[https://nvbugs/5630345][chore] unwaive DS-v32 nvfp4 and fp8 tests

[lfr-0531]

Summary by CodeRabbit

• Tests
  • Enhanced integration tests with intelligent memory-based skip conditions to prevent out-of-memory failures on resource-constrained devices, automatically skipping tests requiring more than 140GB of memory.
  • Removed deprecated skip configurations for legacy test baselines that are no longer necessary.

Description

Test Coverage

PR Checklist

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[lfr-0531]

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[coderabbitai]

📝 Walkthrough

Walkthrough

The PR adds device memory skip conditions to two GPU-intensive tests in the test suite and removes outdated skip entries from a waiver list, streamlining test execution based on hardware constraints.

Changes

Cohort / File(s)	Summary
Test Memory Skip Decorators tests/integration/defs/accuracy/test_llm_api_pytorch.py	Added @pytest.mark.skip_less_device_memory(140000) decorator to TestDeepSeekV32.test_fp8_blockscale and TestDeepSeekV3Lite.test_fp8_block_scales to gate execution on devices with less than 140 GB memory
Waiver List Cleanup tests/integration/test_lists/waives.txt	Removed SKIP entries for TestDeepSeekV32::test_nvfp4_multi_gpus test variants ([baseline], [baseline_mtp1], [baseline_fp8kv])

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

• Changes are purely configuration-based (decorator additions and waiver list removals)
• No logic modifications or error handling changes
• Consistent pattern applied across affected tests

Suggested reviewers

• chang-l
• EmmaQiaoCh

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The pull request description is incomplete. While the author has checked the PR checklist and included the repository template, the Description, Test Coverage, and substantive explanations of the issue and solution are entirely empty or contain only template placeholders. This fails to provide reviewers with meaningful context about why these tests are being unwaived, what the changes accomplish, or which tests safeguard the changes.	Fill in the Description section with a clear explanation of what problem the PR solves (e.g., why these tests were waived and why they can now be safely re-enabled). Add a Test Coverage section listing the specific tests affected (TestDeepSeekV32::test_fp8_blockscale, TestDeepSeekV3Lite::test_fp8_block_scales, and the nvfp4 tests being unwaived). Remove or update the template placeholder text to make the PR description substantive and reviewer-friendly.

✅ Passed checks (1 passed)

Check name	Status	Explanation
Title check	✅ Passed	The pull request title clearly and specifically describes the main changes. It references the NVBugs ticket ID [https://nvbugs/5630345], uses the appropriate [chore] type, and accurately summarizes the work: unwaiving (re-enabling) DeepSeek-v32 nvfp4 and fp8 tests that were previously skipped. This directly aligns with the code changes shown in the raw summary, which remove SKIP entries from the waives list and add device memory decorators to specific tests.

✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

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

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📜 Recent review details

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📥 Commits

Reviewing files that changed from the base of the PR and between db2a42f and eb73919.

📒 Files selected for processing (2)

• tests/integration/defs/accuracy/test_llm_api_pytorch.py (1 hunks)
• tests/integration/test_lists/waives.txt (0 hunks)

💤 Files with no reviewable changes (1)

• tests/integration/test_lists/waives.txt

🧰 Additional context used

📓 Path-based instructions (3)

**/*.{h,hpp,hh,hxx,cpp,cxx,cc,cu,cuh,py}

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• tests/integration/defs/accuracy/test_llm_api_pytorch.py

**/*.py

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Files:

• tests/integration/defs/accuracy/test_llm_api_pytorch.py

**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}

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• tests/integration/defs/accuracy/test_llm_api_pytorch.py

🧠 Learnings (2)

📓 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: 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*").

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.

📚 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/accuracy/test_llm_api_pytorch.py

⏰ 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/defs/accuracy/test_llm_api_pytorch.py (1)

2315-2315: LGTM! Memory requirement properly enforced for large-scale test.

The addition of the memory requirement decorator is appropriate for this GPU-intensive test that runs on 8 GPUs with FP8 quantization. The 140GB requirement correctly supersedes the class-level 80GB requirement and follows established patterns in the codebase.

Note: The AI summary mentions changes to both TestDeepSeekV32.test_fp8_blockscale and TestDeepSeekV3Lite.test_fp8_block_scales, but only the former is visible in the provided diff. You may want to verify that all intended changes were included in this PR.

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[tensorrt-cicd]

PR_Github #23404 [ run ] triggered by Bot. Commit: eb73919

[tensorrt-cicd]

PR_Github #23404 [ run ] completed with state SUCCESS. Commit: eb73919
/LLM/main/L0_MergeRequest_PR pipeline #17627 completed with status: 'SUCCESS'

[lfr-0531]

/bot run --stage-list "DGX_B200-8_GPUs-PyTorch-1, DGX_B200-4_GPUs-PyTorch-Post-Merge-1"

[tensorrt-cicd]

PR_Github #23436 [ run ] triggered by Bot. Commit: eb73919

[tensorrt-cicd]

PR_Github #23436 [ run ] completed with state SUCCESS. Commit: eb73919
/LLM/main/L0_MergeRequest_PR pipeline #17650 (Partly Tested) completed with status: 'FAILURE'