[None][fix] Bypass key-word matching for multimodal tests

[Wanli-Jiang]

Don't need to mass integrate to main branch.

To fix 1.1 branch faster, we will skip key-word-matching, and only run sanity checking.

It will fix

• https://nvbugs/5547437
• https://nvbugs/5568836
• https://nvbugs/5591109
• https://nvbugs/5630274

see test report in https://prod.blsm.nvidia.com/swqa-tensorrt-qa-test/view/TRT-LLM-Function-Pipelines/job/DEBUG_LLM_FUNCTION_TEST/2045/testReport/H100/test_e2e/

Also unwaived the below tests:

• https://nvbugs/5509024
• https://nvbugs/5444095
• https://nvbugs/5453725

Besides that, I also added phi4mm MMMU accuracy tests.

Summary by CodeRabbit

Tests

• Added test coverage for new multimodal model variant with LoRA support
• Migrated test data from external URLs to local files for improved test stability
• Adjusted validation thresholds across multimodal test suite

Reference Data

• Added accuracy baseline metrics (53.67%) for new model configuration

Description

Test Coverage

PR Checklist

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• CODEOWNERS updated if ownership changes

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[coderabbitai]

📝 Walkthrough

Walkthrough

This PR adds a new test case for Phi-4 multimodal model with fused vision LoRA. It introduces a new test class to the accuracy test suite, adds corresponding reference accuracy data, and registers the test in multiple test lists. It also adjusts test thresholds and replaces external media URLs with local file references in end-to-end tests.

Changes

Cohort / File(s)	Summary
Test Class Addition tests/integration/defs/accuracy/test_llm_api_pytorch.py	Added new test class TestPhi4MMFusedVisionLora extending LlmapiAccuracyTestHarness with model configuration, sampling parameters, KV cache config, and test_auto_dtype() method for MMMU evaluation
Reference Data tests/integration/defs/accuracy/references/mmmu.yaml	Added accuracy reference entry for microsoft/Phi-4-multimodal-instruct with value 53.67
Test List Registrations tests/integration/test_lists/qa/llm_function_core.txt, llm_function_l20.txt, llm_function_nim.txt	Registered new test entry accuracy/test_llm_api_pytorch.py::TestPhi4MMFusedVisionLora::test_auto_dtype across three test manifests
End-to-End Test Updates tests/integration/defs/test_e2e.py	Lowered match_ratio thresholds to 0.0 on multimodal and KV-cache tests; replaced external media URLs with local test data file paths (inpaint.png, 61.jpg, video files)

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

• test_e2e.py: Verify that lowering match_ratio thresholds to 0.0 is intentional and confirm the purpose of disabling accuracy checks for affected multimodal tests. Cross-check that all referenced local media files exist.
• test_llm_api_pytorch.py: Confirm that TestPhi4MMFusedVisionLora correctly mirrors existing Phi-4 test patterns and that model path and parameters are appropriate.

Pre-merge checks and finishing touches

❌ Failed checks (1 warning, 1 inconclusive)

Check name	Status	Explanation	Resolution
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.
Description check	❓ Inconclusive	PR description lacks structure and clarity; core sections (Description, Test Coverage) are empty, and the initial comment appears incomplete or informal.	Fill in the Description section explaining what changes were made and why. Complete the Test Coverage section listing relevant tests. Consider clarifying the statement about not needing to integrate to main branch.

✅ Passed checks (1 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly summarizes the main change: bypassing key-word matching for multimodal tests, with proper format and no extraneous details.

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[coderabbitai]

Actionable comments posted: 1

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (4)

tests/integration/defs/test_e2e.py (4)

2625-2635: 0% threshold disables accuracy; add minimal sanity checks to prevent false passes

With match_ratio = 0.0, the keyword gate is fully bypassed. If parse_output returns fewer items (or none), zip(...) won’t assert. Add output-count and non-empty checks before looping.

Apply this diff:

 parsed_outputs = parse_output(output)
+expected_count = len(accuracy_inputs[modality]["prompt"])
+assert len(parsed_outputs) == expected_count, (
+    f"Parsed {len(parsed_outputs)} outputs but expected {expected_count}. "
+    "This indicates parsing or generation failed."
+)
+assert all(o and o.strip() for o in parsed_outputs), "Empty generation detected."
 for prompt_output, prompt_keywords in zip(
         parsed_outputs, expected_keywords[model_name][modality]):

---

3034-3043: Phi‑4MM sanity: add minimal asserts like in image/video tests

Same bypass risk here. Add count/non-empty asserts before the loop.

