llvm-project/mlir/lib/IR/MLIRContext.cpp

1572 lines
56 KiB
C++

//===- MLIRContext.cpp - MLIR Type Classes --------------------------------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
#include "mlir/IR/MLIRContext.h"
#include "AffineExprDetail.h"
#include "AffineMapDetail.h"
#include "AttributeDetail.h"
#include "AttributeListStorage.h"
#include "IntegerSetDetail.h"
#include "LocationDetail.h"
#include "TypeDetail.h"
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/Function.h"
#include "mlir/IR/Identifier.h"
#include "mlir/IR/IntegerSet.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/Types.h"
#include "mlir/Support/MathExtras.h"
#include "mlir/Support/STLExtras.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/StringMap.h"
#include "llvm/Support/Allocator.h"
#include "llvm/Support/raw_ostream.h"
#include <memory>
using namespace mlir;
using namespace mlir::detail;
using namespace llvm;
namespace {
struct AffineMapKeyInfo : DenseMapInfo<AffineMap> {
// Affine maps are uniqued based on their dim/symbol counts and affine
// expressions.
using KeyTy = std::tuple<unsigned, unsigned, ArrayRef<AffineExpr>,
ArrayRef<AffineExpr>>;
using DenseMapInfo<AffineMap>::isEqual;
static unsigned getHashValue(const AffineMap &key) {
return getHashValue(KeyTy(key.getNumDims(), key.getNumSymbols(),
key.getResults(), key.getRangeSizes()));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(
std::get<0>(key), std::get<1>(key),
hash_combine_range(std::get<2>(key).begin(), std::get<2>(key).end()),
hash_combine_range(std::get<3>(key).begin(), std::get<3>(key).end()));
}
static bool isEqual(const KeyTy &lhs, AffineMap rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == std::make_tuple(rhs.getNumDims(), rhs.getNumSymbols(),
rhs.getResults(), rhs.getRangeSizes());
}
};
struct IntegerSetKeyInfo : DenseMapInfo<IntegerSet> {
// Integer sets are uniqued based on their dim/symbol counts, affine
// expressions appearing in the LHS of constraints, and eqFlags.
using KeyTy =
std::tuple<unsigned, unsigned, ArrayRef<AffineExpr>, ArrayRef<bool>>;
using DenseMapInfo<IntegerSet>::isEqual;
static unsigned getHashValue(const IntegerSet &key) {
return getHashValue(KeyTy(key.getNumDims(), key.getNumSymbols(),
key.getConstraints(), key.getEqFlags()));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(
std::get<0>(key), std::get<1>(key),
hash_combine_range(std::get<2>(key).begin(), std::get<2>(key).end()),
hash_combine_range(std::get<3>(key).begin(), std::get<3>(key).end()));
}
static bool isEqual(const KeyTy &lhs, IntegerSet rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == std::make_tuple(rhs.getNumDims(), rhs.getNumSymbols(),
rhs.getConstraints(), rhs.getEqFlags());
}
};
struct FloatAttrKeyInfo : DenseMapInfo<FloatAttributeStorage *> {
// Float attributes are uniqued based on wrapped APFloat.
using KeyTy = std::pair<Type, APFloat>;
using DenseMapInfo<FloatAttributeStorage *>::isEqual;
static unsigned getHashValue(FloatAttributeStorage *key) {
return getHashValue(KeyTy(key->type, key->getValue()));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(key.first, llvm::hash_value(key.second));
}
static bool isEqual(const KeyTy &lhs, const FloatAttributeStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs.first == rhs->type && lhs.second.bitwiseIsEqual(rhs->getValue());
}
};
struct IntegerAttrKeyInfo : DenseMapInfo<IntegerAttributeStorage *> {
// Integer attributes are uniqued based on wrapped APInt.
using KeyTy = std::pair<Type, APInt>;
using DenseMapInfo<IntegerAttributeStorage *>::isEqual;
static unsigned getHashValue(IntegerAttributeStorage *key) {
return getHashValue(KeyTy(key->type, key->getValue()));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(key.first, llvm::hash_value(key.second));
}
static bool isEqual(const KeyTy &lhs, const IntegerAttributeStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
assert(lhs.first.isIndex() ||
(lhs.first.isa<IntegerType>() &&
lhs.first.cast<IntegerType>().getWidth() ==
lhs.second.getBitWidth()) &&
"mismatching integer type and value bitwidth");
return lhs.first == rhs->type && lhs.second == rhs->getValue();
}
};
struct ArrayAttrKeyInfo : DenseMapInfo<ArrayAttributeStorage *> {
// Array attributes are uniqued based on their elements.
using KeyTy = ArrayRef<Attribute>;
using DenseMapInfo<ArrayAttributeStorage *>::isEqual;
static unsigned getHashValue(ArrayAttributeStorage *key) {
return getHashValue(KeyTy(key->value));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine_range(key.begin(), key.end());
}
static bool isEqual(const KeyTy &lhs, const ArrayAttributeStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == rhs->value;
}
};
struct AttributeListKeyInfo : DenseMapInfo<AttributeListStorage *> {
// Array attributes are uniqued based on their elements.
using KeyTy = ArrayRef<NamedAttribute>;
using DenseMapInfo<AttributeListStorage *>::isEqual;
static unsigned getHashValue(AttributeListStorage *key) {
return getHashValue(KeyTy(key->getElements()));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine_range(key.begin(), key.end());
}
static bool isEqual(const KeyTy &lhs, const AttributeListStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == rhs->getElements();
}
};
struct DenseElementsAttrInfo : DenseMapInfo<DenseElementsAttributeStorage *> {
using KeyTy = std::pair<VectorOrTensorType, ArrayRef<char>>;
using DenseMapInfo<DenseElementsAttributeStorage *>::isEqual;
static unsigned getHashValue(DenseElementsAttributeStorage *key) {
return getHashValue(KeyTy(key->type, key->data));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(
key.first, hash_combine_range(key.second.begin(), key.second.end()));
}
static bool isEqual(const KeyTy &lhs,
const DenseElementsAttributeStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == std::make_pair(rhs->type, rhs->data);
}
};
struct OpaqueElementsAttrInfo : DenseMapInfo<OpaqueElementsAttributeStorage *> {
using KeyTy = std::pair<VectorOrTensorType, StringRef>;
using DenseMapInfo<OpaqueElementsAttributeStorage *>::isEqual;
static unsigned getHashValue(OpaqueElementsAttributeStorage *key) {
return getHashValue(KeyTy(key->type, key->bytes));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(
key.first, hash_combine_range(key.second.begin(), key.second.end()));
}
static bool isEqual(const KeyTy &lhs,
const OpaqueElementsAttributeStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == std::make_pair(rhs->type, rhs->bytes);
}
};
struct CallSiteLocationKeyInfo : DenseMapInfo<CallSiteLocationStorage *> {
// Call locations are uniqued based on their held concret location
// and the caller location.
