code: def test_fit_chain(X):
      d = Poisson().fit(X[:4])
      _test_efd_from_summaries(
          d, "lambdas", "_log_lambdas", [1.0, 1.25, 1.25]
      )
  
      d.fit(X[4:])
      _test_efd_from_summaries(
          d, "lambdas", "_log_lambdas", [3.333333, 1.0, 1.3333333]
      )
  
      d = Poisson().fit(X)
      _test_efd_from_summaries(
          d, "lambdas", "_log_lambdas", [2.0, 1.142857, 1.285714]
      )
  
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 36 for calling a global function with example usage: test_fit_chain(X) without return types