code: def test_from_summaries_null(X, probs):
      d = Categorical(probs)
      d.from_summaries()
      assert (
          d.probs[1, 0] != probs[1][0] and d.probs[0][1] != probs[0][1]
      )
      assert_array_almost_equal(d._w_sum, [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],
          ],
      )
  
      d = Categorical(probs, inertia=0.5)
      d.from_summaries()
      assert (
          d.probs[1, 0] != probs[1][0] and d.probs[0][1] != probs[0][1]
      )
      assert_array_almost_equal(d._w_sum, [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],
          ],
      )
  
      d = Categorical(probs, inertia=0.5, frozen=True)
      d.from_summaries()
      _test_fit_params(
          d,
          [
              [0.1, 0.2, 0.2, 0.5],
              [0.3, 0.1, 0.3, 0.3],
              [0.7, 0.05, 0.05, 0.2],
          ],
      )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Categorical
  from ._utils import _test_initialization_raises_one_parameter
  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 28 for calling a global function with example usage: test_from_summaries_null(X, probs) without return types