code: def test_from_summaries_weighted_inertia(X, w, probs):
      d = Bernoulli(probs, inertia=0.3)
      d.summarize(X, sample_weight=w)
      d.from_summaries()
      _test_efd_from_summaries(
          d, "probs", "_log_probs", [0.602727, 0.770091, 0.365545]
      )
  
      d = Bernoulli(probs, inertia=1.0)
      d.summarize(X[:4])
      d.from_summaries()
      _test_efd_from_summaries(d, "probs", "_log_probs", probs)
  
      d.summarize(X[4:])
      d.from_summaries()
      _test_efd_from_summaries(d, "probs", "_log_probs", probs)
  
      d = Bernoulli(probs, inertia=1.0)
      d.summarize(X)
      d.from_summaries()
      _test_efd_from_summaries(d, "probs", "_log_probs", probs)
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Bernoulli
  from ._utils import _test_initialization_raises_one_parameter
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._utils import _test_efd_from_summaries
  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_weighted_inertia(X, w, probs) without return types