Yes, I was able to run the matrixMul cuda sample:

[Matrix Multiply Using CUDA] - Starting…
GPU Device 0: “Turing” with compute capability 7.5
MatrixA(320,320), MatrixB(640,320)
Computing result using CUDA Kernel…
done
Performance= 70.49 GFlop/s, Time= 1.859 msec, Size= 131072000 Ops, WorkgroupSize= 1024 threads/block
Checking computed result for correctness: Result = PASS
NOTE: The CUDA Samples are not meant for performancemeasurements. Results may vary when GPU Boost is enabled.
C:\ProgramData\NVIDIA Corporation\CUDA Samples\v11.2\0_Simple\matrixMul…/…/bin/win64/Debug/matrixMul.exe (process 14432) exited with code 0.

Unfortunately I can’t test pytorch from a container because this would imply setting up cuda on WSL and for this I need to use the windows preview builds, which I don’t want to do because this is my main machine.
Related to the conda or pip binaries, yes, I have tried them and it’s working but there is a problem there also. Using the prebuild binaries, every time I execute the first instruction on GPU, it takes around 15 minutes to execute it. After that, every succeeding instructions on the same python kernel are execute instantly. This is one of the reasons for which I want to try installing from source.
Appreciate your effort in helping me with this.