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llvm-project/flang/lib/Optimizer/Dialect/FIROps.cpp
Slava Zakharin 70343c8d44
[mlir][flang] Added Weighted[Region]BranchOpInterface's. (#142079) 
The new interfaces provide getters and setters for the weight
information about the branches of BranchOpInterface and
RegionBranchOpInterface operations.

These interfaces are done the same way as LLVM dialect's
BranchWeightOpInterface.

The plan is to produce this information in Flang, e.g. mark
most probably "cold" code as such and allow LLVM to order
basic blocks accordingly. An example of such a code is
copy loops generated for arrays repacking - we can mark it
as "cold" assuming that the copy will not happen dynamically.
If the copy actually happens the overhead of the copy is probably high
enough so that we may not care about the little overhead
of jumping to the "cold" code and fetching it.
2025-06-17 16:14:13 -07:00

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//===-- FIROps.cpp --------------------------------------------------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// Coding style: https://mlir.llvm.org/getting_started/DeveloperGuide/
//
//===----------------------------------------------------------------------===//
#include "flang/Optimizer/Dialect/FIROps.h"
#include "flang/Optimizer/Dialect/FIRAttr.h"
#include "flang/Optimizer/Dialect/FIRDialect.h"
#include "flang/Optimizer/Dialect/FIROpsSupport.h"
#include "flang/Optimizer/Dialect/FIRType.h"
#include "flang/Optimizer/Dialect/Support/FIRContext.h"
#include "flang/Optimizer/Dialect/Support/KindMapping.h"
#include "flang/Optimizer/Support/Utils.h"
#include "mlir/Dialect/CommonFolders.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/OpenACC/OpenACC.h"
#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/BuiltinAttributes.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/OpDefinition.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/TypeRange.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/TypeSwitch.h"
#include "llvm/Support/CommandLine.h"
namespace {
#include "flang/Optimizer/Dialect/CanonicalizationPatterns.inc"
} // namespace
static llvm::cl::opt<bool> clUseStrictVolatileVerification(
"strict-fir-volatile-verifier", llvm::cl::init(false),
llvm::cl::desc(
"use stricter verifier for FIR operations with volatile types"));
bool fir::useStrictVolatileVerification() {
return clUseStrictVolatileVerification;
}
static void propagateAttributes(mlir::Operation *fromOp,
mlir::Operation *toOp) {
if (!fromOp || !toOp)
return;
for (mlir::NamedAttribute attr : fromOp->getAttrs()) {
if (attr.getName().getValue().starts_with(
mlir::acc::OpenACCDialect::getDialectNamespace()))
toOp->setAttr(attr.getName(), attr.getValue());
}
}
/// Return true if a sequence type is of some incomplete size or a record type
/// is malformed or contains an incomplete sequence type. An incomplete sequence
/// type is one with more unknown extents in the type than have been provided
/// via `dynamicExtents`. Sequence types with an unknown rank are incomplete by
/// definition.
static bool verifyInType(mlir::Type inType,
llvm::SmallVectorImpl<llvm::StringRef> &visited,
unsigned dynamicExtents = 0) {
if (auto st = mlir::dyn_cast<fir::SequenceType>(inType)) {
auto shape = st.getShape();
if (shape.size() == 0)
return true;
for (std::size_t i = 0, end = shape.size(); i < end; ++i) {
if (shape[i] != fir::SequenceType::getUnknownExtent())
continue;
if (dynamicExtents-- == 0)
return true;
}
} else if (auto rt = mlir::dyn_cast<fir::RecordType>(inType)) {
// don't recurse if we're already visiting this one
if (llvm::is_contained(visited, rt.getName()))
return false;
// keep track of record types currently being visited
visited.push_back(rt.getName());
for (auto &field : rt.getTypeList())
if (verifyInType(field.second, visited))
return true;
visited.pop_back();
}
return false;
}
static bool verifyTypeParamCount(mlir::Type inType, unsigned numParams) {
auto ty = fir::unwrapSequenceType(inType);
if (numParams > 0) {
if (auto recTy = mlir::dyn_cast<fir::RecordType>(ty))
return numParams != recTy.getNumLenParams();
if (auto chrTy = mlir::dyn_cast<fir::CharacterType>(ty))
return !(numParams == 1 && chrTy.hasDynamicLen());
return true;
}
if (auto chrTy = mlir::dyn_cast<fir::CharacterType>(ty))
return !chrTy.hasConstantLen();
return false;
}
/// Parser shared by Alloca and Allocmem
///
/// operation ::= %res = (`fir.alloca` | `fir.allocmem`) $in_type
/// ( `(` $typeparams `)` )? ( `,` $shape )?
/// attr-dict-without-keyword
template <typename FN>
static mlir::ParseResult parseAllocatableOp(FN wrapResultType,
mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::Type intype;
if (parser.parseType(intype))
return mlir::failure();
auto &builder = parser.getBuilder();
result.addAttribute("in_type", mlir::TypeAttr::get(intype));
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> operands;
llvm::SmallVector<mlir::Type> typeVec;
bool hasOperands = false;
std::int32_t typeparamsSize = 0;
if (!parser.parseOptionalLParen()) {
// parse the LEN params of the derived type. (<params> : <types>)
if (parser.parseOperandList(operands, mlir::OpAsmParser::Delimiter::None) ||
parser.parseColonTypeList(typeVec) || parser.parseRParen())
return mlir::failure();
typeparamsSize = operands.size();
hasOperands = true;
}
std::int32_t shapeSize = 0;
if (!parser.parseOptionalComma()) {
// parse size to scale by, vector of n dimensions of type index
if (parser.parseOperandList(operands, mlir::OpAsmParser::Delimiter::None))
return mlir::failure();
shapeSize = operands.size() - typeparamsSize;
auto idxTy = builder.getIndexType();
for (std::int32_t i = typeparamsSize, end = operands.size(); i != end; ++i)
typeVec.push_back(idxTy);
hasOperands = true;
}
if (hasOperands &&
parser.resolveOperands(operands, typeVec, parser.getNameLoc(),
result.operands))
return mlir::failure();
mlir::Type restype = wrapResultType(intype);
if (!restype) {
parser.emitError(parser.getNameLoc(), "invalid allocate type: ") << intype;
return mlir::failure();
}
result.addAttribute("operandSegmentSizes", builder.getDenseI32ArrayAttr(
{typeparamsSize, shapeSize}));
if (parser.parseOptionalAttrDict(result.attributes) ||
parser.addTypeToList(restype, result.types))
return mlir::failure();
return mlir::success();
}
template <typename OP>
static void printAllocatableOp(mlir::OpAsmPrinter &p, OP &op) {
p << ' ' << op.getInType();
if (!op.getTypeparams().empty()) {
p << '(' << op.getTypeparams() << " : " << op.getTypeparams().getTypes()
<< ')';
}
// print the shape of the allocation (if any); all must be index type
for (auto sh : op.getShape()) {
p << ", ";
p.printOperand(sh);
}
p.printOptionalAttrDict(op->getAttrs(), {"in_type", "operandSegmentSizes"});
}
//===----------------------------------------------------------------------===//
// AllocaOp
//===----------------------------------------------------------------------===//
/// Create a legal memory reference as return type
static mlir::Type wrapAllocaResultType(mlir::Type intype) {
// FIR semantics: memory references to memory references are disallowed
if (mlir::isa<fir::ReferenceType>(intype))
return {};
return fir::ReferenceType::get(intype);
}
mlir::Type fir::AllocaOp::getAllocatedType() {
return mlir::cast<fir::ReferenceType>(getType()).getEleTy();
}
mlir::Type fir::AllocaOp::getRefTy(mlir::Type ty) {
return fir::ReferenceType::get(ty);
}
void fir::AllocaOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
llvm::StringRef uniqName, mlir::ValueRange typeparams,
mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
auto nameAttr = builder.getStringAttr(uniqName);
build(builder, result, wrapAllocaResultType(inType), inType, nameAttr, {},
/*pinned=*/false, typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocaOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
llvm::StringRef uniqName, bool pinned,
mlir::ValueRange typeparams, mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
auto nameAttr = builder.getStringAttr(uniqName);
build(builder, result, wrapAllocaResultType(inType), inType, nameAttr, {},
pinned, typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocaOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
llvm::StringRef uniqName, llvm::StringRef bindcName,
mlir::ValueRange typeparams, mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
auto nameAttr =
uniqName.empty() ? mlir::StringAttr{} : builder.getStringAttr(uniqName);
auto bindcAttr =
bindcName.empty() ? mlir::StringAttr{} : builder.getStringAttr(bindcName);
build(builder, result, wrapAllocaResultType(inType), inType, nameAttr,
bindcAttr, /*pinned=*/false, typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocaOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
llvm::StringRef uniqName, llvm::StringRef bindcName,
bool pinned, mlir::ValueRange typeparams,
mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
auto nameAttr =
uniqName.empty() ? mlir::StringAttr{} : builder.getStringAttr(uniqName);
auto bindcAttr =
bindcName.empty() ? mlir::StringAttr{} : builder.getStringAttr(bindcName);
build(builder, result, wrapAllocaResultType(inType), inType, nameAttr,
bindcAttr, pinned, typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocaOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
mlir::ValueRange typeparams, mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
build(builder, result, wrapAllocaResultType(inType), inType, {}, {},
/*pinned=*/false, typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocaOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
bool pinned, mlir::ValueRange typeparams,
mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
build(builder, result, wrapAllocaResultType(inType), inType, {}, {}, pinned,
typeparams, shape);
result.addAttributes(attributes);
}
mlir::ParseResult fir::AllocaOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseAllocatableOp(wrapAllocaResultType, parser, result);
}
void fir::AllocaOp::print(mlir::OpAsmPrinter &p) {
printAllocatableOp(p, *this);
}
llvm::LogicalResult fir::AllocaOp::verify() {
llvm::SmallVector<llvm::StringRef> visited;
if (verifyInType(getInType(), visited, numShapeOperands()))
return emitOpError("invalid type for allocation");
if (verifyTypeParamCount(getInType(), numLenParams()))
return emitOpError("LEN params do not correspond to type");
mlir::Type outType = getType();
if (!mlir::isa<fir::ReferenceType>(outType))
return emitOpError("must be a !fir.ref type");
return mlir::success();
}
bool fir::AllocaOp::ownsNestedAlloca(mlir::Operation *op) {
return op->hasTrait<mlir::OpTrait::IsIsolatedFromAbove>() ||
op->hasTrait<mlir::OpTrait::AutomaticAllocationScope>() ||
mlir::isa<mlir::LoopLikeOpInterface>(*op);
}
mlir::Region *fir::AllocaOp::getOwnerRegion() {
mlir::Operation *currentOp = getOperation();
while (mlir::Operation *parentOp = currentOp->getParentOp()) {
// If the operation was not registered, inquiries about its traits will be
// incorrect and it is not possible to reason about the operation. This
// should not happen in a normal Fortran compilation flow, but be foolproof.
if (!parentOp->isRegistered())
return nullptr;
if (fir::AllocaOp::ownsNestedAlloca(parentOp))
return currentOp->getParentRegion();
currentOp = parentOp;
}
return nullptr;
}
//===----------------------------------------------------------------------===//
// AllocMemOp
//===----------------------------------------------------------------------===//
/// Create a legal heap reference as return type
static mlir::Type wrapAllocMemResultType(mlir::Type intype) {
// Fortran semantics: C852 an entity cannot be both ALLOCATABLE and POINTER
// 8.5.3 note 1 prohibits ALLOCATABLE procedures as well
// FIR semantics: one may not allocate a memory reference value
if (mlir::isa<fir::ReferenceType, fir::HeapType, fir::PointerType,
mlir::FunctionType>(intype))
return {};
return fir::HeapType::get(intype);
}
mlir::Type fir::AllocMemOp::getAllocatedType() {
return mlir::cast<fir::HeapType>(getType()).getEleTy();
}
mlir::Type fir::AllocMemOp::getRefTy(mlir::Type ty) {
return fir::HeapType::get(ty);
}
void fir::AllocMemOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
llvm::StringRef uniqName,
mlir::ValueRange typeparams, mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
auto nameAttr = builder.getStringAttr(uniqName);
build(builder, result, wrapAllocMemResultType(inType), inType, nameAttr, {},
typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocMemOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
llvm::StringRef uniqName, llvm::StringRef bindcName,
mlir::ValueRange typeparams, mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
auto nameAttr = builder.getStringAttr(uniqName);
auto bindcAttr = builder.getStringAttr(bindcName);
build(builder, result, wrapAllocMemResultType(inType), inType, nameAttr,
bindcAttr, typeparams, shape);
result.addAttributes(attributes);
}
void fir::AllocMemOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Type inType,
mlir::ValueRange typeparams, mlir::ValueRange shape,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
build(builder, result, wrapAllocMemResultType(inType), inType, {}, {},
typeparams, shape);
result.addAttributes(attributes);
}
mlir::ParseResult fir::AllocMemOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseAllocatableOp(wrapAllocMemResultType, parser, result);
}
void fir::AllocMemOp::print(mlir::OpAsmPrinter &p) {
printAllocatableOp(p, *this);
}
llvm::LogicalResult fir::AllocMemOp::verify() {
llvm::SmallVector<llvm::StringRef> visited;
if (verifyInType(getInType(), visited, numShapeOperands()))
return emitOpError("invalid type for allocation");
if (verifyTypeParamCount(getInType(), numLenParams()))
return emitOpError("LEN params do not correspond to type");
mlir::Type outType = getType();
if (!mlir::dyn_cast<fir::HeapType>(outType))
return emitOpError("must be a !fir.heap type");
if (fir::isa_unknown_size_box(fir::dyn_cast_ptrEleTy(outType)))
return emitOpError("cannot allocate !fir.box of unknown rank or type");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ArrayCoorOp
//===----------------------------------------------------------------------===//
// CHARACTERs and derived types with LEN PARAMETERs are dependent types that
// require runtime values to fully define the type of an object.
static bool validTypeParams(mlir::Type dynTy, mlir::ValueRange typeParams,
bool allowParamsForBox = false) {
dynTy = fir::unwrapAllRefAndSeqType(dynTy);
if (mlir::isa<fir::BaseBoxType>(dynTy)) {
// A box value will contain type parameter values itself.
if (!allowParamsForBox)
return typeParams.size() == 0;
// A boxed value may have no length parameters, when the lengths
// are assumed. If dynamic lengths are used, then proceed
// to the verification below.
if (typeParams.size() == 0)
return true;
dynTy = fir::getFortranElementType(dynTy);
}
// Derived type must have all type parameters satisfied.
if (auto recTy = mlir::dyn_cast<fir::RecordType>(dynTy))
return typeParams.size() == recTy.getNumLenParams();
// Characters with non-constant LEN must have a type parameter value.
if (auto charTy = mlir::dyn_cast<fir::CharacterType>(dynTy))
if (charTy.hasDynamicLen())
return typeParams.size() == 1;
// Otherwise, any type parameters are invalid.
return typeParams.size() == 0;
}
llvm::LogicalResult fir::ArrayCoorOp::verify() {
auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(getMemref().getType());
auto arrTy = mlir::dyn_cast<fir::SequenceType>(eleTy);
if (!arrTy)
return emitOpError("must be a reference to an array");
auto arrDim = arrTy.getDimension();
if (auto shapeOp = getShape()) {
auto shapeTy = shapeOp.getType();
unsigned shapeTyRank = 0;
if (auto s = mlir::dyn_cast<fir::ShapeType>(shapeTy)) {
shapeTyRank = s.getRank();
} else if (auto ss = mlir::dyn_cast<fir::ShapeShiftType>(shapeTy)) {
shapeTyRank = ss.getRank();
} else {
auto s = mlir::cast<fir::ShiftType>(shapeTy);
shapeTyRank = s.getRank();
// TODO: it looks like PreCGRewrite and CodeGen can support
// fir.shift with plain array reference, so we may consider
// removing this check.
if (!mlir::isa<fir::BaseBoxType>(getMemref().getType()))
return emitOpError("shift can only be provided with fir.box memref");
}
if (arrDim && arrDim != shapeTyRank)
return emitOpError("rank of dimension mismatched");
// TODO: support slicing with changing the number of dimensions,
// e.g. when array_coor represents an element access to array(:,1,:)
// slice: the shape is 3D and the number of indices is 2 in this case.
if (shapeTyRank != getIndices().size())
return emitOpError("number of indices do not match dim rank");
}
if (auto sliceOp = getSlice()) {
if (auto sl = mlir::dyn_cast_or_null<fir::SliceOp>(sliceOp.getDefiningOp()))
if (!sl.getSubstr().empty())
return emitOpError("array_coor cannot take a slice with substring");
if (auto sliceTy = mlir::dyn_cast<fir::SliceType>(sliceOp.getType()))
if (sliceTy.getRank() != arrDim)
return emitOpError("rank of dimension in slice mismatched");
}
if (!validTypeParams(getMemref().getType(), getTypeparams()))
return emitOpError("invalid type parameters");
return mlir::success();
}
// Pull in fir.embox and fir.rebox into fir.array_coor when possible.
struct SimplifyArrayCoorOp : public mlir::OpRewritePattern<fir::ArrayCoorOp> {
using mlir::OpRewritePattern<fir::ArrayCoorOp>::OpRewritePattern;
llvm::LogicalResult
matchAndRewrite(fir::ArrayCoorOp op,
mlir::PatternRewriter &rewriter) const override {
mlir::Value memref = op.getMemref();
if (!mlir::isa<fir::BaseBoxType>(memref.getType()))
return mlir::failure();
mlir::Value boxedMemref, boxedShape, boxedSlice;
if (auto emboxOp =
mlir::dyn_cast_or_null<fir::EmboxOp>(memref.getDefiningOp())) {
boxedMemref = emboxOp.getMemref();
boxedShape = emboxOp.getShape();
boxedSlice = emboxOp.getSlice();
// If any of operands, that are not currently supported for migration
// to ArrayCoorOp, is present, don't rewrite.
if (!emboxOp.getTypeparams().empty() || emboxOp.getSourceBox() ||
emboxOp.getAccessMap())
return mlir::failure();
} else if (auto reboxOp = mlir::dyn_cast_or_null<fir::ReboxOp>(
memref.getDefiningOp())) {
boxedMemref = reboxOp.getBox();
boxedShape = reboxOp.getShape();
// Avoid pulling in rebox that performs reshaping.
// There is no way to represent box reshaping with array_coor.
if (boxedShape && !mlir::isa<fir::ShiftType>(boxedShape.getType()))
return mlir::failure();
boxedSlice = reboxOp.getSlice();
} else {
return mlir::failure();
}
bool boxedShapeIsShift =
boxedShape && mlir::isa<fir::ShiftType>(boxedShape.getType());
bool boxedShapeIsShape =
boxedShape && mlir::isa<fir::ShapeType>(boxedShape.getType());
bool boxedShapeIsShapeShift =
boxedShape && mlir::isa<fir::ShapeShiftType>(boxedShape.getType());
// Slices changing the number of dimensions are not supported
// for array_coor yet.
unsigned origBoxRank;
if (mlir::isa<fir::BaseBoxType>(boxedMemref.getType()))
origBoxRank = fir::getBoxRank(boxedMemref.getType());
else if (auto arrTy = mlir::dyn_cast<fir::SequenceType>(
fir::unwrapRefType(boxedMemref.getType())))
origBoxRank = arrTy.getDimension();
else
return mlir::failure();
if (fir::getBoxRank(memref.getType()) != origBoxRank)
return mlir::failure();
// Slices with substring are not supported by array_coor.
if (boxedSlice)
if (auto sliceOp =
mlir::dyn_cast_or_null<fir::SliceOp>(boxedSlice.getDefiningOp()))
if (!sliceOp.getSubstr().empty())
return mlir::failure();
// If embox/rebox and array_coor have conflicting shapes or slices,
// do nothing.
if (op.getShape() && boxedShape && boxedShape != op.getShape())
return mlir::failure();
if (op.getSlice() && boxedSlice && boxedSlice != op.getSlice())
return mlir::failure();
std::optional<IndicesVectorTy> shiftedIndices;
// The embox/rebox and array_coor either have compatible
// shape/slice at this point or shape/slice is null
// in one of them but not in the other.
// The compatibility means they are equal or both null.
if (!op.getShape()) {
if (boxedShape) {
if (op.getSlice()) {
if (!boxedSlice) {
if (boxedShapeIsShift) {
// %0 = fir.rebox %arg(%shift)
// %1 = fir.array_coor %0 [%slice] %idx
// Both the slice indices and %idx are 1-based, so the rebox
// may be pulled in as:
// %1 = fir.array_coor %arg [%slice] %idx
boxedShape = nullptr;
} else if (boxedShapeIsShape) {
// %0 = fir.embox %arg(%shape)
// %1 = fir.array_coor %0 [%slice] %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
} else if (boxedShapeIsShapeShift) {
// %0 = fir.embox %arg(%shapeshift)
// %1 = fir.array_coor %0 [%slice] %idx
// Pull in as:
// %shape = fir.shape <extents from the %shapeshift>
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
boxedShape = getShapeFromShapeShift(boxedShape, rewriter);
if (!boxedShape)
return mlir::failure();
} else {
return mlir::failure();
}
} else {
if (boxedShapeIsShift) {
// %0 = fir.rebox %arg(%shift) [%slice]
// %1 = fir.array_coor %0 [%slice] %idx
// This FIR may only be valid if the shape specifies
// that all lower bounds are 1s and the slice's start indices
// and strides are all 1s.
// We could pull in the rebox as:
// %1 = fir.array_coor %arg [%slice] %idx
// Do not do anything for the time being.
return mlir::failure();
} else if (boxedShapeIsShape) {
// %0 = fir.embox %arg(%shape) [%slice]
// %1 = fir.array_coor %0 [%slice] %idx
// This FIR may only be valid if the slice's start indices
// and strides are all 1s.
// We could pull in the embox as:
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
return mlir::failure();
} else if (boxedShapeIsShapeShift) {
// %0 = fir.embox %arg(%shapeshift) [%slice]
// %1 = fir.array_coor %0 [%slice] %idx
// This FIR may only be valid if the shape specifies
// that all lower bounds are 1s and the slice's start indices
// and strides are all 1s.
// We could pull in the embox as:
// %shape = fir.shape <extents from the %shapeshift>
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
return mlir::failure();
} else {
return mlir::failure();
}
}
} else { // !op.getSlice()
if (!boxedSlice) {
if (boxedShapeIsShift) {
// %0 = fir.rebox %arg(%shift)
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %1 = fir.array_coor %arg %idx
boxedShape = nullptr;
} else if (boxedShapeIsShape) {
// %0 = fir.embox %arg(%shape)
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) %idx
} else if (boxedShapeIsShapeShift) {
// %0 = fir.embox %arg(%shapeshift)
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %shape = fir.shape <extents from the %shapeshift>
// %1 = fir.array_coor %arg(%shape) %idx
boxedShape = getShapeFromShapeShift(boxedShape, rewriter);
if (!boxedShape)
return mlir::failure();
} else {
return mlir::failure();
}
} else {
if (boxedShapeIsShift) {
// %0 = fir.embox %arg(%shift) [%slice]
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %tmp = arith.addi %idx, %shift.origin
// %idx_shifted = arith.subi %tmp, 1
// %1 = fir.array_coor %arg(%shift) %[slice] %idx_shifted
shiftedIndices =
getShiftedIndices(boxedShape, op.getIndices(), rewriter);
if (!shiftedIndices)
return mlir::failure();
} else if (boxedShapeIsShape) {
// %0 = fir.embox %arg(%shape) [%slice]
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) %[slice] %idx
} else if (boxedShapeIsShapeShift) {
// %0 = fir.embox %arg(%shapeshift) [%slice]
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %tmp = arith.addi %idx, %shapeshift.lb
// %idx_shifted = arith.subi %tmp, 1
// %1 = fir.array_coor %arg(%shapeshift) %[slice] %idx_shifted
shiftedIndices =
getShiftedIndices(boxedShape, op.getIndices(), rewriter);
if (!shiftedIndices)
return mlir::failure();
} else {
return mlir::failure();
}
}
}
} else { // !boxedShape
if (op.getSlice()) {
if (!boxedSlice) {
// %0 = fir.rebox %arg
// %1 = fir.array_coor %0 [%slice] %idx
// Pull in as:
// %1 = fir.array_coor %arg [%slice] %idx
} else {
// %0 = fir.rebox %arg [%slice]
// %1 = fir.array_coor %0 [%slice] %idx
// This is a valid FIR iff the slice's lower bounds
// and strides are all 1s.
