def create_random_augment(
    input_size,
    auto_augment=None,
    interpolation="bilinear",
):
    """
    Get video randaug transform.

    Args:
        input_size: The size of the input video in tuple.
        auto_augment: Parameters for randaug. An example:
            "rand-m7-n4-mstd0.5-inc1" (m is the magnitude and n is the number
            of operations to apply).
        interpolation: Interpolation method.
    """
    if isinstance(input_size, tuple):
        img_size = input_size[-2:]
    else:
        img_size = input_size

    if auto_augment:
        assert isinstance(auto_augment, str)
        if isinstance(img_size, tuple):
            img_size_min = min(img_size)
        else:
            img_size_min = img_size
        aa_params = {"translate_const": int(img_size_min * 0.45)}
        if interpolation and interpolation != "random":
            aa_params["interpolation"] = _pil_interp(interpolation)
        if auto_augment.startswith("rand"):
            return transforms.Compose(
                [rand_augment_transform(auto_augment, aa_params)]
            )
    raise NotImplementedError
Get video randaug transform.

Args:
input_size: The size of the input video in tuple.
auto_augment: Parameters for randaug. An example:
"rand-m7-n4-mstd0.5-inc1" (m is the magnitude and n is the number
of operations to apply).
interpolation: Interpolation method.
videomamba/video_sm/datasets/video_transforms.py