code: def test_gmm_correct_covariance_type():
      """Test that GMM estimation is successful when the correct covariance type
      is passed in as a keyword argument.
      """
  
      gmm = learn_gmm(
          np.random.random((10, 10)),
          n_modes=2,
          gm_args={"covariance_type": "diag"},
      )
  
      assert gmm.means_ is not None
      assert gmm.covariances_ is not None
      assert gmm.weights_ is not None
  
file_path: scikit-image/skimage/feature/tests/test_fisher_vector.py
imports: import pytest
  import numpy
  from skimage.feature._fisher_vector import learn_gmm, fisher_vector, FisherVectorException, DescriptorException
label_desc: Use image node_id 8 for calling a global function with example usage: test_gmm_correct_covariance_type() without return types