code: def test_issues_from_scores_different_input_sizes():
      # Test if function works correctly for different sizes of input arrays
      for num_images in range(1, 5):
          image_scores = np.random.rand(num_images)
          pixel_scores = np.random.rand(num_images, 100, 100)
          issues_from_score_result = issues_from_scores(
              image_scores, pixel_scores, threshold=0.5
          )
          assert np.shape(issues_from_score_result) == np.shape(
              pixel_scores
          )
  
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 13 for calling a global function with example usage: test_issues_from_scores_different_input_sizes() without return types