class ModelWithDatetimeField(BaseModel):
        dt_field: datetime

        @field_serializer("dt_field")
        def serialize_datetime(self, dt_field: datetime):
            return dt_field.replace(microsecond=0, tzinfo=timezone.utc).isoformat()

    app = FastAPI()
    model = ModelWithDatetimeField(dt_field=datetime(2019, 1, 1, 8))

    @app.get("/model", response_model=ModelWithDatetimeField)
    def get_model():

    class ModelWithCustomEncoder(BaseModel):
        dt_field: datetime

        @field_serializer("dt_field")
        def serialize_dt_field(self, dt):
            return dt.replace(microsecond=0, tzinfo=timezone.utc).isoformat()

    class ModelWithCustomEncoderSubclass(ModelWithCustomEncoder):
        pass

    model = ModelWithCustomEncoder(dt_field=datetime(2019, 1, 1, 8))

def generate_operation_summary(*, route: routing.APIRoute, method: str) -> str:
    if route.summary:
        return route.summary
    return route.name.replace("_", " ").title()


def get_openapi_operation_metadata(
    *, route: routing.APIRoute, method: str, operation_ids: Set[str]
) -> Dict[str, Any]:
    operation: Dict[str, Any] = {}
    if route.tags:

            use_annotation,
            field_info,
            param_name,
        )
        if not field_info.alias and getattr(field_info, "convert_underscores", None):
            alias = param_name.replace("_", "-")
        else:
            alias = field_info.alias or param_name
        field_info.alias = alias
        field = create_response_field(
            name=param_name,

            if (/code|token|error/.test(window.location.hash)) {
                qp = window.location.hash.substring(1).replace('?', '&');
            } else {
                qp = location.search.substring(1);
            }

            arr = qp.split("&");
            arr.forEach(function (v,i,_arr) { _arr[i] = '"' + v.replace('=', '":"') + '"';});
            qp = qp ? JSON.parse('{' + arr.join() + '}',

      # Convert package name to the short version:
      # tensorflow._api.v2.distribute.experimental to
      # tensorflow.distribute.experimental
      short_package_name = package_name.replace(f"_api.{version}.", "")
      # skip non-importable paths
      if short_package_name not in self.packages_for_skip:
        try:
          __import__(short_package_name)
        except ImportError:

            # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207
            json_schema["title"] = (
                field.field_info.title or field.alias.title().replace("_", " ")
            )
        return json_schema

    def get_compat_model_name_map(fields: List[ModelField]) -> ModelNameMap:
        return {}

    def get_definitions(
        *,

  else:
    output = subprocess.check_output(cmd, stderr=stderr)
  return output.decode('UTF-8').strip()


def cygpath(path):
  """Convert path from posix to windows."""
  return os.path.abspath(path).replace('\\', '/')


def get_python_path(environ_cp, python_bin_path):
  """Get the python site package paths."""
  python_paths = []
  if environ_cp.get('PYTHONPATH'):

            name: str
            description: str | None = None

        app = FastAPI()

        @app.put("/items/{item_id}")
        def replace_item(item_id: str, item: Item):
            return {"message": "Item replaced", "id": item_id}
        ```
        """
        return self.router.put(
            path,
            response_model=response_model,

If you depend on functionality not listed there, please file an issue.
"""
contrib = _LazyLoader("contrib", globals(), "tensorflow.contrib",
                      _CONTRIB_WARNING)
# The templated code that replaces the placeholder above sometimes
# 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