path.isdir(os.path.join(root_dir, d))]\n        self.record_dirs.sort(key=lambda x: os.path.getsize(x)) # Sort dataset based on sequence length\n\n        # Updated transformations\n        self.transform = Compose([\n            Lambda(lambda x: Image.fromarray((x.transpose(1, 2, 0) * 255).astype(np.uint8))),\n            ColorJitter(brightness=0.1, contrast=0.1),\n            Lambda(lambda x: np.array(x)),\n            Lambda(lambda x: x.transpose(2, 0, 1)),\n            Lambda(lambda x: torch.from_numpy(x).float()),\n            RandomAffine(degrees=0, scale=(0.8, 1.2), shear=20),\n            Resize((320, 320)),\n            Lambda(lambda x: pad(x, (0, 0, 0, (32 - x.shape[1] % 32) % 32)))\n            \n        ])\n        self.target_transform = Compose([\n            Lambda(lambda x: torch.from_numpy(x).float())\n        ])\n\n    def __len__(self):\n        return len(self.record_dirs)\n\n    def __getitem__(self, idx):\n        record_dir = self.record_dirs[idx]\n        \n        # Updated to use bands from 13 to 16 (4 bands)\n        bands = [np.load(os.path.join(record_dir, f\"band_{band}.npy\"))[..., 0] for band in [13, 14, 15, 16]]\n        bands_array = np.stack(bands)\n        sample = bands_array\n\n        # Load aggregated ground truth mask\n        target_path = os.path.join(record_dir, 'human_pixel_masks.npy')\n        target = np.load(target_path) if os.path.exists(target_path) else None\n\n        # Apply the target transformations to the target\n        if target is not None:\n            # Ensure the target has only one channel and appropriate shape.\n            target = np.mean(target, axis=(0, 1))\n\n            # Ensure the data type is uint8 and values range between 0 and 255\n            target = (target * 255).astype(np.uint8)\n\n            # Convert numpy array to PIL Image, then resize, and convert back to numpy array\n            target_pil = Image.fromarray(target)\n\n            # Resize the target to 256x256 to match the model's output\n            target_resized = np.array(Resize((256, 256))(target_pil))\n\n            # Normalize to [0, 1]\n            target_resized = target_resized / 255.0\n\n            # Convert to PyTorch tensors\n            sample = torch.tensor(sample, dtype=torch.float32)\n            if target is not None:\n                target = torch.tensor(target_resized, dtype=torch.float32).unsqueeze(0)  # Add channel dimension\n\n            return sample, target\n        \nclass CombinedLoss(nn.Module):\n    def __init__(self):\n        super(CombinedLoss, self).__init__()\n        self.dice_loss = DiceLoss()\n        self.focal_loss = FocalLoss()\n    \n    def forward(self, inputs, targets):\n        dice = self.dice_loss(inputs, targets)\n        focal = self.focal_loss(inputs, targets)\n        return dice + focal\n\nclass ContrailModel(pl.LightningModule):\n    def __init__(self, in_channels):\n        super(ContrailModel, self).__init__()\n        self.model = smp.Unet(\n            encoder_name=\"resnet34\",\n            encoder_weights=\"imagenet\",\n            in_channels=in_channels,\n            classes=1\n        )\n        self.loss = CombinedLoss()\n        self.sigmoid = nn.Sigmoid()\n\n    def forward(self, x):\n        x = self.model(x)\n        x = self.sigmoid(x)\n        # Ensure the outputs are strictly within the [0, 1] range\n        x = torch.clamp(x, 1e-5, 1-1e-5)\n        return x\n\n    def training_step(self, batch, batch_idx):\n        x, y = batch\n        y_hat = self(x)\n        print(y_hat.shape)\n        print(y.shape)\n        loss_val = self.loss(y_hat, y)  #  compute combined loss\n        self.log('train_loss', loss_val)\n        return loss_val\n\n    def configure_optimizers(self):\n        return Adam(self.parameters(), lr=0.001)\n\n# Training Function\ndef train_model(train_dataset, val_dataset, model, epochs=10, batch_size=8, lr=0.001):\n    # Use the collate function in data loader\n    train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n    val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False)\n    optimizer = Adam(model.parameters(), lr=lr)\n    criterion = BCEWithLogitsLoss()\n    \n    for epoch in range(epochs):\n        model.train()\n        for images, masks in train_loader: \n            optimizer.zero_grad()\n            outputs = model(images)\n            loss = criterion(outputs, masks) \n            loss.backward()\n            optimizer.step()\n        \n        model.eval()\n        val_loss = sum(criterion(model(images), masks).item() for images, masks in val_loader) / len(val_loader)\n        print(f\"Epoch {epoch+1}/{epochs}, Validation Loss: {val_loss:.4f}\")\n\n# Instantiate datasets\ndataset_train = ContrailDataset(root_dir=train_data_path)\ndataset_val = ContrailDataset(root_dir=val_data_path)\n\n# Instantiate model\nmodel = ContrailModel(in_channels=4)\n\n\n# Use PyTorch Lightning's Trainer to train the model\ntrainer = pl.Trainer(max_epochs=10)\ntrainer.fit(model, DataLoader(dataset_train, batch_size=8, shuffle=True), DataLoader(dataset_val, batch_size=8))","metadata":{"execution":{"iopub.status.busy":"2023-08-06T17:41:08.222060Z","iopub.execute_input":"2023-08-06T17:41:08.222593Z","iopub.status.idle":"2023-08-06T21:12:50.682224Z","shell.execute_reply.started":"2023-08-06T17:41:08.222554Z","shell.execute_reply":"2023-08-06T21:12:50.677780Z"},"collapsed":true,"jupyter":{"outputs_hidden":true},"trusted":true},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":"Training: 0it [00:00, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"75c80ee0265747e28253ecb380be5cdb"}},"metadata":{}},{"name":"stdout","text":"torch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([1, 1, 256, 256])\ntorch.Size([1, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\ntorch.Size([8, 1, 256, 256])\n","output_type":"stream"},{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py:52: UserWarning: Detected KeyboardInterrupt, attempting graceful shutdown...\n  rank_zero_warn(\"Detected KeyboardInterrupt, attempting graceful shutdown...\")\n","output_type":"stream"}]},{"cell_type":"code","source":"# Check the installed version\n! pip show pytorch_lightning\n\n# Update to the latest version\n# ! pip install -q pytorch_lightning --upgrade\n\n!pip install -q pytorch_lightning==1.4.9\n\n","metadata":{"execution":{"iopub.status.busy":"2023-08-06T21:24:10.647456Z","iopub.execute_input":"2023-08-06T21:24:10.648048Z","iopub.status.idle":"2023-08-06T21:24:49.514277Z","shell.execute_reply.started":"2023-08-06T21:24:10.648011Z","shell.execute_reply":"2023-08-06T21:24:49.512514Z"},"trusted":true},"execution_count":22,"outputs":[{"name":"stdout","text":"Name: pytorch-lightning\nVersion: 2.0.6\nSummary: PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.\nHome-page: https://github.com/Lightning-AI/lightning\nAuthor: Lightning AI et al.\nAuthor-email: pytorch@lightning.ai\nLicense: Apache-2.0\nLocation: /opt/conda/lib/python3.10/site-packages\nRequires: fsspec, lightning-utilities, numpy, packaging, PyYAML, torch, torchmetrics, tqdm, typing-extensions\nRequired-by: \n","output_type":"stream"}]},{"cell_type":"code","source":"import os\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.optim import Adam\nfrom torch.utils.data import Dataset, DataLoader\nimport torchvision.transforms as transforms\nfrom PIL import Image\nfrom PIL import ImageOps\nfrom utils_contrails_loss_functions import DiceLoss, FocalLoss\nimport segmentation_models_pytorch as smp\nimport pytorch_lightning as pl\n\n# Dataset paths\ntrain_data_path = \"/kaggle/input/google-research-identify-contrails-reduce-global-warming/train\"\nval_data_path = \"/kaggle/input/google-research-identify-contrails-reduce-global-warming/validation\"\n\nclass ContrailDataset(Dataset):\n    def __init__(self, root_dir):\n        self.root_dir = root_dir\n        self.record_dirs = [os.path.join(root_dir, d) for d in os.listdir(root_dir) if os.path.isdir(os.path.join(root_dir, d))]\n        self.record_dirs.sort(key=lambda x: os.path.getsize(x))\n        \n        self.transform = transforms.Compose([\n            transforms.ColorJitter(brightness=0.1, contrast=0.1),\n            transforms.RandomAffine(degrees=0, scale=(0.8, 1.2), shear=20),\n            transforms.Resize((320, 320)),\n            transforms.Lambda(lambda x: ImageOps.pad(x, (0, 0, 0, max(0, (32 - x.size[1] % 32) % 32))))\n        ])\n\n    def __len__(self):\n        return len(self.record_dirs)\n\n    def __getitem__(self, idx):\n        record_dir = self.record_dirs[idx]\n        bands = [np.load(os.path.join(record_dir, f\"band_{band}.npy\"))[..., 0] for band in [13, 14, 15, 16]]\n        bands_array = np.stack(bands)\n        image = Image.fromarray((bands_array.transpose(1, 2, 0) * 255).astype(np.uint8))\n        sample = self.transform(image)\n        \n        # Load aggregated ground truth mask\n        target_path = os.path.join(record_dir, 'human_pixel_masks.npy')\n        if os.path.exists(target_path):\n            target = np.mean(np.load(target_path), axis=(0, 1))\n            target = Image.fromarray((target * 255).astype(np.uint8))\n            target = transforms.Resize((256, 256))(target)\n            target = torch.tensor(np.array(target), dtype=torch.float32) / 255.0\n        else:\n            target = None\n\n        return transforms.ToTensor()(sample), target.unsqueeze(0) if target is not None else None\n\nclass CombinedLoss(nn.Module):\n    def __init__(self):\n        super(CombinedLoss, self).