Hello I am new in pytorch. Now I am trying to run my network in GPU. Some of the articles recommend me to use torch.cuda.set_device(0) as long as my GPU ID is 0. However some articles also tell me to convert all of the computation to Cuda, so every operation should be followed by .cuda() . My questions are:
-) Is there any simple way to set mode of pytorch to GPU, without using .cuda() per instruction?, I just want to set all computation just in 1 GPU.
-) How to check and make sure that our network is running on GPU?, when I am using torch.cuda.set_device(0), I checked using nvidia-smi and I got 0% in volatile GPU. It is different when I am using Tensorflow or caffe which more than 10%. I am affraid that my pytorch still using CPU.
-Thank you-