[#8391][chore] added llama_v3.3_70b_instruct AutoDeploy perf test to L0

[MrGeva]

Summary by CodeRabbit

• Tests
  • Added a new performance test case to the testing suite for benchmarking validation.

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Description

Test Coverage

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

• Update tava architecture diagram if there is a significant design change in PR.

• The reviewers assigned automatically/manually are appropriate for the PR.

• Please check this after reviewing the above items as appropriate for this PR.

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[MrGeva]

/bot run

[coderabbitai]

📝 Walkthrough

Walkthrough

A new performance test entry is added to the l0_perf.yml configuration file for the perf/tests suite. The test executes perf/test_perf.py::test_perf with specific benchmark parameters for an Llama model, extending the existing test list without modifying any current entries.

Changes

Cohort / File(s)	Summary
Test Configuration tests/integration/test_lists/test-db/l0_perf.yml	Adds new performance test entry with llama_v3.3_70b_instruct-bench model using float16 precision and specified input/output length and request parameters

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The PR description only contains the template without filling in the required sections: Description, Test Coverage, and PR Checklist are empty or uncompleted.	Fill in the Description section explaining why this test is being added, provide Test Coverage details about the new test, and complete the PR Checklist items.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and specifically describes the main change: adding an llama_v3.3_70b_instruct AutoDeploy performance test to the L0 test suite.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

✨ Finishing touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment

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📜 Recent review details

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 06900a7 and 5365375.

📒 Files selected for processing (1)

• tests/integration/test_lists/test-db/l0_perf.yml

🧰 Additional context used

🧠 Learnings (3)

📓 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.

Learnt from: fredricz-20070104
Repo: NVIDIA/TensorRT-LLM PR: 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
Repo: NVIDIA/TensorRT-LLM PR: 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
Repo: NVIDIA/TensorRT-LLM PR: 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*").

📚 Learning: 2025-09-09T09:40:45.658Z

Learnt from: fredricz-20070104
Repo: NVIDIA/TensorRT-LLM PR: 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/test-db/l0_perf.yml

📚 Learning: 2025-07-28T17:06:08.621Z

Learnt from: moraxu
Repo: NVIDIA/TensorRT-LLM PR: 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/test-db/l0_perf.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/test-db/l0_perf.yml (1)

46-46: No actionable issues identified.

Llama-3.3-70B-Instruct is officially supported by AutoDeploy (listed in support matrix) and was intentionally added to L0 with these parameters by the developer. AutoDeploy's automated optimizations (graph sharding, quantization, KV-cache management, GEMM fusion) are designed to enable large models to run on single GPUs, directly addressing the memory constraint concern. The specific test parameters appear deliberate and validated. No evidence indicates this test fails, times out, or blocks CI.

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[tensorrt-cicd]

PR_Github #29645 [ run ] triggered by Bot. Commit: 5365375

[tensorrt-cicd]

PR_Github #29645 [ run ] completed with state DISABLED
CI server is currently disabled for scheduled maintenance. Estimated completion time: 12 PM PST on 12/23.

[MrGeva]

/bot run

[tensorrt-cicd]

PR_Github #29745 [ run ] triggered by Bot. Commit: 5365375

[tensorrt-cicd]

PR_Github #29745 [ run ] completed with state SUCCESS. Commit: 5365375
/LLM/main/L0_MergeRequest_PR pipeline #22856 completed with status: 'FAILURE'

⚠️ Action Required:

• Please check the failed tests and fix your PR
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