Use _WeakTensorRef over weakref in test_autograd.py (#55726)
Summary:
There are a few autograd tests checking for tensors leaked by reference cycles. This changes them to use `_WeakTensorRef` over `weakref`. `_WeakTensorRef`, added in https://github.com/pytorch/pytorch/issues/52874, accesses the C++ level `TensorImpl` reference count, compared to `weakref` which accesses python refcounts and so can only tell if the python wrapper object gets deallocated. Not only is this less code, it's also more accurately detecting that the Tensor itself is deallocated.
I didn't touch `weakref` usage in [test_anomaly_assign_parent_cleanup](https://github.com/pytorch/pytorch/blob/fc349cbcde10a5d9e8c1fc9a47bbba025a8e9018/test/test_autograd.py#L3733) and [test_nested_anomaly_printstack_cleanup](https://github.com/pytorch/pytorch/blob/fc349cbcde10a5d9e8c1fc9a47bbba025a8e9018/test/test_autograd.py#L3772) because these are intentionally testing for python object cleanup.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55726
Reviewed By: ngimel
Differential Revision: D27718526
Pulled By: albanD
fbshipit-source-id: 37a4914360e35dd4ae8db06b29525cebec4d4b84
