Class SimulateDelay

monai/transforms/utility/array.py:749–780

This is a pass through transform to be used for testing purposes. It allows adding fake behaviors that are useful for testing purposes to simulate how large datasets behave without needing to test on large data sets. For example, simulating slow NFS data transfers, or slow network

class SimulateDelay(Transform):
    """
    This is a pass through transform to be used for testing purposes. It allows
    adding fake behaviors that are useful for testing purposes to simulate
    how large datasets behave without needing to test on large data sets.

    For example, simulating slow NFS data transfers, or slow network transfers
    in testing by adding explicit timing delays. Testing of small test data
    can lead to incomplete understanding of real world issues, and may lead
    to sub-optimal design choices.
    """

    backend = [TransformBackends.TORCH, TransformBackends.NUMPY]

    def __init__(self, delay_time: float = 0.0) -> None:
        """
        Args:
            delay_time: The minimum amount of time, in fractions of seconds,
                to accomplish this delay task.
        """
        super().__init__()
        self.delay_time: float = delay_time

    def __call__(self, img: NdarrayOrTensor, delay_time: float | None = None) -> NdarrayOrTensor:
        """
        Args:
            img: data remain unchanged throughout this transform.
            delay_time: The minimum amount of time, in fractions of seconds,
                to accomplish this delay task.
        """
        time.sleep(self.delay_time if delay_time is None else delay_time)
        return img


class Lambda(InvertibleTransform):