This is an API change, so please review carefully.
With this PR, torchdynamo returns an `OptimizedModule` class object, a subclass of `torch.nn.Module`, when asked to optimize a `nn.Module` object. Most of the methods are redirected to the original `nn.Module`, which is installed as `_mod` in the `OptimizedModule`.
This is helpful for many cases
```
mod = MockModule()
opt_mod = torch._dynamo.optimize()(mod)
print(opt_mod) # Works
opt_mod = opt_mod.to(device="cuda")
print(opt_mod) # Works
opt_mod(input) # Triggers recompile if necessary, earlier we were shedding the TorchDynamo wrapper
opt_mod.parameters() # Refers to the original module
```
Topics unclear to me
* I have overridden many methods to raise NotImplementedError. A careful review of those will be good.
* hooks
* For the optimized forward, should we call torchdynamo optimization on `__call__` or `forward`
* What else to test
Pull Request resolved: https://github.com/pytorch/pytorch/pull/88629
Approved by: https://github.com/Chillee, https://github.com/jansel, https://github.com/msaroufim
