67d0d7ac0a
The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure. Reviewed By: mehdi_amini, rriddle Differential Review: https://reviews.llvm.org/D132838
321 lines
13 KiB
C++
321 lines
13 KiB
C++
//===- AbstractResult.cpp - Conversion of Abstract Function Result --------===//
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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 "flang/Optimizer/Builder/Todo.h"
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#include "flang/Optimizer/Dialect/FIRDialect.h"
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#include "flang/Optimizer/Dialect/FIROps.h"
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#include "flang/Optimizer/Dialect/FIRType.h"
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#include "flang/Optimizer/Transforms/Passes.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/IR/Diagnostics.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "mlir/Transforms/Passes.h"
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#include "llvm/ADT/TypeSwitch.h"
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namespace fir {
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#define GEN_PASS_DEF_ABSTRACTRESULTONFUNCOPT
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#define GEN_PASS_DEF_ABSTRACTRESULTONGLOBALOPT
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#include "flang/Optimizer/Transforms/Passes.h.inc"
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} // namespace fir
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#define DEBUG_TYPE "flang-abstract-result-opt"
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namespace fir {
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namespace {
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static mlir::Type getResultArgumentType(mlir::Type resultType,
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bool shouldBoxResult) {
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return llvm::TypeSwitch<mlir::Type, mlir::Type>(resultType)
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.Case<fir::SequenceType, fir::RecordType>(
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[&](mlir::Type type) -> mlir::Type {
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if (shouldBoxResult)
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return fir::BoxType::get(type);
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return fir::ReferenceType::get(type);
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})
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.Case<fir::BoxType>([](mlir::Type type) -> mlir::Type {
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return fir::ReferenceType::get(type);
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})
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.Default([](mlir::Type) -> mlir::Type {
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llvm_unreachable("bad abstract result type");
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});
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}
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static mlir::FunctionType getNewFunctionType(mlir::FunctionType funcTy,
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bool shouldBoxResult) {
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auto resultType = funcTy.getResult(0);
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auto argTy = getResultArgumentType(resultType, shouldBoxResult);
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llvm::SmallVector<mlir::Type> newInputTypes = {argTy};
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newInputTypes.append(funcTy.getInputs().begin(), funcTy.getInputs().end());
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return mlir::FunctionType::get(funcTy.getContext(), newInputTypes,
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/*resultTypes=*/{});
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}
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static bool mustEmboxResult(mlir::Type resultType, bool shouldBoxResult) {
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return resultType.isa<fir::SequenceType, fir::RecordType>() &&
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shouldBoxResult;
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}
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class CallOpConversion : public mlir::OpRewritePattern<fir::CallOp> {
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public:
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using OpRewritePattern::OpRewritePattern;
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CallOpConversion(mlir::MLIRContext *context, bool shouldBoxResult)
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: OpRewritePattern(context), shouldBoxResult{shouldBoxResult} {}
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mlir::LogicalResult
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matchAndRewrite(fir::CallOp callOp,
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mlir::PatternRewriter &rewriter) const override {
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auto loc = callOp.getLoc();
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auto result = callOp->getResult(0);
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if (!result.hasOneUse()) {
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mlir::emitError(loc,
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"calls with abstract result must have exactly one user");
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return mlir::failure();
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}
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auto saveResult =
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mlir::dyn_cast<fir::SaveResultOp>(result.use_begin().getUser());
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if (!saveResult) {
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mlir::emitError(
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loc, "calls with abstract result must be used in fir.save_result");
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return mlir::failure();
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}
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auto argType = getResultArgumentType(result.getType(), shouldBoxResult);
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auto buffer = saveResult.getMemref();
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mlir::Value arg = buffer;
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if (mustEmboxResult(result.getType(), shouldBoxResult))
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arg = rewriter.create<fir::EmboxOp>(
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loc, argType, buffer, saveResult.getShape(), /*slice*/ mlir::Value{},
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saveResult.getTypeparams());
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llvm::SmallVector<mlir::Type> newResultTypes;
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if (callOp.getCallee()) {
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llvm::SmallVector<mlir::Value> newOperands = {arg};
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newOperands.append(callOp.getOperands().begin(),
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callOp.getOperands().end());
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rewriter.create<fir::CallOp>(loc, *callOp.getCallee(), newResultTypes,
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newOperands);
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} else {
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// Indirect calls.
