code: def test_from_summaries_weighted(X, w, probs):
      for param in probs, None:
          d = JointCategorical(probs)
          d.summarize(X[:4], sample_weight=w[:4])
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.7179],
                      [0.0000, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.0000, 0.0000],
                      [0.2821, 0.0000],
                  ],
              ],
          )
  
          d.summarize(X[4:], sample_weight=w[4:])
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.0000],
                      [0.2396, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.7604, 0.0000],
                      [0.0000, 0.0000],
                  ],
              ],
          )
  
          d = JointCategorical(probs)
          d.summarize(X, sample_weight=w)
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "probs",
              "_log_probs",
              [
                  [
                      [0.0000, 0.2074],
                      [0.1704, 0.0000],
                      [0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000],
                      [0.5407, 0.0000],
                      [0.0815, 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 23 for calling a global function with example usage: test_from_summaries_weighted(X, w, probs) without return types