[https://nvbugs/5744427][fix] Make Gemma3 multimodal test fp8

[brb-nv]

Description

Currently, Gemma3 27B VLM runs on a tight memory budget on H100 PCIe and goes OOM intermittently. This MR replaced BF16 test with FP8 test.

Test Coverage

$ pytest tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py::TestGemma3_27BInstruct::test_fp8_prequantized -s -v

PR Checklist

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[brb-nv]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #30294 [ run ] triggered by Bot. Commit: e7fad07

[coderabbitai]

📝 Walkthrough

Walkthrough

The PR refactors Gemma3-27B Instruct tests from auto dtype inference to explicit FP8 quantization. Test method is renamed to test_fp8_prequantized, model path updated to FP8-quantized variant, and accuracy reference metadata updated with FP8 quantization parameters.

Changes

Cohort / File(s)	Summary
Test Configuration Updates tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py	Test method renamed from test_auto_dtype to test_fp8_prequantized; updated model path to FP8-quantized variant; added dtype="fp8" to KvCacheConfig; added cuda_graph_config=None parameter to LLM invocation.
Accuracy Reference Metadata tests/integration/defs/accuracy/references/mmmu.yaml	Added FP8 quantization metadata for google/gemma-3-27b-it: quant_algo: FP8 and kv_cache_quant_algo: FP8; updated accuracy value from 52.0 to 51.0.
Test List Updates tests/integration/test_lists/qa/llm_function_core.txt, llm_function_core_sanity.txt, llm_function_nim.txt, test-db/l0_h100.yml	Updated test references across four list files to replace TestGemma3_27BInstruct::test_auto_dtype with TestGemma3_27BInstruct::test_fp8_prequantized in multimodal accuracy suite.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~8 minutes

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

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.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly describes the main change: converting the Gemma3 multimodal test to use FP8 quantization instead of auto dtype.
Description check	✅ Passed	PR description includes required sections (Description, Test Coverage, PR Checklist) with clear explanation of the issue and solution, though the description section is brief.

✨ Finishing touches

• 📝 Generate docstrings

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[tensorrt-cicd]

PR_Github #30294 [ run ] completed with state SUCCESS. Commit: e7fad07
/LLM/main/L0_MergeRequest_PR pipeline #23328 completed with status: 'SUCCESS'

[brb-nv]

Test passed in pre-merge as part of H100_PCIe-PyTorch-3 stage.

[brb-nv]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #30309 [ run ] triggered by Bot. Commit: 2894a1b

[tensorrt-cicd]

PR_Github #30309 [ run ] completed with state SUCCESS. Commit: 2894a1b
/LLM/main/L0_MergeRequest_PR pipeline #23343 completed with status: 'FAILURE'

⚠️ Action Required:

• Please check the failed tests and fix your PR
• If you cannot view the failures, ask the CI triggerer to share details
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[brb-nv]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #30316 [ run ] triggered by Bot. Commit: 2894a1b

[tensorrt-cicd]

PR_Github #30316 [ run ] completed with state SUCCESS. Commit: 2894a1b
/LLM/main/L0_MergeRequest_PR pipeline #23350 completed with status: 'SUCCESS'