TensorRT-LLMs/tests/integration

TensorRT LLM test definitions

The following subfolder contains test definitions for Tensorrt LLM.

Directory structure

.
└── integration              # Root directory for integration tests
    ├── defs            #     Test definitions
    ├── perf_configs    #     Configs for perf tests
    └── test_lists      #     Test lists
        ├── test-db     #         Test-DB that is the test list convention adopted by CI
        ├── dev         #         Other test lists used by TRT LLM developers
        ├── qa          #         Test lists used by QA
        └── waives.txt  #         Test waive list

• To run perf tests, you also need to first build the cpp benchmark by calling build_wheel.py with --benchmarks flag.

Run perf tests

All the perf test names are in the form of perf/test_perf.py::test_perf[...] where the ... part is the test parameters.

Below are some specific pytest options used for perf tests

# execute these in the tensorrt-llm source repo root dir.
# install dependencies, do not need to do it every time if already installed.
pip install -r requirements-dev.txt

# example 1: run a test case
# 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:
cd LLM_ROOT/tests/integration/defs
echo "perf/test_perf.py::test_perf[llama_7b-cppmanager-exe-plugin_ifb-float16-input_output_len:128,128,+512,32]" > perf.txt
pytest --perf --test-list=perf.txt --output-dir=/workspace/test-log --perf-log-formats csv --perf-log-formats yaml

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:

1. test_perf_metric_build_time: The engine building time in seconds.
2. test_perf_metric_build_peak_cpu_memory: The build-phase peak CPU mem usage in MB.
3. test_perf_metric_build_peak_gpu_memory: The build-phase peak GPU mem usage in MB.
4. test_perf_metric_inference_time: The inference latency in ms.
5. test_perf_metric_inference_peak_gpu_memory: The inference-phase peak GPU mem usage in GB.
6. test_perf_metric_context_gpu_memory: The context GPU mem usage in MB.

Common Issues and solutions

1. No package 'libffi' found Install libffi by sudo apt-get install libffi-dev and rerun.