using KeyTy = std::pair<Location, Location>;
using DenseMapInfo<CallSiteLocationStorage *>::isEqual;
static unsigned getHashValue(CallSiteLocationStorage *key) {
return getHashValue(KeyTy(key->callee, key->caller));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(key.first, key.second);
}
static bool isEqual(const KeyTy &lhs, const CallSiteLocationStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == std::make_pair(rhs->callee, rhs->caller);
}
};
struct FusedLocKeyInfo : DenseMapInfo<FusedLocationStorage *> {
// Fused locations are uniqued based on their held locations and an optional
// metadata attribute.
using KeyTy = std::pair<ArrayRef<Location>, Attribute>;
using DenseMapInfo<FusedLocationStorage *>::isEqual;
static unsigned getHashValue(FusedLocationStorage *key) {
return getHashValue(KeyTy(key->getLocations(), key->metadata));
}
static unsigned getHashValue(KeyTy key) {
return hash_combine(hash_combine_range(key.first.begin(), key.first.end()),
key.second);
}
static bool isEqual(const KeyTy &lhs, const FusedLocationStorage *rhs) {
if (rhs == getEmptyKey() || rhs == getTombstoneKey())
return false;
return lhs == std::make_pair(rhs->getLocations(), rhs->metadata);
}
};
} // end anonymous namespace.
namespace mlir {
/// This is the implementation of the MLIRContext class, using the pImpl idiom.
/// This class is completely private to this file, so everything is public.
class MLIRContextImpl {
public:
/// We put location info into this allocator, since it is generally not
/// touched by compiler passes.
llvm::BumpPtrAllocator locationAllocator;
/// The singleton for UnknownLoc.
UnknownLocationStorage *theUnknownLoc = nullptr;
/// These are filename locations uniqued into this MLIRContext.
llvm::StringMap<char, llvm::BumpPtrAllocator &> filenames;
/// FileLineColLoc uniquing.
DenseMap<std::tuple<const char *, unsigned, unsigned>,
FileLineColLocationStorage *>
fileLineColLocs;
/// NameLocation uniquing.
DenseMap<const char *, NameLocationStorage *> nameLocs;
/// CallLocation uniquing.
DenseSet<CallSiteLocationStorage *, CallSiteLocationKeyInfo> callLocs;
/// FusedLoc uniquing.
using FusedLocations = DenseSet<FusedLocationStorage *, FusedLocKeyInfo>;
FusedLocations fusedLocs;
/// We put immortal objects into this allocator.
llvm::BumpPtrAllocator allocator;
/// This is the handler to use to report diagnostics, or null if not
/// registered.
MLIRContext::DiagnosticHandlerTy diagnosticHandler;
/// This is a list of dialects that are created referring to this context.
/// The MLIRContext owns the objects.
std::vector<std::unique_ptr<Dialect>> dialects;
/// This is a mapping from operation name to AbstractOperation for registered
/// operations.
StringMap<AbstractOperation> registeredOperations;
/// This is a mapping from type identifier to Dialect for registered types.
DenseMap<const void *, Dialect *> registeredTypes;
/// These are identifiers uniqued into this MLIRContext.
llvm::StringMap<char, llvm::BumpPtrAllocator &> identifiers;
// Affine map uniquing.
using AffineMapSet = DenseSet<AffineMap, AffineMapKeyInfo>;
AffineMapSet affineMaps;
// Integer set uniquing.
using IntegerSets = DenseSet<IntegerSet, IntegerSetKeyInfo>;
IntegerSets integerSets;
// Affine binary op expression uniquing. Figure out uniquing of dimensional
// or symbolic identifiers.
DenseMap<std::tuple<unsigned, AffineExpr, AffineExpr>, AffineExpr>
affineExprs;
// Uniqui'ing of AffineDimExpr, AffineSymbolExpr's by their position.
std::vector<AffineDimExprStorage *> dimExprs;
std::vector<AffineSymbolExprStorage *> symbolExprs;
// Uniqui'ing of AffineConstantExprStorage using constant value as key.
DenseMap<int64_t, AffineConstantExprStorage *> constExprs;
/// Type uniquing.
TypeUniquer typeUniquer;
// Attribute uniquing.
BoolAttributeStorage *boolAttrs[2] = {nullptr};
DenseSet<IntegerAttributeStorage *, IntegerAttrKeyInfo> integerAttrs;
DenseSet<FloatAttributeStorage *, FloatAttrKeyInfo> floatAttrs;
StringMap<StringAttributeStorage *> stringAttrs;
using ArrayAttrSet = DenseSet<ArrayAttributeStorage *, ArrayAttrKeyInfo>;
ArrayAttrSet arrayAttrs;
DenseMap<AffineMap, AffineMapAttributeStorage *> affineMapAttrs;
DenseMap<IntegerSet, IntegerSetAttributeStorage *> integerSetAttrs;
DenseMap<Type, TypeAttributeStorage *> typeAttrs;
using AttributeListSet =
DenseSet<AttributeListStorage *, AttributeListKeyInfo>;
AttributeListSet attributeLists;
DenseMap<const Function *, FunctionAttributeStorage *> functionAttrs;
DenseMap<std::pair<Type, Attribute>, SplatElementsAttributeStorage *>
splatElementsAttrs;
using DenseElementsAttrSet =
DenseSet<DenseElementsAttributeStorage *, DenseElementsAttrInfo>;
DenseElementsAttrSet denseElementsAttrs;
using OpaqueElementsAttrSet =
DenseSet<OpaqueElementsAttributeStorage *, OpaqueElementsAttrInfo>;
OpaqueElementsAttrSet opaqueElementsAttrs;
DenseMap<std::tuple<Type, Attribute, Attribute>,
SparseElementsAttributeStorage *>
sparseElementsAttrs;
public:
MLIRContextImpl() : filenames(locationAllocator), identifiers(allocator) {}
/// Copy the specified array of elements into memory managed by our bump
/// pointer allocator. This assumes the elements are all PODs.
