[PROF-8006] Add Pytorch Profiler Integration for GPU Data

[peterg17]

Checklist

• [ ] Change(s) are motivated and described in the PR description.
• [ ] Testing strategy is described if automated tests are not included in the PR.
• [ ] Risk is outlined (performance impact, potential for breakage, maintainability, etc).
• [ ] Change is maintainable (easy to change, telemetry, documentation).
• [ ] Library release note guidelines are followed. If no release note is required, add label changelog/no-changelog.
• [ ] Documentation is included (in-code, generated user docs, public corp docs).
• [ ] Backport labels are set (if applicable)

Reviewer Checklist

• [ ] Title is accurate.
• [ ] No unnecessary changes are introduced.
• [ ] Description motivates each change.
• [ ] Avoids breaking API changes unless absolutely necessary.
• [ ] Testing strategy adequately addresses listed risk(s).
• [ ] Change is maintainable (easy to change, telemetry, documentation).
• [ ] Release note makes sense to a user of the library.
• [ ] Reviewer has explicitly acknowledged and discussed the performance implications of this PR as reported in the benchmarks PR comment.
• [ ] Backport labels are set in a manner that is consistent with the release branch maintenance policy

[pr-commenter[bot]]

Benchmarks

Benchmark execution time: 2023-11-28 18:48:21

Comparing candidate commit 74780872476524778b7ba95ae81028694374e1c3 in PR branch peterg17/pytorch_profiling_integration with baseline commit f75455bb4ec47ed40c57e079259a4bf9af9380e4 in branch 2.x.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 66 metrics, 0 unstable metrics.