mirror of
https://github.com/intel/llvm.git
synced 2026-01-15 12:25:46 +08:00
7be89bb07b
This includes the rename from `mlirOpRewritePattenCreate` to `mlirOpRewritePatternCreate` in CAPI, and other typo fixes in docs and code comments.
442 lines
17 KiB
C++
442 lines
17 KiB
C++
//===- Rewrite.cpp - Rewrite ----------------------------------------------===//
|
|
//
|
|
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
|
|
// See https://llvm.org/LICENSE.txt for license information.
|
|
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include "Rewrite.h"
|
|
|
|
#include "IRModule.h"
|
|
#include "mlir-c/IR.h"
|
|
#include "mlir-c/Rewrite.h"
|
|
#include "mlir-c/Support.h"
|
|
// clang-format off
|
|
#include "mlir/Bindings/Python/Nanobind.h"
|
|
#include "mlir-c/Bindings/Python/Interop.h" // This is expected after nanobind.
|
|
// clang-format on
|
|
#include "mlir/Config/mlir-config.h"
|
|
#include "nanobind/nanobind.h"
|
|
|
|
namespace nb = nanobind;
|
|
using namespace mlir;
|
|
using namespace nb::literals;
|
|
using namespace mlir::python;
|
|
|
|
namespace {
|
|
|
|
class PyPatternRewriter {
|
|
public:
|
|
PyPatternRewriter(MlirPatternRewriter rewriter)
|
|
: base(mlirPatternRewriterAsBase(rewriter)),
|
|
ctx(PyMlirContext::forContext(mlirRewriterBaseGetContext(base))) {}
|
|
|
|
PyInsertionPoint getInsertionPoint() const {
|
|
MlirBlock block = mlirRewriterBaseGetInsertionBlock(base);
|
|
MlirOperation op = mlirRewriterBaseGetOperationAfterInsertion(base);
|
|
|
|
if (mlirOperationIsNull(op)) {
|
|
MlirOperation owner = mlirBlockGetParentOperation(block);
|
|
auto parent = PyOperation::forOperation(ctx, owner);
|
|
return PyInsertionPoint(PyBlock(parent, block));
|
|
}
|
|
|
|
return PyInsertionPoint(PyOperation::forOperation(ctx, op));
|
|
}
|
|
|
|
void replaceOp(MlirOperation op, MlirOperation newOp) {
|
|
mlirRewriterBaseReplaceOpWithOperation(base, op, newOp);
|
|
}
|
|
|
|
void replaceOp(MlirOperation op, const std::vector<MlirValue> &values) {
|
|
mlirRewriterBaseReplaceOpWithValues(base, op, values.size(), values.data());
|
|
}
|
|
|
|
void eraseOp(MlirOperation op) { mlirRewriterBaseEraseOp(base, op); }
|
|
|
|
private:
|
|
MlirRewriterBase base;
|
|
PyMlirContextRef ctx;
|
|
};
|
|
|
|
#if MLIR_ENABLE_PDL_IN_PATTERNMATCH
|
|
static nb::object objectFromPDLValue(MlirPDLValue value) {
|
|
if (MlirValue v = mlirPDLValueAsValue(value); !mlirValueIsNull(v))
|
|
return nb::cast(v);
|
|
if (MlirOperation v = mlirPDLValueAsOperation(value); !mlirOperationIsNull(v))
|
|
return nb::cast(v);
|
|
if (MlirAttribute v = mlirPDLValueAsAttribute(value); !mlirAttributeIsNull(v))
|
|
return nb::cast(v);
|
|
if (MlirType v = mlirPDLValueAsType(value); !mlirTypeIsNull(v))
|
|
return nb::cast(v);
|
|
|
|
throw std::runtime_error("unsupported PDL value type");
|
|
}
|
|
|
|
static std::vector<nb::object> objectsFromPDLValues(size_t nValues,
|
|
MlirPDLValue *values) {
|
|
std::vector<nb::object> args;
|
|
args.reserve(nValues);
|
|
for (size_t i = 0; i < nValues; ++i)
|
|
args.push_back(objectFromPDLValue(values[i]));
|
|
return args;
|
|
}
|
|
|
|
// Convert the Python object to a boolean.
|
|
// If it evaluates to False, treat it as success;
|
|
// otherwise, treat it as failure.
|
|
// Note that None is considered success.
