code: def test_score_samples(self, implementation):
      X = np.array(
          [
              [1, 1, 3, 0],
              [3, 1, 1, 0],
              [3, 0, 2, 0],
              [2, 2, 0, 1],
              [2, 2, 0, 1],
              [0, 1, 1, 3],
              [1, 0, 3, 1],
              [2, 0, 1, 2],
              [0, 2, 1, 2],
              [1, 0, 1, 3],
          ]
      )
      n_samples = X.shape[0]
      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))
  
file_path: hmmlearn/lib/hmmlearn/tests/test_multinomial_hmm.py
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 3 for calling the TestMultinomialHMM obj's underlying member method code with example usage: obj.test_score_samples(implementation) without return types