def start_server()

in miscellaneous/distributed_tensorflow_mask_rcnn/container-serving-optimized/resources/serve.py [0:0]

• 27 lines of code
• 3 McCabe index (conditional complexity)

def start_server():
    print("Starting the inference server with {} workers.".format(model_server_workers))

    # link the log streams to stdout/err so they will be logged to the container logs
    subprocess.check_call(["ln", "-sf", "/dev/stdout", "/var/log/nginx/access.log"])
    subprocess.check_call(["ln", "-sf", "/dev/stderr", "/var/log/nginx/error.log"])

    nginx = subprocess.Popen(["nginx", "-c", "/nginx.conf"])
    gunicorn = subprocess.Popen(
        [
            "gunicorn",
            "--timeout",
            str(model_server_timeout),
            "-k",
            "gevent",
            "-b",
            "unix:/tmp/gunicorn.sock",
            "-w",
            str(model_server_workers),
            "wsgi:app",
        ]
    )

    signal.signal(signal.SIGTERM, lambda a, b: sigterm_handler(nginx.pid, gunicorn.pid))

    # If either subprocess exits, so do we.
    pids = set([nginx.pid, gunicorn.pid])
    while True:
        pid, _ = os.wait()
        if pid in pids:
            break

    sigterm_handler(nginx.pid, gunicorn.pid)
    print("Inference server exiting")