|
|
static MlirLogicalResult logicalResultFromObject(const nb::object &obj) {
|
|
if (obj.is_none())
|
|
return mlirLogicalResultSuccess();
|
|
|
|
return nb::cast<bool>(obj) ? mlirLogicalResultFailure()
|
|
: mlirLogicalResultSuccess();
|
|
}
|
|
|
|
/// Owning Wrapper around a PDLPatternModule.
|
|
class PyPDLPatternModule {
|
|
public:
|
|
PyPDLPatternModule(MlirPDLPatternModule module) : module(module) {}
|
|
PyPDLPatternModule(PyPDLPatternModule &&other) noexcept
|
|
: module(other.module) {
|
|
other.module.ptr = nullptr;
|
|
}
|
|
~PyPDLPatternModule() {
|
|
if (module.ptr != nullptr)
|
|
mlirPDLPatternModuleDestroy(module);
|
|
}
|
|
MlirPDLPatternModule get() { return module; }
|
|
|
|
void registerRewriteFunction(const std::string &name,
|
|
const nb::callable &fn) {
|
|
mlirPDLPatternModuleRegisterRewriteFunction(
|
|
get(), mlirStringRefCreate(name.data(), name.size()),
|
|
[](MlirPatternRewriter rewriter, MlirPDLResultList results,
|
|
size_t nValues, MlirPDLValue *values,
|
|
void *userData) -> MlirLogicalResult {
|
|
nb::handle f = nb::handle(static_cast<PyObject *>(userData));
|
|
return logicalResultFromObject(
|
|
f(PyPatternRewriter(rewriter), results,
|
|
objectsFromPDLValues(nValues, values)));
|
|
},
|
|
fn.ptr());
|
|
}
|
|
|
|
void registerConstraintFunction(const std::string &name,
|
|
const nb::callable &fn) {
|
|
mlirPDLPatternModuleRegisterConstraintFunction(
|
|
get(), mlirStringRefCreate(name.data(), name.size()),
|
|
[](MlirPatternRewriter rewriter, MlirPDLResultList results,
|
|
size_t nValues, MlirPDLValue *values,
|
|
void *userData) -> MlirLogicalResult {
|
|
nb::handle f = nb::handle(static_cast<PyObject *>(userData));
|
|
return logicalResultFromObject(
|
|
f(PyPatternRewriter(rewriter), results,
|
|
objectsFromPDLValues(nValues, values)));
|
|
},
|
|
fn.ptr());
|
|
}
|
|
|
|
private:
|
|
MlirPDLPatternModule module;
|
|
};
|
|
#endif // MLIR_ENABLE_PDL_IN_PATTERNMATCH
|
|
|
|
/// Owning Wrapper around a FrozenRewritePatternSet.
|
|
class PyFrozenRewritePatternSet {
|
|
public:
|
|
PyFrozenRewritePatternSet(MlirFrozenRewritePatternSet set) : set(set) {}
|
|
PyFrozenRewritePatternSet(PyFrozenRewritePatternSet &&other) noexcept
|
|
: set(other.set) {
|
|
other.set.ptr = nullptr;
|
|
}
|
|
~PyFrozenRewritePatternSet() {
|
|
if (set.ptr != nullptr)
|
|
mlirFrozenRewritePatternSetDestroy(set);
|
|
}
|
|
MlirFrozenRewritePatternSet get() { return set; }
|
|
|
|
nb::object getCapsule() {
|
|
return nb::steal<nb::object>(
|
|
mlirPythonFrozenRewritePatternSetToCapsule(get()));
|
|
}
|
|
|
|
static nb::object createFromCapsule(const nb::object &capsule) {
|
|
MlirFrozenRewritePatternSet rawPm =
|
|
mlirPythonCapsuleToFrozenRewritePatternSet(capsule.ptr());
|
|
if (rawPm.ptr == nullptr)
|
|
throw nb::python_error();
|
|
return nb::cast(PyFrozenRewritePatternSet(rawPm), nb::rv_policy::move);
|
|
}
|
|
|
|
private:
|
|
MlirFrozenRewritePatternSet set;
|
|
};
|
|
|
|
class PyRewritePatternSet {
|
|
public:
|
|
PyRewritePatternSet(MlirContext ctx)
|
|
: set(mlirRewritePatternSetCreate(ctx)), ctx(ctx) {}
|
|
~PyRewritePatternSet() {
|
|
if (set.ptr)
|
|
mlirRewritePatternSetDestroy(set);
|
|
}
|
|
|
|
void add(MlirStringRef rootName, unsigned benefit,
|
|
const nb::callable &matchAndRewrite) {
|
|
MlirRewritePatternCallbacks callbacks;
|
|
callbacks.construct = [](void *userData) {
|
|
nb::handle(static_cast<PyObject *>(userData)).inc_ref();
|
|
};
|
|
callbacks.destruct = [](void *userData) {
|
|
nb::handle(static_cast<PyObject *>(userData)).dec_ref();
