[TRTLLM-9551][infra] Partition test_llm_pytorch.py for parallel execution#10400
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📝 WalkthroughWalkthroughThe changes partition the Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes Pre-merge checks and finishing touches❌ Failed checks (1 warning)
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🧠 Learnings (8)📓 Common learnings📚 Learning: 2025-09-09T09:40:45.658ZApplied to files:
📚 Learning: 2025-09-17T02:48:52.732ZApplied to files:
📚 Learning: 2025-08-26T09:49:04.956ZApplied to files:
📚 Learning: 2025-07-28T17:06:08.621ZApplied to files:
📚 Learning: 2025-08-29T14:07:45.863ZApplied to files:
📚 Learning: 2025-07-17T09:01:27.402ZApplied to files:
📚 Learning: 2025-08-06T13:58:07.506ZApplied to files:
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tests/unittest/llmapi/test_llm_pytorch.py (1)
824-837: Critical: Duplicate class definition will hide tests.
TestLlmErroris defined twice—once at line 824 and again at line 956. Python will use only the second definition, which means thetest_max_num_token_checkfrom the first class definition will be completely ignored during test execution.🔎 Proposed fix: Remove or rename one of the duplicate classes
If both test methods are intended to be distinct tests, rename one of the classes:
-class TestLlmError: +class TestLlmError2: @pytest.mark.part3 def test_max_num_token_check(self):If they're identical, remove the duplicate entirely.
Also applies to: 956-968
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tests/integration/test_lists/test-db/l0_a100.ymltests/integration/test_lists/test-db/l0_h100.ymltests/unittest/llmapi/test_llm_pytorch.py
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**/*.py
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**/*.py: 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 in Python, even if only one class or function from a module is used
Python files should use snake_case naming:some_file.py
Python classes should use PascalCase naming:class SomeClass
Python functions and methods should use snake_case naming:def my_awesome_function():
Python local variables should use snake_case naming:my_variable = ...
Python variable names that start with a number should be prefixed with 'k':k_99th_percentile = ...
Python global variables should use upper snake_case with prefix 'G':G_MY_GLOBAL = ...
Python constants should use upper snake_case naming: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
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Use Google style docstrings in Python for classes and functions, which can be parsed by Sphinx
Python attributes and variables can be documented inline with type and description
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When using try-except blocks in Python, limit the except 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, using the else block for logic
Files:
tests/unittest/llmapi/test_llm_pytorch.py
**/*.{cpp,h,cu,cuh,py}
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
All TensorRT-LLM Open Source Software code should contain an NVIDIA copyright header that includes the year of its latest meaningful modification
Files:
tests/unittest/llmapi/test_llm_pytorch.py
🧠 Learnings (8)
📓 Common learnings
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.
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: 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: 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.
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.
📚 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/test-db/l0_h100.ymltests/integration/test_lists/test-db/l0_a100.ymltests/unittest/llmapi/test_llm_pytorch.py
📚 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/test-db/l0_h100.ymltests/integration/test_lists/test-db/l0_a100.yml
📚 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/test-db/l0_h100.ymltests/integration/test_lists/test-db/l0_a100.ymltests/unittest/llmapi/test_llm_pytorch.py
📚 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/test-db/l0_h100.ymltests/integration/test_lists/test-db/l0_a100.ymltests/unittest/llmapi/test_llm_pytorch.py
📚 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/test_lists/test-db/l0_h100.ymltests/integration/test_lists/test-db/l0_a100.ymltests/unittest/llmapi/test_llm_pytorch.py
📚 Learning: 2025-07-17T09:01:27.402Z
Learnt from: amitz-nv
Repo: NVIDIA/TensorRT-LLM PR: 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.
Applied to files:
tests/unittest/llmapi/test_llm_pytorch.py
📚 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/unittest/llmapi/test_llm_pytorch.py
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🔇 Additional comments (3)
tests/integration/test_lists/test-db/l0_h100.yml (1)
151-154: LGTM!The 4-way partitioning correctly splits test_llm_pytorch.py execution using pytest marker filters. Each invocation with
-m "part0"through-m "part3"will run a distinct subset of tests, enabling parallel execution without duplication.Based on learnings, the TensorRT-LLM CI infrastructure properly honors pytest markers even when test files have
__main__blocks.tests/integration/test_lists/test-db/l0_a100.yml (1)
16-19: LGTM!The 4-way partitioning mirrors the l0_h100.yml configuration and correctly implements parallel execution for A100 hardware. Each partition filter (
-m "part0"through-m "part3") will execute a distinct test subset, enabling the reported 74% reduction in CI execution time.tests/unittest/llmapi/test_llm_pytorch.py (1)
923-1209: Add partition markers to unmarked tests or confirm they should be excluded from partitioned execution.The following tests in this file lack
@pytest.mark.part0–@pytest.mark.part3markers:
test_llm_return_logprobs(line 923)test_llm_return_logprobs_streaming(line 945)test_llm_rpc(line 973)test_llm_rpc_streaming(line 991)test_llm_rpc_get_stats(line 1009)test_llm_rpc_get_stats_async(line 1034)When test execution uses
-m "part0"through-m "part3", pytest will deselect these unmarked tests. Confirm whether they should be included in partitioned test runs with an appropriate marker, or if their exclusion is intentional.
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PR_Github #30540 [ run ] triggered by Bot. Commit: |
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Enable 4-way parallel execution of test_llm_pytorch.py by adding pytest
partition markers and updating test list YAML files.
Changes:
- Added @pytest.mark.part{0,1,2,3} markers to all 29 tests in
test_llm_pytorch.py
- Updated l0_a100.yml and l0_h100.yml to run test_llm_pytorch.py
as 4 separate partitioned jobs
- Created backups of modified YAML files for rollback capability
- Generated test_list_update_summary.txt documenting the changes
Benefits:
- ~74% reduction in CI execution time (4-way parallelization)
- Balanced partition distribution with 4.7% variance
- Consistent with existing test_llm.py and test_llm_models.py patterns
Test partition distribution:
- part0: 8 tests
- part1: 8 tests
- part2: 6 tests
- part3: 7 tests
Signed-off-by: Superjomn <328693+Superjomn@users.noreply.github.com>
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PR_Github #30602 [ run ] triggered by Bot. Commit: |
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PR_Github #30602 [ run ] completed with state |
…tion (NVIDIA#10400) Signed-off-by: Superjomn <328693+Superjomn@users.noreply.github.com> Signed-off-by: Daniil Kulko <kulkodaniil@gmail.com>
3 participants
Enable 4-way parallel execution of test_llm_pytorch.py by adding pytest partition markers and updating test list YAML files.
Changes:
Benefits:
Test partition distribution:
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