[TRTLLM-7070][feat] add gpt-oss serve benchmark tests #7638

xinhe-nv · 2025-09-09T06:52:06Z

Summary by CodeRabbit

Tests
- Expanded TRT-LLM serving benchmark to run against two model variants for broader coverage.
- Refined test selection to target specific parameterized scenarios, improving reliability and clarity of results.
- Enhanced benchmark assertions to verify successful execution and output presence.
- Updated GPU memory skip thresholds to decimal GB units, aligning test execution with typical hardware reporting.
- Adjusted QA test lists to include the new parameterized cases across suites for consistent execution.

Description

Test Coverage

Add gpt-oss trtllm-serve benchmark tests.
The tests are failure due to benchmark script is not stable. https://prod.blsm.nvidia.com/swqa-tensorrt-qa-test/view/TRT-LLM-Function-Pipelines/job/DEBUG_LLM_FUNCTION_TEST/1734/testReport/

PR Checklist

Please review the following before submitting your PR:

PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (see test instructions)
Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
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xinhe-nv · 2025-09-10T02:31:07Z

/bot run

coderabbitai · 2025-09-10T02:34:26Z

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📥 Commits

Reviewing files that changed from the base of the PR and between f412f5c and 7f20a30.

📒 Files selected for processing (6)

tests/integration/defs/test_e2e.py (1 hunks)
tests/integration/test_lists/qa/llm_function_core.txt (1 hunks)
tests/integration/test_lists/qa/llm_function_core_sanity.txt (1 hunks)
tests/integration/test_lists/qa/llm_function_nim.txt (1 hunks)
tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py (3 hunks)
tests/unittest/utils/util.py (1 hunks)

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📓 Path-based instructions (3)

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tests/unittest/utils/util.py
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tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py

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tests/integration/defs/test_e2e.py
tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py

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🧠 Learnings (4)

📓 Common learnings

Learnt from: fredricz-20070104
PR: NVIDIA/TensorRT-LLM#7645
File: tests/integration/test_lists/qa/llm_function_core.txt:648-648
Timestamp: 2025-09-09T09:40:45.658Z
Learning: In TensorRT-LLM test lists, it's common and intentional for the same test to appear in multiple test list files when they serve different purposes (e.g., llm_function_core.txt for comprehensive core functionality testing and llm_function_core_sanity.txt for quick sanity checks). This duplication allows tests to be run in different testing contexts.

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.

Learnt from: pengbowang-nv
PR: NVIDIA/TensorRT-LLM#7192
File: tests/integration/test_lists/test-db/l0_dgx_b200.yml:56-72
Timestamp: 2025-08-26T09:49:04.956Z
Learning: In TensorRT-LLM test configuration files, the test scheduling system handles wildcard matching with special rules that prevent duplicate test execution even when the same tests appear in multiple yaml files with overlapping GPU wildcards (e.g., "*b200*" and "*gb200*").

Learnt from: achartier
PR: NVIDIA/TensorRT-LLM#6763
File: tests/integration/defs/triton_server/conftest.py:16-22
Timestamp: 2025-08-11T20:09:24.389Z
Learning: In the TensorRT-LLM test infrastructure, the team prefers simple, direct solutions (like hard-coding directory traversal counts) over more complex but robust approaches when dealing with stable directory structures. They accept the maintenance cost of updating tests if the layout changes.

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: 2025-09-09T09:40:45.658Z

Learnt from: fredricz-20070104
PR: NVIDIA/TensorRT-LLM#7645
File: tests/integration/test_lists/qa/llm_function_core.txt:648-648
Timestamp: 2025-09-09T09:40:45.658Z
Learning: In TensorRT-LLM test lists, it's common and intentional for the same test to appear in multiple test list files when they serve different purposes (e.g., llm_function_core.txt for comprehensive core functionality testing and llm_function_core_sanity.txt for quick sanity checks). This duplication allows tests to be run in different testing contexts.

Applied to files:

tests/integration/test_lists/qa/llm_function_core_sanity.txt
tests/integration/test_lists/qa/llm_function_nim.txt
tests/integration/defs/test_e2e.py
tests/integration/test_lists/qa/llm_function_core.txt

📚 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_function_core_sanity.txt
tests/integration/test_lists/qa/llm_function_nim.txt
tests/integration/defs/test_e2e.py
tests/integration/test_lists/qa/llm_function_core.txt
tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py

📚 Learning: 2025-08-26T09:49:04.956Z

Learnt from: pengbowang-nv
PR: NVIDIA/TensorRT-LLM#7192
File: tests/integration/test_lists/test-db/l0_dgx_b200.yml:56-72
Timestamp: 2025-08-26T09:49:04.956Z
Learning: In TensorRT-LLM test configuration files, the test scheduling system handles wildcard matching with special rules that prevent duplicate test execution even when the same tests appear in multiple yaml files with overlapping GPU wildcards (e.g., "*b200*" and "*gb200*").

