code: def test_overall_label_health_score_function_calls():
      dataset_name = "caltech256"
      (
          pred_probs,
          labels,
      ) = _get_pred_probs_labels_from_labelerrors_datasets(dataset_name)
      score = overall_label_health_score(
          labels=labels, pred_probs=pred_probs
      )
  
      confident_joint = compute_confident_joint(
          labels=labels, pred_probs=pred_probs
      )
      num_examples = len(labels)
      score_cj = overall_label_health_score(
          labels=None,
          pred_probs=pred_probs,
          confident_joint=confident_joint,
      )
      joint = estimate_joint(labels=labels, pred_probs=pred_probs)
      score_joint = overall_label_health_score(
          labels=None,
          pred_probs=pred_probs,
          joint=joint,
          num_examples=num_examples,
      )
      joint_cj = estimate_joint(
          labels=labels,
          pred_probs=pred_probs,
          confident_joint=confident_joint,
      )
      score_joint_cj = overall_label_health_score(
          labels=None,
          pred_probs=pred_probs,
          joint=joint_cj,
          num_examples=num_examples,
      )
      assert score_cj != score
      assert score_cj == score_joint
      assert score_joint_cj == score_joint
  
file_path: cleanlab/tests/test_dataset.py
imports: import requests
  import pytest
  import hypothesis.extra.numpy
  import hypothesis.strategies
  import io
  import numpy
  from hypothesis import given, settings
  from cleanlab.dataset import health_summary, find_overlapping_classes, rank_classes_by_label_quality, overall_label_health_score
  from cleanlab.count import estimate_joint, num_label_issues, compute_confident_joint
label_desc: Use image node_id 7 for calling a global function with example usage: test_overall_label_health_score_function_calls() without return types