// Pull in as:
// %1 = fir.array_coor %arg [%slice] %idx
}
} else { // !op.getSlice()
if (!boxedSlice) {
// %0 = fir.rebox %arg
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %1 = fir.array_coor %arg %idx
} else {
// %0 = fir.rebox %arg [%slice]
// %1 = fir.array_coor %0 %idx
// Pull in as:
// %1 = fir.array_coor %arg [%slice] %idx
}
}
}
} else { // op.getShape()
if (boxedShape) {
// Check if pulling in non-default shape is correct.
if (op.getSlice()) {
if (!boxedSlice) {
// %0 = fir.embox %arg(%shape)
// %1 = fir.array_coor %0(%shape) [%slice] %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
} else {
// %0 = fir.embox %arg(%shape) [%slice]
// %1 = fir.array_coor %0(%shape) [%slice] %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
}
} else { // !op.getSlice()
if (!boxedSlice) {
// %0 = fir.embox %arg(%shape)
// %1 = fir.array_coor %0(%shape) %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) %idx
} else {
// %0 = fir.embox %arg(%shape) [%slice]
// %1 = fir.array_coor %0(%shape) %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
}
}
} else { // !boxedShape
if (op.getSlice()) {
if (!boxedSlice) {
// %0 = fir.rebox %arg
// %1 = fir.array_coor %0(%shape) [%slice] %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) [%slice] %idx
} else {
// %0 = fir.rebox %arg [%slice]
// %1 = fir.array_coor %0(%shape) [%slice] %idx
return mlir::failure();
}
} else { // !op.getSlice()
if (!boxedSlice) {
// %0 = fir.rebox %arg
// %1 = fir.array_coor %0(%shape) %idx
// Pull in as:
// %1 = fir.array_coor %arg(%shape) %idx
} else {
// %0 = fir.rebox %arg [%slice]
// %1 = fir.array_coor %0(%shape) %idx
// Cannot pull in without adjusting the slice indices.
return mlir::failure();
}
}
}
}
// TODO: temporarily avoid producing array_coor with the shape shift
// and plain array reference (it seems to be a limitation of
// ArrayCoorOp verifier).
if (!mlir::isa<fir::BaseBoxType>(boxedMemref.getType())) {
if (boxedShape) {
if (mlir::isa<fir::ShiftType>(boxedShape.getType()))
return mlir::failure();
} else if (op.getShape() &&
mlir::isa<fir::ShiftType>(op.getShape().getType())) {
return mlir::failure();
}
}
rewriter.modifyOpInPlace(op, [&]() {
op.getMemrefMutable().assign(boxedMemref);
if (boxedShape)
op.getShapeMutable().assign(boxedShape);
if (boxedSlice)
op.getSliceMutable().assign(boxedSlice);
if (shiftedIndices)
op.getIndicesMutable().assign(*shiftedIndices);
});
return mlir::success();
}
private:
using IndicesVectorTy = std::vector<mlir::Value>;
// If v is a shape_shift operation:
// fir.shape_shift %l1, %e1, %l2, %e2, ...
// create:
// fir.shape %e1, %e2, ...
static mlir::Value getShapeFromShapeShift(mlir::Value v,
mlir::PatternRewriter &rewriter) {
auto shapeShiftOp =
mlir::dyn_cast_or_null<fir::ShapeShiftOp>(v.getDefiningOp());
if (!shapeShiftOp)
return nullptr;
mlir::OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPoint(shapeShiftOp);
return rewriter.create<fir::ShapeOp>(shapeShiftOp.getLoc(),
shapeShiftOp.getExtents());
}
static std::optional<IndicesVectorTy>
getShiftedIndices(mlir::Value v, mlir::ValueRange indices,
mlir::PatternRewriter &rewriter) {
auto insertAdjustments = [&](mlir::Operation *op, mlir::ValueRange lbs) {
// Compute the shifted indices using the extended type.
// Note that this can probably result in less efficient
// MLIR and further LLVM IR due to the extra conversions.
mlir::OpBuilder::InsertPoint savedIP = rewriter.saveInsertionPoint();
rewriter.setInsertionPoint(op);
mlir::Location loc = op->getLoc();
mlir::Type idxTy = rewriter.getIndexType();
mlir::Value one = rewriter.create<mlir::arith::ConstantOp>(
loc, idxTy, rewriter.getIndexAttr(1));
rewriter.restoreInsertionPoint(savedIP);
auto nsw = mlir::arith::IntegerOverflowFlags::nsw;
IndicesVectorTy shiftedIndices;
for (auto [lb, idx] : llvm::zip(lbs, indices)) {
mlir::Value extLb = rewriter.create<fir::ConvertOp>(loc, idxTy, lb);
mlir::Value extIdx = rewriter.create<fir::ConvertOp>(loc, idxTy, idx);
mlir::Value add =
rewriter.create<mlir::arith::AddIOp>(loc, extIdx, extLb, nsw);
mlir::Value sub =
rewriter.create<mlir::arith::SubIOp>(loc, add, one, nsw);
shiftedIndices.push_back(sub);
}
return shiftedIndices;
};
if (auto shiftOp =
mlir::dyn_cast_or_null<fir::ShiftOp>(v.getDefiningOp())) {
return insertAdjustments(shiftOp.getOperation(), shiftOp.getOrigins());
} else if (auto shapeShiftOp = mlir::dyn_cast_or_null<fir::ShapeShiftOp>(
v.getDefiningOp())) {
return insertAdjustments(shapeShiftOp.getOperation(),
shapeShiftOp.getOrigins());
}
return std::nullopt;
}
};
void fir::ArrayCoorOp::getCanonicalizationPatterns(
mlir::RewritePatternSet &patterns, mlir::MLIRContext *context) {
// TODO: !fir.shape<1> operand may be removed from array_coor always.
patterns.add<SimplifyArrayCoorOp>(context);
}
//===----------------------------------------------------------------------===//
// ArrayLoadOp
//===----------------------------------------------------------------------===//
static mlir::Type adjustedElementType(mlir::Type t) {
if (auto ty = mlir::dyn_cast<fir::ReferenceType>(t)) {
auto eleTy = ty.getEleTy();
if (fir::isa_char(eleTy))
return eleTy;
if (fir::isa_derived(eleTy))
return eleTy;
if (mlir::isa<fir::SequenceType>(eleTy))
return eleTy;
}
return t;
}
std::vector<mlir::Value> fir::ArrayLoadOp::getExtents() {
if (auto sh = getShape())
if (auto *op = sh.getDefiningOp()) {
if (auto shOp = mlir::dyn_cast<fir::ShapeOp>(op)) {
auto extents = shOp.getExtents();
return {extents.begin(), extents.end()};
}
return mlir::cast<fir::ShapeShiftOp>(op).getExtents();
}
return {};
}
void fir::ArrayLoadOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
effects.emplace_back(mlir::MemoryEffects::Read::get(), &getMemrefMutable(),
mlir::SideEffects::DefaultResource::get());
addVolatileMemoryEffects({getMemref().getType()}, effects);
}
llvm::LogicalResult fir::ArrayLoadOp::verify() {
auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(getMemref().getType());
auto arrTy = mlir::dyn_cast<fir::SequenceType>(eleTy);
if (!arrTy)
return emitOpError("must be a reference to an array");
auto arrDim = arrTy.getDimension();
if (auto shapeOp = getShape()) {
auto shapeTy = shapeOp.getType();
unsigned shapeTyRank = 0u;
if (auto s = mlir::dyn_cast<fir::ShapeType>(shapeTy)) {
shapeTyRank = s.getRank();
} else if (auto ss = mlir::dyn_cast<fir::ShapeShiftType>(shapeTy)) {
shapeTyRank = ss.getRank();
} else {
auto s = mlir::cast<fir::ShiftType>(shapeTy);
shapeTyRank = s.getRank();
if (!mlir::isa<fir::BaseBoxType>(getMemref().getType()))
return emitOpError("shift can only be provided with fir.box memref");
}
if (arrDim && arrDim != shapeTyRank)
return emitOpError("rank of dimension mismatched");
}
if (auto sliceOp = getSlice()) {
if (auto sl = mlir::dyn_cast_or_null<fir::SliceOp>(sliceOp.getDefiningOp()))
if (!sl.getSubstr().empty())
return emitOpError("array_load cannot take a slice with substring");
if (auto sliceTy = mlir::dyn_cast<fir::SliceType>(sliceOp.getType()))
if (sliceTy.getRank() != arrDim)
return emitOpError("rank of dimension in slice mismatched");
}
if (!validTypeParams(getMemref().getType(), getTypeparams()))
return emitOpError("invalid type parameters");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ArrayMergeStoreOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ArrayMergeStoreOp::verify() {
if (!mlir::isa<fir::ArrayLoadOp>(getOriginal().getDefiningOp()))
return emitOpError("operand #0 must be result of a fir.array_load op");
if (auto sl = getSlice()) {
if (auto sliceOp =
mlir::dyn_cast_or_null<fir::SliceOp>(sl.getDefiningOp())) {
if (!sliceOp.getSubstr().empty())
return emitOpError(
"array_merge_store cannot take a slice with substring");
if (!sliceOp.getFields().empty()) {
// This is an intra-object merge, where the slice is projecting the
// subfields that are to be overwritten by the merge operation.
auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(getMemref().getType());
if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(eleTy)) {
auto projTy =
fir::applyPathToType(seqTy.getEleTy(), sliceOp.getFields());
if (fir::unwrapSequenceType(getOriginal().getType()) != projTy)
return emitOpError(
"type of origin does not match sliced memref type");
if (fir::unwrapSequenceType(getSequence().getType()) != projTy)
return emitOpError(
"type of sequence does not match sliced memref type");
return mlir::success();
}
return emitOpError("referenced type is not an array");
}
}
return mlir::success();
}
auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(getMemref().getType());
if (getOriginal().getType() != eleTy)
return emitOpError("type of origin does not match memref element type");
if (getSequence().getType() != eleTy)
return emitOpError("type of sequence does not match memref element type");
if (!validTypeParams(getMemref().getType(), getTypeparams()))
return emitOpError("invalid type parameters");
return mlir::success();
}
void fir::ArrayMergeStoreOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
effects.emplace_back(mlir::MemoryEffects::Write::get(), &getMemrefMutable(),
mlir::SideEffects::DefaultResource::get());
addVolatileMemoryEffects({getMemref().getType()}, effects);
}
//===----------------------------------------------------------------------===//
// ArrayFetchOp
//===----------------------------------------------------------------------===//
// Template function used for both array_fetch and array_update verification.
template <typename A>
mlir::Type validArraySubobject(A op) {
auto ty = op.getSequence().getType();
return fir::applyPathToType(ty, op.getIndices());
}
llvm::LogicalResult fir::ArrayFetchOp::verify() {
auto arrTy = mlir::cast<fir::SequenceType>(getSequence().getType());
auto indSize = getIndices().size();
if (indSize < arrTy.getDimension())
return emitOpError("number of indices != dimension of array");
if (indSize == arrTy.getDimension() &&
::adjustedElementType(getElement().getType()) != arrTy.getEleTy())
return emitOpError("return type does not match array");
auto ty = validArraySubobject(*this);
if (!ty || ty != ::adjustedElementType(getType()))
return emitOpError("return type and/or indices do not type check");
if (!mlir::isa<fir::ArrayLoadOp>(getSequence().getDefiningOp()))
return emitOpError("argument #0 must be result of fir.array_load");
if (!validTypeParams(arrTy, getTypeparams()))
return emitOpError("invalid type parameters");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ArrayAccessOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ArrayAccessOp::verify() {
auto arrTy = mlir::cast<fir::SequenceType>(getSequence().getType());
std::size_t indSize = getIndices().size();
if (indSize < arrTy.getDimension())
return emitOpError("number of indices != dimension of array");
if (indSize == arrTy.getDimension() &&
getElement().getType() != fir::ReferenceType::get(arrTy.getEleTy()))
return emitOpError("return type does not match array");
mlir::Type ty = validArraySubobject(*this);
if (!ty || fir::ReferenceType::get(ty) != getType())
return emitOpError("return type and/or indices do not type check");
if (!validTypeParams(arrTy, getTypeparams()))
return emitOpError("invalid type parameters");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ArrayUpdateOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ArrayUpdateOp::verify() {
if (fir::isa_ref_type(getMerge().getType()))
return emitOpError("does not support reference type for merge");
auto arrTy = mlir::cast<fir::SequenceType>(getSequence().getType());
auto indSize = getIndices().size();
if (indSize < arrTy.getDimension())
return emitOpError("number of indices != dimension of array");
if (indSize == arrTy.getDimension() &&
::adjustedElementType(getMerge().getType()) != arrTy.getEleTy())
return emitOpError("merged value does not have element type");
auto ty = validArraySubobject(*this);
if (!ty || ty != ::adjustedElementType(getMerge().getType()))
return emitOpError("merged value and/or indices do not type check");
if (!validTypeParams(arrTy, getTypeparams()))
return emitOpError("invalid type parameters");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ArrayModifyOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ArrayModifyOp::verify() {
auto arrTy = mlir::cast<fir::SequenceType>(getSequence().getType());
auto indSize = getIndices().size();
if (indSize < arrTy.getDimension())
return emitOpError("number of indices must match array dimension");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// BoxAddrOp
//===----------------------------------------------------------------------===//
void fir::BoxAddrOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Value val) {
mlir::Type type =
llvm::TypeSwitch<mlir::Type, mlir::Type>(val.getType())
.Case<fir::BaseBoxType>([&](fir::BaseBoxType ty) -> mlir::Type {
mlir::Type eleTy = ty.getEleTy();
if (fir::isa_ref_type(eleTy))
return eleTy;
return fir::ReferenceType::get(eleTy);
})
.Case<fir::BoxCharType>([&](fir::BoxCharType ty) -> mlir::Type {
return fir::ReferenceType::get(ty.getEleTy());
})
.Case<fir::BoxProcType>(
[&](fir::BoxProcType ty) { return ty.getEleTy(); })
.Default([&](const auto &) { return mlir::Type{}; });
assert(type && "bad val type");
build(builder, result, type, val);
}
mlir::OpFoldResult fir::BoxAddrOp::fold(FoldAdaptor adaptor) {
if (auto *v = getVal().getDefiningOp()) {
if (auto box = mlir::dyn_cast<fir::EmboxOp>(v)) {
// Fold only if not sliced
if (!box.getSlice() && box.getMemref().getType() == getType()) {
propagateAttributes(getOperation(), box.getMemref().getDefiningOp());
return box.getMemref();
}
}
if (auto box = mlir::dyn_cast<fir::EmboxCharOp>(v))
if (box.getMemref().getType() == getType())
return box.getMemref();
}
return {};
}
//===----------------------------------------------------------------------===//
// BoxCharLenOp
//===----------------------------------------------------------------------===//
mlir::OpFoldResult fir::BoxCharLenOp::fold(FoldAdaptor adaptor) {
if (auto v = getVal().getDefiningOp()) {
if (auto box = mlir::dyn_cast<fir::EmboxCharOp>(v))
return box.getLen();
}
return {};
}
//===----------------------------------------------------------------------===//
// BoxDimsOp
//===----------------------------------------------------------------------===//
/// Get the result types packed in a tuple tuple
mlir::Type fir::BoxDimsOp::getTupleType() {
// note: triple, but 4 is nearest power of 2
llvm::SmallVector<mlir::Type> triple{
getResult(0).getType(), getResult(1).getType(), getResult(2).getType()};
return mlir::TupleType::get(getContext(), triple);
}
//===----------------------------------------------------------------------===//
// BoxRankOp
//===----------------------------------------------------------------------===//
void fir::BoxRankOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
mlir::OpOperand &inputBox = getBoxMutable();
if (fir::isBoxAddress(inputBox.get().getType()))
effects.emplace_back(mlir::MemoryEffects::Read::get(), &inputBox,
mlir::SideEffects::DefaultResource::get());
}
//===----------------------------------------------------------------------===//
// CallOp
//===----------------------------------------------------------------------===//
mlir::FunctionType fir::CallOp::getFunctionType() {
return mlir::FunctionType::get(getContext(), getOperandTypes(),
getResultTypes());
}
void fir::CallOp::print(mlir::OpAsmPrinter &p) {
bool isDirect = getCallee().has_value();
p << ' ';
if (isDirect)
p << *getCallee();
else
p << getOperand(0);
p << '(' << (*this)->getOperands().drop_front(isDirect ? 0 : 1) << ')';
// Print `proc_attrs<...>`, if present.
fir::FortranProcedureFlagsEnumAttr procAttrs = getProcedureAttrsAttr();
if (procAttrs &&
procAttrs.getValue() != fir::FortranProcedureFlagsEnum::none) {
p << ' ' << fir::FortranProcedureFlagsEnumAttr::getMnemonic();
p.printStrippedAttrOrType(procAttrs);
}
// Print 'fastmath<...>' (if it has non-default value) before
// any other attributes.
mlir::arith::FastMathFlagsAttr fmfAttr = getFastmathAttr();
if (fmfAttr.getValue() != mlir::arith::FastMathFlags::none) {
p << ' ' << mlir::arith::FastMathFlagsAttr::getMnemonic();
p.printStrippedAttrOrType(fmfAttr);
}
p.printOptionalAttrDict((*this)->getAttrs(),
{fir::CallOp::getCalleeAttrNameStr(),
getFastmathAttrName(), getProcedureAttrsAttrName(),
getArgAttrsAttrName(), getResAttrsAttrName()});
p << " : ";
mlir::call_interface_impl::printFunctionSignature(
p, getArgs().drop_front(isDirect ? 0 : 1).getTypes(), getArgAttrsAttr(),
/*isVariadic=*/false, getResultTypes(), getResAttrsAttr());
}
mlir::ParseResult fir::CallOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> operands;
if (parser.parseOperandList(operands))
return mlir::failure();
mlir::NamedAttrList attrs;
mlir::SymbolRefAttr funcAttr;
bool isDirect = operands.empty();
if (isDirect)
if (parser.parseAttribute(funcAttr, fir::CallOp::getCalleeAttrNameStr(),
attrs))
return mlir::failure();
if (parser.parseOperandList(operands, mlir::OpAsmParser::Delimiter::Paren))
return mlir::failure();
// Parse `proc_attrs<...>`, if present.
fir::FortranProcedureFlagsEnumAttr procAttr;
if (mlir::succeeded(parser.parseOptionalKeyword(
fir::FortranProcedureFlagsEnumAttr::getMnemonic())))
if (parser.parseCustomAttributeWithFallback(
procAttr, mlir::Type{}, getProcedureAttrsAttrName(result.name),
attrs))
return mlir::failure();
// Parse 'fastmath<...>', if present.
mlir::arith::FastMathFlagsAttr fmfAttr;
llvm::StringRef fmfAttrName = getFastmathAttrName(result.name);
if (mlir::succeeded(parser.parseOptionalKeyword(fmfAttrName)))
if (parser.parseCustomAttributeWithFallback(fmfAttr, mlir::Type{},
fmfAttrName, attrs))
return mlir::failure();
if (parser.parseOptionalAttrDict(attrs) || parser.parseColon())
return mlir::failure();
llvm::SmallVector<mlir::Type> argTypes;
llvm::SmallVector<mlir::Type> resTypes;
llvm::SmallVector<mlir::DictionaryAttr> argAttrs;
llvm::SmallVector<mlir::DictionaryAttr> resultAttrs;
if (mlir::call_interface_impl::parseFunctionSignature(
parser, argTypes, argAttrs, resTypes, resultAttrs))
return parser.emitError(parser.getNameLoc(), "expected function type");
mlir::FunctionType funcType =
mlir::FunctionType::get(parser.getContext(), argTypes, resTypes);
if (isDirect) {
if (parser.resolveOperands(operands, funcType.getInputs(),
parser.getNameLoc(), result.operands))
return mlir::failure();
} else {
auto funcArgs =
llvm::ArrayRef<mlir::OpAsmParser::UnresolvedOperand>(operands)
.drop_front();
if (parser.resolveOperand(operands[0], funcType, result.operands) ||
parser.resolveOperands(funcArgs, funcType.getInputs(),
parser.getNameLoc(), result.operands))
return mlir::failure();
}
result.attributes = attrs;
mlir::call_interface_impl::addArgAndResultAttrs(
parser.getBuilder(), result, argAttrs, resultAttrs,
getArgAttrsAttrName(result.name), getResAttrsAttrName(result.name));
result.addTypes(funcType.getResults());
return mlir::success();
}
void fir::CallOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::func::FuncOp callee, mlir::ValueRange operands) {
result.addOperands(operands);
result.addAttribute(getCalleeAttrNameStr(), mlir::SymbolRefAttr::get(callee));
result.addTypes(callee.getFunctionType().getResults());
}
void fir::CallOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::SymbolRefAttr callee,
llvm::ArrayRef<mlir::Type> results,
mlir::ValueRange operands) {
result.addOperands(operands);
if (callee)
result.addAttribute(getCalleeAttrNameStr(), callee);
result.addTypes(results);
}
//===----------------------------------------------------------------------===//
// CharConvertOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::CharConvertOp::verify() {
auto unwrap = [&](mlir::Type t) {
t = fir::unwrapSequenceType(fir::dyn_cast_ptrEleTy(t));
return mlir::dyn_cast<fir::CharacterType>(t);
};
auto inTy = unwrap(getFrom().getType());
auto outTy = unwrap(getTo().getType());
if (!(inTy && outTy))
return emitOpError("not a reference to a character");
if (inTy.getFKind() == outTy.getFKind())
return emitOpError("buffers must have different KIND values");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// CmpOp
//===----------------------------------------------------------------------===//
template <typename OPTY>
static void printCmpOp(mlir::OpAsmPrinter &p, OPTY op) {
p << ' ';
auto predSym = mlir::arith::symbolizeCmpFPredicate(
op->template getAttrOfType<mlir::IntegerAttr>(
OPTY::getPredicateAttrName())
.getInt());
assert(predSym.has_value() && "invalid symbol value for predicate");
p << '"' << mlir::arith::stringifyCmpFPredicate(predSym.value()) << '"'
<< ", ";
p.printOperand(op.getLhs());
p << ", ";
p.printOperand(op.getRhs());
p.printOptionalAttrDict(op->getAttrs(),
/*elidedAttrs=*/{OPTY::getPredicateAttrName()});
p << " : " << op.getLhs().getType();
}
template <typename OPTY>
static mlir::ParseResult parseCmpOp(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> ops;
mlir::NamedAttrList attrs;
mlir::Attribute predicateNameAttr;
mlir::Type type;
if (parser.parseAttribute(predicateNameAttr, OPTY::getPredicateAttrName(),
attrs) ||
parser.parseComma() || parser.parseOperandList(ops, 2) ||
parser.parseOptionalAttrDict(attrs) || parser.parseColonType(type) ||
parser.resolveOperands(ops, type, result.operands))
return mlir::failure();
if (!mlir::isa<mlir::StringAttr>(predicateNameAttr))
return parser.emitError(parser.getNameLoc(),
"expected string comparison predicate attribute");
// Rewrite string attribute to an enum value.
llvm::StringRef predicateName =
mlir::cast<mlir::StringAttr>(predicateNameAttr).getValue();
auto predicate = fir::CmpcOp::getPredicateByName(predicateName);
auto builder = parser.getBuilder();
mlir::Type i1Type = builder.getI1Type();
attrs.set(OPTY::getPredicateAttrName(),
builder.getI64IntegerAttr(static_cast<std::int64_t>(predicate)));
result.attributes = attrs;
result.addTypes({i1Type});
return mlir::success();
}
//===----------------------------------------------------------------------===//
// CmpcOp
//===----------------------------------------------------------------------===//
void fir::buildCmpCOp(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::arith::CmpFPredicate predicate, mlir::Value lhs,
mlir::Value rhs) {
result.addOperands({lhs, rhs});
result.types.push_back(builder.getI1Type());
result.addAttribute(
fir::CmpcOp::getPredicateAttrName(),
builder.getI64IntegerAttr(static_cast<std::int64_t>(predicate)));
}
mlir::arith::CmpFPredicate
fir::CmpcOp::getPredicateByName(llvm::StringRef name) {
auto pred = mlir::arith::symbolizeCmpFPredicate(name);
assert(pred.has_value() && "invalid predicate name");
return pred.value();
}
void fir::CmpcOp::print(mlir::OpAsmPrinter &p) { printCmpOp(p, *this); }
mlir::ParseResult fir::CmpcOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseCmpOp<fir::CmpcOp>(parser, result);
}
//===----------------------------------------------------------------------===//
// VolatileCastOp
//===----------------------------------------------------------------------===//
static bool typesMatchExceptForVolatility(mlir::Type fromType,
mlir::Type toType) {
// If we can change only the volatility and get identical types, then we
// match.
