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我查找了所有"'Tensor'对象没有属性***"但似乎没有任何与Keras有关(除了TensorFlow:AttributeError:'Tensor'对象没有属性'log10'没有帮助)...

我正在制作一种GAN(Generative Adversarial Networks).在这里你可以找到结构.

Layer (type)                     Output Shape          Param #         Connected to                     
_____________________________________________________________________________
input_1 (InputLayer)             (None, 30, 91)        0                                            
_____________________________________________________________________________
model_1 (Model)                  (None, 30, 1)         12558           input_1[0][0]                    
_____________________________________________________________________________
model_2 (Model)                  (None, 30, 91)        99889           input_1[0][0]                    
                                                                       model_1[1][0]                    
_____________________________________________________________________________
model_3 (Model)                  (None, 1)             456637          model_2[1][0]                    
_____________________________________________________________________________

我预先训练了model_2和model_3.事情是我预先训练了model_2,列表由0和1组成,但是model_1返回了接近的值.所以我考虑使用以下代码舍入model1_output:model1_out上的K.round().

import keras.backend as K
[...]
def make_gan(GAN_in, model1, model2, model3):
    model1_out = model1(GAN_in)
    model2_out = model2([GAN_in, K.round(model1_out)])
    GAN_out = model3(model2_out)
    GAN = Model(GAN_in, GAN_out)
    GAN.compile(loss=loss, optimizer=model1.optimizer, metrics=['binary_accuracy'])
    return GAN
[...]

我有以下错误:

AttributeError:'Tensor'对象没有属性'_keras_history'

完全追溯: …