foo: ModelB

        @field_validator("name")
        def lower_username(cls, name: str, info: ValidationInfo):
            if not name.endswith("A"):
                raise ValueError("name must end in A")
            return name

    async def get_model_c() -> ModelC:
        return ModelC(username="test-user", password="test-password")

    @app.get("/model/{name}", response_model=ModelA)

        if not isinstance(v, StarletteUploadFile):
            raise ValueError(f"Expected UploadFile, received: {type(v)}")
        return v

    @classmethod
    def _validate(cls, __input_value: Any, _: Any) -> "UploadFile":
        if not isinstance(__input_value, StarletteUploadFile):
            raise ValueError(f"Expected UploadFile, received: {type(__input_value)}")
        return cast(UploadFile, __input_value)

    assert jsonable_encoder(item, exclude={}) == {"name": "foo", "count": 100}


def test_encode_unsupported():
    unserializable = Unserializable()
    with pytest.raises(ValueError):
        jsonable_encoder(unserializable)


@needs_pydanticv2
def test_encode_custom_json_encoders_model_pydanticv2():
    from pydantic import field_serializer

            detail="Invalid authentication credentials",
            headers=unauthorized_headers,
        )
        try:
            data = b64decode(param).decode("ascii")
        except (ValueError, UnicodeDecodeError, binascii.Error):
            raise invalid_user_credentials_exc  # noqa: B904
        username, separator, password = data.partition(":")
        if not separator:

    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,
        by_alias=by_alias,
        exclude_unset=exclude_unset,

  environ_cp['TF_CUDNN_VERSION'] = tf_cudnn_version


def set_tf_tensorrt_version(environ_cp):
  """Set TF_TENSORRT_VERSION."""
  if not (is_linux() or is_windows()):
    raise ValueError('Currently TensorRT is only supported on Linux platform.')

  if not int(environ_cp.get('TF_NEED_TENSORRT', False)):
    return

  ask_tensorrt_version = (

    *   Add a Nearest Neighbor Resize op.
    *   Add an `ignore_unknown` argument to `parse_values` which suppresses
        ValueError for unknown hyperparameter types. Such * Add
        `tf.linalg.matvec` convenience function.
    *   `tf.einsum()`raises `ValueError` for unsupported equations like
        `"ii->"`.
    *   Add DCT-I and IDCT-I in `tf.signal.dct` and `tf.signal.idct`.
    *   Add LU decomposition op.