if (fir::updateTypeWithVolatility(fromType, fir::isa_volatile_type(toType)) ==
toType)
return true;
// Otherwise, recurse on the element types if the base classes are the same.
const bool match =
llvm::TypeSwitch<mlir::Type, bool>(fromType)
.Case<fir::BoxType, fir::ReferenceType, fir::ClassType>(
[&](auto type) {
using TYPE = decltype(type);
// If we are not the same base class, then we don't match.
auto castedToType = mlir::dyn_cast<TYPE>(toType);
if (!castedToType)
return false;
// If we are the same base class, we match if the element types
// match.
return typesMatchExceptForVolatility(type.getEleTy(),
castedToType.getEleTy());
})
.Default([](mlir::Type) { return false; });
return match;
}
llvm::LogicalResult fir::VolatileCastOp::verify() {
mlir::Type fromType = getValue().getType();
mlir::Type toType = getType();
if (!typesMatchExceptForVolatility(fromType, toType))
return emitOpError("types must be identical except for volatility ")
<< fromType << " / " << toType;
return mlir::success();
}
mlir::OpFoldResult fir::VolatileCastOp::fold(FoldAdaptor adaptor) {
if (getValue().getType() == getType())
return getValue();
return {};
}
//===----------------------------------------------------------------------===//
// ConvertOp
//===----------------------------------------------------------------------===//
void fir::ConvertOp::getCanonicalizationPatterns(
mlir::RewritePatternSet &results, mlir::MLIRContext *context) {
results.insert<ConvertConvertOptPattern, ConvertAscendingIndexOptPattern,
ConvertDescendingIndexOptPattern, RedundantConvertOptPattern,
CombineConvertOptPattern, CombineConvertTruncOptPattern,
ForwardConstantConvertPattern, ChainedPointerConvertsPattern>(
context);
}
mlir::OpFoldResult fir::ConvertOp::fold(FoldAdaptor adaptor) {
if (getValue().getType() == getType())
return getValue();
if (matchPattern(getValue(), mlir::m_Op<fir::ConvertOp>())) {
auto inner = mlir::cast<fir::ConvertOp>(getValue().getDefiningOp());
// (convert (convert 'a : logical -> i1) : i1 -> logical) ==> forward 'a
if (auto toTy = mlir::dyn_cast<fir::LogicalType>(getType()))
if (auto fromTy =
mlir::dyn_cast<fir::LogicalType>(inner.getValue().getType()))
if (mlir::isa<mlir::IntegerType>(inner.getType()) && (toTy == fromTy))
return inner.getValue();
// (convert (convert 'a : i1 -> logical) : logical -> i1) ==> forward 'a
if (auto toTy = mlir::dyn_cast<mlir::IntegerType>(getType()))
if (auto fromTy =
mlir::dyn_cast<mlir::IntegerType>(inner.getValue().getType()))
if (mlir::isa<fir::LogicalType>(inner.getType()) && (toTy == fromTy) &&
(fromTy.getWidth() == 1))
return inner.getValue();
}
return {};
}
bool fir::ConvertOp::isInteger(mlir::Type ty) {
return mlir::isa<mlir::IntegerType, mlir::IndexType, fir::IntegerType>(ty);
}
bool fir::ConvertOp::isIntegerCompatible(mlir::Type ty) {
return isInteger(ty) || mlir::isa<fir::LogicalType>(ty);
}
bool fir::ConvertOp::isFloatCompatible(mlir::Type ty) {
return mlir::isa<mlir::FloatType>(ty);
}
bool fir::ConvertOp::isPointerCompatible(mlir::Type ty) {
return mlir::isa<fir::ReferenceType, fir::PointerType, fir::HeapType,
fir::LLVMPointerType, mlir::MemRefType, mlir::FunctionType,
fir::TypeDescType, mlir::LLVM::LLVMPointerType>(ty);
}
static std::optional<mlir::Type> getVectorElementType(mlir::Type ty) {
mlir::Type elemTy;
if (mlir::isa<fir::VectorType>(ty))
elemTy = mlir::dyn_cast<fir::VectorType>(ty).getElementType();
else if (mlir::isa<mlir::VectorType>(ty))
elemTy = mlir::dyn_cast<mlir::VectorType>(ty).getElementType();
else
return std::nullopt;
// e.g. fir.vector<4:ui32> => mlir.vector<4xi32>
// e.g. mlir.vector<4xui32> => mlir.vector<4xi32>
if (elemTy.isUnsignedInteger()) {
elemTy = mlir::IntegerType::get(
ty.getContext(), mlir::dyn_cast<mlir::IntegerType>(elemTy).getWidth());
}
return elemTy;
}
static std::optional<uint64_t> getVectorLen(mlir::Type ty) {
if (mlir::isa<fir::VectorType>(ty))
return mlir::dyn_cast<fir::VectorType>(ty).getLen();
else if (mlir::isa<mlir::VectorType>(ty)) {
// fir.vector only supports 1-D vector
if (!(mlir::dyn_cast<mlir::VectorType>(ty).isScalable()))
return mlir::dyn_cast<mlir::VectorType>(ty).getShape()[0];
}
return std::nullopt;
}
bool fir::ConvertOp::areVectorsCompatible(mlir::Type inTy, mlir::Type outTy) {
if (!(mlir::isa<fir::VectorType>(inTy) &&
mlir::isa<mlir::VectorType>(outTy)) &&
!(mlir::isa<mlir::VectorType>(inTy) && mlir::isa<fir::VectorType>(outTy)))
return false;
// Only support integer, unsigned and real vector
// Both vectors must have the same element type
std::optional<mlir::Type> inElemTy = getVectorElementType(inTy);
std::optional<mlir::Type> outElemTy = getVectorElementType(outTy);
if (!inElemTy.has_value() || !outElemTy.has_value() ||
inElemTy.value() != outElemTy.value())
return false;
// Both vectors must have the same number of elements
std::optional<uint64_t> inLen = getVectorLen(inTy);
std::optional<uint64_t> outLen = getVectorLen(outTy);
if (!inLen.has_value() || !outLen.has_value() ||
inLen.value() != outLen.value())
return false;
return true;
}
static bool areRecordsCompatible(mlir::Type inTy, mlir::Type outTy) {
// Both records must have the same field types.
// Trust frontend semantics for in-depth checks, such as if both records
// have the BIND(C) attribute.
auto inRecTy = mlir::dyn_cast<fir::RecordType>(inTy);
auto outRecTy = mlir::dyn_cast<fir::RecordType>(outTy);
return inRecTy && outRecTy && inRecTy.getTypeList() == outRecTy.getTypeList();
}
bool fir::ConvertOp::canBeConverted(mlir::Type inType, mlir::Type outType) {
if (inType == outType)
return true;
return (isPointerCompatible(inType) && isPointerCompatible(outType)) ||
(isIntegerCompatible(inType) && isIntegerCompatible(outType)) ||
(isInteger(inType) && isFloatCompatible(outType)) ||
(isFloatCompatible(inType) && isInteger(outType)) ||
(isFloatCompatible(inType) && isFloatCompatible(outType)) ||
(isIntegerCompatible(inType) && isPointerCompatible(outType)) ||
(isPointerCompatible(inType) && isIntegerCompatible(outType)) ||
(mlir::isa<fir::BoxType>(inType) &&
mlir::isa<fir::BoxType>(outType)) ||
(mlir::isa<fir::BoxProcType>(inType) &&
mlir::isa<fir::BoxProcType>(outType)) ||
(fir::isa_complex(inType) && fir::isa_complex(outType)) ||
(fir::isBoxedRecordType(inType) && fir::isPolymorphicType(outType)) ||
(fir::isPolymorphicType(inType) && fir::isPolymorphicType(outType)) ||
(fir::isPolymorphicType(inType) && mlir::isa<BoxType>(outType)) ||
areVectorsCompatible(inType, outType) ||
areRecordsCompatible(inType, outType);
}
// In general, ptrtoint-like conversions are allowed to lose volatility
// information because they are either:
//
// 1. passing an entity to an external function and there's nothing we can do
// about volatility after that happens, or
// 2. for code generation, at which point we represent volatility with
// attributes on the LLVM instructions and intrinsics.
//
// For all other cases, volatility ought to match exactly.
static mlir::LogicalResult verifyVolatility(mlir::Type inType,
mlir::Type outType) {
const bool toLLVMPointer = mlir::isa<mlir::LLVM::LLVMPointerType>(outType);
const bool toInteger = fir::isa_integer(outType);
// When converting references to classes or allocatables into boxes for
// runtime arguments, we cast away all the volatility information and pass a
// box<none>. This is allowed.
const bool isBoxNoneLike = [&]() {
if (fir::isBoxNone(outType))
return true;
if (auto referenceType = mlir::dyn_cast<fir::ReferenceType>(outType)) {
if (fir::isBoxNone(referenceType.getElementType())) {
return true;
}
}
return false;
}();
const bool isPtrToIntLike = toLLVMPointer || toInteger || isBoxNoneLike;
if (isPtrToIntLike) {
return mlir::success();
}
// In all other cases, we need to check for an exact volatility match.
return mlir::success(fir::isa_volatile_type(inType) ==
fir::isa_volatile_type(outType));
}
llvm::LogicalResult fir::ConvertOp::verify() {
mlir::Type inType = getValue().getType();
mlir::Type outType = getType();
if (fir::useStrictVolatileVerification()) {
if (failed(verifyVolatility(inType, outType))) {
return emitOpError("this conversion does not preserve volatility: ")
<< inType << " / " << outType;
}
}
if (canBeConverted(inType, outType))
return mlir::success();
return emitOpError("invalid type conversion")
<< getValue().getType() << " / " << getType();
}
//===----------------------------------------------------------------------===//
// CoordinateOp
//===----------------------------------------------------------------------===//
void fir::CoordinateOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
mlir::Type resultType, mlir::Value ref,
mlir::ValueRange coor) {
llvm::SmallVector<int32_t> fieldIndices;
llvm::SmallVector<mlir::Value> dynamicIndices;
bool anyField = false;
for (mlir::Value index : coor) {
if (auto field = index.getDefiningOp<fir::FieldIndexOp>()) {
auto recTy = mlir::cast<fir::RecordType>(field.getOnType());
fieldIndices.push_back(recTy.getFieldIndex(field.getFieldId()));
anyField = true;
} else {
fieldIndices.push_back(fir::CoordinateOp::kDynamicIndex);
dynamicIndices.push_back(index);
}
}
auto typeAttr = mlir::TypeAttr::get(ref.getType());
if (anyField) {
build(builder, result, resultType, ref, dynamicIndices, typeAttr,
builder.getDenseI32ArrayAttr(fieldIndices));
} else {
build(builder, result, resultType, ref, dynamicIndices, typeAttr, nullptr);
}
}
void fir::CoordinateOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
mlir::Type resultType, mlir::Value ref,
llvm::ArrayRef<fir::IntOrValue> coor) {
llvm::SmallVector<int32_t> fieldIndices;
llvm::SmallVector<mlir::Value> dynamicIndices;
bool anyField = false;
for (fir::IntOrValue index : coor) {
llvm::TypeSwitch<fir::IntOrValue>(index)
.Case<mlir::IntegerAttr>([&](mlir::IntegerAttr intAttr) {
fieldIndices.push_back(intAttr.getInt());
anyField = true;
})
.Case<mlir::Value>([&](mlir::Value value) {
dynamicIndices.push_back(value);
fieldIndices.push_back(fir::CoordinateOp::kDynamicIndex);
});
}
auto typeAttr = mlir::TypeAttr::get(ref.getType());
if (anyField) {
build(builder, result, resultType, ref, dynamicIndices, typeAttr,
builder.getDenseI32ArrayAttr(fieldIndices));
} else {
build(builder, result, resultType, ref, dynamicIndices, typeAttr, nullptr);
}
}
void fir::CoordinateOp::print(mlir::OpAsmPrinter &p) {
p << ' ' << getRef();
if (!getFieldIndicesAttr()) {
p << ", " << getCoor();
} else {
mlir::Type eleTy = fir::getFortranElementType(getRef().getType());
for (auto index : getIndices()) {
p << ", ";
llvm::TypeSwitch<fir::IntOrValue>(index)
.Case<mlir::IntegerAttr>([&](mlir::IntegerAttr intAttr) {
if (auto recordType = llvm::dyn_cast<fir::RecordType>(eleTy)) {
int fieldId = intAttr.getInt();
if (fieldId < static_cast<int>(recordType.getNumFields())) {
auto nameAndType = recordType.getTypeList()[fieldId];
p << std::get<std::string>(nameAndType);
eleTy = fir::getFortranElementType(
std::get<mlir::Type>(nameAndType));
return;
}
}
// Invalid index, still print it so that invalid IR can be
// investigated.
p << intAttr;
})
.Case<mlir::Value>([&](mlir::Value value) { p << value; });
}
}
p.printOptionalAttrDict(
(*this)->getAttrs(),
/*elideAttrs=*/{getBaseTypeAttrName(), getFieldIndicesAttrName()});
p << " : ";
p.printFunctionalType(getOperandTypes(), (*this)->getResultTypes());
}
mlir::ParseResult fir::CoordinateOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::OpAsmParser::UnresolvedOperand memref;
if (parser.parseOperand(memref) || parser.parseComma())
return mlir::failure();
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> coorOperands;
llvm::SmallVector<std::pair<llvm::StringRef, int>> fieldNames;
llvm::SmallVector<int32_t> fieldIndices;
while (true) {
llvm::StringRef fieldName;
if (mlir::succeeded(parser.parseOptionalKeyword(&fieldName))) {
fieldNames.push_back({fieldName, static_cast<int>(fieldIndices.size())});
// Actual value will be computed later when base type has been parsed.
fieldIndices.push_back(0);
} else {
mlir::OpAsmParser::UnresolvedOperand index;
if (parser.parseOperand(index))
return mlir::failure();
fieldIndices.push_back(fir::CoordinateOp::kDynamicIndex);
coorOperands.push_back(index);
}
if (mlir::failed(parser.parseOptionalComma()))
break;
}
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> allOperands;
allOperands.push_back(memref);
allOperands.append(coorOperands.begin(), coorOperands.end());
mlir::FunctionType funcTy;
auto loc = parser.getCurrentLocation();
if (parser.parseOptionalAttrDict(result.attributes) ||
parser.parseColonType(funcTy) ||
parser.resolveOperands(allOperands, funcTy.getInputs(), loc,
result.operands) ||
parser.addTypesToList(funcTy.getResults(), result.types))
return mlir::failure();
result.addAttribute(getBaseTypeAttrName(result.name),
mlir::TypeAttr::get(funcTy.getInput(0)));
if (!fieldNames.empty()) {
mlir::Type eleTy = fir::getFortranElementType(funcTy.getInput(0));
for (auto [fieldName, operandPosition] : fieldNames) {
auto recTy = llvm::dyn_cast<fir::RecordType>(eleTy);
if (!recTy)
return parser.emitError(
loc, "base must be a derived type when field name appears");
unsigned fieldNum = recTy.getFieldIndex(fieldName);
if (fieldNum > recTy.getNumFields())
return parser.emitError(loc)
<< "field '" << fieldName
<< "' is not a component or subcomponent of the base type";
fieldIndices[operandPosition] = fieldNum;
eleTy = fir::getFortranElementType(
std::get<mlir::Type>(recTy.getTypeList()[fieldNum]));
}
result.addAttribute(getFieldIndicesAttrName(result.name),
parser.getBuilder().getDenseI32ArrayAttr(fieldIndices));
}
return mlir::success();
}
llvm::LogicalResult fir::CoordinateOp::verify() {
const mlir::Type refTy = getRef().getType();
if (fir::isa_ref_type(refTy)) {
auto eleTy = fir::dyn_cast_ptrEleTy(refTy);
if (auto arrTy = mlir::dyn_cast<fir::SequenceType>(eleTy)) {
if (arrTy.hasUnknownShape())
return emitOpError("cannot find coordinate in unknown shape");
if (arrTy.getConstantRows() < arrTy.getDimension() - 1)
return emitOpError("cannot find coordinate with unknown extents");
}
if (!(fir::isa_aggregate(eleTy) || fir::isa_complex(eleTy) ||
fir::isa_char_string(eleTy)))
return emitOpError("cannot apply to this element type");
}
auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(refTy);
unsigned dimension = 0;
const unsigned numCoors = getCoor().size();
for (auto coorOperand : llvm::enumerate(getCoor())) {
auto co = coorOperand.value();
if (dimension == 0 && mlir::isa<fir::SequenceType>(eleTy)) {
dimension = mlir::cast<fir::SequenceType>(eleTy).getDimension();
if (dimension == 0)
return emitOpError("cannot apply to array of unknown rank");
}
if (auto *defOp = co.getDefiningOp()) {
if (auto index = mlir::dyn_cast<fir::LenParamIndexOp>(defOp)) {
// Recovering a LEN type parameter only makes sense from a boxed
// value. For a bare reference, the LEN type parameters must be
// passed as additional arguments to `index`.
if (mlir::isa<fir::BoxType>(refTy)) {
if (coorOperand.index() != numCoors - 1)
return emitOpError("len_param_index must be last argument");
if (getNumOperands() != 2)
return emitOpError("too many operands for len_param_index case");
}
if (eleTy != index.getOnType())
emitOpError(
"len_param_index type not compatible with reference type");
return mlir::success();
} else if (auto index = mlir::dyn_cast<fir::FieldIndexOp>(defOp)) {
if (eleTy != index.getOnType())
emitOpError("field_index type not compatible with reference type");
if (auto recTy = mlir::dyn_cast<fir::RecordType>(eleTy)) {
eleTy = recTy.getType(index.getFieldName());
continue;
}
return emitOpError("field_index not applied to !fir.type");
}
}
if (dimension) {
if (--dimension == 0)
eleTy = mlir::cast<fir::SequenceType>(eleTy).getElementType();
} else {
if (auto t = mlir::dyn_cast<mlir::TupleType>(eleTy)) {
// FIXME: Generally, we don't know which field of the tuple is being
// referred to unless the operand is a constant. Just assume everything
// is good in the tuple case for now.
return mlir::success();
} else if (auto t = mlir::dyn_cast<fir::RecordType>(eleTy)) {
// FIXME: This is the same as the tuple case.
return mlir::success();
} else if (auto t = mlir::dyn_cast<mlir::ComplexType>(eleTy)) {
eleTy = t.getElementType();
} else if (auto t = mlir::dyn_cast<fir::CharacterType>(eleTy)) {
if (t.getLen() == fir::CharacterType::singleton())
return emitOpError("cannot apply to character singleton");
eleTy = fir::CharacterType::getSingleton(t.getContext(), t.getFKind());
if (fir::unwrapRefType(getType()) != eleTy)
return emitOpError("character type mismatch");
} else {
return emitOpError("invalid parameters (too many)");
}
}
}
return mlir::success();
}
fir::CoordinateIndicesAdaptor fir::CoordinateOp::getIndices() {
return CoordinateIndicesAdaptor(getFieldIndicesAttr(), getCoor());
}
//===----------------------------------------------------------------------===//
// DispatchOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::DispatchOp::verify() {
// Check that pass_arg_pos is in range of actual operands. pass_arg_pos is
// unsigned so check for less than zero is not needed.
if (getPassArgPos() && *getPassArgPos() > (getArgOperands().size() - 1))
return emitOpError(
"pass_arg_pos must be smaller than the number of operands");
// Operand pointed by pass_arg_pos must have polymorphic type.
if (getPassArgPos() &&
!fir::isPolymorphicType(getArgOperands()[*getPassArgPos()].getType()))
return emitOpError("pass_arg_pos must be a polymorphic operand");
return mlir::success();
}
mlir::FunctionType fir::DispatchOp::getFunctionType() {
return mlir::FunctionType::get(getContext(), getOperandTypes(),
getResultTypes());
}
//===----------------------------------------------------------------------===//
// TypeInfoOp
//===----------------------------------------------------------------------===//
void fir::TypeInfoOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, fir::RecordType type,
fir::RecordType parentType,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
result.addRegion();
result.addRegion();
result.addAttribute(mlir::SymbolTable::getSymbolAttrName(),
builder.getStringAttr(type.getName()));
result.addAttribute(getTypeAttrName(result.name), mlir::TypeAttr::get(type));
if (parentType)
result.addAttribute(getParentTypeAttrName(result.name),
mlir::TypeAttr::get(parentType));
result.addAttributes(attrs);
}
llvm::LogicalResult fir::TypeInfoOp::verify() {
if (!getDispatchTable().empty())
for (auto &op : getDispatchTable().front().without_terminator())
if (!mlir::isa<fir::DTEntryOp>(op))
return op.emitOpError("dispatch table must contain dt_entry");
if (!mlir::isa<fir::RecordType>(getType()))
return emitOpError("type must be a fir.type");
if (getParentType() && !mlir::isa<fir::RecordType>(*getParentType()))
return emitOpError("parent_type must be a fir.type");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// EmboxOp
//===----------------------------------------------------------------------===//
// Conversions from reference types to box types must preserve volatility.
static llvm::LogicalResult
verifyEmboxOpVolatilityInvariants(mlir::Type memrefType,
mlir::Type resultType) {
if (!fir::useStrictVolatileVerification())
return mlir::success();
mlir::Type boxElementType =
llvm::TypeSwitch<mlir::Type, mlir::Type>(resultType)
.Case<fir::BoxType, fir::ClassType>(
[&](auto type) { return type.getEleTy(); })
.Default([&](mlir::Type type) { return type; });
// If the embox is simply wrapping a non-volatile type into a volatile box,
// we're not losing any volatility information.
if (boxElementType == memrefType) {
return mlir::success();
}
// Otherwise, the volatility of the input and result must match.
const bool volatilityMatches =
fir::isa_volatile_type(memrefType) == fir::isa_volatile_type(resultType);
return mlir::success(volatilityMatches);
}
llvm::LogicalResult fir::EmboxOp::verify() {
auto eleTy = fir::dyn_cast_ptrEleTy(getMemref().getType());
bool isArray = false;
if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(eleTy)) {
eleTy = seqTy.getEleTy();
isArray = true;
}
if (hasLenParams()) {
auto lenPs = numLenParams();
if (auto rt = mlir::dyn_cast<fir::RecordType>(eleTy)) {
if (lenPs != rt.getNumLenParams())
return emitOpError("number of LEN params does not correspond"
" to the !fir.type type");
} else if (auto strTy = mlir::dyn_cast<fir::CharacterType>(eleTy)) {
if (strTy.getLen() != fir::CharacterType::unknownLen())
return emitOpError("CHARACTER already has static LEN");
} else {
return emitOpError("LEN parameters require CHARACTER or derived type");
}
for (auto lp : getTypeparams())
if (!fir::isa_integer(lp.getType()))
return emitOpError("LEN parameters must be integral type");
}
if (getShape() && !isArray)
return emitOpError("shape must not be provided for a scalar");
if (getSlice() && !isArray)
return emitOpError("slice must not be provided for a scalar");
if (getSourceBox() && !mlir::isa<fir::ClassType>(getResult().getType()))
return emitOpError("source_box must be used with fir.class result type");
if (failed(verifyEmboxOpVolatilityInvariants(getMemref().getType(),
getResult().getType())))
return emitOpError(
"cannot convert between volatile and non-volatile types:")
<< " " << getMemref().getType() << " " << getResult().getType();
return mlir::success();
}
//===----------------------------------------------------------------------===//
// EmboxCharOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::EmboxCharOp::verify() {
auto eleTy = fir::dyn_cast_ptrEleTy(getMemref().getType());
if (!mlir::dyn_cast_or_null<fir::CharacterType>(eleTy))
return mlir::failure();
return mlir::success();
}
//===----------------------------------------------------------------------===//
// EmboxProcOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::EmboxProcOp::verify() {
// host bindings (optional) must be a reference to a tuple
if (auto h = getHost()) {
if (auto r = mlir::dyn_cast<fir::ReferenceType>(h.getType()))
if (mlir::isa<mlir::TupleType>(r.getEleTy()))
return mlir::success();
return mlir::failure();
}
return mlir::success();
}
//===----------------------------------------------------------------------===//
// TypeDescOp
//===----------------------------------------------------------------------===//
void fir::TypeDescOp::build(mlir::OpBuilder &, mlir::OperationState &result,
mlir::TypeAttr inty) {
result.addAttribute("in_type", inty);
result.addTypes(TypeDescType::get(inty.getValue()));
}
mlir::ParseResult fir::TypeDescOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::Type intype;
if (parser.parseType(intype))
return mlir::failure();
result.addAttribute("in_type", mlir::TypeAttr::get(intype));
mlir::Type restype = fir::TypeDescType::get(intype);
if (parser.addTypeToList(restype, result.types))
return mlir::failure();
return mlir::success();
}
void fir::TypeDescOp::print(mlir::OpAsmPrinter &p) {
p << ' ' << getOperation()->getAttr("in_type");
p.printOptionalAttrDict(getOperation()->getAttrs(), {"in_type"});
}
llvm::LogicalResult fir::TypeDescOp::verify() {
mlir::Type resultTy = getType();
if (auto tdesc = mlir::dyn_cast<fir::TypeDescType>(resultTy)) {
if (tdesc.getOfTy() != getInType())
return emitOpError("wrapped type mismatched");
return mlir::success();
}
return emitOpError("must be !fir.tdesc type");
}
//===----------------------------------------------------------------------===//
// GlobalOp
//===----------------------------------------------------------------------===//
mlir::Type fir::GlobalOp::resultType() {
return wrapAllocaResultType(getType());
}
mlir::ParseResult fir::GlobalOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
// Parse the optional linkage
llvm::StringRef linkage;
auto &builder = parser.getBuilder();
if (mlir::succeeded(parser.parseOptionalKeyword(&linkage))) {
if (fir::GlobalOp::verifyValidLinkage(linkage))
return mlir::failure();
mlir::StringAttr linkAttr = builder.getStringAttr(linkage);
result.addAttribute(fir::GlobalOp::getLinkNameAttrName(result.name),
linkAttr);
}
// Parse the name as a symbol reference attribute.
