vasilito
cb424d7448
verify-patch-sanity.py validates every active recipe .patch has internally- consistent hunk line counts — catching the 'malformed patch at line N' failure at commit/CI/preflight time instead of hours into a cook. This cycle hit that class three times (qtwaylandscanner, sddm, xwayland), each only discovered when cookbook tried to apply the patch. Running it across the repo found 29 latent malformed patches (validated against GNU patch: e.g. relibc/P3-sysv-ipc reproduces 'malformed patch at line 22'). They were harmless only because they sit in vendored recipes (baked, not re- applied) — but would fail on any version-bump re-derivation. --fix recounts the hunk headers (body untouched) and repaired all 29. Wired into build-preflight.sh (Phase 1.0D) and redbear-ci.yml, with a unit test (test-patch-sanity.sh). Skips archived/legacy trees and unvalidatable formats (empty placeholders, bare-@@ git hunks).
507 lines
20 KiB
C++
507 lines
20 KiB
C++
//===-- HlfirIntrinsics.cpp -----------------------------------------------===//
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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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//
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// Coding style: https://mlir.llvm.org/getting_started/DeveloperGuide/
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//
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//===----------------------------------------------------------------------===//
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#include "flang/Lower/HlfirIntrinsics.h"
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#include "flang/Optimizer/Builder/BoxValue.h"
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#include "flang/Optimizer/Builder/FIRBuilder.h"
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#include "flang/Optimizer/Builder/HLFIRTools.h"
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#include "flang/Optimizer/Builder/IntrinsicCall.h"
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#include "flang/Optimizer/Builder/MutableBox.h"
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#include "flang/Optimizer/Builder/Todo.h"
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#include "flang/Optimizer/Dialect/FIRType.h"
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#include "flang/Optimizer/HLFIR/HLFIRDialect.h"
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#include "flang/Optimizer/HLFIR/HLFIROps.h"
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#include "mlir/IR/Value.h"
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#include "llvm/ADT/SmallVector.h"
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#include <mlir/IR/ValueRange.h>
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namespace {
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class HlfirTransformationalIntrinsic {
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public:
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explicit HlfirTransformationalIntrinsic(fir::FirOpBuilder &builder,
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mlir::Location loc)
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: builder(builder), loc(loc) {}
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virtual ~HlfirTransformationalIntrinsic() = default;
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hlfir::EntityWithAttributes
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lower(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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mlir::Value res = lowerImpl(loweredActuals, argLowering, stmtResultType);
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for (const hlfir::CleanupFunction &fn : cleanupFns)
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fn();
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return {hlfir::EntityWithAttributes{res}};
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}
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protected:
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fir::FirOpBuilder &builder;
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mlir::Location loc;
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llvm::SmallVector<hlfir::CleanupFunction, 3> cleanupFns;
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virtual mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) = 0;
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llvm::SmallVector<mlir::Value> getOperandVector(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering);
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mlir::Type computeResultType(mlir::Value argArray, mlir::Type stmtResultType);
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template <typename OP, typename... BUILD_ARGS>
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inline OP createOp(BUILD_ARGS... args) {
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return builder.create<OP>(loc, args...);
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}
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mlir::Value loadBoxAddress(
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const std::optional<Fortran::lower::PreparedActualArgument> &arg);
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void addCleanup(std::optional<hlfir::CleanupFunction> cleanup) {
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if (cleanup)
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cleanupFns.emplace_back(std::move(*cleanup));
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}
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};
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template <typename OP, bool HAS_MASK>
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class HlfirReductionIntrinsic : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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using HlfirSumLowering = HlfirReductionIntrinsic<hlfir::SumOp, true>;
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using HlfirProductLowering = HlfirReductionIntrinsic<hlfir::ProductOp, true>;
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using HlfirMaxvalLowering = HlfirReductionIntrinsic<hlfir::MaxvalOp, true>;
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using HlfirMinvalLowering = HlfirReductionIntrinsic<hlfir::MinvalOp, true>;
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using HlfirAnyLowering = HlfirReductionIntrinsic<hlfir::AnyOp, false>;
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using HlfirAllLowering = HlfirReductionIntrinsic<hlfir::AllOp, false>;
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template <typename OP>
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class HlfirMinMaxLocIntrinsic : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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using HlfirMinlocLowering = HlfirMinMaxLocIntrinsic<hlfir::MinlocOp>;
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using HlfirMaxlocLowering = HlfirMinMaxLocIntrinsic<hlfir::MaxlocOp>;
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template <typename OP>
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class HlfirProductIntrinsic : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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using HlfirMatmulLowering = HlfirProductIntrinsic<hlfir::MatmulOp>;
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using HlfirDotProductLowering = HlfirProductIntrinsic<hlfir::DotProductOp>;
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class HlfirTransposeLowering : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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class HlfirCountLowering : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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class HlfirCharExtremumLowering : public HlfirTransformationalIntrinsic {