|
|
};
|
|
callbacks.matchAndRewrite = [](MlirRewritePattern, MlirOperation op,
|
|
MlirPatternRewriter rewriter,
|
|
void *userData) -> MlirLogicalResult {
|
|
nb::handle f(static_cast<PyObject *>(userData));
|
|
|
|
PyMlirContextRef ctx =
|
|
PyMlirContext::forContext(mlirOperationGetContext(op));
|
|
nb::object opView = PyOperation::forOperation(ctx, op)->createOpView();
|
|
|
|
nb::object res = f(opView, PyPatternRewriter(rewriter));
|
|
return logicalResultFromObject(res);
|
|
};
|
|
MlirRewritePattern pattern = mlirOpRewritePatternCreate(
|
|
rootName, benefit, ctx, callbacks, matchAndRewrite.ptr(),
|
|
/* nGeneratedNames */ 0,
|
|
/* generatedNames */ nullptr);
|
|
mlirRewritePatternSetAdd(set, pattern);
|
|
}
|
|
|
|
PyFrozenRewritePatternSet freeze() {
|
|
MlirRewritePatternSet s = set;
|
|
set.ptr = nullptr;
|
|
return mlirFreezeRewritePattern(s);
|
|
}
|
|
|
|
private:
|
|
MlirRewritePatternSet set;
|
|
MlirContext ctx;
|
|
};
|
|
|
|
} // namespace
|
|
|
|
/// Create the `mlir.rewrite` here.
|
|
void mlir::python::populateRewriteSubmodule(nb::module_ &m) {
|
|
//----------------------------------------------------------------------------
|
|
// Mapping of the PatternRewriter
|
|
//----------------------------------------------------------------------------
|
|
nb::
|
|
class_<PyPatternRewriter>(m, "PatternRewriter")
|
|
.def_prop_ro("ip", &PyPatternRewriter::getInsertionPoint,
|
|
"The current insertion point of the PatternRewriter.")
|
|
.def(
|
|
"replace_op",
|
|
[](PyPatternRewriter &self, MlirOperation op,
|
|
MlirOperation newOp) { self.replaceOp(op, newOp); },
|
|
"Replace an operation with a new operation.", nb::arg("op"),
|
|
nb::arg("new_op"),
|
|
// clang-format off
|
|
nb::sig("def replace_op(self, op: " MAKE_MLIR_PYTHON_QUALNAME("ir.Operation") ", new_op: " MAKE_MLIR_PYTHON_QUALNAME("ir.Operation") ") -> None")
|
|
// clang-format on
|
|
)
|
|
.def(
|
|
"replace_op",
|
|
[](PyPatternRewriter &self, MlirOperation op,
|
|
const std::vector<MlirValue> &values) {
|
|
self.replaceOp(op, values);
|
|
},
|
|
"Replace an operation with a list of values.", nb::arg("op"),
|
|
nb::arg("values"),
|
|
// clang-format off
|
|
nb::sig("def replace_op(self, op: " MAKE_MLIR_PYTHON_QUALNAME("ir.Operation") ", values: list[" MAKE_MLIR_PYTHON_QUALNAME("ir.Value") "]) -> None")
|
|
// clang-format on
|
|
)
|
|
.def("erase_op", &PyPatternRewriter::eraseOp, "Erase an operation.",
|
|
nb::arg("op"),
|
|
// clang-format off
|
|
nb::sig("def erase_op(self, op: " MAKE_MLIR_PYTHON_QUALNAME("ir.Operation") ") -> None")
|
|
// clang-format on
|
|
);
|
|
|
|
//----------------------------------------------------------------------------
|
|
// Mapping of the RewritePatternSet
|
|
//----------------------------------------------------------------------------
|
|
nb::class_<PyRewritePatternSet>(m, "RewritePatternSet")
|
|
.def(
|
|
"__init__",
|
|
[](PyRewritePatternSet &self, DefaultingPyMlirContext context) {
|
|
new (&self) PyRewritePatternSet(context.get()->get());
|
|
},
|
|
"context"_a = nb::none())
|
|
.def(
|
|
"add",
|
|
[](PyRewritePatternSet &self, nb::handle root, const nb::callable &fn,
|
|
unsigned benefit) {
|
|
std::string opName =
|
|
nb::cast<std::string>(root.attr("OPERATION_NAME"));
|
|
self.add(mlirStringRefCreate(opName.data(), opName.size()), benefit,
|
|
fn);
|
|
},
|
|
"root"_a, "fn"_a, "benefit"_a = 1,
|
|
"Add a new rewrite pattern on the given root operation with the "
|
|
"callable as the matching and rewriting function and the given "
|
|
"benefit.")
