code: def test_modf_execution(setup):
      data1 = np.random.random((5, 9))
  
      arr1 = tensor(data1.copy(), chunk_size=3)
  
      o1, o2 = modf(arr1)
      o = o1 + o2
  
      res = o.execute().fetch()
      expected = sum(np.modf(data1))
      np.testing.assert_array_almost_equal(res, expected)
  
      o1, o2 = modf([0, 3.5])
      o = o1 + o2
  
      res = o.execute().fetch()
      expected = sum(np.modf([0, 3.5]))
      np.testing.assert_array_almost_equal(res, expected)
  
      arr1 = tensor(data1.copy(), chunk_size=3)
      o1 = zeros(data1.shape, chunk_size=3)
      o2 = zeros(data1.shape, chunk_size=3)
      modf(arr1, o1, o2)
      o = o1 + o2
  
      res = o.execute().fetch()
      expected = sum(np.modf(data1))
      np.testing.assert_array_almost_equal(res, expected)
  
      data1 = sps.random(5, 9, density=0.1)
  
      arr1 = tensor(data1.copy(), chunk_size=3)
  
      o1, o2 = modf(arr1)
      o = o1 + o2
  
      res = o.execute().fetch()
      expected = sum(np.modf(data1.toarray()))
      np.testing.assert_equal(res.toarray(), expected)
  
imports: import functools
  import operator
  import numpy
  import scipy.sparse
  import pytest
  from ....config import option_context
  from ....session import execute, fetch
  from ....tests.core import require_cupy
  from ....utils import ignore_warning
  from ...datasource import ones, tensor, zeros, arange
  from ..None import add, cos, truediv, frexp, modf, clip, isclose, arctan2, tree_add, tree_multiply
label_desc: Use image node_id 13 for calling a global function with example usage: test_modf_execution(setup) without return types