{ "imports": [ "$import torch", "$import json", "$import ignite" ], "bundle_root": "/workspace/bundle/endoscopic_inbody_classification", "ckpt_dir": "$@bundle_root + '/models'", "output_dir": "$@bundle_root + '/eval'", "dataset_dir": "/workspace/data/endoscopic_inbody_classification", "train_json": "$@dataset_dir+'/train.json'", "val_json": "$@dataset_dir+'/val.json'", "train_fp": "$open(@train_json,'r', encoding='utf8')", "train_dict": "$json.load(@train_fp)", "train_close": "$@train_fp.close()", "val_fp": "$open(@val_json,'r', encoding='utf8')", "val_dict": "$json.load(@val_fp)", "val_interval": 1, "val_close": "$@val_fp.close()", "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", "network_def": { "_target_": "SEResNet50", "spatial_dims": 2, "in_channels": 3, "num_classes": 2 }, "network": "$@network_def.to(@device)", "loss": { "_target_": "torch.nn.CrossEntropyLoss", "reduction": "sum" }, "optimizer": { "_target_": "torch.optim.Adam", "params": "$@network.parameters()", "lr": 0.001 }, "train": { "deterministic_transforms": [ { "_target_": "LoadImaged", "keys": "image" }, { "_target_": "ToTensord", "keys": "label" }, { "_target_": "AsChannelFirstd", "keys": "image" }, { "_target_": "Resized", "keys": "image", "spatial_size": [ 256, 256 ], "mode": "bilinear" }, { "_target_": "CastToTyped", "dtype": "$torch.float32", "keys": "image" }, { "_target_": "NormalizeIntensityd", "nonzero": true, "channel_wise": true, "keys": "image" }, { "_target_": "EnsureTyped", "keys": "image" } ], "random_transforms": [ { "_target_": "RandRotated", "range_x": 0.3, "prob": 0.2, "mode": "bilinear", "keys": "image" }, { "_target_": "RandScaleIntensityd", "factors": 0.3, "prob": 0.5, "keys": "image" }, { "_target_": "RandShiftIntensityd", "offsets": 0.1, "prob": 0.5, "keys": "image" }, { "_target_": "RandGaussianNoised", "std": 0.01, "prob": 0.15, "keys": "image" }, { "_target_": "RandFlipd", "spatial_axis": 0, "prob": 0.5, "keys": "image" }, { "_target_": "RandFlipd", "spatial_axis": 1, "prob": 0.5, "keys": "image" } ], "preprocessing": { "_target_": "Compose", "transforms": "$@train#deterministic_transforms + @train#random_transforms" }, "dataset": { "_target_": "Dataset", "data": "@train_dict", "transform": "@train#preprocessing" }, "dataloader": { "_target_": "DataLoader", "dataset": "@train#dataset", "batch_size": 64, "shuffle": true, "num_workers": 4 }, "inferer": { "_target_": "SimpleInferer" }, "handlers": [ { "_target_": "ValidationHandler", "validator": "@validate#evaluator", "epoch_level": true, "interval": "@val_interval" }, { "_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_accu": { "_target_": "ignite.metrics.Accuracy", "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" } }, "postprocessing": { "_target_": "Compose", "transforms": [ { "_target_": "AsDiscreted", "argmax": [ true, false ], "to_onehot": [ 2, 2 ], "keys": [ "pred", "label" ] } ] }, "trainer": { "_target_": "SupervisedTrainer", "max_epochs": 25, "device": "@device", "train_data_loader": "@train#dataloader", "network": "@network", "loss_function": "@loss", "optimizer": "@optimizer", "inferer": "@train#inferer", "postprocessing": "@train#postprocessing", "key_train_metric": "@train#key_metric", "train_handlers": "@train#handlers" } }, "validate": { "preprocessing": { "_target_": "Compose", "transforms": "%train#deterministic_transforms" }, "dataset": { "_target_": "Dataset", "data": "@val_dict", "transform": "@validate#preprocessing" }, "dataloader": { "_target_": "DataLoader", "dataset": "@validate#dataset", "batch_size": 64, "shuffle": false, "num_workers": 4 }, "inferer": { "_target_": "SimpleInferer" }, "postprocessing": { "_target_": "Compose", "transforms": "%train#postprocessing" }, "handlers": [ { "_target_": "StatsHandler", "iteration_log": false }, { "_target_": "TensorBoardStatsHandler", "log_dir": "@output_dir", "iteration_log": false }, { "_target_": "CheckpointSaver", "save_dir": "@ckpt_dir", "save_dict": { "model": "@network" }, "save_key_metric": true, "key_metric_filename": "model.pt" } ], "key_metric": { "val_accu": { "_target_": "ignite.metrics.Accuracy", "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" } }, "evaluator": { "_target_": "SupervisedEvaluator", "device": "@device", "val_data_loader": "@validate#dataloader", "network": "@network", "inferer": "@validate#inferer", "postprocessing": "@validate#postprocessing", "key_val_metric": "@validate#key_metric", "val_handlers": "@validate#handlers" } }, "training": [ "$monai.utils.set_determinism(seed=0)", "$setattr(torch.backends.cudnn, 'benchmark', True)", "$@train#trainer.run()" ] }