Add tensor to fake clone snapshot for immutable source of truth (#100128)
There's a longstanding, well known mutability bug in dynamo, https://github.com/pytorch/pytorch/issues/93610 (and more issues, but this is the one I had at hand).
Ops that do in place mutation of tensors will mutate their corresponding FakeTensors.
So, for example, if you do `t_` on a tensor, you will reverse its strides. This, in turn, means that the FakeTensors strides are now also reversed, say, if you are trying to torch.compile:
```
class F(torch.nn.Module):
def forward(self, x, y):
x = x.t_()
y = y.t_()
return (x + y,)
```
However, we recently introduced accessing the fake_tensor memo/cache to get the symbolic shape values for sizes and strides during guard installation time.
This means that tensors captured with a given size and stride, say, for x above, size:(3,3) stride:(3, 1), will get their memo updates to size(3, 3), stride(1, 3). Now, whenever you access this value for anything, it reflects it's current state in the tracing, as opposed to the state at which we initially started tracing on.
This causes us to produce guards that are never valid, for the example above, that `x.stride()[0] == 3`.
The solution is to not allow mutation to affect the fake tensors we use as source of truth here. We can do this by forcing a clone of the fake tensor at builder time, and storing that as the source of truth for our dynamic sizes and strides during guard installation.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/100128
Approved by: https://github.com/ezyang
