def download_file(url, dest=None, chunk_size=1024, replace="ask",
                  label="Downloading {dest_basename} ({size:.2f}MB)",
                  expected_extension=None):
    """Download a file from a given URL and display progress.

    :param dest: If the destination exists and is a directory, the filename
        will be guessed from the Content-Disposition header. If the destination
        is an existing file, the user will either be prompted to overwrite, or
        the file will be replaced (depending on the value of **replace**). If
        the destination does not exist, it will be used as the filename.
    :param int chunk_size: bytes read in at a time.
    :param replace: If `False`, an existing destination file will not be
        overwritten.
    :param label: a string which is formatted and displayed as the progress bar
        label. Variables provided include *dest_basename*, *dest*, and *size*.
    :param expected_extension: if set, the filename will be sanitized to ensure
        it has the given extension. The extension should not start with a dot
        (`.`).
    """
    dest = Path(dest or url.split("/")[-1])
    response = get(url, stream=True)
    if (dest.exists()
            and dest.is_dir()
            and "Content-Disposition" in response.headers):
        content_disposition = rfc6266.parse_requests_response(response)
        if expected_extension is not None:
            filename = content_disposition.filename_sanitized(
                expected_extension)
        filename = secure_filename(filename)
        dest = dest / filename
    if dest.exists() and not dest.is_dir():
        if (replace is False
                or replace == "ask"
                and not click.confirm("Replace {}?".format(dest))):
            return str(dest)
    size = int(response.headers.get("content-length", 0))
    label = label.format(dest=dest, dest_basename=dest.name,
                         size=size/1024.0/1024)
    with click.open_file(str(dest), "wb") as f:
        content_iter = response.iter_content(chunk_size=chunk_size)
        with click.progressbar(content_iter, length=size/1024,
                               label=label) as bar:
            for chunk in bar:
                if chunk:
                    f.write(chunk)
                    f.flush()
    return str(dest)
def recover_session(self,
                      master,
                      saver=None,
                      checkpoint_dir=None,
                      checkpoint_filename_with_path=None,
                      wait_for_checkpoint=False,
                      max_wait_secs=7200,
                      config=None):
    """Creates a `Session`, recovering if possible.

    Creates a new session on 'master'.  If the session is not initialized
    and can be recovered from a checkpoint, recover it.

    Args:
      master: `String` representation of the TensorFlow master to use.
      saver: A `Saver` object used to restore a model.
      checkpoint_dir: Path to the checkpoint files. The latest checkpoint in the
        dir will be used to restore.
      checkpoint_filename_with_path: Full file name path to the checkpoint file.
      wait_for_checkpoint: Whether to wait for checkpoint to become available.
      max_wait_secs: Maximum time to wait for checkpoints to become available.
      config: Optional `ConfigProto` proto used to configure the session.

    Returns:
      A pair (sess, initialized) where 'initialized' is `True` if
      the session could be recovered and initialized, `False` otherwise.

    Raises:
      ValueError: If both checkpoint_dir and checkpoint_filename_with_path are
        set.
    """

    sess, is_loaded_from_checkpoint = self._restore_checkpoint(
        master,
        saver,
        checkpoint_dir=checkpoint_dir,
        checkpoint_filename_with_path=checkpoint_filename_with_path,
        wait_for_checkpoint=wait_for_checkpoint,
        max_wait_secs=max_wait_secs,
        config=config)

    # Always try to run local_init_op
    local_init_success, msg = self._try_run_local_init_op(sess)

    if not is_loaded_from_checkpoint:
      # Do not need to run checks for readiness
      return sess, False

    restoring_file = checkpoint_dir or checkpoint_filename_with_path
    if not local_init_success:
      logging.info(
          "Restoring model from %s did not make model ready for local init:"
          " %s", restoring_file, msg)
      return sess, False

    is_ready, msg = self._model_ready(sess)
    if not is_ready:
      logging.info("Restoring model from %s did not make model ready: %s",
                   restoring_file, msg)
      return sess, False

    logging.info("Restored model from %s", restoring_file)
    return sess, is_loaded_from_checkpoint