app = FastAPI(generate_unique_id_function=custom_generate_unique_id)
    router = APIRouter(generate_unique_id_function=custom_generate_unique_id2)

    @app.post(
        "/",
        response_model=List[Item],
        responses={404: {"model": List[Message]}},
        generate_unique_id_function=custom_generate_unique_id3,
    )
    def post_root(item1: Item, item2: Item):

        </ul>
        <script>
        var ws = null;
            function connect(event) {
                var itemId = document.getElementById("itemId")
                var token = document.getElementById("token")
                ws = new WebSocket("ws://localhost:8000/items/" + itemId.value + "/ws?token=" + token.value);
                ws.onmessage = function(event) {
                    var messages = document.getElementById('messages')

        **extra,
    )


def Depends(  # noqa: N802
    dependency: Annotated[
        Optional[Callable[..., Any]],
        Doc(
            """
            A "dependable" callable (like a function).

            Don't call it directly, FastAPI will call it for you, just pass the object
            directly.
            """
        ),
    ] = None,
    *,
    use_cache: Annotated[

    field_info = FieldInfo(annotation=str)
    field = ModelField(name="foo", field_info=field_info)
    assert field.default is Undefined


@needs_pydanticv1
def test_upload_file_dummy_with_info_plain_validator_function():
    # For coverage
    assert UploadFile.__get_pydantic_core_schema__(str, lambda x: None) == {}


@needs_pydanticv1
def test_union_scalar_list():
    # For coverage

    # attempts)
    for p in testsuite._elem.xpath(".//error | .//failure"):
      # Sharded tests have target names like this:
      # WindowOpsTest.test_tflite_convert0 (<function hann_window at
      #     0x7fc61728dd40>, 10, False, tf.float32)
      # Where 0x... is a thread ID (or something) that is not important for
      # debugging, but breaks this "number of failures" counter because it's

"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

from fastapi.exceptions import HTTPException
from fastapi.openapi.models import OAuth2 as OAuth2Model
from fastapi.openapi.models import OAuthFlows as OAuthFlowsModel
from fastapi.param_functions import Form
from fastapi.security.base import SecurityBase
from fastapi.security.utils import get_authorization_scheme_param
from starlette.requests import Request

            ws.onmessage = function(event) {
                var messages = document.getElementById('messages')
                var message = document.createElement('li')
                var content = document.createTextNode(event.data)
                message.appendChild(content)
                messages.appendChild(message)
            };
            function sendMessage(event) {

from .param_functions import Body as Body
from .param_functions import Cookie as Cookie
from .param_functions import Depends as Depends
from .param_functions import File as File
from .param_functions import Form as Form
from .param_functions import Header as Header
from .param_functions import Path as Path
from .param_functions import Query as Query
from .param_functions import Security as Security

                """
            ),
        ] = None,
        generate_unique_id_function: Annotated[
            Callable[[routing.APIRoute], str],
            Doc(
                """
                Customize the function used to generate unique IDs for the *path
                operations* shown in the generated OpenAPI.