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public:
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HlfirCharExtremumLowering(fir::FirOpBuilder &builder, mlir::Location loc,
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hlfir::CharExtremumPredicate pred)
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: HlfirTransformationalIntrinsic(builder, loc), pred{pred} {}
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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protected:
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hlfir::CharExtremumPredicate pred;
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};
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class HlfirCShiftLowering : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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class HlfirReshapeLowering : public HlfirTransformationalIntrinsic {
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public:
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using HlfirTransformationalIntrinsic::HlfirTransformationalIntrinsic;
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protected:
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mlir::Value
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lowerImpl(const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) override;
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};
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} // namespace
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mlir::Value HlfirTransformationalIntrinsic::loadBoxAddress(
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const std::optional<Fortran::lower::PreparedActualArgument> &arg) {
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if (!arg)
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return mlir::Value{};
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hlfir::Entity actual = arg->getActual(loc, builder);
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if (!arg->handleDynamicOptional()) {
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if (actual.isMutableBox()) {
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// this is a box address type but is not dynamically optional. Just load
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// the box, assuming it is well formed (!fir.ref<!fir.box<...>> ->
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// !fir.box<...>)
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return builder.create<fir::LoadOp>(loc, actual.getBase());
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}
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return actual;
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}
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auto [exv, cleanup] = hlfir::translateToExtendedValue(loc, builder, actual);
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addCleanup(cleanup);
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mlir::Value isPresent = arg->getIsPresent();
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// createBox will not do create any invalid memory dereferences if exv is
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// absent. The created fir.box will not be usable, but the SelectOp below
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// ensures it won't be.
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mlir::Value box = builder.createBox(loc, exv);
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mlir::Type boxType = box.getType();
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auto absent = builder.create<fir::AbsentOp>(loc, boxType);
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auto boxOrAbsent = builder.create<mlir::arith::SelectOp>(
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loc, boxType, isPresent, box, absent);
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return boxOrAbsent;
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}
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static mlir::Value loadOptionalValue(
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mlir::Location loc, fir::FirOpBuilder &builder,
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const std::optional<Fortran::lower::PreparedActualArgument> &arg,
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hlfir::Entity actual) {
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if (!arg->handleDynamicOptional())
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return hlfir::loadTrivialScalar(loc, builder, actual);
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mlir::Value isPresent = arg->getIsPresent();
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mlir::Type eleType = hlfir::getFortranElementType(actual.getType());
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return builder
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.genIfOp(loc, {eleType}, isPresent,
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/*withElseRegion=*/true)
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.genThen([&]() {
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assert(actual.isScalar() && fir::isa_trivial(eleType) &&
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"must be a numerical or logical scalar");
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hlfir::Entity val = hlfir::loadTrivialScalar(loc, builder, actual);
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builder.create<fir::ResultOp>(loc, val);
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})
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.genElse([&]() {
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mlir::Value zero = fir::factory::createZeroValue(builder, loc, eleType);
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builder.create<fir::ResultOp>(loc, zero);
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})
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.getResults()[0];
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}
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llvm::SmallVector<mlir::Value> HlfirTransformationalIntrinsic::getOperandVector(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering) {
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llvm::SmallVector<mlir::Value> operands;
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operands.reserve(loweredActuals.size());
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for (size_t i = 0; i < loweredActuals.size(); ++i) {
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std::optional<Fortran::lower::PreparedActualArgument> arg =
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loweredActuals[i];
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if (!arg) {
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operands.emplace_back();
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continue;
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}
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hlfir::Entity actual = arg->getActual(loc, builder);
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mlir::Value valArg;
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if (!argLowering) {
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valArg = hlfir::loadTrivialScalar(loc, builder, actual);
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} else {
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fir::ArgLoweringRule argRules =
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fir::lowerIntrinsicArgumentAs(*argLowering, i);
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if (argRules.lowerAs == fir::LowerIntrinsicArgAs::Box)
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valArg = loadBoxAddress(arg);
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else if (!argRules.handleDynamicOptional &&
