[https://nvbugs/5629833][fix] Use torch.empty instead of torch.zeros in get_buffer

[lancelly]

The buffer tensor returned by get_buffer does not need to be initailized. The callers should initialize the returned buffer themseves if needed.

Summary by CodeRabbit

• Refactor
  • Optimized memory buffer allocation efficiency without changes to the public API.

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[lancelly]

/bot run --disable-fail-fast

[coderabbitai]

📝 Walkthrough

Walkthrough

The memory_buffer_utils module was modified to use uninitialized cuda uint8 buffers instead of zero-initialized ones during allocation in the get_buffer method. An explanatory docstring was added to the method. No public API signatures were changed.

Changes

Cohort / File(s)	Summary
Buffer allocation optimization tensorrt_llm/_torch/memory_buffer_utils.py	Replaced torch.zeros with torch.empty in both buffer allocation paths within get_buffer for uninitialized memory allocation. Added explanatory docstring to the method.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~8 minutes

• Straightforward substitution pattern applied consistently across both allocation paths
• Single-file change with localized scope
• Requires verification that memory initialization behavior change is intentional and safe for all downstream usage

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The description is minimal and lacks required sections from the template including detailed explanation of the issue, test coverage information, and PR checklist confirmation.	Expand description to explain why this optimization is safe, add test coverage section, and complete the PR checklist items as specified in the template.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and specifically describes the main change: replacing torch.zeros with torch.empty in the get_buffer function, referencing the NVBugs ticket.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment

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📜 Recent review details

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between b6483ef and 9b211b2.

📒 Files selected for processing (1)

• tensorrt_llm/_torch/memory_buffer_utils.py (3 hunks)

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)

• GitHub Check: Pre-commit Check

🔇 Additional comments (2)

tensorrt_llm/_torch/memory_buffer_utils.py (2)

54-59: Good addition of explanatory docstring.

The docstring clearly documents that the returned buffer contains uninitialized memory and advises callers to overwrite the data before use. This is important documentation for preventing misuse.

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100-102: ****

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[tensorrt-cicd]

PR_Github #25352 [ run ] triggered by Bot. Commit: 9b211b2

[lancelly]

duplicated with：#9296

[tensorrt-cicd]

PR_Github #25352 [ run ] completed with state SUCCESS. Commit: 9b211b2
/LLM/main/L0_MergeRequest_PR pipeline #19176 completed with status: 'FAILURE'