Fix LLaMA3 training resolve device string maca error

[whollo]

Fix: resolve maca device string error during LLaMA3 training

[gemini-code-assist]

Summary of Changes

Hello @whollo, 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 issue that was preventing LLaMA3 training by fixing an incorrect device string assignment within the flagcxBackend implementation. The change ensures that when the USE_METAX_ADAPTOR is used, the system correctly identifies the device as "cuda" instead of "maca", thus resolving device recognition errors. Additionally, a minor formatting inconsistency was resolved by adding a newline at the end of the file.

Highlights

• Device String Correction: Corrected the device string from "maca" to "cuda" when the USE_METAX_ADAPTOR preprocessor directive is active. This resolves an error encountered during LLaMA3 training.
• File Formatting: Added a missing newline character at the end of the backend_flagcx.hpp file.

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[gemini-code-assist]

Code Review

This pull request addresses an error during LLaMA3 training on MetaX (maca) devices by correcting the device string reported to PyTorch. The change from "maca" to "cuda" aligns with how PyTorch recognizes CUDA-compatible devices, resolving the issue. The fix is appropriate. I have added one suggestion to include a comment explaining this mapping for better code maintainability.

[MC952-arch]

LGTM

[yuejiewang]

LGTM