{
    "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()"
    ]
}