@app.post("/login")
    def login(form_data: Annotated[OAuth2PasswordRequestForm, Depends()]):
        data = {}
        data["scopes"] = []
        for scope in form_data.scopes:
            data["scopes"].append(scope)
        if form_data.client_id:
            data["client_id"] = form_data.client_id
        if form_data.client_secret:
            data["client_secret"] = form_data.client_secret
        return data
    ```

        bool,
        Doc(
            """
            When `embed` is `True`, the parameter will be expected in a JSON body as a
            key instead of being the JSON body itself.

            This happens automatically when more than one `Body` parameter is declared.

            Read more about it in the

setattr(_current_module, "optimizers", _optimizers)
setattr(_current_module, "initializers", _initializers)


# Do an eager load for Keras' code so that any function/method that needs to
# happen at load time will trigger, eg registration of optimizers in the
# SavedModel registry.
# See b/196254385 for more details.
try:
  if _tf_uses_legacy_keras:
    importlib.import_module("tf_keras.src.optimizers")

    sponsors = []
    for key in keys:
        sponsor_group = []
        for login, sponsor in tiers[key].items():
            sponsor_group.append(
                {"login": login, "avatarUrl": sponsor.avatarUrl, "url": sponsor.url}
            )
        sponsors.append(sponsor_group)

    people = {
        "maintainers": maintainers,
        "experts": experts,
        "last_month_experts": last_month_experts,

    if field_info_in == params.ParamTypes.path:
        dependant.path_params.append(field)
    elif field_info_in == params.ParamTypes.query:
        dependant.query_params.append(field)
    elif field_info_in == params.ParamTypes.header:
        dependant.header_params.append(field)
    else:
        assert (
            field_info_in == params.ParamTypes.cookie

                "update it in docs/language_names.yml"
            )
            raise typer.Abort()
        use_name = f"{code} - {local_language_names[code]}"
        new_alternate.append({"link": url, "name": use_name})
    new_alternate.append({"link": "/em/", "name": "😉"})
    config["extra"]["alternate"] = new_alternate
    return config


def update_config() -> None:
    config = get_updated_config_content()

                    route.body_field, ModelField
                ), "A request body must be a Pydantic Field"
                body_fields_from_routes.append(route.body_field)
            if route.response_field:
                responses_from_routes.append(route.response_field)
            if route.response_fields:
                responses_from_routes.extend(route.response_fields.values())
            if route.callbacks:

_current_module = _sys.modules[__name__]
_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
if not hasattr(_current_module, "__path__"):
  __path__ = [_tf_api_dir]
elif _tf_api_dir not in __path__:
  __path__.append(_tf_api_dir)

# Hook external TensorFlow modules.
# Import compat before trying to import summary from tensorboard, so that
# reexport_tf_summary can get compat from sys.modules. Only needed if using
# lazy loading.

    except AsyncDependencyError:
        errors.append("/async_raise")
        raise
    finally:
        state["/async_raise"] = "asyncgen raise finalized"


def generator_state_try(state: Dict[str, str] = Depends(get_state)):
    state["/sync_raise"] = "generator raise started"
    try:
        yield state["/sync_raise"]
    except SyncDependencyError:
        errors.append("/sync_raise")
        raise
    finally:

            return encoder(obj)

    try:
        data = dict(obj)
    except Exception as e:
        errors: List[Exception] = []
        errors.append(e)
        try:
            data = vars(obj)
        except Exception as e:
            errors.append(e)
            raise ValueError(errors) from e
    return jsonable_encoder(
        data,
        include=include,
        exclude=exclude,