code: def custom_issue_manager():
      from cleanlab.datalab.internal.issue_manager.issue_manager import (
          IssueManager,
      )
  
      class CustomIssueManager(IssueManager):
          issue_name = "custom_issue"
  
          def find_issues(self, custom_argument: int = 1, **_) -> None:
              # Flag example as an issue if the custom argument equals its index
              scores = [
                  abs(i - custom_argument) / (i + custom_argument)
                  for i in range(len(self.datalab.data))
              ]
              self.issues = pd.DataFrame(
                  {
                      f"is_{self.issue_name}_issue": [
                          i == custom_argument
                          for i in range(len(self.datalab.data))
                      ],
                      self.issue_score_key: scores,
                  },
              )
              summary_score = np.mean(scores)
              self.summary = self.make_summary(score=summary_score)
  
      return CustomIssueManager
  
file_path: cleanlab/tests/datalab/conftest.py
imports: import numpy
  import pandas
  import pytest
  from datasets import load_dataset
  from datasets.arrow_dataset import Dataset
  from PIL import Image
  from sklearn.neighbors import NearestNeighbors
  from cleanlab.datalab.datalab import Datalab
label_desc: Use image node_id 6 for calling a global function with example usage: custom_issue_manager() and returns: CustomIssueManager