template <typename T> ArrayRef<T> copyInto(ArrayRef<T> elements) {
auto result = allocator.Allocate<T>(elements.size());
std::uninitialized_copy(elements.begin(), elements.end(), result);
return ArrayRef<T>(result, elements.size());
}
};
} // end namespace mlir
MLIRContext::MLIRContext() : impl(new MLIRContextImpl()) {
new BuiltinDialect(this);
registerAllDialects(this);
}
MLIRContext::~MLIRContext() {}
//===----------------------------------------------------------------------===//
// Diagnostic Handlers
//===----------------------------------------------------------------------===//
/// Register an issue handler with this MLIR context. The issue handler is
/// passed location information along with a message and a DiagnosticKind enum
/// value that indicates the type of the diagnostic (e.g., Warning, Error).
void MLIRContext::registerDiagnosticHandler(
const DiagnosticHandlerTy &handler) {
getImpl().diagnosticHandler = handler;
}
/// Return the current diagnostic handler, or null if none is present.
auto MLIRContext::getDiagnosticHandler() const -> DiagnosticHandlerTy {
return getImpl().diagnosticHandler;
}
/// This emits a diagnostic using the registered issue handle if present, or
/// with the default behavior if not. The MLIR compiler should not generally
/// interact with this, it should use methods on Instruction instead.
void MLIRContext::emitDiagnostic(Location location, const llvm::Twine &message,
DiagnosticKind kind) const {
// Check to see if we are emitting a diagnostic on a fused location.
if (auto fusedLoc = location.dyn_cast<FusedLoc>()) {
auto fusedLocs = fusedLoc->getLocations();
// Emit the original diagnostic with the first location in the fused list.
emitDiagnostic(fusedLocs.front(), message, kind);
// Emit the rest of the locations as notes.
for (unsigned i = 1, e = fusedLocs.size(); i != e; ++i)
emitDiagnostic(fusedLocs[i], "fused from here", DiagnosticKind::Note);
return;
}
// If we had a handler registered, emit the diagnostic using it.
auto handler = getImpl().diagnosticHandler;
if (handler)
return handler(location, message.str(), kind);
// The default behavior for notes and warnings is to ignore them.
if (kind != DiagnosticKind::Error)
return;
auto &os = llvm::errs();
if (!location.isa<UnknownLoc>())
os << location << ": ";
os << "error: ";
// The default behavior for errors is to emit them to stderr.
os << message.str() << '\n';
os.flush();
}
bool MLIRContext::emitError(Location location,
const llvm::Twine &message) const {
emitDiagnostic(location, message, DiagnosticKind::Error);
return true;
}
//===----------------------------------------------------------------------===//
// Dialect and Operation Registration
//===----------------------------------------------------------------------===//
/// Return information about all registered IR dialects.
std::vector<Dialect *> MLIRContext::getRegisteredDialects() const {
std::vector<Dialect *> result;
result.reserve(getImpl().dialects.size());
for (auto &dialect : getImpl().dialects)
result.push_back(dialect.get());
return result;
}
/// Get a registered IR dialect with the given namespace. If none is found,
/// then return nullptr.
Dialect *MLIRContext::getRegisteredDialect(StringRef name) const {
for (auto &dialect : getImpl().dialects)
if (name == dialect->getNamespace())
return dialect.get();
return nullptr;
}
/// Register this dialect object with the specified context. The context
/// takes ownership of the heap allocated dialect.
void Dialect::registerDialect(MLIRContext *context) {
context->getImpl().dialects.push_back(std::unique_ptr<Dialect>(this));
}
/// Return information about all registered operations. This isn't very
/// efficient, typically you should ask the operations about their properties
/// directly.
std::vector<AbstractOperation *> MLIRContext::getRegisteredOperations() const {
// We just have the operations in a non-deterministic hash table order. Dump
// into a temporary array, then sort it by operation name to get a stable
// ordering.
StringMap<AbstractOperation> &registeredOps = getImpl().registeredOperations;
std::vector<std::pair<StringRef, AbstractOperation *>> opsToSort;
opsToSort.reserve(registeredOps.size());
for (auto &elt : registeredOps)
opsToSort.push_back({elt.first(), &elt.second});
llvm::array_pod_sort(opsToSort.begin(), opsToSort.end());
std::vector<AbstractOperation *> result;
result.reserve(opsToSort.size());
for (auto &elt : opsToSort)
result.push_back(elt.second);
return result;
}
void Dialect::addOperation(AbstractOperation opInfo) {
assert((namePrefix.empty() || (opInfo.name.split('.').first == namePrefix)) &&
"op name doesn't start with dialect prefix");
assert(&opInfo.dialect == this && "Dialect object mismatch");
auto &impl = context->getImpl();
if (!impl.registeredOperations.insert({opInfo.name, opInfo}).second) {
llvm::errs() << "error: ops named '" << opInfo.name
<< "' is already registered.\n";
abort();
}
}
/// Register a dialect-specific type with the current context.
void Dialect::addType(const void *const typeID) {
auto &impl = context->getImpl();
if (impl.registeredTypes.count(typeID)) {
llvm::errs() << "error: type already registered.\n";
abort();
}
impl.registeredTypes.try_emplace(typeID, this);
}
/// Look up the specified operation in the operation set and return a pointer
/// to it if present. Otherwise, return a null pointer.
const AbstractOperation *AbstractOperation::lookup(StringRef opName,
MLIRContext *context) {
auto &impl = context->getImpl();
auto it = impl.registeredOperations.find(opName);
if (it != impl.registeredOperations.end())
return &it->second;
return nullptr;
}
//===----------------------------------------------------------------------===//
// Identifier uniquing
//===----------------------------------------------------------------------===//
/// Return an identifier for the specified string.
Identifier Identifier::get(StringRef str, const MLIRContext *context) {
assert(!str.empty() && "Cannot create an empty identifier");
assert(str.find('\0') == StringRef::npos &&
"Cannot create an identifier with a nul character");
auto &impl = context->getImpl();
auto it = impl.identifiers.insert({str, char()}).first;
return Identifier(it->getKeyData());
}
//===----------------------------------------------------------------------===//
// Location uniquing
//===----------------------------------------------------------------------===//
UnknownLoc UnknownLoc::get(MLIRContext *context) {
auto &impl = context->getImpl();
if (auto *result = impl.theUnknownLoc)
return result;
impl.theUnknownLoc = impl.allocator.Allocate<UnknownLocationStorage>();
new (impl.theUnknownLoc) UnknownLocationStorage{Location::Kind::Unknown};
return impl.theUnknownLoc;
}
UniquedFilename UniquedFilename::get(StringRef filename, MLIRContext *context) {
auto &impl = context->getImpl();
auto it = impl.filenames.insert({filename, char()}).first;
return UniquedFilename(it->getKeyData());
}
FileLineColLoc FileLineColLoc::get(UniquedFilename filename, unsigned line,
unsigned column, MLIRContext *context) {
auto &impl = context->getImpl();
auto &entry =
impl.fileLineColLocs[std::make_tuple(filename.data(), line, column)];
if (!entry) {
entry = impl.allocator.Allocate<FileLineColLocationStorage>();
new (entry) FileLineColLocationStorage{
{Location::Kind::FileLineCol}, filename, line, column};
}
return entry;
}
NameLoc NameLoc::get(Identifier name, MLIRContext *context) {
auto &impl = context->getImpl();
auto &entry = impl.nameLocs[name.data()];
if (!entry) {
entry = impl.allocator.Allocate<NameLocationStorage>();
new (entry) NameLocationStorage{{Location::Kind::Name}, name};
}
return entry;
}
CallSiteLoc CallSiteLoc::get(Location callee, Location caller,
MLIRContext *context) {
auto &impl = context->getImpl();
// Look to see if the fused location has been created already.
