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  • Bug Fix
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  • More Models or Datasets Support

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Summary of Changes

Hello @tastelikefeet, 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 compatibility and configuration for PPU (presumably a specific type of processing unit) environments. It introduces a mechanism to detect PPU hardware and apply necessary environment variable adjustments to ensure proper single-device execution. Furthermore, it explicitly disables multi-processing features when a PPU is detected, streamlining the setup and preventing potential conflicts in such specialized environments.

Highlights

  • PPU Detection and Configuration: Introduced is_ppu() and fix_ppu() utilities to detect PPU environments and adjust CUDA_VISIBLE_DEVICES and LOCAL_RANK for single-device operation.
  • CLI Integration: The fix_ppu() function is now called at the start of pt.py, rlhf.py, and sft.py CLI scripts to ensure PPU-specific environment setup.
  • Multi-processing Compatibility: Modified the is_mp() function to explicitly disable multi-processing when running in a PPU environment, ensuring compatibility and preventing potential issues.
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Code Review

This pull request introduces a fix for PPU environments by adjusting CUDA_VISIBLE_DEVICES and LOCAL_RANK at script startup. The overall approach is sound, but there are several areas for improvement regarding code robustness and maintainability. I've identified duplicated code that should be consolidated and a lack of error handling around external process calls and environment variable access, which could lead to unexpected crashes. My review comments provide specific suggestions to address these issues.

@tastelikefeet tastelikefeet merged commit 2a07f0a into modelscope:main Nov 10, 2025
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2 participants