mlir::SymbolRefAttr nameAttr;
if (parser.parseAttribute(nameAttr,
fir::GlobalOp::getSymrefAttrName(result.name),
result.attributes))
return mlir::failure();
result.addAttribute(mlir::SymbolTable::getSymbolAttrName(),
nameAttr.getRootReference());
bool simpleInitializer = false;
if (mlir::succeeded(parser.parseOptionalLParen())) {
mlir::Attribute attr;
if (parser.parseAttribute(attr, getInitValAttrName(result.name),
result.attributes) ||
parser.parseRParen())
return mlir::failure();
simpleInitializer = true;
}
if (parser.parseOptionalAttrDict(result.attributes))
return mlir::failure();
if (succeeded(
parser.parseOptionalKeyword(getConstantAttrName(result.name)))) {
// if "constant" keyword then mark this as a constant, not a variable
result.addAttribute(getConstantAttrName(result.name),
builder.getUnitAttr());
}
if (succeeded(parser.parseOptionalKeyword(getTargetAttrName(result.name))))
result.addAttribute(getTargetAttrName(result.name), builder.getUnitAttr());
mlir::Type globalType;
if (parser.parseColonType(globalType))
return mlir::failure();
result.addAttribute(fir::GlobalOp::getTypeAttrName(result.name),
mlir::TypeAttr::get(globalType));
if (simpleInitializer) {
result.addRegion();
} else {
// Parse the optional initializer body.
auto parseResult =
parser.parseOptionalRegion(*result.addRegion(), /*arguments=*/{});
if (parseResult.has_value() && mlir::failed(*parseResult))
return mlir::failure();
}
return mlir::success();
}
void fir::GlobalOp::print(mlir::OpAsmPrinter &p) {
if (getLinkName())
p << ' ' << *getLinkName();
p << ' ';
p.printAttributeWithoutType(getSymrefAttr());
if (auto val = getValueOrNull())
p << '(' << val << ')';
// Print all other attributes that are not pretty printed here.
p.printOptionalAttrDict((*this)->getAttrs(), /*elideAttrs=*/{
getSymNameAttrName(), getSymrefAttrName(),
getTypeAttrName(), getConstantAttrName(),
getTargetAttrName(), getLinkNameAttrName(),
getInitValAttrName()});
if (getOperation()->getAttr(getConstantAttrName()))
p << " " << getConstantAttrName().strref();
if (getOperation()->getAttr(getTargetAttrName()))
p << " " << getTargetAttrName().strref();
p << " : ";
p.printType(getType());
if (hasInitializationBody()) {
p << ' ';
p.printRegion(getOperation()->getRegion(0),
/*printEntryBlockArgs=*/false,
/*printBlockTerminators=*/true);
}
}
void fir::GlobalOp::appendInitialValue(mlir::Operation *op) {
getBlock().getOperations().push_back(op);
}
void fir::GlobalOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, llvm::StringRef name,
bool isConstant, bool isTarget, mlir::Type type,
mlir::Attribute initialVal, mlir::StringAttr linkage,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
result.addRegion();
result.addAttribute(getTypeAttrName(result.name), mlir::TypeAttr::get(type));
result.addAttribute(mlir::SymbolTable::getSymbolAttrName(),
builder.getStringAttr(name));
result.addAttribute(getSymrefAttrName(result.name),
mlir::SymbolRefAttr::get(builder.getContext(), name));
if (isConstant)
result.addAttribute(getConstantAttrName(result.name),
builder.getUnitAttr());
if (isTarget)
result.addAttribute(getTargetAttrName(result.name), builder.getUnitAttr());
if (initialVal)
result.addAttribute(getInitValAttrName(result.name), initialVal);
if (linkage)
result.addAttribute(getLinkNameAttrName(result.name), linkage);
result.attributes.append(attrs.begin(), attrs.end());
}
void fir::GlobalOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, llvm::StringRef name,
mlir::Type type, mlir::Attribute initialVal,
mlir::StringAttr linkage,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
build(builder, result, name, /*isConstant=*/false, /*isTarget=*/false, type,
{}, linkage, attrs);
}
void fir::GlobalOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, llvm::StringRef name,
bool isConstant, bool isTarget, mlir::Type type,
mlir::StringAttr linkage,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
build(builder, result, name, isConstant, isTarget, type, {}, linkage, attrs);
}
void fir::GlobalOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, llvm::StringRef name,
mlir::Type type, mlir::StringAttr linkage,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
build(builder, result, name, /*isConstant=*/false, /*isTarget=*/false, type,
{}, linkage, attrs);
}
void fir::GlobalOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, llvm::StringRef name,
bool isConstant, bool isTarget, mlir::Type type,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
build(builder, result, name, isConstant, isTarget, type, mlir::StringAttr{},
attrs);
}
void fir::GlobalOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, llvm::StringRef name,
mlir::Type type,
llvm::ArrayRef<mlir::NamedAttribute> attrs) {
build(builder, result, name, /*isConstant=*/false, /*isTarget=*/false, type,
attrs);
}
mlir::ParseResult fir::GlobalOp::verifyValidLinkage(llvm::StringRef linkage) {
// Supporting only a subset of the LLVM linkage types for now
static const char *validNames[] = {"common", "internal", "linkonce",
"linkonce_odr", "weak"};
return mlir::success(llvm::is_contained(validNames, linkage));
}
//===----------------------------------------------------------------------===//
// GlobalLenOp
//===----------------------------------------------------------------------===//
mlir::ParseResult fir::GlobalLenOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
llvm::StringRef fieldName;
if (failed(parser.parseOptionalKeyword(&fieldName))) {
mlir::StringAttr fieldAttr;
if (parser.parseAttribute(fieldAttr,
fir::GlobalLenOp::getLenParamAttrName(),
result.attributes))
return mlir::failure();
} else {
result.addAttribute(fir::GlobalLenOp::getLenParamAttrName(),
parser.getBuilder().getStringAttr(fieldName));
}
mlir::IntegerAttr constant;
if (parser.parseComma() ||
parser.parseAttribute(constant, fir::GlobalLenOp::getIntAttrName(),
result.attributes))
return mlir::failure();
return mlir::success();
}
void fir::GlobalLenOp::print(mlir::OpAsmPrinter &p) {
p << ' ' << getOperation()->getAttr(fir::GlobalLenOp::getLenParamAttrName())
<< ", " << getOperation()->getAttr(fir::GlobalLenOp::getIntAttrName());
}
//===----------------------------------------------------------------------===//
// FieldIndexOp
//===----------------------------------------------------------------------===//
template <typename TY>
mlir::ParseResult parseFieldLikeOp(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
llvm::StringRef fieldName;
auto &builder = parser.getBuilder();
mlir::Type recty;
if (parser.parseOptionalKeyword(&fieldName) || parser.parseComma() ||
parser.parseType(recty))
return mlir::failure();
result.addAttribute(fir::FieldIndexOp::getFieldAttrName(),
builder.getStringAttr(fieldName));
if (!mlir::dyn_cast<fir::RecordType>(recty))
return mlir::failure();
result.addAttribute(fir::FieldIndexOp::getTypeAttrName(),
mlir::TypeAttr::get(recty));
if (!parser.parseOptionalLParen()) {
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> operands;
llvm::SmallVector<mlir::Type> types;
auto loc = parser.getNameLoc();
if (parser.parseOperandList(operands, mlir::OpAsmParser::Delimiter::None) ||
parser.parseColonTypeList(types) || parser.parseRParen() ||
parser.resolveOperands(operands, types, loc, result.operands))
return mlir::failure();
}
mlir::Type fieldType = TY::get(builder.getContext());
if (parser.addTypeToList(fieldType, result.types))
return mlir::failure();
return mlir::success();
}
mlir::ParseResult fir::FieldIndexOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseFieldLikeOp<fir::FieldType>(parser, result);
}
template <typename OP>
void printFieldLikeOp(mlir::OpAsmPrinter &p, OP &op) {
p << ' '
<< op.getOperation()
->template getAttrOfType<mlir::StringAttr>(
fir::FieldIndexOp::getFieldAttrName())
.getValue()
<< ", " << op.getOperation()->getAttr(fir::FieldIndexOp::getTypeAttrName());
if (op.getNumOperands()) {
p << '(';
p.printOperands(op.getTypeparams());
auto sep = ") : ";
for (auto op : op.getTypeparams()) {
p << sep;
if (op)
p.printType(op.getType());
else
p << "()";
sep = ", ";
}
}
}
void fir::FieldIndexOp::print(mlir::OpAsmPrinter &p) {
printFieldLikeOp(p, *this);
}
void fir::FieldIndexOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
llvm::StringRef fieldName, mlir::Type recTy,
mlir::ValueRange operands) {
result.addAttribute(getFieldAttrName(), builder.getStringAttr(fieldName));
result.addAttribute(getTypeAttrName(), mlir::TypeAttr::get(recTy));
result.addOperands(operands);
}
llvm::SmallVector<mlir::Attribute> fir::FieldIndexOp::getAttributes() {
llvm::SmallVector<mlir::Attribute> attrs;
attrs.push_back(getFieldIdAttr());
attrs.push_back(getOnTypeAttr());
return attrs;
}
//===----------------------------------------------------------------------===//
// InsertOnRangeOp
//===----------------------------------------------------------------------===//
static mlir::ParseResult
parseCustomRangeSubscript(mlir::OpAsmParser &parser,
mlir::DenseIntElementsAttr &coord) {
llvm::SmallVector<std::int64_t> lbounds;
llvm::SmallVector<std::int64_t> ubounds;
if (parser.parseKeyword("from") ||
parser.parseCommaSeparatedList(
mlir::AsmParser::Delimiter::Paren,
[&] { return parser.parseInteger(lbounds.emplace_back(0)); }) ||
parser.parseKeyword("to") ||
parser.parseCommaSeparatedList(mlir::AsmParser::Delimiter::Paren, [&] {
return parser.parseInteger(ubounds.emplace_back(0));
}))
return mlir::failure();
llvm::SmallVector<std::int64_t> zippedBounds;
for (auto zip : llvm::zip(lbounds, ubounds)) {
zippedBounds.push_back(std::get<0>(zip));
zippedBounds.push_back(std::get<1>(zip));
}
coord = mlir::Builder(parser.getContext()).getIndexTensorAttr(zippedBounds);
return mlir::success();
}
static void printCustomRangeSubscript(mlir::OpAsmPrinter &printer,
fir::InsertOnRangeOp op,
mlir::DenseIntElementsAttr coord) {
printer << "from (";
auto enumerate = llvm::enumerate(coord.getValues<std::int64_t>());
// Even entries are the lower bounds.
llvm::interleaveComma(
make_filter_range(
enumerate,
[](auto indexed_value) { return indexed_value.index() % 2 == 0; }),
printer, [&](auto indexed_value) { printer << indexed_value.value(); });
printer << ") to (";
// Odd entries are the upper bounds.
llvm::interleaveComma(
make_filter_range(
enumerate,
[](auto indexed_value) { return indexed_value.index() % 2 != 0; }),
printer, [&](auto indexed_value) { printer << indexed_value.value(); });
printer << ")";
}
/// Range bounds must be nonnegative, and the range must not be empty.
llvm::LogicalResult fir::InsertOnRangeOp::verify() {
if (fir::hasDynamicSize(getSeq().getType()))
return emitOpError("must have constant shape and size");
mlir::DenseIntElementsAttr coorAttr = getCoor();
if (coorAttr.size() < 2 || coorAttr.size() % 2 != 0)
return emitOpError("has uneven number of values in ranges");
bool rangeIsKnownToBeNonempty = false;
for (auto i = coorAttr.getValues<std::int64_t>().end(),
b = coorAttr.getValues<std::int64_t>().begin();
i != b;) {
int64_t ub = (*--i);
int64_t lb = (*--i);
if (lb < 0 || ub < 0)
return emitOpError("negative range bound");
if (rangeIsKnownToBeNonempty)
continue;
if (lb > ub)
return emitOpError("empty range");
rangeIsKnownToBeNonempty = lb < ub;
}
return mlir::success();
}
bool fir::InsertOnRangeOp::isFullRange() {
auto extents = getType().getShape();
mlir::DenseIntElementsAttr indexes = getCoor();
if (indexes.size() / 2 != static_cast<int64_t>(extents.size()))
return false;
auto cur_index = indexes.value_begin<int64_t>();
for (unsigned i = 0; i < indexes.size(); i += 2) {
if (*(cur_index++) != 0)
return false;
if (*(cur_index++) != extents[i / 2] - 1)
return false;
}
return true;
}
//===----------------------------------------------------------------------===//
// InsertValueOp
//===----------------------------------------------------------------------===//
static bool checkIsIntegerConstant(mlir::Attribute attr, std::int64_t conVal) {
if (auto iattr = mlir::dyn_cast<mlir::IntegerAttr>(attr))
return iattr.getInt() == conVal;
return false;
}
static bool isZero(mlir::Attribute a) { return checkIsIntegerConstant(a, 0); }
static bool isOne(mlir::Attribute a) { return checkIsIntegerConstant(a, 1); }
// Undo some complex patterns created in the front-end and turn them back into
// complex ops.
template <typename FltOp, typename CpxOp>
struct UndoComplexPattern : public mlir::RewritePattern {
UndoComplexPattern(mlir::MLIRContext *ctx)
: mlir::RewritePattern("fir.insert_value", 2, ctx) {}
llvm::LogicalResult
matchAndRewrite(mlir::Operation *op,
mlir::PatternRewriter &rewriter) const override {
auto insval = mlir::dyn_cast_or_null<fir::InsertValueOp>(op);
if (!insval || !mlir::isa<mlir::ComplexType>(insval.getType()))
return mlir::failure();
auto insval2 = mlir::dyn_cast_or_null<fir::InsertValueOp>(
insval.getAdt().getDefiningOp());
if (!insval2)
return mlir::failure();
auto binf = mlir::dyn_cast_or_null<FltOp>(insval.getVal().getDefiningOp());
auto binf2 =
mlir::dyn_cast_or_null<FltOp>(insval2.getVal().getDefiningOp());
if (!binf || !binf2 || insval.getCoor().size() != 1 ||
!isOne(insval.getCoor()[0]) || insval2.getCoor().size() != 1 ||
!isZero(insval2.getCoor()[0]))
return mlir::failure();
auto eai = mlir::dyn_cast_or_null<fir::ExtractValueOp>(
binf.getLhs().getDefiningOp());
auto ebi = mlir::dyn_cast_or_null<fir::ExtractValueOp>(
binf.getRhs().getDefiningOp());
auto ear = mlir::dyn_cast_or_null<fir::ExtractValueOp>(
binf2.getLhs().getDefiningOp());
auto ebr = mlir::dyn_cast_or_null<fir::ExtractValueOp>(
binf2.getRhs().getDefiningOp());
if (!eai || !ebi || !ear || !ebr || ear.getAdt() != eai.getAdt() ||
ebr.getAdt() != ebi.getAdt() || eai.getCoor().size() != 1 ||
!isOne(eai.getCoor()[0]) || ebi.getCoor().size() != 1 ||
!isOne(ebi.getCoor()[0]) || ear.getCoor().size() != 1 ||
!isZero(ear.getCoor()[0]) || ebr.getCoor().size() != 1 ||
!isZero(ebr.getCoor()[0]))
return mlir::failure();
rewriter.replaceOpWithNewOp<CpxOp>(op, ear.getAdt(), ebr.getAdt());
return mlir::success();
}
};
void fir::InsertValueOp::getCanonicalizationPatterns(
mlir::RewritePatternSet &results, mlir::MLIRContext *context) {
results.insert<UndoComplexPattern<mlir::arith::AddFOp, fir::AddcOp>,
UndoComplexPattern<mlir::arith::SubFOp, fir::SubcOp>>(context);
}
//===----------------------------------------------------------------------===//
// IterWhileOp
//===----------------------------------------------------------------------===//
void fir::IterWhileOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Value lb,
mlir::Value ub, mlir::Value step,
mlir::Value iterate, bool finalCountValue,
mlir::ValueRange iterArgs,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
result.addOperands({lb, ub, step, iterate});
if (finalCountValue) {
result.addTypes(builder.getIndexType());
result.addAttribute(getFinalValueAttrNameStr(), builder.getUnitAttr());
}
result.addTypes(iterate.getType());
result.addOperands(iterArgs);
for (auto v : iterArgs)
result.addTypes(v.getType());
mlir::Region *bodyRegion = result.addRegion();
bodyRegion->push_back(new mlir::Block{});
bodyRegion->front().addArgument(builder.getIndexType(), result.location);
bodyRegion->front().addArgument(iterate.getType(), result.location);
bodyRegion->front().addArguments(
iterArgs.getTypes(),
llvm::SmallVector<mlir::Location>(iterArgs.size(), result.location));
result.addAttributes(attributes);
}
mlir::ParseResult fir::IterWhileOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
auto &builder = parser.getBuilder();
mlir::OpAsmParser::Argument inductionVariable, iterateVar;
mlir::OpAsmParser::UnresolvedOperand lb, ub, step, iterateInput;
if (parser.parseLParen() || parser.parseArgument(inductionVariable) ||
parser.parseEqual())
return mlir::failure();
// Parse loop bounds.
auto indexType = builder.getIndexType();
auto i1Type = builder.getIntegerType(1);
if (parser.parseOperand(lb) ||
parser.resolveOperand(lb, indexType, result.operands) ||
parser.parseKeyword("to") || parser.parseOperand(ub) ||
parser.resolveOperand(ub, indexType, result.operands) ||
parser.parseKeyword("step") || parser.parseOperand(step) ||
parser.parseRParen() ||
parser.resolveOperand(step, indexType, result.operands) ||
parser.parseKeyword("and") || parser.parseLParen() ||
parser.parseArgument(iterateVar) || parser.parseEqual() ||
parser.parseOperand(iterateInput) || parser.parseRParen() ||
parser.resolveOperand(iterateInput, i1Type, result.operands))
return mlir::failure();
// Parse the initial iteration arguments.
auto prependCount = false;
// Induction variable.
llvm::SmallVector<mlir::OpAsmParser::Argument> regionArgs;
regionArgs.push_back(inductionVariable);
regionArgs.push_back(iterateVar);
if (succeeded(parser.parseOptionalKeyword("iter_args"))) {
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> operands;
llvm::SmallVector<mlir::Type> regionTypes;
// Parse assignment list and results type list.
if (parser.parseAssignmentList(regionArgs, operands) ||
parser.parseArrowTypeList(regionTypes))
return mlir::failure();
if (regionTypes.size() == operands.size() + 2)
prependCount = true;
llvm::ArrayRef<mlir::Type> resTypes = regionTypes;
resTypes = prependCount ? resTypes.drop_front(2) : resTypes;
// Resolve input operands.
for (auto operandType : llvm::zip(operands, resTypes))
if (parser.resolveOperand(std::get<0>(operandType),
std::get<1>(operandType), result.operands))
return mlir::failure();
if (prependCount) {
result.addTypes(regionTypes);
} else {
result.addTypes(i1Type);
result.addTypes(resTypes);
}
} else if (succeeded(parser.parseOptionalArrow())) {
llvm::SmallVector<mlir::Type> typeList;
if (parser.parseLParen() || parser.parseTypeList(typeList) ||
parser.parseRParen())
return mlir::failure();
// Type list must be "(index, i1)".
if (typeList.size() != 2 || !mlir::isa<mlir::IndexType>(typeList[0]) ||
!typeList[1].isSignlessInteger(1))
return mlir::failure();
result.addTypes(typeList);
prependCount = true;
} else {
result.addTypes(i1Type);
}
if (parser.parseOptionalAttrDictWithKeyword(result.attributes))
return mlir::failure();
llvm::SmallVector<mlir::Type> argTypes;
// Induction variable (hidden)
if (prependCount)
result.addAttribute(IterWhileOp::getFinalValueAttrNameStr(),
builder.getUnitAttr());
else
argTypes.push_back(indexType);
// Loop carried variables (including iterate)
argTypes.append(result.types.begin(), result.types.end());
// Parse the body region.
auto *body = result.addRegion();
if (regionArgs.size() != argTypes.size())
return parser.emitError(
parser.getNameLoc(),
"mismatch in number of loop-carried values and defined values");
for (size_t i = 0, e = regionArgs.size(); i != e; ++i)
regionArgs[i].type = argTypes[i];
if (parser.parseRegion(*body, regionArgs))
return mlir::failure();
fir::IterWhileOp::ensureTerminator(*body, builder, result.location);
return mlir::success();
}
llvm::LogicalResult fir::IterWhileOp::verify() {
// Check that the body defines as single block argument for the induction
// variable.
auto *body = getBody();
if (!body->getArgument(1).getType().isInteger(1))
return emitOpError(
"expected body second argument to be an index argument for "
"the induction variable");
if (!body->getArgument(0).getType().isIndex())
return emitOpError(
"expected body first argument to be an index argument for "
"the induction variable");
auto opNumResults = getNumResults();
if (getFinalValue()) {
// Result type must be "(index, i1, ...)".
if (!mlir::isa<mlir::IndexType>(getResult(0).getType()))
return emitOpError("result #0 expected to be index");
if (!getResult(1).getType().isSignlessInteger(1))
return emitOpError("result #1 expected to be i1");
opNumResults--;
} else {
// iterate_while always returns the early exit induction value.