__init__()\n        self.dice_loss = DiceLoss()\n        self.focal_loss = FocalLoss()\n\n    def forward(self, inputs, targets):\n        return self.dice_loss(inputs, targets) + self.focal_loss(inputs, targets)\n\nclass ContrailModel(pl.LightningModule):\n    def __init__(self, in_channels):\n        super(ContrailModel, self).__init__()\n        self.model = smp.Unet(encoder_name=\"resnet34\", encoder_weights=\"imagenet\", in_channels=in_channels, classes=1)\n        self.loss = CombinedLoss()\n\n    def forward(self, x):\n        x = torch.sigmoid(self.model(x))\n        return torch.clamp(x, 1e-5, 1-1e-5)\n\n    def training_step(self, batch, batch_idx):\n        x, y = batch\n        y_hat = self(x)\n        loss_val = self.loss(y_hat, y)\n        self.log('train_loss', loss_val)\n        return loss_val\n\n    def configure_optimizers(self):\n        return Adam(self.parameters(), lr=0.001)\n\n# Instantiate datasets\ndataset_train = ContrailDataset(root_dir=train_data_path)\ndataset_val = ContrailDataset(root_dir=val_data_path)\n\n# Instantiate model\nmodel = ContrailModel(in_channels=4)\n\n# Use PyTorch Lightning's Trainer to train the model without the gpus argument\ntrainer = pl.Trainer(max_epochs=10)\ntrainer.fit(model, DataLoader(dataset_train, batch_size=8, shuffle=True), DataLoader(dataset_val, batch_size=8))\n","metadata":{"execution":{"iopub.status.busy":"2023-08-06T21:38:13.723490Z","iopub.execute_input":"2023-08-06T21:38:13.723993Z","iopub.status.idle":"2023-08-06T21:38:23.420430Z","shell.execute_reply.started":"2023-08-06T21:38:13.723958Z","shell.execute_reply":"2023-08-06T21:38:23.418798Z"},"trusted":true},"execution_count":28,"outputs":[{"output_type":"display_data","data":{"text/plain":"Training: 0it [00:00, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a19048ab09134ecdb1687edc4635527a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m<module>\u001b[0m:\u001b[94m91\u001b[0m                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m88 \u001b[0m                                                                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m89 \u001b[0m\u001b[2m# Use PyTorch Lightning's Trainer to train the model without the gpus argument\u001b[0m              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m90 \u001b[0mtrainer = pl.Trainer(max_epochs=\u001b[94m10\u001b[0m)                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m91 trainer.fit(model, DataLoader(dataset_train, batch_size=\u001b[94m8\u001b[0m, shuffle=\u001b[94mTrue\u001b[0m), DataLoader(dat    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m92 \u001b[0m                                                                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/\u001b[0m\u001b[1;33mtrainer.py\u001b[0m:\u001b[94m531\u001b[0m in \u001b[92mfit\u001b[0m          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 528 \u001b[0m\u001b[2;33m│   │   \u001b[0m\u001b[33m\"\"\"\u001b[0m                                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 529 \u001b[0m\u001b[2m│   │   \u001b[0mmodel = _maybe_unwrap_optimized(model)                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 530 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.strategy._lightning_module = model                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 531 \u001b[2m│   │   \u001b[0mcall._call_and_handle_interrupt(                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 532 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m, \u001b[96mself\u001b[0m._fit_impl, model, train_dataloaders, val_dataloaders, datamodule,  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 533 \u001b[0m\u001b[2m│   │   \u001b[0m)                                                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 534 \u001b[0m                                                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m_call_and_handle_interrupt\u001b[0m:\u001b[94m42\u001b[0m                                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 39 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mtry\u001b[0m:                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 40 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m trainer.strategy.launcher \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m:                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 41 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer,    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 42 \u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m trainer_fn(*args, **kwargs)                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 43 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 44 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mexcept\u001b[0m _TunerExitException:                                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 45 \u001b[0m\u001b[2m│   │   \u001b[0m_call_teardown_hook(trainer)                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/\u001b[0m\u001b[1;33mtrainer.py\u001b[0m:\u001b[94m570\u001b[0m in \u001b[92m_fit_impl\u001b[0m    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 567 \u001b[0m\u001b[2m│   │   │   \u001b[0mmodel_provided=\u001b[94mTrue\u001b[0m,                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 568 \u001b[0m\u001b[2m│   │   │   \u001b[0mmodel_connected=\u001b[96mself\u001b[0m.lightning_module \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m,                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 569 \u001b[0m\u001b[2m│   │   \u001b[0m)                                                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 570 \u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._run(model, ckpt_path=ckpt_path)                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 571 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 572 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94massert\u001b[0m \u001b[96mself\u001b[0m.state.stopped                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 573 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.training = \u001b[94mFalse\u001b[0m                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/\u001b[0m\u001b[1;33mtrainer.py\u001b[0m:\u001b[94m975\u001b[0m in \u001b[92m_run\u001b[0m         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 972 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# ----------------------------\u001b[0m                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 973 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# RUN THE TRAINER\u001b[0m                                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 974 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# ----------------------------\u001b[0m                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 975 \u001b[2m│   │   \u001b[0mresults = \u001b[96mself\u001b[0m._run_stage()                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 976 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 977 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# ----------------------------\u001b[0m                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 978 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# POST-Training CLEAN UP\u001b[0m                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/\u001b[0m\u001b[1;33mtrainer.py\u001b[0m:\u001b[94m1018\u001b[0m in \u001b[92m_run_stage\u001b[0m  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m1015 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mwith\u001b[0m isolate_rng():                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m1016 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._run_sanity_check()                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m1017 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mwith\u001b[0m torch.autograd.set_detect_anomaly(\u001b[96mself\u001b[0m._detect_anomaly):                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1018 \u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.fit_loop.run()                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m1019 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mNone\u001b[0m                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m1020 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mRuntimeError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33mUnexpected state \u001b[0m\u001b[33m{\u001b[0m\u001b[96mself\u001b[0m.state\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m1021 \u001b[0m                                                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/\u001b[0m\u001b[1;33mfit_loop.py\u001b[0m:\u001b[94m201\u001b[0m in \u001b[92mrun\u001b[0m           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m198 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mwhile\u001b[0m \u001b[95mnot\u001b[0m \u001b[96mself\u001b[0m.done:                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m199 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m200 