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TypeError: list indices must be integers or slices, not str

See original GitHub issue

Issue description

Terminal output (from Wandb): output.log

log: log.log

version_info.log

Config file

{
    "command": "train",
    "gpu_ids": [4],
    "path_output": "seg_lesion_output",
    "model_name": "seg_lesion_model",
    "debugging": true,
    "object_detection_params": {
        "object_detection_path": null,
        "safety_factor": [1.0, 1.0, 1.0]
    },
    "wandb": {
        "wandb_api_key": "9095e2bc9e4ab445d478c9c8a81759ae908be8c6",
        "project_name": "basel-mp2rage-lesion",
        "group_name": "my_group",
        "run_name": "run-1",
        "log_grads_every": 100
    },
    "loader_parameters": {
        "path_data": ["/home/GRAMES.POLYMTL.CA/p101317/data_nvme_p101317/data_seg_mp2rage_20221212_175444/data_processed_lesionseg"],
        "subject_selection": {
            "n": [],
            "metadata": [],
            "value": []
        },
        "target_suffix": [["_lesion-manual", "_lesion-manual2"]],
        "extensions": [],
        "roi_params": {
            "suffix": null,
            "slice_filter_roi": null
        },
        "contrast_params": {
            "training_validation": ["UNIT1"],
            "testing": ["UNIT1"],
            "balance": {}
        },
        "slice_filter_params": {
            "filter_empty_mask": false,
            "filter_empty_input": false
        },
        "slice_axis": "axial",
        "multichannel": false,
        "soft_gt": false
    },
    "split_dataset": {
        "fname_split": null,
        "random_seed": 42,
        "center_test": [],
        "method": "per_patient",
        "balance": null,
        "train_fraction": 0.75,
        "test_fraction": 0.2
    },
    "training_parameters": {
        "batch_size": 4,
        "loss": {
            "name": "DiceLoss"
        },
        "training_time": {
            "num_epochs": 100,
            "early_stopping_patience": 200,
            "early_stopping_epsilon": 0.001
        },
        "scheduler": {
            "initial_lr": 1e-3,
            "lr_scheduler": {
                "name": "CosineAnnealingLR",
                "base_lr": 1e-5,
                "max_lr": 1e-3
            }
        },
        "balance_samples": {
            "applied": false,
            "type": "gt"
        },
        "mixup_alpha": null,
        "transfer_learning": {
            "retrain_model": null,
            "retrain_fraction": 1.0,
            "reset": true
        }
    },
    "default_model": {
        "name": "Unet",
        "dropout_rate": 0.3,
        "bn_momentum": 0.1,
        "depth": 4,
        "is_2d": false,
        "final_activation": "sigmoid"
    },
    "uncertainty": {
        "epistemic": false,
        "aleatoric": false,
        "n_it": 0
    },
    "postprocessing": {"binarize_prediction": {"thr": 0.5}},
    "evaluation_parameters": {},
    "transformation": {
        "Resample": {
            "wspace": 1.0,
            "hspace": 1.0,
            "dspace": 1.0
        },
        "CenterCrop": {
            "size": [32, 64, 128]
        },
        "RandomReverse": {
            "applied_to": ["im", "gt"],
            "dataset_type": ["training"]
        },
        "RandomAffine": {
            "degrees": 10,
            "scale": [0.2, 0.2, 0.2],
            "translate": [0.2, 0.2, 0.2],
            "applied_to": ["im", "gt"],
            "dataset_type": ["training"]
        },
        "ElasticTransform": {
            "alpha_range": [25.0, 35.0],
            "sigma_range": [3.5, 5.5],
            "p": 0.5,
            "applied_to": ["im", "gt"],
            "dataset_type": ["training"]
        },
        "RandomGamma": {
            "log_gamma_range": [-1.5, 1.5],
            "p": 0.5,
            "applied_to": ["im"],
            "dataset_type": ["training"]
        },
        "NumpyToTensor": {},
        "NormalizeInstance": {
            "applied_to": ["im"]
        }
    },
    "Modified3DUNet": {
        "applied": true,
        "length_3D": [32, 64, 128],
        "stride_3D": [32, 64, 128],
        "attention": false,
        "n_filters": 8
    }
}