code: def create_split_logs_and_evaluator():
      def _create_split_logs_and_evaluator(eval_name):
          logs = {
              eval_name + "_0": {"roc_auc": 0.48},
              eval_name + "_1": {"roc_auc": 0.52},
          }
          base_evaluator = evaluator_extractor(evaluator_name="roc_auc")
          return logs, base_evaluator
  
      return _create_split_logs_and_evaluator
  
file_path: fklearn/tests/metrics/test_pd_extractors.py
imports: from datetime import timedelta
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import fetch_california_housing
  from fklearn.data.datasets import make_tutorial_data
  from fklearn.metrics.pd_extractors import combined_evaluator_extractor, evaluator_extractor, extract, split_evaluator_extractor, split_evaluator_extractor_iteration, temporal_split_evaluator_extractor
  from fklearn.training.regression import linear_regression_learner
  from fklearn.validation.evaluators import combined_evaluators, r2_evaluator, spearman_evaluator, split_evaluator, temporal_split_evaluator, mse_evaluator
  from fklearn.validation.splitters import forward_stability_curve_time_splitter, out_of_time_and_space_splitter, stability_curve_time_splitter, time_learning_curve_splitter
  from fklearn.validation.validator import validator
label_desc: Use image node_id 1 for calling a global function with example usage: create_split_logs_and_evaluator() and returns: _create_split_logs_and_evaluator, logs,  base_evaluator