Class RandomOrder

monai/transforms/compose.py:567–661

``RandomOrder`` provides the ability to apply a list of transformations in random order. Args: transforms: sequence of callables. map_items: whether to apply transform to each item in the input `data` if `data` is a list or tuple. defaults to `True`. unp

class RandomOrder(Compose):
    """
    ``RandomOrder`` provides the ability to apply a list of transformations in random order.

    Args:
        transforms: sequence of callables.
        map_items: whether to apply transform to each item in the input `data` if `data` is a list or tuple.
            defaults to `True`.
        unpack_items: whether to unpack input `data` with `*` as parameters for the callable function of transform.
            defaults to `False`.
        log_stats: this optional parameter allows you to specify a logger by name for logging of pipeline execution.
            Setting this to False disables logging. Setting it to True enables logging to the default loggers.
            Setting a string overrides the logger name to which logging is performed.
        lazy: whether to enable :ref:`Lazy Resampling<lazy_resampling>` for lazy transforms. If False, transforms will
            be carried out on a transform by transform basis. If True, all lazy transforms will be executed by
            accumulating changes and resampling as few times as possible. If lazy is None, `Compose` will
            perform lazy execution on lazy transforms that have their `lazy` property set to True.
        overrides: this optional parameter allows you to specify a dictionary of parameters that should be overridden
            when executing a pipeline. These each parameter that is compatible with a given transform is then applied
            to that transform before it is executed. Note that overrides are currently only applied when
            :ref:`Lazy Resampling<lazy_resampling>` is enabled for the pipeline or a given transform. If lazy is False
            they are ignored. Currently supported args are:
            {``"mode"``, ``"padding_mode"``, ``"dtype"``, ``"align_corners"``, ``"resample_mode"``, ``device``}.
    """

    def __init__(
        self,
        transforms: Sequence[Callable] | Callable | None = None,
        map_items: bool = True,
        unpack_items: bool = False,
        log_stats: bool | str = False,
        lazy: bool | None = False,
        overrides: dict | None = None,
    ) -> None:
        super().__init__(transforms, map_items, unpack_items, log_stats, lazy, overrides)
        self.log_stats = log_stats

    def __call__(self, input_, start=0, end=None, threading=False, lazy: bool | None = None):
        if start != 0:
            raise ValueError(f"RandomOrder requires 'start' parameter to be 0 (start set to {start})")
        if end is not None:
            raise ValueError(f"RandomOrder requires 'end' parameter to be None (end set to {end}")

        if len(self.transforms) == 0:
            return input_

        num = len(self.transforms)
        applied_order = self.R.permutation(range(num))
        _lazy = self._lazy if lazy is None else lazy

        input_ = execute_compose(
            input_,
            [self.transforms[ind] for ind in applied_order],
            start=start,
            end=end,
            map_items=self.map_items,
            unpack_items=self.unpack_items,
            lazy=_lazy,