seq2seq_aligner.py 文件源码

def pad_up_to(vector, size):
    rank = vector.get_shape().ndims - 1

    length_diff = tf.reshape(size - tf.shape(vector)[1], shape=(1,))
    with tf.control_dependencies([tf.assert_non_negative(length_diff, data=(vector, size, tf.shape(vector)))]):
        padding = tf.reshape(tf.concat([[0, 0, 0], length_diff, [0,0]*(rank-1)], axis=0), shape=((rank+1), 2))
        return tf.pad(vector, padding, mode='constant')