|
|
.def("freeze", &PyRewritePatternSet::freeze,
|
|
"Freeze the pattern set into a frozen one.");
|
|
|
|
//----------------------------------------------------------------------------
|
|
// Mapping of the PDLResultList and PDLModule
|
|
//----------------------------------------------------------------------------
|
|
#if MLIR_ENABLE_PDL_IN_PATTERNMATCH
|
|
nb::class_<MlirPDLResultList>(m, "PDLResultList")
|
|
.def(
|
|
"append",
|
|
[](MlirPDLResultList results, const PyValue &value) {
|
|
mlirPDLResultListPushBackValue(results, value);
|
|
},
|
|
// clang-format off
|
|
nb::sig("def append(self, value: " MAKE_MLIR_PYTHON_QUALNAME("ir.Value") ")")
|
|
// clang-format on
|
|
)
|
|
.def(
|
|
"append",
|
|
[](MlirPDLResultList results, const PyOperation &op) {
|
|
mlirPDLResultListPushBackOperation(results, op);
|
|
},
|
|
// clang-format off
|
|
nb::sig("def append(self, op: " MAKE_MLIR_PYTHON_QUALNAME("ir.Operation") ")")
|
|
// clang-format on
|
|
)
|
|
.def(
|
|
"append",
|
|
[](MlirPDLResultList results, const PyType &type) {
|
|
mlirPDLResultListPushBackType(results, type);
|
|
},
|
|
// clang-format off
|
|
nb::sig("def append(self, type: " MAKE_MLIR_PYTHON_QUALNAME("ir.Type") ")")
|
|
// clang-format on
|
|
)
|
|
.def(
|
|
"append",
|
|
[](MlirPDLResultList results, const PyAttribute &attr) {
|
|
mlirPDLResultListPushBackAttribute(results, attr);
|
|
},
|
|
// clang-format off
|
|
nb::sig("def append(self, attr: " MAKE_MLIR_PYTHON_QUALNAME("ir.Attribute") ")")
|
|
// clang-format on
|
|
);
|
|
nb::class_<PyPDLPatternModule>(m, "PDLModule")
|
|
.def(
|
|
"__init__",
|
|
[](PyPDLPatternModule &self, MlirModule module) {
|
|
new (&self)
|
|
PyPDLPatternModule(mlirPDLPatternModuleFromModule(module));
|
|
},
|
|
// clang-format off
|
|
nb::sig("def __init__(self, module: " MAKE_MLIR_PYTHON_QUALNAME("ir.Module") ") -> None"),
|
|
// clang-format on
|
|
"module"_a, "Create a PDL module from the given module.")
|
|
.def(
|
|
"__init__",
|
|
[](PyPDLPatternModule &self, PyModule &module) {
|
|
new (&self) PyPDLPatternModule(
|
|
mlirPDLPatternModuleFromModule(module.get()));
|
|
},
|
|
// clang-format off
|
|
nb::sig("def __init__(self, module: " MAKE_MLIR_PYTHON_QUALNAME("ir.Module") ") -> None"),
|
|
// clang-format on
|
|
"module"_a, "Create a PDL module from the given module.")
