import tensorflow as tf

            name='H')
        T = tf.layers.dense(
            inputs,
            units=depth,
            activation=tf.nn.sigmoid,
            name='T',
            bias_initializer=tf.constant_initializer(-1.0))
        return H * T + inputs * (1.0 - T)


def conv1d(inputs, kernel_size, channels, activation, is_training, scope):
    with tf.variable_scope(scope):
