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)

                    # 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:

_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

            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):

    }

    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__

        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(

    (explicit) kernel methods in TensorFlow.

## Bug Fixes and Other Changes

*   In python, `Operation.get_attr` on type attributes returns the Python DType
    version of the type to match expected get_attr documentation rather than the
    protobuf enum.
*   tensorflow/contrib/rnn undergoes RNN cell variable renaming for consistency