Inductor Freezing (#100652)
Adds a freezing pass that will constant fold parameters in inductor `config.freezing`. This occurs post functionalization in aot autograd to capture both dispatching and allow passes to occur post functionalization. A few notes:
- There is an option to discard parameters `config.freezing_discard_parameters` which will take the current eager modules and wrap parameters to a Tensor subclass which will error if used.
- I needed to expose flat_params in aot_autograd in order to discard old references when we constant fold away parameters, like with amp. I also exposed `fw_metadata` to avoid constant folding mutated paraemters.
- Caching parameter transformations/constant folding across different inferences nyi
- Checking version_counter of constant folded params nyi
I'm not really sure what the actual naming should be. In jit there was both "freezing", which was platform agnostic, and "optimize for inference", which made device specific optimizations. We're doing the latter here but maybe freezing is a better name.
Differential Revision: [D46244033](https://our.internmc.facebook.com/intern/diff/D46244033)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/100652
Approved by: https://github.com/jansel
