code: def test_outplace_with_invalid_grads(self, device, dtype, op):
      func, *_ = self._get_funcs(op)
      sample = next(
          iter(
              op.sample_inputs(
                  dtype=dtype,
                  device=device,
                  requires_grad=True,
                  num_input_tensors=[2],
                  same_size=True,
              )
          )
      )
      self.assertTrue(all(t.requires_grad for t in sample.input))
      (out1, out2) = func(
          [sample.input, *sample.args],
          is_cuda=False,
          expect_fastpath=False,
          **sample.kwargs,
      )
      out1.backward(torch.ones_like(out1))
      self.assertIsNotNone(sample.input[0].grad)
      self.assertIsNone(sample.input[1].grad)
  
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 21 for calling the TestForeach obj's underlying member method code with example usage: obj.test_outplace_with_invalid_grads(device, dtype, op) without return types