code: def test_from_summaries(X, probs):
      d = JointCategorical(probs)
      d.summarize(X)
      d.from_summaries()
      assert_raises(
          AssertionError, assert_array_almost_equal, probs, d.probs
      )
  
      for param in probs, None:
          d = JointCategorical(param)
          d.summarize(X[:4])
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.2500],
                      [0.0000, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.0000, 0.0000],
                      [0.7500, 0.0000],
                  ],
              ],
          )
  
          d.summarize(X[4:])
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.0000],
                      [0.3333, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.6667, 0.0000],
                      [0.0000, 0.0000],
                  ],
              ],
          )
  
          d = JointCategorical(param)
          d.summarize(X[:4])
          d.summarize(X[4:])
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.1429],
                      [0.1429, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.2857, 0.0000],
                      [0.4286, 0.0000],
                  ],
              ],
          )
  
          d = JointCategorical(param)
          d.summarize(X)
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.1429],
                      [0.1429, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.2857, 0.0000],
                      [0.4286, 0.0000],
                  ],
              ],
          )
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.distributions import JointCategorical
  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 22 for calling a global function with example usage: test_from_summaries(X, probs) without return types