from fastapi.dependencies.utils import (
    multipart_incorrect_install_error,
    multipart_not_installed_error,
)


def test_incorrect_multipart_installed_form(monkeypatch):
    monkeypatch.setattr("python_multipart.__version__", "0.0.12")
    with warnings.catch_warnings(record=True):
        warnings.simplefilter("always")
        monkeypatch.delattr("multipart.multipart.parse_options_header", raising=False)

_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)
setattr(_current_module, "metrics", _metrics)
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

                    # For Pydantic v1
                    and getattr(field, "shape", 1) == 1
                )
            )

    return ParamDetails(type_annotation=type_annotation, depends=depends, field=field)


def add_param_to_fields(*, field: ModelField, dependant: Dependant) -> None:
    field_info = field.field_info
    field_info_in = getattr(field_info, "in_", None)
    if field_info_in == params.ParamTypes.path:

    }

    public void setId(final String id) {
        this.id = id;
    }

    public void setCss(final String css) {
        this.css = css;
    }

    public void setAttr(final String name, final String value) {
        attrName = name;
        attrValue = value;
    }

    @Override
    public String toString() {

  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v1.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__

            openapi_examples = getattr(field_info, "openapi_examples", None)
            example = getattr(field_info, "example", None)
            if openapi_examples:
                parameter["examples"] = jsonable_encoder(openapi_examples)
            elif example != Undefined:
                parameter["example"] = jsonable_encoder(example)
            if getattr(field_info, "deprecated", None):

        self, dependency: Optional[Callable[..., Any]] = None, *, use_cache: bool = True
    ):
        self.dependency = dependency
        self.use_cache = use_cache

    def __repr__(self) -> str:
        attr = getattr(self.dependency, "__name__", type(self.dependency).__name__)
        cache = "" if self.use_cache else ", use_cache=False"
        return f"{self.__class__.__name__}({attr}{cache})"


class Security(Depends):

                "/"
            ), "A path prefix must not end with '/', as the routes will start with '/'"
        else:
            for r in router.routes:
                path = getattr(r, "path")  # noqa: B009
                name = getattr(r, "name", "unknown")
                if path is not None and not path:
                    raise FastAPIError(

        which would previously raise an error. This will correspond to an
        attribute name with an embedded '.' symbol (e.g. 'a.b'), which can only
        be accessed indirectly (e.g. through getattr and setattr). To set this
        up the user will first need to explicitly add the variable to the hparam
        object (e.g. "hparams.add_hparam(name='a.b', value=0.0)").
    *   Benchmark for tf.scan in graph and eager modes.