code: def test_0dim_tensor_overload_cpu_ok(self):
      tensors = [
          torch.ones((), device="cuda", dtype=torch.float32)
          for _ in range(2)
      ]
      scalar_cpu_tensor = torch.tensor(4.0, device="cpu")
  
      # For mul and div, the scalar is allowed to be on CPU too
      actual = torch._foreach_mul(tensors, scalar_cpu_tensor)
      self.assertEqual(
          actual, [t.mul(scalar_cpu_tensor) for t in tensors]
      )
      actual = torch._foreach_div(tensors, scalar_cpu_tensor)
      self.assertEqual(
          actual, [t.div(scalar_cpu_tensor) for t in tensors]
      )
  
imports: from contextlib import nullcontext
  from numbers import Number
  import random
  import re
  import torch
  import unittest
  import itertools
  import weakref
  from torch.testing import make_tensor
  from torch.testing._comparison import default_tolerances
  from torch.testing._internal.common_cuda import TEST_MULTIGPU
  from torch.testing._internal.common_utils import TestCase, run_tests, TEST_WITH_ROCM, skipIfTorchDynamo, parametrize, gradcheck
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, dtypes, onlyCUDA, ops, OpDTypes
  from torch.testing._internal.common_methods_invocations import foreach_unary_op_db, foreach_binary_op_db, foreach_pointwise_op_db, foreach_reduce_op_db, foreach_other_op_db
  from torch.testing._internal.common_dtype import all_types_and_complex_and, floating_types_and, floating_types, integral_types_and
label_desc: Use image node_id 24 for calling the TestForeach obj's underlying member method code with example usage: obj.test_0dim_tensor_overload_cpu_ok() without return types