[mlir] Overhaul C/Python registration APIs to properly scope registration/loading activities.Since the very first commits, the Python and C MLIR APIs have had mis-placed registration/load functiona
[mlir] Overhaul C/Python registration APIs to properly scope registration/loading activities.Since the very first commits, the Python and C MLIR APIs have had mis-placed registration/load functionality for dialects, extensions, etc. This was done pragmatically in order to get bootstrapped and then just grew in. Downstreams largely bypass and do their own thing by providing various APIs to register things they need. Meanwhile, the C++ APIs have stabilized around this and it would make sense to follow suit.The thing we have observed in canonical usage by downstreams is that each downstream tends to have native entry points that configure its installation to its preferences with one-stop APIs. This patch leans in to this approach with `RegisterEverything.h` and `mlir._mlir_libs._mlirRegisterEverything` being the one-stop entry points for the "upstream packages". The `_mlir_libs.__init__.py` now allows customization of the environment and Context by adding "initialization modules" to the `_mlir_libs` package. If present, `_mlirRegisterEverything` is treated as such a module. Others can be added by downstreams by adding a `_site_initialize_{i}.py` module, where '{i}' is a number starting with zero. The number will be incremented and corresponding module loaded until one is not found. Initialization modules can:* Perform load time customization to the global environment (i.e. registering passes, hooks, etc).* Define a `register_dialects(registry: DialectRegistry)` function that can extend the `DialectRegistry` that will be used to bootstrap the `Context`.* Define a `context_init_hook(context: Context)` function that will be added to a list of callbacks which will be invoked after dialect registration during `Context` initialization.Note that the `MLIRPythonExtension.RegisterEverything` is not included by default when building a downstream (its corresponding behavior was prior). For downstreams which need the default MLIR initialization to take place, they must add this back in to their Python CMake build just like they add their own components (i.e. to `add_mlir_python_common_capi_library` and `add_mlir_python_modules`). It is perfectly valid to not do this, in which case, only the things explicitly depended on and initialized by downstreams will be built/packaged. If the downstream has not been set up for this, it is recommended to simply add this back for the time being and pay the build time/package size cost.CMake changes:* `MLIRCAPIRegistration` -> `MLIRCAPIRegisterEverything` (renamed to signify what it does and force an evaluation: a number of places were incidentally linking this very expensive target)* `MLIRPythonSoure.Passes` removed (without replacement: just drop)* `MLIRPythonExtension.AllPassesRegistration` removed (without replacement: just drop)* `MLIRPythonExtension.Conversions` removed (without replacement: just drop)* `MLIRPythonExtension.Transforms` removed (without replacement: just drop)Header changes:* `mlir-c/Registration.h` is deleted. Dialect registration functionality is now in `IR.h`. Registration of upstream features are in `mlir-c/RegisterEverything.h`. When updating MLIR and a couple of downstreams, I found that proper usage was commingled so required making a choice vs just blind S&R.Python APIs removed: * mlir.transforms and mlir.conversions (previously only had an __init__.py which indirectly triggered `mlirRegisterTransformsPasses()` and `mlirRegisterConversionPasses()` respectively). Downstream impact: Remove these imports if present (they now happen as part of default initialization). * mlir._mlir_libs._all_passes_registration, mlir._mlir_libs._mlirTransforms, mlir._mlir_libs._mlirConversions. Downstream impact: None expected (these were internally used).C-APIs changed: * mlirRegisterAllDialects(MlirContext) now takes an MlirDialectRegistry instead. It also used to trigger loading of all dialects, which was already marked with a TODO to remove -- it no longer does, and for direct use, dialects must be explicitly loaded. Downstream impact: Direct C-API users must ensure that needed dialects are loaded or call `mlirContextLoadAllAvailableDialects(MlirContext)` to emulate the prior behavior. Also see the `ir.c` test case (e.g. ` mlirContextGetOrLoadDialect(ctx, mlirStringRefCreateFromCString("func"));`). * mlirDialectHandle* APIs were moved from Registration.h (which now is restricted to just global/upstream registration) to IR.h, arguably where it should have been. Downstream impact: include correct header (likely already doing so).C-APIs added: * mlirContextLoadAllAvailableDialects(MlirContext): Corresponds to C++ API with the same purpose.Python APIs added: * mlir.ir.DialectRegistry: Mapping for an MlirDialectRegistry. * mlir.ir.Context.append_dialect_registry(MlirDialectRegistry) * mlir.ir.Context.load_all_available_dialects() * mlir._mlir_libs._mlirAllRegistration: New native extension that exposes a `register_dialects(MlirDialectRegistry)` entry point and performs all upstream pass/conversion/transforms registration on init. In this first step, we eagerly load this as part of the __init__.py and use it to monkey patch the Context to emulate prior behavior. * Type caster and capsule support for MlirDialectRegistryThis should make it possible to build downstream Python dialects that only depend on a subset of MLIR. See: https://github.com/llvm/llvm-project/issues/56037Here is an example PR, minimally adapting IREE to these changes: https://github.com/iree-org/iree/pull/9638/files In this situation, IREE is opting to not link everything, since it is already configuring the Context to its liking. For projects that would just like to not think about it and pull in everything, add `MLIRPythonExtension.RegisterEverything` to the list of Python sources getting built, and the old behavior will continue.Reviewed By: mehdi_amini, ftynseDifferential Revision: https://reviews.llvm.org/D128593
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[mlir] Rework subclass construction in PybindAdaptors.hThe constructor function was being defined without indicating its "__init__"name, which made it interpret it as a regular fuction rather than
[mlir] Rework subclass construction in PybindAdaptors.hThe constructor function was being defined without indicating its "__init__"name, which made it interpret it as a regular fuction rather than aconstructor. When overload resolution failed, Pybind would attempt to print thearguments actually passed to the function, including "self", which is notinitialized since the constructor couldn't be called. This would result in"__repr__" being called with "self" referencing an uninitialized MLIR C APIobject, which in turn would cause undefined behavior when attempting to printin C++. Even if the correct name is provided, the mechanism used byPybindAdaptors.h to bind constructors directly as "__init__" functions taking"self" is deprecated by Pybind. The new mechanism does not seem to have accessto a fully-constructed "self" object (i.e., the constructor in C++ takes a`pybind11::detail::value_and_holder` that cannot be forwarded back to Python).Instead, redefine "__new__" to perform the required checks (there are noadditional initialization needed for attributes and types as they are allwrappers around a C++ pointer). "__new__" can call its equivalent on asuperclass without needing "self".Bump pybind11 dependency to 3.8.0, which is the first version that allows oneto redefine "__new__".Reviewed By: stellaraccidentDifferential Revision: https://reviews.llvm.org/D117646
[mlir] support interfaces in Python bindingsIntroduce the initial support for operation interfaces in C API and Pythonbindings. Interfaces are a key component of MLIR's extensibility and should be
[mlir] support interfaces in Python bindingsIntroduce the initial support for operation interfaces in C API and Pythonbindings. Interfaces are a key component of MLIR's extensibility and should beavailable in bindings to make use of full potential of MLIR.This initial implementation exposes InferTypeOpInterface all the way to thePython bindings since it can be later used to simplify the operationconstruction methods by inferring their return types instead of requiring theuser to do so. The general infrastructure for binding interfaces is defined andInferTypeOpInterface can be used as an example for binding other interfaces.Reviewed By: gysitDifferential Revision: https://reviews.llvm.org/D111656