code: def test_initialize(X, probs):
      d = ConditionalCategorical()
      assert d.d is None
      assert d.probs is None
      assert d._initialized == False
      assert_raises(AttributeError, getattr, d, "_w_sum")
      assert_raises(AttributeError, getattr, d, "_xw_sum")
      assert_raises(AttributeError, getattr, d, "_log_probs")
  
      d._initialize(2, [(2, 2), (2, 3)])
      assert d._initialized == True
      assert d.probs[0].shape == (2, 2)
      assert d.probs[1].shape == (2, 3)
      assert d.d == 2
  
      assert_array_almost_equal(d.probs[0], [[0.0, 0.0], [0.0, 0.0]])
      assert_array_almost_equal(d._w_sum[0], [0.0, 0.0])
      assert_array_almost_equal(d._xw_sum[0], [[0.0, 0.0], [0.0, 0.0]])
  
      assert_array_almost_equal(
          d.probs[1], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
      )
      assert_array_almost_equal(d._w_sum[1], [0.0, 0.0])
      assert_array_almost_equal(
          d._xw_sum[1], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
      )
  
      d._initialize(1, [(3, 2, 3)])
      assert d._initialized == True
      assert d.probs[0].shape == (3, 2, 3)
      assert d.d == 1
  
      assert_array_almost_equal(
          d.probs[0],
          [
              [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
              [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
              [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
          ],
      )
      assert_array_almost_equal(
          d._w_sum[0], [[0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
      )
      assert_array_almost_equal(
          d._xw_sum[0],
          [
              [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
              [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
              [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
          ],
      )
  
      d = ConditionalCategorical(probs)
      assert d._initialized == True
      assert d.d == 3
      assert d.n_categories == [(2, 2), (3, 2), (2, 2)]
  
      d._initialize(3, [(2, 2), (3, 2), (2, 2)])
      d.summarize(X)
      assert d._initialized == True
      assert d.probs[0].shape == (2, 2)
      assert d.probs[1].shape == (3, 2)
      assert d.probs[2].shape == (2, 2)
      assert d.d == 3
  
      assert_array_almost_equal(d._w_sum[0], [1.0, 6.0])
      assert_array_almost_equal(d._xw_sum[0], [[1.0, 0.0], [4.0, 2.0]])
  
      assert_array_almost_equal(d._w_sum[1], [0.0, 3.0, 4.0])
      assert_array_almost_equal(
          d._xw_sum[1], [[0.0, 0.0], [2.0, 1.0], [2.0, 2.0]]
      )
  
      assert_array_almost_equal(d._w_sum[2], [5.0, 2.0])
      assert_array_almost_equal(d._xw_sum[2], [[5.0, 0.0], [0.0, 2.0]])
  
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 9 for calling a global function with example usage: test_initialize(X, probs) without return types