// Result type must be "(i1, ...)"
if (!getResult(0).getType().isSignlessInteger(1))
return emitOpError("result #0 expected to be i1");
}
if (opNumResults == 0)
return mlir::failure();
if (getNumIterOperands() != opNumResults)
return emitOpError(
"mismatch in number of loop-carried values and defined values");
if (getNumRegionIterArgs() != opNumResults)
return emitOpError(
"mismatch in number of basic block args and defined values");
auto iterOperands = getIterOperands();
auto iterArgs = getRegionIterArgs();
auto opResults = getFinalValue() ? getResults().drop_front() : getResults();
unsigned i = 0u;
for (auto e : llvm::zip(iterOperands, iterArgs, opResults)) {
if (std::get<0>(e).getType() != std::get<2>(e).getType())
return emitOpError() << "types mismatch between " << i
<< "th iter operand and defined value";
if (std::get<1>(e).getType() != std::get<2>(e).getType())
return emitOpError() << "types mismatch between " << i
<< "th iter region arg and defined value";
i++;
}
return mlir::success();
}
void fir::IterWhileOp::print(mlir::OpAsmPrinter &p) {
p << " (" << getInductionVar() << " = " << getLowerBound() << " to "
<< getUpperBound() << " step " << getStep() << ") and (";
assert(hasIterOperands());
auto regionArgs = getRegionIterArgs();
auto operands = getIterOperands();
p << regionArgs.front() << " = " << *operands.begin() << ")";
if (regionArgs.size() > 1) {
p << " iter_args(";
llvm::interleaveComma(
llvm::zip(regionArgs.drop_front(), operands.drop_front()), p,
[&](auto it) { p << std::get<0>(it) << " = " << std::get<1>(it); });
p << ") -> (";
llvm::interleaveComma(
llvm::drop_begin(getResultTypes(), getFinalValue() ? 0 : 1), p);
p << ")";
} else if (getFinalValue()) {
p << " -> (" << getResultTypes() << ')';
}
p.printOptionalAttrDictWithKeyword((*this)->getAttrs(),
{getFinalValueAttrNameStr()});
p << ' ';
p.printRegion(getRegion(), /*printEntryBlockArgs=*/false,
/*printBlockTerminators=*/true);
}
llvm::SmallVector<mlir::Region *> fir::IterWhileOp::getLoopRegions() {
return {&getRegion()};
}
mlir::BlockArgument fir::IterWhileOp::iterArgToBlockArg(mlir::Value iterArg) {
for (auto i : llvm::enumerate(getInitArgs()))
if (iterArg == i.value())
return getRegion().front().getArgument(i.index() + 1);
return {};
}
void fir::IterWhileOp::resultToSourceOps(
llvm::SmallVectorImpl<mlir::Value> &results, unsigned resultNum) {
auto oper = getFinalValue() ? resultNum + 1 : resultNum;
auto *term = getRegion().front().getTerminator();
if (oper < term->getNumOperands())
results.push_back(term->getOperand(oper));
}
mlir::Value fir::IterWhileOp::blockArgToSourceOp(unsigned blockArgNum) {
if (blockArgNum > 0 && blockArgNum <= getInitArgs().size())
return getInitArgs()[blockArgNum - 1];
return {};
}
std::optional<llvm::MutableArrayRef<mlir::OpOperand>>
fir::IterWhileOp::getYieldedValuesMutable() {
auto *term = getRegion().front().getTerminator();
return getFinalValue() ? term->getOpOperands().drop_front()
: term->getOpOperands();
}
//===----------------------------------------------------------------------===//
// LenParamIndexOp
//===----------------------------------------------------------------------===//
mlir::ParseResult fir::LenParamIndexOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseFieldLikeOp<fir::LenType>(parser, result);
}
void fir::LenParamIndexOp::print(mlir::OpAsmPrinter &p) {
printFieldLikeOp(p, *this);
}
void fir::LenParamIndexOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
llvm::StringRef fieldName, mlir::Type recTy,
mlir::ValueRange operands) {
result.addAttribute(getFieldAttrName(), builder.getStringAttr(fieldName));
result.addAttribute(getTypeAttrName(), mlir::TypeAttr::get(recTy));
result.addOperands(operands);
}
llvm::SmallVector<mlir::Attribute> fir::LenParamIndexOp::getAttributes() {
llvm::SmallVector<mlir::Attribute> attrs;
attrs.push_back(getFieldIdAttr());
attrs.push_back(getOnTypeAttr());
return attrs;
}
//===----------------------------------------------------------------------===//
// LoadOp
//===----------------------------------------------------------------------===//
void fir::LoadOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::Value refVal) {
if (!refVal) {
mlir::emitError(result.location, "LoadOp has null argument");
return;
}
auto eleTy = fir::dyn_cast_ptrEleTy(refVal.getType());
if (!eleTy) {
mlir::emitError(result.location, "not a memory reference type");
return;
}
build(builder, result, eleTy, refVal);
}
void fir::LoadOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::Type resTy, mlir::Value refVal) {
if (!refVal) {
mlir::emitError(result.location, "LoadOp has null argument");
return;
}
result.addOperands(refVal);
result.addTypes(resTy);
}
mlir::ParseResult fir::LoadOp::getElementOf(mlir::Type &ele, mlir::Type ref) {
if ((ele = fir::dyn_cast_ptrEleTy(ref)))
return mlir::success();
return mlir::failure();
}
mlir::ParseResult fir::LoadOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::Type type;
mlir::OpAsmParser::UnresolvedOperand oper;
if (parser.parseOperand(oper) ||
parser.parseOptionalAttrDict(result.attributes) ||
parser.parseColonType(type) ||
parser.resolveOperand(oper, type, result.operands))
return mlir::failure();
mlir::Type eleTy;
if (fir::LoadOp::getElementOf(eleTy, type) ||
parser.addTypeToList(eleTy, result.types))
return mlir::failure();
return mlir::success();
}
void fir::LoadOp::print(mlir::OpAsmPrinter &p) {
p << ' ';
p.printOperand(getMemref());
p.printOptionalAttrDict(getOperation()->getAttrs(), {});
p << " : " << getMemref().getType();
}
void fir::LoadOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
effects.emplace_back(mlir::MemoryEffects::Read::get(), &getMemrefMutable(),
mlir::SideEffects::DefaultResource::get());
addVolatileMemoryEffects({getMemref().getType()}, effects);
}
//===----------------------------------------------------------------------===//
// DoLoopOp
//===----------------------------------------------------------------------===//
void fir::DoLoopOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Value lb,
mlir::Value ub, mlir::Value step, bool unordered,
bool finalCountValue, mlir::ValueRange iterArgs,
mlir::ValueRange reduceOperands,
llvm::ArrayRef<mlir::Attribute> reduceAttrs,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
result.addOperands({lb, ub, step});
result.addOperands(reduceOperands);
result.addOperands(iterArgs);
result.addAttribute(getOperandSegmentSizeAttr(),
builder.getDenseI32ArrayAttr(
{1, 1, 1, static_cast<int32_t>(reduceOperands.size()),
static_cast<int32_t>(iterArgs.size())}));
if (finalCountValue) {
result.addTypes(builder.getIndexType());
result.addAttribute(getFinalValueAttrName(result.name),
builder.getUnitAttr());
}
for (auto v : iterArgs)
result.addTypes(v.getType());
mlir::Region *bodyRegion = result.addRegion();
bodyRegion->push_back(new mlir::Block{});
if (iterArgs.empty() && !finalCountValue)
fir::DoLoopOp::ensureTerminator(*bodyRegion, builder, result.location);
bodyRegion->front().addArgument(builder.getIndexType(), result.location);
bodyRegion->front().addArguments(
iterArgs.getTypes(),
llvm::SmallVector<mlir::Location>(iterArgs.size(), result.location));
if (unordered)
result.addAttribute(getUnorderedAttrName(result.name),
builder.getUnitAttr());
if (!reduceAttrs.empty())
result.addAttribute(getReduceAttrsAttrName(result.name),
builder.getArrayAttr(reduceAttrs));
result.addAttributes(attributes);
}
mlir::ParseResult fir::DoLoopOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
auto &builder = parser.getBuilder();
mlir::OpAsmParser::Argument inductionVariable;
mlir::OpAsmParser::UnresolvedOperand lb, ub, step;
// Parse the induction variable followed by '='.
if (parser.parseArgument(inductionVariable) || parser.parseEqual())
return mlir::failure();
// Parse loop bounds.
auto indexType = builder.getIndexType();
if (parser.parseOperand(lb) ||
parser.resolveOperand(lb, indexType, result.operands) ||
parser.parseKeyword("to") || parser.parseOperand(ub) ||
parser.resolveOperand(ub, indexType, result.operands) ||
parser.parseKeyword("step") || parser.parseOperand(step) ||
parser.resolveOperand(step, indexType, result.operands))
return mlir::failure();
if (mlir::succeeded(parser.parseOptionalKeyword("unordered")))
result.addAttribute("unordered", builder.getUnitAttr());
// Parse the reduction arguments.
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> reduceOperands;
llvm::SmallVector<mlir::Type> reduceArgTypes;
if (succeeded(parser.parseOptionalKeyword("reduce"))) {
// Parse reduction attributes and variables.
llvm::SmallVector<ReduceAttr> attributes;
if (failed(parser.parseCommaSeparatedList(
mlir::AsmParser::Delimiter::Paren, [&]() {
if (parser.parseAttribute(attributes.emplace_back()) ||
parser.parseArrow() ||
parser.parseOperand(reduceOperands.emplace_back()) ||
parser.parseColonType(reduceArgTypes.emplace_back()))
return mlir::failure();
return mlir::success();
})))
return mlir::failure();
// Resolve input operands.
for (auto operand_type : llvm::zip(reduceOperands, reduceArgTypes))
if (parser.resolveOperand(std::get<0>(operand_type),
std::get<1>(operand_type), result.operands))
return mlir::failure();
llvm::SmallVector<mlir::Attribute> arrayAttr(attributes.begin(),
attributes.end());
result.addAttribute(getReduceAttrsAttrName(result.name),
builder.getArrayAttr(arrayAttr));
}
// Parse the optional initial iteration arguments.
llvm::SmallVector<mlir::OpAsmParser::Argument> regionArgs;
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> iterOperands;
llvm::SmallVector<mlir::Type> argTypes;
bool prependCount = false;
regionArgs.push_back(inductionVariable);
if (succeeded(parser.parseOptionalKeyword("iter_args"))) {
// Parse assignment list and results type list.
if (parser.parseAssignmentList(regionArgs, iterOperands) ||
parser.parseArrowTypeList(result.types))
return mlir::failure();
if (result.types.size() == iterOperands.size() + 1)
prependCount = true;
// Resolve input operands.
llvm::ArrayRef<mlir::Type> resTypes = result.types;
for (auto operand_type : llvm::zip(
iterOperands, prependCount ? resTypes.drop_front() : resTypes))
if (parser.resolveOperand(std::get<0>(operand_type),
std::get<1>(operand_type), result.operands))
return mlir::failure();
} else if (succeeded(parser.parseOptionalArrow())) {
if (parser.parseKeyword("index"))
return mlir::failure();
result.types.push_back(indexType);
prependCount = true;
}
// Set the operandSegmentSizes attribute
result.addAttribute(getOperandSegmentSizeAttr(),
builder.getDenseI32ArrayAttr(
{1, 1, 1, static_cast<int32_t>(reduceOperands.size()),
static_cast<int32_t>(iterOperands.size())}));
if (parser.parseOptionalAttrDictWithKeyword(result.attributes))
return mlir::failure();
// Induction variable.
if (prependCount)
result.addAttribute(DoLoopOp::getFinalValueAttrName(result.name),
builder.getUnitAttr());
else
argTypes.push_back(indexType);
// Loop carried variables
argTypes.append(result.types.begin(), result.types.end());
// Parse the body region.
auto *body = result.addRegion();
if (regionArgs.size() != argTypes.size())
return parser.emitError(
parser.getNameLoc(),
"mismatch in number of loop-carried values and defined values");
for (size_t i = 0, e = regionArgs.size(); i != e; ++i)
regionArgs[i].type = argTypes[i];
if (parser.parseRegion(*body, regionArgs))
return mlir::failure();
DoLoopOp::ensureTerminator(*body, builder, result.location);
return mlir::success();
}
fir::DoLoopOp fir::getForInductionVarOwner(mlir::Value val) {
auto ivArg = mlir::dyn_cast<mlir::BlockArgument>(val);
if (!ivArg)
return {};
assert(ivArg.getOwner() && "unlinked block argument");
auto *containingInst = ivArg.getOwner()->getParentOp();
return mlir::dyn_cast_or_null<fir::DoLoopOp>(containingInst);
}
// Lifted from loop.loop
llvm::LogicalResult fir::DoLoopOp::verify() {
// Check that the body defines as single block argument for the induction
// variable.
auto *body = getBody();
if (!body->getArgument(0).getType().isIndex())
return emitOpError(
"expected body first argument to be an index argument for "
"the induction variable");
auto opNumResults = getNumResults();
if (opNumResults == 0)
return mlir::success();
if (getFinalValue()) {
if (getUnordered())
return emitOpError("unordered loop has no final value");
opNumResults--;
}
if (getNumIterOperands() != opNumResults)
return emitOpError(
"mismatch in number of loop-carried values and defined values");
if (getNumRegionIterArgs() != opNumResults)
return emitOpError(
"mismatch in number of basic block args and defined values");
auto iterOperands = getIterOperands();
auto iterArgs = getRegionIterArgs();
auto opResults = getFinalValue() ? getResults().drop_front() : getResults();
unsigned i = 0u;
for (auto e : llvm::zip(iterOperands, iterArgs, opResults)) {
if (std::get<0>(e).getType() != std::get<2>(e).getType())
return emitOpError() << "types mismatch between " << i
<< "th iter operand and defined value";
if (std::get<1>(e).getType() != std::get<2>(e).getType())
return emitOpError() << "types mismatch between " << i
<< "th iter region arg and defined value";
i++;
}
auto reduceAttrs = getReduceAttrsAttr();
if (getNumReduceOperands() != (reduceAttrs ? reduceAttrs.size() : 0))
return emitOpError(
"mismatch in number of reduction variables and reduction attributes");
return mlir::success();
}
void fir::DoLoopOp::print(mlir::OpAsmPrinter &p) {
bool printBlockTerminators = false;
p << ' ' << getInductionVar() << " = " << getLowerBound() << " to "
<< getUpperBound() << " step " << getStep();
if (getUnordered())
p << " unordered";
if (hasReduceOperands()) {
p << " reduce(";
auto attrs = getReduceAttrsAttr();
auto operands = getReduceOperands();
llvm::interleaveComma(llvm::zip(attrs, operands), p, [&](auto it) {
p << std::get<0>(it) << " -> " << std::get<1>(it) << " : "
<< std::get<1>(it).getType();
});
p << ')';
printBlockTerminators = true;
}
if (hasIterOperands()) {
p << " iter_args(";
auto regionArgs = getRegionIterArgs();
auto operands = getIterOperands();
llvm::interleaveComma(llvm::zip(regionArgs, operands), p, [&](auto it) {
p << std::get<0>(it) << " = " << std::get<1>(it);
});
p << ") -> (" << getResultTypes() << ')';
printBlockTerminators = true;
} else if (getFinalValue()) {
p << " -> " << getResultTypes();
printBlockTerminators = true;
}
p.printOptionalAttrDictWithKeyword(
(*this)->getAttrs(),
{"unordered", "finalValue", "reduceAttrs", "operandSegmentSizes"});
p << ' ';
p.printRegion(getRegion(), /*printEntryBlockArgs=*/false,
printBlockTerminators);
}
llvm::SmallVector<mlir::Region *> fir::DoLoopOp::getLoopRegions() {
return {&getRegion()};
}
/// Translate a value passed as an iter_arg to the corresponding block
/// argument in the body of the loop.
mlir::BlockArgument fir::DoLoopOp::iterArgToBlockArg(mlir::Value iterArg) {
for (auto i : llvm::enumerate(getInitArgs()))
if (iterArg == i.value())
return getRegion().front().getArgument(i.index() + 1);
return {};
}
/// Translate the result vector (by index number) to the corresponding value
/// to the `fir.result` Op.
void fir::DoLoopOp::resultToSourceOps(
llvm::SmallVectorImpl<mlir::Value> &results, unsigned resultNum) {
auto oper = getFinalValue() ? resultNum + 1 : resultNum;
auto *term = getRegion().front().getTerminator();
if (oper < term->getNumOperands())
results.push_back(term->getOperand(oper));
}
/// Translate the block argument (by index number) to the corresponding value
/// passed as an iter_arg to the parent DoLoopOp.
mlir::Value fir::DoLoopOp::blockArgToSourceOp(unsigned blockArgNum) {
if (blockArgNum > 0 && blockArgNum <= getInitArgs().size())
return getInitArgs()[blockArgNum - 1];
return {};
}
std::optional<llvm::MutableArrayRef<mlir::OpOperand>>
fir::DoLoopOp::getYieldedValuesMutable() {
auto *term = getRegion().front().getTerminator();
return getFinalValue() ? term->getOpOperands().drop_front()
: term->getOpOperands();
}
//===----------------------------------------------------------------------===//
// DTEntryOp
//===----------------------------------------------------------------------===//
mlir::ParseResult fir::DTEntryOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
llvm::StringRef methodName;
// allow `methodName` or `"methodName"`
if (failed(parser.parseOptionalKeyword(&methodName))) {
mlir::StringAttr methodAttr;
if (parser.parseAttribute(methodAttr, getMethodAttrName(result.name),
result.attributes))
return mlir::failure();
} else {
result.addAttribute(getMethodAttrName(result.name),
parser.getBuilder().getStringAttr(methodName));
}
mlir::SymbolRefAttr calleeAttr;
if (parser.parseComma() ||
parser.parseAttribute(calleeAttr, fir::DTEntryOp::getProcAttrNameStr(),
result.attributes))
return mlir::failure();
return mlir::success();
}
void fir::DTEntryOp::print(mlir::OpAsmPrinter &p) {
p << ' ' << getMethodAttr() << ", " << getProcAttr();
}
//===----------------------------------------------------------------------===//
// ReboxOp
//===----------------------------------------------------------------------===//
/// Get the scalar type related to a fir.box type.
/// Example: return f32 for !fir.box<!fir.heap<!fir.array<?x?xf32>>.
static mlir::Type getBoxScalarEleTy(mlir::Type boxTy) {
auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(boxTy);
if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(eleTy))
return seqTy.getEleTy();
return eleTy;
}
/// Test if \p t1 and \p t2 are compatible character types (if they can
/// represent the same type at runtime).
static bool areCompatibleCharacterTypes(mlir::Type t1, mlir::Type t2) {
auto c1 = mlir::dyn_cast<fir::CharacterType>(t1);
auto c2 = mlir::dyn_cast<fir::CharacterType>(t2);
if (!c1 || !c2)
return false;
if (c1.hasDynamicLen() || c2.hasDynamicLen())
return true;
return c1.getLen() == c2.getLen();
}
llvm::LogicalResult fir::ReboxOp::verify() {
auto inputBoxTy = getBox().getType();
if (fir::isa_unknown_size_box(inputBoxTy))
return emitOpError("box operand must not have unknown rank or type");
auto outBoxTy = getType();
if (fir::isa_unknown_size_box(outBoxTy))
return emitOpError("result type must not have unknown rank or type");
auto inputRank = fir::getBoxRank(inputBoxTy);
auto inputEleTy = getBoxScalarEleTy(inputBoxTy);
auto outRank = fir::getBoxRank(outBoxTy);
auto outEleTy = getBoxScalarEleTy(outBoxTy);
if (auto sliceVal = getSlice()) {
// Slicing case
if (mlir::cast<fir::SliceType>(sliceVal.getType()).getRank() != inputRank)
return emitOpError("slice operand rank must match box operand rank");
if (auto shapeVal = getShape()) {
if (auto shiftTy = mlir::dyn_cast<fir::ShiftType>(shapeVal.getType())) {
if (shiftTy.getRank() != inputRank)
return emitOpError("shape operand and input box ranks must match "
"when there is a slice");
} else {
return emitOpError("shape operand must absent or be a fir.shift "
"when there is a slice");
}
}
if (auto sliceOp = sliceVal.getDefiningOp()) {
auto slicedRank = mlir::cast<fir::SliceOp>(sliceOp).getOutRank();
if (slicedRank != outRank)
return emitOpError("result type rank and rank after applying slice "
"operand must match");
}
} else {
// Reshaping case
unsigned shapeRank = inputRank;
if (auto shapeVal = getShape()) {
auto ty = shapeVal.getType();
if (auto shapeTy = mlir::dyn_cast<fir::ShapeType>(ty)) {
shapeRank = shapeTy.getRank();
} else if (auto shapeShiftTy = mlir::dyn_cast<fir::ShapeShiftType>(ty)) {
shapeRank = shapeShiftTy.getRank();
} else {
auto shiftTy = mlir::cast<fir::ShiftType>(ty);
shapeRank = shiftTy.getRank();
if (shapeRank != inputRank)
return emitOpError("shape operand and input box ranks must match "
"when the shape is a fir.shift");
}
}
if (shapeRank != outRank)
return emitOpError("result type and shape operand ranks must match");
}
if (inputEleTy != outEleTy) {
// TODO: check that outBoxTy is a parent type of inputBoxTy for derived
// types.
// Character input and output types with constant length may be different if
// there is a substring in the slice, otherwise, they must match. If any of
// the types is a character with dynamic length, the other type can be any
// character type.
const bool typeCanMismatch =
mlir::isa<fir::RecordType>(inputEleTy) ||
mlir::isa<mlir::NoneType>(outEleTy) ||
(mlir::isa<mlir::NoneType>(inputEleTy) &&
mlir::isa<fir::RecordType>(outEleTy)) ||
(getSlice() && mlir::isa<fir::CharacterType>(inputEleTy)) ||
(getSlice() && fir::isa_complex(inputEleTy) &&
mlir::isa<mlir::FloatType>(outEleTy)) ||
areCompatibleCharacterTypes(inputEleTy, outEleTy);
if (!typeCanMismatch)
return emitOpError(
"op input and output element types must match for intrinsic types");
}
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ReboxAssumedRankOp
//===----------------------------------------------------------------------===//
static bool areCompatibleAssumedRankElementType(mlir::Type inputEleTy,
mlir::Type outEleTy) {
if (inputEleTy == outEleTy)
return true;
// Output is unlimited polymorphic -> output dynamic type is the same as input
// type.
if (mlir::isa<mlir::NoneType>(outEleTy))
return true;
// Output/Input are derived types. Assuming input extends output type, output
// dynamic type is the output static type, unless output is polymorphic.
if (mlir::isa<fir::RecordType>(inputEleTy) &&
mlir::isa<fir::RecordType>(outEleTy))
return true;
if (areCompatibleCharacterTypes(inputEleTy, outEleTy))
return true;
return false;
}
llvm::LogicalResult fir::ReboxAssumedRankOp::verify() {
mlir::Type inputType = getBox().getType();
if (!mlir::isa<fir::BaseBoxType>(inputType) && !fir::isBoxAddress(inputType))
return emitOpError("input must be a box or box address");
mlir::Type inputEleTy =
mlir::cast<fir::BaseBoxType>(fir::unwrapRefType(inputType))
.unwrapInnerType();
mlir::Type outEleTy =
mlir::cast<fir::BaseBoxType>(getType()).unwrapInnerType();
if (!areCompatibleAssumedRankElementType(inputEleTy, outEleTy))
return emitOpError("input and output element types are incompatible");
return mlir::success();
}
void fir::ReboxAssumedRankOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
mlir::OpOperand &inputBox = getBoxMutable();
if (fir::isBoxAddress(inputBox.get().getType()))
effects.emplace_back(mlir::MemoryEffects::Read::get(), &inputBox,
mlir::SideEffects::DefaultResource::get());
}
//===----------------------------------------------------------------------===//
// ResultOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ResultOp::verify() {
auto *parentOp = (*this)->getParentOp();
auto results = parentOp->getResults();
auto operands = (*this)->getOperands();
if (parentOp->getNumResults() != getNumOperands())
return emitOpError() << "parent of result must have same arity";
for (auto e : llvm::zip(results, operands))
if (std::get<0>(e).getType() != std::get<1>(e).getType())
return emitOpError() << "types mismatch between result op and its parent";
return mlir::success();
}
//===----------------------------------------------------------------------===//
// SaveResultOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::SaveResultOp::verify() {
auto resultType = getValue().getType();
if (resultType != fir::dyn_cast_ptrEleTy(getMemref().getType()))
return emitOpError("value type must match memory reference type");
if (fir::isa_unknown_size_box(resultType))
return emitOpError("cannot save !fir.box of unknown rank or type");
if (mlir::isa<fir::BoxType>(resultType)) {
if (getShape() || !getTypeparams().empty())
return emitOpError(
"must not have shape or length operands if the value is a fir.box");
return mlir::success();
}
// fir.record or fir.array case.
