code: def test_partial_summarize(model, X, y):
      model.summarize(X[:4], y[:4])
      assert_array_almost_equal(model._w_sum, [2.0, 2.0])
  
      model.summarize(X[4:], y[4:])
      assert_array_almost_equal(model._w_sum, [6.0, 5.0])
  
      model = BayesClassifier([Exponential(), Exponential()])
      model.summarize(X[:4], y[:4])
      assert_array_almost_equal(model._w_sum, [2.0, 2.0])
  
      model.summarize(X[4:], y[4:])
      assert_array_almost_equal(model._w_sum, [6.0, 5.0])
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.bayes_classifier import BayesClassifier
  from pomegranate.distributions import Exponential
  from .distributions._utils import _test_initialization_raises_one_parameter
  from .distributions._utils import _test_initialization
  from .distributions._utils import _test_predictions
  from .distributions._utils import _test_efd_from_summaries
  from .distributions._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 20 for calling a global function with example usage: test_partial_summarize(model, X, y) without return types