basic_seq2seq.py 文件源码

def _decode_infer(self, decoder, bridge, _encoder_output, features, labels):
    """Runs decoding in inference mode"""
    batch_size = self.batch_size(features, labels)
    if self.use_beam_search:
      batch_size = self.params["inference.beam_search.beam_width"]

    target_start_id = self.target_vocab_info.special_vocab.SEQUENCE_START
    helper_infer = tf_decode_helper.GreedyEmbeddingHelper(
        embedding=self.target_embedding,
        start_tokens=tf.fill([batch_size], target_start_id),
        end_token=self.target_vocab_info.special_vocab.SEQUENCE_END)
    decoder_initial_state = bridge()
    return decoder(decoder_initial_state, helper_infer)