I have GT 710. It has compute capability of 3.5. This means that if I want to use PyTorch with a GPU, I have to build PyTorch from source.
I have already made several attempts but unsuccessfully. I didn’t expect the build process to take hours, in addition CPU is 100% busy. I work on Windows and this makes the installation process even more complicated. I have a few questions and would like to have some answers before I proceed to the next attempt.
I use Unity mlagents toolkit. It requires pytorch >=1.6.0,<1.9.0. I chose the minimum configuration (pytorch 1.6, CUDA 9.2, cuDNN v7) to ease the build process.
Question 1: Is it justified to use the minimal configuration?
I found the pytorch 1.6 repository at https://github.com/pytorch/pytorch/tree/release/1.6 3 but I’m not sure if this is correct.
Question 2: Where should I look for pytorch repositories of different versions?
I have Visual Studio 2019 16.11.7 and I can’t install toolset 14.11. The instructions say:
“There is no guarantee of the correct building with VC++ 2017 toolsets, others than version 15.4 v14.11.”
Does this apply to Studio 2019?
Question 3: Can I use Visual Studio 2019 to build?
I do not see how I can specify the desired compute capability. May be

set TORCH_CUDA_ARCH_LIST=“3.5”

Question 4: How do I specify the desired compute capability?
Let’s say I built the pytorch binaries successfully. Where are these binaries located? How do I install these binaries?
Question 5: How do I install new pytorch binaries?