I have a Dockerfile which installs PyTorch library from the source code.
Here is the snippet from Dockerfile which performs the installation from source code of pytorch
RUN cd /tmp/ && git clone https://github.com/pytorch/pytorch.git && cd pytorch && git submodule sync && git submodule update --init --recursive && sudo TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0" python3 setup.py install
I don’t have proper understanding of what’s happening here and would appreciate some input from the community:
- Why does PyTorch need different way of installation for different CUDA versions?
- What is the role of
TORCH_CUDA_ARCH_LISTin this context?
- If my machine has multiple CUDA setups, does that mean I will have multiple PyTorch versions (specific to each CUDA setup) installed in my Docker container?
- If my machine has none of the mentioned CUDA setups ("6.0 6.1 7.0 7.5 8.0"), will the PyTorch installation fail?
Source: Docker Questions