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| { | |
| "imports": [ | |
| "$import glob", | |
| "$import ignite", | |
| "$import json", | |
| "$import pathlib", | |
| "$import os" | |
| ], | |
| "bundle_root": "/workspace/data/pathology_nuclei_classification", | |
| "ckpt_dir": "$@bundle_root + '/models'", | |
| "output_dir": "$@bundle_root + '/eval'", | |
| "dataset_dir": "/workspace/data/CoNSePNuclei", | |
| "dataset_json": "$@dataset_dir + '/dataset.json'", | |
| "train_datalist": "$json.loads(pathlib.Path(@dataset_json).read_text())['training']", | |
| "val_datalist": "$json.loads(pathlib.Path(@dataset_json).read_text())['validation']", | |
| "val_interval": 1, | |
| "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", | |
| "network_def": { | |
| "_target_": "DenseNet121", | |
| "spatial_dims": 2, | |
| "in_channels": 4, | |
| "out_channels": 4 | |
| }, | |
| "network": "$@network_def.to(@device)", | |
| "loss": { | |
| "_target_": "torch.nn.CrossEntropyLoss" | |
| }, | |
| "optimizer": { | |
| "_target_": "torch.optim.Adam", | |
| "params": "$@network.parameters()", | |
| "lr": 0.0001 | |
| }, | |
| "max_epochs": 50, | |
| "train": { | |
| "preprocessing": { | |
| "_target_": "Compose", | |
| "transforms": [ | |
| { | |
| "_target_": "LoadImaged", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "dtype": "uint8" | |
| }, | |
| { | |
| "_target_": "EnsureChannelFirstd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| }, | |
| { | |
| "_target_": "SplitLabeld", | |
| "keys": "label", | |
| "mask_value": "", | |
| "others_value": 255, | |
| "to_binary_mask": false | |
| }, | |
| { | |
| "_target_": "RandTorchVisiond", | |
| "keys": "image", | |
| "name": "ColorJitter", | |
| "brightness": 0.25, | |
| "contrast": 0.75, | |
| "saturation": 0.25, | |
| "hue": 0.04 | |
| }, | |
| { | |
| "_target_": "RandFlipd", | |
| "keys": [ | |
| "image", | |
| "label", | |
| "others" | |
| ], | |
| "prob": 0.5 | |
| }, | |
| { | |
| "_target_": "RandRotate90d", | |
| "keys": [ | |
| "image", | |
| "label", | |
| "others" | |
| ], | |
| "prob": 0.5 | |
| }, | |
| { | |
| "_target_": "ScaleIntensityRanged", | |
| "keys": "image", | |
| "a_min": 0.0, | |
| "a_max": 255.0, | |
| "b_min": -1.0, | |
| "b_max": 1.0 | |
| }, | |
| { | |
| "_target_": "AddLabelAsGuidanced", | |
| "keys": "image", | |
| "source": "label" | |
| }, | |
| { | |
| "_target_": "SetLabelClassd", | |
| "keys": "label", | |
| "offset": -1 | |
| }, | |
| { | |
| "_target_": "SelectItemsd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| } | |
| ] | |
| }, | |
| "dataset": { | |
| "_target_": "CacheDataset", | |
| "data": "@train_datalist", | |
| "transform": "@train#preprocessing", | |
| "cache_rate": 1.0, | |
| "num_workers": 4 | |
| }, | |
| "dataloader": { | |
| "_target_": "DataLoader", | |
| "dataset": "@train#dataset", | |
| "batch_size": 64, | |
| "shuffle": true, | |
| "num_workers": 4 | |
| }, | |
| "inferer": { | |
| "_target_": "SimpleInferer" | |
| }, | |
| "postprocessing": { | |
| "_target_": "Compose", | |
| "transforms": [ | |
| { | |
| "_target_": "Activationsd", | |
| "keys": "pred", | |
| "softmax": true | |
| }, | |
| { | |
| "_target_": "AsDiscreted", | |
| "keys": [ | |
| "pred", | |
| "label" | |
| ], | |
| "argmax": [ | |
| true, | |
| false | |
| ], | |
| "to_onehot": 4 | |
| }, | |
| { | |
| "_target_": "ToTensord", | |
| "keys": [ | |