Apply this diff:

 parsed_outputs = parse_output(output)
+expected_count = len(accuracy_inputs[modality]["prompt"])
+assert len(parsed_outputs) == expected_count, "Parsed outputs count mismatch."
+assert all(o and o.strip() for o in parsed_outputs), "Empty generation detected."
 for prompt_output, prompt_keywords in zip(parsed_outputs,
                                           expected_keywords[modality]):

---

3142-3153: 2‑GPU MM sanity: assert output count to avoid silent passes

Add the same output-count/non-empty checks here.

Apply this diff:

 parsed_outputs = parse_output(output)
+expected_count = len(accuracy_inputs["image"]["prompt"])
+assert len(parsed_outputs) == expected_count, "Parsed outputs count mismatch."
+assert all(o and o.strip() for o in parsed_outputs), "Empty generation detected."
 for prompt_output, prompt_keywords in zip(
         parsed_outputs, expected_keywords[model_name]["image"]):

---

3250-3265: Multiturn MM sanity: assert output count and non‑empty generations

Same rationale; prevents false positives when match_ratio = 0.0.

Apply this diff:

 parsed_outputs = parse_output(output)
+expected_count = len(accuracy_inputs["image"]["prompt"])
+assert len(parsed_outputs) == expected_count, "Parsed outputs count mismatch."
+assert all(o and o.strip() for o in parsed_outputs), "Empty generation detected."
 for prompt_output, prompt_keywords in zip(
         parsed_outputs, expected_keywords[model_name]["image"]):

🧹 Nitpick comments (2)

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

2648-2657: Local media assets: add existence guard to avoid brittle CI failures

Good switch to local files. Guard for missing assets and skip with a clear reason.

Apply this diff near the functionality_inputs definition (right after it):

 functionality_inputs = {
   ...
 }
+# Ensure media files exist; skip gracefully if not present.
+media_files = [p for p in functionality_inputs[modality]["media"] if p]
+missing = [p for p in media_files if not os.path.exists(p)]
+if missing:
+    pytest.skip(f"Missing test media files: {missing}")

---

2819-2828: Explicit 0.0 thresholds acknowledged

OK to bypass for now; please add a TODO with NVBug IDs and revert plan/date so it’s not forgotten.

📜 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 d43036e and 9ad6238.

📒 Files selected for processing (6)

• tests/integration/defs/accuracy/references/mmmu.yaml (1 hunks)
• tests/integration/defs/accuracy/test_llm_api_pytorch.py (1 hunks)
• tests/integration/defs/test_e2e.py (8 hunks)
• tests/integration/test_lists/qa/llm_function_core.txt (1 hunks)
• tests/integration/test_lists/qa/llm_function_l20.txt (1 hunks)
• tests/integration/test_lists/qa/llm_function_nim.txt (1 hunks)

🧰 Additional context used

🧠 Learnings (8)

📓 Common learnings

Learnt from: tongyuantongyu
Repo: NVIDIA/TensorRT-LLM PR: 7781
File: tests/integration/test_lists/waives.txt:313-313
Timestamp: 2025-09-17T02:48:52.732Z
Learning: In TensorRT-LLM, `tests/integration/test_lists/waives.txt` is specifically for waiving/skipping tests, while other test list files like those in `test-db/` and `qa/` directories are for different test execution contexts (pre-merge, post-merge, QA tests). The same test appearing in both waives.txt and execution list files is intentional - the test is part of test suites but will be skipped due to the waiver.

Learnt from: djns99
Repo: NVIDIA/TensorRT-LLM PR: 6915
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:4010-4012
Timestamp: 2025-08-14T23:23:27.449Z
Learning: For MOE (Mixture of Experts) code reviews in TensorRT-LLM, avoid repeatedly suggesting finalize fusion validation checks and safety assertions. The user djns99 has indicated these suggestions are repetitive and unwanted across multiple MOE-related changes.

