code: def test_autograd_function_registered_to_cpu(self, mode):
      with autograd_fallback_mode(mode):
          lib = Library(self.test_ns, "FRAGMENT")
          lib.define("foo(Tensor self) -> Tensor")
  
          class NumpySin(torch.autograd.Function):
              @staticmethod
              def forward(ctx, x):
                  ctx.save_for_backward(x)
                  return torch.tensor(np.sin(x.cpu().numpy()))
  
              @staticmethod
              def backward(ctx, gx):
                  (x,) = ctx.saved_tensors
                  return gx * x.cos()
  
          lib.impl("foo", NumpySin.apply, "CPU")
          op = self.get_op("foo")
  
          x = torch.randn(3, requires_grad=True)
          y = op(x).sum()
          with self._check_ctx(mode):
              y.backward()
              self.assertEqual(x.grad, x.cos())
  
imports: import contextlib
  import warnings
  import numpy
  import torch
  from torch.library import Library
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TestCase
label_desc: Use image node_id 10 for calling the TestAutogradFallback obj's underlying member method code with example usage: obj.test_autograd_function_registered_to_cpu(mode) and returns: torch, unknown