code: def test_probability_raises(model, X):
      assert_raises(ValueError, model.probability, [X])
      assert_raises(ValueError, model.probability, X[0])
      assert_raises((ValueError, TypeError), model.probability, X[0][0])
  
      assert_raises(
          ValueError,
          model.probability,
          [[MIN_VALUE - 0.1 for i in range(len(X[0]))]],
      )
      assert_raises(
          ValueError,
          model.probability,
          [[MAX_VALUE + 0.1 for i in range(len(X[0]))]],
      )
  
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 10 for calling a global function with example usage: test_probability_raises(model, X) without return types