keras model prediction is nan after saving and loading

Question

I trained a neural network with google colab.
I saved the neural network using joblib.dump()

I then loaded the model on my PC using joblib.load()

I made a prediction on the exact same sample, using the same model, on both colab and my PC. On colab, it has an output of [[0.51]] . On my pc, it has an output of [[nan]] .

The model summary reports that the architecture of the model is the same. I checked the weights of the model I loaded on my PC, and the model on colab, and the weights are the exact same.

Any ideas as to what I can do? Thank you.

Quick update: even if I change all of my inputs to zero, the prediction is still nan.

Answer 1

据我所知keras有自己的保存模型的功能比如model.save('file.h5') ，使用joblib库来保存sklearn模型。