[None][Fix] Prevent resource leak warnings

[IanBoyanZhang]

Warning: WARNING: destroy_process_group() was not called before program exit which can leak resources. For more info

When compiler_helpers() function failed to complete the subprocess

I hit this warning while trying to run a Mistral 7B training example on a single GPU. The dataset preparation failed, which resulted in this warning.

What does this PR do ?

⚠️ For major changes (either in lines of code or in its impact), please make sure to first share a design doc with the team. If you're unsure what's the best way to do so, contact the @mcore-oncall.

Contribution process

flowchart LR
    A[Pre-checks] --> B[PR Tests]
    subgraph Code Review/Approval
        C1[Expert Review] --> C2[Final Review]
    end
    B --> C1
    C2 --> D[Merge]

Loading

Pre-checks

• I want this PR in a versioned release and have added the appropriate Milestone (e.g., Core 0.8)
• I have added relevant unit tests
• I have added relevant functional tests
• I have added proper typing to my code Typing guidelines
• I have added relevant documentation
• I have run the autoformatter.sh on my PR

Code review

The following process is enforced via the CODEOWNERS file for changes into megatron/core. For changes outside of megatron/core, it is up to the PR author whether or not to tag the Final Reviewer team.

For MRs into `main` branch

Feel free to message or comment the @mcore-oncall to help accelerate your merge into main. The less complex your PR is, the faster it will be approved and merged!

(Step 1): Add PR label Expert Review

(Step 2): Collect the expert reviewers reviews

1. Attach the Expert Review label when your PR is ready for review.
2. GitHub auto-assigns expert reviewers based on your changes. They will get notified and pick up your PR soon.

⚠️ Only proceed to the next step once all reviewers have approved, merge-conflict are resolved and the CI is passing.
Final Review might get declined if these requirements are not fulfilled.

(Step 3): Final Review

1. Add Final Review label
2. GitHub auto-assigns final reviewers based on your changes. They will get notified and pick up your PR soon.

(Optional Step 4): Cherry-pick into release branch

If this PR also needs to be merged into core_r* release branches, after this PR has been merged, select Cherry-pick to open a new PR into the release branch.

For MRs into `dev` branch

The proposed review process for `dev` branch is under active discussion.

MRs are mergable after one approval by either eharper@nvidia.com or zijiey@nvidia.com.

Merging your PR

Any member of core-adlr and core-nemo will be able to merge your PR.

[copy-pr-bot]

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

[dimapihtar]

/ok to test fe4e1d1

[IanBoyanZhang]

/ok to test fe4e1d1

[yaox12]

/ok to test 5dfce30

[yaox12]

/ok to test bbe2c64

[yaox12]

/ok to test 2ffbdd6

[yaox12]

/ok to test 5833bce

[yaox12]

I just realized two potential issues with this PR.

1. We need to check dist.is_initialized before calling dist.destroy_process_group().
2. The destroy code is under the if condition if subprocess.run(command).returncode != 0:, so if some processes succeed in compiling, while others fail, we cannot make sure all processes call dist.destroy_process_group().

I will revert this PR.

[IanBoyanZhang]

@yaox12, apologies for the extra hassle, and thanks for taking the time to review the PR!

Through the codebase except one instance in /training/initialize.py, it follows this pattern:

if torch.distributed.is_available():
    utils.initialize_distributed()
    if torch.distributed.get_rank() == 0:
        compile_helpers()
        torch.distributed.barrier()
    else:
        compile_helpers()

Do you think it makes more sense to move this logic into the compile_helper() function itself? For example

def _internal_helper():
       .e.g. log and exit()

def compile_helper(): 
    if torch.distributed.is_available():
        Utils.initialize_distributed()
        if torch.distributed.get_rank() == 0:
            x = "subprocess make -C .... "
            torch.distributed.barrier()
            if (not x):
                log()
                dist.destroy_process_group()
                exit(1)
    else:
        x = "subprocess make -C ..."
        if (not x):
            log()
            dist.destroy_process_group()
            exit(1)

Thanks again!