def METHOD_NAME(image: tf.Tensor) -> tf.Tensor:
    """
    Crops an image to a random part of the image, then randomly flips.
    :param image: `Tensor` representing an image of arbitrary size.
    :return: a cropped image `Tensor`.
    """
    bbox = tf.constant([0.0, 0.0, 1.0, 1.0], dtype=tf.float32, shape=[1, 1, 4])
    shape = tf.shape(image)
    sample_distorted_bounding_box = tf.image.sample_distorted_bounding_box(
        shape,
        bounding_boxes=bbox,
        min_object_covered=0.1,
        aspect_ratio_range=[0.75, 1.33],
        area_range=[0.05, 1.0],
        max_attempts=100,
        use_image_if_no_bounding_boxes=True,
    )
    bbox_begin, bbox_size, _ = sample_distorted_bounding_box
    # Reassemble the bounding box in the format the crop op requires.
    offset_height, offset_width, _ = tf.unstack(bbox_begin)
    target_height, target_width, _ = tf.unstack(bbox_size)
    cropped = tf.image.crop_to_bounding_box(
        image,
        offset_height=offset_height,
        offset_width=offset_width,
        target_height=target_height,
        target_width=target_width,
    )
    # Flip to add a little more random distortion in.
    cropped = tf.image.random_flip_left_right(cropped)
    return cropped