class_docstr: Test class for custom metric tests.
docstr: Clean up any custom metrics.
docstr_tok: ["Clean","up","any","custom","metrics","."]
code: def _cleanup_custom_metrics(self):
      """Clean up any custom metrics."""
      for metric_name in [
          "f06_micro",
          "f075_macro",
          "fake_prob_metric",
          "fake_prob_metric_multiclass",
          "one_minus_f1_macro",
          "one_minus_precision",
          "ratio_of_ones",
      ]:
          try:
              delattr(skll.experiments, metric_name)
          except AttributeError:
              pass
  
          try:
              delattr(skll.metrics, metric_name)
          except AttributeError:
              pass
  
          # remove any metric functions from _CUSTOM_METRICS
          if metric_name in _CUSTOM_METRICS:
              del _CUSTOM_METRICS[metric_name]
  
      for module_name in ["custom_metrics", "custom_metrics2"]:
          try:
              del sys.modules[module_name]
          except KeyError:
              pass
  
imports: import json
  import sys
  import unittest
  from itertools import chain
  import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal, assert_raises_regex
  from sklearn.metrics import fbeta_score
  import skll.metrics
  from skll.data import NDJReader
  from skll.experiments import run_configuration
  from skll.learner import Learner
  from skll.metrics import _CUSTOM_METRICS, register_custom_metric, use_score_func
  from skll.utils.testing import config_dir, fill_in_config_paths_for_single_file, make_classification_data, other_dir, output_dir, unlink
label_desc: Use image node_id 3 for calling the TestCustomMetrics obj's underlying member method code with example usage: obj._cleanup_custom_metrics() without return types