[None] Add export data to build and run script for AD

[tcherckez-nvidia]

Summary by CodeRabbit

• Chores
  • Enhanced example auto-deployment script to capture and log additional configuration information in results output.

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Description

Test Coverage

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[tcherckez-nvidia]

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[coderabbitai]

📝 Walkthrough

Walkthrough

The pull request modifies the results dictionary in the build and run execution flow to include additional configuration parameters: world size (tp), compile backend, attention backend, and runtime. No control flow or error handling logic is altered.

Changes

Cohort / File(s)	Summary
Results Dictionary Expansion examples/auto_deploy/build_and_run_ad.py	Added four configuration entries to logged results: tp (world_size), compile_backend, attn_backend, and runtime from config.args

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~8 minutes

Pre-merge checks and finishing touches

❌ Failed checks (2 warnings)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The PR description contains only the repository template with empty placeholders. Required sections like 'Description' and 'Test Coverage' are not filled out with substantive content.	Please fill out the 'Description' section explaining what changes were made and why, and provide details in 'Test Coverage' about relevant tests for these changes.
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.

✅ Passed checks (1 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly describes the main change: adding export data to the build and run script for AD. It follows the repository template format with [None] and a descriptive summary.

✨ 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

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📥 Commits

Reviewing files that changed from the base of the PR and between 97b38ac and 435428c.

📒 Files selected for processing (1)

• examples/auto_deploy/build_and_run_ad.py

🧰 Additional context used

📓 Path-based instructions (2)

**/*.py

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

**/*.py: Code developed for TensorRT-LLM should conform to Python 3.8+
Indent Python code with 4 spaces. Do not use tabs
Always maintain the namespace when importing in Python, even if only one class or function from a module is used
Python files should use snake_case naming: some_file.py
Python classes should use PascalCase naming: class SomeClass
Python functions and methods should use snake_case naming: def my_awesome_function():
Python local variables should use snake_case naming: my_variable = ...
Python variable names that start with a number should be prefixed with 'k': k_99th_percentile = ...
Python global variables should use upper snake_case with prefix 'G': G_MY_GLOBAL = ...
Python constants should use upper snake_case naming: MY_CONSTANT = ...
Avoid shadowing variables declared in an outer scope in Python
Initialize all externally visible members of a Python class in the constructor
For Python interfaces that may be used outside a file, prefer docstrings over comments
Python comments should be reserved for code within a function, or interfaces that are local to a file
Use Google style docstrings in Python for classes and functions, which can be parsed by Sphinx
Python attributes and variables can be documented inline with type and description
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When using try-except blocks in Python, limit the except to the smallest set of errors possible
When using try-except blocks in Python to handle multiple possible variable types (duck-typing), keep the body of the try as small as possible, using the else block for logic

Files:

• examples/auto_deploy/build_and_run_ad.py

**/*.{cpp,h,cu,cuh,py}

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

All TensorRT-LLM Open Source Software code should contain an NVIDIA copyright header that includes the year of its latest meaningful modification

Files:

• examples/auto_deploy/build_and_run_ad.py

🧠 Learnings (1)

📓 Common learnings

Learnt from: venkywonka
Repo: NVIDIA/TensorRT-LLM PR: 6029
File: .github/pull_request_template.md:45-53
Timestamp: 2025-08-27T17:50:13.264Z
Learning: For PR templates in TensorRT-LLM, avoid suggesting changes that would increase developer overhead, such as converting plain bullets to mandatory checkboxes. The team prefers guidance-style bullets that don't require explicit interaction to reduce friction in the PR creation process.

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[tensorrt-cicd]

PR_Github #29955 [ run ] triggered by Bot. Commit: 435428c

[tensorrt-cicd]

PR_Github #29955 [ run ] completed with state SUCCESS. Commit: 435428c
/LLM/main/L0_MergeRequest_PR pipeline #23041 completed with status: 'SUCCESS'
Pipeline passed with automatic retried tests. Check the rerun report for details.