code: def test_log_probability(model, X):
      logp = model.log_probability(X)
      assert_array_almost_equal(
          logp,
          [
              -3.3932,
              -5.3391,
              -5.7446,
              -4.9337,
              -6.7254,
              -5.4727,
              -3.3242,
              -6.9078,
              -5.8781,
              -4.646,
              -4.5282,
          ],
          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 7 for calling a global function with example usage: test_log_probability(model, X) without return types