Hello,
First, I am no Pytorch user, I only build the wheels for others.
At the moment, I build a CPU and GPU wheel and suffixed them with _cpu
and _gpu
. The drawback is that some users have difficulties installing the torch wheels since many other wheels depends on torch
and not torch_[cg]pu
(e.g. allennlp
, pytorch-pretrained-bert
).
I wonder if I build torch with GPU+CPU support, then if users not using GPUs will encounters issues?
(errors such as : “no cuda capable device found” are ok and acceptable in the context of no GPU device and code not targeted to the CPU.)
I am aware that many GPU operations are encapsulated into torch.cuda
and shielded with torch.cuda.is_available()
.
I did run the Pytorch tests with a torch_gpu
wheel and no GPU device, and most of them succeeded.
What are your thoughts on this? Do you see any caveats/issues?
Thanks