import tensorflow as tf

        flattened_inputs = tf.contrib.layers.flatten(preprocessed_inputs)
        class_prediction = tf.contrib.layers.fully_connected(
            flattened_inputs, self._num_classes)
        box_prediction = tf.contrib.layers.fully_connected(flattened_inputs, 4)

        return {
            'class_predictions_with_background': tf.reshape(
                class_prediction, [-1, 1, self._num_classes]),
            'box_encodings': tf.reshape(box_prediction, [-1, 1, 4])
        }

    def postprocess(self, prediction_dict, true_image_shapes, **params):
        """Convert predicted output tensors to final detections. Unused.

        Args:
          prediction_dict: a dictionary holding prediction tensors.
