feat(runtimes): add AMD ROCm torch distributed runtime ref #2335

[JEETDESAI25]

What this PR does / why we need it:

Adds AMD ROCm PyTorch distributed training runtime, enabling distributed training on AMD GPUs (e.g., MI300X accelerators).
This follows the same pattern as the existing NVIDIA torch runtime added in #2328, using the official rocm/pytorch image with a pinned version matching the PyTorch version used in the NVIDIA runtime (2.7.1).

Which issue(s) this PR fixes :

#2335

Checklist:

• [ ] Docs included if any changes are user facing

[google-oss-prow]

[APPROVALNOTIFIER] This PR is NOT APPROVED

This pull-request has been approved by:
Once this PR has been reviewed and has the lgtm label, please assign andreyvelich for approval. For more information see the Kubernetes Code Review Process.

The full list of commands accepted by this bot can be found here.

Details

Needs approval from an approver in each of these files:

• OWNERS

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

[github-actions]

🎉 Welcome to the Kubeflow Trainer! 🎉

Thanks for opening your first PR! We're happy to have you as part of our community 🚀

Here's what happens next:

• If you haven't already, please check out our Contributing Guide for repo-specific guidelines and the Kubeflow Contributor Guide for general community standards.
• Our team will review your PR soon! cc @kubeflow/kubeflow-trainer-team

Join the community:

• Slack: Join our #kubeflow-trainer Slack channel.
• Meetings: Attend the Kubeflow AutoML and Training Working Group bi-weekly meetings.

Feel free to ask questions in the comments if you need any help or clarification!
Thanks again for contributing to Kubeflow! 🙏

[JEETDESAI25]

/assign @andreyvelich