code: def test_display_issues(monkeypatch):
      monkeypatch.setattr(plt, "show", lambda: None)
      issues = find_label_issues(
          labels, pred_probs, downsample=1, n_jobs=None, batch_size=1000
      )
      display_issues(issues, top=1)
  
      display_issues(
          issues,
          pred_probs=pred_probs,
          labels=labels,
          top=2,
          class_names=["one", "two"],
      )
  
      display_issues(
          issues, pred_probs=pred_probs, labels=labels, top=2
      )
      display_issues(issues, labels=labels, top=2)
      display_issues(issues, pred_probs=pred_probs, top=2)
  
      # too many issues for top
      display_issues(
          issues,
          pred_probs=pred_probs,
          labels=labels,
          top=len(issues) + 5,
      )
  
      class_issues = filter_by_class(
          0, issues, labels=labels, pred_probs=pred_probs
      )
      display_issues(
          class_issues, pred_probs=pred_probs, labels=labels, top=2
      )
  
      image_scores, pixel_scores = (
          image_scores_softmin,
          pixel_scores,
      ) = get_label_quality_scores(labels, pred_probs, method="softmin")
      issues_from_score = issues_from_scores(
          image_scores, pixel_scores, threshold=0.5
      )
      display_issues(
          issues_from_score, pred_probs=pred_probs, labels=labels, top=2
      )
  
      display_issues(
          issues_from_score,
          pred_probs=pred_probs,
          labels=labels,
          top=2,
          exclude=[0],
      )
  
      with pytest.raises(ValueError) as e:
          display_issues(
              issues_from_score,
              pred_probs=pred_probs,
              labels=None,
              top=2,
              exclude=[0],
          )
  
imports: import numpy
  import random
  import pytest
  from unittest import mock
  import matplotlib.pyplot
  from pathlib import Path
  from cleanlab.internal.multilabel_scorer import softmin
  from cleanlab.internal.segmentation_utils import _check_input, _get_valid_optional_params, _get_summary_optional_params
  from cleanlab.segmentation.filter import find_label_issues
  from cleanlab.segmentation.rank import get_label_quality_scores, issues_from_scores, _get_label_quality_per_image
  from cleanlab.segmentation.summary import display_issues, common_label_issues, filter_by_class, _generate_colormap
label_desc: Use image node_id 17 for calling a global function with example usage: test_display_issues(monkeypatch) without return types