
This patch updates fir.coordinate_op to carry the field index as attributes instead of relying on getting it from the fir.field_index operations defining its operands. The rational is that FIR currently has a few operations that require DAGs to be preserved in order to be able to do code generation. This is the case of fir.coordinate_op, which requires its fir.field operand producer to be visible. This makes IR transformation harder/brittle, so I want to update FIR to get rid if this. Codegen/printer/parser of fir.coordinate_of and many tests need to be updated after this change.
4559 lines
180 KiB
C++
4559 lines
180 KiB
C++
//===-- FIROps.cpp --------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// Coding style: https://mlir.llvm.org/getting_started/DeveloperGuide/
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//
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//===----------------------------------------------------------------------===//
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#include "flang/Optimizer/Dialect/FIROps.h"
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#include "flang/Optimizer/Dialect/FIRAttr.h"
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#include "flang/Optimizer/Dialect/FIRDialect.h"
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#include "flang/Optimizer/Dialect/FIROpsSupport.h"
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#include "flang/Optimizer/Dialect/FIRType.h"
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#include "flang/Optimizer/Dialect/Support/FIRContext.h"
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#include "flang/Optimizer/Dialect/Support/KindMapping.h"
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#include "flang/Optimizer/Support/Utils.h"
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#include "mlir/Dialect/CommonFolders.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/OpenACC/OpenACC.h"
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#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
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#include "mlir/IR/Attributes.h"
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#include "mlir/IR/BuiltinAttributes.h"
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#include "mlir/IR/BuiltinOps.h"
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#include "mlir/IR/Diagnostics.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/IR/OpDefinition.h"
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#include "mlir/IR/PatternMatch.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/ADT/TypeSwitch.h"
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namespace {
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#include "flang/Optimizer/Dialect/CanonicalizationPatterns.inc"
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} // namespace
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static void propagateAttributes(mlir::Operation *fromOp,
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mlir::Operation *toOp) {
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if (!fromOp || !toOp)
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return;
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for (mlir::NamedAttribute attr : fromOp->getAttrs()) {
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if (attr.getName().getValue().starts_with(
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mlir::acc::OpenACCDialect::getDialectNamespace()))
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toOp->setAttr(attr.getName(), attr.getValue());
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}
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}
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/// Return true if a sequence type is of some incomplete size or a record type
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/// is malformed or contains an incomplete sequence type. An incomplete sequence
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/// type is one with more unknown extents in the type than have been provided
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/// via `dynamicExtents`. Sequence types with an unknown rank are incomplete by
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/// definition.
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static bool verifyInType(mlir::Type inType,
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llvm::SmallVectorImpl<llvm::StringRef> &visited,
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unsigned dynamicExtents = 0) {
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if (auto st = mlir::dyn_cast<fir::SequenceType>(inType)) {
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auto shape = st.getShape();
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if (shape.size() == 0)
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return true;
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for (std::size_t i = 0, end = shape.size(); i < end; ++i) {
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if (shape[i] != fir::SequenceType::getUnknownExtent())
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continue;
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if (dynamicExtents-- == 0)
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return true;
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}
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} else if (auto rt = mlir::dyn_cast<fir::RecordType>(inType)) {
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// don't recurse if we're already visiting this one
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if (llvm::is_contained(visited, rt.getName()))
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return false;
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// keep track of record types currently being visited
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visited.push_back(rt.getName());
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for (auto &field : rt.getTypeList())
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if (verifyInType(field.second, visited))
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return true;
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visited.pop_back();
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}
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return false;
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}
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static bool verifyTypeParamCount(mlir::Type inType, unsigned numParams) {
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auto ty = fir::unwrapSequenceType(inType);
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if (numParams > 0) {
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if (auto recTy = mlir::dyn_cast<fir::RecordType>(ty))
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return numParams != recTy.getNumLenParams();
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if (auto chrTy = mlir::dyn_cast<fir::CharacterType>(ty))
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return !(numParams == 1 && chrTy.hasDynamicLen());
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return true;
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}
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if (auto chrTy = mlir::dyn_cast<fir::CharacterType>(ty))
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return !chrTy.hasConstantLen();
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return false;
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}
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/// Parser shared by Alloca and Allocmem
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///
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/// operation ::= %res = (`fir.alloca` | `fir.allocmem`) $in_type
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/// ( `(` $typeparams `)` )? ( `,` $shape )?
