import tensorflow as tf

    ValueError: if `image_tensor`'s' width or height is smaller than `min_dim`.
  """
  image_shape = image_tensor.get_shape()
  image_height = static_shape.get_height(image_shape)
  image_width = static_shape.get_width(image_shape)
  if image_height is None or image_width is None:
    shape_assert = tf.Assert(
        tf.logical_and(tf.greater_equal(tf.shape(image_tensor)[1], min_dim),
                       tf.greater_equal(tf.shape(image_tensor)[2], min_dim)),
        ['image size must be >= {} in both height and width.'.format(min_dim)])
    with tf.control_dependencies([shape_assert]):
      return tf.identity(image_tensor)

  if image_height < min_dim or image_width < min_dim:
    raise ValueError(
        'image size must be >= %d in both height and width; image dim = %d,%d' %
        (min_dim, image_height, image_width))

  return image_tensor


def assert_shape_equal(shape_a, shape_b):
