for comment in pr.comments.nodes:
            if comment.author:
                authors[comment.author.login] = comment.author
                if comment.author.login == author_name:
                    continue
                pr_commentors.add(comment.author.login)
        for author_name in pr_commentors:
            commenters[author_name] += 1
        for review in pr.reviews.nodes:
            if review.author:

            continue
        if add_non_field_param_to_dependency(
            param_name=param_name,
            type_annotation=type_annotation,
            dependant=dependant,
        ):
            assert (
                param_field is None
            ), f"Cannot specify multiple FastAPI annotations for {param_name!r}"
            continue
        assert param_field is not None

        language_names_path.read_text(encoding="utf-8")
    )
    for lang_path in get_lang_paths():
        if lang_path.name in {"en", "em"} or not lang_path.is_dir():
            continue
        code = lang_path.name
        languages.append({code: f"/{code}/"})
    for lang_dict in languages:
        code = list(lang_dict.keys())[0]
        url = lang_dict[code]

    parameters = []
    for param in all_route_params:
        field_info = param.field_info
        field_info = cast(Param, field_info)
        if not field_info.include_in_schema:
            continue
        param_schema = get_schema_from_model_field(
            field=param,
            schema_generator=schema_generator,
            model_name_map=model_name_map,
            field_mapping=field_mapping,

  current_url = None
  for i in range(len(log_lines)):
    line = log_lines[i]
    result_store_line_match = re.search(RESULT_STORE_LINK_RE, line)
    if not result_store_line_match:
      continue

    url = result_store_line_match.group(1)
    url_lines = result_store_links.setdefault(url, {})
    # Each bazel RBE invocation should produce two

        at_least_one_scalar_sequence = False
        for arg in get_args(annotation):
            if field_annotation_is_scalar_sequence(arg):
                at_least_one_scalar_sequence = True
                continue
            elif not field_annotation_is_scalar(arg):
                return False
        return at_least_one_scalar_sequence
    return field_annotation_is_sequence(annotation) and all(

            resolve_file(item=item, files=files, config=config)
        elif isinstance(item, dict):
            assert len(item) == 1
            values = list(item.values())
            if not values:
                continue
            if isinstance(values[0], str):
                resolve_file(item=values[0], files=files, config=config)
            elif isinstance(values[0], list):

  Raises:
    UserInputError: if an environment variable is set, but it cannot be
      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)