(self, deep: Union[bool, Literal[0]] = True)
return out
Get parameters for this operator.

        This method follows scikit-learn's convention that all operators
        have a constructor which takes a list of keyword arguments.
        This is not required for operator impls which do not desire
        scikit-compatibility.

        Parameters
        ----------
        deep : boolean, optional
            If True, will return the parameters for this operator, and their nested parameters
            If False, will return the parameters for this operator, along with '_lale_XXX` fields needed to support cloning

        Returns
        -------
        params : mapping of string to any
            Parameter names mapped to their values.
Get parameters for this operator.
Get parameters for this operator .
def get_params(self, deep: Union[bool, Literal[0]] = True) -> Dict[str, Any]:
        """Get parameters for this operator.

        This method follows scikit-learn's convention that all operators
        have a constructor which takes a list of keyword arguments.
        This is not required for operator impls which do not desire
        scikit-compatibility.

        Parameters
        ----------
        deep : boolean, optional
            If True, will return the parameters for this operator, and their nested parameters
            If False, will return the parameters for this operator, along with '_lale_XXX` fields needed to support cloning

        Returns
        -------
        params : mapping of string to any
            Parameter names mapped to their values.
        """

        out: Dict[str, Any] = dict()
        if deep is False:
            out["_lale_name"] = self._name
            out["_lale_schemas"] = self._schemas
            out["_lale_impl"] = _WithoutGetParams.wrap(self._wrapped_impl_class())
        # we need to stringify the class object, since the class object
        # has a get_params method (the instance method), which causes problems for
        # sklearn clone

        if self._is_instantiated():
            impl = self._impl_instance()
            if hasattr(impl, "get_params"):
                out.update(impl.get_params(deep=deep))
            elif hasattr(impl, "_wrapped_model") and hasattr(
                impl._wrapped_model, "get_params"
            ):
                out.update(impl._wrapped_model.get_params(deep=bool(deep)))
            else:
                out.update(self._get_params_all(deep=bool(deep)))
        else:
            out.update(self._get_params_all(deep=bool(deep)))

        if deep is False and self.frozen_hyperparams() is not None:
            out["_lale_frozen_hyperparameters"] = self.frozen_hyperparams()

        return out
def get_params ( self , deep : Union [ bool , Literal [ 0 ] ] = True ) -> Dict [ str , Any ] : out : Dict [ str , Any ] = dict ( ) if deep is False : out [ "_lale_name" ] = self . _name out [ "_lale_schemas" ] = self . _schemas out [ "_lale_impl" ] = _WithoutGetParams . wrap ( self . _wrapped_impl_class ( ) ) # we need to stringify the class object, since the class object # has a get_params method (the instance method), which causes problems for # sklearn clone if self . _is_instantiated ( ) : impl = self . _impl_instance ( ) if hasattr ( impl , "get_params" ) : out . update ( impl . get_params ( deep = deep ) ) elif hasattr ( impl , "_wrapped_model" ) and hasattr ( impl . _wrapped_model , "get_params" ) : out . update ( impl . _wrapped_model . get_params ( deep = bool ( deep ) ) ) else : out . update ( self . _get_params_all ( deep = bool ( deep ) ) ) else : out . update ( self . _get_params_all ( deep = bool ( deep ) ) ) if deep is False and self . frozen_hyperparams ( ) is not None : out [ "_lale_frozen_hyperparameters" ] = self . frozen_hyperparams ( ) return out