b56d1ec6cb
Relands #118583, with a fix for Python 3.8 compatibility. It was not possible to set the buffer protocol accessers via slots in Python 3.8. Why? https://nanobind.readthedocs.io/en/latest/why.html says it better than I can, but my primary motivation for this change is to improve MLIR IR construction time from JAX. For a complicated Google-internal LLM model in JAX, this change improves the MLIR lowering time by around 5s (out of around 30s), which is a significant speedup for simply switching binding frameworks. To a large extent, this is a mechanical change, for instance changing `pybind11::` to `nanobind::`. Notes: * this PR needs Nanobind 2.4.0, because it needs a bug fix (https://github.com/wjakob/nanobind/pull/806) that landed in that release. * this PR does not port the in-tree dialect extension modules. They can be ported in a future PR. * I removed the py::sibling() annotations from def_static and def_class in `PybindAdapters.h`. These ask pybind11 to try to form an overload with an existing method, but it's not possible to form mixed pybind11/nanobind overloads this ways and the parent class is now defined in nanobind. Better solutions may be possible here. * nanobind does not contain an exact equivalent of pybind11's buffer protocol support. It was not hard to add a nanobind implementation of a similar API. * nanobind is pickier about casting to std::vector<bool>, expecting that the input is a sequence of bool types, not truthy values. In a couple of places I added code to support truthy values during casting. * nanobind distinguishes bytes (`nb::bytes`) from strings (e.g., `std::string`). This required nb::bytes overloads in a few places.
114 lines
3.8 KiB
C++
114 lines
3.8 KiB
C++
//===- Rewrite.cpp - Rewrite ----------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "Rewrite.h"
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#include <nanobind/nanobind.h>
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#include "IRModule.h"
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#include "mlir-c/Bindings/Python/Interop.h"
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#include "mlir-c/Rewrite.h"
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#include "mlir/Config/mlir-config.h"
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namespace nb = nanobind;
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using namespace mlir;
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using namespace nb::literals;
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using namespace mlir::python;
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namespace {
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#if MLIR_ENABLE_PDL_IN_PATTERNMATCH
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/// Owning Wrapper around a PDLPatternModule.
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class PyPDLPatternModule {
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public:
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PyPDLPatternModule(MlirPDLPatternModule module) : module(module) {}
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PyPDLPatternModule(PyPDLPatternModule &&other) noexcept
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: module(other.module) {
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other.module.ptr = nullptr;
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}
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~PyPDLPatternModule() {
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if (module.ptr != nullptr)
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mlirPDLPatternModuleDestroy(module);
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}
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MlirPDLPatternModule get() { return module; }
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private:
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MlirPDLPatternModule module;
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};
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#endif // MLIR_ENABLE_PDL_IN_PATTERNMATCH
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/// Owning Wrapper around a FrozenRewritePatternSet.
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class PyFrozenRewritePatternSet {
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public:
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PyFrozenRewritePatternSet(MlirFrozenRewritePatternSet set) : set(set) {}
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PyFrozenRewritePatternSet(PyFrozenRewritePatternSet &&other) noexcept
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: set(other.set) {
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other.set.ptr = nullptr;
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}
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~PyFrozenRewritePatternSet() {
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if (set.ptr != nullptr)
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mlirFrozenRewritePatternSetDestroy(set);
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}
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MlirFrozenRewritePatternSet get() { return set; }
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nb::object getCapsule() {
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return nb::steal<nb::object>(
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mlirPythonFrozenRewritePatternSetToCapsule(get()));
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}
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static nb::object createFromCapsule(nb::object capsule) {
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MlirFrozenRewritePatternSet rawPm =
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mlirPythonCapsuleToFrozenRewritePatternSet(capsule.ptr());
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if (rawPm.ptr == nullptr)
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throw nb::python_error();
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return nb::cast(PyFrozenRewritePatternSet(rawPm), nb::rv_policy::move);
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}
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private:
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MlirFrozenRewritePatternSet set;
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};
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} // namespace
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/// Create the `mlir.rewrite` here.
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void mlir::python::populateRewriteSubmodule(nb::module_ &m) {
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//----------------------------------------------------------------------------
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// Mapping of the top-level PassManager
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//----------------------------------------------------------------------------
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#if MLIR_ENABLE_PDL_IN_PATTERNMATCH
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nb::class_<PyPDLPatternModule>(m, "PDLModule")
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.def(
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"__init__",
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[](PyPDLPatternModule &self, MlirModule module) {
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new (&self)
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PyPDLPatternModule(mlirPDLPatternModuleFromModule(module));
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},
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"module"_a, "Create a PDL module from the given module.")
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.def("freeze", [](PyPDLPatternModule &self) {
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return new PyFrozenRewritePatternSet(mlirFreezeRewritePattern(
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mlirRewritePatternSetFromPDLPatternModule(self.get())));
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});
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#endif // MLIR_ENABLE_PDL_IN_PATTERNMATCH
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nb::class_<PyFrozenRewritePatternSet>(m, "FrozenRewritePatternSet")
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.def_prop_ro(MLIR_PYTHON_CAPI_PTR_ATTR,
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&PyFrozenRewritePatternSet::getCapsule)
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.def(MLIR_PYTHON_CAPI_FACTORY_ATTR,
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&PyFrozenRewritePatternSet::createFromCapsule);
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m.def(
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"apply_patterns_and_fold_greedily",
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[](MlirModule module, MlirFrozenRewritePatternSet set) {
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auto status = mlirApplyPatternsAndFoldGreedily(module, set, {});
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if (mlirLogicalResultIsFailure(status))
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// FIXME: Not sure this is the right error to throw here.
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throw nb::value_error("pattern application failed to converge");
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},
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"module"_a, "set"_a,
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"Applys the given patterns to the given module greedily while folding "
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"results.");
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}
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