我尝试在Keras 2.0中合并两个连续模型,使用以下行:
merged_model.add(Merge([model1, model2], mode='concat'))
这仍然可以正常工作,但会发出警告:
"The `Merge` layer is deprecated and will be removed after 08/2017. Use
instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc."
然而,研究Keras文档并尝试add,add(),并没有产生什么效果。我读了一些来自有同样问题的人的帖子,但是没有找到在我下面的案例中有效的解决方案。有什么建议吗?
model = Sequential()
model1 = Sequential()
model1.add(Dense(300, input_dim=40, activation='relu', name='layer_1'))
model2 = Sequential()
model2.add(Dense(300, input_dim=40, activation='relu', name='layer_2'))
merged_model = Sequential()
merged_model.add(Merge([model1, model2], mode='concat'))
merged_model.add(Dense(1, activation='softmax', name='output_layer'))
merged_model.compile(loss='binary_crossentropy', optimizer='adam',
metrics=['accuracy'])
checkpoint = ModelCheckpoint('weights.h5', monitor='val_acc',
save_best_only=True, verbose=2)
early_stopping = EarlyStopping(monitor="val_loss", patience=5)
merged_model.fit([x1, x2], y=y, batch_size=384, epochs=200,
verbose=1, validation_split=0.1, shuffle=True,
callbacks=[early_stopping, checkpoint])
编辑:当我尝试时(肯特·索默建议如下):
from keras.layers.merge import concatenate
merged_model.add(concatenate([model1, model2]))
这是错误消息:
Traceback (most recent call last):
File "/anaconda/lib/python3.6/site- packages/keras/engine/topology.py", line 425,
in assert_input_compatibility
K.is_keras_tensor(x)
File "/anaconda/lib/python3.6/site-
packages/keras/backend/tensorflow_backend.py", line 403, in is_keras_tensor
raise ValueError('Unexpectedly found an instance of type `' +
str(type(x)) + '`. '
ValueError: Unexpectedly found an instance of type
`<class'keras.models.Sequential'>`. Expected a symbolic tensor instance.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "quoradeeptest_simple1.py", line 78, in <module>
merged_model.add(concatenate([model1, model2]))
File "/anaconda/lib/python3.6/site-packages/keras/layers/merge.py",
line 600, in concatenate return Concatenate(axis=axis, **kwargs)(inputs)
File "/anaconda/lib/python3.6/site- packages/keras/engine/topology.py",
line 558, in __call__self.assert_input_compatibility(inputs)
File "/anaconda/lib/python3.6/site-packages/keras/engine/topology.py", line 431,
in assert_input_compatibility str(inputs) + '.All inputs to the layer '
ValueError: Layer concatenate_1 was called with an input that isn't a
symbolic tensor. Received type: <class 'keras.models.Sequential'>.
Full input: [<keras.models.Sequential object at 0x140fa7ba8>,
<keras.models.Sequential object at 0x140fabdd8>]. All inputs to the
layer should be tensors.
使用keras==2.2.4和tensorflow==1.13.1尝试此演示:
除非您有充分的理由保持模型分离,否则您可以(而且应该)在单个模型中具有相同的拓扑。类似于:
警告的意思是,不同的模式现在已经被分割成各自的层,而不是使用带有特定模式的合并层。
所以
Merge(mode='concat')
现在是concatenate(axis=-1)
。但是,由于要合并模型而不是图层,因此这在您的情况下不起作用。您需要做的是使用函数模型,因为基本顺序模型类型不再支持此行为。
在您的情况下,这意味着代码应该更改为以下内容:
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