import tensorflow as tf

            weights=mix_kernels,
            strides=[1, 1, 1, 1, 1],
            symmetric_weights=self.symmetric_gate_weights,
            dilations=self.hgru_dilations[layer_idx])

        with tf.variable_scope(
                '%s/g2_bn' % var_scope,
                reuse=self.scope_reuse) as scope:
            g2_intermediate = tf.contrib.layers.batch_norm(
                inputs=g2_intermediate + mix_bias,
