Function create_transform

Args: input_size: Target input size (channels, height, width) tuple or size scalar. is_training: Return training (random) transforms. no_aug: Disable augmentation for training (useful for debug). train_crop_mode: Training random crop mode ('rrc', 'rkrc', 'rkrr')

(
        input_size: Union[int, Tuple[int, int], Tuple[int, int, int]] = 224,
        is_training: bool = False,
        no_aug: bool = False,
        train_crop_mode: Optional[str] = None,
        scale: Optional[Tuple[float, float]] = None,
        ratio: Optional[Tuple[float, float]] = None,
        hflip: float = 0.5,
        vflip: float = 0.,
        color_jitter: Union[float, Tuple[float, ...]] = 0.4,
        color_jitter_prob: Optional[float] = None,
        grayscale_prob: float = 0.,
        gaussian_blur_prob: float = 0.,
        auto_augment: Optional[str] = None,
        interpolation: str = 'bilinear',
        mean: Tuple[float, ...] = IMAGENET_DEFAULT_MEAN,
        std: Tuple[float, ...] = IMAGENET_DEFAULT_STD,
        re_prob: float = 0.,
        re_mode: str = 'const',
        re_count: int = 1,
        re_num_splits: int = 0,
        crop_pct: Optional[float] = None,
        crop_mode: Optional[str] = None,
        crop_border_pixels: Optional[int] = None,
        tf_preprocessing: bool = False,
        use_prefetcher: bool = False,
        separate: bool = False,
)