连接层（Keras函数API）的ValueError

Question

在这里搜索了一下，我还是找不到解决办法。我是凯拉斯的新手，如果有解决办法我会道歉，我真的不明白这和我的问题有什么关系。

我正在用Keras 2/Functional API制作一个小的RNN，我很难使连接层工作。

这是我的结构：

inputSentence = Input(shape=(30, 91))
sentenceMatrix = LSTM(91, return_sequences=True, input_shape=(30, 91))(inputSentence)

inputDeletion = Input(shape=(30, 1))
deletionMatrix = (LSTM(30, return_sequences=True, input_shape=(30, 1)))(inputDeletion)

fusion = Concatenate([sentenceMatrix, deletionMatrix])
fusion = Dense(122, activation='relu')(fusion)
fusion = Dense(102, activation='relu')(fusion)
fusion = Dense(91, activation='sigmoid')(fusion)

F = Model(inputs=[inputSentence, inputDeletion], outputs=fusion)

下面是错误：

ValueError: Unexpectedly found an instance of type `<class 'keras.layers.merge.Concatenate'>`. Expected a symbolic tensor instance.

完整的历史记录（如果有帮助的话）：

Using TensorFlow backend.
    str(inputs) + '. All inputs to the layer '
ValueError: Layer dense_1 was called with an input that isn't a symbolic tensor. Received type: <class 'keras.layers.merge.Concatenate'>. Full input: [<keras.layers.merge.Concatenate object at 0x00000000340DC4E0>]. All inputs to the layer should be tensors.
self.assert_input_compatibility(inputs)
  File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\topology.py", line 425, in assert_input_compatibility
fusion = Dense(122, activation='relu')(fusion)
  File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\topology.py", line 552, in __call__
Traceback (most recent call last):
  File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\topology.py", line 419, in assert_input_compatibility
K.is_keras_tensor(x)
  File "C:\ProgramData\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 392, in is_keras_tensor
raise ValueError('Unexpectedly found an instance of type `' + str(type(x)) + '`. '
ValueError: Unexpectedly found an instance of type `<class 'keras.layers.merge.Concatenate'>`. Expected a symbolic tensor instance.

我在Windows7上使用Python3.6和Spyder3.1.4。今早我用pip升级了TensorFlow和Keras。

感谢您的帮助！

Answer 1

试试看

fusion = Concatenate()([sentenceMatrix, deletionMatrix])

Answer 2

尝试：

fusion = concatenate([sentenceMatrix, deletionMatrix])

Concatenate用于Sequential模型，而concatenate用于Functional API。