I use the CopyNetWapper to wrap a decoder, this is my code:
train_decoder = tf.contrib.seq2seq.AttentionWrapper(decoder, attention_mechanism,
attention_layer_size=self.config.PHVM_decoder_dim)
train_encoder_state = train_decoder.zero_state(self.batch_size, dtype=tf.float32).clone(
cell_state=sent_dec_state)
copynet_decoder = CopyNetWrapper(train_decoder, sent_input, sent_lens, sent_lens, self.tgt_vocab_size)
copy_train_encoder_state = copynet_decoder.zero_state(self.batch_size, dtype=tf.float32).clone(
cell_state=train_encoder_state)
However, during train I got an error:
Traceback (most recent call last):
File "/home/work/mnt/project/.local/lib/python3.6/site-packages/tensorflow/python/util/nest.py", line 297, in assert_same_structure
expand_composites)
TypeError: The two structures don't have the same nested structure.
First structure: type=CopyNetWrapperState str=CopyNetWrapperState(cell_state=AttentionWrapperState(cell_state=(<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/checked_cell_state:0' shape=(?, 300) dtype=float32>, <tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/checked_cell_state_1:0' shape=(?, 300) dtype=float32>), attention=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros_2:0' shape=(?, 300) dtype=float32>, time=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros_1:0' shape=() dtype=int32>, alignments=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros:0' shape=(?, ?) dtype=float32>, alignment_history=(), attention_state=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros_3:0' shape=(?, ?) dtype=float32>), last_ids=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/sub:0' shape=(?,) dtype=int32>, prob_c=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/zeros_1:0' shape=(?, ?) dtype=float32>)
Second structure: type=CopyNetWrapperState str=CopyNetWrapperState(cell_state=(<tf.Tensor 'sentence_level/train/while/sent_deocde/sent_dec_state/dense/BiasAdd:0' shape=(?, 300) dtype=float32>, <tf.Tensor 'sentence_level/train/while/sent_deocde/sent_dec_state/dense_1/BiasAdd:0' shape=(?, 300) dtype=float32>), last_ids=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/sub:0' shape=(?,) dtype=int32>, prob_c=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/zeros_1:0' shape=(?, ?) dtype=float32>)
More specifically: The two namedtuples don't have the same sequence type. First structure type=AttentionWrapperState str=AttentionWrapperState(cell_state=(<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/checked_cell_state:0' shape=(?, 300) dtype=float32>, <tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/checked_cell_state_1:0' shape=(?, 300) dtype=float32>), attention=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros_2:0' shape=(?, 300) dtype=float32>, time=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros_1:0' shape=() dtype=int32>, alignments=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros:0' shape=(?, ?) dtype=float32>, alignment_history=(), attention_state=<tf.Tensor 'sentence_level/train/while/sent_deocde/CopyNetWrapperZeroState/AttentionWrapperZeroState/zeros_3:0' shape=(?, ?) dtype=float32>) has type AttentionWrapperState, while second structure type=tuple str=(<tf.Tensor 'sentence_level/train/while/sent_deocde/sent_dec_state/dense/BiasAdd:0' shape=(?, 300) dtype=float32>, <tf.Tensor 'sentence_level/train/while/sent_deocde/sent_dec_state/dense_1/BiasAdd:0' shape=(?, 300) dtype=float32>) has type tuple
I have no idea how to solve the problem. Have someone met the same error before?
It will be very nice if you can offer me some advice.
Plus,
copynet_cell = CopyNetWrapper(cell, encoder_outputs, encoder_input_ids,
vocab_size, gen_vocab_size)
Would you please explain the parameters in detail ?
Looking forward to any reply.
I use the CopyNetWapper to wrap a decoder, this is my code:
However, during train I got an error:
I have no idea how to solve the problem. Have someone met the same error before?
It will be very nice if you can offer me some advice.
Plus,
Would you please explain the parameters in detail ?
Looking forward to any reply.