import tensorflow as tf

            name="dense2",
        )
        outputs = H * T + inputs * (1.0 - T)
    return outputs


def conv1d_banks(inputs, K=16, is_training=True, scope="conv1d_banks"):
    with tf.variable_scope(scope):
        outputs = tf.layers.conv1d(inputs, embed_size // 2, 1, padding="SAME")
        for k in range(2, K + 1):
            with tf.variable_scope("num_{}".format(k)):
                output = tf.layers.conv1d(inputs, embed_size // 2, k, padding="SAME")
                outputs = tf.concat((outputs, output), -1)
        outputs = tf.nn.relu(tf.layers.batch_normalization(outputs, training=is_training))
    return outputs