📚 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/defs/accuracy/test_llm_api_pytorch.py
• tests/integration/test_lists/qa/llm_function_core.txt
• tests/integration/test_lists/qa/llm_function_l20.txt
• tests/integration/test_lists/qa/llm_function_nim.txt
• tests/integration/defs/test_e2e.py

📚 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/defs/accuracy/test_llm_api_pytorch.py
• tests/integration/test_lists/qa/llm_function_core.txt
• tests/integration/test_lists/qa/llm_function_l20.txt
• tests/integration/test_lists/qa/llm_function_nim.txt
• tests/integration/defs/test_e2e.py

📚 Learning: 2025-08-09T02:04:49.623Z

Learnt from: Fridah-nv
Repo: NVIDIA/TensorRT-LLM PR: 6760
File: tensorrt_llm/_torch/auto_deploy/models/quant_config_reader.py:81-98
Timestamp: 2025-08-09T02:04:49.623Z
Learning: In TensorRT-LLM's auto_deploy module, torch.dtype values in configuration dictionaries must be stored as string representations (e.g., "float16" instead of torch.float16) because OmegaConf.merge does not support torch.dtype types. These string representations are converted to actual torch.dtype objects in downstream code.

Applied to files:

• tests/integration/test_lists/qa/llm_function_core.txt
• tests/integration/test_lists/qa/llm_function_l20.txt

📚 Learning: 2025-09-17T02:48:52.732Z

Learnt from: tongyuantongyu
Repo: NVIDIA/TensorRT-LLM PR: 7781
File: tests/integration/test_lists/waives.txt:313-313
Timestamp: 2025-09-17T02:48:52.732Z
Learning: In TensorRT-LLM, `tests/integration/test_lists/waives.txt` is specifically for waiving/skipping tests, while other test list files like those in `test-db/` and `qa/` directories are for different test execution contexts (pre-merge, post-merge, QA tests). The same test appearing in both waives.txt and execution list files is intentional - the test is part of test suites but will be skipped due to the waiver.

Applied to files:

• tests/integration/test_lists/qa/llm_function_l20.txt
• tests/integration/test_lists/qa/llm_function_nim.txt

📚 Learning: 2025-08-06T13:58:07.506Z

Learnt from: galagam
Repo: NVIDIA/TensorRT-LLM PR: 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_function_l20.txt
• tests/integration/test_lists/qa/llm_function_nim.txt

📚 Learning: 2025-10-20T17:09:21.560Z

Learnt from: nvchenghaoz
Repo: NVIDIA/TensorRT-LLM PR: 8469
File: tensorrt_llm/_torch/auto_deploy/transform/library/rms_norm.py:180-182
Timestamp: 2025-10-20T17:09:21.560Z
Learning: In tensorrt_llm/_torch/auto_deploy/transform/library/rms_norm.py, the _gated_rmsnorm_replacement function does not need to cast the output of torch.ops.auto_deploy.torch_rmsnorm_gated back to the input dtype, even though the custom op returns fp32. The dtype handling is managed elsewhere or the fp32 output is acceptable for downstream consumers.

Applied to files:

• tests/integration/test_lists/qa/llm_function_l20.txt

📚 Learning: 2025-08-29T14:07:45.863Z

Learnt from: EmmaQiaoCh
Repo: NVIDIA/TensorRT-LLM PR: 7370
File: tests/unittest/trt/model_api/test_model_quantization.py:24-27
Timestamp: 2025-08-29T14:07:45.863Z
Learning: In TensorRT-LLM's CI infrastructure, pytest skip markers (pytest.mark.skip) are properly honored even when test files have __main__ blocks that call test functions directly. The testing system correctly skips tests without requiring modifications to the __main__ block execution pattern.

Applied to files:

• tests/integration/defs/test_e2e.py

🧬 Code graph analysis (1)

tests/integration/defs/accuracy/test_llm_api_pytorch.py (5)

tests/integration/defs/accuracy/accuracy_core.py (4)

• LlmapiAccuracyTestHarness (844-855)
• MMMU (384-401)
• evaluate (184-245)
• evaluate (763-773)

tests/integration/defs/conftest.py (1)

• llm_models_root (79-93)

tensorrt_llm/sampling_params.py (1)

• SamplingParams (126-512)

tensorrt_llm/evaluate/lm_eval.py (2)

• MMMU (620-666)
• evaluate (385-417)

tensorrt_llm/llmapi/llm_args.py (1)

• KvCacheConfig (976-1110)

⏰ 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 (7)

tests/integration/test_lists/qa/llm_function_core.txt (1)

600-601: New accuracy test entry looks correct

Entry for TestPhi4MMFusedVisionLora added consistently. No concerns.

Based on learnings

tests/integration/test_lists/qa/llm_function_l20.txt (1)

44-45: Mirrored Phi‑4MM fused LoRA entry in L20 list

LGTM; duplication across lists is intentional for different contexts.

