TensorRT-LLMs/tests/integration/test_lists/qa
Chuang Zhu 595f78078c
[https://nvbugs/5624367][fix] Fix disagg GPT-OSS test (#8870)
Signed-off-by: Chuang Zhu <111838961+chuangz0@users.noreply.github.com>
2025-11-05 01:47:09 -08:00
..
.gitignore Update (#2978) 2025-03-23 16:39:35 +08:00
llm_digits_func.txt [TRTLLM-6928][fix] Refactor multimodal unittest (#8453) 2025-11-03 06:01:07 -08:00
llm_digits_perf.txt [None][doc] add introduction doc on qa test (#6535) 2025-08-05 17:02:17 +08:00
llm_function_core_sanity.txt [https://nvbugs/5624367][fix] Fix disagg GPT-OSS test (#8870) 2025-11-05 01:47:09 -08:00
llm_function_core.txt [https://nvbugs/5624367][fix] Fix disagg GPT-OSS test (#8870) 2025-11-05 01:47:09 -08:00
llm_function_gb20x.txt [TRTLLM-6928][fix] Refactor multimodal unittest (#8453) 2025-11-03 06:01:07 -08:00
llm_function_l20.txt [TRTLLM-6928][fix] Refactor multimodal unittest (#8453) 2025-11-03 06:01:07 -08:00
llm_function_multinode.txt [None][feat] add Nemotron-Ultra multi nodes eval tests (#8577) 2025-10-23 02:44:26 -04:00
llm_function_nim.txt [https://nvbugs/5624367][fix] Fix disagg GPT-OSS test (#8870) 2025-11-05 01:47:09 -08:00
llm_function_rtx6k.txt [https://nvbugs/5540752][fix] Support quantized Phi4 MM models (#8190) 2025-10-20 06:36:09 -04:00
llm_function_stress.txt [None][test] Add accuracy benchmark in stress test (#7561) 2025-09-19 16:09:46 +08:00
llm_perf_cluster_nim.yml [https://nvbugs/5564465][test] ensure deepseek_v3_lite isl + osl < max_seq_len (#8565) 2025-10-28 15:25:52 +08:00
llm_perf_cluster.yml [https://nvbugs/5564465][test] ensure deepseek_v3_lite isl + osl < max_seq_len (#8565) 2025-10-28 15:25:52 +08:00
llm_perf_core.yml [https://nvbugs/5564465][test] ensure deepseek_v3_lite isl + osl < max_seq_len (#8565) 2025-10-28 15:25:52 +08:00
llm_perf_nim.yml [TRTLLM-8991][test] Add Llama 3.3 70B model with different performance config (#8753) 2025-11-03 13:34:06 +08:00
llm_perf_sanity.yml [https://nvbugs/5564465][test] ensure deepseek_v3_lite isl + osl < max_seq_len (#8565) 2025-10-28 15:25:52 +08:00
llm_triton_integration.txt [None][doc] add introduction doc on qa test (#6535) 2025-08-05 17:02:17 +08:00
llm_trt_integration_perf_sanity.yml [None][test] correct test-db context for perf yaml file (#6686) 2025-08-07 02:47:10 -04:00
llm_trt_integration_perf.yml [None][test] correct test-db context for perf yaml file (#6686) 2025-08-07 02:47:10 -04:00
README.md [None][test] update nim and full test list (#7468) 2025-09-04 09:06:01 -04:00

Description

This folder contains QA test definitions for TensorRT-LLM, which are executed on a daily/release schedule. These tests focus on end-to-end validation, accuracy verification, disaggregated testing, and performance benchmarking.

Test Categories

QA tests are organized into three main categories:

1. Functional Tests

Functional tests include E2E (end-to-end), accuracy, and disaggregated test cases:

  • E2E Tests: Complete workflow validation from model loading to inference output
  • Accuracy Tests: Model accuracy verification against reference implementations
  • Disaggregated Tests: Distributed deployment and multi-node scenario validation

2. Performance Tests

Performance tests focus on benchmarking and performance validation:

  • Baseline performance measurements
  • Performance regression detection
  • Throughput and latency benchmarking
  • Resource utilization analysis

3. Triton Backend Tests

Triton backend tests validate the integration with NVIDIA Triton Inference Server:

  • Backend functionality validation
  • Model serving capabilities
  • API compatibility testing
  • Integration performance testing

Dependencies

The following Python packages are required for running QA tests:

pip3 install -r ${TensorRT-LLM_PATH}/requirements-dev.txt

Dependency Details

  • mako: Template engine for test generation and configuration
  • oyaml: YAML parser with ordered dictionary support
  • rouge_score: ROUGE evaluation metrics for text generation quality assessment
  • lm_eval: Language model evaluation framework

Test Files

This directory contains various test configuration files:

Functional Test Lists

  • llm_function_core.txt - Primary test list for single node multi-GPU scenarios (all new test cases should be added here)
  • llm_function_core_sanity.txt - Subset of examples for quick torch flow validation
  • llm_function_nim.txt - NIM-specific functional test cases
  • llm_function_multinode.txt - Multi-node functional test cases
  • llm_function_gb20x.txt - GB20X release test cases
  • llm_function_rtx6k.txt - RTX 6000 series specific tests
  • llm_function_l20.txt - L20 specific tests, only contains single gpu cases

Performance Test Files

  • llm_perf_full.yml - Main performance test configuration
  • llm_perf_cluster.yml - Cluster-based performance tests
  • llm_perf_sanity.yml - Performance sanity checks
  • llm_perf_nim.yml - NIM-specific performance tests
  • llm_trt_integration_perf.yml - Integration performance tests
  • llm_trt_integration_perf_sanity.yml - Integration performance sanity checks

Triton Backend Tests

  • llm_triton_integration.txt - Triton backend integration tests

Release-Specific Tests

  • llm_digits_func.txt - Functional tests for DIGITS release
  • llm_digits_perf.txt - Performance tests for DIGITS release

Test Execution Schedule

QA tests are executed on a regular schedule:

  • Weekly: Automated regression testing
  • Release: Comprehensive validation before each release
    • Full Cycle Testing: run all gpu with llm_function_core.txt + run NIM specific gpu with llm_function_nim.txt
    • Sanity Cycle Testing: run all gpu with llm_function_core_sanity.txt
    • NIM Cycle Testing: run all gpu with llm_function_core_sanity.txt + run NIM specific gpu with llm_function_nim.txt
  • On-demand: Manual execution for specific validation needs

Running Tests

Manual Execution

To run specific test categories:

# direct to defs folder
cd tests/integration/defs
# Run all fp8 functional test
pytest --no-header -vs --test-list=../test_lists/qa/llm_function_full.txt -k fp8
# Run a single test case
pytest -vs accuracy/test_cli_flow.py::TestLlama3_1_8B::test_auto_dtype

Automated Execution

QA tests are typically executed through CI/CD pipelines with appropriate test selection based on:

  • Release requirements
  • Hardware availability
  • Test priority and scope

Test Guidelines

Adding New Test Cases

  • Primary Location: For functional testing, new test cases should be added to llm_function_full.txt first
  • Categorization: Test cases should be categorized based on their scope and execution time
  • Validation: Ensure test cases are properly validated before adding to any test list