| "pred", | |
| "label" | |
| ], | |
| "device": "@device" | |
| } | |
| ] | |
| }, | |
| "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": "$monai.handlers.from_engine(['loss'], first=True)" | |
| }, | |
| { | |
| "_target_": "scripts.TensorBoardImageHandler", | |
| "class_names": { | |
| "0": "Other", | |
| "1": "Inflammatory", | |
| "2": "Epithelial", | |
| "3": "Spindle-Shaped" | |
| }, | |
| "log_dir": "@output_dir", | |
| "batch_limit": 4, | |
| "tag_name": "train" | |
| } | |
| ], | |
| "key_metric": { | |
| "train_f1": { | |
| "_target_": "ConfusionMatrix", | |
| "metric_name": "f1 score", | |
| "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" | |
| } | |
| }, | |
| "trainer": { | |
| "_target_": "SupervisedTrainer", | |
| "max_epochs": "@max_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": true | |
| } | |
| }, | |
| "validate": { | |
| "preprocessing": { | |
| "_target_": "Compose", | |
| "transforms": [ | |
| { | |
| "_target_": "LoadImaged", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ], | |
| "dtype": "uint8" | |
| }, | |
| { | |
| "_target_": "EnsureChannelFirstd", | |
| "keys": [ | |
| "image", | |
| "label" | |
| ] | |
| }, | |
| { | |
| "_target_": "SplitLabeld", | |
| "keys": "label", | |
| "mask_value": "", | |
| "others_value": 255, | |
| "to_binary_mask": false | |
| }, | |
| { | |
| "_target_": "ScaleIntensityRanged", | |
| "keys": "image", | |
| "a_min": 0.0, | |
| "a_max": 255.0, | |
| "b_min": -1.0, | |
| "b_max": 1.0 | |
| }, | |
| { | |
| "_target_": "AddLabelAsGuidanced", | |
| "keys": "image", | |
| "source": "label" | |
| }, | |
| { | |
| "_target_": "SetLabelClassd", | |
| "keys": "label", | |
| "offset": -1 | |
| }, | |
| { | |
| "_target_": "SelectItemsd", | |
| "keys": [ | |
| "image", | |
| "label", | |
| "image_meta_dict" | |
| ] | |
| } | |
| ] | |
| }, | |
| "dataset": { | |
| "_target_": "CacheDataset", | |
| "data": "@val_datalist", | |
| "transform": "@validate#preprocessing", | |
| "cache_rate": 1.0 | |
| }, | |
| "dataloader": { | |
| "_target_": "DataLoader", | |
| "dataset": "@validate#dataset", | |
| "batch_size": 64, | |
| "shuffle": false, | |
| "num_workers": 4 | |
| }, | |
| "inferer": { | |
| "_target_": "SimpleInferer" | |
| }, | |
| "postprocessing": "%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" | |
| }, | |
| { | |
| "_target_": "scripts.TensorBoardImageHandler", | |
| "class_names": { | |
| "0": "Other", | |
| "1": "Inflammatory", | |
| "2": "Epithelial", | |
| "3": "Spindle-Shaped" | |
| }, | |
| "log_dir": "@output_dir", | |
| "batch_limit": 8, | |
| "tag_name": "val" | |
| } | |
| ], | |
| "key_metric": { | |
| "val_f1": { | |
| "_target_": "ConfusionMatrix", | |
| "metric_name": "f1 score", | |
| "output_transform": "$monai.handlers.from_engine(['pred', 'label'])" | |
| } | |
| }, | |
| "additional_metrics": { | |
| "val_accuracy": { | |
| "_target_": "ignite.metrics.Accuracy", | |
| "output_transform": "$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", | |
| "additional_metrics": "@validate#additional_metrics", | |
| "val_handlers": "@validate#handlers", | |
| "amp": true | |
| } | |
| }, | |
| "training": [ | |
| "$import sys", | |
| "$sys.path.append(@bundle_root)", | |
| "$monai.utils.set_determinism(seed=123)", | |
| "$setattr(torch.backends.cudnn, 'benchmark', True)", | |
| "$@train#trainer.run()" | |
| ] | |
| } | |