| { | |
| "imports": [ | |
| "$import glob", | |
| "$import os" | |
| ], | |
| "bundle_root": "/workspace/brats_mri_segmentation", | |
| "ckpt_dir": "$@bundle_root + '/models'", | |
| "output_dir": "$@bundle_root + '/eval'", | |
| "data_list_file_path": "$@bundle_root + '/configs/datalist.json'", | |
| "data_file_base_dir": "/workspace/data/medical/brats2018challenge", | |
| "train_datalist": "$monai.data.load_decathlon_datalist(@data_list_file_path, data_list_key='training', base_dir=@data_file_base_dir)", | |
| "val_datalist": "$monai.data.load_decathlon_datalist(@data_list_file_path, data_list_key='validation', base_dir=@data_file_base_dir)", | |
| "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", | |
| "epochs": 300, | |
| "num_interval_per_valid": 1, | |
| "learning_rate": 0.0001, | |
| "amp": true, | |
| "network_def": { | |
| "_target_": "SegResNet", | |
| "blocks_down": [ | |
| 1, | |
| 2, | |
| 2, | |
| 4 | |
| ], | |
| "blocks_up": [ | |
| 1, | |
| 1, | |
| 1 | |
| ], | |
| "init_filters": 16, | |
| "in_channels": 4, | |
| "out_channels": 3, | |
| "dropout_prob": 0.2 | |
| }, | |
| "network": "$@network_def.to(@device)", | |
| "loss": { | |
| "_target_": "DiceLoss", | |
| "smooth_nr": 0, | |
| "smooth_dr": 1e-05, | |
| "squared_pred": true, | |
| "to_onehot_y": false, | |
| "sigmoid": true | |
| }, | |
| "optimizer": { | |
| "_target_": "torch.optim.Adam", | |
| "params": "$@network.parameters()", | |
| "lr": "@learning_rate", | |
| "weight_decay": 1e-05 | |
| }, | |
| "lr_scheduler": { | |
| "_target_": "torch.optim.lr_scheduler.CosineAnnealingLR", | |
| "optimizer": "@optimizer", | |
| "T_max": "@epochs" | |
| }, | |
| "train": { | |
| "preprocessing_transforms": [ | |
| { | |
| "_target_": "LoadImaged", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| }, | |
| { | |
| "_target_": "ConvertToMultiChannelBasedOnBratsClassesd", | |
| "keys": "label" | |
| }, | |
| { | |
| "_target_": "NormalizeIntensityd", | |
| "keys": "image", | |
| "nonzero": true, | |
| "channel_wise": true | |
| } | |
| ], | |
| "random_transforms": [ | |
| { | |
| "_target_": "RandSpatialCropd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "roi_size": [ | |
| 224, | |
| 224, | |
| 144 | |
| ], | |
| "random_size": false | |
| }, | |
| { | |
| "_target_": "RandFlipd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "prob": 0.5, | |
| "spatial_axis": 0 | |
| }, | |
| { | |
| "_target_": "RandFlipd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "prob": 0.5, | |
| "spatial_axis": 1 | |
| }, | |
| { | |
| "_target_": "RandFlipd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "prob": 0.5, | |
| "spatial_axis": 2 | |
| }, | |
| { | |
| "_target_": "RandScaleIntensityd", | |
| "keys": "image", | |
| "factors": 0.1, | |
| "prob": 1.0 | |
| }, | |
| { | |
| "_target_": "RandShiftIntensityd", | |
| "keys": "image", | |
| "offsets": 0.1, | |
| "prob": 1.0 | |
| } | |
| ], | |
| "final_transforms": [ | |
| { | |
| "_target_": "ToTensord", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| } | |
| ], | |
| "preprocessing": { | |
| "_target_": "Compose", | |
| "transforms": "$@train#preprocessing_transforms + @train#random_transforms + @train#final_transforms" | |
| }, | |
| "dataset": { | |
| "_target_": "Dataset", | |
| "data": "@train_datalist", | |
| "transform": "@train#preprocessing" | |
| }, | |
| "dataloader": { | |
| "_target_": "DataLoader", | |
| "dataset": "@train#dataset", | |
| "batch_size": 1, | |
| "shuffle": true, | |
| "num_workers": 4 | |
| }, | |
| "inferer": { | |
| "_target_": "SimpleInferer" | |
| }, | |
| "postprocessing": { | |
| "_target_": "Compose", | |
| "transforms": [ | |
| { | |
| "_target_": "Activationsd", | |
| "keys": "pred", | |
| "sigmoid": true | |
| }, | |
| { | |
| "_target_": "AsDiscreted", | |
| "keys": "pred", | |
| "threshold": 0.5 | |
| } | |
| ] | |
| }, | |
| "handlers": [ | |
| { | |
| "_target_": "LrScheduleHandler", | |
| "lr_scheduler": "@lr_scheduler", | |
| "print_lr": true | |
| }, | |
| { | |
| "_target_": "ValidationHandler", | |
