* Two op interfaces, one for querying instance metadata and one for getting static data needed to construct an op from a generic form.
* For torch.generic_kernel ops, metadata is splatted in during capture from Torch (it comes from the op registry, which will work for either device capture or graph import).
* Moved the 'add' out of the generated set so I can experiment on it. It implements the TorchBuildableKernelOpInterface interface which provides its metadata.
* The ATenRecognizeKernelsPass pass generically lowers from a torch.generic_kernel to recognized ops that implement the TorchBuildableKernelOpInterface, handling the various types of transformations that we allow at this stage.
* Enables the conv2d fwd test and ResA (which are both small).
* Deletes resnet18 and vgg, which both run but generate output that crashes FileCheck and lit (or at least makes them take an eternity).
* Adds a trampoline/loader 'torch_mlir' module.
* Plumbs through the MLIR python Context and Module creation, interoping with the MLIR Python API (resolves TODO on creating with own context and accessing the module being built).
* Inter-module Python API interop is still a bit rough but workable via the capsule mechanism. Can be evolved later.
* Exports the frontends/pytorch python sources to the project python/ build directory.
* Requires D89294 to land.
* Also adds two lit tests to verify that all of our extensions load without fireworks, which is a good indication that the shared library deps are sane.
* Bumps llvm-project version to use D89167.
* Had to stop short of modifying the function return signature because of a missing C-API upstream.
* Committing here is good enough for a test and will resolve the various TODOs about upstream APIs next.
* Adds at::Tensor -> MlirValue tracking.
* Adds conversions for tensor and scalar types to MLIR types.
* Adds npcomp C APIs for constructing custom types.
* Reworks pybind include so as to get Torch pybind helpers (needed to pass at::Tensor type from Python->C++).
* Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise).
* Quite a few TODOs and not yet populating the function in any way.
* Uses the new dispatcher API.
* Just prints to the console for the moment when an op is captured.
* Executes the op through the existing implementation.
Stella Laurenzo