class_docstr: Test cases related to more complex DType promotions.  Further promotion
  tests are defined in `test_numeric.py`
code: def test_complex_scalar_value_based(self, other, expected):
      # This would change if we modify the value based promotion
      complex_scalar = 1j
  
      res = np.result_type(other, complex_scalar)
      assert res == expected
      # Check the same for a simple ufunc call that uses the same logic:
      res = np.minimum(np.ones(3, dtype=other), complex_scalar).dtype
      assert res == expected
  
imports: import functools
  import operator
  import pickle
  import sys
  import types
  from itertools import permutations
  from typing import Any
  from unittest import skipIf
  import pytest
  from pytest import raises
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, subtest, TEST_WITH_TORCHDYNAMO, TestCase, xpassIfTorchDynamo
  import numpy
label_desc: Use image node_id 2 for calling the TestPromotion obj's underlying member method code with example usage: obj.test_complex_scalar_value_based(other, expected) without return types