change model from gpu to cpu
fanlamda opened this issue · comments
I wish to train the model on GPU，but predict with cpu，so I tried using cudnn.convert(self.model, nn). But it seems something in the model remains Cuda form.
Is there any method to solve this problem? Any advice is welcome.
In order to switch back to CPU mode you would also need to call self.model:float() as well as cudnn.convert(self.model, nn).
Yes，I used self.model:float() After cudnn.convert(), but I found cudnn.batchBRNNReLU remains unchanged. It comes error like 'unknown object cudnn.batchBRNNReLU'
Ah this is my fault there is no CPU version of cudnn.BatchBRNNReLU. I'll have to modify the DeepSpeechModel class to take this into consideration; the alternative is to use the rnn package seqBRNN which will allow conversion, which will involve having to train a new model
I'm training a smaller model on AN4 that is CPU based (but training on GPU with a few hacks). Will add this to the pre-trained networks once finished.
I dont have a gpu , I am still learning , Is there any small pretrained model that will work with only cpu(core i5 of my laptop and raspberry pi 3 ? )