c11520dbcc6c1c3889bc76a2b76f6adf5e99c54d,cde/density_estimator/BaseNNEstimator.py,BaseNNEstimator,fit_by_cv,#BaseNNEstimator#,39

Before Change

        // check if all results are available and rerun failed fit_evals
        for i, j in zip(param_ids, fold_ids):
            if (i, j) not in set(score_dict.keys()):
                _fit_eval(i, j)
        assert len(score_dict.keys()) == len(param_list) * len(train_splits)
        print(score_dict)

        // Select the best parameter setting

After Change

            failed_runs = [x for x in zip(param_ids, fold_ids) if x not in score_dict]
            if not failed_runs:
                break
            if verbose:
                print("{} runs succeeded, {} runs failed. Rerunning failed runs".format(len(score_dict.keys()),
                                                                                        len(failed_runs)))
            for (p, f) in failed_runs:
                try:
                    _fit_eval(p, f, verbose=verbose, i_rand=i)
                except Exception as e:

Instances