def METHOD_NAME():
    conditions = [
        CheckEndpoints(f"{INFERENCE_API_URL}/ping"),
        CheckEndpoints(f"{MANAGEMENT_API_URL}/models"),
        CheckEndpoints(OPENMETRICS_ENDPOINT),
        WaitFor(register_model, args=("linear_regression_1_1.mar",)),
        WaitFor(update_workers, args=("linear_regression_1_1", 2, 4)),
        WaitFor(run_prediction, args=("linear_regression_1_1",)),
        WaitFor(run_prediction, args=("linear_regression_1_2",)),
        WaitFor(run_prediction, args=("linear_regression_2_2",)),
        WaitFor(run_prediction, args=("linear_regression_2_3",)),
        WaitFor(run_prediction, args=("linear_regression_3_2",)),
        WaitFor(set_model_default_version, args=("linear_regression_1_2", "3")),
    ]
    with docker_run(
        compose_file=os.path.join(
            get_here(),
            "docker",
            "docker-compose.yaml",
        ),
        conditions=conditions,
        sleep=10,
        wrappers=[create_log_volumes()],
    ):
        for _ in range(10):
            for model in (
                "linear_regression_1_1",
                "linear_regression_1_2",
                "linear_regression_2_2",
                "linear_regression_2_3",
                "linear_regression_3_2",
            ):
                run_prediction(model)
        yield {
            "init_config": {
                "service": "my_torchserve",
            },
            "instances": [
                OPENMETRICS_INSTANCE,
                INFERENCE_INSTANCE,
                MANAGEMENT_INSTANCE,
            ],
        }, E2E_METADATA