code: def test_fit_sparse_data(self, implementation):
      n_samples = 1000
      h = self.new_hmm(implementation)
      h.means_ *= 1000  # this will put gaussians very far apart
      X, _states = h.sample(n_samples)
  
      # this should not raise
      # "ValueError: array must not contain infs or NaNs"
      h._init(X, [1000])
      h.fit(X)
  
imports: import numpy
  from numpy.testing import assert_allclose, assert_array_less
  import pytest
  from sklearn.utils import check_random_state
  from ..hmm import GMMHMM
  from .test_gmm_hmm import create_random_gmm
  from .None import assert_log_likelihood_increasing, normalized
label_desc: Use image node_id 8 for calling the GMMHMMTestMixin obj's underlying member method code with example usage: obj.test_fit_sparse_data(implementation) without return types