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问题是将给定的学生答案与给出模态答案或正确答案的教师进行比较，并为学生的答案打分。经过大量研究，具有 LSTM 的 Siamese 架构似乎是神经网络架构的一个非常好的选择，因为该问题与查找两对句子之间的文本相似性高度相似。我目前采用了最简单的架构，其中一个嵌入层使用预训练的 word2vec 模型，在嵌入之上添加 LSTM，采用多对一架构，然后使用余弦相似度来计算正确答案和学生给出的答案之间的相似度.

模型创建似乎很好，但我在使用余弦相似度度量合并两个 LSTM 时遇到问题

这是我的代码..

true_ans_model = Sequential()
true_ans_model.add(Embedding(nbwords+1, EMBEDDING_DIM, weights= weightMatrixWithPadding], mask_zero=True, trainable=False ))
x_left = true_ans_model.add(LSTM(MAX_SENTENCE_LENGTH,return_sequences=False))

stud_ans_model = Sequential()
stud_ans_model.add(Embedding(nbwords+1, EMBEDDING_DIM, weights=[weightMatrixWithPadding], mask_zero=True, trainable=False ))
stud_ans_model.add(LSTM(MAX_SENTENCE_LENGTH, return_sequences=False))

merge_lstms = merge([x_left, x_right], mode='cos', dot_axes=1)

这是错误：

ValueError                                Traceback (most recent call last)
~\Anaconda3\lib\site-packages\keras\engine\topology.py in assert_input_compatibility(self, inputs)
   418             try:
--> 419                 K.is_keras_tensor(x)
420             except ValueError:

~\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in is_keras_tensor(x)
392                           tf.SparseTensor)):
--> 393         raise ValueError('Unexpectedly found an instance of type `' + str(type(x)) + '`. '
394                          'Expected a symbolic tensor instance.')

ValueError: Unexpectedly found an instance of type `<class 'NoneType'>`. Expected a symbolic tensor instance.

During handling of the above exception, another exception occurred:
~\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in is_keras_tensor(x)
392                           tf.SparseTensor)):
--> 393         raise ValueError('Unexpectedly found an instance of type `' + str(type(x)) + '`. '
 394                          'Expected a symbolic tensor instance.')

ValueError: Unexpectedly found an instance of type `<class 'NoneType'>`. 
Expected a symbolic tensor instance.

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
    <ipython-input-41-7a6e14b23349> in <module>()
----> 1 merge_lstms = merge([x_left, x_right], mode='cos', dot_axes=1)
  #final_layer = dot([x_left,x_right], axes=1, normalize=True)
  predictions = Dense(1, activation = 'sigmoid')(final_layer)

 ~\Anaconda3\lib\site-packages\keras\legacy\layers.py in merge(inputs, mode, concat_axis, dot_axes, output_shape, output_mask, arguments, name)
  466                             arguments=arguments,
  467                             name=name)
--> 468         return merge_layer(inputs)
  469 
470 

~\Anaconda3\lib\site-packages\keras\engine\topology.py in __call__(self, inputs, **kwargs)
550                 # Raise exceptions in case the input is not compatible
551                 # with the input_spec specified in the layer constructor.
--> 552                 self.assert_input_compatibility(inputs)
553 
554                 # Collect input shapes to build layer.

~\Anaconda3\lib\site-packages\keras\engine\topology.py in assert_input_compatibility(self, inputs)
    423                                  'Received type: ' +
    424                                  str(type(x)) + '. Full input: ' +
--> 425                                  str(inputs) + '. All inputs to the 
layer '
    426                                  'should be tensors.')


ValueError: Layer merge_3 was called with an input that isn't a symbolic tensor. Received type: <class 'NoneType'>. Full input: [None, None]. All inputs to the layer should be tensors.
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