(self, pipeline_name=None, astype="lale", **kwargs)
return result.export_to_sklearn_pipeline()
Retrieve one of the trials.

        Parameters
        ----------
        pipeline_name : union type, default None

            - string
                Key for table returned by summary(), return a trainable pipeline.

            - None
                When not specified, return the best trained pipeline found.

        astype : 'lale' or 'sklearn', default 'lale'
            Type of resulting pipeline.

        Returns
        -------
        result : Trained operator if best, trainable operator otherwise.
Retrieve one of the trials.
Retrieve one of the trials .
def get_pipeline(self, pipeline_name=None, astype="lale", **kwargs):
        """Retrieve one of the trials.

        Parameters
        ----------
        pipeline_name : union type, default None

            - string
                Key for table returned by summary(), return a trainable pipeline.

            - None
                When not specified, return the best trained pipeline found.

        astype : 'lale' or 'sklearn', default 'lale'
            Type of resulting pipeline.

        Returns
        -------
        result : Trained operator if best, trainable operator otherwise."""
        result = self.add_suffix(
            self._optimizer.get_pipeline(
                pipeline_name=pipeline_name, astype=astype, **kwargs
            )
        )

        if result is None or astype == "lale":
            return result
        assert astype == "sklearn", astype
        return result.export_to_sklearn_pipeline()
def get_pipeline ( self , pipeline_name = None , astype = "lale" , * * kwargs ) : result = self . add_suffix ( self . _optimizer . get_pipeline ( pipeline_name = pipeline_name , astype = astype , * * kwargs ) ) if result is None or astype == "lale" : return result assert astype == "sklearn" , astype return result . export_to_sklearn_pipeline ( )