Prebuilt wheels provided via 3rd party repository

## Prebuilt wheels for PyTorch packages with custom ops

I've created a repository that can build PyTorch wheels with custom ops through the GitHub Actions pipeline and publish them using GitHub Releases. Check it out at https://github.com/MiroPsota/torch_packages_builder.

Since there are various ways how to use it, please refer to the repository README for more information.

If you prefer own build or can't trust a 3rd party repository, feel free to fork it and build any package/version/commit ID you desire yourself.

- **No Support for Pip Cache**: pip relies on http cache, and GitHub generates on-the-fly redirections for release links, so they are probably not playing nicely together. I recommend hosting it yourself.

### SAM_2 specific info:

Install using pip:
```
pip install --extra-index-url https://miropsota.github.io/torch_packages_builder SAM_2==+pt
```
Where `` is, as in PyTorch, one of `cpu`, `cu` (e.g. `cu121`, `cu118`, `cu102`), or `rocm` (not supported right now).

For example, the newest sam_2 commit (as of writing) `c2ec8e1`, PyTorch 2.6.0 with CUDA 12.6:
```
pip install --extra-index-url https://miropsota.github.io/torch_packages_builder SAM_2==1.0+c2ec8e1pt2.6.0cu12.6
```
Look at releases section if there are any other combinations, I will probably build occasionally with new pytorch releases and versions/commits.

These wheels are built with PyTorch versions `2.3.1` to `2.6.0` and their respective compute platforms and supported operating systems. Please note an exception for cu102 on Windows (due to no VS 2017 on the GitHub `windows-2019` runner) and the ROCm platform. The build is done using the available public GitHub runners, so they might not work on older OSes.

Although the wheels have been successfully built, I don't test them to work correctly.

If you've installed PyTorch with pip, there's no need to have CUDA installed on your system, as the PyTorch wheels for pip bundle CUDA.