code: def test_frexp_execution(setup):
      data1 = np.random.RandomState(0).randint(0, 100, (5, 9, 6))
  
      arr1 = tensor(data1.copy(), chunk_size=4)
  
      o1, o2 = frexp(arr1)
      o = o1 + o2
  
      res = o.execute().fetch()
      expected = sum(np.frexp(data1))
      np.testing.assert_array_almost_equal(res, expected)
  
      arr1 = tensor(data1.copy(), chunk_size=4)
      o1 = zeros(data1.shape, chunk_size=4)
      o2 = zeros(data1.shape, dtype="i8", chunk_size=4)
      frexp(arr1, o1, o2)
      res1, res2 = fetch(*execute(o1, o2))
  
      res = res1 * 2**res2
      np.testing.assert_array_almost_equal(res, data1, decimal=3)
  
      data1 = sps.random(5, 9, density=0.1)
  
      arr1 = tensor(data1.copy(), chunk_size=4)
  
      o1, o2 = frexp(arr1)
      o = o1 + o2
  
      res = o.execute().fetch()
      expected = sum(np.frexp(data1.toarray()))
      np.testing.assert_equal(res.toarray(), expected)
  
      x = np.arange(9)
      a = np.zeros(9)
      b = np.zeros(9)
      mx = arange(9)
      ma = zeros(9)
      mb = zeros(9)
      res = frexp(mx, ma, mb, where=mx > 5).execute()
      expected = np.frexp(x, a, b, where=x > 5)
      np.testing.assert_equal(res[0], expected[0])
      np.testing.assert_equal(res[1], expected[1])
  
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 11 for calling a global function with example usage: test_frexp_execution(setup) without return types