在 keras 中将连接输入传递给 LSTM 的问题

2024-06-03 • 问答

我有几个神经网络。它们的输出被连接起来，然后传递给 LSTM。

这是一个简化的代码片段：

import keras.backend as K

from keras.layers import Input,Dense,LSTM,concatenate
from keras.models import Model

# 1st NN
input_l1 = Input(shape=(1,))
out_l1 = Dense(1)(input_l1)

# 2nd NN
input_l2 = Input(shape=(1,))
out_l2 = Dense(1)(input_l2)

# concatenated layer
concat_vec = concatenate([out_l1,out_l2])

# expand dimensions to (None,2,1)
expanded_concat = K.expand_dims(concat_vec,axis=2)

lstm_out = LSTM(10)(expanded_concat)

model = keras.Model(inputs=[input_l1,input_l2],outputs=lstm_out)

不幸的是，我在最后一行出现错误：

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-53-a16fe60c0fc3> in <module>
      2 lstm_out = LSTM(10)(expanded_concat)
      3 
----> 4 model = keras.Model(inputs=[input_l1,outputs=lstm_out)

/usr/local/lib/python3.9/site-packages/keras/legacy/interfaces.py in wrapper(*args,**kwargs)
     89                 warnings.warn('Update your `' + object_name + '` call to the ' +
     90                               'Keras 2 API: ' + signature,stacklevel=2)
---> 91             return func(*args,**kwargs)
     92         wrapper._original_function = func
     93         return wrapper

/usr/local/lib/python3.9/site-packages/keras/engine/network.py in __init__(self,*args,**kwargs)
     91                 'inputs' in kwargs and 'outputs' in kwargs):
     92             # Graph network
---> 93             self._init_graph_network(*args,**kwargs)
     94         else:
     95             # Subclassed network

/usr/local/lib/python3.9/site-packages/keras/engine/network.py in _init_graph_network(self,inputs,outputs,name)
    228 
    229         # Keep track of the network's nodes and layers.
--> 230         nodes,nodes_by_depth,layers,layers_by_depth = _map_graph_network(
    231             self.inputs,self.outputs)
    232         self._network_nodes = nodes

/usr/local/lib/python3.9/site-packages/keras/engine/network.py in _map_graph_network(inputs,outputs)
   1361     for x in outputs:
   1362         layer,node_index,tensor_index = x._keras_history
-> 1363         build_map(x,finished_nodes,nodes_in_progress,1364                   layer=layer,1365                   node_index=node_index,/usr/local/lib/python3.9/site-packages/keras/engine/network.py in build_map(tensor,layer,tensor_index)
   1350             node_index = node.node_indices[i]
   1351             tensor_index = node.tensor_indices[i]
-> 1352             build_map(x,1353                       node_index,tensor_index)
   1354 

/usr/local/lib/python3.9/site-packages/keras/engine/network.py in build_map(tensor,tensor_index)
   1323             ValueError: if a cycle is detected.
   1324         """
-> 1325         node = layer._inbound_nodes[node_index]
   1326 
   1327         # Prevent cycles.

AttributeError: 'NoneType' object has no attribute '_inbound_nodes'

有办法解决吗？如果重要的话，我使用 PlaidML 后端作为支持独立 GPU 的 macOS 的唯一选择。

import tensorflow as tf from tensorflow.keras.layers import Input,Dense,LSTM,concatenate from tensorflow.keras.models import Model # 1st NN input_l1 = Input(shape=(1,)) out_l1 = Dense(1)(input_l1) # 2nd NN input_l2 = Input(shape=(1,)) out_l2 = Dense(1)(input_l2) # concatenated layer concat_vec = concatenate([out_l1,out_l2]) # expand dimensions to (None,2,1) expanded_concat = tf.keras.layers.Reshape((2,1))(concat_vec) #expanded_concat = K.expand_dims(concat_vec,axis=2) lstm_out = LSTM(10)(expanded_concat) model = Model(inputs=[input_l1,input_l2],outputs=lstm_out) model.summary()

Model: "model" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1 (InputLayer) [(None,1)] 0 __________________________________________________________________________________________________ input_2 (InputLayer) [(None,1)] 0 __________________________________________________________________________________________________ dense (Dense) (None,1) 2 input_1[0][0] __________________________________________________________________________________________________ dense_1 (Dense) (None,1) 2 input_2[0][0] __________________________________________________________________________________________________ concatenate (Concatenate) (None,2) 0 dense[0][0] dense_1[0][0] __________________________________________________________________________________________________ reshape_1 (Reshape) (None,1) 0 concatenate[0][0] __________________________________________________________________________________________________ lstm (LSTM) (None,10) 480 reshape_1[0][0] ================================================================================================== Total params: 484 Trainable params: 484 Non-trainable params: 0 __________________________________________________________________________________________________

在 keras 中将连接输入传递给 LSTM 的问题

imauzhw 回答：在 keras 中将连接输入传递给 LSTM 的问题

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