Function engine_apply_transform

monai/engines/utils.py:325–350

Apply transform on `batch` and `output`. If `batch` and `output` are dictionaries, temporarily combine them for the transform, otherwise, apply the transform for `output` data only.

(batch: Any, output: Any, transform: Callable[..., dict])

def engine_apply_transform(batch: Any, output: Any, transform: Callable[..., dict]) -> tuple[Any, Any]:
    """
    Apply transform on `batch` and `output`.
    If `batch` and `output` are dictionaries, temporarily combine them for the transform,
    otherwise, apply the transform for `output` data only.

    """
    if isinstance(batch, dict) and isinstance(output, dict):
        data = dict(batch)
        data.update(output)
        transformed_data = apply_transform(transform, data)

        if not isinstance(transformed_data, dict):
            raise AssertionError("With a dict supplied to apply_transform a single dict return is expected.")

        for k, v in transformed_data.items():
            # split the output data of post transforms into `output` and `batch`,
            # `batch` should be read-only, so save the generated key-value into `output`
            if k in output or k not in batch:
                output[k] = v
            else:
                batch[k] = v
    else:
        output = apply_transform(transform, output)

    return batch, output


def default_metric_cmp_fn(current_metric: float, prev_best: float) -> bool: