def _grid_search(self, train_X, train_y): if callable(self.inner_cv): inner_cv = self.inner_cv(train_X, train_y) else: inner_cv = _check_cv(self.inner_cv, train_X, train_y, classifier=is_classifier(self.estimator)) master = MPIGridSearchCVMaster(self.param_grid, inner_cv, self.estimator, self.scorer_, self.fit_params) return master.run(train_X, train_y)
def fit(self, X, y): X, y = check_X_y(X, y, force_all_finite=False, multi_output=self.multi_output) _check_param_grid(self.param_grid) cv = _check_cv(self.cv, X, y, classifier=is_classifier(self.estimator)) self.scorer_ = check_scoring(self.estimator, scoring=self.scoring) if comm_rank == 0: self._fit_master(X, y, cv) else: self._fit_slave() return self