code: def test_binary_op_tensors_on_different_devices(
      self, device, dtype, op
  ):
      # `tensors1`: ['cuda', 'cpu']
      # `tensors2`: ['cuda', 'cpu']
      _cuda_tensors = next(
          iter(
              op.sample_inputs(
                  device, dtype, num_input_tensors=[2], same_size=True
              )
          )
      ).input
      _cpu_tensors = next(
          iter(
              op.sample_inputs(
                  "cpu", dtype, num_input_tensors=[2], same_size=True
              )
          )
      ).input
      tensors1, tensors2 = list(zip(_cuda_tensors, _cpu_tensors))
  
      foreach_op, foreach_op_ = op.method_variant, op.inplace_variant
      native_op, native_op_ = op.ref, op.ref_inplace
      try:
          actual = foreach_op(tensors1, tensors2)
      except RuntimeError as e:
          with self.assertRaisesRegex(type(e), re.escape(str(e))):
              [native_op(t1, t2) for t1, t2 in zip(tensors1, tensors2)]
      else:
          expected = [
              native_op(t1, t2) for t1, t2 in zip(tensors1, tensors2)
          ]
          self.assertEqual(expected, actual)
      try:
          foreach_op_(tensors1, tensors2)
      except RuntimeError as e:
          with self.assertRaisesRegex(type(e), re.escape(str(e))):
              [native_op_(t1, t2) for t1, t2 in zip(tensors1, tensors2)]
      else:
          self.assertEqual(actual, tensors1)
  
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 16 for calling the TestForeach obj's underlying member method code with example usage: obj.test_binary_op_tensors_on_different_devices(device, dtype, op) without return types