Applied to files:

tests/integration/test_lists/qa/llm_function_core_sanity.txt
tests/integration/test_lists/qa/llm_function_nim.txt
tests/integration/test_lists/qa/llm_function_core.txt

🧬 Code graph analysis (1)

tests/integration/defs/test_e2e.py (2)

tests/integration/defs/conftest.py (2)

llm_venv (715-732)

unittest_path (89-90)

tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py (1)

model_name (15-16)

🪛 Ruff (0.12.2)

tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py

51-51: Unused function argument: server

(ARG001)

62-62: subprocess call: check for execution of untrusted input

(S603)

⏰ 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

📝 Walkthrough

Walkthrough

Parameterizes TRT-LLM benchmark tests to run for two models, updates E2E wrapper to target specific parametrized inner test, adjusts test lists to enumerate new parameterized cases, enhances unit test to pass server args and assert output, and switches GPU memory skip thresholds from GiB to decimal GB.

Changes

Cohort / File(s)	Summary
E2E wrapper parameterization `tests/integration/defs/test_e2e.py`	Converts `test_trtllm_benchmark_serving` to pytest-parametrized over `model_name`; adjusts signature to `(llm_venv, model_name)`; invokes specific inner test case via path-spec `.../_test_trtllm_serve_benchmark.py::test_trtllm_serve_benchmark[{model_name}]`.
QA test lists updates `tests/integration/test_lists/qa/llm_function_core.txt`, `tests/integration/test_lists/qa/llm_function_core_sanity.txt`, `tests/integration/test_lists/qa/llm_function_nim.txt`	Replaces single test entry with two parametrized entries in core; switches sanity list to `[gpt_oss/gpt-oss-20b]`; adds `[gpt_oss/gpt-oss-20b]` entries in nim list.
Inner benchmark test enhancements `tests/unittest/llmapi/apps/_test_trtllm_serve_benchmark.py`	Parameterizes `test_trtllm_serve_benchmark` over two models with `indirect=True`; `model_name` fixture now `def model_name(request)` returning `request.param`; server fixture adds CLI arg `kv_cache_free_gpu_memory_fraction=0.8`; subprocess output captured; asserts return code 0 and stdout contains "Serving Benchmark Result".
GPU memory skip thresholds `tests/unittest/utils/util.py`	Changes skip thresholds from GiB (1024-based) to decimal GB (1000-based) for 40, 80, and 138 GB helpers.

Sequence Diagram(s)

sequenceDiagram
  autonumber
  actor PyTestRunner as PyTest Runner
  participant E2E as E2E Wrapper Test
  participant Inner as Parametrized Inner Test
  participant Server as TRT-LLM Server (fixture)
  participant Bench as benchmark_serving.py (subprocess)

  PyTestRunner->>E2E: run test_trtllm_benchmark_serving[model_name]
  E2E->>Inner: invoke _test_trtllm_serve_benchmark.py::test_trtllm_serve_benchmark[model_name]
  activate Inner
  Inner->>Server: start with args (kv_cache_free_gpu_memory_fraction=0.8)
  activate Server
  Server-->>Inner: server ready
  Inner->>Bench: run with model arg (derived from model_path)
  Bench-->>Inner: exit code, stdout
  Inner->>Inner: assert rc==0 and "Serving Benchmark Result" in stdout
  deactivate Server
  Inner-->>PyTestRunner: test result (per model)
  deactivate Inner

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Pre-merge checks (1 passed, 2 warnings)

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Check name	Status	Explanation	Resolution
Description Check	⚠️ Warning	The current description retains template placeholders instead of providing an actual summary and leaves the Description section empty, while the Test Coverage section only notes instability without listing specific tests; this omission of substantive content fails to fulfill the required template sections for clear explanation of the issue, solution, and relevant test safeguards.	Please replace the @coderabbitai placeholder with a concise summary, fill in the Description section with an explanation of the issue and the implemented solution, and expand the Test Coverage section to list the exact test cases added or modified to ensure adequate coverage.
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 pull request title “[TRTLLM-7070][feat] add gpt-oss serve benchmark tests” concisely summarizes the primary change by referencing the relevant ticket, specifying the change type, and clearly describing the new benchmark tests being added, which aligns with the project’s guidelines for clear and focused titles.

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tensorrt-cicd · 2025-09-10T02:36:22Z

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add gpt-oss serve benchmark tests

0e712af

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Merge branch 'main' into user/xinhe/feat

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xinhe-nv merged commit 1fbea49 into NVIDIA:main Sep 16, 2025
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Wong4j pushed a commit to Wong4j/TensorRT-LLM that referenced this pull request Sep 20, 2025

[TRTLLM-7070][feat] add gpt-oss serve benchmark tests (NVIDIA#7638)

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Signed-off-by: Xin He (SW-GPU) <200704525+xinhe-nv@users.noreply.github.com>

MrGeva pushed a commit to nv-auto-deploy/TensorRT-LLM that referenced this pull request Sep 21, 2025

[TRTLLM-7070][feat] add gpt-oss serve benchmark tests (NVIDIA#7638)

d4ece85

Signed-off-by: Xin He (SW-GPU) <200704525+xinhe-nv@users.noreply.github.com>

[TRTLLM-7070][feat] add gpt-oss serve benchmark tests #7638

[TRTLLM-7070][feat] add gpt-oss serve benchmark tests #7638

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Summary by CodeRabbit

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Sequence Diagram(s)

Estimated code review effort

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xinhe-nv commented Sep 9, 2025 •

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coderabbitai bot commented Sep 10, 2025 •

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