code: def test_base_does_not_require_grad(self, mode):
      with autograd_fallback_mode(mode):
          lib = self.get_lib()
          lib.define("foo(Tensor(a!) x) -> Tensor(a!)")
          op = self.get_op("foo")
  
          def foo_impl(a):
              with torch.no_grad():
                  return a.zero_()
  
          lib.impl("foo", foo_impl, "CPU")
          x = torch.randn(3)
          y = x[:]
          y.requires_grad_()
          w = y[:]
          self.assertTrue(w._base is x)
  
          # Hook should be registered on w, but not w._base
          op(w)
          with self._check_ctx(mode):
              w.sum().backward()
  
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 16 for calling the TestAutogradFallback obj's underlying member method code with example usage: obj.test_base_does_not_require_grad(mode) and returns: a