|
|
.def(
|
|
"freeze",
|
|
[](PyPDLPatternModule &self) {
|
|
return PyFrozenRewritePatternSet(mlirFreezeRewritePattern(
|
|
mlirRewritePatternSetFromPDLPatternModule(self.get())));
|
|
},
|
|
nb::keep_alive<0, 1>())
|
|
.def(
|
|
"register_rewrite_function",
|
|
[](PyPDLPatternModule &self, const std::string &name,
|
|
const nb::callable &fn) {
|
|
self.registerRewriteFunction(name, fn);
|
|
},
|
|
nb::keep_alive<1, 3>())
|
|
.def(
|
|
"register_constraint_function",
|
|
[](PyPDLPatternModule &self, const std::string &name,
|
|
const nb::callable &fn) {
|
|
self.registerConstraintFunction(name, fn);
|
|
},
|
|
nb::keep_alive<1, 3>());
|
|
#endif // MLIR_ENABLE_PDL_IN_PATTERNMATCH
|
|
nb::class_<PyFrozenRewritePatternSet>(m, "FrozenRewritePatternSet")
|
|
.def_prop_ro(MLIR_PYTHON_CAPI_PTR_ATTR,
|
|
&PyFrozenRewritePatternSet::getCapsule)
|
|
.def(MLIR_PYTHON_CAPI_FACTORY_ATTR,
|
|
&PyFrozenRewritePatternSet::createFromCapsule);
|
|
m.def(
|
|
"apply_patterns_and_fold_greedily",
|
|
[](PyModule &module, PyFrozenRewritePatternSet &set) {
|
|
auto status =
|
|
mlirApplyPatternsAndFoldGreedily(module.get(), set.get(), {});
|
|
if (mlirLogicalResultIsFailure(status))
|
|
throw std::runtime_error("pattern application failed to converge");
|
|
},
|
|
"module"_a, "set"_a,
|
|
// clang-format off
|
|
nb::sig("def apply_patterns_and_fold_greedily(module: " MAKE_MLIR_PYTHON_QUALNAME("ir.Module") ", set: FrozenRewritePatternSet) -> None"),
|
|
// clang-format on
|
|
"Applys the given patterns to the given module greedily while folding "
|
|
"results.")
|
|
.def(
|
|
"apply_patterns_and_fold_greedily",
|
|
[](PyModule &module, MlirFrozenRewritePatternSet set) {
|
|
auto status =
|
|
mlirApplyPatternsAndFoldGreedily(module.get(), set, {});
|
|
if (mlirLogicalResultIsFailure(status))
|
|
throw std::runtime_error(
|
|
"pattern application failed to converge");
|
|
},
|
|
"module"_a, "set"_a,
|
|
// clang-format off
|
|
nb::sig("def apply_patterns_and_fold_greedily(module: " MAKE_MLIR_PYTHON_QUALNAME("ir.Module") ", set: FrozenRewritePatternSet) -> None"),
|
|
// clang-format on
|
|
"Applys the given patterns to the given module greedily while "
|
|
"folding "
|
|
"results.")
|
|
.def(
|
|
"apply_patterns_and_fold_greedily",
|
|
[](PyOperationBase &op, PyFrozenRewritePatternSet &set) {
|
|
auto status = mlirApplyPatternsAndFoldGreedilyWithOp(
|
|
op.getOperation(), set.get(), {});
|
|
if (mlirLogicalResultIsFailure(status))
|
|
throw std::runtime_error(
|
|
"pattern application failed to converge");
|
|
},
|
|
"op"_a, "set"_a,
|
|
// clang-format off
|
|
nb::sig("def apply_patterns_and_fold_greedily(op: " MAKE_MLIR_PYTHON_QUALNAME("ir._OperationBase") ", set: FrozenRewritePatternSet) -> None"),
|
|
// clang-format on
|
|
"Applys the given patterns to the given op greedily while folding "
|
|
"results.")
|
|
.def(
|
|
"apply_patterns_and_fold_greedily",
|
|
[](PyOperationBase &op, MlirFrozenRewritePatternSet set) {
|
|
auto status = mlirApplyPatternsAndFoldGreedilyWithOp(
|
|
op.getOperation(), set, {});
|
|
if (mlirLogicalResultIsFailure(status))
|
|
throw std::runtime_error(
|
|
"pattern application failed to converge");
|
|
},
|
|
"op"_a, "set"_a,
|
|
// clang-format off
|
|
nb::sig("def apply_patterns_and_fold_greedily(op: " MAKE_MLIR_PYTHON_QUALNAME("ir._OperationBase") ", set: FrozenRewritePatternSet) -> None"),
|
|
// clang-format on
|
|
"Applys the given patterns to the given op greedily while folding "
|
|
"results.");
|
|
}
|