if _os.path.exists(_plugin_dir):
      _ll.load_library(_plugin_dir)
      # Load Pluggable Device Library
      _ll.load_pluggable_device_library(_plugin_dir)

if _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH", ""):
  _ll.load_pluggable_device_library(
      _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH")
  )

# Add Keras module aliases
_losses = _KerasLazyLoader(globals(), submodule="losses", name="losses")

                 sts_ep='http://localhost:9000'):
        self.cid = cid
        self.csec = csec
        self.idp_ep = idp_ep
        self.sts_ep = sts_ep

        # Load CA certificates from SSL_CERT_FILE file if set
        ca_certs = os.environ.get('SSL_CERT_FILE')
        if not ca_certs:
            ca_certs = certifi.where()

        self._http = urllib3.PoolManager(

    importlib.reload(tutorial001)

    client = TestClient(tutorial001.app)
    return client


@needs_pydanticv2
def test_disable_openapi(monkeypatch):
    monkeypatch.setenv("OPENAPI_URL", "")
    # Load the client after setting the env var
    client = get_client()
    response = client.get("/openapi.json")
    assert response.status_code == 404, response.text
    response = client.get("/docs")

@lru_cache
def is_mkdocs_insiders() -> bool:
    version = metadata.version("mkdocs-material")
    return "insiders" in version


def get_en_config() -> Dict[str, Any]:
    return mkdocs.utils.yaml_load(en_config_path.read_text(encoding="utf-8"))


def get_lang_paths() -> List[Path]:
    return sorted(docs_path.iterdir())


def lang_callback(lang: Optional[str]) -> Union[str, None]:
    if lang is None:

            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.model_validate(data)
    except ValidationError as e:

def normalize(rl, args):
    for i in range(len(rl)):
        rl[i] = normalize_res(rl[i], args)

    return rl


def compare(args):
    j0 = normalize(list(yaml.safe_load_all(open(args.orig))), args)
    j1 = normalize(list(yaml.safe_load_all(open(args.new))), args)

    q0 = {by_resource_name(res): res for res in j0 if res is not None}
    q1 = {by_resource_name(res): res for res in j1 if res is not None}

  # version.
  meta = open(os.path.join(android_ndk_home_path, 'meta/platforms.json'))
  platforms = json.load(meta)
  meta.close()
  aliases = platforms['aliases']
  api_levels = sorted(list(set([aliases[i] for i in aliases])))

  android_ndk_api_level = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='ANDROID_NDK_API_LEVEL',
      var_default='21',  # 21 is required for ARM64 support.

  def setUp(self):
    def _get_api_packages_v2():
      api_packages_path = pkg_resources.resource_filename(
          "tensorflow", "_api/v2/api_packages.txt"
      )

      logging.info("Load api packages file: %s", api_packages_path)
      with open(api_packages_path) as file:
        return set(file.read().splitlines())

    super().setUp()
    self.api_packages_v2 = _get_api_packages_v2()

from fastapi import FastAPI


def fake_answer_to_everything_ml_model(x: float):
    return x * 42


ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)

            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.parse_obj(data)
    except ValidationError as e: