import tensorflow.contrib as contrib

                # BN
                normalizer_fn=contrib.layers.batch_norm,
                normalizer_params={
                    "is_training": is_training,
                    "scale": True,
                    "updates_collections": None
                }
        ):
            fc1_1 = contrib.layers.fully_connected(X, 32, scope="fc1_1")
            fc1_2 = contrib.layers.fully_connected(X, 32, scope="fc1_2")

            if cross_stitch_enabled:
                with tf.variable_scope("cross_stitch_1"):
                    stitch1_1, stitch1_2 = apply_cross_stitch(fc1_1, fc1_2)
            else:
                stitch1_1, stitch1_2 = fc1_1, fc1_2
