当我运行以下代码(来自this IPython notebook)时,出现错误:
import theano
def get_submodel(model, start, end):
return theano.function([model.layers[start].input],
model.layers[end].get_output(train=False),
allow_input_downcast=True)
def get_encoder(ae):
return get_submodel(ae, 0, (len(ae.layers) // 2) - 1)
ae_encoder = get_encoder(ae)
这是错误消息:
Traceback (most recent call last):
File "Parametric t-SNE (Keras).py", line 432, in <module>
ae_encoder = get_encoder(ae)
File "Parametric t-SNE (Keras).py", line 424, in get_encoder
return get_submodel(ae, 0, (len(ae.layers) // 2) - 1)
File "Parametric t-SNE (Keras).py", line 422, in get_submodel
allow_input_downcast=True)
File "/usr/lib64/python3.4/site-packages/theano/compile/function.py", line 326, in function
output_keys=output_keys)
File "/usr/lib64/python3.4/site-packages/theano/compile/pfunc.py", line 397, in pfunc
for p in params]
File "/usr/lib64/python3.4/site-packages/theano/compile/pfunc.py", line 397, in <listcomp>
for p in params]
File "/usr/lib64/python3.4/site-packages/theano/compile/pfunc.py", line 496, in _pfunc_param_to_in
raise TypeError('Unknown parameter type: %s' % type(param))
TypeError: Unknown parameter type: <class 'tensorflow.python.framework.ops.Tensor'>
供参考,这里定义了ae
:
n = X_train.shape[1]
ae = Sequential()
ae.add(Dense(500, activation='relu', weights=encoder.layers[0].get_weights(), input_shape=(n,)))
ae.add(Dense(500, activation='relu', weights=encoder.layers[1].get_weights()))
ae.add(Dense(2000, activation='relu', weights=encoder.layers[2].get_weights()))
ae.add(Dense(2, weights=encoder.layers[3].get_weights()))
ae.add(Dense(2000, activation='relu', weights=decoder.layers[0].get_weights()))
ae.add(Dense(500, activation='relu', weights=decoder.layers[1].get_weights()))
ae.add(Dense(500, activation='relu', weights=decoder.layers[2].get_weights()))
ae.add(Dense(n, weights=decoder.layers[3].get_weights()))
ae.compile(loss='mse', optimizer='rmsprop')
ae.fit(X_train, X_train, nb_epoch=100, verbose=2, batch_size=32)
基于对a similar question的回答,我怀疑get_submodel
可能需要修改为使用符号变量而不是张量/矩阵。但是,我不知道如何做到这一点,以及为什么它甚至会出错,因为GitHub上的IPython笔记本似乎没有包含任何错误消息。我无法找到有关tensorflow.python.framework.ops.Tensor
错误消息的更具体建议。
答案 0 :(得分:1)
您似乎有一个tensorflow
后端 - 而不是theano
后端。这就是使用theano.function
生成错误的原因。尝试使用keras.backend.function
。