Functional API中的Keras Flatten层是什么？

Question

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())

我希望你能将这个 keras 代码从顺序版本更改为功能版本，就像以下代码一样。

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()

但是它出现了错误。

  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: []

- verystrongjoe

Answer 1

您的模型定义有误，Model的输入参数应该传递到您的Input层，像这样：

input = Input(shape=(1,) + (52,))
i = Flatten()(input)
h = Dense(100, activation='relu')(i)
o = Dense(2, activation='linear')(h)
model = Model(inputs=inputs, outputs=o)

我相信在模型中，你不能将除了输入层以外的张量作为输入。

- Dr. Snoopy

Answer 2

模型的输入应该是输入层（第一层没有任何密集层）。

因此，它应该像这样：

model = Model(inputs=input, outputs=o)

- DANISH REZA