f'Bazel invocations.\n'
          f'ResultStore contains individual representations of each target '
          f'that were run/built during the invocation.\n'
          f'These results are generally easier to read than looking through '
          f'the entire build log:\n')
  i = 1
  for url, invocation_results in result_store_dict.items():
    line_str = f'Invocation #{i} ({invocation_results["status"]}):\n'

      interpreted as a boolean indicator, assume that the user has made a
      scripting error, and will continue to provide invalid input.
      Raise the error to avoid infinitely looping.
  """
  if not question:
    question = 'Do you wish to build TensorFlow with {} support?'.format(
        query_item)
  if not yes_reply:

                This is simply inherited from Starlette.

                Read more about it in the
                [Starlette docs for Applications](https://www.starlette.io/applications/#storing-state-on-the-app-instance).
                """
            ),
        ] = State()
        self.dependency_overrides: Annotated[
            Dict[Callable[..., Any], Callable[..., Any]],
            Doc(