Source code for slideflow.biscuit.hp

"""Hyperparameters associated with the published manuscript."""

import slideflow as sf


def nature2022():
    """Hyperparameters used in the associated manuscript.

    Dolezal, J.M., Srisuwananukorn, A., Karpeyev, D. et al.
    Uncertainty-informed deep learning models enable high-confidence
    predictions for digital histopathology. Nat Commun 13, 6572 (2022).
    https://doi.org/10.1038/s41467-022-34025-x

    Returns:
        ``sf.ModelParams``

    """
    if sf.backend() == 'tensorflow':
        loss = 'sparse_categorical_crossentropy'
    else:
        loss = 'CrossEntropy'
    return sf.ModelParams(
        model='xception',
        tile_px=299,
        tile_um=302,
        batch_size=128,
        epochs=[1],         # epochs 1, 3, 5, 10 used for initial sweep
        early_stop=True,
        early_stop_method='accuracy',
        dropout=0.1,
        uq=False,           # to be enabled in separate sub-experiments
        hidden_layer_width=1024,
        optimizer='Adam',
        learning_rate=0.0001,
        learning_rate_decay_steps=512,
        learning_rate_decay=0.98,
        loss=loss,
        normalizer='reinhard_fast',
        include_top=False,
        hidden_layers=2,
        pooling='avg',
        augment='xyrjb'
    )