import tensorflow as tf

  cropped_shape = control_flow_ops.with_dependencies(
      [rank_assertion],
      tf.pack([crop_height, crop_width, original_shape[2]]))

  size_assertion = tf.Assert(
      tf.logical_and(
          tf.greater_equal(original_shape[0], crop_height),
          tf.greater_equal(original_shape[1], crop_width)),
      ['Crop size greater than the image size.'])

  offsets = tf.to_int32(tf.pack([offset_height, offset_width, 0]))

  # Use tf.slice instead of crop_to_bounding box as it accepts tensors to
  # define the crop size.