auto existing =
impl.callLocs.insert_as(nullptr, std::make_pair(callee, caller));
// If it has been created, return it.
if (!existing.second)
return *existing.first;
// On the first use, we allocate them into the bump pointer.
auto *result = impl.allocator.Allocate<detail::CallSiteLocationStorage>();
// Initialize the memory using placement new.
new (result) detail::CallSiteLocationStorage{
{Location::Kind::CallSite}, callee, caller};
return *existing.first = result;
}
CallSiteLoc CallSiteLoc::get(Location name, ArrayRef<Location> frames,
MLIRContext *context) {
assert(!frames.empty() && "required at least 1 frames");
auto it = frames.rbegin();
Location caller = *it++;
for (auto e = frames.rend(); it != e; ++it) {
caller = CallSiteLoc::get(*it, caller, context);
}
return CallSiteLoc::get(name, caller, context);
}
Location FusedLoc::get(ArrayRef<Location> locs, MLIRContext *context) {
return get(locs, Attribute(), context);
}
Location FusedLoc::get(ArrayRef<Location> locs, Attribute metadata,
MLIRContext *context) {
// Unique the set of locations to be fused.
SmallSetVector<Location, 4> decomposedLocs;
for (auto loc : locs) {
// If the location is a fused location we decompose it if it has no
// metadata or the metadata is the same as the top level metadata.
if (auto fusedLoc = loc.dyn_cast<FusedLoc>()) {
if (fusedLoc->getMetadata() == metadata) {
// UnknownLoc's have already been removed from FusedLocs so we can
// simply add all of the internal locations.
decomposedLocs.insert(fusedLoc->getLocations().begin(),
fusedLoc->getLocations().end());
continue;
}
}
// Otherwise, only add known locations to the set.
if (!loc.isa<UnknownLoc>())
decomposedLocs.insert(loc);
}
locs = decomposedLocs.getArrayRef();
// Handle the simple cases of less than two locations.
if (locs.empty())
return UnknownLoc::get(context);
if (locs.size() == 1)
return locs.front();
auto &impl = context->getImpl();
// Look to see if the fused location has been created already.
auto existing =
impl.fusedLocs.insert_as(nullptr, std::make_pair(locs, metadata));
// If it has been created, return it.
if (!existing.second)
return *existing.first;
auto byteSize = FusedLocationStorage::totalSizeToAlloc<Location>(locs.size());
auto rawMem =
impl.allocator.Allocate(byteSize, alignof(FusedLocationStorage));
auto result =
new (rawMem) FusedLocationStorage{{Location::Kind::FusedLocation},
{},
static_cast<unsigned>(locs.size()),
metadata};
std::uninitialized_copy(locs.begin(), locs.end(),
result->getTrailingObjects<Location>());
return *existing.first = result;
}
//===----------------------------------------------------------------------===//
// Type uniquing
//===----------------------------------------------------------------------===//
/// Get the type uniquer for this context.
TypeUniquer &MLIRContext::getTypeUniquer() const {
return getImpl().typeUniquer;
}
/// Get a reference to the internal allocator.
llvm::BumpPtrAllocator &TypeStorageAllocator::getAllocator() {
return ctx->getImpl().allocator;
}
/// Get the dialect that registered the type with the provided typeid.
const Dialect &TypeUniquer::lookupDialectForType(MLIRContext *ctx,
const void *const typeID) {
auto &impl = ctx->getImpl();
assert(impl.registeredTypes.count(typeID) && "typeID is not registered.");
return *impl.registeredTypes[typeID];
}
//===----------------------------------------------------------------------===//
// Attribute uniquing
//===----------------------------------------------------------------------===//
BoolAttr BoolAttr::get(bool value, MLIRContext *context) {
auto *&result = context->getImpl().boolAttrs[value];
if (result)
return result;
result = context->getImpl().allocator.Allocate<BoolAttributeStorage>();
new (result) BoolAttributeStorage{{Attribute::Kind::Bool,
/*isOrContainsFunction=*/false},
IntegerType::get(1, context),
value};
return result;
}
IntegerAttr IntegerAttr::get(Type type, const APInt &value) {
auto &impl = type.getContext()->getImpl();
// Look to see if the integer attribute has been created already.
IntegerAttrKeyInfo::KeyTy key({type, value});
auto existing = impl.integerAttrs.insert_as(nullptr, key);
// If it has been created, return it.
if (!existing.second)
return *existing.first;
// If it doesn't, create one and return it.
auto elements = ArrayRef<uint64_t>(value.getRawData(), value.getNumWords());
auto byteSize =
IntegerAttributeStorage::totalSizeToAlloc<uint64_t>(elements.size());
auto rawMem =
impl.allocator.Allocate(byteSize, alignof(IntegerAttributeStorage));
// TODO: This uses 64 bit APInts by default without consideration of value.
auto result = ::new (rawMem) IntegerAttributeStorage{
{Attribute::Kind::Integer, /*isOrContainsFunction=*/false},
type,
elements.size()};
std::uninitialized_copy(elements.begin(), elements.end(),
result->getTrailingObjects<uint64_t>());
return *existing.first = result;
}
IntegerAttr IntegerAttr::get(Type type, int64_t value) {
// This uses 64 bit APInts by default for index type.
if (type.isIndex())
return get(type, APInt(64, value));
auto intType = type.dyn_cast<IntegerType>();
assert(intType && "expected an integer type for an integer attribute");
return get(type, APInt(intType.getWidth(), value));
}
static FloatAttr getFloatAttr(Type type, double value,
llvm::Optional<Location> loc) {
if (!type.isa<FloatType>()) {
if (loc)
type.getContext()->emitError(*loc, "expected floating point type");
return nullptr;
}
// Treat BF16 as double because it is not supported in LLVM's APFloat.
