[JIT] UseVariadicOp handles multiple lists (#66288)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66288
This change makes it so `UseVariadicOp` can transform ops with many Tensor list inputs.
Input pattern:
```
%output : Type = op(%list_1, %arg_1, %list_2, %list_3)
```
Output pattern:
```
%output : Type = variadic_op(%list_11, ..., %list_1N, %arg_1, %list_21, ..., %list_2M, %list_31, ..., %list_3K, N, M, K)
```
The length of each list is passed at the end of the variadic op so that the op implementation can process the inputs appropriately. This also frees us from needing to update `hasVarArgs` in static runtime each time we add a variadic op.
This diff also makes `UseVariadicOp` more robust. Before, `list_idx` was passed as an argument. Now, `VariadicUpdater` determines `list_idx` from the node's schema.
Test Plan:
Existing variadic ops do not break:
`buck test caffe2/benchmarks/static_runtime:static_runtime_cpptest`
Reviewed By: d1jang
Differential Revision: D31450811
fbshipit-source-id: 808fcc3ae8940b9e602586f38f8cf9154c9a6462
