[#11203][feat] AutoDeploy: Improve detect_sharding transform time

[taylor-yb-lee]

Description

detect_sharding transform in AutoDeploy backend is very slow for large models (e.g., Nemotron SuperV3 : 6min)
This PR improves detect_sharding processing time by caching weight shapes. By result, Nemotron SuperV3 detect sharding can be done in 88 sec.

Test Coverage

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Summary by CodeRabbit

• Refactor
  • Improved efficiency of the auto-deployment transformation process through enhanced shape data handling.

[coderabbitai]

📝 Walkthrough

Walkthrough

A context manager shape_cache_scope() is introduced to manage shape caching during node processing. The sharding module is refactored to use this context manager, wrapping sharding source processing (factory, manual, heuristic) within the scoped block to localize cache lifecycle management.

Changes

Cohort / File(s)	Summary
New Shape Cache Mechanism tensorrt_llm/_torch/auto_deploy/utils/node_utils.py	Added module-level caches (_param_names_cache, _weight_shape_cache) and _cache_enabled flag. Implemented shape_cache_scope() context manager to enable/disable caching and clear caches on exit. Integrated caching into extract_weight_nodes() and get_weight_shape() functions, with cache population on compute and reuse when enabled.
Sharding Source Refactoring tensorrt_llm/_torch/auto_deploy/transform/library/sharding.py	Reorganized sharding source processing loop to wrap factory, manual, and heuristic source handling inside shape_cache_scope() context manager. Replaced direct conditional branches with centralized control flow calling detect_sharding_from_config() for factory/manual sources while preserving heuristic dimension checks. Added import for shape_cache_scope utility.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

🚥 Pre-merge checks | ✅ 1 | ❌ 2

❌ Failed checks (2 warnings)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 66.67% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.
Description check	⚠️ Warning	The PR description is incomplete and missing critical required sections: Test Coverage is empty, and the PR title format is incorrect.	Add a proper PR title following [type] format (e.g., [#11203][feat]), complete the Test Coverage section with relevant test names, and provide more detail on the implementation approach and why the caching strategy was chosen.

✅ Passed checks (1 passed)

Check name	Status	Explanation
Title check	✅ Passed	The PR title clearly describes the main optimization—improving detect_sharding transform time via caching, which directly matches the core changes (shape_cache_scope context manager and weight shape caching).

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[taylor-yb-lee]

/bot run

[tensorrt-cicd]

PR_Github #34538 [ run ] triggered by Bot. Commit: 98872d1

[tensorrt-cicd]

PR_Github #34538 [ run ] completed with state SUCCESS. Commit: 98872d1
/LLM/main/L0_MergeRequest_PR pipeline #26649 completed with status: 'FAILURE'

⚠️ Action Required:

• Please check the failed tests and fix your PR
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[taylor-yb-lee]

/bot run

[tensorrt-cicd]

PR_Github #34568 [ run ] triggered by Bot. Commit: 98872d1

[tensorrt-cicd]

PR_Github #34568 [ run ] completed with state FAILURE. Commit: 98872d1
/LLM/main/L0_MergeRequest_PR pipeline #26676 completed with status: 'FAILURE'

⚠️ Action Required:

• Please check the failed tests and fix your PR
• If you cannot view the failures, ask the CI triggerer to share details
• Once fixed, request an NVIDIA team member to trigger CI again

[taylor-yb-lee]

/bot run

[tensorrt-cicd]

PR_Github #34682 [ run ] triggered by Bot. Commit: 98872d1

[tensorrt-cicd]

PR_Github #34682 [ run ] completed with state SUCCESS. Commit: 98872d1
/LLM/main/L0_MergeRequest_PR pipeline #26763 completed with status: 'FAILURE'

⚠️ Action Required:

• Please check the failed tests and fix your PR
• If you cannot view the failures, ask the CI triggerer to share details
• Once fixed, request an NVIDIA team member to trigger CI again

[taylor-yb-lee]

Replace with #11250