code: def test_issues_from_scores_various_thresholds():
      # Test if function works correctly for various values of threshold
      image_scores_softmin, pixel_scores = get_label_quality_scores(
          labels, pred_probs, method="softmin"
      )
      for threshold in [0.1, 0.5, 0.9]:
          issues_from_score_result = issues_from_scores(
              image_scores_softmin, pixel_scores, threshold=threshold
          )
          assert np.all(
              issues_from_score_result == (pixel_scores < threshold)
          )
  
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 11 for calling a global function with example usage: test_issues_from_scores_various_thresholds() without return types