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.on_advance_start()                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m201 \u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.advance()                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m202 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.on_advance_end()                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m203 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._restarting = \u001b[94mFalse\u001b[0m                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m204 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mStopIteration\u001b[0m:                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/\u001b[0m\u001b[1;33mfit_loop.py\u001b[0m:\u001b[94m354\u001b[0m in \u001b[92madvance\u001b[0m       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m351 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94massert\u001b[0m \u001b[96mself\u001b[0m._data_fetcher \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m                                              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m352 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._data_fetcher.setup(combined_loader)                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m353 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mwith\u001b[0m \u001b[96mself\u001b[0m.trainer.profiler.profile(\u001b[33m\"\u001b[0m\u001b[33mrun_training_epoch\u001b[0m\u001b[33m\"\u001b[0m):                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m354 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m.epoch_loop.run(\u001b[96mself\u001b[0m._data_fetcher)                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m355 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m356 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mon_advance_end\u001b[0m(\u001b[96mself\u001b[0m) -> \u001b[94mNone\u001b[0m:                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m357 \u001b[0m\u001b[2m│   │   \u001b[0mtrainer = \u001b[96mself\u001b[0m.trainer                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92mrun\u001b[0m:\u001b[94m133\u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m130 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.on_run_start(data_fetcher)                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m131 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mwhile\u001b[0m \u001b[95mnot\u001b[0m \u001b[96mself\u001b[0m.done:                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m132 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m133 \u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.advance(data_fetcher)                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m134 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.on_advance_end()                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m135 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._restarting = \u001b[94mFalse\u001b[0m                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m136 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mStopIteration\u001b[0m:                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92madvance\u001b[0m:\u001b[94m189\u001b[0m                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m186 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.val_loop.restarting = \u001b[94mFalse\u001b[0m                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m187 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m188 \u001b[0m\u001b[2m│   │   \u001b[0mbatch_idx = data_fetcher.fetched \u001b[94mif\u001b[0m \u001b[96misinstance\u001b[0m(data_fetcher, _DataLoaderIterData   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m189 \u001b[2m│   │   \u001b[0mbatch = \u001b[96mnext\u001b[0m(data_fetcher)                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m190 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.batch_progress.is_last_batch = data_fetcher.done                              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m191 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m192 \u001b[0m\u001b[2m│   │   \u001b[0mtrainer = \u001b[96mself\u001b[0m.trainer                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m__next__\u001b[0m:\u001b[94m136\u001b[0m                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m133 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melif\u001b[0m \u001b[95mnot\u001b[0m \u001b[96mself\u001b[0m.done:                                                                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m134 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# this will run only when no pre-fetching was done.\u001b[0m                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m135 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m136 \u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._fetch_next_batch(\u001b[96mself\u001b[0m.dataloader_iter)                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m137 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[2m# consume the batch we just fetched\u001b[0m                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m138 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mbatch = \u001b[96mself\u001b[0m.batches.pop(\u001b[94m0\u001b[0m)                                                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m139 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mStopIteration\u001b[0m \u001b[94mas\u001b[0m ex:                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m_fetch_next_batch\u001b[0m:\u001b[94m150\u001b[0m                                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m147 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_fetch_next_batch\u001b[0m(\u001b[96mself\u001b[0m, iterator: Iterator) -> \u001b[94mNone\u001b[0m:                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m148 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._start_profiler()                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m149 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m150 \u001b[2m│   │   │   \u001b[0mbatch = \u001b[96mnext\u001b[0m(iterator)                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m151 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfinally\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m152 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._stop_profiler()                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m153 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.fetched += \u001b[94m1\u001b[0m                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m__next__\u001b[0m:\u001b[94m284\u001b[0m                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m281 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m282 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__next__\u001b[0m(\u001b[96mself\u001b[0m) -> Any:                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m283 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94massert\u001b[0m \u001b[96mself\u001b[0m._iterator \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m284 \u001b[2m│   │   \u001b[0mout = \u001b[96mnext\u001b[0m(\u001b[96mself\u001b[0m._iterator)                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m285 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96misinstance\u001b[0m(\u001b[96mself\u001b[0m._iterator, _Sequential):                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m286 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m out                                                                     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m287 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m tree_unflatten(out, \u001b[96mself\u001b[0m._spec)                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m__next__\u001b[0m:\u001b[94m65\u001b[0m                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 62 \u001b[0m\u001b[2m│   │   \u001b[0mout = [\u001b[94mNone\u001b[0m] * n  \u001b[2m# values per iterator\u001b[0m                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 63 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfor\u001b[0m i \u001b[95min\u001b[0m \u001b[96mrange\u001b[0m(n):                                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 64 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 65 \u001b[2m│   │   │   │   \u001b[0mout[i] = \u001b[96mnext\u001b[0m(\u001b[96mself\u001b[0m.iterators[i])                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 66 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mStopIteration\u001b[0m:                                                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 67 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._consumed[i] = \u001b[94mTrue\u001b[0m                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 68 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mall\u001b[0m(\u001b[96mself\u001b[0m._consumed):                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/torch/utils/data/\u001b[0m\u001b[1;33mdataloader.py\u001b[0m:\u001b[94m634\u001b[0m