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{ |
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"imports": [ |
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"$import glob", |
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"$import os", |
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"$import ignite" |
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], |
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"bundle_root": ".", |
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"ckpt_dir": "$@bundle_root + '/models'", |
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"output_dir": "$@bundle_root + '/eval'", |
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"dataset_dir": "/workspace/data/RawData/", |
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"images": "$list(sorted(glob.glob(@dataset_dir + '/imagesTr/*.nii.gz')))", |
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"labels": "$list(sorted(glob.glob(@dataset_dir + '/labelsTr/*.nii.gz')))", |
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"val_interval": 5, |
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"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", |
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"network_def": { |
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"_target_": "SwinUNETR", |
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"spatial_dims": 3, |
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"img_size": 96, |
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"in_channels": 1, |
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"out_channels": 14, |
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"feature_size": 48, |
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"use_checkpoint": true |
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}, |
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"network": "$@network_def.to(@device)", |
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"loss": { |
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"_target_": "DiceCELoss", |
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"to_onehot_y": true, |
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"softmax": true, |
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"squared_pred": true, |
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"batch": true |
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}, |
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"optimizer": { |
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"_target_": "torch.optim.Adam", |
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"params": "$@network.parameters()", |
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"lr": 0.0002 |
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}, |
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"train": { |
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"deterministic_transforms": [ |
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{ |
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"_target_": "LoadImaged", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"reader": "ITKReader" |
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}, |
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{ |
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"_target_": "EnsureChannelFirstd", |
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"keys": [ |
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"image", |
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"label" |
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] |
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}, |
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{ |
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"_target_": "Orientationd", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"axcodes": "RAS" |
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}, |
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{ |
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"_target_": "Spacingd", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"pixdim": [ |
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1.5, |
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1.5, |
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2.0 |
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], |
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"mode": [ |
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"bilinear", |
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"nearest" |
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] |
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}, |
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{ |
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"_target_": "ScaleIntensityRanged", |
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"keys": "image", |
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"a_min": -175, |
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"a_max": 250, |
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"b_min": 0.0, |
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"b_max": 1.0, |
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"clip": true |
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}, |
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{ |
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"_target_": "EnsureTyped", |
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"keys": [ |
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"image", |
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"label" |
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] |
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} |
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], |
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"random_transforms": [ |
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{ |
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"_target_": "RandCropByPosNegLabeld", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"label_key": "label", |
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"spatial_size": [ |
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96, |
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96, |
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96 |
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], |
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"pos": 1, |
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"neg": 1, |
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"num_samples": 2, |
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"image_key": "image", |
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"image_threshold": 0 |
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}, |
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{ |
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"_target_": "RandFlipd", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"spatial_axis": [ |
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0 |
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], |
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"prob": 0.1 |
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}, |
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{ |
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"_target_": "RandFlipd", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"spatial_axis": [ |
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1 |
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], |
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"prob": 0.1 |
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}, |
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{ |
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"_target_": "RandFlipd", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"spatial_axis": [ |
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2 |
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], |
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"prob": 0.1 |
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}, |
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{ |
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"_target_": "RandRotate90d", |
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"keys": [ |
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"image", |
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"label" |
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], |
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"max_k": 3, |
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"prob": 0.1 |
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}, |
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{ |
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"_target_": "RandShiftIntensityd", |
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"keys": "image", |
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"offsets": 0.1, |
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"prob": 0.5 |
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} |
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], |
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"preprocessing": { |
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"_target_": "Compose", |
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"transforms": "$@train#deterministic_transforms + @train#random_transforms" |
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}, |
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"dataset": { |
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"_target_": "CacheDataset", |
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"data": "$[{'image': i, 'label': l} for i, l in zip(@images[:-9], @labels[:-9])]", |
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"transform": "@train#preprocessing", |
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"cache_rate": 1.0, |
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"num_workers": 4 |
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}, |
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"dataloader": { |
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"_target_": "DataLoader", |
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"dataset": "@train#dataset", |
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"batch_size": 2, |
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"shuffle": true, |
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"num_workers": 4 |
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}, |
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"inferer": { |
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"_target_": "SimpleInferer" |
