code: def test_probability(model, X):
      p = model.probability(X)
      assert_array_almost_equal(
          p,
          [
              0.0336,
              0.0048,
              0.0032,
              0.0072,
              0.0012,
              0.0042,
              0.036,
              0.001,
              0.0028,
              0.0096,
              0.0108,
          ],
          4,
      )
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.markov_chain import MarkovChain
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import ConditionalCategorical
  from .distributions._utils import _test_initialization_raises_one_parameter
  from .distributions._utils import _test_initialization
  from .distributions._utils import _test_predictions
  from .distributions._utils import _test_efd_from_summaries
  from .distributions._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 9 for calling a global function with example usage: test_probability(model, X) without return types