in \u001b[92m__next__\u001b[0m           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 631 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m._sampler_iter \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m:                                                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 632 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[2m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[0m                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 633 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._reset()  \u001b[2m# type: ignore[call-arg]\u001b[0m                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 634 \u001b[2m│   │   │   \u001b[0mdata = \u001b[96mself\u001b[0m._next_data()                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 635 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._num_yielded += \u001b[94m1\u001b[0m                                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 636 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m._dataset_kind == _DatasetKind.Iterable \u001b[95mand\u001b[0m \\                          \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 637 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._IterableDataset_len_called \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m \u001b[95mand\u001b[0m \\                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/torch/utils/data/\u001b[0m\u001b[1;33mdataloader.py\u001b[0m:\u001b[94m678\u001b[0m in \u001b[92m_next_data\u001b[0m         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 675 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 676 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_next_data\u001b[0m(\u001b[96mself\u001b[0m):                                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 677 \u001b[0m\u001b[2m│   │   \u001b[0mindex = \u001b[96mself\u001b[0m._next_index()  \u001b[2m# may raise StopIteration\u001b[0m                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 678 \u001b[2m│   │   \u001b[0mdata = \u001b[96mself\u001b[0m._dataset_fetcher.fetch(index)  \u001b[2m# may raise StopIteration\u001b[0m              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 679 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m._pin_memory:                                                              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 680 \u001b[0m\u001b[2m│   │   │   \u001b[0mdata = _utils.pin_memory.pin_memory(data, \u001b[96mself\u001b[0m._pin_memory_device)            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 681 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m data                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/\u001b[0m\u001b[1;33mfetch.py\u001b[0m:\u001b[94m51\u001b[0m in \u001b[92mfetch\u001b[0m             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m48 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mhasattr\u001b[0m(\u001b[96mself\u001b[0m.dataset, \u001b[33m\"\u001b[0m\u001b[33m__getitems__\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mand\u001b[0m \u001b[96mself\u001b[0m.dataset.__getitems__:         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m49 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mdata = \u001b[96mself\u001b[0m.dataset.__getitems__(possibly_batched_index)                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m50 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m51 \u001b[2m│   │   │   │   \u001b[0mdata = [\u001b[96mself\u001b[0m.dataset[idx] \u001b[94mfor\u001b[0m idx \u001b[95min\u001b[0m possibly_batched_index]                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m52 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m53 \u001b[0m\u001b[2m│   │   │   \u001b[0mdata = \u001b[96mself\u001b[0m.dataset[possibly_batched_index]                                     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m54 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m.collate_fn(data)                                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/\u001b[0m\u001b[1;33mfetch.py\u001b[0m:\u001b[94m51\u001b[0m in \u001b[92m<listcomp>\u001b[0m        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m48 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mhasattr\u001b[0m(\u001b[96mself\u001b[0m.dataset, \u001b[33m\"\u001b[0m\u001b[33m__getitems__\u001b[0m\u001b[33m\"\u001b[0m) \u001b[95mand\u001b[0m \u001b[96mself\u001b[0m.dataset.__getitems__:         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m49 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mdata = \u001b[96mself\u001b[0m.dataset.__getitems__(possibly_batched_index)                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m50 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m51 \u001b[2m│   │   │   │   \u001b[0mdata = [\u001b[96mself\u001b[0m.dataset[idx] \u001b[94mfor\u001b[0m idx \u001b[95min\u001b[0m possibly_batched_index]                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m52 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m53 \u001b[0m\u001b[2m│   │   │   \u001b[0mdata = \u001b[96mself\u001b[0m.dataset[possibly_batched_index]                                     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m54 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m.collate_fn(data)                                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m__getitem__\u001b[0m:\u001b[94m39\u001b[0m                                                                                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m36 \u001b[0m\u001b[2m│   │   \u001b[0mbands = [np.load(os.path.join(record_dir, \u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33mband_\u001b[0m\u001b[33m{\u001b[0mband\u001b[33m}\u001b[0m\u001b[33m.npy\u001b[0m\u001b[33m\"\u001b[0m))[..., \u001b[94m0\u001b[0m] \u001b[94mfor\u001b[0m band     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m37 \u001b[0m\u001b[2m│   │   \u001b[0mbands_array = np.stack(bands)                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m38 \u001b[0m\u001b[2m│   │   \u001b[0mimage = Image.fromarray((bands_array.transpose(\u001b[94m1\u001b[0m, \u001b[94m2\u001b[0m, \u001b[94m0\u001b[0m) * \u001b[94m255\u001b[0m).astype(np.uint8))    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m39 \u001b[2m│   │   \u001b[0msample = \u001b[96mself\u001b[0m.transform(image)                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m40 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m41 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# Load aggregated ground truth mask\u001b[0m                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m42 \u001b[0m\u001b[2m│   │   \u001b[0mtarget_path = os.path.join(record_dir, \u001b[33m'\u001b[0m\u001b[33mhuman_pixel_masks.npy\u001b[0m\u001b[33m'\u001b[0m)                     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/torchvision/transforms/\u001b[0m\u001b[1;33mtransforms.py\u001b[0m:\u001b[94m95\u001b[0m in \u001b[92m__call__\u001b[0m      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m  92 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m  93 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__call__\u001b[0m(\u001b[96mself\u001b[0m, img):                                                              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m  94 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfor\u001b[0m t \u001b[95min\u001b[0m \u001b[96mself\u001b[0m.transforms:                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m  95 \u001b[2m│   │   │   \u001b[0mimg = t(img)                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m  96 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m img                                                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m  97 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m  98 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__repr__\u001b[0m(\u001b[96mself\u001b[0m) -> \u001b[96mstr\u001b[0m:                                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/torchvision/transforms/\u001b[0m\u001b[1;33mtransforms.py\u001b[0m:\u001b[94m486\u001b[0m in \u001b[92m__call__\u001b[0m     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 483 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.lambd = lambd                                                                \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 484 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 485 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__call__\u001b[0m(\u001b[96mself\u001b[0m, img):                                                              \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 486 \u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m.lambd(img)                                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 487 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 488 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__repr__\u001b[0m(\u001b[96mself\u001b[0m) -> \u001b[96mstr\u001b[0m:                                                            \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m 489 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0m\u001b[96mself\u001b[0m.