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//===- Canonicalizer.cpp - Canonicalize MLIR operations -------------------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
//
// This transformation pass converts operations into their canonical forms by
// folding constants, applying operation identity transformations etc.
//
//===----------------------------------------------------------------------===//
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/Pass.h"
#include "mlir/Transforms/Passes.h"
using namespace mlir;
//===----------------------------------------------------------------------===//
// The actual Canonicalizer Pass.
//===----------------------------------------------------------------------===//
namespace {
/// Canonicalize operations in functions.
struct Canonicalizer : public FunctionPass {
PassResult runOnFunction(Function *fn) override;
static char passID;
};
} // end anonymous namespace
char Canonicalizer::passID = 0;
PassResult Canonicalizer::runOnFunction(Function *fn) {
auto *context = fn->getContext();
OwningPatternList patterns;
// TODO: Instead of adding all known patterns from the whole system lazily add
// and cache the canonicalization patterns for ops we see in practice when
// building the worklist. For now, we just grab everything.
for (auto *op : fn->getContext()->getRegisteredOperations())
op->getCanonicalizationPatterns(patterns, context);
applyPatternsGreedily(fn, std::move(patterns));
return success();
}
/// Create a Canonicalizer pass.
FunctionPass *mlir::createCanonicalizerPass() { return new Canonicalizer(); }
static PassRegistration<Canonicalizer> pass("canonicalize",
"Canonicalize operations");