code: def test_inplace_autograd_function_registered_to_cpu(self, mode):
      with autograd_fallback_mode(mode):
          lib = Library(self.test_ns, "FRAGMENT")
          lib.define("foo(Tensor(a!) self) -> Tensor(a!)")
  
          class NumpySin_(torch.autograd.Function):
              @staticmethod
              def forward(ctx, x):
                  ctx.save_for_backward(x.clone())
                  x_np = x.detach().numpy()
                  np.sin(x_np, out=x_np)
                  ctx.mark_dirty(x)
                  return x
  
              @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)
          z = x.clone()
          w = z[0]
          y = op(w)
  
          expected = torch.zeros_like(x)
          expected[0] = x[0].cos()
          with self._check_ctx(mode):
              (gx,) = torch.autograd.grad(
                  y, x, torch.ones_like(y), retain_graph=True
              )
              self.assertEqual(gx, expected)
  
          expected = torch.ones_like(x)
          expected[0] = x[0].cos()
          with self._check_ctx(mode):
              (gx,) = torch.autograd.grad(z, x, torch.ones_like(z))
              self.assertEqual(gx, expected)
  
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 11 for calling the TestAutogradFallback obj's underlying member method code with example usage: obj.test_inplace_autograd_function_registered_to_cpu(mode) and returns: x, unknown