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argRules.lowerAs != fir::LowerIntrinsicArgAs::Inquired)
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valArg = hlfir::derefPointersAndAllocatables(loc, builder, actual);
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else if (argRules.handleDynamicOptional &&
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argRules.lowerAs == fir::LowerIntrinsicArgAs::Value)
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valArg = loadOptionalValue(loc, builder, arg, actual);
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else if (argRules.handleDynamicOptional)
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TODO(loc, "hlfir transformational intrinsic dynamically optional "
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"argument without box lowering");
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else
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valArg = actual.getBase();
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}
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operands.emplace_back(valArg);
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}
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return operands;
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}
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mlir::Type
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HlfirTransformationalIntrinsic::computeResultType(mlir::Value argArray,
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mlir::Type stmtResultType) {
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mlir::Type normalisedResult =
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hlfir::getFortranElementOrSequenceType(stmtResultType);
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if (auto array = mlir::dyn_cast<fir::SequenceType>(normalisedResult)) {
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hlfir::ExprType::Shape resultShape =
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hlfir::ExprType::Shape{array.getShape()};
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mlir::Type elementType = array.getEleTy();
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return hlfir::ExprType::get(builder.getContext(), resultShape, elementType,
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fir::isPolymorphicType(stmtResultType));
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} else if (auto resCharType =
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mlir::dyn_cast<fir::CharacterType>(stmtResultType)) {
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normalisedResult = hlfir::ExprType::get(
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builder.getContext(), hlfir::ExprType::Shape{}, resCharType,
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/*polymorphic=*/false);
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}
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return normalisedResult;
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}
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template <typename OP, bool HAS_MASK>
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mlir::Value HlfirReductionIntrinsic<OP, HAS_MASK>::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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mlir::Value array = operands[0];
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mlir::Value dim = operands[1];
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// dim, mask can be NULL if these arguments are not given
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if (dim)
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dim = hlfir::loadTrivialScalar(loc, builder, hlfir::Entity{dim});
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mlir::Type resultTy = computeResultType(array, stmtResultType);
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OP op;
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if constexpr (HAS_MASK)
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op = createOp<OP>(resultTy, array, dim,
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/*mask=*/operands[2]);
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else
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op = createOp<OP>(resultTy, array, dim);
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return op;
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}
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template <typename OP>
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mlir::Value HlfirMinMaxLocIntrinsic<OP>::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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mlir::Value array = operands[0];
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mlir::Value dim = operands[1];
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mlir::Value mask = operands[2];
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mlir::Value back = operands[4];
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// dim, mask and back can be NULL if these arguments are not given.
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if (dim)
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dim = hlfir::loadTrivialScalar(loc, builder, hlfir::Entity{dim});
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if (back)
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back = hlfir::loadTrivialScalar(loc, builder, hlfir::Entity{back});
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mlir::Type resultTy = computeResultType(array, stmtResultType);
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return createOp<OP>(resultTy, array, dim, mask, back);
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}
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template <typename OP>
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mlir::Value HlfirProductIntrinsic<OP>::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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mlir::Type resultType = computeResultType(operands[0], stmtResultType);
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return createOp<OP>(resultType, operands[0], operands[1]);
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}
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mlir::Value HlfirTransposeLowering::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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hlfir::ExprType::Shape resultShape;
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mlir::Type normalisedResult =
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hlfir::getFortranElementOrSequenceType(stmtResultType);
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auto array = mlir::cast<fir::SequenceType>(normalisedResult);
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llvm::ArrayRef<int64_t> arrayShape = array.getShape();
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assert(arrayShape.size() == 2 && "arguments to transpose have a rank of 2");
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mlir::Type elementType = array.getEleTy();
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resultShape.push_back(arrayShape[0]);
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resultShape.push_back(arrayShape[1]);
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if (auto resCharType = mlir::dyn_cast<fir::CharacterType>(elementType))
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if (!resCharType.hasConstantLen()) {
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// The FunctionRef expression might have imprecise character
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// type at this point, and we can improve it by propagating
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// the constant length from the argument.
