[inductor] Apply fx passes recursively to nested subgraphs (#120665)
Summary: The current machinery of Inductor's `compile_fx` assumes that the incoming fx graph is flat. As a result, everything before `graph.run` is applied to the outermost graph. This assumption was valid before #119759, but now there is control flow bringing (arbitrarily deeply) nested fx subgraphs to `compile_fx`.
In this PR, we start extending the `compile_fx` machinery to deal with nested fx subgraphs. Namely, we recursively apply Inductor's `pre_grad`, `joint_graph`, and `post_grad` passes to the nested subgraphs in the incoming fx graph.
For the recursive application of the `pre_grad` passes (which require example inputs per subgraph), we don't pass example inputs for the nested subgraphs. A few different attempts to infer the latter via fake tensor prop has led to different side effects in the model. Therefore, to the nested subgraphs, we only apply a subset of `pre_grad` passes that doesn't require example inputs.
Test Plan:
```
$ python test/inductor/test_control_flow.py
...
----------------------------------------------------------------------
Ran 26 tests in 59.252s
OK
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/120665
Approved by: https://github.com/eellison