\u001b[91m__class__\u001b[0m.\u001b[91m__name__\u001b[0m\u001b[33m}\u001b[0m\u001b[33m()\u001b[0m\u001b[33m\"\u001b[0m                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m in \u001b[92m<lambda>\u001b[0m:\u001b[94m28\u001b[0m                                                                                   \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m25 \u001b[0m\u001b[2m│   │   │   \u001b[0mtransforms.ColorJitter(brightness=\u001b[94m0.1\u001b[0m, contrast=\u001b[94m0.1\u001b[0m),                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m26 \u001b[0m\u001b[2m│   │   │   \u001b[0mtransforms.RandomAffine(degrees=\u001b[94m0\u001b[0m, scale=(\u001b[94m0.8\u001b[0m, \u001b[94m1.2\u001b[0m), shear=\u001b[94m20\u001b[0m),                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m27 \u001b[0m\u001b[2m│   │   │   \u001b[0mtransforms.Resize((\u001b[94m320\u001b[0m, \u001b[94m320\u001b[0m)),                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m28 \u001b[2m│   │   │   \u001b[0mtransforms.Lambda(\u001b[94mlambda\u001b[0m x: ImageOps.pad(x, (\u001b[94m0\u001b[0m, \u001b[94m0\u001b[0m, \u001b[94m0\u001b[0m, \u001b[96mmax\u001b[0m(\u001b[94m0\u001b[0m, (\u001b[94m32\u001b[0m - x.size[\u001b[94m1\u001b[0m]    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m29 \u001b[0m\u001b[2m│   │   \u001b[0m])                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m30 \u001b[0m\u001b[2m│   \u001b[0m                                                                                        \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m31 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__len__\u001b[0m(\u001b[96mself\u001b[0m):                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/PIL/\u001b[0m\u001b[1;33mImageOps.py\u001b[0m:\u001b[94m291\u001b[0m in \u001b[92mpad\u001b[0m                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m288 \u001b[0m\u001b[2;33m│   \u001b[0m\u001b[33m:return: An image.\u001b[0m                                                                     \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m289 \u001b[0m\u001b[2;33m│   \u001b[0m\u001b[33m\"\"\"\u001b[0m                                                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m290 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m291 \u001b[2m│   \u001b[0mresized = contain(image, size, method)                                                 \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m292 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m resized.size == size:                                                               \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m293 \u001b[0m\u001b[2m│   │   \u001b[0mout = resized                                                                      \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m294 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94melse\u001b[0m:                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/lib/python3.10/site-packages/PIL/\u001b[0m\u001b[1;33mImageOps.py\u001b[0m:\u001b[94m255\u001b[0m in \u001b[92mcontain\u001b[0m                           \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m252 \u001b[0m\u001b[2;33m│   \u001b[0m\u001b[33m\"\"\"\u001b[0m                                                                                    \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m253 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m254 \u001b[0m\u001b[2m│   \u001b[0mim_ratio = image.width / image.height                                                  \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m255 \u001b[2m│   \u001b[0mdest_ratio = size[\u001b[94m0\u001b[0m] / size[\u001b[94m1\u001b[0m]                                                         \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m256 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m257 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m im_ratio != dest_ratio:                                                             \u001b[31m│\u001b[0m\n\u001b[31m│\u001b[0m   \u001b[2m258 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m im_ratio > dest_ratio:                                                          \u001b[31m│\u001b[0m\n\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n\u001b[1;91mZeroDivisionError: \u001b[0mdivision by zero\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">&lt;module&gt;</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">91</span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">88 </span>                                                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">89 # Use PyTorch Lightning's Trainer to train the model without the gpus argument</span>              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">90 </span>trainer = pl.Trainer(max_epochs=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">10</span>)                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>91 trainer.fit(model, DataLoader(dataset_train, batch_size=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">8</span>, shuffle=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>), DataLoader(dat    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">92 </span>                                                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">trainer.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">531</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">fit</span>          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 528 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"</span>                                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 529 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>model = _maybe_unwrap_optimized(model)                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 530 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.strategy._lightning_module = model                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 531 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>call._call_and_handle_interrupt(                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 532 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._fit_impl, model, train_dataloaders, val_dataloaders, datamodule,  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 533 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>)                                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 534 </span>                                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_call_and_handle_interrupt</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">42</span>                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 39 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 40 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> trainer.strategy.launcher <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 41 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer,    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 42 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> trainer_fn(*args, **kwargs)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 43 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 44 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span> _TunerExitException:                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 45 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>_call_teardown_hook(trainer)                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">trainer.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">570</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_fit_impl</span>    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 567 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>model_provided=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>,                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 568 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>model_connected=<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.lightning_module <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>,                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 569 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>)                                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 570 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._run(model, ckpt_path=ckpt_path)                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 571 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 572 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">assert</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.state.stopped                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 573 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.training = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">trainer.