code: def test_bad_covariance_type(self, implementation):
      with pytest.raises(ValueError):
          h = hmm.GaussianHMM(
              20,
              implementation=implementation,
              covariance_type="badcovariance_type",
          )
          h.means_ = self.means
          h.covars_ = []
          h.startprob_ = self.startprob
          h.transmat_ = self.transmat
          h._check()
  
imports: import numpy
  from numpy.testing import assert_allclose
  import pytest
  from sklearn.utils import check_random_state
  from ..None import hmm
  from .None import assert_log_likelihood_increasing, make_covar_matrix, normalized
label_desc: Use image node_id 2 for calling the GaussianHMMTestMixin obj's underlying member method code with example usage: obj.test_bad_covariance_type(implementation) without return types