Add PyTorch integration test to Kineto CI workflow with multi-backend support

[sraikund16]

Summary: Enhance the libkineto CI workflow to build PyTorch from source with the PR's Kineto changes and run test/test_profiler.py across multiple hardware backends (CUDA and ROCm). This ensures Kineto changes are validated in the full PyTorch context before merging, catching integration issues early. The workflow uses a matrix strategy to test on both NVIDIA GPUs (A10G) and AMD ROCm GPUs, clones PyTorch, replaces its bundled Kineto submodule with the PR version via symlink, compiles PyTorch with the appropriate backend flags, and runs the profiler tests.

Differential Revision: D88681772

[meta-codesync]

@sraikund16 has exported this pull request. If you are a Meta employee, you can view the originating Diff in D88681772.

[meta-cla]

Hi @sraikund16!

Thank you for your pull request.

We require contributors to sign our Contributor License Agreement, and yours needs attention.

You currently have a record in our system, but the CLA is no longer valid, and will need to be resubmitted.

Process

In order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA.

Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with CLA signed. The tagging process may take up to 1 hour after signing. Please give it that time before contacting us about it.

If you have received this in error or have any questions, please contact us at cla@meta.com. Thanks!