(metric, eval_cfg, data_len, eval_indexes)
| 20 | |
| 21 | |
| 22 | def build_evaluator(metric, eval_cfg, data_len, eval_indexes): |
| 23 | cfg = copy.deepcopy(eval_cfg) |
| 24 | cfg.update(metric) |
| 25 | cfg.pop('metrics') |
| 26 | cfg['data_len'] = data_len |
| 27 | cfg['eval_indexes'] = eval_indexes |
| 28 | evaluator = EVALUATORS.build(cfg) |
| 29 | if evaluator.append_indexes is not None: |
| 30 | for i in range(eval_cfg['replication_times']): |
| 31 | eval_indexes[i] = np.concatenate( |
| 32 | (eval_indexes[i], evaluator.append_indexes[i]), axis=0) |
| 33 | return evaluator, eval_indexes |