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auto argCharType = mlir::dyn_cast<fir::CharacterType>(
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hlfir::getFortranElementType(operands[0].getType()));
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if (argCharType && argCharType.hasConstantLen())
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elementType = fir::CharacterType::get(
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builder.getContext(), resCharType.getFKind(), argCharType.getLen());
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}
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mlir::Type resultTy =
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hlfir::ExprType::get(builder.getContext(), resultShape, elementType,
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fir::isPolymorphicType(stmtResultType));
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return createOp<hlfir::TransposeOp>(resultTy, operands[0]);
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}
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mlir::Value HlfirCountLowering::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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mlir::Value array = operands[0];
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mlir::Value dim = operands[1];
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if (dim)
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dim = hlfir::loadTrivialScalar(loc, builder, hlfir::Entity{dim});
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mlir::Type resultType = computeResultType(array, stmtResultType);
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return createOp<hlfir::CountOp>(resultType, array, dim);
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}
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mlir::Value HlfirCharExtremumLowering::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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assert(operands.size() >= 2);
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return createOp<hlfir::CharExtremumOp>(pred, mlir::ValueRange{operands});
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}
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mlir::Value HlfirCShiftLowering::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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assert(operands.size() == 3);
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mlir::Value dim = operands[2];
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if (!dim) {
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// If DIM is not present, drop the last element which is a null Value.
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operands.truncate(2);
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} else {
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// If DIM is present, then dereference it if it is a ref.
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dim = hlfir::loadTrivialScalar(loc, builder, hlfir::Entity{dim});
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operands[2] = dim;
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}
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mlir::Type resultType = computeResultType(operands[0], stmtResultType);
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return createOp<hlfir::CShiftOp>(resultType, operands);
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}
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mlir::Value HlfirReshapeLowering::lowerImpl(
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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auto operands = getOperandVector(loweredActuals, argLowering);
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assert(operands.size() == 4);
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mlir::Type resultType = computeResultType(operands[0], stmtResultType);
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return createOp<hlfir::ReshapeOp>(resultType, operands[0], operands[1],
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operands[2], operands[3]);
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}
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std::optional<hlfir::EntityWithAttributes> Fortran::lower::lowerHlfirIntrinsic(
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fir::FirOpBuilder &builder, mlir::Location loc, const std::string &name,
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const Fortran::lower::PreparedActualArguments &loweredActuals,
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const fir::IntrinsicArgumentLoweringRules *argLowering,
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mlir::Type stmtResultType) {
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// If the result is of a derived type that may need finalization,
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// we have to use DestroyOp with 'finalize' attribute for the result
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// of the intrinsic operation.
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if (name == "sum")
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return HlfirSumLowering{builder, loc}.lower(loweredActuals, argLowering,
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stmtResultType);
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if (name == "product")
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return HlfirProductLowering{builder, loc}.lower(loweredActuals, argLowering,
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|
stmtResultType);
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if (name == "any")
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return HlfirAnyLowering{builder, loc}.lower(loweredActuals, argLowering,
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|
stmtResultType);
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if (name == "all")
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return HlfirAllLowering{builder, loc}.lower(loweredActuals, argLowering,
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|
stmtResultType);
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if (name == "matmul")
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return HlfirMatmulLowering{builder, loc}.lower(loweredActuals, argLowering,
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|
stmtResultType);
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|
if (name == "dot_product")
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|
return HlfirDotProductLowering{builder, loc}.lower(
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|
loweredActuals, argLowering, stmtResultType);
|
|
// FIXME: the result may need finalization.
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|
if (name == "transpose")
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|
return HlfirTransposeLowering{builder, loc}.lower(
|
|
loweredActuals, argLowering, stmtResultType);
|
|
if (name == "count")
|
|
return HlfirCountLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (name == "maxval")
|
|
return HlfirMaxvalLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (name == "minval")
|
|
return HlfirMinvalLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (name == "minloc")
|
|
return HlfirMinlocLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (name == "maxloc")
|
|
return HlfirMaxlocLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (name == "cshift")
|
|
return HlfirCShiftLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (name == "reshape")
|
|
return HlfirReshapeLowering{builder, loc}.lower(loweredActuals, argLowering,
|
|
stmtResultType);
|
|
if (mlir::isa<fir::CharacterType>(stmtResultType)) {
|
|
if (name == "min")
|
|
return HlfirCharExtremumLowering{builder, loc,
|
|
hlfir::CharExtremumPredicate::min}
|
|
.lower(loweredActuals, argLowering, stmtResultType);
|
|
if (name == "max")
|
|
return HlfirCharExtremumLowering{builder, loc,
|
|
hlfir::CharExtremumPredicate::max}
|
|
.lower(loweredActuals, argLowering, stmtResultType);
|
|
}
|
|
return std::nullopt;
|
|
}
|