telegram.py 文件源码

python
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项目:Seq2Seq-Chatbot 作者: FR0ST1N 项目源码 文件源码
def decode():
  gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.2)
  config = tf.ConfigProto(gpu_options=gpu_options)

  with tf.Session(config=config) as sess:
    model = create_model(sess, True)
    model.batch_size = 1 
    enc_vocab_path = os.path.join(working_directory,"vocab%d.enc" % enc_vocab_size)
    dec_vocab_path = os.path.join(working_directory,"vocab%d.dec" % dec_vocab_size)

    enc_vocab, _ = data_utils.initialize_vocabulary(enc_vocab_path)
    _, rev_dec_vocab = data_utils.initialize_vocabulary(dec_vocab_path)
    print('Start chatting...')
    @bot.message_handler(func=lambda sentence: True)
    def reply_all(message):
        sentence = (message.text).lower()
        token_ids = data_utils.sentence_to_token_ids(tf.compat.as_bytes(sentence), enc_vocab)
        bucket_id = min([b for b in xrange(len(_buckets))
                        if _buckets[b][0] > len(token_ids)])
        encoder_inputs, decoder_inputs, target_weights = model.get_batch(
            {bucket_id: [(token_ids, [])]}, bucket_id)
        _, _, output_logits = model.step(sess, encoder_inputs, decoder_inputs,
                                        target_weights, bucket_id, True)
        outputs = [int(np.argmax(logit, axis=1)) for logit in output_logits]
        if data_utils.EOS_ID in outputs:
            outputs = outputs[:outputs.index(data_utils.EOS_ID)]
        message_text = " ".join([tf.compat.as_str(rev_dec_vocab[output]) for output in outputs])
        bot.reply_to(message, message_text)
    while True:
        try:
            bot.polling(none_stop=True)
        except Exception as ex:
            print(str(ex))
            bot.stop_polling()
            time.sleep(5)
            bot.polling()
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