code: def _test_BayesianGaussianMixture(
      self,
      n_components,
      weight_concentration_prior_type="dirichlet_process",
      covariance_type="full",
      backend="torch",
      extra_config={},
  ):
      X, y = make_blobs(n_samples=100, random_state=0)
  
      model = BayesianGaussianMixture(
          n_components=n_components,
          verbose=1,
          max_iter=100,
          covariance_type=covariance_type,
          weight_concentration_prior_type=weight_concentration_prior_type,
          random_state=0,
      )
      model.fit(X)
  
      torch_model = hummingbird.ml.convert(
          model, backend, X, extra_config=extra_config
      )
      self.assertTrue(torch_model is not None)
      np.testing.assert_allclose(
          model.predict(X), torch_model.predict(X), rtol=1e-6, atol=1e-6
      )
  
file_path: hummingbird/tests/test_sklearn_mixture.py
imports: import unittest
  import numpy
  from sklearn.mixture import BayesianGaussianMixture
  from sklearn.datasets import make_blobs
  import hummingbird.ml
label_desc: Use image node_id 1 for calling the TestSklearnMixture obj's underlying member method code with example usage: obj._test_BayesianGaussianMixture(n_components, weight_concentration_prior_type, covariance_type, backend, extra_config) without return types