[mlir] Fix Bazel for 5e83a5b4752da6631d79c446f21e5d128b5c5495Export the __init__.py from _mlir_libs.
[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][complex] Add Python bindings for complex ops.Reviewed By: aartbikDifferential Revision: https://reviews.llvm.org/D127916
[mlir] Introduce Transform ops for loopsIntroduce transform ops for "for" loops, in particular for peeling, softwarepipelining and unrolling, along with a couple of "IR navigation" ops. These ops
[mlir] Introduce Transform ops for loopsIntroduce transform ops for "for" loops, in particular for peeling, softwarepipelining and unrolling, along with a couple of "IR navigation" ops. These opsare intended to be generalized to different kinds of loops when possible andtherefore use the "loop" prefix. They currently live in the SCF dialect asthere is no clear place to put transform ops that may span across severaldialects, this decision is postponed until the ops actually need to handlenon-SCF loops.Additionally refactor some common utilities for transform ops into trait orinterface methods, and change the loop pipelining to be a returning pattern.Reviewed By: springermDifferential Revision: https://reviews.llvm.org/D127300
[mlir] provide Python bindings for the Transform dialectPython bindings for extensions of the Transform dialect are defined in separatePython source files that can be imported on-demand, i.e., tha
[mlir] provide Python bindings for the Transform dialectPython bindings for extensions of the Transform dialect are defined in separatePython source files that can be imported on-demand, i.e., that are not importedwith the "main" transform dialect. This requires a minor addition to theODS-based bindings generator. This approach is consistent with the currentmodel for downstream projects that are expected to bundle MLIR Python bindings:such projects can include their custom extensions into the bundle similarly tohow they include their dialects.Reviewed By: nicolasvasilacheDifferential Revision: https://reviews.llvm.org/D126208
[mlir][bufferization] Fix Python bindingsDifferential Revision: https://reviews.llvm.org/D126179
[mlir][python] Add Python bindings for ml_program dialect.Differential Revision: https://reviews.llvm.org/D125852
[mlir][bazel] filegroups for Python CF, PDL, Tensor dialectsThese dialects have Python bindings and are tested, but were notpreviously exposed through Bazel filegroups.Differential Revision: htt
[mlir][bazel] filegroups for Python CF, PDL, Tensor dialectsThese dialects have Python bindings and are tested, but were notpreviously exposed through Bazel filegroups.Differential Revision: https://reviews.llvm.org/D122138
[mlir][bazel] make .pyi files available to BazelThese files are necessary for various type checking and autocompletiontooling to work.Differential Revision: https://reviews.llvm.org/D121810
[bazel] Build fixes for 23aa5a744666
[bazel] Fix the python bindings for 7ceffae18c43Also run buildifier.
[mlir] Introduce Python bindings for the quantization dialectSo far, only the custom dialect types are exposed.The build and packaging is same as for Linalg and SparseTensor, and inneed of refac
[mlir] Introduce Python bindings for the quantization dialectSo far, only the custom dialect types are exposed.The build and packaging is same as for Linalg and SparseTensor, and inneed of refactoring that is beyond the scope of this patch.Reviewed By: stellaraccidentDifferential Revision: https://reviews.llvm.org/D116605
Add a Bazel build file for mlir/python.This BUILD file:* generates machine-generated Python files using tblgen, and* exports both generated and handwritten Python files via filegroup() rules.Th
Add a Bazel build file for mlir/python.This BUILD file:* generates machine-generated Python files using tblgen, and* exports both generated and handwritten Python files via filegroup() rules.This allows downstream users to use Bazel to build Python wheels that incorporate the MLIR Python bindings.Reviewed By: GMNGeoffreyDifferential Revision: https://reviews.llvm.org/D112844