code: def test_summary_sizes(monkeypatch):
      monkeypatch.setattr(plt, "show", lambda: None)
  
      for _ in range(5):
          h, w = np.random.randint(1, 100, 2)
          labels, pred_probs = np.random.randint(
              0, 2, (2, h, w)
          ), np.random.random((2, 2, h, w))
          issues = find_label_issues(
              labels,
              pred_probs,
              downsample=1,
              n_jobs=None,
              batch_size=1000,
          )
          class_300_issues = filter_by_class(
              0, issues, labels=labels, pred_probs=pred_probs
          )
          df = common_label_issues(issues, labels, pred_probs)
          display_issues(issues)
  
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 22 for calling a global function with example usage: test_summary_sizes(monkeypatch) without return types