ElectrikVocal_95:

I use CUDA Toolkit 11.1 and the cuDNN of that version. But should I download them or leave them as I have them?


If you’ve already installed a local CUDA toolkit (with cudnn), you can just use it and don’t need to reinstall it.



 ElectrikVocal_95:

And with the compiler what i need do? What do I need to download? (As it says that “or above” version I guess it would be fine, right? )


The CUDA toolkit installs the CUDA compiler (nvcc) and you could check, if it’s working by either compiling the CUDA Samples or checking if it can be found and used via nvcc --version.



 ElectrikVocal_95:

Would I need to disable CUDA Support?


If you want to use the GPU (I assume you want to), you should not disable CUDA support.
Otherwise, you could also install the CPU-only binaries and wouldn’t need to build PyTorch from source.



 ElectrikVocal_95:

From Jetson Nano I guess I don’t need anything…


No, you don’t need to build for Jetson.



 ElectrikVocal_95:

From the ROCm compiler do I need something? or I not need disable nothing?


No, ROCm is used for AMD GPUs.



 ElectrikVocal_95:

If I understood correctly, I should only install this with conda, right?


Yes, you would need some dependencies to build PyTorch from source. If you miss to install a dependency, the installation will yield an error pointing to the missing package.



 ElectrikVocal_95:

is it possible to do this without git? Just downloading the project and running from my terminal?


You might be able to download the repository from GitHub directly, but I’m not sure if this would also download all third-party modules, so I would recommend to use git.