* upstream/master: (117 commits)
  Add full namespace resolution in CAFFE_DURATION (pytorch#12065)
  T33898723: Simple put operators for caffe2 stats (pytorch#12057)
  add narrow() support for sparse tensors re: pytorch#8853 (pytorch#11342)
  Fix ONNX bug, add symbolic for full
  Enable tracing of tensor factories with an out argument
  Fix warnings emitted when testing distributions (pytorch#12038)
  Unify versions across setup.py, libtorch, and libcaffe2 (pytorch#12053)
  add autodiff expressions for common operations (pytorch#11832)
  Blob doesn't allow access to destroyCall anymore (pytorch#11548)
  IValue can store Blob (pytorch#11414)
  Move Blob to ATen/core (pytorch#11924)
  Use tempfile during serialized test comparison (pytorch#12021)
  fix segfault when grad to a hook fn is None (pytorch#12028)
  Fallback CreateMutex/AtomicIter operators for mkl-dnn
  Unify all *_EXPORT and *_IMPORT macros across c++ backend (pytorch#12019)
  Add safety asserts for methods on TensorImpl which don't work on Variable. (pytorch#12058)
  Make USE_IDEEP work again (pytorch#12026)
  Fix "identifier following the 'template' keyword does not refer to a template" (pytorch#12037)
  Delete some unused variables. (pytorch#12059)
  Support TypeIdentifier::name() (pytorch#12036)
  ...

Summary:
- fixes pytorch#11751 by checking if a grad is a Python None object before getting cdata from it
- behaviors:

pre-fix
```
>>> a = torch.randn(5, requires_grad=True)
>>> a_list = a.unbind()

>>> a0 = a_list[0]
>>> a0.register_hook
...:    def hook(grad):
...:        print(grad)

>>> a_list[0].backward()
tensor(1.)

>>> print('a_list[0]', a_list[0].grad, a.grad)
('a_list[0]', None, tensor([1., 0., 0., 0., 0.]))

>>> a_list[1].backward() # segfault
```

post-fix
```
>>> a = torch.randn(5, requires_grad=True)
>>> a_list = a.unbind()

>>> a0 = a_list[0]
>>> a0.register_hook
... :   def hook(grad):
... :       print(grad)

>>> a_list[0].backward()
tensor(1.)

>>> print(a_list[0].grad, a.grad)
(None, tensor([1., 0., 0., 0., 0.]))

>>> a_list[1].backward()
None

>>> print(a_list[1].grad, a.grad)
(None, tensor([1., 1., 0., 0., 0.]))
```
Pull Request resolved: pytorch#12028

Differential Revision: D10034094

Pulled By: weiyangfb

fbshipit-source-id: 3f2135325fa7d338b920f57752057e4f6a6c0b1d