ecb4dacbf793ee4276dd7ad4625bf2cb53feb9a1,deeppavlov/paramsearch.py,,main,#,48

Before Change

        for comb in combinations:
            config = config_init.copy()
            for i, param_value in enumerate(comb):
                config = params_helper.insert_value_or_dict_into_config(config, param_paths[i], param_value)

            if (n_folds is not None) | is_loo:
                // CV for model evaluation

After Change

        if param_name != target_metric:
            params_helper.insert_value_or_dict_into_config(best_config, param_paths[i], best_params_dict[param_name])

    best_model_filename = pipeline_config_path.with_suffix(".cvbest.json")
    save_json(best_config, best_model_filename)
    log.info("Best model saved in json-file: {}".format(best_model_filename))

Instances