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">975</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_run</span>         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 972 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># ----------------------------</span>                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 973 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># RUN THE TRAINER</span>                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 974 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># ----------------------------</span>                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 975 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>results = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._run_stage()                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 976 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 977 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># ----------------------------</span>                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 978 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># POST-Training CLEAN UP</span>                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">trainer.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1018</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_run_stage</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1015 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">with</span> isolate_rng():                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1016 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._run_sanity_check()                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1017 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">with</span> torch.autograd.set_detect_anomaly(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._detect_anomaly):                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1018 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.fit_loop.run()                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1019 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1020 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">raise</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">RuntimeError</span>(<span style=\"color: #808000; text-decoration-color: #808000\">f\"Unexpected state {</span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.state<span style=\"color: #808000; text-decoration-color: #808000\">}\"</span>)                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1021 </span>                                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">fit_loop.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">201</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run</span>           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">198 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">while</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.done:                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">199 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">200 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.on_advance_start()                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>201 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.advance()                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">202 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.on_advance_end()                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">203 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._restarting = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">204 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">StopIteration</span>:                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">fit_loop.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">354</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">advance</span>       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">351 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">assert</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._data_fetcher <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">352 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._data_fetcher.setup(combined_loader)                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">353 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">with</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.trainer.profiler.profile(<span style=\"color: #808000; text-decoration-color: #808000\">\"run_training_epoch\"</span>):                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>354 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.epoch_loop.run(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._data_fetcher)                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">355 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">356 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">on_advance_end</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>) -&gt; <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">357 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>trainer = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.trainer                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">133</span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">130 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.on_run_start(data_fetcher)                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">131 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">while</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.done:                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">132 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>133 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.advance(data_fetcher)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">134 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.on_advance_end()                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">135 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._restarting = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">136 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">StopIteration</span>:                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">advance</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">189</span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">186 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.val_loop.restarting = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">187 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">188 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>batch_idx = data_fetcher.fetched <span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">isinstance</span>(data_fetcher, _DataLoaderIterData   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>189 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>batch = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">next</span>(data_fetcher)                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">190 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.batch_progress.is_last_batch = data_fetcher.done                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">191 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">192 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>trainer = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.trainer                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__next__</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">136</span>                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">133 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">elif</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.done:                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">134 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># this will run only when no pre-fetching was done.</span>                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">135 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>136 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._fetch_next_batch(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataloader_iter)                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">137 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># consume the batch we just fetched</span>                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">138 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>batch = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.batches.pop(<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>)                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">StopIteration</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">as</span> ex:                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_fetch_next_batch</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">150</span>                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">147 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_fetch_next_batch</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>, iterator: Iterator) -&gt; <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">148 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._start_profiler()                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">149 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>150 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>batch = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">next</span>(iterator)                