code: def test_from_summaries_weighted(X, w, lambdas):
      for param in lambdas, None:
          d = Poisson(lambdas)
          d.summarize(X[:4], sample_weight=w[:4])
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "lambdas",
              "_log_lambdas",
              [0.333333, 0.666667, 0.666667],
          )
  
          d.summarize(X[4:], sample_weight=w[4:])
          d.from_summaries()
          _test_efd_from_summaries(
              d, "lambdas", "_log_lambdas", [3.0, 1.0, 0.5]
          )
  
          d = Poisson(lambdas)
          d.summarize(X, sample_weight=w)
          d.from_summaries()
          _test_efd_from_summaries(
              d,
              "lambdas",
              "_log_lambdas",
              [2.272727, 0.909091, 0.545455],
          )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Poisson
  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 27 for calling a global function with example usage: test_from_summaries_weighted(X, w, lambdas) without return types