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llvm::SmallVector<mlir::Type> newInputTypes = {argType};
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for (auto operand : callOp.getOperands().drop_front())
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newInputTypes.push_back(operand.getType());
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auto funTy = mlir::FunctionType::get(callOp.getContext(), newInputTypes,
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newResultTypes);
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llvm::SmallVector<mlir::Value> newOperands;
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newOperands.push_back(
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rewriter.create<fir::ConvertOp>(loc, funTy, callOp.getOperand(0)));
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newOperands.push_back(arg);
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newOperands.append(callOp.getOperands().begin() + 1,
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callOp.getOperands().end());
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rewriter.create<fir::CallOp>(loc, mlir::SymbolRefAttr{}, newResultTypes,
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newOperands);
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}
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callOp->dropAllReferences();
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rewriter.eraseOp(callOp);
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return mlir::success();
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}
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private:
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bool shouldBoxResult;
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};
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class SaveResultOpConversion
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: public mlir::OpRewritePattern<fir::SaveResultOp> {
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public:
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using OpRewritePattern::OpRewritePattern;
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SaveResultOpConversion(mlir::MLIRContext *context)
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: OpRewritePattern(context) {}
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mlir::LogicalResult
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matchAndRewrite(fir::SaveResultOp op,
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mlir::PatternRewriter &rewriter) const override {
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rewriter.eraseOp(op);
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return mlir::success();
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}
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};
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class ReturnOpConversion : public mlir::OpRewritePattern<mlir::func::ReturnOp> {
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public:
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using OpRewritePattern::OpRewritePattern;
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ReturnOpConversion(mlir::MLIRContext *context, mlir::Value newArg)
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: OpRewritePattern(context), newArg{newArg} {}
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mlir::LogicalResult
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matchAndRewrite(mlir::func::ReturnOp ret,
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mlir::PatternRewriter &rewriter) const override {
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rewriter.setInsertionPoint(ret);
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auto returnedValue = ret.getOperand(0);
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bool replacedStorage = false;
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if (auto *op = returnedValue.getDefiningOp())
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if (auto load = mlir::dyn_cast<fir::LoadOp>(op)) {
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auto resultStorage = load.getMemref();
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load.getMemref().replaceAllUsesWith(newArg);
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replacedStorage = true;
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if (auto *alloc = resultStorage.getDefiningOp())
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if (alloc->use_empty())
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rewriter.eraseOp(alloc);
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}
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// The result storage may have been optimized out by a memory to
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// register pass, this is possible for fir.box results, or fir.record
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// with no length parameters. Simply store the result in the result storage.
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// at the return point.
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if (!replacedStorage)
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rewriter.create<fir::StoreOp>(ret.getLoc(), returnedValue, newArg);
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rewriter.replaceOpWithNewOp<mlir::func::ReturnOp>(ret);
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return mlir::success();
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}
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private:
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mlir::Value newArg;
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};
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class AddrOfOpConversion : public mlir::OpRewritePattern<fir::AddrOfOp> {
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public:
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using OpRewritePattern::OpRewritePattern;
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AddrOfOpConversion(mlir::MLIRContext *context, bool shouldBoxResult)
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: OpRewritePattern(context), shouldBoxResult{shouldBoxResult} {}
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mlir::LogicalResult
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matchAndRewrite(fir::AddrOfOp addrOf,
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mlir::PatternRewriter &rewriter) const override {
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auto oldFuncTy = addrOf.getType().cast<mlir::FunctionType>();
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auto newFuncTy = getNewFunctionType(oldFuncTy, shouldBoxResult);
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auto newAddrOf = rewriter.create<fir::AddrOfOp>(addrOf.getLoc(), newFuncTy,
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addrOf.getSymbol());
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// Rather than converting all op a function pointer might transit through
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// (e.g calls, stores, loads, converts...), cast new type to the abstract
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// type. A conversion will be added when calling indirect calls of abstract
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// types.
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rewriter.replaceOpWithNewOp<fir::ConvertOp>(addrOf, oldFuncTy, newAddrOf);
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return mlir::success();
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}
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private:
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bool shouldBoxResult;
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};
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/// @brief Base CRTP class for AbstractResult pass family.
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/// Contains common logic for abstract result conversion in a reusable fashion.
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/// @tparam Pass target class that implements operation-specific logic.
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/// @tparam PassBase base class template for the pass generated by TableGen.
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/// The `Pass` class must define runOnSpecificOperation(OpTy, bool,
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/// mlir::RewritePatternSet&, mlir::ConversionTarget&) member function.
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/// This function should implement operation-specific functionality.
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template <typename Pass, template <typename> class PassBase>
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class AbstractResultOptTemplate : public PassBase<Pass> {
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public:
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void runOnOperation() override {
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auto *context = &this->getContext();
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auto op = this->getOperation();
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mlir::RewritePatternSet patterns(context);
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mlir::ConversionTarget target = *context;
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const bool shouldBoxResult = this->passResultAsBox.getValue();
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auto &self = static_cast<Pass &>(*this);
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self.runOnSpecificOperation(op, shouldBoxResult, patterns, target);
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// Convert the calls and, if needed, the ReturnOp in the function body.
