[PyTorch] Fix cuBLAS workspace leak in applications that initialize+destroy Userbuffers more than once

[denera]

Description

In cases where initialize_ub()+destroy_ub() pairs are called more than once (e.g. in-process restarts), the cuBLAS workspace allocation is mishandled and grows exponentially. This PR safeguards the workspace expansion in initialize_ub() to avoid this leak.

Type of change

• [ ] Documentation change (change only to the documentation, either a fix or a new content)
• [x] Bug fix (non-breaking change which fixes an issue)
• [ ] New feature (non-breaking change which adds functionality)
• [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
• [ ] Infra/Build change
• [ ] Code refactoring

Checklist:

• [x] I have read and followed the contributing guidelines
• [x] The functionality is complete
• [x] I have commented my code, particularly in hard-to-understand areas
• [x] I have made corresponding changes to the documentation
• [x] My changes generate no new warnings
• [ ] I have added tests that prove my fix is effective or that my feature works
• [x] New and existing unit tests pass locally with my changes

[denera]

/te-ci pytorch L0 L1

[ksivaman]

Confirmed offline that this fixes the issue of GPU memory not being reclaimed after user buffer cleanup (destroy_ub).

[ksivaman]

Pipeline 27525544