// TODO(jpienaar): add BF16 support to APFloat?
if (type.isBF16() || type.isF64())
return FloatAttr::get(type, APFloat(value));
// This handles, e.g., F16 because there is no APFloat constructor for it.
bool unused;
APFloat val(value);
val.convert(type.cast<FloatType>().getFloatSemantics(),
APFloat::rmNearestTiesToEven, &unused);
return FloatAttr::get(type, val);
}
FloatAttr FloatAttr::getChecked(Type type, double value, Location loc) {
return getFloatAttr(type, value, loc);
}
FloatAttr FloatAttr::get(Type type, double value) {
auto res = getFloatAttr(type, value, /*loc=*/llvm::None);
assert(res && "failed to construct float attribute");
return res;
}
FloatAttr FloatAttr::get(Type type, const APFloat &value) {
auto fltType = type.cast<FloatType>();
assert(&fltType.getFloatSemantics() == &value.getSemantics() &&
"FloatAttr type doesn't match the type implied by its value");
(void)fltType;
auto &impl = type.getContext()->getImpl();
// Look to see if the float attribute has been created already.
FloatAttrKeyInfo::KeyTy key({type, value});
auto existing = impl.floatAttrs.insert_as(nullptr, key);
// If it has been created, return it.
if (!existing.second)
return *existing.first;
// If it doesn't, create one, unique it and return it.
const auto &apint = value.bitcastToAPInt();
// Here one word's bitwidth equals to that of uint64_t.
auto elements = ArrayRef<uint64_t>(apint.getRawData(), apint.getNumWords());
auto byteSize =
FloatAttributeStorage::totalSizeToAlloc<uint64_t>(elements.size());
auto rawMem =
impl.allocator.Allocate(byteSize, alignof(FloatAttributeStorage));
auto result = ::new (rawMem) FloatAttributeStorage{
{Attribute::Kind::Float, /*isOrContainsFunction=*/false},
value.getSemantics(),
type,
elements.size()};
std::uninitialized_copy(elements.begin(), elements.end(),
result->getTrailingObjects<uint64_t>());
return *existing.first = result;
}
StringAttr StringAttr::get(StringRef bytes, MLIRContext *context) {
auto it = context->getImpl().stringAttrs.insert({bytes, nullptr}).first;
if (it->second)
return it->second;
auto result = context->getImpl().allocator.Allocate<StringAttributeStorage>();
new (result) StringAttributeStorage{{Attribute::Kind::String,
/*isOrContainsFunction=*/false},
it->first()};
it->second = result;
return result;
}
ArrayAttr ArrayAttr::get(ArrayRef<Attribute> value, MLIRContext *context) {
auto &impl = context->getImpl();
// Look to see if we already have this.
auto existing = impl.arrayAttrs.insert_as(nullptr, value);
// If we already have it, return that value.
if (!existing.second)
return *existing.first;
// On the first use, we allocate them into the bump pointer.
auto *result = impl.allocator.Allocate<ArrayAttributeStorage>();
// Copy the elements into the bump pointer.
value = impl.copyInto(value);
// Check to see if any of the elements have a function attr.
bool hasFunctionAttr = false;
for (auto elt : value)
if (elt.isOrContainsFunction()) {
hasFunctionAttr = true;
break;
}
// Initialize the memory using placement new.
new (result)
ArrayAttributeStorage{{Attribute::Kind::Array, hasFunctionAttr}, value};
// Cache and return it.
return *existing.first = result;
}
AffineMapAttr AffineMapAttr::get(AffineMap value) {
auto *context = value.getResult(0).getContext();
auto &result = context->getImpl().affineMapAttrs[value];
if (result)
return result;
result = context->getImpl().allocator.Allocate<AffineMapAttributeStorage>();
new (result) AffineMapAttributeStorage{{Attribute::Kind::AffineMap,
/*isOrContainsFunction=*/false},
value};
return result;
}
IntegerSetAttr IntegerSetAttr::get(IntegerSet value) {
auto *context = value.getConstraint(0).getContext();
auto &result = context->getImpl().integerSetAttrs[value];
if (result)
return result;
result = context->getImpl().allocator.Allocate<IntegerSetAttributeStorage>();
new (result) IntegerSetAttributeStorage{{Attribute::Kind::IntegerSet,
/*isOrContainsFunction=*/false},
value};
return result;
}
TypeAttr TypeAttr::get(Type type, MLIRContext *context) {
auto *&result = context->getImpl().typeAttrs[type];
if (result)
return result;
result = context->getImpl().allocator.Allocate<TypeAttributeStorage>();
new (result) TypeAttributeStorage{{Attribute::Kind::Type,
/*isOrContainsFunction=*/false},
type};
return result;
}
FunctionAttr FunctionAttr::get(const Function *value, MLIRContext *context) {
assert(value && "Cannot get FunctionAttr for a null function");
auto *&result = context->getImpl().functionAttrs[value];
if (result)
return result;
result = context->getImpl().allocator.Allocate<FunctionAttributeStorage>();
new (result) FunctionAttributeStorage{{Attribute::Kind::Function,
/*isOrContainsFunction=*/true},
const_cast<Function *>(value)};
return result;
}
/// This function is used by the internals of the Function class to null out
/// attributes refering to functions that are about to be deleted.
void FunctionAttr::dropFunctionReference(Function *value) {
// Check to see if there was an attribute referring to this function.
auto &functionAttrs = value->getContext()->getImpl().functionAttrs;
// If not, then we're done.
auto it = functionAttrs.find(value);
if (it == functionAttrs.end())
return;
// If so, null out the function reference in the attribute (to avoid dangling
// pointers) and remove the entry from the map so the map doesn't contain
// dangling keys.
it->second->value = nullptr;
functionAttrs.erase(it);
}
/// Perform a three-way comparison between the names of the specified
/// NamedAttributes.
static int compareNamedAttributes(const NamedAttribute *lhs,
const NamedAttribute *rhs) {
return lhs->first.str().compare(rhs->first.str());
}
/// Given a list of NamedAttribute's, canonicalize the list (sorting
/// by name) and return the unique'd result. Note that the empty list is
/// represented with a null pointer.
AttributeListStorage *AttributeListStorage::get(ArrayRef<NamedAttribute> attrs,
MLIRContext *context) {
// We need to sort the element list to canonicalize it, but we also don't want
// to do a ton of work in the super common case where the element list is
// already sorted.
