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ValueError:两个结构的元素数量不同

with tf.variable_scope('forward'):
  cell_img_fwd = tf.nn.rnn_cell.GRUCell(hidden_state_size, hidden_state_size)
  img_init_state_fwd = rnn_img_mapped[:, 0, :]
  img_init_state_fwd = tf.multiply(
      img_init_state_fwd, 
      tf.zeros([batch_size, hidden_state_size]))
  rnn_outputs2, final_state2 = tf.nn.dynamic_rnn(
      cell_img_fwd, 
      rnn_img_mapped, 
      initial_state=img_init_state_fwd, 
      dtype=tf.float32)
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这是我用于输入维度100x196x50的GRU的代码,它应该沿第二维(即196)解压缩.hidden_state_size是50,batch_size是100.但是我收到以下错误:

ValueError: The two structures don't have the same number of elements.
First structure: Tensor("backward/Tile:0", shape=(100, 50), dtype=float32), 
second structure: 
  (<tf.Tensor 'backward/bwd_states/while/GRUCell/add:0' shape=(100, 50) dtype=float32>, 
   <tf.Tensor 'backward/bwd_states/while/GRUCell/add:0' shape=(100, 50) dtype=float32>).
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有任何线索如何解决这个问题?

tensorflow recurrent-neural-network gated-recurrent-unit

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