code: def test_clf_fit_inm():
      cl = CleanLearning()
      # Example of a bad noise matrix (impossible to learn from)
      inm = np.array([[0.1, 0.9], [0.9, 0.1]])
      try:
          cl.fit(
              X=np.arange(3),
              labels=np.array([0, 0, 1]),
              inverse_noise_matrix=inm,
          )
      except Exception as e:
          assert "Trace(inverse_noise_matrix)" in str(e)
          with pytest.raises(ValueError) as e:
              cl.fit(
                  X=np.arange(3),
                  labels=np.array([0, 0, 1]),
                  inverse_noise_matrix=inm,
              )
  
imports: from copy import deepcopy
  import warnings
  from sklearn.linear_model import LogisticRegression
  from sklearn.base import BaseEstimator
  from sklearn.model_selection import GridSearchCV
  import scipy
  import pytest
  import numpy
  import pandas
  from cleanlab.classification import CleanLearning
  from cleanlab.benchmarking.noise_generation import generate_noise_matrix_from_trace
  from cleanlab.benchmarking.noise_generation import generate_noisy_labels
  from cleanlab.internal.latent_algebra import compute_inv_noise_matrix
  from cleanlab.count import compute_confident_joint, estimate_cv_predicted_probabilities, get_confident_thresholds
  from cleanlab.filter import find_label_issues
label_desc: Use image node_id 17 for calling a global function with example usage: test_clf_fit_inm() without return types