code: def test_binary_op_list_slow_path(self, device, dtype, op):
      foreach_op, native_op, foreach_op_, native_op_ = self._get_funcs(
          op
      )
      # 0-strides
      tensor1 = make_tensor((10, 10), dtype=dtype, device=device)
      tensor2 = make_tensor((1,), device=device, dtype=dtype).expand_as(
          tensor1
      )
      inputs = ([tensor1], [tensor2])
      self._binary_test(
          dtype,
          foreach_op,
          native_op,
          inputs,
          is_fastpath=False,
          is_inplace=False,
          alpha=None,
          scalar_self_arg=False,
      )
      self._binary_test(
          dtype,
          foreach_op_,
          native_op_,
          inputs,
          is_fastpath=False,
          is_inplace=True,
          alpha=None,
          scalar_self_arg=False,
      )
  
      # different strides
      tensor1 = torch.zeros(10, 10, device=device, dtype=dtype)
      tensor2 = torch.ones(10, 10, device=device, dtype=dtype)
      inputs = ([tensor1], [tensor2.t()])
      self._binary_test(
          dtype,
          foreach_op,
          native_op,
          inputs,
          is_fastpath=False,
          is_inplace=False,
          alpha=None,
          scalar_self_arg=False,
      )
      self._binary_test(
          dtype,
          foreach_op_,
          native_op_,
          inputs,
          is_fastpath=False,
          is_inplace=True,
          alpha=None,
          scalar_self_arg=False,
      )
  
      # non contiguous
      tensor1 = make_tensor(
          (5, 2, 1, 3), device=device, dtype=dtype, noncontiguous=True
      )
      tensor2 = make_tensor(
          (5, 2, 1, 3), device=device, dtype=dtype, noncontiguous=True
      )
      self.assertFalse(tensor1.is_contiguous())
      self.assertFalse(tensor2.is_contiguous())
      inputs = ([tensor1], [tensor2])
      self._binary_test(
          dtype,
          foreach_op,
          native_op,
          inputs,
          is_fastpath=False,
          is_inplace=False,
          alpha=None,
          scalar_self_arg=False,
      )
      self._binary_test(
          dtype,
          foreach_op_,
          native_op_,
          inputs,
          is_fastpath=False,
          is_inplace=True,
          alpha=None,
          scalar_self_arg=False,
      )
  
      # sliced tensor
      tensor1 = make_tensor((5, 2, 1, 3), device=device, dtype=dtype)
      tensor2 = make_tensor(
          (5, 2, 1, 3 * 7), device=device, dtype=dtype
      )[:, :, :, ::7]
      inputs = ([tensor1], [tensor2])
      self._binary_test(
          dtype,
          foreach_op,
          native_op,
          inputs,
          is_fastpath=False,
          is_inplace=False,
          alpha=None,
          scalar_self_arg=False,
      )
      self._binary_test(
          dtype,
          foreach_op_,
          native_op_,
          inputs,
          is_fastpath=False,
          is_inplace=True,
          alpha=None,
          scalar_self_arg=False,
      )
  
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 13 for calling the TestForeach obj's underlying member method code with example usage: obj.test_binary_op_list_slow_path(device, dtype, op) without return types