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">151 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">finally</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">152 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._stop_profiler()                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">153 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.fetched += <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__next__</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">284</span>                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">281 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">282 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__next__</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>) -&gt; Any:                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">283 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">assert</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._iterator <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>284 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>out = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">next</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._iterator)                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">285 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">isinstance</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._iterator, _Sequential):                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> out                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">287 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> tree_unflatten(out, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._spec)                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__next__</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">65</span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 62 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>out = [<span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>] * n  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># values per iterator</span>                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 63 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> i <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">range</span>(n):                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 64 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 65 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>out[i] = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">next</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.iterators[i])                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 66 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">StopIteration</span>:                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 67 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._consumed[i] = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 68 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">all</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._consumed):                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/torch/utils/data/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataloader.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">634</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__next__</span>           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 631 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._sampler_iter <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 632 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># TODO(https://github.com/pytorch/pytorch/issues/76750)</span>                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 633 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._reset()  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># type: ignore[call-arg]</span>                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 634 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>data = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._next_data()                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 635 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._num_yielded += <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 636 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._dataset_kind == _DatasetKind.Iterable <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">and</span> \\                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 637 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._IterableDataset_len_called <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">and</span> \\                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/torch/utils/data/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataloader.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">678</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_next_data</span>         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 675 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 676 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_next_data</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>):                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 677 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>index = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._next_index()  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># may raise StopIteration</span>                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 678 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>data = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._dataset_fetcher.fetch(index)  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># may raise StopIteration</span>              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 679 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._pin_memory:                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 680 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>data = _utils.pin_memory.pin_memory(data, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._pin_memory_device)            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 681 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> data                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">fetch.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">51</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">fetch</span>             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">48 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">hasattr</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset, <span style=\"color: #808000; text-decoration-color: #808000\">\"__getitems__\"</span>) <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">and</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset.__getitems__:         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">49 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>data = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset.__getitems__(possibly_batched_index)                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>51 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>data = [<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset[idx] <span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> idx <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> possibly_batched_index]                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">52 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">53 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>data = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset[possibly_batched_index]                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">54 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.collate_fn(data)                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">fetch.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">51</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">&lt;listcomp&gt;</span>        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">48 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">hasattr</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset, <span style=\"color: #808000; text-decoration-color: #808000\">\"__getitems__\"</span>) <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">and</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset.__getitems__:         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">49 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>data = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset.