# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 """ Test suite for profile_sla aiconfigurator functionality. profile_sla should be able to use aiconfigurator functionality even without access to any GPU system. """ import sys from pathlib import Path import pytest # Add the project root to sys.path to enable imports project_root = Path(__file__).parent.parent.parent sys.path.insert(0, str(project_root)) from benchmarks.profiler.profile_sla import run_profile # noqa: E402 from benchmarks.profiler.utils.model_info import ModelInfo # noqa: E402 # Override the logger fixture from conftest.py to prevent directory creation @pytest.fixture(autouse=True) def logger(request): """Override the logger fixture to prevent test directory creation. This replaces the logger fixture from tests/conftest.py that creates directories named after each test. """ # Simply do nothing - no directories created, no file handlers added yield class TestProfileSlaAiconfigurator: """Test class for profile_sla aiconfigurator functionality.""" @pytest.fixture def llm_args(self, request): class Args: def __init__(self): self.model = "" self.dgd_image = "" self.backend = "trtllm" self.config = "examples/backends/trtllm/deploy/disagg.yaml" # Use unique output directory per test for parallel execution self.output_dir = f"/tmp/test_profiling_results_{request.node.name}" self.namespace = f"test-namespace-{request.node.name}" self.min_num_gpus_per_engine = 1 self.max_num_gpus_per_engine = 8 self.skip_existing_results = False self.force_rerun = False self.isl = 3000 self.osl = 500 self.ttft = 50 self.itl = 10 self.prefill_interpolation_granularity = 16 self.decode_interpolation_granularity = 6 self.service_name = "" self.dry_run = False self.use_ai_configurator = True self.aic_system = "h200_sxm" self.aic_hf_id = "Qwen/Qwen3-32B" self.aic_backend = "" self.aic_backend_version = None self.num_gpus_per_node = 8 self.deploy_after_profile = False self.pick_with_webui = False # Provide minimal model_info to avoid HF queries self.model_info = ModelInfo( model_size=16384.0, architecture="TestArchitecture", is_moe=False, max_context_length=16384, ) return Args() @pytest.mark.pre_merge @pytest.mark.gpu_0 @pytest.mark.performance @pytest.mark.parallel @pytest.mark.asyncio @pytest.mark.parametrize("missing_arg", ["aic_system", "aic_hf_id"]) async def test_aiconfigurator_missing_args(self, llm_args, missing_arg): # Check that validation error happens when a required arg is missing. # Note: aic_backend_version is optional - when None, auto-detects latest version setattr(llm_args, missing_arg, None) with pytest.raises(ValueError): await run_profile(llm_args) @pytest.mark.pre_merge @pytest.mark.gpu_0 @pytest.mark.performance @pytest.mark.parallel @pytest.mark.asyncio @pytest.mark.parametrize( "arg_name, bad_value", [ # these values don't exist in the aiconfigurator database. ("aic_system", "fake_gpu_system"), ("aic_backend_version", "0.1.0"), ], ) async def test_aiconfigurator_no_data(self, llm_args, arg_name, bad_value): # Check that an appropriate error is raised when the system/model/backend # is not found in the aiconfigurator database. setattr(llm_args, arg_name, bad_value) with pytest.raises(ValueError, match="Database not found"): await run_profile(llm_args) @pytest.mark.pre_merge @pytest.mark.parallel @pytest.mark.asyncio @pytest.mark.gpu_1 @pytest.mark.performance async def test_trtllm_aiconfigurator_single_model(self, llm_args): # Test that profile_sla works with the model & backend in the llm_args fixture. await run_profile(llm_args) @pytest.mark.parallel @pytest.mark.asyncio @pytest.mark.gpu_1 @pytest.mark.nightly @pytest.mark.performance @pytest.mark.parametrize( "backend, aic_backend_version", [ ("trtllm", None), ("trtllm", "0.20.0"), ("trtllm", "1.0.0rc3"), ("vllm", None), ("vllm", "0.11.0"), ("sglang", None), ("sglang", "0.5.1.post1"), ], ) @pytest.mark.parametrize( "hf_model_id", [ "Qwen/Qwen3-32B", "meta-llama/Llama-3.1-405B", ], ) async def test_aiconfigurator_dense_models( self, llm_args, hf_model_id, backend, aic_backend_version ): # Test that profile_sla works with a variety of backend versions and model names. llm_args.aic_hf_id = hf_model_id llm_args.backend = backend llm_args.aic_backend_version = aic_backend_version await run_profile(llm_args)