Summary:
Currently, `reshape` does an `as_strided` when the geometry is viewable. However, `as_strided` backward is not very optimized, and can not always detect such cases. Improvements are planned at pytorch/pytorch#8965, and I will finish it some day. But the current situation is that in these cases backward through `reshape` will copy gradient while a simple `view` will not. This is unnecessary.

Notably this affects `flatten` and a whole bunch of other ops implemented on top of `reshape`.

```py
In [15]: x = torch.randn(3, 4, requires_grad=True)

In [16]: y = x.reshape(x.shape)

In [17]: assert y._base is not None

In [18]: gy = torch.randn_like(y)

In [20]: gx = torch.autograd.grad(y, x, gy)[0]

In [21]: gx
Out[21]:
tensor([[ 0.2189,  0.3396, -0.1108,  1.7703],
        [ 1.0737, -0.1222,  1.0765, -1.3363],
        [-1.3798, -0.2950,  0.0800,  0.2501]])

In [22]: gx._base  # not gy
Out[22]:
tensor([ 0.2189,  0.3396, -0.1108,  1.7703,  1.0737, -0.1222,  1.0765, -1.3363,
        -1.3798, -0.2950,  0.0800,  0.2501])

In [23]: gy.zero_()
Out[23]:
tensor([[0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.]])

In [24]: gx  # not sharing storage with gy
Out[24]:
tensor([[ 0.2189,  0.3396, -0.1108,  1.7703],
        [ 1.0737, -0.1222,  1.0765, -1.3363],
        [-1.3798, -0.2950,  0.0800,  0.2501]])

# but everything is optimized with view, which should be equivalent with reshape in this case
In [25]: y = x.view(x.shape)

In [26]: assert y._base is not None

In [27]: gy = torch.randn_like(y)

In [28]: gx = torch.autograd.grad(y, x, gy)[0]

In [29]: gx
Out[29]:
tensor([[-2.4463,  1.1446,  0.1501,  0.1212],
        [-1.1125,  1.4661,  0.9092, -0.2153],
        [-0.1937, -0.3381, -1.3883, -0.7329]])

In [30]: gy.zero_()
Out[30]:
tensor([[0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.]])

In [31]: gx  # sharing storage with gy
Out[31]:
tensor([[0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.]])

```
Pull Request resolved: pytorch/pytorch#28901

Differential Revision: D18240868

Pulled By: ezyang

fbshipit-source-id: 28fdaa0c7014a9dae6731dfe8b67784d38fc27f0