code: def test_sample(model):
      torch.manual_seed(0)
  
      X = model.sample(1)
      assert_array_almost_equal(X, [[[2], [1], [2]]])
  
      X = model.sample(5)
      assert_array_almost_equal(
          X,
          [
              [[1], [2], [0]],
              [[2], [2], [2]],
              [[0], [2], [0]],
              [[2], [1], [0]],
              [[0], [0], [2]],
          ],
          3,
      )
  
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 6 for calling a global function with example usage: test_sample(model) without return types