__getitems__(possibly_batched_index)                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>51 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>data = [<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset[idx] <span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> idx <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> possibly_batched_index]                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">52 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">53 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>data = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.dataset[possibly_batched_index]                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">54 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.collate_fn(data)                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__getitem__</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">39</span>                                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">36 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>bands = [np.load(os.path.join(record_dir, <span style=\"color: #808000; text-decoration-color: #808000\">f\"band_{</span>band<span style=\"color: #808000; text-decoration-color: #808000\">}.npy\"</span>))[..., <span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>] <span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> band     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">37 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>bands_array = np.stack(bands)                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">38 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>image = Image.fromarray((bands_array.transpose(<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">2</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>) * <span style=\"color: #0000ff; text-decoration-color: #0000ff\">255</span>).astype(np.uint8))    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>39 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>sample = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.transform(image)                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">40 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">41 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Load aggregated ground truth mask</span>                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">42 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>target_path = os.path.join(record_dir, <span style=\"color: #808000; text-decoration-color: #808000\">'human_pixel_masks.npy'</span>)                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/torchvision/transforms/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">transforms.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">95</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__call__</span>      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  92 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  93 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__call__</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>, img):                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  94 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> t <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.transforms:                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>  95 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>img = t(img)                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  96 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> img                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  97 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  98 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__repr__</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>) -&gt; <span style=\"color: #00ffff; text-decoration-color: #00ffff\">str</span>:                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/torchvision/transforms/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">transforms.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">486</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__call__</span>     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 483 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.lambd = lambd                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 484 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 485 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__call__</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>, img):                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 486 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.lambd(img)                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 487 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 488 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__repr__</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>) -&gt; <span style=\"color: #00ffff; text-decoration-color: #00ffff\">str</span>:                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 489 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.<span style=\"color: #ff0000; text-decoration-color: #ff0000\">__class__</span>.<span style=\"color: #ff0000; text-decoration-color: #ff0000\">__name__</span><span style=\"color: #808000; text-decoration-color: #808000\">}()\"</span>                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">&lt;lambda&gt;</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">28</span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">25 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>transforms.ColorJitter(brightness=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0.1</span>, contrast=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0.1</span>),                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">26 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>transforms.RandomAffine(degrees=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>, scale=(<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0.8</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1.2</span>), shear=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">20</span>),                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">27 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>transforms.Resize((<span style=\"color: #0000ff; text-decoration-color: #0000ff\">320</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">320</span>)),                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>28 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>transforms.Lambda(<span style=\"color: #0000ff; text-decoration-color: #0000ff\">lambda</span> x: ImageOps.pad(x, (<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">max</span>(<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>, (<span style=\"color: #0000ff; text-decoration-color: #0000ff\">32</span> - x.size[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>]    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">29 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>])                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">30 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">31 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__len__</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>):                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/PIL/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">ImageOps.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">291</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">pad</span>                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">288 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">:return: An image.</span>                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">289 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"</span>                                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>291 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>resized = contain(image, size, method)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">292 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> resized.size == size:                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">293 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>out = resized                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">294 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/opt/conda/lib/python3.10/site-packages/PIL/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">ImageOps.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">255</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">contain</span>                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">252 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"</span>                                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">253 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">254 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>im_ratio = image.width / image.height                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>255 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>dest_ratio = size[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>] / size[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>]                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">256 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">257 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> im_ratio != dest_ratio:                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">258 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> im_ratio &gt; dest_ratio:                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ZeroDivisionError: </span>division by zero\n</pre>\n"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}