maps.json

{
    "architecture": "Conv5_FC3",
    "multi_network": false,
    "dropout": 0.0,
    "latent_space_size": 128,
    "feature_size": 1024,
    "n_conv": 4,
    "io_layer_channels": 8,
    "recons_weight": 1,
    "kl_weight": 1,
    "normalization": "batch",
    "selection_metrics": [
        "loss"
    ],
    "label": "age",
    "loss": "MSELoss",
    "gpu": false,
    "n_proc": 2,
    "batch_size": 8,
    "evaluation_steps": 0,
    "amp": false,
    "seed": 0,
    "deterministic": false,
    "compensation": "memory",
    "transfer_path": "",
    "transfer_selection_metric": "loss",
    "nb_unfrozen_layer": 0,
    "use_extracted_features": false,
    "multi_cohort": false,
    "diagnoses": [
        "AD",
        "CN"
    ],
    "baseline": false,
    "normalize": true,
    "data_augmentation": false,
    "sampler": "random",
    "size_reduction": false,
    "size_reduction_factor": 2,
    "n_splits": 2,
    "optimizer": "Adam",
    "epochs": 5,
    "learning_rate": 0.0001,
    "weight_decay": 0.0001,
    "patience": 0,
    "tolerance": 0.0,
    "accumulation_steps": 1,
    "profiler": false,
    "network_task": "regression",
    "caps_directory": "/Users/camille.brianceau/aramis/clinicadl_data_ci/data_ci/train/in/caps_image",
    "tsv_path": "/Users/camille.brianceau/aramis/clinicadl_data_ci/data_ci/train/in/labels_list/2_fold",
    "preprocessing_dict": {
        "preprocessing": "t1-linear",
        "mode": "image",
        "use_uncropped_image": false,
        "prepare_dl": false,
        "extract_json": "t1-linear_mode-image.json",
        "file_type": {
            "pattern": "*space-MNI152NLin2009cSym_desc-Crop_res-1x1x1_T1w.nii.gz",
            "description": "T1W Image registered using t1-linear and cropped (matrix size 169\u00d7208\u00d7179, 1 mm isotropic voxels)",
            "needed_pipeline": "t1-linear"
        }
    },
    "mode": "image",
    "split": [],
    "validation": "KFoldSplit",
    "selection_threshold": null,
    "label_code": null,
    "num_networks": 1,
    "output_size": 1,
    "input_size": [
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    ]
}