我有一个正常工作的网络如下：

output = LSTM(8)(output)output = Dense(2)(output)

现在对于同一模型，我尝试像下面这样堆叠几个LSTM层：

output = LSTM(8)(output, return_sequences=True)output = LSTM(8)(output)output = Dense(2)(output)

但我遇到了以下错误：

TypeError                                 Traceback (most recent call last)<ipython-input-2-0d0ced2c7417> in <module>()     39      40 output = Concatenate(axis=2)([leftOutput,rightOutput])---> 41 output = LSTM(8)(output, return_sequences=True)     42 output = LSTM(8)(output)     43 output = Dense(2)(output)/usr/local/lib/python3.4/dist-packages/keras/layers/recurrent.py in __call__(self, inputs, initial_state, constants, **kwargs)    480     481         if initial_state is None and constants is None:--> 482             return super(RNN, self).__call__(inputs, **kwargs)    483     484         # If any of `initial_state` or `constants` are specified and are Keras/usr/local/lib/python3.4/dist-packages/keras/engine/topology.py in __call__(self, inputs, **kwargs)    601     602             # Actually call the layer, collecting output(s), mask(s), and shape(s).--> 603             output = self.call(inputs, **kwargs)    604             output_mask = self.compute_mask(inputs, previous_mask)    605 TypeError: call() got an unexpected keyword argument 'return_sequences'

这很令人困惑，因为根据Keras文档，return_sequences是一个有效的参数：https://keras.io/layers/recurrent/#lstm

我在这里做错了什么？谢谢！

回答：

问题在于return_sequences应该作为参数传递给层构造函数，而不是层调用。将代码更改为：

output = LSTM(8, return_sequences=True)(output)

解决了这个问题。