Based on learnings

tests/integration/test_lists/qa/llm_function_nim.txt (1)

351-352: NIM list updated with Phi‑4MM fused LoRA

Looks good and consistent with other QA lists.

Based on learnings

tests/integration/defs/accuracy/references/mmmu.yaml (1)

5-6: Key usage verified—LGTM

Confirmed the consumer uses the exact key microsoft/Phi-4-multimodal-instruct to join results. The AccuracyTask.__init__ method performs a direct YAML lookup via .get(model_name, []) where model_name is passed as the test's MODEL_NAME. The added entry matches the key used by TestPhi4MM class and aligns with entries in other reference files (gsm8k.yaml, mmlu.yaml).

tests/integration/defs/accuracy/test_llm_api_pytorch.py (3)

3650-3667: Implementation aligns with PR objectives.

The new test class successfully adds MMMU accuracy testing for the Phi-4 multimodal model with fused vision LoRA, as stated in the PR objectives. The implementation:

• Follows established patterns from similar VLM test classes (TestQwen2_VL_7B, TestNano_V2_VLM)
• Properly extends LlmapiAccuracyTestHarness
• Configures appropriate sampling parameters and KV cache settings
• Uses the MMMU evaluation task correctly

The structure is sound, pending verification of the specific configuration choices (stop token and resource requirements) noted in previous comments.

---

3650-3660: Verify the stop token and model path in your test environment.

The new test class follows established patterns in the codebase. However, verification of two items requires manual confirmation:

1. Stop token "<|USER|>": This differs from other VLM tests (which use "<|endoftext|>"). Confirm this is the correct stop token for Phi-4-multimodal-instruct with fused vision LoRA by checking the model's official documentation or card.

2. Model path: Verify that {llm_models_root()}/multimodals/Phi-4-multimodal-instruct-fuse-vision-lora exists and is accessible in your test environment before running the test.

---

3661-3667: Verify if resource decorators are needed for this multimodal test.

The test method at lines 3661-3667 in TestPhi4MMFusedVisionLora currently has no resource decorators. While similar multimodal/VLM tests in the codebase do use decorators:

• TestQwQ_32B.test_auto_dtype_tp4 uses @pytest.mark.skip_less_device_memory(80000) and @pytest.mark.skip_less_device(4)
• TestLlama3_1_8B.test_auto_dtype uses @pytest.mark.skip_less_device_memory(32000)

Given that this test uses MAX_NUM_TOKENS=25600 with multimodal evaluation, consider verifying whether resource decorators should be added (e.g., @pytest.mark.skip_less_device_memory(...)) to prevent failures on hardware with limited GPU memory.

[Wanli-Jiang]

/bot run

[tensorrt-cicd]

PR_Github #24582 [ run ] triggered by Bot. Commit: f2671bf

[tensorrt-cicd]

PR_Github #24582 [ run ] completed with state FAILURE. Commit: f2671bf
/LLM/release-1.1/L0_MergeRequest_PR pipeline #494 completed with status: 'FAILURE'

[Wanli-Jiang]

/bot run

[tensorrt-cicd]

PR_Github #24594 [ run ] triggered by Bot. Commit: 8eba7ea

[tensorrt-cicd]

PR_Github #24594 [ run ] completed with state FAILURE. Commit: 8eba7ea
/LLM/release-1.1/L0_MergeRequest_PR pipeline #495 completed with status: 'FAILURE'

[Wanli-Jiang]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #24647 [ run ] triggered by Bot. Commit: 8eba7ea

[tensorrt-cicd]

PR_Github #24647 [ run ] completed with state SUCCESS. Commit: 8eba7ea
/LLM/release-1.1/L0_MergeRequest_PR pipeline #498 completed with status: 'FAILURE'

[Wanli-Jiang]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #24725 [ run ] triggered by Bot. Commit: ef8ec52

[tensorrt-cicd]

PR_Github #24725 [ run ] completed with state SUCCESS. Commit: ef8ec52
/LLM/release-1.1/L0_MergeRequest_PR pipeline #500 completed with status: 'FAILURE'

[Wanli-Jiang]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #24747 [ run ] triggered by Bot. Commit: e84da2a

[tensorrt-cicd]

PR_Github #24747 [ run ] completed with state SUCCESS. Commit: e84da2a
/LLM/release-1.1/L0_MergeRequest_PR pipeline #501 completed with status: 'SUCCESS'