import tensorflow as tf

    # pad_input_data_to_static_shape assumes that image is already concatenated
    # with additional channels.
    self.assertAllEqual(
        padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
        [5, 6, 5])
    self.assertAllEqual(
        padded_tensor_dict[fields.InputDataFields.image_additional_channels]
        .shape.as_list(), [5, 6, 2])

  def test_images_and_additional_channels_errors(self):
    input_tensor_dict = {
        fields.InputDataFields.image:
            tf.placeholder(tf.float32, [None, None, 3]),
        fields.InputDataFields.image_additional_channels:
            tf.placeholder(tf.float32, [None, None, 2]),
        fields.InputDataFields.original_image:
            tf.placeholder(tf.float32, [None, None, 3]),
    }
    with self.assertRaises(ValueError):
      _ = inputs.pad_input_data_to_static_shapes(
          tensor_dict=input_tensor_dict,
          max_num_boxes=3,
          num_classes=3,
          spatial_image_shape=[5, 6])