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/// attr-dict-without-keyword
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template <typename FN>
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static mlir::ParseResult parseAllocatableOp(FN wrapResultType,
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mlir::OpAsmParser &parser,
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mlir::OperationState &result) {
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mlir::Type intype;
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if (parser.parseType(intype))
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return mlir::failure();
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auto &builder = parser.getBuilder();
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result.addAttribute("in_type", mlir::TypeAttr::get(intype));
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llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand> operands;
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llvm::SmallVector<mlir::Type> typeVec;
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bool hasOperands = false;
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std::int32_t typeparamsSize = 0;
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if (!parser.parseOptionalLParen()) {
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// parse the LEN params of the derived type. (<params> : <types>)
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if (parser.parseOperandList(operands, mlir::OpAsmParser::Delimiter::None) ||
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parser.parseColonTypeList(typeVec) || parser.parseRParen())
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return mlir::failure();
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typeparamsSize = operands.size();
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hasOperands = true;
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}
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std::int32_t shapeSize = 0;
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if (!parser.parseOptionalComma()) {
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// parse size to scale by, vector of n dimensions of type index
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if (parser.parseOperandList(operands, mlir::OpAsmParser::Delimiter::None))
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return mlir::failure();
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shapeSize = operands.size() - typeparamsSize;
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auto idxTy = builder.getIndexType();
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for (std::int32_t i = typeparamsSize, end = operands.size(); i != end; ++i)
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typeVec.push_back(idxTy);
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hasOperands = true;
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}
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if (hasOperands &&
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parser.resolveOperands(operands, typeVec, parser.getNameLoc(),
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result.operands))
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return mlir::failure();
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mlir::Type restype = wrapResultType(intype);
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if (!restype) {
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parser.emitError(parser.getNameLoc(), "invalid allocate type: ") << intype;
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return mlir::failure();
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}
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result.addAttribute("operandSegmentSizes", builder.getDenseI32ArrayAttr(
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{typeparamsSize, shapeSize}));
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if (parser.parseOptionalAttrDict(result.attributes) ||
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parser.addTypeToList(restype, result.types))
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return mlir::failure();
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return mlir::success();
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}
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template <typename OP>
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static void printAllocatableOp(mlir::OpAsmPrinter &p, OP &op) {
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p << ' ' << op.getInType();
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if (!op.getTypeparams().empty()) {
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p << '(' << op.getTypeparams() << " : " << op.getTypeparams().getTypes()
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<< ')';
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}
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// print the shape of the allocation (if any); all must be index type
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for (auto sh : op.getShape()) {
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p << ", ";
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p.printOperand(sh);
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}
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p.printOptionalAttrDict(op->getAttrs(), {"in_type", "operandSegmentSizes"});
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}
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//===----------------------------------------------------------------------===//
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// AllocaOp
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//===----------------------------------------------------------------------===//
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/// Create a legal memory reference as return type
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static mlir::Type wrapAllocaResultType(mlir::Type intype) {
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// FIR semantics: memory references to memory references are disallowed
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if (mlir::isa<fir::ReferenceType>(intype))
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return {};
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return fir::ReferenceType::get(intype);
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}
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mlir::Type fir::AllocaOp::getAllocatedType() {
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return mlir::cast<fir::ReferenceType>(getType()).getEleTy();
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}
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mlir::Type fir::AllocaOp::getRefTy(mlir::Type ty) {
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return fir::ReferenceType::get(ty);
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}
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void fir::AllocaOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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llvm::StringRef uniqName, mlir::ValueRange typeparams,
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mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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auto nameAttr = builder.getStringAttr(uniqName);
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build(builder, result, wrapAllocaResultType(inType), inType, nameAttr, {},
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/*pinned=*/false, typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocaOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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llvm::StringRef uniqName, bool pinned,
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mlir::ValueRange typeparams, mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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auto nameAttr = builder.getStringAttr(uniqName);
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build(builder, result, wrapAllocaResultType(inType), inType, nameAttr, {},
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pinned, typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocaOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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llvm::StringRef uniqName, llvm::StringRef bindcName,
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mlir::ValueRange typeparams, mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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auto nameAttr =
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uniqName.empty() ? mlir::StringAttr{} : builder.getStringAttr(uniqName);
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auto bindcAttr =
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bindcName.empty() ? mlir::StringAttr{} : builder.getStringAttr(bindcName);
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build(builder, result, wrapAllocaResultType(inType), inType, nameAttr,
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bindcAttr, /*pinned=*/false, typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocaOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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llvm::StringRef uniqName, llvm::StringRef bindcName,
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bool pinned, mlir::ValueRange typeparams,
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mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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auto nameAttr =
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uniqName.empty() ? mlir::StringAttr{} : builder.getStringAttr(uniqName);
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auto bindcAttr =
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bindcName.empty() ? mlir::StringAttr{} : builder.getStringAttr(bindcName);
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build(builder, result, wrapAllocaResultType(inType), inType, nameAttr,
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bindcAttr, pinned, typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocaOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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mlir::ValueRange typeparams, mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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build(builder, result, wrapAllocaResultType(inType), inType, {}, {},
