fixes hardcoded "cuda" device references in unit tests to use a dynamic device selection

[kalyank007]

fixes hardcoded "cuda" device references in unit tests to use a dynamic device selection function instead. This change improves test portability across different hardware backends (e.g., CUDA, XPU, ROCm, CPU).

Key changes:
Replaced all hardcoded "cuda" string literals with get_device() function calls, Applied changes to two test methods: test_build_unified_kv_indices and _test_extend_attention_unified_vs_regular_once

[gemini-code-assist]

Summary of Changes

Hello @kalyank007, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request improves the robustness and portability of unit tests by eliminating hardcoded "cuda" device references. By dynamically selecting the appropriate device, the tests can now run seamlessly on diverse hardware backends, ensuring broader compatibility and reducing maintenance overhead for different computing environments.

Highlights

• Dynamic Device Selection: Replaced hardcoded "cuda" device references in unit tests with a dynamic get_device() function call.
• Improved Test Portability: Enhances the portability of unit tests across various hardware backends like CUDA, XPU, ROCm, and CPU.
• Affected Test Methods: Changes were applied to test_build_unified_kv_indices and _test_extend_attention_unified_vs_regular_once methods.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[gemini-code-assist]

Code Review

This pull request is a good step towards making the unit tests device-agnostic by replacing hardcoded "cuda" strings with dynamic device selection.

However, the implementation is incomplete. The changes are only applied to _test_extend_attention_unified_vs_regular_once and test_build_unified_kv_indices, but many other test methods in test/srt/test_triton_attention_kernels.py still have hardcoded "cuda" device references. To fully achieve the goal of this PR, I recommend updating the following methods as well:

• _test_extend_attention_once
• _test_extend_attention_sliding_window_once
• _test_context_attention_once
• _test_decode_attention_once
• _test_grouped_decode_attention_once

Most importantly, the current changes introduce a NameError because the get_device function is used without being imported. I've added a specific comment pointing out where this needs to be fixed.

[kalyank007]

Code Review

This pull request is a good step towards making the unit tests device-agnostic by replacing hardcoded "cuda" strings with dynamic device selection.

However, the implementation is incomplete. The changes are only applied to _test_extend_attention_unified_vs_regular_once and test_build_unified_kv_indices, but many other test methods in test/srt/test_triton_attention_kernels.py still have hardcoded "cuda" device references. To fully achieve the goal of this PR, I recommend updating the following methods as well:

• _test_extend_attention_once
• _test_extend_attention_sliding_window_once
• _test_context_attention_once
• _test_decode_attention_once
• _test_grouped_decode_attention_once

Most importantly, the current changes introduce a NameError because the get_device function is used without being imported. I've added a specific comment pointing out where this needs to be fixed.

resolved