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@ruodil ruodil commented Aug 8, 2025

Summary by CodeRabbit

  • Style
    • Corrected YAML indentation in test configuration files for improved readability and structure.

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Test Coverage

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@ruodil ruodil self-assigned this Aug 8, 2025
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coderabbitai bot commented Aug 8, 2025

📝 Walkthrough

Walkthrough

The YAML file for an integration test was updated to correct indentation under a specific FP8-related test condition. The terms and wildcards keys were properly nested under the condition node. No changes were made to the test logic or entries, only the YAML structure was adjusted.

Changes

Cohort / File(s) Change Summary
YAML Indentation Correction
tests/integration/test_lists/qa/llm_perf_nim.yml
Adjusted indentation for terms and wildcards under the condition block to ensure correct YAML structure. No logic or test changes.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

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  • LarryXFly
  • StanleySun639
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Actionable comments posted: 0

🧹 Nitpick comments (1)
tests/integration/test_lists/qa/llm_perf_nim.yml (1)

113-119: Add CI linting to prevent future YAML syntax regressions

A lightweight yamllint (or similar) step in the testing pipeline would flag mis-indented keys early, avoiding PR round-trips for simple syntax issues.

📜 Review details

Configuration used: .coderabbit.yaml
Review profile: CHILL
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📥 Commits

Reviewing files that changed from the base of the PR and between d289d85 and 1f0a5b2.

📒 Files selected for processing (1)
  • tests/integration/test_lists/qa/llm_perf_nim.yml (1 hunks)
🧰 Additional context used
🧠 Learnings (3)
📓 Common learnings
Learnt from: galagam
PR: NVIDIA/TensorRT-LLM#6487
File: tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_trtllm_bench.py:1-12
Timestamp: 2025-08-06T13:58:07.506Z
Learning: In TensorRT-LLM, test files (files under tests/ directories) do not require NVIDIA copyright headers, unlike production source code files. Test files typically start directly with imports, docstrings, or code.
📚 Learning: 2025-08-06T13:58:07.506Z
Learnt from: galagam
PR: NVIDIA/TensorRT-LLM#6487
File: tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_trtllm_bench.py:1-12
Timestamp: 2025-08-06T13:58:07.506Z
Learning: In TensorRT-LLM, test files (files under tests/ directories) do not require NVIDIA copyright headers, unlike production source code files. Test files typically start directly with imports, docstrings, or code.

Applied to files:

  • tests/integration/test_lists/qa/llm_perf_nim.yml
📚 Learning: 2025-07-28T17:06:08.621Z
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.

Applied to files:

  • tests/integration/test_lists/qa/llm_perf_nim.yml
⏰ 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 (1)
tests/integration/test_lists/qa/llm_perf_nim.yml (1)

113-119: Indentation fix resolves YAML parsing error

terms and wildcards are now correctly nested beneath condition, so the block is valid YAML and will be parsed as intended.

@LarryXFly LarryXFly merged commit 28b762a into NVIDIA:release/1.0 Aug 8, 2025
4 checks passed
dominicshanshan pushed a commit to dominicshanshan/TensorRT-LLM that referenced this pull request Aug 19, 2025
dominicshanshan pushed a commit to dominicshanshan/TensorRT-LLM that referenced this pull request Aug 19, 2025
dominicshanshan pushed a commit to dominicshanshan/TensorRT-LLM that referenced this pull request Aug 20, 2025
dominicshanshan pushed a commit to dominicshanshan/TensorRT-LLM that referenced this pull request Aug 20, 2025
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2 participants