b7222818e9dd4d33ee933388e73a11ad8d0bf89b,tests/helper_functions.py,,score_model_in_sagemaker_docker_container,#Any#Any#,24

Before Change

    proc = Popen(["mlflow", "sagemaker", "run-local", "-m", model_path], stdout=PIPE, stderr=STDOUT,
                 universal_newlines=True, env=env)
    try:
        for i in range(0, 50):
            assert proc.poll() is None, "scoring process died"
            time.sleep(5)
            // noinspection PyBroadException
            try:
                ping_status = requests.get(url="http://localhost:5000/ping")
                print("connection attempt", i, "server is up! ping status", ping_status)
                if ping_status.status_code == 200:
                    break
            except Exception:  // pylint: disable=broad-except
                print("connection attempt", i, "failed, server is not up yet")

        assert proc.poll() is None, "scoring process died"
        ping_status = requests.get(url="http://localhost:5000/ping")
        print("server up, ping status", ping_status)
        if ping_status.status_code != 200:
            raise Exception("ping failed, server is not happy")
        if type(data) == pd.DataFrame:
            data = data.to_dict(orient="records")
        y = requests.post(url="http://localhost:5000/invocations", json=data)
        import json
        return json.loads(y.content)
    finally:
        if proc.poll() is None:
            proc.terminate()

After Change

                 universal_newlines=True, env=env)
    r = _score_proc(proc, 5000, data, "json").content
    import json
    return json.loads(r)  // TODO: we should return pd.Dataframe the same as pyfunc serve


def pyfunc_serve_and_score_model(model_path, data):

Instances