code: def test_score_samples(self, implementation):
      idx = np.repeat(np.arange(self.n_components), 10)
      n_samples = len(idx)
      X = np.random.randint(self.n_features, size=(n_samples, 1))
      h = self.new_hmm(implementation)
  
      ll, posteriors = h.score_samples(X)
      assert posteriors.shape == (n_samples, self.n_components)
      assert_allclose(posteriors.sum(axis=1), np.ones(n_samples))
  
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 4 for calling the TestCategoricalHMM obj's underlying member method code with example usage: obj.test_score_samples(implementation) without return types