code: def test_low_example_count():
      data_tiny = make_data(num_examples=3)
      X_tiny, y_tiny = data_tiny["X"], data_tiny["y"]
  
      try:
          cl = CleanLearning()
          cl.find_label_issues(X_tiny, y_tiny)
      except ValueError as e:
          assert "There are too few examples" in str(e)
  
      cl = CleanLearning(cv_n_folds=3)
      cl.find_label_issues(X_tiny, y_tiny)
      assert isinstance(cl.get_label_issues(), pd.DataFrame)
  
imports: import pytest
  import random
  import numpy
  import pandas
  from sklearn.svm import SVR
  from sklearn.metrics import r2_score
  from sklearn.linear_model import LinearRegression
  from cleanlab.regression.rank import get_label_quality_scores, _get_residual_score_for_each_label, _get_outre_score_for_each_label
  from cleanlab.regression.learn import CleanLearning
label_desc: Use image node_id 13 for calling a global function with example usage: test_low_example_count() without return types