SmallVector<NamedAttribute, 8> storage;
switch (attrs.size()) {
case 0:
// An empty list is represented with a null pointer.
return nullptr;
case 1:
// A single element is already sorted.
break;
case 2:
// Don't invoke a general sort for two element case.
if (attrs[0].first.str() > attrs[1].first.str()) {
storage.push_back(attrs[1]);
storage.push_back(attrs[0]);
attrs = storage;
}
break;
default:
// Check to see they are sorted already.
bool isSorted = true;
for (unsigned i = 0, e = attrs.size() - 1; i != e; ++i) {
if (attrs[i].first.str() > attrs[i + 1].first.str()) {
isSorted = false;
break;
}
}
// If not, do a general sort.
if (!isSorted) {
storage.append(attrs.begin(), attrs.end());
llvm::array_pod_sort(storage.begin(), storage.end(),
compareNamedAttributes);
attrs = storage;
}
}
auto &impl = context->getImpl();
// Look to see if we already have this.
auto existing = impl.attributeLists.insert_as(nullptr, attrs);
// If we already have it, return that value.
if (!existing.second)
return *existing.first;
// Otherwise, allocate a new AttributeListStorage, unique it and return it.
auto byteSize =
AttributeListStorage::totalSizeToAlloc<NamedAttribute>(attrs.size());
auto rawMem = impl.allocator.Allocate(byteSize, alignof(NamedAttribute));
// Placement initialize the AggregateSymbolicValue.
auto result = ::new (rawMem) AttributeListStorage(attrs.size());
std::uninitialized_copy(attrs.begin(), attrs.end(),
result->getTrailingObjects<NamedAttribute>());
return *existing.first = result;
}
// Returns false if the given `attr` is not of the given `type`.
// Note: This function is only intended to be used for assertion. So it's
// possibly allowing invalid cases that are unimplemented.
static bool attrIsOfType(Attribute attr, Type type) {
if (auto floatAttr = attr.dyn_cast<FloatAttr>())
return floatAttr.getType() == type;
if (auto intAttr = attr.dyn_cast<IntegerAttr>())
return intAttr.getType() == type;
if (auto elementsAttr = attr.dyn_cast<ElementsAttr>())
return elementsAttr.getType() == type;
// TODO: check the other cases
return true;
}
SplatElementsAttr SplatElementsAttr::get(VectorOrTensorType type,
Attribute elt) {
auto attr = elt.dyn_cast<NumericAttr>();
assert(attr && "expected numeric value");
assert(attr.getType() == type.getElementType() &&
"value should be of the given type");
(void)attr;
auto &impl = type.getContext()->getImpl();
// Look to see if we already have this.
auto *&result = impl.splatElementsAttrs[{type, elt}];
// If we already have it, return that value.
if (result)
return result;
// Otherwise, allocate them into the bump pointer.
result = impl.allocator.Allocate<SplatElementsAttributeStorage>();
new (result) SplatElementsAttributeStorage{{{Attribute::Kind::SplatElements,
/*isOrContainsFunction=*/false},
type},
elt};
return result;
}
DenseElementsAttr DenseElementsAttr::get(VectorOrTensorType type,
ArrayRef<char> data) {
auto bitsRequired = type.getSizeInBits();
(void)bitsRequired;
assert((bitsRequired <= data.size() * 8L) &&
"Input data bit size should be larger than that type requires");
auto &impl = type.getContext()->getImpl();
// Look to see if this constant is already defined.
DenseElementsAttrInfo::KeyTy key({type, data});
auto existing = impl.denseElementsAttrs.insert_as(nullptr, key);
// If we already have it, return that value.
if (!existing.second)
return *existing.first;
Attribute::Kind kind;
switch (type.getElementType().getKind()) {
case StandardTypes::BF16:
case StandardTypes::F16:
case StandardTypes::F32:
case StandardTypes::F64:
kind = Attribute::Kind::DenseFPElements;
break;
case StandardTypes::Integer:
kind = Attribute::Kind::DenseIntElements;
break;
default:
llvm_unreachable("unexpected element type");
}
// Otherwise, allocate a new one, unique it and return it.
auto *copy = (char *)impl.allocator.Allocate(data.size(), 64);
std::uninitialized_copy(data.begin(), data.end(), copy);
auto *result = impl.allocator.Allocate<DenseElementsAttributeStorage>();
new (result) DenseElementsAttributeStorage{
{{kind, /*isOrContainsFunction=*/false}, type}, {copy, data.size()}};
return *existing.first = result;
}
DenseElementsAttr DenseElementsAttr::get(VectorOrTensorType type,
ArrayRef<Attribute> values) {
assert(type.getElementType().isIntOrFloat() &&
"expected int or float element type");
assert(values.size() == type.getNumElements() &&
"expected 'values' to contain the same number of elements as 'type'");
// FIXME(b/121118307): using 64 bits for BF16 because it is currently stored
// with double semantics.
auto eltType = type.getElementType();
size_t bitWidth = eltType.isBF16() ? 64 : eltType.getIntOrFloatBitWidth();
// Compress the attribute values into a character buffer.
SmallVector<char, 8> data(APInt::getNumWords(bitWidth * values.size()) * 8L);
for (unsigned i = 0, e = values.size(); i < e; ++i) {
unsigned bitPos = i * bitWidth;
APInt intVal;
switch (eltType.getKind()) {
case StandardTypes::BF16:
case StandardTypes::F16:
case StandardTypes::F32:
case StandardTypes::F64:
assert(eltType == values[i].cast<FloatAttr>().getType() &&
"expected attribute value to have element type");
intVal = values[i].cast<FloatAttr>().getValue().bitcastToAPInt();
break;
case StandardTypes::Integer:
assert(eltType == values[i].cast<IntegerAttr>().getType() &&
"expected attribute value to have element type");
intVal = values[i].cast<IntegerAttr>().getValue();
break;
default:
llvm_unreachable("unexpected element type");
}
assert(intVal.getBitWidth() == bitWidth &&
"expected value to have same bitwidth as element type");
writeBits(data.data(), bitPos, intVal);
}
return get(type, data);
}
OpaqueElementsAttr OpaqueElementsAttr::get(VectorOrTensorType type,
StringRef bytes) {
assert(TensorType::isValidElementType(type.getElementType()) &&
"Input element type should be a valid tensor element type");
auto &impl = type.getContext()->getImpl();
// Look to see if this constant is already defined.
