{
    "imports": [
        "$import glob",
        "$import os"
    ],
    "bundle_root": ".",
    "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,
    "val_interval": 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
            }
        ],
        "preprocessing": {
            "_target_": "Compose",
            "transforms": "$@train#preprocessing_transforms + @train#random_transforms"
        },
        "dataset": {
            "_target_": "Dataset",
            "data": "@train_datalist",
            "transform": "@train#preprocessing"
        },
        "dataloader": {
            "_target_": "DataLoader",
            "dataset": "@train#dataset",
            "batch_size": 1,
            "shuffle": true,
            "num_workers": 4
        },
        "inferer": {
            "_target_": "SimpleInferer"
        },
        "postprocessing": {
            "_target_": "Compose",
            "transforms": [
                {
                    "_target_": "Activationsd",
                    "keys": "pred",
                    "sigmoid": true
                },
                {
                    "_target_": "AsDiscreted",
                    "keys": "pred",
                    "threshold": 0.5
                }
            ]
        },
        "handlers": [
            {
                "_target_": "LrScheduleHandler",
                "lr_scheduler": "@lr_scheduler",
                "print_lr": true
            },
            {
                "_target_": "ValidationHandler",
                "validator": "@validate#evaluator",
                "epoch_level": true,
                "interval": "@val_interval"
            },
            {
                "_target_": "StatsHandler",
                "tag_name": "train_loss",
                "output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
            },
            {
                "_target_": "TensorBoardStatsHandler",
                "log_dir": "@output_dir",
                "tag_name": "train_loss",
                "output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
            }
        ],
        "key_metric": {
            "train_mean_dice": {
                "_target_": "MeanDice",
                "include_background": true,
                "output_transform": "$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"
        },
        "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_": "SplitDimd",
                    "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()"
    ]
}