code: def test_fit_weighted(model, X, w):
      model.fit(X, sample_weight=w)
  
      assert_array_almost_equal(
          model._w_sum, [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
      )
      assert_array_almost_equal(
          model._xw_sum, [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
      )
      assert_array_almost_equal(
          model.centroids, [[0.428571, 1.0, 0.857143], [3.0, 1.0, 0.5]]
      )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.kmeans import KMeans
  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 26 for calling a global function with example usage: test_fit_weighted(model, X, w) without return types