OpaqueElementsAttrInfo::KeyTy key({type, bytes});
auto existing = impl.opaqueElementsAttrs.insert_as(nullptr, key);
// If we already have it, return that value.
if (!existing.second)
return *existing.first;
// Otherwise, allocate a new one, unique it and return it.
auto *result = impl.allocator.Allocate<OpaqueElementsAttributeStorage>();
bytes = bytes.copy(impl.allocator);
new (result) OpaqueElementsAttributeStorage{
{{Attribute::Kind::OpaqueElements, /*isOrContainsFunction=*/false}, type},
bytes};
return *existing.first = result;
}
SparseElementsAttr SparseElementsAttr::get(VectorOrTensorType type,
DenseIntElementsAttr indices,
DenseElementsAttr values) {
assert(indices.getType().getElementType().isInteger(64) &&
"expected sparse indices to be 64-bit integer values");
auto &impl = type.getContext()->getImpl();
// Look to see if we already have this.
auto key = std::make_tuple(type, indices, values);
auto *&result = impl.sparseElementsAttrs[key];
// If we already have it, return that value.
if (result)
return result;
// Otherwise, allocate them into the bump pointer.
result = impl.allocator.Allocate<SparseElementsAttributeStorage>();
new (result) SparseElementsAttributeStorage{{{Attribute::Kind::SparseElements,
/*isOrContainsFunction=*/false},
type},
indices,
values};
return result;
}
//===----------------------------------------------------------------------===//
// AffineMap and AffineExpr uniquing
//===----------------------------------------------------------------------===//
AffineMap AffineMap::get(unsigned dimCount, unsigned symbolCount,
ArrayRef<AffineExpr> results,
ArrayRef<AffineExpr> rangeSizes) {
// The number of results can't be zero.
assert(!results.empty());
assert(rangeSizes.empty() || results.size() == rangeSizes.size());
auto &impl = results[0].getContext()->getImpl();
// Check if we already have this affine map.
auto key = std::make_tuple(dimCount, symbolCount, results, rangeSizes);
auto existing = impl.affineMaps.insert_as(AffineMap(), key);
// If we already have it, return that value.
if (!existing.second)
return *existing.first;
// On the first use, we allocate them into the bump pointer.
auto *res = impl.allocator.Allocate<detail::AffineMapStorage>();
// Copy the results and range sizes into the bump pointer.
results = impl.copyInto(results);
rangeSizes = impl.copyInto(rangeSizes);
// Initialize the memory using placement new.
new (res)
detail::AffineMapStorage{dimCount, symbolCount, results, rangeSizes};
// Cache and return it.
return *existing.first = AffineMap(res);
}
/// Simplify add expression. Return nullptr if it can't be simplified.
static AffineExpr simplifyAdd(AffineExpr lhs, AffineExpr rhs) {
auto lhsConst = lhs.dyn_cast<AffineConstantExpr>();
auto rhsConst = rhs.dyn_cast<AffineConstantExpr>();
// Fold if both LHS, RHS are a constant.
if (lhsConst && rhsConst)
return getAffineConstantExpr(lhsConst.getValue() + rhsConst.getValue(),
lhs.getContext());
// Canonicalize so that only the RHS is a constant. (4 + d0 becomes d0 + 4).
// If only one of them is a symbolic expressions, make it the RHS.
if (lhs.isa<AffineConstantExpr>() ||
(lhs.isSymbolicOrConstant() && !rhs.isSymbolicOrConstant())) {
return rhs + lhs;
}
// At this point, if there was a constant, it would be on the right.
// Addition with a zero is a noop, return the other input.
if (rhsConst) {
if (rhsConst.getValue() == 0)
return lhs;
}
// Fold successive additions like (d0 + 2) + 3 into d0 + 5.
auto lBin = lhs.dyn_cast<AffineBinaryOpExpr>();
if (lBin && rhsConst && lBin.getKind() == AffineExprKind::Add) {
if (auto lrhs = lBin.getRHS().dyn_cast<AffineConstantExpr>())
return lBin.getLHS() + (lrhs.getValue() + rhsConst.getValue());
}
// When doing successive additions, bring constant to the right: turn (d0 + 2)
// + d1 into (d0 + d1) + 2.
if (lBin && lBin.getKind() == AffineExprKind::Add) {
if (auto lrhs = lBin.getRHS().dyn_cast<AffineConstantExpr>()) {
return lBin.getLHS() + rhs + lrhs;
}
}
// Detect and transform "expr - c * (expr floordiv c)" to "expr mod c". This
// leads to a much more efficient form when 'c' is a power of two, and in
// general a more compact and readable form.
// Process '(expr floordiv c) * (-c)'.
AffineBinaryOpExpr rBinOpExpr = rhs.dyn_cast<AffineBinaryOpExpr>();
if (!rBinOpExpr)
return nullptr;
auto lrhs = rBinOpExpr.getLHS();
auto rrhs = rBinOpExpr.getRHS();
// Process lrhs, which is 'expr floordiv c'.
AffineBinaryOpExpr lrBinOpExpr = lrhs.dyn_cast<AffineBinaryOpExpr>();
if (!lrBinOpExpr)
return nullptr;
auto llrhs = lrBinOpExpr.getLHS();
auto rlrhs = lrBinOpExpr.getRHS();
if (lhs == llrhs && rlrhs == -rrhs) {
return lhs % rlrhs;
}
return nullptr;
}
/// Simplify a multiply expression. Return nullptr if it can't be simplified.
static AffineExpr simplifyMul(AffineExpr lhs, AffineExpr rhs) {
auto lhsConst = lhs.dyn_cast<AffineConstantExpr>();
auto rhsConst = rhs.dyn_cast<AffineConstantExpr>();
if (lhsConst && rhsConst)
return getAffineConstantExpr(lhsConst.getValue() * rhsConst.getValue(),
lhs.getContext());
assert(lhs.isSymbolicOrConstant() || rhs.isSymbolicOrConstant());
// Canonicalize the mul expression so that the constant/symbolic term is the
// RHS. If both the lhs and rhs are symbolic, swap them if the lhs is a
// constant. (Note that a constant is trivially symbolic).
if (!rhs.isSymbolicOrConstant() || lhs.isa<AffineConstantExpr>()) {
// At least one of them has to be symbolic.
return rhs * lhs;
}
// At this point, if there was a constant, it would be on the right.
