code: def test_allclose_execution(setup):
      a = tensor([1e10, 1e-7], chunk_size=1)
      b = tensor([1.00001e10, 1e-8], chunk_size=1)
  
      t = allclose(a, b)
  
      res = t.execute().fetch()
      assert res is False
  
      a = tensor([1e10, 1e-8], chunk_size=1)
      b = tensor([1.00001e10, 1e-9], chunk_size=1)
  
      t = allclose(a, b)
  
      res = t.execute().fetch()
      assert res is True
  
      a = tensor([1.0, np.nan], chunk_size=1)
      b = tensor([1.0, np.nan], chunk_size=1)
  
      t = allclose(a, b, equal_nan=True)
  
      res = t.execute().fetch()
      assert res is True
  
      a = tensor(sps.csr_matrix([[1e10, 1e-7], [0, 0]]), chunk_size=1)
      b = tensor(
          sps.csr_matrix([[1.00001e10, 1e-8], [0, 0]]), chunk_size=1
      )
  
      t = allclose(a, b)
  
      res = t.execute().fetch()
      assert res is False
  
      # test string dtype
      with pytest.raises(TypeError):
          a = tensor(list("abcdefghi"), dtype=object)
          allclose(a, a).execute()
  
imports: import numpy
  import scipy.sparse
  import pytest
  from ....utils import ignore_warning
  from ...datasource import ones, tensor
  from ..None import mean, nansum, nanmax, nanmin, nanmean, nanprod, nanargmax, nanargmin, nanvar, nanstd, count_nonzero, allclose, array_equal, var, std, nancumsum, nancumprod
label_desc: Use image node_id 14 for calling a global function with example usage: test_allclose_execution(setup) without return types