[None][test] Add DGX-Spark Perf QA test cases for single node #10497
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Signed-off-by: Jenny Liu <JennyLiu-nv+JennyLiu@users.noreply.github.com>
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📝 WalkthroughWalkthroughAdded model path mappings for multiple new models (Qwen3, Phi-4, DeepSeek, NVIDIA Nemotron) to configuration dictionaries. Removed existing test entries from performance test list. Introduced new integration test configuration file with hardware-specific constraints targeting PyTorch-based performance testing. Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~12 minutes 🚥 Pre-merge checks | ✅ 2 | ❌ 1❌ Failed checks (1 inconclusive)
✅ Passed checks (2 passed)
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Actionable comments posted: 2
🤖 Fix all issues with AI agents
In @tests/integration/defs/perf/test_perf.py:
- Around line 152-153: Remove the duplicate dictionary entry "starcoder2_7b"
(the second occurrence that follows "nvidia_nemotron_nano_9b_v2_nvfp4") so the
mapping only contains a single "starcoder2_7b" key (keep the original one
defined earlier), i.e., delete the later duplicate line and run tests to ensure
no regressions.
In @tests/integration/test_lists/qa/llm_digits_perf.yml:
- Around line 14-44: The test YAML references 21 model keys that aren't defined;
add entries for each missing model to the appropriate registry so tests can
resolve them: update MODEL_PATH_DICT (in test_perf.py) or HF_MODEL_PATH if using
HF names, or append the models to _allowed_configs in allowed_configs.py with
the correct config dicts (precision/engine/tag) matching existing entries;
ensure identifiers exactly match the names in the test list (e.g.,
"gpt_oss_20b_fp4", "qwen3_8b_fp8", "phi_4_reasoning_plus_fp4", etc.) and include
valid path/value strings used elsewhere so the perf tests load rather than fail.
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📒 Files selected for processing (3)
tests/integration/defs/perf/test_perf.pytests/integration/test_lists/qa/llm_digits_perf.txttests/integration/test_lists/qa/llm_digits_perf.yml
💤 Files with no reviewable changes (1)
- tests/integration/test_lists/qa/llm_digits_perf.txt
🧰 Additional context used
📓 Path-based instructions (2)
**/*.py
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
**/*.py: The code developed for TensorRT-LLM should conform to Python 3.8+
Indent Python code with 4 spaces. Do not use tabs
Always maintain the namespace when importing Python modules, even if only one class or function from a module is used
Python filenames should use snake_case (e.g.,some_file.py)
Python classes should use PascalCase (e.g.,class SomeClass)
Python functions and methods should use snake_case (e.g.,def my_awesome_function():)
Python local variables should use snake_case, with prefixkfor variable names that start with a number (e.g.,k_99th_percentile)
Python global variables should use upper snake_case with prefixG(e.g.,G_MY_GLOBAL)
Python constants should use upper snake_case (e.g.,MY_CONSTANT)
Avoid shadowing variables declared in an outer scope in Python
Initialize all externally visible members of a Python class in the constructor
For Python interfaces that may be used outside a file, prefer docstrings over comments
Use comments in Python for code within a function, or interfaces that are local to a file
Use Google-style docstrings for Python classes and functions, which can be parsed by Sphinx
Python attributes and variables can be documented inline with the format"""<type>: Description"""
Avoid using reflection in Python when functionality can be easily achieved without reflection
When using try-except blocks in Python, limit the except clause to the smallest set of errors possible
When using try-except blocks in Python to handle multiple possible variable types (duck-typing), keep the body of the try as small as possible and use the else block for the main logic
Files:
tests/integration/defs/perf/test_perf.py
**/*.{cpp,cc,cxx,h,hpp,hxx,cu,cuh,py}
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
All TensorRT-LLM source files (.cpp, .h, .cu, .py, and other source files) should contain an NVIDIA copyright header with the year of latest meaningful modification
Files:
tests/integration/defs/perf/test_perf.py
🧠 Learnings (7)
📓 Common learnings
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: 2025-08-26T09:49:04.956Z
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*").
Applied to files:
tests/integration/test_lists/qa/llm_digits_perf.yml
📚 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/qa/llm_digits_perf.yml
📚 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_digits_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/qa/llm_digits_perf.yml
📚 Learning: 2025-08-13T11:07:11.772Z
Learnt from: Funatiq
Repo: NVIDIA/TensorRT-LLM PR: 6754
File: tests/integration/test_lists/test-db/l0_a30.yml:41-47
Timestamp: 2025-08-13T11:07:11.772Z
Learning: In TensorRT-LLM test configuration files like tests/integration/test_lists/test-db/l0_a30.yml, TIMEOUT values are specified in minutes, not seconds.
Applied to files:
tests/integration/test_lists/qa/llm_digits_perf.yml
📚 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_digits_perf.yml
🪛 Ruff (0.14.10)
tests/integration/defs/perf/test_perf.py
153-153: Dictionary key literal "starcoder2_7b" repeated
Remove repeated key literal "starcoder2_7b"
(F601)
⏰ 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 (5)
tests/integration/test_lists/qa/llm_digits_perf.yml (1)
1-13: Configuration structure looks good.The hardware constraints appropriately target single-node DGX-Spark systems with GB10 GPUs and ARM architecture, matching the PR objectives for single-node performance testing.
tests/integration/defs/perf/test_perf.py (4)
103-104: LGTM.The new model path entry for
deepseek_r1_distill_llama_70bfollows the established pattern for DeepSeek models.
132-135: LGTM.The phi_4_multimodal_instruct FP4 and FP8 variants follow the established precision variant pattern and directory structure.
154-163: LGTM.The Qwen3 model variants follow a consistent naming pattern with appropriate precision suffixes and path structures.
164-166: No HF_MODEL_PATH entries are required for phi_4_reasoning_plus variants.The phi_4_reasoning_plus entries in MODEL_PATH_DICT are intended as local model paths (e.g.,
"Phi-4/Phi-4-reasoning-plus"), not HuggingFace models. HF_MODEL_PATH entries are only needed for models available directly from HuggingFace and are distinguished by the_hfsuffix (e.g.,phi_4_mini_instruct_hf). The MODEL_PATH_DICT entries for phi_4_reasoning_plus variants are correct as-is.
Signed-off-by: Jenny Liu <JennyLiu-nv+JennyLiu@users.noreply.github.com>
- Add Qwen2.5-VL-7B models (base, FP8, FP4) - Add Gemma-3-12B models (base, FP8, FP4) - Add Gemma-3-27B models (base, FP8, FP4) - Add corresponding test cases to llm_digits_perf.yml Signed-off-by: Jenny Liu <JennyLiu-nv+JennyLiu@users.noreply.github.com>
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Add DGX-Spark Perf QA test cases for single node
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