code: def test_sample(self, implementation, n_samples=1000):
      h = self.new_hmm(implementation)
      X, state_sequence = h.sample(n_samples)
      assert X.ndim == 2
      assert len(X) == len(state_sequence) == n_samples
      assert len(np.unique(X)) == self.n_features
  
imports: import numpy
  from numpy.testing import assert_allclose
  import pytest
  from hmmlearn import hmm
  from .None import assert_log_likelihood_increasing, normalized
label_desc: Use image node_id 5 for calling the TestCategoricalHMM obj's underlying member method code with example usage: obj.test_sample(implementation, n_samples) without return types