seq2seq_model.py 文件源码

def source_embedding(self):
    """Returns the embedding used for the source sequence.
    """
    return tf.get_variable(
        name="W",
        shape=[self.source_vocab_info.total_size, self.params["embedding.dim"]],
        initializer=tf.random_uniform_initializer(
            -self.params["embedding.init_scale"],
            self.params["embedding.init_scale"]))