import tensorflow as tf

    else:
        initializer = tf.random_normal_initializer(stddev=weight_scale)

    with tf.device('/cpu:0'):
        embedding = get_variable('embedding_{}'.format(decoder.name), shape=embedding_shape, initializer=initializer)

    input_shape = tf.shape(decoder_inputs)
    batch_size = input_shape[0]
    time_steps = input_shape[1]

    scope_name = 'decoder_{}'.format(decoder.name)
    scope_name += '/' + '_'.join(encoder.name for encoder in encoders)