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}, |
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"postprocessing": { |
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"_target_": "Compose", |
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"transforms": [ |
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{ |
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"_target_": "Activationsd", |
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"keys": "pred", |
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"softmax": true |
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}, |
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{ |
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"_target_": "AsDiscreted", |
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"keys": [ |
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"pred", |
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"label" |
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], |
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"argmax": [ |
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true, |
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false |
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], |
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"to_onehot": 14 |
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} |
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] |
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}, |
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"handlers": [ |
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{ |
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"_target_": "ValidationHandler", |
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"validator": "@validate#evaluator", |
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"epoch_level": true, |
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"interval": "@val_interval" |
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}, |
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{ |
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"_target_": "StatsHandler", |
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"tag_name": "train_loss", |
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"output_transform": "$monai.handlers.from_engine(['loss'], first=True)" |
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}, |
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{ |
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"_target_": "TensorBoardStatsHandler", |
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"log_dir": "@output_dir", |
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"tag_name": "train_loss", |
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"output_transform": "$monai.handlers.from_engine(['loss'], first=True)" |
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} |
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], |
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"key_metric": { |
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"train_accuracy": { |
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"_target_": "ignite.metrics.Accuracy", |
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"output_transform": "$monai.handlers.from_engine(['pred', 'label'])" |
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} |
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}, |
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"trainer": { |
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"_target_": "SupervisedTrainer", |
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"max_epochs": 500, |
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"device": "@device", |
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"train_data_loader": "@train#dataloader", |
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"network": "@network", |
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"loss_function": "@loss", |
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"optimizer": "@optimizer", |
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"inferer": "@train#inferer", |
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"postprocessing": "@train#postprocessing", |
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"key_train_metric": "@train#key_metric", |
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"train_handlers": "@train#handlers", |
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"amp": true |
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} |
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}, |
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"validate": { |
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"preprocessing": { |
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"_target_": "Compose", |
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"transforms": "%train#deterministic_transforms" |
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}, |
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"dataset": { |
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"_target_": "CacheDataset", |
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"data": "$[{'image': i, 'label': l} for i, l in zip(@images[-9:], @labels[-9:])]", |
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"transform": "@validate#preprocessing", |
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"cache_rate": 1.0 |
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}, |
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"dataloader": { |
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"_target_": "DataLoader", |
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"dataset": "@validate#dataset", |
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"batch_size": 1, |
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"shuffle": false, |
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"num_workers": 4 |
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}, |
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"inferer": { |
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"_target_": "SlidingWindowInferer", |
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"roi_size": [ |
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96, |
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96, |
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96 |
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], |
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"sw_batch_size": 2, |
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"overlap": 0.25 |
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}, |
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"postprocessing": "%train#postprocessing", |
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"handlers": [ |
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{ |
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"_target_": "StatsHandler", |
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"iteration_log": false |
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}, |
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{ |
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"_target_": "TensorBoardStatsHandler", |
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"log_dir": "@output_dir", |
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"iteration_log": false |
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}, |
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{ |
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"_target_": "CheckpointSaver", |
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"save_dir": "@ckpt_dir", |
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"save_dict": { |
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"model": "@network" |
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}, |
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"save_key_metric": true, |
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"key_metric_filename": "model.pt" |
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} |
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], |
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"key_metric": { |
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"val_mean_dice": { |
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"_target_": "MeanDice", |
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"include_background": false, |
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"output_transform": "$monai.handlers.from_engine(['pred', 'label'])" |
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} |
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}, |
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"additional_metrics": { |
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"val_accuracy": { |
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"_target_": "ignite.metrics.Accuracy", |
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"output_transform": "$monai.handlers.from_engine(['pred', 'label'])" |
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} |
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}, |
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"evaluator": { |
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"_target_": "SupervisedEvaluator", |
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"device": "@device", |
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"val_data_loader": "@validate#dataloader", |
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"network": "@network", |
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"inferer": "@validate#inferer", |
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"postprocessing": "@validate#postprocessing", |
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"key_val_metric": "@validate#key_metric", |
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"additional_metrics": "@validate#additional_metrics", |
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"val_handlers": "@validate#handlers", |
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"amp": true |
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} |
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}, |
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"initialize": [ |
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"$monai.utils.set_determinism(seed=123)" |
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], |
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"run": [ |
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"$@train#trainer.run()" |
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] |
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} |
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