code: def test_possible_and_impossible_reduce(self):
      # For reductions to work, the first and last operand must have the
      # same dtype.  For this parametric DType that is not necessarily true.
      a = self._get_array(2.0)
      # Addition reductin works (as of writing requires to pass initial
      # because setting a scaled-float from the default `0` fails).
      res = np.add.reduce(a, initial=0.0)
      assert res == a.astype(np.float64).sum()
  
      # But each multiplication changes the factor, so a reduction is not
      # possible (the relaxed version of the old refusal to handle any
      # flexible dtype).
      with pytest.raises(
          TypeError, match="the resolved dtypes are not compatible"
      ):
          np.multiply.reduce(a)
  
imports: import pytest
  import numpy
  from numpy.testing import assert_array_equal
  from numpy.core._multiarray_umath import _discover_array_parameters, _get_sfloat_dtype
label_desc: Use image node_id 13 for calling the TestSFloat obj's underlying member method code with example usage: obj.test_possible_and_impossible_reduce() without return types