code: def test_sample(probs, X):
      torch.manual_seed(0)
  
      X = ConditionalCategorical(probs).sample(1, [[[0, 1, 0]]])
      assert_array_almost_equal(X, [[1, 0, 1]])
  
      x = [
          [[0, 1, 0]],
          [[1, 1, 0]],
          [[0, 0, 0]],
          [[0, 0, 0]],
          [[1, 0, 1]],
      ]
  
      X = ConditionalCategorical(probs).sample(5, x)
      assert_array_almost_equal(
          X, [[1, 1, 1], [0, 1, 1], [1, 1, 0], [0, 1, 1], [1, 1, 0]], 3
      )
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.distributions import ConditionalCategorical
  from ._utils import _test_initialization_raises_one_parameter
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._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_sample(probs, X) without return types