小编Arg*_*rgs的帖子

值在哪里

rnn_size: 512
batch_size: 128


rnn_inputs: Tensor("embedding_lookup/Identity_1:0", shape=(?, ?, 128), dtype=float32)
sequence_length: Tensor("inputs_length:0", shape=(?,), dtype=int32)
cell_fw: <tensorflow.python.keras.layers.legacy_rnn.rnn_cell_impl.DropoutWrapper object at 0x7f4f534eb6d0>
cell_bw: <tensorflow.python.keras.layers.legacy_rnn.rnn_cell_impl.DropoutWrapper object at 0x7f4f534eb910>

获取 enc_state 值

enc_output, enc_state = tf.compat.v1.nn.bidirectional_dynamic_rnn(cell_fw, 
                                                                        cell_bw, 
                                                                        rnn_inputs,
                                                                        sequence_length,
                                                                        dtype=tf.float32)

enc_state 值在哪里

enc_state: LSTMStateTuple(c=<tf.Tensor 'RNN_Encoder_Cell_2D/encoder_1/bidirectional_rnn/fw/fw/while/Exit_3:0' shape=(?, 512) dtype=float32>, h=<tf.Tensor 'RNN_Encoder_Cell_2D/encoder_1/bidirectional_rnn/fw/fw/while/Exit_4:0' shape=(?, 512) dtype=float32>)

TF1代码：

initial_state = tf.contrib.seq2seq.DynamicAttentionWrapperState(enc_state,
                                                                _zero_state_tensors(rnn_size, 
                                                                                    batch_size, 
                                                                                    tf.float32))

转换为 TF2

initial_state = tfa.seq2seq.AttentionWrapper(enc_state,_zero_state_tensors(rnn_size, batch_size, tf.float32))

获取错误：

TypeError                                 Traceback (most recent call last)
<ipython-input-54-d87646b9df5d> in <module>()
      8                                                     threshold) 
      9             model = build_graph(keep_probability, rnn_size, …