TypeError:如果启用了Tensor相等，则Tensor无法散列.而是使用tensor.experimental_ref()作为键 [英] TypeError: Tensor is unhashable if Tensor equality is enabled. Instead, use tensor.experimental_ref() as the key

问题描述

我试图将转移学习应用于InceptionV3.这是我的代码:

I was trying to apply transfer learning to the InceptionV3. Here is my code:

inception_model = InceptionV3(weights='imagenet',include_top=False)
output_inception = inception_model.output
output_globalavgpooling = GlobalAveragePooling2D()(output_inception)
output_dense = Dense(1024,activation='relu')(output_globalavgpooling)
predictions = Dense(1,activation='sigmoid')(output_dense)

final_model = Model(inception_model.input,output=predictions)

final_model.compile()

inception_model.summary()

运行此代码时，在final_model = Model(inception_model.input,output=predictions)行出现以下错误:

When i run this code I am getting following error at the final_model = Model(inception_model.input,output=predictions) line:

TypeError: Tensor is unhashable if Tensor equality is enabled. Instead, use tensor.experimental_ref() as the key.

我该怎么办?

推荐答案

我有一个类似的错误.就我而言，这是由于使用了conda的Keras和Tensorflow 2的旧版本.当前存在一些问题，无法通过conda在当前的Keras中使用Tensorflow 2.

I had a similar error. In my case it was due to using an old version of Keras and Tensorflow 2 from conda. There currently is some issues preventing the use of Tensorflow 2 with current Keras via conda.

我创建了一个新环境，并根据Keras/Tensorflow网站(在我的情况下为仅CPU版本)进行安装:

I created a new environment and installed using according to the Keras/Tensorflow websites (CPU only version in my case):

pip install tensorflow
pip install keras

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