Function start

tensorboard/manager.py:425–494

Start a new TensorBoard instance, or reuse a compatible one. If the cache key determined by the provided arguments and the current working directory (see `cache_key`) matches the cache key of a running TensorBoard process (see `get_all`), that process will be reused. Otherwise, a n

(arguments, timeout=datetime.timedelta(seconds=60))

def start(arguments, timeout=datetime.timedelta(seconds=60)):
    """Start a new TensorBoard instance, or reuse a compatible one.

    If the cache key determined by the provided arguments and the current
    working directory (see `cache_key`) matches the cache key of a running
    TensorBoard process (see `get_all`), that process will be reused.

    Otherwise, a new TensorBoard process will be spawned with the provided
    arguments, using the `tensorboard` binary from the system path.

    Args:
      arguments: List of strings to be passed as arguments to
        `tensorboard`. (If you have a raw command-line string, see
        `shlex.split`.)
      timeout: `datetime.timedelta` object describing how long to wait for
        the subprocess to initialize a TensorBoard server and write its
        `TensorBoardInfo` file. If the info file is not written within
        this time period, `start` will assume that the subprocess is stuck
        in a bad state, and will give up on waiting for it and return a
        `StartTimedOut` result. Note that in such a case the subprocess
        will not be killed. Default value is 60 seconds.

    Returns:
      A `StartReused`, `StartLaunched`, `StartFailed`, or `StartTimedOut`
      object.
    """
    this_cache_key = cache_key(
        working_directory=os.getcwd(),
        arguments=arguments,
        configure_kwargs={},
    )
    match = _find_matching_instance(this_cache_key)
    if match:
        return StartReused(info=match)

    (stdout_fd, stdout_path) = tempfile.mkstemp(prefix=".tensorboard-stdout-")
    (stderr_fd, stderr_path) = tempfile.mkstemp(prefix=".tensorboard-stderr-")
    start_time_seconds = time.time()
    explicit_tb = os.environ.get("TENSORBOARD_BINARY", None)
    try:
        p = subprocess.Popen(
            ["tensorboard" if explicit_tb is None else explicit_tb] + arguments,
            env=_subprocess_environ(),
            stdout=stdout_fd,
            stderr=stderr_fd,
        )
    except OSError as e:
        return StartExecFailed(os_error=e, explicit_binary=explicit_tb)
    finally:
        os.close(stdout_fd)
        os.close(stderr_fd)

    poll_interval_seconds = 0.5
    end_time_seconds = start_time_seconds + timeout.total_seconds()
    while time.time() < end_time_seconds:
        time.sleep(poll_interval_seconds)
        subprocess_result = p.poll()
        if subprocess_result is not None: