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我訓練一個類似於在tensorflow教程，爲連續數據的RNN session.run Tensorflow ValueError異常。數據是[batch_size，step，dimension]，標籤是[batch_size，num_classes]。由於不同樣本的序列長度不同，因此我想創建批次訓練 - 每次抓取32個樣本數據時，將它們填充到最長的序列大小，然後將它們送入rnn圖形進行訓練。上一批培訓
的數據被定義爲：
data = DataGenerator(data_path, label_path)
train_data, train_label, train_seqlen, test_data, test_label = data.train_test_data(0.2)
x = tf.placeholder(tf.float32, [batch_size, None, num_dim])
y = tf.placeholder(tf.float32, [batch_size, num_classes])
seqlen = tf.placeholder(tf.int32, [batch_size])
model = VariableSeqModel(x, y, seqlen)
Train_data是[batch_size時，步驟，暗淡]，train_label是[batch_size時，num_classes]。 Seqlen是[batch_size時，1]用於記錄樣品的實際序列長度中的每個批次。這是否正確，我將x定義爲[batch_size，None，num_dim]用於變量序列長度？
限定RNN和數據結構，啓動會話，因爲這代碼示例中後：
with tf.Session() as sess:
sess.run(tf.initialize_all_variables())
step = 1
while step*batch_size < 1000:
batch_xx, batch_y, batch_seqlen = data.next(batch_size, train_data, train_label, train_seqlen)
batch_x = data.batch_padding(batch_xx,batch_seqlen)
sess.run(model.optimize, feed_dict={x: batch_xx, y: batch_y, seqlen: batch_seqlen})
step += 1
我打於以下ValueError異常（下面堆棧跟蹤）：
dynamic_rnn.py in <module>()
--> 129 sess.run(model.optimize, feed_dict={x: batch_xx, y: batch_y, seqlen: batch_seqlen})
tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
708 try:
709 result = self._run(None, fetches, feed_dict, options_ptr,
--> 710 run_metadata_ptr)
711 if run_metadata:
712 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
879 ' to a larger type (e.g. int64).')
880
--> 881 np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
882
883 if not subfeed_t.get_shape().is_compatible_with(np_val.shape):
numpy/core/numeric.pyc in asarray(a, dtype, order)
480
481 """
--> 482 return array(a, dtype, copy=False, order=order)
483
484 def asanyarray(a, dtype=None, order=None):
ValueError: setting an array element with a sequence.
我在難倒這點。任何幫助感謝！