context) here.
You can check the archs pytorch was built with using:
bash
python -c "import torch; print(torch.cuda.get_arch_list())"
Here is how to find out the arch for one of the installed GPU. For example, for GPU 0:
bash
CUDA_VISIBLE_DEVICES=0 python -c "import torch; \
print(torch.cuda.get_device_properties(torch.device('cuda')))"
If the output is:
bash
_CudaDeviceProperties(name='GeForce RTX 3090', major=8, minor=6, total_memory=24268MB, multi_processor_count=82)
then you know that this card's arch is 8.6.
You can also leave TORCH_CUDA_ARCH_LIST out completely and then the build program will automatically query the
architecture of the GPUs the build is made on. This may or may not match the GPUs on the target machines, that's why
it's best to specify the desired archs explicitly.
If after trying everything suggested you still encounter build issues, please, proceed with the GitHub Issue of
