model = Sequential()
model.add(Flatten(input_shape=(1,) + (52,)))
model.add(Dense(100))
model.add(Activation('relu'))
model.add(Dense(2))
model.add(Activation('linear'))
print(model.summary())
我想改变这个keras代码在顺序版本相同的代码与功能版本如下。
input = Input(shape=(1,) + (52,))
i = Flatten()(input)
h = Dense(100, activation='relu')(i)
o = Dense(2, activation='linear')(h)
model = Model(inputs=i, outputs=o)
model.summary()
但它出错了
File "C:\Users\SDS\Anaconda3\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "C:\Users\SDS\Anaconda3\lib\site-packages\keras\engine\network.py", line 93, in __init__
self._init_graph_network(*args, **kwargs)
File "C:\Users\SDS\Anaconda3\lib\site-packages\keras\engine\network.py", line 237, in _init_graph_network
self.inputs, self.outputs)
File "C:\Users\SDS\Anaconda3\lib\site-packages\keras\engine\network.py", line 1430, in _map_graph_network
str(layers_with_complete_input))
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_1:0", shape=(?, 1, 52), dtype=float32) at layer "input_1". The following previous layers were accessed without issue: []
2条答案
按热度按时间j1dl9f461#
您的模型定义不正确,模型的输入参数应转到您的输入层,如下所示:
我相信您不能将输入层以外的任何Tensor作为模型的输入。
tpxzln5u2#
模型的输入应该是输入层(没有任何密集层的第一层),因此应该是:
型号=型号(输入=输入,输出=o)