code: def test_log_probability(model, X):
      logp = model.log_probability(X)
      assert_array_almost_equal(
          logp,
          [
              -4.0935,
              -3.9571,
              -5.4276,
              -6.4169,
              -2.3241,
              -9.0034,
              -1.8418,
              -5.1051,
              -1.3582,
              -4.6289,
              2.4106,
          ],
          4,
      )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.bayes_classifier import BayesClassifier
  from pomegranate.distributions import Exponential
  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 12 for calling a global function with example usage: test_log_probability(model, X) without return types