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feat(pt): support CPU parallel training with PT #4224

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merged 3 commits into from
Oct 23, 2024

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@iProzd iProzd commented Oct 16, 2024

Fix #4132.

Summary by CodeRabbit

  • New Features

    • Enhanced backend selection for distributed training, allowing for flexible use of NCCL or Gloo based on availability.
  • Bug Fixes

    • Corrected indentation for improved code clarity.

@iProzd iProzd linked an issue Oct 16, 2024 that may be closed by this pull request
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coderabbitai bot commented Oct 16, 2024

📝 Walkthrough
📝 Walkthrough

Walkthrough

The changes in this pull request focus on the get_trainer function in deepmd/pt/entrypoints/main.py, enhancing the initialization of the distributed process group by implementing a flexible backend selection process. The new logic checks for the availability of both NCCL and Gloo backends, initializing the process group with a combined backend string. The local_rank variable's indentation has been corrected, and the control flow for invoking the prepare_trainer_input_single function has been clarified. The overall structure of the train function remains unchanged.

Changes

File Change Summary
deepmd/pt/entrypoints/main.py Modified get_trainer function for flexible backend selection (NCCL or Gloo); corrected indentation of local_rank assignment; clarified control flow for invoking prepare_trainer_input_single.

Assessment against linked issues

Objective Addressed Explanation
Support CPU parallel training with PT (#4132)

Possibly related PRs

  • feat(pt): support DeepEval.eval_descriptor #4214: The changes in the DeepEval class may relate to the overall training and evaluation process, which could be impacted by the modifications in the get_trainer function regarding backend initialization for distributed training.
  • fix(pt): make PT training step idx consistent with TF #4221: The adjustments to the training step index in the Trainer class could be relevant as they may affect how training progress is logged and displayed, which is part of the broader training framework that the get_trainer function is involved in.

Suggested reviewers

  • wanghan-iapcm

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📥 Commits

Files that changed from the base of the PR and between 0b0d943 and f9b43e8.

📒 Files selected for processing (1)
  • deepmd/pt/entrypoints/main.py (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
  • deepmd/pt/entrypoints/main.py

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Actionable comments posted: 1

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

📥 Commits

Files that changed from the base of the PR and between 5050f61 and 0b0d943.

📒 Files selected for processing (1)
  • deepmd/pt/entrypoints/main.py (1 hunks)
🧰 Additional context used

deepmd/pt/entrypoints/main.py Outdated Show resolved Hide resolved
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codecov bot commented Oct 16, 2024

Codecov Report

Attention: Patch coverage is 0% with 1 line in your changes missing coverage. Please review.

Project coverage is 84.54%. Comparing base (5050f61) to head (f9b43e8).
Report is 13 commits behind head on devel.

Files with missing lines Patch % Lines
deepmd/pt/entrypoints/main.py 0.00% 1 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##            devel    #4224      +/-   ##
==========================================
+ Coverage   83.52%   84.54%   +1.02%     
==========================================
  Files         542      537       -5     
  Lines       52544    51236    -1308     
  Branches     3043     3050       +7     
==========================================
- Hits        43888    43320     -568     
+ Misses       7709     6966     -743     
- Partials      947      950       +3     

☔ View full report in Codecov by Sentry.
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@iProzd iProzd requested review from njzjz and wanghan-iapcm October 16, 2024 12:24
@iProzd iProzd requested a review from njzjz October 23, 2024 04:48
@iProzd iProzd added this pull request to the merge queue Oct 23, 2024
Merged via the queue into deepmodeling:devel with commit a74d963 Oct 23, 2024
60 checks passed
@iProzd iProzd deleted the add_gloo_support branch October 23, 2024 16:29
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[Feature Request] support CPU parallel training with PT
3 participants