import tensorflow as tf

          true_image_shapes: int32 tensor of shape [batch, 3] where each row is
            of the form [height, width, channels] indicating the shapes
            of true images in the resized images, as resized images can be padded
            with zeros.
        """
        true_image_shapes = [inputs.shape[:-1].as_list()
                             for _ in range(inputs.shape[-1])]
        return tf.image.resize_images(inputs, [28, 28]), true_image_shapes

    def predict(self, preprocessed_inputs, true_image_shapes):
        """Prediction tensors from inputs tensor.

        Args:
          preprocessed_inputs: a [batch, 28, 28, channels] float32 tensor.
