问题
I have used an AWS p3 instance to train the following model using GPU acceleration:
x = CuDNNLSTM(128, return_sequences=True)(inputs)
x = Dropout(0.2)(x)
x = CuDNNLSTM(128, return_sequences=False)(x)
x = Dropout(0.2)(x)
predictions = Dense(1, activation='tanh')(x)
model = Model(inputs=inputs, outputs=predictions)
After training I saved the model with Keras' save_model function and moved it to a separate production server that doesn't have a GPU.
When I attempt to predict using the model on the production server it fails with the following error:
No OpKernel was registered to support Op 'CudnnRNN' with these attrs. Registered devices: [CPU], Registered kernels:
I'm guessing this is because the production server doesn't have GPU support, but I was hoping this wouldn't be a problem. Is there any way I can use this model on a production server without a GPU?
回答1:
No, you can't, CuDNN requires the use of a CUDA GPU. You have to replace your CuDNNLSTM layers with standard LSTM ones.
回答2:
try
pip install tensorflow-gpu
来源：https://stackoverflow.com/questions/48086014/keras-model-with-cudnnlstm-layers-doesnt-work-on-production-server