aab60f7a1b5bc8cbeaeb37c036387bcf8cc9556c,dask_ml/wrappers.py,ParallelPostFit,fit,#ParallelPostFit#Any#Any#,80

Before Change

        result = self.estimator.fit(X, y, **kwargs)

        // Copy over learned attributes
        attrs = {k: v for k, v in vars(result).items() if k.endswith("_")}
        for k, v in attrs.items():
            setattr(self, k, v)

        return self

    def transform(self, X):
        Transform block or partition-wise for dask inputs.

After Change

        logger.info("Starting fit")
        result = self.estimator.fit(X, y, **kwargs)
        stop = tic()
        logger.info("Finished fit, %0.2f", stop - start)

        // Copy over learned attributes
        copy_learned_attributes(result, self)
        copy_learned_attributes(result, self.estimator)

Instances