[Ray] v1 Change device str for platform compatibility

[1StepForever]

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

Change the "GPU" str to platform device key.
When using ray to create placement groups, there is a key error for other platforms. So fix it with platform abstraction.
image

Test Plan

No test needed

Test Result

(Optional) Documentation Update

[github-actions]

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[gemini-code-assist]

Summary of Changes

Hello @1StepForever, 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 addresses a critical platform compatibility issue within the Ray placement group creation logic. By abstracting the device resource key, it ensures that resource allocation correctly identifies and utilizes available hardware, moving away from a GPU-specific assumption to a more generalized approach suitable for diverse computing environments.

Highlights

• Platform Compatibility: This PR enhances platform compatibility by replacing the hardcoded 'GPU' string with a dynamic device_key when creating Ray placement groups. This resolves key errors encountered on platforms that do not use 'GPU' as their device identifier.
• Resource Abstraction: Introduced an abstraction layer by importing current_platform from vllm.platforms to retrieve the appropriate ray_device_key. This makes the resource allocation logic more generic and adaptable to different hardware configurations.

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[gemini-code-assist]

Code Review

This PR addresses an important compatibility issue by abstracting the device key for Ray placement groups. The use of current_platform.ray_device_key is a good step towards platform independence.

One area for improvement is the test plan. The PR description states "No test needed". However, for changes impacting platform compatibility, it's crucial to have some form of verification. This could involve:

• Manual testing on different target platforms (e.g., CUDA, ROCm if applicable) to confirm the fix works and no regressions are introduced.
• Adding a unit test that checks the value of current_platform.ray_device_key for mocked or common platforms.
• An integration test that verifies placement group creation with the new dynamic key.

Without testing, it's harder to be confident that this change behaves correctly across all intended environments and won't cause issues in the future. Please consider adding details about how this change was verified or a plan for testing it.

Additionally, please ensure the PR description checklist items like 'Test Results' are filled if any manual or automated tests are performed.

[gemini-code-assist]

According to PEP 8, imports like from vllm.platforms import current_platform should generally be placed at the top of the file. This improves code readability and organization.

Since vllm.platforms.current_platform appears to be lazily initialized (via __getattr__ in vllm/platforms/__init__.py), moving this import to the top-level imports of vllm/v1/utils.py should be safe and is the standard practice.

After moving the import, current_platform.ray_device_key (as used on the next line) will correctly access the top-level import.

Suggested change

	from vllm.platforms import current_platform
	device_key = current_platform.ray_device_key
	# The import 'from vllm.platforms import current_platform' should be moved to the top of this file.
	device_key = current_platform.ray_device_key # This line now relies on the top-level import.