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@xinhe-nv xinhe-nv commented Aug 6, 2025

Summary by CodeRabbit

  • Tests
    • Added new accuracy reference entries for the Llama-3.3-70B-Instruct model with FP8 quantization settings across multiple benchmarks.
    • Removed skip entries for specific Llama-3.1-8B and Llama-3.3-70B FP8-related tests, enabling them to run as part of the test suite.
    • Updated skip entries to reflect current bug tracking for select Llama-3.3-70B FP8 tests.
    • Introduced memory-based test skipping for Llama-3.3-70B-Instruct tests requiring at least 80 GB of device memory.
    • Improved server readiness checks by adding a timeout to prevent indefinite waiting during test setup.

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📝 Walkthrough

Walkthrough

Additional entries specifying kv_cache_quant_algo: FP8 were added to the accuracy reference YAML files for the meta-llama/Llama-3.3-70B-Instruct model, duplicating existing quant_algo: FP8 entries. Three skip entries related to FP8 tests were removed from the test waive list, and one new skip entry was added referencing a different bug. Pytest markers were added to skip tests if device memory is insufficient. The infinite wait loop for disaggregated serving health was replaced with a time-bounded wait.

Changes

Cohort / File(s) Change Summary
Accuracy Reference Updates
tests/integration/defs/accuracy/references/gpqa_diamond.yaml, tests/integration/defs/accuracy/references/gsm8k.yaml, tests/integration/defs/accuracy/references/mmlu.yaml
Added duplicate accuracy entries for meta-llama/Llama-3.3-70B-Instruct with both quant_algo: FP8 and kv_cache_quant_algo: FP8, matching existing accuracy values.
Test Waive List Cleanup and Update
tests/integration/test_lists/waives.txt
Removed three skip entries related to FP8 tests referencing bug https://nvbugs/5409414. Added one new skip entry for TestLlama3_3_70BInstruct::test_fp8_tp4 referencing bug https://nvbugs/5440241.
Test Class Pytest Marker Additions
tests/integration/defs/accuracy/test_cli_flow.py, tests/integration/defs/accuracy/test_llm_api_pytorch.py
Added @pytest.mark.skip_less_device_memory(80000) decorator to TestLlama3_3_70BInstruct class to skip tests if device memory is below 80,000 MB.
Disaggregated Serving Health Check Timeout
tests/integration/defs/accuracy/test_disaggregated_serving.py
Replaced infinite loop waiting for server health with a loop bounded by a 3600-second timeout, checking health endpoint once per second.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~8 minutes

Possibly related PRs

Suggested labels

Speculative Decoding, Disaggregated Serving, CI

Suggested reviewers

  • LarryXFly
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Reviewing files that changed from the base of the PR and between 47ec440 and 608eb35.

📒 Files selected for processing (7)
  • tests/integration/defs/accuracy/references/gpqa_diamond.yaml (1 hunks)
  • tests/integration/defs/accuracy/references/gsm8k.yaml (1 hunks)
  • tests/integration/defs/accuracy/references/mmlu.yaml (1 hunks)
  • tests/integration/defs/accuracy/test_cli_flow.py (1 hunks)
  • tests/integration/defs/accuracy/test_disaggregated_serving.py (1 hunks)
  • tests/integration/defs/accuracy/test_llm_api_pytorch.py (1 hunks)
  • tests/integration/test_lists/waives.txt (1 hunks)
✅ Files skipped from review due to trivial changes (3)
  • tests/integration/defs/accuracy/references/gpqa_diamond.yaml
  • tests/integration/defs/accuracy/test_cli_flow.py
  • tests/integration/defs/accuracy/test_llm_api_pytorch.py
🚧 Files skipped from review as they are similar to previous changes (3)
  • tests/integration/defs/accuracy/references/mmlu.yaml
  • tests/integration/defs/accuracy/references/gsm8k.yaml
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PR: NVIDIA/TensorRT-LLM#5616
File: tensorrt_llm/executor/worker.py:375-384
Timestamp: 2025-07-17T09:01:27.402Z
Learning: In tensorrt_llm/executor/worker.py, the LoRA adapter cache optimization logic that checks `is_adapter_in_cpu_cache()` and conditionally passes None for weights/config has a known race condition issue that cannot be solved with simple error handling or verification checks. This is a known limitation that requires a more comprehensive solution.
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tests/integration/defs/accuracy/test_disaggregated_serving.py (1)

149-150: LGTM! Excellent improvement to prevent indefinite test hangs.

Replacing the infinite loop with a time-bounded wait (3600 seconds) is a crucial improvement that prevents tests from hanging indefinitely if the disaggregated server fails to start. The timeout aligns with the --server_start_timeout parameter and still allows for early exit when the health endpoint responds successfully.

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@xinhe-nv xinhe-nv force-pushed the user/xinhe/fix branch 2 times, most recently from f9f7992 to 1112768 Compare August 6, 2025 08:59
@xinhe-nv xinhe-nv changed the title [None][fix] fix Not registered specs [https://nvbugs/5409414][fix] fix Not registered specs Aug 6, 2025
@xinhe-nv xinhe-nv marked this pull request as ready for review August 6, 2025 09:16
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xinhe-nv commented Aug 6, 2025

/bot run

@xinhe-nv xinhe-nv enabled auto-merge (squash) August 6, 2025 09:16
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PR_Github #14289 [ run ] triggered by Bot

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PR_Github #14289 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #10793 completed with status: 'FAILURE'

Signed-off-by: Xin He (SW-GPU) <200704525+xinhe-nv@users.noreply.github.com>
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xinhe-nv commented Aug 7, 2025

/bot run

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PR_Github #14369 [ run ] triggered by Bot

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PR_Github #14369 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #10860 completed with status: 'FAILURE'

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xinhe-nv commented Aug 7, 2025

/bot run

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PR_Github #14396 [ run ] triggered by Bot

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PR_Github #14396 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #10882 completed with status: 'FAILURE'

@LarryXFly LarryXFly disabled auto-merge August 7, 2025 07:55
@LarryXFly LarryXFly merged commit 0a467b0 into NVIDIA:main Aug 7, 2025
3 checks passed
@xinhe-nv xinhe-nv deleted the user/xinhe/fix branch August 7, 2025 08:08
Shunkangz pushed a commit to hcyezhang/TensorRT-LLM that referenced this pull request Aug 8, 2025
Signed-off-by: Xin He (SW-GPU) <200704525+xinhe-nv@users.noreply.github.com>
Co-authored-by: Larry <197874197+LarryXFly@users.noreply.github.com>
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4 participants