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Repository Guidelines

Skills

The skills/ directory contains structured guides for common tasks (running tests, building containers, managing dependencies, submitting SLURM jobs, etc.). Always read the relevant SKILL.md before starting any task it covers — skills are mandatory context, not optional background reading.

Workflow — mandatory order for every task:

  1. Pull information first. Read the commit, PR, error log, file, or whatever artifact the task is about. Do not reason about it yet.
  2. Select and invoke the skill. Based on what you just read, identify the relevant skill and invoke it before forming any answer or plan.
  3. Answer or implement. Only after the skill is loaded, use its context to reason, diagnose, or write code.

Never skip or reorder these steps. Do not wait for the user to name the right skill keyword — infer it from the artifact you read.

Contributing

Pull Requests

  • All PRs must be created as drafts. Use gh pr create --draft or the GitHub UI draft option.
  • Never push branches directly to https://github.com/NVIDIA/Megatron-LM. You must push your branch to a personal fork (e.g. https://github.com/<your-username>/Megatron-LM), then open a PR from the fork's branch against NVIDIA/Megatron-LM.
  • Commit PR changes with both -s and -S: -s adds the required Signed-off-by trailer, and -S signs the commit so copy-pr-bot and /ok to test can verify the pushed commit without manually specifying the SHA. Megatron Core engineers at NVIDIA should sign using their NVIDIA emails so they are automatically added to the right user groups on the internal Slack workspace.
  • Read @docs/developer/contribute.md for the full contribution policy, including code style, commit message conventions, and issue guidelines.

Code Quality

  • After editing imports in any Python files, always run uv run isort on those files to fix import order before committing.

Megatron Core Process Groups

  • In megatron/core production code, avoid adding new direct reads of global process groups from parallel_state (for example, parallel_state.get_tensor_model_parallel_group() or directly imported get_*_group() helpers). Prefer accepting a ProcessGroupCollection or an explicit torch.distributed.ProcessGroup from the caller and passing that through.
  • Allowed compatibility points include megatron/core/parallel_state.py, megatron/core/process_groups_config.py, initialization/bootstrap code that materializes a ProcessGroupCollection from MPU globals, tests, docs, and migration fallbacks with an explicit comment.
  • This guidance targets Megatron Core library code. Do not apply it to megatron/training or other training-loop code unless the PR explicitly opts into that migration.
  • In reviews, flag new direct parallel_state.get_*_group() usage in megatron/core unless it is one of the compatibility points above. This is advisory guidance, not a CI gate.