unsigned shapeTyRank = 0;
if (auto shapeVal = getShape()) {
auto shapeTy = shapeVal.getType();
if (auto s = mlir::dyn_cast<fir::ShapeType>(shapeTy))
shapeTyRank = s.getRank();
else
shapeTyRank = mlir::cast<fir::ShapeShiftType>(shapeTy).getRank();
}
auto eleTy = resultType;
if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(resultType)) {
if (seqTy.getDimension() != shapeTyRank)
emitOpError("shape operand must be provided and have the value rank "
"when the value is a fir.array");
eleTy = seqTy.getEleTy();
} else {
if (shapeTyRank != 0)
emitOpError(
"shape operand should only be provided if the value is a fir.array");
}
if (auto recTy = mlir::dyn_cast<fir::RecordType>(eleTy)) {
if (recTy.getNumLenParams() != getTypeparams().size())
emitOpError("length parameters number must match with the value type "
"length parameters");
} else if (auto charTy = mlir::dyn_cast<fir::CharacterType>(eleTy)) {
if (getTypeparams().size() > 1)
emitOpError("no more than one length parameter must be provided for "
"character value");
} else {
if (!getTypeparams().empty())
emitOpError("length parameters must not be provided for this value type");
}
return mlir::success();
}
//===----------------------------------------------------------------------===//
// IntegralSwitchTerminator
//===----------------------------------------------------------------------===//
static constexpr llvm::StringRef getCompareOffsetAttr() {
return "compare_operand_offsets";
}
static constexpr llvm::StringRef getTargetOffsetAttr() {
return "target_operand_offsets";
}
template <typename OpT>
static llvm::LogicalResult verifyIntegralSwitchTerminator(OpT op) {
if (!mlir::isa<mlir::IntegerType, mlir::IndexType, fir::IntegerType>(
op.getSelector().getType()))
return op.emitOpError("must be an integer");
auto cases =
op->template getAttrOfType<mlir::ArrayAttr>(op.getCasesAttr()).getValue();
auto count = op.getNumDest();
if (count == 0)
return op.emitOpError("must have at least one successor");
if (op.getNumConditions() != count)
return op.emitOpError("number of cases and targets don't match");
if (op.targetOffsetSize() != count)
return op.emitOpError("incorrect number of successor operand groups");
for (decltype(count) i = 0; i != count; ++i) {
if (!mlir::isa<mlir::IntegerAttr, mlir::UnitAttr>(cases[i]))
return op.emitOpError("invalid case alternative");
}
return mlir::success();
}
static mlir::ParseResult parseIntegralSwitchTerminator(
mlir::OpAsmParser &parser, mlir::OperationState &result,
llvm::StringRef casesAttr, llvm::StringRef operandSegmentAttr) {
mlir::OpAsmParser::UnresolvedOperand selector;
mlir::Type type;
if (fir::parseSelector(parser, result, selector, type))
return mlir::failure();
llvm::SmallVector<mlir::Attribute> ivalues;
llvm::SmallVector<mlir::Block *> dests;
llvm::SmallVector<llvm::SmallVector<mlir::Value>> destArgs;
while (true) {
mlir::Attribute ivalue; // Integer or Unit
mlir::Block *dest;
llvm::SmallVector<mlir::Value> destArg;
mlir::NamedAttrList temp;
if (parser.parseAttribute(ivalue, "i", temp) || parser.parseComma() ||
parser.parseSuccessorAndUseList(dest, destArg))
return mlir::failure();
ivalues.push_back(ivalue);
dests.push_back(dest);
destArgs.push_back(destArg);
if (!parser.parseOptionalRSquare())
break;
if (parser.parseComma())
return mlir::failure();
}
auto &bld = parser.getBuilder();
result.addAttribute(casesAttr, bld.getArrayAttr(ivalues));
llvm::SmallVector<int32_t> argOffs;
int32_t sumArgs = 0;
const auto count = dests.size();
for (std::remove_const_t<decltype(count)> i = 0; i != count; ++i) {
result.addSuccessors(dests[i]);
result.addOperands(destArgs[i]);
auto argSize = destArgs[i].size();
argOffs.push_back(argSize);
sumArgs += argSize;
}
result.addAttribute(operandSegmentAttr,
bld.getDenseI32ArrayAttr({1, 0, sumArgs}));
result.addAttribute(getTargetOffsetAttr(), bld.getDenseI32ArrayAttr(argOffs));
return mlir::success();
}
template <typename OpT>
static void printIntegralSwitchTerminator(OpT op, mlir::OpAsmPrinter &p) {
p << ' ';
p.printOperand(op.getSelector());
p << " : " << op.getSelector().getType() << " [";
auto cases =
op->template getAttrOfType<mlir::ArrayAttr>(op.getCasesAttr()).getValue();
auto count = op.getNumConditions();
for (decltype(count) i = 0; i != count; ++i) {
if (i)
p << ", ";
auto &attr = cases[i];
if (auto intAttr = mlir::dyn_cast_or_null<mlir::IntegerAttr>(attr))
p << intAttr.getValue();
else
p.printAttribute(attr);
p << ", ";
op.printSuccessorAtIndex(p, i);
}
p << ']';
p.printOptionalAttrDict(
op->getAttrs(), {op.getCasesAttr(), getCompareOffsetAttr(),
getTargetOffsetAttr(), op.getOperandSegmentSizeAttr()});
}
//===----------------------------------------------------------------------===//
// SelectOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::SelectOp::verify() {
return verifyIntegralSwitchTerminator(*this);
}
mlir::ParseResult fir::SelectOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseIntegralSwitchTerminator(parser, result, getCasesAttr(),
getOperandSegmentSizeAttr());
}
void fir::SelectOp::print(mlir::OpAsmPrinter &p) {
printIntegralSwitchTerminator(*this, p);
}
template <typename A, typename... AdditionalArgs>
static A getSubOperands(unsigned pos, A allArgs, mlir::DenseI32ArrayAttr ranges,
AdditionalArgs &&...additionalArgs) {
unsigned start = 0;
for (unsigned i = 0; i < pos; ++i)
start += ranges[i];
return allArgs.slice(start, ranges[pos],
std::forward<AdditionalArgs>(additionalArgs)...);
}
static mlir::MutableOperandRange
getMutableSuccessorOperands(unsigned pos, mlir::MutableOperandRange operands,
llvm::StringRef offsetAttr) {
mlir::Operation *owner = operands.getOwner();
mlir::NamedAttribute targetOffsetAttr =
*owner->getAttrDictionary().getNamed(offsetAttr);
return getSubOperands(
pos, operands,
mlir::cast<mlir::DenseI32ArrayAttr>(targetOffsetAttr.getValue()),
mlir::MutableOperandRange::OperandSegment(pos, targetOffsetAttr));
}
std::optional<mlir::OperandRange> fir::SelectOp::getCompareOperands(unsigned) {
return {};
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectOp::getCompareOperands(llvm::ArrayRef<mlir::Value>, unsigned) {
return {};
}
mlir::SuccessorOperands fir::SelectOp::getSuccessorOperands(unsigned oper) {
return mlir::SuccessorOperands(::getMutableSuccessorOperands(
oper, getTargetArgsMutable(), getTargetOffsetAttr()));
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectOp::getSuccessorOperands(llvm::ArrayRef<mlir::Value> operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
std::optional<mlir::ValueRange>
fir::SelectOp::getSuccessorOperands(mlir::ValueRange operands, unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
unsigned fir::SelectOp::targetOffsetSize() {
return (*this)
->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr())
.size();
}
//===----------------------------------------------------------------------===//
// SelectCaseOp
//===----------------------------------------------------------------------===//
std::optional<mlir::OperandRange>
fir::SelectCaseOp::getCompareOperands(unsigned cond) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getCompareOffsetAttr());
return {getSubOperands(cond, getCompareArgs(), a)};
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectCaseOp::getCompareOperands(llvm::ArrayRef<mlir::Value> operands,
unsigned cond) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getCompareOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(cond, getSubOperands(1, operands, segments), a)};
}
std::optional<mlir::ValueRange>
fir::SelectCaseOp::getCompareOperands(mlir::ValueRange operands,
unsigned cond) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getCompareOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(cond, getSubOperands(1, operands, segments), a)};
}
mlir::SuccessorOperands fir::SelectCaseOp::getSuccessorOperands(unsigned oper) {
return mlir::SuccessorOperands(::getMutableSuccessorOperands(
oper, getTargetArgsMutable(), getTargetOffsetAttr()));
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectCaseOp::getSuccessorOperands(llvm::ArrayRef<mlir::Value> operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
std::optional<mlir::ValueRange>
fir::SelectCaseOp::getSuccessorOperands(mlir::ValueRange operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
// parser for fir.select_case Op
mlir::ParseResult fir::SelectCaseOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::OpAsmParser::UnresolvedOperand selector;
mlir::Type type;
if (fir::parseSelector(parser, result, selector, type))
return mlir::failure();
llvm::SmallVector<mlir::Attribute> attrs;
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> opers;
llvm::SmallVector<mlir::Block *> dests;
llvm::SmallVector<llvm::SmallVector<mlir::Value>> destArgs;
llvm::SmallVector<std::int32_t> argOffs;
std::int32_t offSize = 0;
while (true) {
mlir::Attribute attr;
mlir::Block *dest;
llvm::SmallVector<mlir::Value> destArg;
mlir::NamedAttrList temp;
if (parser.parseAttribute(attr, "a", temp) || isValidCaseAttr(attr) ||
parser.parseComma())
return mlir::failure();
attrs.push_back(attr);
if (mlir::dyn_cast_or_null<mlir::UnitAttr>(attr)) {
argOffs.push_back(0);
} else if (mlir::dyn_cast_or_null<fir::ClosedIntervalAttr>(attr)) {
mlir::OpAsmParser::UnresolvedOperand oper1;
mlir::OpAsmParser::UnresolvedOperand oper2;
if (parser.parseOperand(oper1) || parser.parseComma() ||
parser.parseOperand(oper2) || parser.parseComma())
return mlir::failure();
opers.push_back(oper1);
opers.push_back(oper2);
argOffs.push_back(2);
offSize += 2;
} else {
mlir::OpAsmParser::UnresolvedOperand oper;
if (parser.parseOperand(oper) || parser.parseComma())
return mlir::failure();
opers.push_back(oper);
argOffs.push_back(1);
++offSize;
}
if (parser.parseSuccessorAndUseList(dest, destArg))
return mlir::failure();
dests.push_back(dest);
destArgs.push_back(destArg);
if (mlir::succeeded(parser.parseOptionalRSquare()))
break;
if (parser.parseComma())
return mlir::failure();
}
result.addAttribute(fir::SelectCaseOp::getCasesAttr(),
parser.getBuilder().getArrayAttr(attrs));
if (parser.resolveOperands(opers, type, result.operands))
return mlir::failure();
llvm::SmallVector<int32_t> targOffs;
int32_t toffSize = 0;
const auto count = dests.size();
for (std::remove_const_t<decltype(count)> i = 0; i != count; ++i) {
result.addSuccessors(dests[i]);
result.addOperands(destArgs[i]);
auto argSize = destArgs[i].size();
targOffs.push_back(argSize);
toffSize += argSize;
}
auto &bld = parser.getBuilder();
result.addAttribute(fir::SelectCaseOp::getOperandSegmentSizeAttr(),
bld.getDenseI32ArrayAttr({1, offSize, toffSize}));
result.addAttribute(getCompareOffsetAttr(),
bld.getDenseI32ArrayAttr(argOffs));
result.addAttribute(getTargetOffsetAttr(),
bld.getDenseI32ArrayAttr(targOffs));
return mlir::success();
}
void fir::SelectCaseOp::print(mlir::OpAsmPrinter &p) {
p << ' ';
p.printOperand(getSelector());
p << " : " << getSelector().getType() << " [";
auto cases =
getOperation()->getAttrOfType<mlir::ArrayAttr>(getCasesAttr()).getValue();
auto count = getNumConditions();
for (decltype(count) i = 0; i != count; ++i) {
if (i)
p << ", ";
p << cases[i] << ", ";
if (!mlir::isa<mlir::UnitAttr>(cases[i])) {
auto caseArgs = *getCompareOperands(i);
p.printOperand(*caseArgs.begin());
p << ", ";
if (mlir::isa<fir::ClosedIntervalAttr>(cases[i])) {
p.printOperand(*(++caseArgs.begin()));
p << ", ";
}
}
printSuccessorAtIndex(p, i);
}
p << ']';
p.printOptionalAttrDict(getOperation()->getAttrs(),
{getCasesAttr(), getCompareOffsetAttr(),
getTargetOffsetAttr(), getOperandSegmentSizeAttr()});
}
unsigned fir::SelectCaseOp::compareOffsetSize() {
return (*this)
->getAttrOfType<mlir::DenseI32ArrayAttr>(getCompareOffsetAttr())
.size();
}
unsigned fir::SelectCaseOp::targetOffsetSize() {
return (*this)
->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr())
.size();
}
void fir::SelectCaseOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
mlir::Value selector,
llvm::ArrayRef<mlir::Attribute> compareAttrs,
llvm::ArrayRef<mlir::ValueRange> cmpOperands,
llvm::ArrayRef<mlir::Block *> destinations,
llvm::ArrayRef<mlir::ValueRange> destOperands,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
result.addOperands(selector);
result.addAttribute(getCasesAttr(), builder.getArrayAttr(compareAttrs));
llvm::SmallVector<int32_t> operOffs;
int32_t operSize = 0;
for (auto attr : compareAttrs) {
if (mlir::isa<fir::ClosedIntervalAttr>(attr)) {
operOffs.push_back(2);
operSize += 2;
} else if (mlir::isa<mlir::UnitAttr>(attr)) {
operOffs.push_back(0);
} else {
operOffs.push_back(1);
++operSize;
}
}
for (auto ops : cmpOperands)
result.addOperands(ops);
result.addAttribute(getCompareOffsetAttr(),
builder.getDenseI32ArrayAttr(operOffs));
const auto count = destinations.size();
for (auto d : destinations)
result.addSuccessors(d);
const auto opCount = destOperands.size();
llvm::SmallVector<std::int32_t> argOffs;
std::int32_t sumArgs = 0;
for (std::remove_const_t<decltype(count)> i = 0; i != count; ++i) {
if (i < opCount) {
result.addOperands(destOperands[i]);
const auto argSz = destOperands[i].size();
argOffs.push_back(argSz);
sumArgs += argSz;
} else {
argOffs.push_back(0);
}
}
result.addAttribute(getOperandSegmentSizeAttr(),
builder.getDenseI32ArrayAttr({1, operSize, sumArgs}));
result.addAttribute(getTargetOffsetAttr(),
builder.getDenseI32ArrayAttr(argOffs));
result.addAttributes(attributes);
}
/// This builder has a slightly simplified interface in that the list of
/// operands need not be partitioned by the builder. Instead the operands are
/// partitioned here, before being passed to the default builder. This
/// partitioning is unchecked, so can go awry on bad input.
void fir::SelectCaseOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
mlir::Value selector,
llvm::ArrayRef<mlir::Attribute> compareAttrs,
llvm::ArrayRef<mlir::Value> cmpOpList,
llvm::ArrayRef<mlir::Block *> destinations,
llvm::ArrayRef<mlir::ValueRange> destOperands,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
llvm::SmallVector<mlir::ValueRange> cmpOpers;
auto iter = cmpOpList.begin();
for (auto &attr : compareAttrs) {
if (mlir::isa<fir::ClosedIntervalAttr>(attr)) {
cmpOpers.push_back(mlir::ValueRange({iter, iter + 2}));
iter += 2;
} else if (mlir::isa<mlir::UnitAttr>(attr)) {
cmpOpers.push_back(mlir::ValueRange{});
} else {
cmpOpers.push_back(mlir::ValueRange({iter, iter + 1}));
++iter;
}
}
build(builder, result, selector, compareAttrs, cmpOpers, destinations,
destOperands, attributes);
}
llvm::LogicalResult fir::SelectCaseOp::verify() {
if (!mlir::isa<mlir::IntegerType, mlir::IndexType, fir::IntegerType,
fir::LogicalType, fir::CharacterType>(getSelector().getType()))
return emitOpError("must be an integer, character, or logical");
auto cases =
getOperation()->getAttrOfType<mlir::ArrayAttr>(getCasesAttr()).getValue();
auto count = getNumDest();
if (count == 0)
return emitOpError("must have at least one successor");
if (getNumConditions() != count)
return emitOpError("number of conditions and successors don't match");
if (compareOffsetSize() != count)
return emitOpError("incorrect number of compare operand groups");
if (targetOffsetSize() != count)
return emitOpError("incorrect number of successor operand groups");
for (decltype(count) i = 0; i != count; ++i) {
auto &attr = cases[i];
if (!(mlir::isa<fir::PointIntervalAttr>(attr) ||
mlir::isa<fir::LowerBoundAttr>(attr) ||
mlir::isa<fir::UpperBoundAttr>(attr) ||
mlir::isa<fir::ClosedIntervalAttr>(attr) ||
mlir::isa<mlir::UnitAttr>(attr)))
return emitOpError("incorrect select case attribute type");
}
return mlir::success();
}
//===----------------------------------------------------------------------===//
// SelectRankOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::SelectRankOp::verify() {
return verifyIntegralSwitchTerminator(*this);
}
mlir::ParseResult fir::SelectRankOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
return parseIntegralSwitchTerminator(parser, result, getCasesAttr(),
getOperandSegmentSizeAttr());
}
void fir::SelectRankOp::print(mlir::OpAsmPrinter &p) {
printIntegralSwitchTerminator(*this, p);
}
std::optional<mlir::OperandRange>
fir::SelectRankOp::getCompareOperands(unsigned) {
return {};
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectRankOp::getCompareOperands(llvm::ArrayRef<mlir::Value>, unsigned) {
return {};
}
mlir::SuccessorOperands fir::SelectRankOp::getSuccessorOperands(unsigned oper) {
return mlir::SuccessorOperands(::getMutableSuccessorOperands(
oper, getTargetArgsMutable(), getTargetOffsetAttr()));
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectRankOp::getSuccessorOperands(llvm::ArrayRef<mlir::Value> operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
std::optional<mlir::ValueRange>
fir::SelectRankOp::getSuccessorOperands(mlir::ValueRange operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
unsigned fir::SelectRankOp::targetOffsetSize() {
return (*this)
->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr())
.size();
}
//===----------------------------------------------------------------------===//
// SelectTypeOp
//===----------------------------------------------------------------------===//
std::optional<mlir::OperandRange>
fir::SelectTypeOp::getCompareOperands(unsigned) {
return {};
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectTypeOp::getCompareOperands(llvm::ArrayRef<mlir::Value>, unsigned) {
return {};
}
mlir::SuccessorOperands fir::SelectTypeOp::getSuccessorOperands(unsigned oper) {
return mlir::SuccessorOperands(::getMutableSuccessorOperands(
oper, getTargetArgsMutable(), getTargetOffsetAttr()));
}
std::optional<llvm::ArrayRef<mlir::Value>>
fir::SelectTypeOp::getSuccessorOperands(llvm::ArrayRef<mlir::Value> operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
std::optional<mlir::ValueRange>
fir::SelectTypeOp::getSuccessorOperands(mlir::ValueRange operands,
unsigned oper) {
auto a =
(*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr());
auto segments = (*this)->getAttrOfType<mlir::DenseI32ArrayAttr>(
getOperandSegmentSizeAttr());
return {getSubOperands(oper, getSubOperands(2, operands, segments), a)};
}
mlir::ParseResult fir::SelectTypeOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::OpAsmParser::UnresolvedOperand selector;
mlir::Type type;
if (fir::parseSelector(parser, result, selector, type))
return mlir::failure();
llvm::SmallVector<mlir::Attribute> attrs;
llvm::SmallVector<mlir::Block *> dests;
llvm::SmallVector<llvm::SmallVector<mlir::Value>> destArgs;
while (true) {
mlir::Attribute attr;
mlir::Block *dest;
llvm::SmallVector<mlir::Value> destArg;
mlir::NamedAttrList temp;
if (parser.parseAttribute(attr, "a", temp) || parser.parseComma() ||
parser.parseSuccessorAndUseList(dest, destArg))
return mlir::failure();
attrs.push_back(attr);
dests.push_back(dest);
destArgs.push_back(destArg);
if (mlir::succeeded(parser.parseOptionalRSquare()))
break;
if (parser.parseComma())
return mlir::failure();
}
auto &bld = parser.getBuilder();
result.addAttribute(fir::SelectTypeOp::getCasesAttr(),
bld.getArrayAttr(attrs));
llvm::SmallVector<int32_t> argOffs;
int32_t offSize = 0;
const auto count = dests.size();
for (std::remove_const_t<decltype(count)> i = 0; i != count; ++i) {
result.addSuccessors(dests[i]);
result.addOperands(destArgs[i]);
auto argSize = destArgs[i].size();
argOffs.push_back(argSize);
offSize += argSize;
}
result.addAttribute(fir::SelectTypeOp::getOperandSegmentSizeAttr(),
bld.getDenseI32ArrayAttr({1, 0, offSize}));
result.addAttribute(getTargetOffsetAttr(), bld.getDenseI32ArrayAttr(argOffs));
return mlir::success();
}
unsigned fir::SelectTypeOp::targetOffsetSize() {
return (*this)
->getAttrOfType<mlir::DenseI32ArrayAttr>(getTargetOffsetAttr())
.size();
}
void fir::SelectTypeOp::print(mlir::OpAsmPrinter &p) {
p << ' ';
p.printOperand(getSelector());
p << " : " << getSelector().getType() << " [";
auto cases =
getOperation()->getAttrOfType<mlir::ArrayAttr>(getCasesAttr()).getValue();
auto count = getNumConditions();
for (decltype(count) i = 0; i != count; ++i) {
if (i)
p << ", ";
p << cases[i] << ", ";
printSuccessorAtIndex(p, i);
}
p << ']';
p.printOptionalAttrDict(getOperation()->getAttrs(),
{getCasesAttr(), getCompareOffsetAttr(),
getTargetOffsetAttr(),
fir::SelectTypeOp::getOperandSegmentSizeAttr()});
}
llvm::LogicalResult fir::SelectTypeOp::verify() {
if (!mlir::isa<fir::BaseBoxType>(getSelector().getType()))
return emitOpError("must be a fir.class or fir.box type");
if (auto boxType = mlir::dyn_cast<fir::BoxType>(getSelector().getType()))
if (!mlir::isa<mlir::NoneType>(boxType.getEleTy()))
return emitOpError("selector must be polymorphic");
auto typeGuardAttr = getCases();
for (unsigned idx = 0; idx < typeGuardAttr.size(); ++idx)
if (mlir::isa<mlir::UnitAttr>(typeGuardAttr[idx]) &&
idx != typeGuardAttr.size() - 1)
return emitOpError("default must be the last attribute");
auto count = getNumDest();
if (count == 0)
return emitOpError("must have at least one successor");
if (getNumConditions() != count)
return emitOpError("number of conditions and successors don't match");
if (targetOffsetSize() != count)
return emitOpError("incorrect number of successor operand groups");
for (unsigned i = 0; i != count; ++i) {
if (!mlir::isa<fir::ExactTypeAttr, fir::SubclassAttr, mlir::UnitAttr>(
typeGuardAttr[i]))
return emitOpError("invalid type-case alternative");
}
return mlir::success();
}
void fir::SelectTypeOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
mlir::Value selector,
llvm::ArrayRef<mlir::Attribute> typeOperands,
llvm::ArrayRef<mlir::Block *> destinations,
llvm::ArrayRef<mlir::ValueRange> destOperands,
llvm::ArrayRef<mlir::NamedAttribute> attributes) {
result.addOperands(selector);
result.addAttribute(getCasesAttr(), builder.getArrayAttr(typeOperands));
const auto count = destinations.size();
for (mlir::Block *dest : destinations)
result.addSuccessors(dest);
const auto opCount = destOperands.size();
llvm::SmallVector<int32_t> argOffs;
int32_t sumArgs = 0;
for (std::remove_const_t<decltype(count)> i = 0; i != count; ++i) {
if (i < opCount) {
result.addOperands(destOperands[i]);
const auto argSz = destOperands[i].size();
argOffs.push_back(argSz);
sumArgs += argSz;
} else {
argOffs.push_back(0);
}
}
result.addAttribute(getOperandSegmentSizeAttr(),
builder.getDenseI32ArrayAttr({1, 0, sumArgs}));
result.addAttribute(getTargetOffsetAttr(),
builder.getDenseI32ArrayAttr(argOffs));
result.addAttributes(attributes);
}
//===----------------------------------------------------------------------===//
// ShapeOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ShapeOp::verify() {
auto size = getExtents().size();
auto shapeTy = mlir::dyn_cast<fir::ShapeType>(getType());
assert(shapeTy && "must be a shape type");
if (shapeTy.getRank() != size)
return emitOpError("shape type rank mismatch");
return mlir::success();
}
void fir::ShapeOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::ValueRange extents) {
auto type = fir::ShapeType::get(builder.getContext(), extents.size());
build(builder, result, type, extents);
}
//===----------------------------------------------------------------------===//
// ShapeShiftOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ShapeShiftOp::verify() {
auto size = getPairs().size();
if (size < 2 || size > 16 * 2)
return emitOpError("incorrect number of args");
if (size % 2 != 0)
return emitOpError("requires a multiple of 2 args");
auto shapeTy = mlir::dyn_cast<fir::ShapeShiftType>(getType());
assert(shapeTy && "must be a shape shift type");
if (shapeTy.getRank() * 2 != size)
return emitOpError("shape type rank mismatch");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// ShiftOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::ShiftOp::verify() {
auto size = getOrigins().size();
auto shiftTy = mlir::dyn_cast<fir::ShiftType>(getType());
assert(shiftTy && "must be a shift type");
if (shiftTy.getRank() != size)
return emitOpError("shift type rank mismatch");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// SliceOp
//===----------------------------------------------------------------------===//
void fir::SliceOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::ValueRange trips, mlir::ValueRange path,
mlir::ValueRange substr) {
const auto rank = trips.size() / 3;
auto sliceTy = fir::SliceType::get(builder.getContext(), rank);
build(builder, result, sliceTy, trips, path, substr);
}
/// Return the output rank of a slice op. The output rank must be between 1 and
/// the rank of the array being sliced (inclusive).
