How to use the albumentations.OneOf function in albumentations

def empty_aug1():
    return [
        HorizontalFlip(p=0.001),
        # IAAPiecewiseAffine(p=1.0),
        OneOf(
            [
                # OpticalDistortion(p=0.1),
                # GridDistortion(p=0.1),
                # IAAPerspective(p=1.0),
                # IAAAffine(p=1.0),
                IAAPiecewiseAffine(p=1.0)
            ],
            p=0.0,
        ),

def light_augmentations():
    return A.Compose([
        A.HorizontalFlip(),
        A.RandomBrightnessContrast(),
        A.OneOf([
            A.ShiftScaleRotate(scale_limit=0.05, rotate_limit=15, border_mode=cv2.BORDER_CONSTANT),
            A.IAAAffine(),
            A.IAAPerspective(),
            A.NoOp()
        ]),
        A.HueSaturationValue(),
        A.Normalize()
    ])

),
            height=train_parameters["height_crop_size"],
            width=train_parameters["width_crop_size"],
            w2h_ratio=1.0,
            p=1,
        ),
        albu.ShiftScaleRotate(
            border_mode=cv2.BORDER_CONSTANT, rotate_limit=10, scale_limit=0, p=0.5, mask_value=ignore_index
        ),
        albu.RandomBrightnessContrast(p=0.5),
        albu.RandomGamma(p=0.5),
        albu.ImageCompression(quality_lower=20, quality_upper=100, p=0.5),
        albu.GaussNoise(p=0.5),
        albu.Blur(p=0.5),
        albu.CoarseDropout(p=0.5, max_height=26, max_width=16),
        albu.OneOf([albu.HueSaturationValue(p=0.5), albu.RGBShift(p=0.5)], p=0.5),
        normalization,
    ],
    p=1,
)

val_augmentations = albu.Compose(
    [
        albu.PadIfNeeded(
            min_height=1024, min_width=2048, border_mode=cv2.BORDER_CONSTANT, mask_value=ignore_index, p=1
        ),
        normalization,
    ],
    p=1,
)

test_augmentations = albu.Compose([normalization], p=1)

value=0),
            A.NoOp()
        ]),

        A.OneOf([

            A.RandomSizedCrop(min_max_height=(int(image_size[0] * 0.75), image_size[0]),
                              height=image_size[0],
                              width=image_size[1], p=0.3),
            A.NoOp()
        ]),

        A.ISONoise(p=0.5),

        # Brightness/contrast augmentations
        A.OneOf([
            A.RandomBrightnessContrast(brightness_limit=0.5,
                                       contrast_limit=0.4),
            IndependentRandomBrightnessContrast(brightness_limit=0.25,
                                                contrast_limit=0.24),
            A.RandomGamma(gamma_limit=(50, 150)),
            A.NoOp()
        ]),

        A.OneOf([
            A.RGBShift(r_shift_limit=40, b_shift_limit=30, g_shift_limit=30),
            A.HueSaturationValue(hue_shift_limit=10,
                                 sat_shift_limit=10),
            A.ToGray(p=0.2),
            A.NoOp()
        ]),

def get_augumentation(phase, width=512, height=512, min_area=0., min_visibility=0.):
    list_transforms = []
    if phase == 'train':
        list_transforms.extend([
            albu.OneOf([
                albu.ShiftScaleRotate(shift_limit=0.05, scale_limit=0.1,
                                      rotate_limit=15,
                                      border_mode=cv2.BORDER_CONSTANT, value=0),
                albu.NoOp()
            ]),
            albu.augmentations.transforms.RandomResizedCrop(
                                 height=height,
                                 width=width, p=1.0),
            albu.OneOf([
                albu.RandomBrightnessContrast(brightness_limit=0.5,
                                              contrast_limit=0.4),
                albu.RandomGamma(gamma_limit=(50, 150)),
                albu.NoOp()
            ]),
            albu.OneOf([
                albu.RGBShift(r_shift_limit=20, b_shift_limit=15,

),
            height=train_parameters["height_crop_size"],
            width=train_parameters["width_crop_size"],
            w2h_ratio=1.0,
            p=1,
        ),
        albu.ShiftScaleRotate(
            border_mode=cv2.BORDER_CONSTANT, rotate_limit=10, scale_limit=0, p=0.5, mask_value=ignore_index
        ),
        albu.RandomBrightnessContrast(p=0.5),
        albu.RandomGamma(p=0.5),
        albu.ImageCompression(quality_lower=20, quality_upper=100, p=0.5),
        albu.GaussNoise(p=0.5),
        albu.Blur(p=0.5),
        albu.CoarseDropout(p=0.5, max_height=26, max_width=16),
        albu.OneOf([albu.HueSaturationValue(p=0.5), albu.RGBShift(p=0.5)], p=0.5),
        normalization,
    ],
    p=1,
)

val_augmentations = albu.Compose(
    [
        albu.PadIfNeeded(
            min_height=1024, min_width=2048, border_mode=cv2.BORDER_CONSTANT, mask_value=ignore_index, p=1
        ),
        normalization,
    ],
    p=1,
)

test_augmentations = albu.Compose([normalization], p=1)