code: def scoring_mix_in_fixture_0():
      mixin = ScoringMixIn(
          metrics=dict(roc_auc=roc_auc_score, f1=f1_score),
          do_score=True,
      )
      assert _get_mixin_data_types(mixin) == [
          ["roc_auc", "f1"],
          ["roc_auc", "f1"],
          ["roc_auc", "f1"],
      ]
      return mixin
  
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 16 for calling a global function with example usage: scoring_mix_in_fixture_0() and returns: mixin