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@hyukn hyukn commented Nov 6, 2025

Summary by CodeRabbit

  • Documentation
    • Clarified description of the autotuner configuration option.

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@hyukn hyukn requested a review from nv-guomingz November 6, 2025 06:56
@hyukn hyukn requested a review from a team as a code owner November 6, 2025 06:56
@hyukn hyukn requested a review from shaharmor98 November 6, 2025 06:56
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📝 Walkthrough

Walkthrough

Comment update for the enable_autotuner field in the config file. The documentation was changed from torch-compile-specific language to a general description of autotuning behavior and fallback handling. No code logic or default values modified.

Changes

Cohort / File(s) Change Summary
Configuration comment update
tensorrt_llm/_torch/pyexecutor/config.py
Updated enable_autotuner field comments to remove torch-compile-specific context and replace with general description of autotuning application to all tunable ops and fallback behavior for non-autotuned ops

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🎯 1 (Trivial) | ⏱️ ~2 minutes

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Description check ⚠️ Warning The PR description is primarily a template with placeholder sections (Description, Test Coverage) that are not filled out; the critical context is missing from the author. Add explicit descriptions of what issue is being addressed and why this change is necessary. Document any relevant test coverage that validates this comment change.
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✅ Passed checks (1 passed)
Check name Status Explanation
Title check ✅ Passed The title clearly and accurately summarizes the main change: revising the comment for the AutoTuner enable flag in PyTorchConfig, which matches the code change summary.
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🔇 Additional comments (2)
tensorrt_llm/_torch/pyexecutor/config.py (2)

88-89: Comment clarification improves scope clarity.

The revised comment effectively generalizes the autotuner description from torch-compile-specific language to a broader statement about autotuning behavior and fallback handling. This better reflects the field's actual scope and intent.


1-1: Verify the Apache-2.0 copyright header is present.

According to the coding guidelines, all .py source files must include the NVIDIA Apache-2.0 copyright header with the current year at the top. The provided code begins with imports; please confirm the copyright header is in place at the file's start.


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