| "validator": "@validate#evaluator", | |
| "epoch_level": true, | |
| "interval": "@num_interval_per_valid" | |
| }, | |
| { | |
| "_target_": "StatsHandler", | |
| "tag_name": "train_loss", | |
| "output_transform": "$monai.handlers.from_engine(['loss'], first=True)" | |
| }, | |
| { | |
| "_target_": "TensorBoardStatsHandler", | |
| "log_dir": "@output_dir", | |
| "tag_name": "train_loss", | |
| "output_transform": "$monai.handlers.from_engine(['loss'], first=True)" | |
| } | |
| ], | |
| "key_metric": { | |
| "train_mean_dice": { | |
| "_target_": "MeanDice", | |
| "include_background": true, | |
| "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" | |
| } | |
| }, | |
| "trainer": { | |
| "_target_": "SupervisedTrainer", | |
| "max_epochs": "@epochs", | |
| "device": "@device", | |
| "train_data_loader": "@train#dataloader", | |
| "network": "@network", | |
| "loss_function": "@loss", | |
| "optimizer": "@optimizer", | |
| "inferer": "@train#inferer", | |
| "postprocessing": "@train#postprocessing", | |
| "key_train_metric": "@train#key_metric", | |
| "train_handlers": "@train#handlers", | |
| "amp": "@amp" | |
| } | |
| }, | |
| "validate": { | |
| "preprocessing": { | |
| "_target_": "Compose", | |
| "transforms": "$@train#preprocessing_transforms + @train#final_transforms" | |
| }, | |
| "dataset": { | |
| "_target_": "Dataset", | |
| "data": "@val_datalist", | |
| "transform": "@validate#preprocessing" | |
| }, | |
| "dataloader": { | |
| "_target_": "DataLoader", | |
| "dataset": "@validate#dataset", | |
| "batch_size": 1, | |
| "shuffle": false, | |
| "num_workers": 4 | |
| }, | |
| "inferer": { | |
| "_target_": "SlidingWindowInferer", | |
| "roi_size": [ | |
| 240, | |
| 240, | |
| 160 | |
| ], | |
| "sw_batch_size": 1, | |
| "overlap": 0.5 | |
| }, | |
| "postprocessing": { | |
| "_target_": "Compose", | |
| "transforms": [ | |
| { | |
| "_target_": "Activationsd", | |
| "keys": "pred", | |
| "sigmoid": true | |
| }, | |
| { | |
| "_target_": "AsDiscreted", | |
| "keys": "pred", | |
| "threshold": 0.5 | |
| }, | |
| { | |
| "_target_": "SplitChanneld", | |
| "keys": [ | |
| "pred", | |
| "label" | |
| ], | |
| "output_postfixes": [ | |
| "tc", | |
| "wt", | |
| "et" | |
| ] | |
| } | |
| ] | |
| }, | |
| "handlers": [ | |
| { | |
| "_target_": "StatsHandler", | |
| "iteration_log": false | |
| }, | |
| { | |
| "_target_": "TensorBoardStatsHandler", | |
| "log_dir": "@output_dir", | |
| "iteration_log": false | |
| }, | |
| { | |
| "_target_": "CheckpointSaver", | |
| "save_dir": "@ckpt_dir", | |
| "save_dict": { | |
| "model": "@network" | |
| }, | |
| "save_key_metric": true, | |
| "key_metric_filename": "model.pt" | |
| } | |
| ], | |
| "key_metric": { | |
| "val_mean_dice": { | |
| "_target_": "MeanDice", | |
| "include_background": true, | |
| "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" | |
| } | |
| }, | |
| "additional_metrics": { | |
| "val_mean_dice_tc": { | |
| "_target_": "MeanDice", | |
| "include_background": true, | |
| "output_transform": "$monai.handlers.from_engine(['pred_tc', 'label_tc'])" | |
| }, | |
| "val_mean_dice_wt": { | |
| "_target_": "MeanDice", | |
| "include_background": true, | |
| "output_transform": "$monai.handlers.from_engine(['pred_wt', 'label_wt'])" | |
| }, | |
| "val_mean_dice_et": { | |
| "_target_": "MeanDice", | |
| "include_background": true, | |
| "output_transform": "$monai.handlers.from_engine(['pred_et', 'label_et'])" | |
| } | |
| }, | |
| "evaluator": { | |
| "_target_": "SupervisedEvaluator", | |
| "device": "@device", | |
| "val_data_loader": "@validate#dataloader", | |
| "network": "@network", | |
| "inferer": "@validate#inferer", | |
| "postprocessing": "@validate#postprocessing", | |
| "key_val_metric": "@validate#key_metric", | |
| "additional_metrics": "@validate#additional_metrics", | |
| "val_handlers": "@validate#handlers", | |
| "amp": "@amp" | |
| } | |
| }, | |
| "training": [ | |
| "$monai.utils.set_determinism(seed=123)", | |
| "$setattr(torch.backends.cudnn, 'benchmark', True)", | |
| "$@train#trainer.run()" | |
| ] | |
| } | |