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/*pinned=*/false, typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocaOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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bool pinned, mlir::ValueRange typeparams,
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mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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build(builder, result, wrapAllocaResultType(inType), inType, {}, {}, pinned,
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typeparams, shape);
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result.addAttributes(attributes);
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}
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mlir::ParseResult fir::AllocaOp::parse(mlir::OpAsmParser &parser,
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mlir::OperationState &result) {
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return parseAllocatableOp(wrapAllocaResultType, parser, result);
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}
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void fir::AllocaOp::print(mlir::OpAsmPrinter &p) {
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printAllocatableOp(p, *this);
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}
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llvm::LogicalResult fir::AllocaOp::verify() {
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llvm::SmallVector<llvm::StringRef> visited;
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if (verifyInType(getInType(), visited, numShapeOperands()))
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return emitOpError("invalid type for allocation");
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if (verifyTypeParamCount(getInType(), numLenParams()))
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return emitOpError("LEN params do not correspond to type");
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mlir::Type outType = getType();
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if (!mlir::isa<fir::ReferenceType>(outType))
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return emitOpError("must be a !fir.ref type");
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return mlir::success();
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}
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bool fir::AllocaOp::ownsNestedAlloca(mlir::Operation *op) {
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return op->hasTrait<mlir::OpTrait::IsIsolatedFromAbove>() ||
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op->hasTrait<mlir::OpTrait::AutomaticAllocationScope>() ||
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mlir::isa<mlir::LoopLikeOpInterface>(*op);
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}
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mlir::Region *fir::AllocaOp::getOwnerRegion() {
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mlir::Operation *currentOp = getOperation();
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while (mlir::Operation *parentOp = currentOp->getParentOp()) {
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// If the operation was not registered, inquiries about its traits will be
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// incorrect and it is not possible to reason about the operation. This
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// should not happen in a normal Fortran compilation flow, but be foolproof.
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if (!parentOp->isRegistered())
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return nullptr;
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if (fir::AllocaOp::ownsNestedAlloca(parentOp))
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return currentOp->getParentRegion();
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currentOp = parentOp;
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}
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return nullptr;
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}
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//===----------------------------------------------------------------------===//
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// AllocMemOp
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//===----------------------------------------------------------------------===//
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/// Create a legal heap reference as return type
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static mlir::Type wrapAllocMemResultType(mlir::Type intype) {
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// Fortran semantics: C852 an entity cannot be both ALLOCATABLE and POINTER
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// 8.5.3 note 1 prohibits ALLOCATABLE procedures as well
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// FIR semantics: one may not allocate a memory reference value
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if (mlir::isa<fir::ReferenceType, fir::HeapType, fir::PointerType,
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mlir::FunctionType>(intype))
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return {};
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return fir::HeapType::get(intype);
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}
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mlir::Type fir::AllocMemOp::getAllocatedType() {
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return mlir::cast<fir::HeapType>(getType()).getEleTy();
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}
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mlir::Type fir::AllocMemOp::getRefTy(mlir::Type ty) {
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return fir::HeapType::get(ty);
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}
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void fir::AllocMemOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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llvm::StringRef uniqName,
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mlir::ValueRange typeparams, mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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auto nameAttr = builder.getStringAttr(uniqName);
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build(builder, result, wrapAllocMemResultType(inType), inType, nameAttr, {},
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typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocMemOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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llvm::StringRef uniqName, llvm::StringRef bindcName,
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mlir::ValueRange typeparams, mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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auto nameAttr = builder.getStringAttr(uniqName);
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auto bindcAttr = builder.getStringAttr(bindcName);
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build(builder, result, wrapAllocMemResultType(inType), inType, nameAttr,
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bindcAttr, typeparams, shape);
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result.addAttributes(attributes);
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}
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void fir::AllocMemOp::build(mlir::OpBuilder &builder,
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mlir::OperationState &result, mlir::Type inType,
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mlir::ValueRange typeparams, mlir::ValueRange shape,
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llvm::ArrayRef<mlir::NamedAttribute> attributes) {
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build(builder, result, wrapAllocMemResultType(inType), inType, {}, {},
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typeparams, shape);
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result.addAttributes(attributes);
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}
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mlir::ParseResult fir::AllocMemOp::parse(mlir::OpAsmParser &parser,
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mlir::OperationState &result) {
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return parseAllocatableOp(wrapAllocMemResultType, parser, result);
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}
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void fir::AllocMemOp::print(mlir::OpAsmPrinter &p) {
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printAllocatableOp(p, *this);
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}
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llvm::LogicalResult fir::AllocMemOp::verify() {
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llvm::SmallVector<llvm::StringRef> visited;
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if (verifyInType(getInType(), visited, numShapeOperands()))
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return emitOpError("invalid type for allocation");
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if (verifyTypeParamCount(getInType(), numLenParams()))
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return emitOpError("LEN params do not correspond to type");
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mlir::Type outType = getType();
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if (!mlir::dyn_cast<fir::HeapType>(outType))
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return emitOpError("must be a !fir.heap type");
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if (fir::isa_unknown_size_box(fir::dyn_cast_ptrEleTy(outType)))
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return emitOpError("cannot allocate !fir.box of unknown rank or type");
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return mlir::success();
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}
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//===----------------------------------------------------------------------===//
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// ArrayCoorOp
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//===----------------------------------------------------------------------===//
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// CHARACTERs and derived types with LEN PARAMETERs are dependent types that
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// require runtime values to fully define the type of an object.