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target.addLegalDialect<fir::FIROpsDialect, mlir::arith::ArithmeticDialect,
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mlir::func::FuncDialect>();
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target.addIllegalOp<fir::SaveResultOp>();
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target.addDynamicallyLegalOp<fir::CallOp>([](fir::CallOp call) {
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return !hasAbstractResult(call.getFunctionType());
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});
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target.addDynamicallyLegalOp<fir::AddrOfOp>([](fir::AddrOfOp addrOf) {
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if (auto funTy = addrOf.getType().dyn_cast<mlir::FunctionType>())
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return !hasAbstractResult(funTy);
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return true;
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});
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target.addDynamicallyLegalOp<fir::DispatchOp>([](fir::DispatchOp dispatch) {
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if (dispatch->getNumResults() != 1)
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return true;
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auto resultType = dispatch->getResult(0).getType();
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if (resultType.isa<fir::SequenceType, fir::BoxType, fir::RecordType>()) {
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TODO(dispatch.getLoc(), "dispatchOp with abstract results");
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return false;
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}
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return true;
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});
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patterns.insert<CallOpConversion>(context, shouldBoxResult);
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patterns.insert<SaveResultOpConversion>(context);
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patterns.insert<AddrOfOpConversion>(context, shouldBoxResult);
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if (mlir::failed(
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mlir::applyPartialConversion(op, target, std::move(patterns)))) {
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mlir::emitError(op.getLoc(), "error in converting abstract results\n");
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this->signalPassFailure();
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}
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}
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};
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class AbstractResultOnFuncOpt
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: public AbstractResultOptTemplate<AbstractResultOnFuncOpt,
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fir::impl::AbstractResultOnFuncOptBase> {
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public:
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void runOnSpecificOperation(mlir::func::FuncOp func, bool shouldBoxResult,
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mlir::RewritePatternSet &patterns,
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mlir::ConversionTarget &target) {
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auto loc = func.getLoc();
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auto *context = &getContext();
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// Convert function type itself if it has an abstract result.
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auto funcTy = func.getFunctionType().cast<mlir::FunctionType>();
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if (hasAbstractResult(funcTy)) {
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func.setType(getNewFunctionType(funcTy, shouldBoxResult));
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if (!func.empty()) {
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// Insert new argument.
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mlir::OpBuilder rewriter(context);
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auto resultType = funcTy.getResult(0);
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auto argTy = getResultArgumentType(resultType, shouldBoxResult);
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mlir::Value newArg = func.front().insertArgument(0u, argTy, loc);
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if (mustEmboxResult(resultType, shouldBoxResult)) {
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auto bufferType = fir::ReferenceType::get(resultType);
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rewriter.setInsertionPointToStart(&func.front());
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newArg = rewriter.create<fir::BoxAddrOp>(loc, bufferType, newArg);
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}
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patterns.insert<ReturnOpConversion>(context, newArg);
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target.addDynamicallyLegalOp<mlir::func::ReturnOp>(
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[](mlir::func::ReturnOp ret) { return ret.operands().empty(); });
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}
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}
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}
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};
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inline static bool containsFunctionTypeWithAbstractResult(mlir::Type type) {
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return mlir::TypeSwitch<mlir::Type, bool>(type)
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.Case([](fir::BoxProcType boxProc) {
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return fir::hasAbstractResult(
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boxProc.getEleTy().cast<mlir::FunctionType>());
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})
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.Case([](fir::PointerType pointer) {
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return fir::hasAbstractResult(
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pointer.getEleTy().cast<mlir::FunctionType>());
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})
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.Default([](auto &&) { return false; });
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}
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class AbstractResultOnGlobalOpt
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: public AbstractResultOptTemplate<
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AbstractResultOnGlobalOpt, fir::impl::AbstractResultOnGlobalOptBase> {
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public:
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void runOnSpecificOperation(fir::GlobalOp global, bool,
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mlir::RewritePatternSet &,
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mlir::ConversionTarget &) {
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if (containsFunctionTypeWithAbstractResult(global.getType())) {
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TODO(global->getLoc(), "support for procedure pointers");
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}
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}
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};
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} // end anonymous namespace
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} // namespace fir
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std::unique_ptr<mlir::Pass> fir::createAbstractResultOnFuncOptPass() {
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return std::make_unique<AbstractResultOnFuncOpt>();
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}
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std::unique_ptr<mlir::Pass> fir::createAbstractResultOnGlobalOptPass() {
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return std::make_unique<AbstractResultOnGlobalOpt>();
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}
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