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Signed-off-by: nv-guomingz <137257613+nv-guomingz@users.noreply.github.com> Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
54 lines
2.5 KiB
Markdown
54 lines
2.5 KiB
Markdown
# TensorRT LLM test definitions
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The following subfolder contains test definitions for Tensorrt LLM.
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## Directory structure
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~~~
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.
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└── integration # Root directory for integration tests
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├── defs # Test definitions
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├── perf_configs # Configs for perf tests
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└── test_lists # Test lists
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├── test-db # Test-DB that is the test list convention adopted by CI
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├── dev # Other test lists used by TRT LLM developers
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├── qa # Test lists used by QA
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└── waives.txt # Test waive list
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~~~
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- To run perf tests, you also need to first build the cpp benchmark by calling `build_wheel.py` with `--benchmarks` flag.
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## Run perf tests
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All the perf test names are in the form of `perf/test_perf.py::test_perf[...]` where the `...` part is the test parameters.
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Below are some specific pytest options used for perf tests
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```bash
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# execute these in the TensorRT LLM source repo root dir.
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# install dependencies, do not need to do it every time if already installed.
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pip install -r requirements-dev.txt
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# example 1: run a test case
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# For example, if QA reports a perf bug for `perf/test_perf.py::test_perf[llama_7b-cppmanager-exe-plugin_ifb-float16-input_output_len:128,128,+512,32]`, then you can repro it by running:
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cd LLM_ROOT/tests/integration/defs
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echo "perf/test_perf.py::test_perf[llama_7b-cppmanager-exe-plugin_ifb-float16-input_output_len:128,128,+512,32]" > perf.txt
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pytest --perf --test-list=perf.txt --output-dir=/workspace/test-log --perf-log-formats csv --perf-log-formats yaml
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```
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The captured perf metrics will be saved in `/workspace/test-log/perf_scripts_test_results.csv` or `/workspace/test-log/perf_scripts_test_results.yaml` depends on the option `--perf-log-formats`, and the test logs are saved in `/workspace/test-log/result.xmk`. Currently, we capture these perf metrics:
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1. `test_perf_metric_build_time`: The engine building time in seconds.
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2. `test_perf_metric_build_peak_cpu_memory`: The build-phase peak CPU mem usage in MB.
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3. `test_perf_metric_build_peak_gpu_memory`: The build-phase peak GPU mem usage in MB.
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4. `test_perf_metric_inference_time`: The inference latency in ms.
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5. `test_perf_metric_inference_peak_gpu_memory`: The inference-phase peak GPU mem usage in GB.
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6. `test_perf_metric_context_gpu_memory`: The context GPU mem usage in MB.
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## Common Issues and solutions
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1. No package 'libffi' found
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Install libffi by `sudo apt-get install libffi-dev` and rerun.
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