# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. import logging import os import pytest from azureml.core import Experiment, RunConfiguration, ScriptRunConfig from tempeh.execution.azureml.environment_setup import configure_environment from conftest import get_all_perf_test_configurations from script_generation import generate_script all_perf_test_configurations = get_all_perf_test_configurations() all_perf_test_configurations_descriptions = \ [config.__repr__().replace(' ', '') for config in all_perf_test_configurations] SCRIPT_DIRECTORY = os.path.join('test', 'perf', 'scripts') EXPERIMENT_NAME = "perftest" logging.basicConfig(level=logging.DEBUG) # ensure the tests are run from the fairlearn repository base directory if not os.getcwd().endswith("fairlearn"): if not os.path.exists("test") or not os.path.exists("fairlearn"): raise Exception("Please run perf tests from the fairlearn repository base directory. " "Current working directory: {}".format(os.getcwd())) @pytest.mark.parametrize("perf_test_configuration", all_perf_test_configurations, ids=all_perf_test_configurations_descriptions) @pytest.mark.perf def test_perf(perf_test_configuration, workspace, request, wheel_file): print("Starting with test case {}".format(request.node.name)) script_name = determine_script_name(request.node.name) generate_script(request, perf_test_configuration, script_name, SCRIPT_DIRECTORY) experiment = Experiment(workspace=workspace, name=EXPERIMENT_NAME) compute_target = workspace.get_default_compute_target(type='cpu') run_config = RunConfiguration() run_config.target = compute_target environment = configure_environment(workspace, wheel_file=wheel_file) run_config.environment = environment environment.register(workspace=workspace) script_run_config = ScriptRunConfig(source_directory=SCRIPT_DIRECTORY, script=script_name, run_config=run_config) print("submitting run") experiment.submit(config=script_run_config, tags=perf_test_configuration.__dict__) print("submitted run") def determine_script_name(test_case_name): hashed_test_case_name = hash(test_case_name) hashed_test_case_name = hashed_test_case_name if hashed_test_case_name >= 0 \ else -1 * hashed_test_case_name return "{}.py".format(str(hashed_test_case_name))