class_docstr: Test cases related to more complex DType promotions.  Further promotion
  tests are defined in `test_numeric.py`
code: def test_python_integer_promotion(self, val):
      # If we only path scalars (mainly python ones!), the result must take
      # into account that the integer may be considered int32, int64, uint64,
      # or object depending on the input value.  So test those paths!
      expected_dtype = np.result_type(
          np.array(val).dtype, np.array(0).dtype
      )
      assert np.result_type(val, 0) == expected_dtype
      # For completeness sake, also check with a NumPy scalar as second arg:
      assert np.result_type(val, np.int8(0)) == expected_dtype
  
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 3 for calling the TestPromotion obj's underlying member method code with example usage: obj.test_python_integer_promotion(val) without return types