) -> Dict[str, Any]:
    headers = {"Authorization": f"token {settings.input_token.get_secret_value()}"}
    # some fields are only used by one query, but GraphQL allows unused variables, so
    # keep them here for simplicity
    variables = {
        "after": after,
        "category_id": category_id,
        "discussion_number": discussion_number,
        "discussion_id": discussion_id,
        "comment_id": comment_id,

  """Set boolean action_env variable.

  Ask user if query_item will be enabled. Default is used if no input is given.
  Set environment variable and write to .bazelrc.

  Args:
    environ_cp: copy of the os.environ.
    var_name: string for name of environment variable, e.g. "TF_NEED_CUDA".
    query_item: string for feature related to the variable, e.g. "CUDA for
      Nvidia GPUs".

    # category_id is only used by one query, but GraphQL allows unused variables, so
    # keep it here for simplicity
    variables = {"after": after, "category_id": category_id}
    response = httpx.post(
        github_graphql_url,
        headers=headers,
        timeout=settings.httpx_timeout,
        json={"query": query, "variables": variables, "operationName": "Q"},
    )
    if response.status_code != 200:

    default: str
    description: Optional[str] = None


class Server(BaseModelWithConfig):
    url: Union[AnyUrl, str]
    description: Optional[str] = None
    variables: Optional[Dict[str, ServerVariable]] = None


class Reference(BaseModel):
    ref: str = Field(alias="$ref")


class Discriminator(BaseModel):
    propertyName: str

                * `url`: A URL to the target host. This URL supports Server Variables
                and MAY be relative, to indicate that the host location is relative
                to the location where the OpenAPI document is being served. Variable
                substitutions will be made when a variable is named in `{`brackets`}`.
                * `description`: An optional string describing the host designated by

# in turn imports from tensorflow.core and tensorflow.python. They
# must come from this module. So python adds these symbols for the
# resolution to succeed.
# pylint: disable=undefined-variable
del python
del core

# sets the __all__ variable. If it does, we have to be sure to add
# "contrib".
if "__all__" in vars():
  vars()["__all__"].append("contrib")

from tensorflow.python.platform import flags
# The "app" module will be imported as part of the placeholder section above.
_current_module.app.flags = flags  # pylint: disable=undefined-variable
setattr(_current_module, "flags", flags)

from pydantic import BaseModel, create_model
from pydantic.version import VERSION as P_VERSION
from starlette.datastructures import UploadFile
from typing_extensions import Annotated, Literal, get_args, get_origin

# Reassign variable to make it reexported for mypy
PYDANTIC_VERSION = P_VERSION
PYDANTIC_V2 = PYDANTIC_VERSION.startswith("2.")


sequence_annotation_to_type = {
    Sequence: list,
    List: list,
    list: list,