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static bool validTypeParams(mlir::Type dynTy, mlir::ValueRange typeParams) {
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dynTy = fir::unwrapAllRefAndSeqType(dynTy);
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// A box value will contain type parameter values itself.
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if (mlir::isa<fir::BoxType>(dynTy))
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return typeParams.size() == 0;
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// Derived type must have all type parameters satisfied.
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if (auto recTy = mlir::dyn_cast<fir::RecordType>(dynTy))
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return typeParams.size() == recTy.getNumLenParams();
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// Characters with non-constant LEN must have a type parameter value.
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if (auto charTy = mlir::dyn_cast<fir::CharacterType>(dynTy))
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if (charTy.hasDynamicLen())
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return typeParams.size() == 1;
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// Otherwise, any type parameters are invalid.
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return typeParams.size() == 0;
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}
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llvm::LogicalResult fir::ArrayCoorOp::verify() {
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auto eleTy = fir::dyn_cast_ptrOrBoxEleTy(getMemref().getType());
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auto arrTy = mlir::dyn_cast<fir::SequenceType>(eleTy);
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if (!arrTy)
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return emitOpError("must be a reference to an array");
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auto arrDim = arrTy.getDimension();
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if (auto shapeOp = getShape()) {
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auto shapeTy = shapeOp.getType();
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unsigned shapeTyRank = 0;
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if (auto s = mlir::dyn_cast<fir::ShapeType>(shapeTy)) {
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shapeTyRank = s.getRank();
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} else if (auto ss = mlir::dyn_cast<fir::ShapeShiftType>(shapeTy)) {
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shapeTyRank = ss.getRank();
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} else {
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auto s = mlir::cast<fir::ShiftType>(shapeTy);
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shapeTyRank = s.getRank();
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// TODO: it looks like PreCGRewrite and CodeGen can support
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// fir.shift with plain array reference, so we may consider
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// removing this check.
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if (!mlir::isa<fir::BaseBoxType>(getMemref().getType()))
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return emitOpError("shift can only be provided with fir.box memref");
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}
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if (arrDim && arrDim != shapeTyRank)
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return emitOpError("rank of dimension mismatched");
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// TODO: support slicing with changing the number of dimensions,
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// e.g. when array_coor represents an element access to array(:,1,:)
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// slice: the shape is 3D and the number of indices is 2 in this case.
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if (shapeTyRank != getIndices().size())
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return emitOpError("number of indices do not match dim rank");
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}
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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 {};
|
|
}
|
|
|
|
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();
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// 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);
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// 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);
|
|
}
|
|
|
|
llvm::LogicalResult fir::ConvertOp::verify() {
|
|
if (canBeConverted(getValue().getType(), getType()))
|
|
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
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
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");
|
|
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();
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// 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();
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// 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, {});
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// 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> ®ions) {
|
|
// 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> ®ions) {
|
|
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 (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 (!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());
|
|
}
|
|
|
|
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()));
|
|
if (!boxType)
|
|
return emitOpError("box_ref operand must have !fir.ref<!fir.box<T>> type");
|
|
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;
|
|
}
|
|
|
|
llvm::LogicalResult fir::DeclareOp::verify() {
|
|
auto fortranVar =
|
|
mlir::cast<fir::FortranVariableOpInterface>(this->getOperation());
|
|
return fortranVar.verifyDeclareLikeOpImpl(getMemref());
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// 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"
|