unsigned fir::SliceOp::getOutputRank(mlir::ValueRange triples) {
unsigned rank = 0;
if (!triples.empty()) {
for (unsigned i = 1, end = triples.size(); i < end; i += 3) {
auto *op = triples[i].getDefiningOp();
if (!mlir::isa_and_nonnull<fir::UndefOp>(op))
++rank;
}
assert(rank > 0);
}
return rank;
}
llvm::LogicalResult fir::SliceOp::verify() {
auto size = getTriples().size();
if (size < 3 || size > 16 * 3)
return emitOpError("incorrect number of args for triple");
if (size % 3 != 0)
return emitOpError("requires a multiple of 3 args");
auto sliceTy = mlir::dyn_cast<fir::SliceType>(getType());
assert(sliceTy && "must be a slice type");
if (sliceTy.getRank() * 3 != size)
return emitOpError("slice type rank mismatch");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// StoreOp
//===----------------------------------------------------------------------===//
mlir::Type fir::StoreOp::elementType(mlir::Type refType) {
return fir::dyn_cast_ptrEleTy(refType);
}
mlir::ParseResult fir::StoreOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
mlir::Type type;
mlir::OpAsmParser::UnresolvedOperand oper;
mlir::OpAsmParser::UnresolvedOperand store;
if (parser.parseOperand(oper) || parser.parseKeyword("to") ||
parser.parseOperand(store) ||
parser.parseOptionalAttrDict(result.attributes) ||
parser.parseColonType(type) ||
parser.resolveOperand(oper, fir::StoreOp::elementType(type),
result.operands) ||
parser.resolveOperand(store, type, result.operands))
return mlir::failure();
return mlir::success();
}
void fir::StoreOp::print(mlir::OpAsmPrinter &p) {
p << ' ';
p.printOperand(getValue());
p << " to ";
p.printOperand(getMemref());
p.printOptionalAttrDict(getOperation()->getAttrs(), {});
p << " : " << getMemref().getType();
}
llvm::LogicalResult fir::StoreOp::verify() {
if (getValue().getType() != fir::dyn_cast_ptrEleTy(getMemref().getType()))
return emitOpError("store value type must match memory reference type");
return mlir::success();
}
void fir::StoreOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::Value value, mlir::Value memref) {
build(builder, result, value, memref, {});
}
void fir::StoreOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
effects.emplace_back(mlir::MemoryEffects::Write::get(), &getMemrefMutable(),
mlir::SideEffects::DefaultResource::get());
addVolatileMemoryEffects({getMemref().getType()}, effects);
}
//===----------------------------------------------------------------------===//
// CopyOp
//===----------------------------------------------------------------------===//
void fir::CopyOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::Value source, mlir::Value destination,
bool noOverlap) {
mlir::UnitAttr noOverlapAttr =
noOverlap ? builder.getUnitAttr() : mlir::UnitAttr{};
build(builder, result, source, destination, noOverlapAttr);
}
llvm::LogicalResult fir::CopyOp::verify() {
mlir::Type sourceType = fir::unwrapRefType(getSource().getType());
mlir::Type destinationType = fir::unwrapRefType(getDestination().getType());
if (sourceType != destinationType)
return emitOpError("source and destination must have the same value type");
return mlir::success();
}
void fir::CopyOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
effects.emplace_back(mlir::MemoryEffects::Read::get(), &getSourceMutable(),
mlir::SideEffects::DefaultResource::get());
effects.emplace_back(mlir::MemoryEffects::Write::get(),
&getDestinationMutable(),
mlir::SideEffects::DefaultResource::get());
addVolatileMemoryEffects({getDestination().getType(), getSource().getType()},
effects);
}
//===----------------------------------------------------------------------===//
// StringLitOp
//===----------------------------------------------------------------------===//
inline fir::CharacterType::KindTy stringLitOpGetKind(fir::StringLitOp op) {
auto eleTy = mlir::cast<fir::SequenceType>(op.getType()).getElementType();
return mlir::cast<fir::CharacterType>(eleTy).getFKind();
}
bool fir::StringLitOp::isWideValue() { return stringLitOpGetKind(*this) != 1; }
static mlir::NamedAttribute
mkNamedIntegerAttr(mlir::OpBuilder &builder, llvm::StringRef name, int64_t v) {
assert(v > 0);
return builder.getNamedAttr(
name, builder.getIntegerAttr(builder.getIntegerType(64), v));
}
void fir::StringLitOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
fir::CharacterType inType, llvm::StringRef val,
std::optional<int64_t> len) {
auto valAttr = builder.getNamedAttr(value(), builder.getStringAttr(val));
int64_t length = len ? *len : inType.getLen();
auto lenAttr = mkNamedIntegerAttr(builder, size(), length);
result.addAttributes({valAttr, lenAttr});
result.addTypes(inType);
}
template <typename C>
static mlir::ArrayAttr convertToArrayAttr(mlir::OpBuilder &builder,
llvm::ArrayRef<C> xlist) {
llvm::SmallVector<mlir::Attribute> attrs;
auto ty = builder.getIntegerType(8 * sizeof(C));
for (auto ch : xlist)
attrs.push_back(builder.getIntegerAttr(ty, ch));
return builder.getArrayAttr(attrs);
}
void fir::StringLitOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
fir::CharacterType inType,
llvm::ArrayRef<char> vlist,
std::optional<std::int64_t> len) {
auto valAttr =
builder.getNamedAttr(xlist(), convertToArrayAttr(builder, vlist));
std::int64_t length = len ? *len : inType.getLen();
auto lenAttr = mkNamedIntegerAttr(builder, size(), length);
result.addAttributes({valAttr, lenAttr});
result.addTypes(inType);
}
void fir::StringLitOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
fir::CharacterType inType,
llvm::ArrayRef<char16_t> vlist,
std::optional<std::int64_t> len) {
auto valAttr =
builder.getNamedAttr(xlist(), convertToArrayAttr(builder, vlist));
std::int64_t length = len ? *len : inType.getLen();
auto lenAttr = mkNamedIntegerAttr(builder, size(), length);
result.addAttributes({valAttr, lenAttr});
result.addTypes(inType);
}
void fir::StringLitOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result,
fir::CharacterType inType,
llvm::ArrayRef<char32_t> vlist,
std::optional<std::int64_t> len) {
auto valAttr =
builder.getNamedAttr(xlist(), convertToArrayAttr(builder, vlist));
std::int64_t length = len ? *len : inType.getLen();
auto lenAttr = mkNamedIntegerAttr(builder, size(), length);
result.addAttributes({valAttr, lenAttr});
result.addTypes(inType);
}
mlir::ParseResult fir::StringLitOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
auto &builder = parser.getBuilder();
mlir::Attribute val;
mlir::NamedAttrList attrs;
llvm::SMLoc trailingTypeLoc;
if (parser.parseAttribute(val, "fake", attrs))
return mlir::failure();
if (auto v = mlir::dyn_cast<mlir::StringAttr>(val))
result.attributes.push_back(
builder.getNamedAttr(fir::StringLitOp::value(), v));
else if (auto v = mlir::dyn_cast<mlir::DenseElementsAttr>(val))
result.attributes.push_back(
builder.getNamedAttr(fir::StringLitOp::xlist(), v));
else if (auto v = mlir::dyn_cast<mlir::ArrayAttr>(val))
result.attributes.push_back(
builder.getNamedAttr(fir::StringLitOp::xlist(), v));
else
return parser.emitError(parser.getCurrentLocation(),
"found an invalid constant");
mlir::IntegerAttr sz;
mlir::Type type;
if (parser.parseLParen() ||
parser.parseAttribute(sz, fir::StringLitOp::size(), result.attributes) ||
parser.parseRParen() || parser.getCurrentLocation(&trailingTypeLoc) ||
parser.parseColonType(type))
return mlir::failure();
auto charTy = mlir::dyn_cast<fir::CharacterType>(type);
if (!charTy)
return parser.emitError(trailingTypeLoc, "must have character type");
type = fir::CharacterType::get(builder.getContext(), charTy.getFKind(),
sz.getInt());
if (!type || parser.addTypesToList(type, result.types))
return mlir::failure();
return mlir::success();
}
void fir::StringLitOp::print(mlir::OpAsmPrinter &p) {
p << ' ' << getValue() << '(';
p << mlir::cast<mlir::IntegerAttr>(getSize()).getValue() << ") : ";
p.printType(getType());
}
llvm::LogicalResult fir::StringLitOp::verify() {
if (mlir::cast<mlir::IntegerAttr>(getSize()).getValue().isNegative())
return emitOpError("size must be non-negative");
if (auto xl = getOperation()->getAttr(fir::StringLitOp::xlist())) {
if (auto xList = mlir::dyn_cast<mlir::ArrayAttr>(xl)) {
for (auto a : xList)
if (!mlir::isa<mlir::IntegerAttr>(a))
return emitOpError("values in initializer must be integers");
} else if (mlir::isa<mlir::DenseElementsAttr>(xl)) {
// do nothing
} else {
return emitOpError("has unexpected attribute");
}
}
return mlir::success();
}
//===----------------------------------------------------------------------===//
// UnboxProcOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::UnboxProcOp::verify() {
if (auto eleTy = fir::dyn_cast_ptrEleTy(getRefTuple().getType()))
if (mlir::isa<mlir::TupleType>(eleTy))
return mlir::success();
return emitOpError("second output argument has bad type");
}
//===----------------------------------------------------------------------===//
// IfOp
//===----------------------------------------------------------------------===//
void fir::IfOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::Value cond, bool withElseRegion) {
build(builder, result, std::nullopt, cond, withElseRegion);
}
void fir::IfOp::build(mlir::OpBuilder &builder, mlir::OperationState &result,
mlir::TypeRange resultTypes, mlir::Value cond,
bool withElseRegion) {
result.addOperands(cond);
result.addTypes(resultTypes);
mlir::Region *thenRegion = result.addRegion();
thenRegion->push_back(new mlir::Block());
if (resultTypes.empty())
IfOp::ensureTerminator(*thenRegion, builder, result.location);
mlir::Region *elseRegion = result.addRegion();
if (withElseRegion) {
elseRegion->push_back(new mlir::Block());
if (resultTypes.empty())
IfOp::ensureTerminator(*elseRegion, builder, result.location);
}
}
// These 3 functions copied from scf.if implementation.
/// Given the region at `index`, or the parent operation if `index` is None,
/// return the successor regions. These are the regions that may be selected
/// during the flow of control.
void fir::IfOp::getSuccessorRegions(
mlir::RegionBranchPoint point,
llvm::SmallVectorImpl<mlir::RegionSuccessor> &regions) {
// The `then` and the `else` region branch back to the parent operation.
if (!point.isParent()) {
regions.push_back(mlir::RegionSuccessor(getResults()));
return;
}
// Don't consider the else region if it is empty.
regions.push_back(mlir::RegionSuccessor(&getThenRegion()));
// Don't consider the else region if it is empty.
mlir::Region *elseRegion = &this->getElseRegion();
if (elseRegion->empty())
regions.push_back(mlir::RegionSuccessor());
else
regions.push_back(mlir::RegionSuccessor(elseRegion));
}
void fir::IfOp::getEntrySuccessorRegions(
llvm::ArrayRef<mlir::Attribute> operands,
llvm::SmallVectorImpl<mlir::RegionSuccessor> &regions) {
FoldAdaptor adaptor(operands);
auto boolAttr =
mlir::dyn_cast_or_null<mlir::BoolAttr>(adaptor.getCondition());
if (!boolAttr || boolAttr.getValue())
regions.emplace_back(&getThenRegion());
// If the else region is empty, execution continues after the parent op.
if (!boolAttr || !boolAttr.getValue()) {
if (!getElseRegion().empty())
regions.emplace_back(&getElseRegion());
else
regions.emplace_back(getResults());
}
}
void fir::IfOp::getRegionInvocationBounds(
llvm::ArrayRef<mlir::Attribute> operands,
llvm::SmallVectorImpl<mlir::InvocationBounds> &invocationBounds) {
if (auto cond = mlir::dyn_cast_or_null<mlir::BoolAttr>(operands[0])) {
// If the condition is known, then one region is known to be executed once
// and the other zero times.
invocationBounds.emplace_back(0, cond.getValue() ? 1 : 0);
invocationBounds.emplace_back(0, cond.getValue() ? 0 : 1);
} else {
// Non-constant condition. Each region may be executed 0 or 1 times.
invocationBounds.assign(2, {0, 1});
}
}
mlir::ParseResult fir::IfOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
result.regions.reserve(2);
mlir::Region *thenRegion = result.addRegion();
mlir::Region *elseRegion = result.addRegion();
auto &builder = parser.getBuilder();
mlir::OpAsmParser::UnresolvedOperand cond;
mlir::Type i1Type = builder.getIntegerType(1);
if (parser.parseOperand(cond) ||
parser.resolveOperand(cond, i1Type, result.operands))
return mlir::failure();
if (mlir::succeeded(
parser.parseOptionalKeyword(getWeightsAttrAssemblyName()))) {
if (parser.parseLParen())
return mlir::failure();
mlir::DenseI32ArrayAttr weights;
if (parser.parseCustomAttributeWithFallback(weights, mlir::Type{}))
return mlir::failure();
if (weights)
result.addAttribute(getRegionWeightsAttrName(result.name), weights);
if (parser.parseRParen())
return mlir::failure();
}
if (parser.parseOptionalArrowTypeList(result.types))
return mlir::failure();
if (parser.parseRegion(*thenRegion, {}, {}))
return mlir::failure();
fir::IfOp::ensureTerminator(*thenRegion, parser.getBuilder(),
result.location);
if (mlir::succeeded(parser.parseOptionalKeyword("else"))) {
if (parser.parseRegion(*elseRegion, {}, {}))
return mlir::failure();
fir::IfOp::ensureTerminator(*elseRegion, parser.getBuilder(),
result.location);
}
// Parse the optional attribute list.
if (parser.parseOptionalAttrDict(result.attributes))
return mlir::failure();
return mlir::success();
}
llvm::LogicalResult fir::IfOp::verify() {
if (getNumResults() != 0 && getElseRegion().empty())
return emitOpError("must have an else block if defining values");
return mlir::success();
}
void fir::IfOp::print(mlir::OpAsmPrinter &p) {
bool printBlockTerminators = false;
p << ' ' << getCondition();
if (auto weights = getRegionWeightsAttr()) {
p << ' ' << getWeightsAttrAssemblyName() << '(';
p.printStrippedAttrOrType(weights);
p << ')';
}
if (!getResults().empty()) {
p << " -> (" << getResultTypes() << ')';
printBlockTerminators = true;
}
p << ' ';
p.printRegion(getThenRegion(), /*printEntryBlockArgs=*/false,
printBlockTerminators);
// Print the 'else' regions if it exists and has a block.
auto &otherReg = getElseRegion();
if (!otherReg.empty()) {
p << " else ";
p.printRegion(otherReg, /*printEntryBlockArgs=*/false,
printBlockTerminators);
}
p.printOptionalAttrDict((*this)->getAttrs(),
/*elideAttrs=*/{getRegionWeightsAttrName()});
}
void fir::IfOp::resultToSourceOps(llvm::SmallVectorImpl<mlir::Value> &results,
unsigned resultNum) {
auto *term = getThenRegion().front().getTerminator();
if (resultNum < term->getNumOperands())
results.push_back(term->getOperand(resultNum));
term = getElseRegion().front().getTerminator();
if (resultNum < term->getNumOperands())
results.push_back(term->getOperand(resultNum));
}
//===----------------------------------------------------------------------===//
// BoxOffsetOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::BoxOffsetOp::verify() {
auto boxType = mlir::dyn_cast_or_null<fir::BaseBoxType>(
fir::dyn_cast_ptrEleTy(getBoxRef().getType()));
mlir::Type boxCharType;
if (!boxType) {
boxCharType = mlir::dyn_cast_or_null<fir::BoxCharType>(
fir::dyn_cast_ptrEleTy(getBoxRef().getType()));
if (!boxCharType)
return emitOpError("box_ref operand must have !fir.ref<!fir.box<T>> or "
"!fir.ref<!fir.boxchar<k>> type");
if (getField() == fir::BoxFieldAttr::derived_type)
return emitOpError("cannot address derived_type field of a fir.boxchar");
}
if (getField() != fir::BoxFieldAttr::base_addr &&
getField() != fir::BoxFieldAttr::derived_type)
return emitOpError("cannot address provided field");
if (getField() == fir::BoxFieldAttr::derived_type) {
if (!fir::boxHasAddendum(boxType))
return emitOpError("can only address derived_type field of derived type "
"or unlimited polymorphic fir.box");
}
return mlir::success();
}
void fir::BoxOffsetOp::build(mlir::OpBuilder &builder,
mlir::OperationState &result, mlir::Value boxRef,
fir::BoxFieldAttr field) {
mlir::Type valueType =
fir::unwrapPassByRefType(fir::unwrapRefType(boxRef.getType()));
mlir::Type resultType = valueType;
if (field == fir::BoxFieldAttr::base_addr)
resultType = fir::LLVMPointerType::get(fir::ReferenceType::get(valueType));
else if (field == fir::BoxFieldAttr::derived_type)
resultType = fir::LLVMPointerType::get(
fir::TypeDescType::get(fir::unwrapSequenceType(valueType)));
build(builder, result, {resultType}, boxRef, field);
}
//===----------------------------------------------------------------------===//
mlir::ParseResult fir::isValidCaseAttr(mlir::Attribute attr) {
if (mlir::isa<mlir::UnitAttr, fir::ClosedIntervalAttr, fir::PointIntervalAttr,
fir::LowerBoundAttr, fir::UpperBoundAttr>(attr))
return mlir::success();
return mlir::failure();
}
unsigned fir::getCaseArgumentOffset(llvm::ArrayRef<mlir::Attribute> cases,
unsigned dest) {
unsigned o = 0;
for (unsigned i = 0; i < dest; ++i) {
auto &attr = cases[i];
if (!mlir::dyn_cast_or_null<mlir::UnitAttr>(attr)) {
++o;
if (mlir::dyn_cast_or_null<fir::ClosedIntervalAttr>(attr))
++o;
}
}
return o;
}
mlir::ParseResult
fir::parseSelector(mlir::OpAsmParser &parser, mlir::OperationState &result,
mlir::OpAsmParser::UnresolvedOperand &selector,
mlir::Type &type) {
if (parser.parseOperand(selector) || parser.parseColonType(type) ||
parser.resolveOperand(selector, type, result.operands) ||
parser.parseLSquare())
return mlir::failure();
return mlir::success();
}
mlir::func::FuncOp fir::createFuncOp(mlir::Location loc, mlir::ModuleOp module,
llvm::StringRef name,
mlir::FunctionType type,
llvm::ArrayRef<mlir::NamedAttribute> attrs,
const mlir::SymbolTable *symbolTable) {
if (symbolTable)
if (auto f = symbolTable->lookup<mlir::func::FuncOp>(name)) {
#ifdef EXPENSIVE_CHECKS
assert(f == module.lookupSymbol<mlir::func::FuncOp>(name) &&
"symbolTable and module out of sync");
#endif
return f;
}
if (auto f = module.lookupSymbol<mlir::func::FuncOp>(name))
return f;
mlir::OpBuilder modBuilder(module.getBodyRegion());
modBuilder.setInsertionPointToEnd(module.getBody());
auto result = modBuilder.create<mlir::func::FuncOp>(loc, name, type, attrs);
result.setVisibility(mlir::SymbolTable::Visibility::Private);
return result;
}
fir::GlobalOp fir::createGlobalOp(mlir::Location loc, mlir::ModuleOp module,
llvm::StringRef name, mlir::Type type,
llvm::ArrayRef<mlir::NamedAttribute> attrs,
const mlir::SymbolTable *symbolTable) {
if (symbolTable)
if (auto g = symbolTable->lookup<fir::GlobalOp>(name)) {
#ifdef EXPENSIVE_CHECKS
assert(g == module.lookupSymbol<fir::GlobalOp>(name) &&
"symbolTable and module out of sync");
#endif
return g;
}
if (auto g = module.lookupSymbol<fir::GlobalOp>(name))
return g;
mlir::OpBuilder modBuilder(module.getBodyRegion());
auto result = modBuilder.create<fir::GlobalOp>(loc, name, type, attrs);
result.setVisibility(mlir::SymbolTable::Visibility::Private);
return result;
}
bool fir::hasHostAssociationArgument(mlir::func::FuncOp func) {
if (auto allArgAttrs = func.getAllArgAttrs())
for (auto attr : allArgAttrs)
if (auto dict = mlir::dyn_cast_or_null<mlir::DictionaryAttr>(attr))
if (dict.get(fir::getHostAssocAttrName()))
return true;
return false;
}
// Test if value's definition has the specified set of
// attributeNames. The value's definition is one of the operations
// that are able to carry the Fortran variable attributes, e.g.
// fir.alloca or fir.allocmem. Function arguments may also represent
// value definitions and carry relevant attributes.
//
// If it is not possible to reach the limited set of definition
// entities from the given value, then the function will return
// std::nullopt. Otherwise, the definition is known and the return
// value is computed as:
// * if checkAny is true, then the function will return true
// iff any of the attributeNames attributes is set on the definition.
// * if checkAny is false, then the function will return true
// iff all of the attributeNames attributes are set on the definition.
static std::optional<bool>
valueCheckFirAttributes(mlir::Value value,
llvm::ArrayRef<llvm::StringRef> attributeNames,
bool checkAny) {
auto testAttributeSets = [&](llvm::ArrayRef<mlir::NamedAttribute> setAttrs,
llvm::ArrayRef<llvm::StringRef> checkAttrs) {
if (checkAny) {
// Return true iff any of checkAttrs attributes is present
// in setAttrs set.
for (llvm::StringRef checkAttrName : checkAttrs)
if (llvm::any_of(setAttrs, [&](mlir::NamedAttribute setAttr) {
return setAttr.getName() == checkAttrName;
}))
return true;
return false;
}
// Return true iff all attributes from checkAttrs are present
// in setAttrs set.
for (mlir::StringRef checkAttrName : checkAttrs)
if (llvm::none_of(setAttrs, [&](mlir::NamedAttribute setAttr) {
return setAttr.getName() == checkAttrName;
}))
return false;
return true;
};
// If this is a fir.box that was loaded, the fir attributes will be on the
// related fir.ref<fir.box> creation.
if (mlir::isa<fir::BoxType>(value.getType()))
if (auto definingOp = value.getDefiningOp())
if (auto loadOp = mlir::dyn_cast<fir::LoadOp>(definingOp))
value = loadOp.getMemref();
// If this is a function argument, look in the argument attributes.
if (auto blockArg = mlir::dyn_cast<mlir::BlockArgument>(value)) {
if (blockArg.getOwner() && blockArg.getOwner()->isEntryBlock())
if (auto funcOp = mlir::dyn_cast<mlir::func::FuncOp>(
blockArg.getOwner()->getParentOp()))
return testAttributeSets(
mlir::cast<mlir::FunctionOpInterface>(*funcOp).getArgAttrs(
blockArg.getArgNumber()),
attributeNames);
// If it is not a function argument, the attributes are unknown.
return std::nullopt;
}
if (auto definingOp = value.getDefiningOp()) {
// If this is an allocated value, look at the allocation attributes.
if (mlir::isa<fir::AllocMemOp>(definingOp) ||
mlir::isa<fir::AllocaOp>(definingOp))
return testAttributeSets(definingOp->getAttrs(), attributeNames);
// If this is an imported global, look at AddrOfOp and GlobalOp attributes.
