我正在使用张量流中的双向动态RNN进行文本标记。匹配输入的维度后，我尝试运行一个Session。这是blstm设置部分：

fw_lstm_cell = BasicLSTMCell(LSTM_DIMS)
bw_lstm_cell = BasicLSTMCell(LSTM_DIMS)

(fw_outputs, bw_outputs), _ = bidirectional_dynamic_rnn(fw_lstm_cell,
                                                        bw_lstm_cell,
                                                        x_place,
                                                        sequence_length=SEQLEN,
                                                        dtype='float32')

这是运行的一部分：

  with tf.Graph().as_default():
    # Placehoder Settings
    x_place, y_place = set_placeholder(BATCH_SIZE, EM_DIMS, MAXLEN)

    # BLSTM Model Building
    hlogits = tf_kcpt.build_blstm(x_place)

    # Compute loss
    loss = tf_kcpt.get_loss(log_likelihood)

    # Training
    train_op = tf_kcpt.training(loss)

    # load Eval method
    eval_correct = tf_kcpt.evaluation(logits, y_place)

    # Session Setting & Init
    init = tf.global_variables_initializer()
    sess = tf.Session()
    sess.run(init)

    # tensor summary setting
    summary = tf.summary.merge_all()
    summary_writer = tf.summary.FileWriter(LOG_DIR, sess.graph)

    # Save
    saver = tf.train.Saver()

    # Run epoch
    for step in range(EPOCH):
        start_time = time.time()

        feed_dict = fill_feed_dict(KCPT_SET['train'], x_place, y_place)
        _, loss_value = sess.run([train_op, loss], feed_dict=feed_dict)

但是，它给了我错误：

ValueError：Tensor（“ Shape：0”，shape =（1，），dtype = int32）必须与Tensor（“ bidirectional_rnn / fw / fw / fw / stack_2：0”，shape =（1，），dtype来自同一张图= int32）。

请帮帮我