code: def test_evaluate_mix_in_1(scoring_mix_in_fixture_1):
      scoring_mix_in_fixture_1 = _call_evaluate(
          scoring_mix_in_fixture_1
      )
      assert scoring_mix_in_fixture_1.last_evaluation_results == dict(
          in_fold=OrderedDict([("roc_auc", 0.75), ("f1", 0.8)]),
          oof=OrderedDict([("f1", 0.8)]),
          holdout=OrderedDict(),
      )
  
imports: from hyperparameter_hunter.metrics import ScoringMixIn, Metric, format_metrics, wrap_xgboost_metric
  from hyperparameter_hunter.metrics import get_formatted_target_metric, get_clean_prediction
  from collections import OrderedDict
  import numpy
  import pandas
  import pytest
  import sys
  from sklearn.metrics import roc_auc_score, hamming_loss, r2_score, f1_score
label_desc: Use image node_id 22 for calling a global function with example usage: test_evaluate_mix_in_1(scoring_mix_in_fixture_1) without return types