// Both operations are looked at because use/host associated variable (the
// AddrOfOp) can have ASYNCHRONOUS/VOLATILE attributes even if the ultimate
// entity (the globalOp) does not have them.
if (auto addressOfOp = mlir::dyn_cast<fir::AddrOfOp>(definingOp)) {
if (testAttributeSets(addressOfOp->getAttrs(), attributeNames))
return true;
if (auto module = definingOp->getParentOfType<mlir::ModuleOp>())
if (auto globalOp =
module.lookupSymbol<fir::GlobalOp>(addressOfOp.getSymbol()))
return testAttributeSets(globalOp->getAttrs(), attributeNames);
}
}
// TODO: Construct associated entities attributes. Decide where the fir
// attributes must be placed/looked for in this case.
return std::nullopt;
}
bool fir::valueMayHaveFirAttributes(
mlir::Value value, llvm::ArrayRef<llvm::StringRef> attributeNames) {
std::optional<bool> mayHaveAttr =
valueCheckFirAttributes(value, attributeNames, /*checkAny=*/true);
return mayHaveAttr.value_or(true);
}
bool fir::valueHasFirAttribute(mlir::Value value,
llvm::StringRef attributeName) {
std::optional<bool> mayHaveAttr =
valueCheckFirAttributes(value, {attributeName}, /*checkAny=*/false);
return mayHaveAttr.value_or(false);
}
bool fir::anyFuncArgsHaveAttr(mlir::func::FuncOp func, llvm::StringRef attr) {
for (unsigned i = 0, end = func.getNumArguments(); i < end; ++i)
if (func.getArgAttr(i, attr))
return true;
return false;
}
std::optional<std::int64_t> fir::getIntIfConstant(mlir::Value value) {
if (auto *definingOp = value.getDefiningOp()) {
if (auto cst = mlir::dyn_cast<mlir::arith::ConstantOp>(definingOp))
if (auto intAttr = mlir::dyn_cast<mlir::IntegerAttr>(cst.getValue()))
return intAttr.getInt();
if (auto llConstOp = mlir::dyn_cast<mlir::LLVM::ConstantOp>(definingOp))
if (auto attr = mlir::dyn_cast<mlir::IntegerAttr>(llConstOp.getValue()))
return attr.getValue().getSExtValue();
}
return {};
}
bool fir::isDummyArgument(mlir::Value v) {
auto blockArg{mlir::dyn_cast<mlir::BlockArgument>(v)};
if (!blockArg) {
auto defOp = v.getDefiningOp();
if (defOp) {
if (auto declareOp = mlir::dyn_cast<fir::DeclareOp>(defOp))
if (declareOp.getDummyScope())
return true;
}
return false;
}
auto *owner{blockArg.getOwner()};
return owner->isEntryBlock() &&
mlir::isa<mlir::FunctionOpInterface>(owner->getParentOp());
}
mlir::Type fir::applyPathToType(mlir::Type eleTy, mlir::ValueRange path) {
for (auto i = path.begin(), end = path.end(); eleTy && i < end;) {
eleTy = llvm::TypeSwitch<mlir::Type, mlir::Type>(eleTy)
.Case<fir::RecordType>([&](fir::RecordType ty) {
if (auto *op = (*i++).getDefiningOp()) {
if (auto off = mlir::dyn_cast<fir::FieldIndexOp>(op))
return ty.getType(off.getFieldName());
if (auto off = mlir::dyn_cast<mlir::arith::ConstantOp>(op))
return ty.getType(fir::toInt(off));
}
return mlir::Type{};
})
.Case<fir::SequenceType>([&](fir::SequenceType ty) {
bool valid = true;
const auto rank = ty.getDimension();
for (std::remove_const_t<decltype(rank)> ii = 0;
valid && ii < rank; ++ii)
valid = i < end && fir::isa_integer((*i++).getType());
return valid ? ty.getEleTy() : mlir::Type{};
})
.Case<mlir::TupleType>([&](mlir::TupleType ty) {
if (auto *op = (*i++).getDefiningOp())
if (auto off = mlir::dyn_cast<mlir::arith::ConstantOp>(op))
return ty.getType(fir::toInt(off));
return mlir::Type{};
})
.Case<mlir::ComplexType>([&](mlir::ComplexType ty) {
if (fir::isa_integer((*i++).getType()))
return ty.getElementType();
return mlir::Type{};
})
.Default([&](const auto &) { return mlir::Type{}; });
}
return eleTy;
}
bool fir::reboxPreservesContinuity(fir::ReboxOp rebox, bool checkWhole) {
// If slicing is not involved, then the rebox does not affect
// the continuity of the array.
auto sliceArg = rebox.getSlice();
if (!sliceArg)
return true;
if (auto sliceOp =
mlir::dyn_cast_or_null<fir::SliceOp>(sliceArg.getDefiningOp())) {
if (sliceOp.getFields().empty() && sliceOp.getSubstr().empty()) {
// TODO: generalize code for the triples analysis with
// hlfir::designatePreservesContinuity, especially when
// recognition of the whole dimension slices is added.
auto triples = sliceOp.getTriples();
assert((triples.size() % 3) == 0 && "invalid triples size");
// A slice with step=1 in the innermost dimension preserves
// the continuity of the array in the innermost dimension.
// If checkWhole is false, then check only the innermost slice triples.
std::size_t checkUpTo = checkWhole ? triples.size() : 3;
checkUpTo = std::min(checkUpTo, triples.size());
for (std::size_t i = 0; i < checkUpTo; i += 3) {
if (triples[i] != triples[i + 1]) {
// This is a section of the dimension. Only allow it
// to be the first triple.
if (i != 0)
return false;
auto constantStep = fir::getIntIfConstant(triples[i + 2]);
if (!constantStep || *constantStep != 1)
return false;
}
}
return true;
}
}
return false;
}
std::optional<int64_t> fir::getAllocaByteSize(fir::AllocaOp alloca,
const mlir::DataLayout &dl,
const fir::KindMapping &kindMap) {
mlir::Type type = alloca.getInType();
// TODO: should use the constant operands when all info is not available in
// the type.
if (!alloca.isDynamic())
if (auto sizeAndAlignment =
getTypeSizeAndAlignment(alloca.getLoc(), type, dl, kindMap))
return sizeAndAlignment->first;
return std::nullopt;
}
//===----------------------------------------------------------------------===//
// DeclareOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::DeclareOp::verify() {
auto fortranVar =
mlir::cast<fir::FortranVariableOpInterface>(this->getOperation());
return fortranVar.verifyDeclareLikeOpImpl(getMemref());
}
//===----------------------------------------------------------------------===//
// PackArrayOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::PackArrayOp::verify() {
mlir::Type arrayType = getArray().getType();
if (!validTypeParams(arrayType, getTypeparams(), /*allowParamsForBox=*/true))
return emitOpError("invalid type parameters");
if (getInnermost() && fir::getBoxRank(arrayType) == 1)
return emitOpError(
"'innermost' is invalid for 1D arrays, use 'whole' instead");
return mlir::success();
}
void fir::PackArrayOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
if (getStack())
effects.emplace_back(
mlir::MemoryEffects::Allocate::get(),
mlir::SideEffects::AutomaticAllocationScopeResource::get());
else
effects.emplace_back(mlir::MemoryEffects::Allocate::get(),
mlir::SideEffects::DefaultResource::get());
if (!getNoCopy())
effects.emplace_back(mlir::MemoryEffects::Read::get(),
mlir::SideEffects::DefaultResource::get());
}
static mlir::ParseResult
parsePackArrayConstraints(mlir::OpAsmParser &parser, mlir::IntegerAttr &maxSize,
mlir::IntegerAttr &maxElementSize,
mlir::IntegerAttr &minStride) {
mlir::OperationName opName = mlir::OperationName(
fir::PackArrayOp::getOperationName(), parser.getContext());
struct {
llvm::StringRef name;
mlir::IntegerAttr &ref;
} attributes[] = {
{fir::PackArrayOp::getMaxSizeAttrName(opName), maxSize},
{fir::PackArrayOp::getMaxElementSizeAttrName(opName), maxElementSize},
{fir::PackArrayOp::getMinStrideAttrName(opName), minStride}};
mlir::NamedAttrList parsedAttrs;
if (succeeded(parser.parseOptionalAttrDict(parsedAttrs))) {
for (auto parsedAttr : parsedAttrs) {
for (auto opAttr : attributes) {
if (parsedAttr.getName() == opAttr.name)
opAttr.ref = mlir::cast<mlir::IntegerAttr>(parsedAttr.getValue());
}
}
return mlir::success();
}
return mlir::failure();
}
static void printPackArrayConstraints(mlir::OpAsmPrinter &p,
fir::PackArrayOp &op,
const mlir::IntegerAttr &maxSize,
const mlir::IntegerAttr &maxElementSize,
const mlir::IntegerAttr &minStride) {
llvm::SmallVector<mlir::NamedAttribute> attributes;
if (maxSize)
attributes.emplace_back(op.getMaxSizeAttrName(), maxSize);
if (maxElementSize)
attributes.emplace_back(op.getMaxElementSizeAttrName(), maxElementSize);
if (minStride)
attributes.emplace_back(op.getMinStrideAttrName(), minStride);
p.printOptionalAttrDict(attributes);
}
//===----------------------------------------------------------------------===//
// UnpackArrayOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::UnpackArrayOp::verify() {
if (auto packOp = getTemp().getDefiningOp<fir::PackArrayOp>())
if (getStack() != packOp.getStack())
return emitOpError() << "the pack operation uses different memory for "
"the temporary (stack vs heap): "
<< *packOp.getOperation() << "\n";
return mlir::success();
}
void fir::UnpackArrayOp::getEffects(
llvm::SmallVectorImpl<
mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect>>
&effects) {
if (getStack())
effects.emplace_back(
mlir::MemoryEffects::Free::get(),
mlir::SideEffects::AutomaticAllocationScopeResource::get());
else
effects.emplace_back(mlir::MemoryEffects::Free::get(),
mlir::SideEffects::DefaultResource::get());
if (!getNoCopy())
effects.emplace_back(mlir::MemoryEffects::Write::get(),
mlir::SideEffects::DefaultResource::get());
}
//===----------------------------------------------------------------------===//
// IsContiguousBoxOp
//===----------------------------------------------------------------------===//
namespace {
struct SimplifyIsContiguousBoxOp
: public mlir::OpRewritePattern<fir::IsContiguousBoxOp> {
using mlir::OpRewritePattern<fir::IsContiguousBoxOp>::OpRewritePattern;
mlir::LogicalResult
matchAndRewrite(fir::IsContiguousBoxOp op,
mlir::PatternRewriter &rewriter) const override;
};
} // namespace
mlir::LogicalResult SimplifyIsContiguousBoxOp::matchAndRewrite(
fir::IsContiguousBoxOp op, mlir::PatternRewriter &rewriter) const {
auto boxType = mlir::cast<fir::BaseBoxType>(op.getBox().getType());
// Nothing to do for assumed-rank arrays and !fir.box<none>.
if (boxType.isAssumedRank() || fir::isBoxNone(boxType))
return mlir::failure();
if (fir::getBoxRank(boxType) == 0) {
// Scalars are always contiguous.
mlir::Type i1Type = rewriter.getI1Type();
rewriter.replaceOpWithNewOp<mlir::arith::ConstantOp>(
op, i1Type, rewriter.getIntegerAttr(i1Type, 1));
return mlir::success();
}
// TODO: support more patterns, e.g. a result of fir.embox without
// the slice is contiguous. We can add fir::isSimplyContiguous(box)
// that walks def-use to figure it out.
return mlir::failure();
}
void fir::IsContiguousBoxOp::getCanonicalizationPatterns(
mlir::RewritePatternSet &patterns, mlir::MLIRContext *context) {
patterns.add<SimplifyIsContiguousBoxOp>(context);
}
//===----------------------------------------------------------------------===//
// BoxTotalElementsOp
//===----------------------------------------------------------------------===//
namespace {
struct SimplifyBoxTotalElementsOp
: public mlir::OpRewritePattern<fir::BoxTotalElementsOp> {
using mlir::OpRewritePattern<fir::BoxTotalElementsOp>::OpRewritePattern;
mlir::LogicalResult
matchAndRewrite(fir::BoxTotalElementsOp op,
mlir::PatternRewriter &rewriter) const override;
};
} // namespace
mlir::LogicalResult SimplifyBoxTotalElementsOp::matchAndRewrite(
fir::BoxTotalElementsOp op, mlir::PatternRewriter &rewriter) const {
auto boxType = mlir::cast<fir::BaseBoxType>(op.getBox().getType());
// Nothing to do for assumed-rank arrays and !fir.box<none>.
if (boxType.isAssumedRank() || fir::isBoxNone(boxType))
return mlir::failure();
if (fir::getBoxRank(boxType) == 0) {
// Scalar: 1 element.
rewriter.replaceOpWithNewOp<mlir::arith::ConstantOp>(
op, op.getType(), rewriter.getIntegerAttr(op.getType(), 1));
return mlir::success();
}
// TODO: support more cases, e.g. !fir.box<!fir.array<10xi32>>.
return mlir::failure();
}
void fir::BoxTotalElementsOp::getCanonicalizationPatterns(
mlir::RewritePatternSet &patterns, mlir::MLIRContext *context) {
patterns.add<SimplifyBoxTotalElementsOp>(context);
}
//===----------------------------------------------------------------------===//
// LocalitySpecifierOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::LocalitySpecifierOp::verifyRegions() {
mlir::Type argType = getArgType();
auto verifyTerminator = [&](mlir::Operation *terminator,
bool yieldsValue) -> llvm::LogicalResult {
if (!terminator->getBlock()->getSuccessors().empty())
return llvm::success();
if (!llvm::isa<fir::YieldOp>(terminator))
return mlir::emitError(terminator->getLoc())
<< "expected exit block terminator to be an `fir.yield` op.";
YieldOp yieldOp = llvm::cast<YieldOp>(terminator);
mlir::TypeRange yieldedTypes = yieldOp.getResults().getTypes();
if (!yieldsValue) {
if (yieldedTypes.empty())
return llvm::success();
return mlir::emitError(terminator->getLoc())
<< "Did not expect any values to be yielded.";
}
if (yieldedTypes.size() == 1 && yieldedTypes.front() == argType)
return llvm::success();
auto error = mlir::emitError(yieldOp.getLoc())
<< "Invalid yielded value. Expected type: " << argType
<< ", got: ";
if (yieldedTypes.empty())
error << "None";
else
error << yieldedTypes;
return error;
};
auto verifyRegion = [&](mlir::Region &region, unsigned expectedNumArgs,
llvm::StringRef regionName,
bool yieldsValue) -> llvm::LogicalResult {
assert(!region.empty());
if (region.getNumArguments() != expectedNumArgs)
return mlir::emitError(region.getLoc())
<< "`" << regionName << "`: "
<< "expected " << expectedNumArgs
<< " region arguments, got: " << region.getNumArguments();
for (mlir::Block &block : region) {
// MLIR will verify the absence of the terminator for us.
if (!block.mightHaveTerminator())
continue;
if (failed(verifyTerminator(block.getTerminator(), yieldsValue)))
return llvm::failure();
}
return llvm::success();
};
// Ensure all of the region arguments have the same type
for (mlir::Region *region : getRegions())
for (mlir::Type ty : region->getArgumentTypes())
if (ty != argType)
return emitError() << "Region argument type mismatch: got " << ty
<< " expected " << argType << ".";
mlir::Region &initRegion = getInitRegion();
if (!initRegion.empty() &&
failed(verifyRegion(getInitRegion(), /*expectedNumArgs=*/2, "init",
/*yieldsValue=*/true)))
return llvm::failure();
LocalitySpecifierType dsType = getLocalitySpecifierType();
if (dsType == LocalitySpecifierType::Local && !getCopyRegion().empty())
return emitError("`local` specifiers do not require a `copy` region.");
if (dsType == LocalitySpecifierType::LocalInit && getCopyRegion().empty())
return emitError(
"`local_init` specifiers require at least a `copy` region.");
if (dsType == LocalitySpecifierType::LocalInit &&
failed(verifyRegion(getCopyRegion(), /*expectedNumArgs=*/2, "copy",
/*yieldsValue=*/true)))
return llvm::failure();
if (!getDeallocRegion().empty() &&
failed(verifyRegion(getDeallocRegion(), /*expectedNumArgs=*/1, "dealloc",
/*yieldsValue=*/false)))
return llvm::failure();
return llvm::success();
}
//===----------------------------------------------------------------------===//
// DoConcurrentOp
//===----------------------------------------------------------------------===//
llvm::LogicalResult fir::DoConcurrentOp::verify() {
mlir::Block *body = getBody();
if (body->empty())
return emitOpError("body cannot be empty");
if (!body->mightHaveTerminator() ||
!mlir::isa<fir::DoConcurrentLoopOp>(body->getTerminator()))
return emitOpError("must be terminated by 'fir.do_concurrent.loop'");
return mlir::success();
}
//===----------------------------------------------------------------------===//
// DoConcurrentLoopOp
//===----------------------------------------------------------------------===//
mlir::ParseResult fir::DoConcurrentLoopOp::parse(mlir::OpAsmParser &parser,
mlir::OperationState &result) {
auto &builder = parser.getBuilder();
// Parse an opening `(` followed by induction variables followed by `)`
llvm::SmallVector<mlir::OpAsmParser::Argument, 4> regionArgs;
if (parser.parseArgumentList(regionArgs, mlir::OpAsmParser::Delimiter::Paren))
return mlir::failure();
llvm::SmallVector<mlir::Type> argTypes(regionArgs.size(),
builder.getIndexType());
// Parse loop bounds.
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand, 4> lower;
if (parser.parseEqual() ||
parser.parseOperandList(lower, regionArgs.size(),
mlir::OpAsmParser::Delimiter::Paren) ||
parser.resolveOperands(lower, builder.getIndexType(), result.operands))
return mlir::failure();
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand, 4> upper;
if (parser.parseKeyword("to") ||
parser.parseOperandList(upper, regionArgs.size(),
mlir::OpAsmParser::Delimiter::Paren) ||
parser.resolveOperands(upper, builder.getIndexType(), result.operands))
return mlir::failure();
// Parse step values.
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand, 4> steps;
if (parser.parseKeyword("step") ||
parser.parseOperandList(steps, regionArgs.size(),
mlir::OpAsmParser::Delimiter::Paren) ||
parser.resolveOperands(steps, builder.getIndexType(), result.operands))
return mlir::failure();
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> reduceOperands;
llvm::SmallVector<mlir::Type> reduceArgTypes;
if (succeeded(parser.parseOptionalKeyword("reduce"))) {
// Parse reduction attributes and variables.
llvm::SmallVector<fir::ReduceAttr> attributes;
if (failed(parser.parseCommaSeparatedList(
mlir::AsmParser::Delimiter::Paren, [&]() {
if (parser.parseAttribute(attributes.emplace_back()) ||
parser.parseArrow() ||
parser.parseOperand(reduceOperands.emplace_back()) ||
parser.parseColonType(reduceArgTypes.emplace_back()))
return mlir::failure();
return mlir::success();
})))
return mlir::failure();
// Resolve input operands.
for (auto operand_type : llvm::zip(reduceOperands, reduceArgTypes))
if (parser.resolveOperand(std::get<0>(operand_type),
std::get<1>(operand_type), result.operands))
return mlir::failure();
llvm::SmallVector<mlir::Attribute> arrayAttr(attributes.begin(),
attributes.end());
result.addAttribute(getReduceAttrsAttrName(result.name),
builder.getArrayAttr(arrayAttr));
}
llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> localOperands;
if (succeeded(parser.parseOptionalKeyword("local"))) {
std::size_t oldArgTypesSize = argTypes.size();
if (failed(parser.parseLParen()))
return mlir::failure();
llvm::SmallVector<mlir::SymbolRefAttr> localSymbolVec;
if (failed(parser.parseCommaSeparatedList([&]() {
if (failed(parser.parseAttribute(localSymbolVec.emplace_back())))
return mlir::failure();
if (parser.parseOperand(localOperands.emplace_back()) ||
parser.parseArrow() ||
parser.parseArgument(regionArgs.emplace_back()))
return mlir::failure();
return mlir::success();
})))
return mlir::failure();
if (failed(parser.parseColon()))
return mlir::failure();
if (failed(parser.parseCommaSeparatedList([&]() {
if (failed(parser.parseType(argTypes.emplace_back())))
return mlir::failure();
return mlir::success();
})))
return mlir::failure();
if (regionArgs.size() != argTypes.size())
return parser.emitError(parser.getNameLoc(),
"mismatch in number of local arg and types");
if (failed(parser.parseRParen()))
return mlir::failure();
for (auto operandType : llvm::zip_equal(
localOperands, llvm::drop_begin(argTypes, oldArgTypesSize)))
if (parser.resolveOperand(std::get<0>(operandType),
std::get<1>(operandType), result.operands))
return mlir::failure();
llvm::SmallVector<mlir::Attribute> symbolAttrs(localSymbolVec.begin(),
localSymbolVec.end());
result.addAttribute(getLocalSymsAttrName(result.name),
builder.getArrayAttr(symbolAttrs));
}
// Set `operandSegmentSizes` attribute.
result.addAttribute(DoConcurrentLoopOp::getOperandSegmentSizeAttr(),
builder.getDenseI32ArrayAttr(
{static_cast<int32_t>(lower.size()),
static_cast<int32_t>(upper.size()),
static_cast<int32_t>(steps.size()),
static_cast<int32_t>(reduceOperands.size()),
static_cast<int32_t>(localOperands.size())}));
// Now parse the body.
for (auto [arg, type] : llvm::zip_equal(regionArgs, argTypes))
arg.type = type;
mlir::Region *body = result.addRegion();
if (parser.parseRegion(*body, regionArgs))
return mlir::failure();
// Parse attributes.
if (parser.parseOptionalAttrDict(result.attributes))
return mlir::failure();
return mlir::success();
}
void fir::DoConcurrentLoopOp::print(mlir::OpAsmPrinter &p) {
p << " (" << getBody()->getArguments().slice(0, getNumInductionVars())
<< ") = (" << getLowerBound() << ") to (" << getUpperBound() << ") step ("
<< getStep() << ")";
if (!getReduceOperands().empty()) {
p << " reduce(";
auto attrs = getReduceAttrsAttr();
auto operands = getReduceOperands();
llvm::interleaveComma(llvm::zip(attrs, operands), p, [&](auto it) {
p << std::get<0>(it) << " -> " << std::get<1>(it) << " : "
<< std::get<1>(it).getType();
});
p << ')';
}
if (!getLocalVars().empty()) {
p << " local(";
llvm::interleaveComma(llvm::zip_equal(getLocalSymsAttr(), getLocalVars(),
getRegionLocalArgs()),
p, [&](auto it) {
p << std::get<0>(it) << " " << std::get<1>(it)
<< " -> " << std::get<2>(it);
});
p << " : ";
llvm::interleaveComma(getLocalVars(), p,
[&](auto it) { p << it.getType(); });
p << ")";
}
p << ' ';
p.printRegion(getRegion(), /*printEntryBlockArgs=*/false);
p.printOptionalAttrDict(
(*this)->getAttrs(),
/*elidedAttrs=*/{DoConcurrentLoopOp::getOperandSegmentSizeAttr(),
DoConcurrentLoopOp::getReduceAttrsAttrName(),
DoConcurrentLoopOp::getLocalSymsAttrName()});
}
llvm::SmallVector<mlir::Region *> fir::DoConcurrentLoopOp::getLoopRegions() {
return {&getRegion()};
}
llvm::LogicalResult fir::DoConcurrentLoopOp::verify() {
mlir::Operation::operand_range lbValues = getLowerBound();
mlir::Operation::operand_range ubValues = getUpperBound();
mlir::Operation::operand_range stepValues = getStep();
mlir::Operation::operand_range localVars = getLocalVars();
if (lbValues.empty())
return emitOpError(
"needs at least one tuple element for lowerBound, upperBound and step");
if (lbValues.size() != ubValues.size() ||
ubValues.size() != stepValues.size())
return emitOpError("different number of tuple elements for lowerBound, "
"upperBound or step");
// Check that the body defines the same number of block arguments as the
// number of tuple elements in step.
mlir::Block *body = getBody();
unsigned numIndVarArgs = body->getNumArguments() - localVars.size();
if (numIndVarArgs != stepValues.size())
return emitOpError() << "expects the same number of induction variables: "
<< body->getNumArguments()
<< " as bound and step values: " << stepValues.size();
for (auto arg : body->getArguments().slice(0, numIndVarArgs))
if (!arg.getType().isIndex())
return emitOpError(
"expects arguments for the induction variable to be of index type");
auto reduceAttrs = getReduceAttrsAttr();
if (getNumReduceOperands() != (reduceAttrs ? reduceAttrs.size() : 0))
return emitOpError(
"mismatch in number of reduction variables and reduction attributes");
return mlir::success();
}
std::optional<llvm::SmallVector<mlir::Value>>
fir::DoConcurrentLoopOp::getLoopInductionVars() {
return llvm::SmallVector<mlir::Value>{
getBody()->getArguments().slice(0, getLowerBound().size())};
}
//===----------------------------------------------------------------------===//
// FIROpsDialect
//===----------------------------------------------------------------------===//
void fir::FIROpsDialect::registerOpExternalInterfaces() {
// Attach default declare target interfaces to operations which can be marked
// as declare target.
fir::GlobalOp::attachInterface<
mlir::omp::DeclareTargetDefaultModel<fir::GlobalOp>>(*getContext());
}
// Tablegen operators
#define GET_OP_CLASSES
#include "flang/Optimizer/Dialect/FIROps.cpp.inc"
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