// Multiplication with a one is a noop, return the other input.
if (rhsConst) {
if (rhsConst.getValue() == 1)
return lhs;
// Multiplication with zero.
if (rhsConst.getValue() == 0)
return rhsConst;
}
// Fold successive multiplications: eg: (d0 * 2) * 3 into d0 * 6.
auto lBin = lhs.dyn_cast<AffineBinaryOpExpr>();
if (lBin && rhsConst && lBin.getKind() == AffineExprKind::Mul) {
if (auto lrhs = lBin.getRHS().dyn_cast<AffineConstantExpr>())
return lBin.getLHS() * (lrhs.getValue() * rhsConst.getValue());
}
// When doing successive multiplication, bring constant to the right: turn (d0
// * 2) * d1 into (d0 * d1) * 2.
if (lBin && lBin.getKind() == AffineExprKind::Mul) {
if (auto lrhs = lBin.getRHS().dyn_cast<AffineConstantExpr>()) {
return (lBin.getLHS() * rhs) * lrhs;
}
}
return nullptr;
}
static AffineExpr simplifyFloorDiv(AffineExpr lhs, AffineExpr rhs) {
auto lhsConst = lhs.dyn_cast<AffineConstantExpr>();
auto rhsConst = rhs.dyn_cast<AffineConstantExpr>();
if (!rhsConst || rhsConst.getValue() < 1)
return nullptr;
if (lhsConst)
return getAffineConstantExpr(
floorDiv(lhsConst.getValue(), rhsConst.getValue()), lhs.getContext());
// Fold floordiv of a multiply with a constant that is a multiple of the
// divisor. Eg: (i * 128) floordiv 64 = i * 2.
if (rhsConst.getValue() == 1)
return lhs;
auto lBin = lhs.dyn_cast<AffineBinaryOpExpr>();
if (lBin && lBin.getKind() == AffineExprKind::Mul) {
if (auto lrhs = lBin.getRHS().dyn_cast<AffineConstantExpr>()) {
// rhsConst is known to be positive if a constant.
if (lrhs.getValue() % rhsConst.getValue() == 0)
return lBin.getLHS() * (lrhs.getValue() / rhsConst.getValue());
}
}
return nullptr;
}
static AffineExpr simplifyCeilDiv(AffineExpr lhs, AffineExpr rhs) {
auto lhsConst = lhs.dyn_cast<AffineConstantExpr>();
auto rhsConst = rhs.dyn_cast<AffineConstantExpr>();
if (!rhsConst || rhsConst.getValue() < 1)
return nullptr;
if (lhsConst)
return getAffineConstantExpr(
ceilDiv(lhsConst.getValue(), rhsConst.getValue()), lhs.getContext());
// Fold ceildiv of a multiply with a constant that is a multiple of the
// divisor. Eg: (i * 128) ceildiv 64 = i * 2.
if (rhsConst.getValue() == 1)
return lhs;
auto lBin = lhs.dyn_cast<AffineBinaryOpExpr>();
if (lBin && lBin.getKind() == AffineExprKind::Mul) {
if (auto lrhs = lBin.getRHS().dyn_cast<AffineConstantExpr>()) {
// rhsConst is known to be positive if a constant.
if (lrhs.getValue() % rhsConst.getValue() == 0)
return lBin.getLHS() * (lrhs.getValue() / rhsConst.getValue());
}
}
return nullptr;
}
static AffineExpr simplifyMod(AffineExpr lhs, AffineExpr rhs) {
auto lhsConst = lhs.dyn_cast<AffineConstantExpr>();
auto rhsConst = rhs.dyn_cast<AffineConstantExpr>();
if (!rhsConst || rhsConst.getValue() < 1)
return nullptr;
if (lhsConst)
return getAffineConstantExpr(mod(lhsConst.getValue(), rhsConst.getValue()),
lhs.getContext());
// Fold modulo of an expression that is known to be a multiple of a constant
// to zero if that constant is a multiple of the modulo factor. Eg: (i * 128)
// mod 64 is folded to 0, and less trivially, (i*(j*4*(k*32))) mod 128 = 0.
if (lhs.getLargestKnownDivisor() % rhsConst.getValue() == 0)
return getAffineConstantExpr(0, lhs.getContext());
return nullptr;
// TODO(bondhugula): In general, this can be simplified more by using the GCD
// test, or in general using quantifier elimination (add two new variables q
// and r, and eliminate all variables from the linear system other than r. All
// of this can be done through mlir/Analysis/'s FlatAffineConstraints.
}
/// Return a binary affine op expression with the specified op type and
/// operands: if it doesn't exist, create it and store it; if it is already
/// present, return from the list. The stored expressions are unique: they are
/// constructed and stored in a simplified/canonicalized form. The result after
/// simplification could be any form of affine expression.
AffineExpr AffineBinaryOpExprStorage::get(AffineExprKind kind, AffineExpr lhs,
AffineExpr rhs) {
auto &impl = lhs.getContext()->getImpl();
// Check if we already have this affine expression, and return it if we do.
auto keyValue = std::make_tuple((unsigned)kind, lhs, rhs);
auto cached = impl.affineExprs.find(keyValue);
if (cached != impl.affineExprs.end())
return cached->second;
// Simplify the expression if possible.
AffineExpr simplified;
switch (kind) {
case AffineExprKind::Add:
simplified = simplifyAdd(lhs, rhs);
break;
case AffineExprKind::Mul:
simplified = simplifyMul(lhs, rhs);
break;
case AffineExprKind::FloorDiv:
simplified = simplifyFloorDiv(lhs, rhs);
break;
case AffineExprKind::CeilDiv:
simplified = simplifyCeilDiv(lhs, rhs);
break;
case AffineExprKind::Mod:
simplified = simplifyMod(lhs, rhs);
break;
default:
llvm_unreachable("unexpected binary affine expr");
}
// The simplified one would have already been cached; just return it.
if (simplified)
return simplified;
// An expression with these operands will already be in the
// simplified/canonical form. Create and store it.
auto *result = impl.allocator.Allocate<AffineBinaryOpExprStorage>();
// Initialize the memory using placement new.
new (result) AffineBinaryOpExprStorage{{kind, lhs.getContext()}, lhs, rhs};
bool inserted = impl.affineExprs.insert({keyValue, result}).second;
assert(inserted && "the expression shouldn't already exist in the map");
(void)inserted;
return result;
}
AffineExpr mlir::getAffineBinaryOpExpr(AffineExprKind kind, AffineExpr lhs,
AffineExpr rhs) {
return AffineBinaryOpExprStorage::get(kind, lhs, rhs);
}
AffineExpr mlir::getAffineDimExpr(unsigned position, MLIRContext *context) {
auto &impl = context->getImpl();
// Check if we need to resize.
if (position >= impl.dimExprs.size())
impl.dimExprs.resize(position + 1, nullptr);
auto *&result = impl.dimExprs[position];
if (result)
return result;
result = impl.allocator.Allocate<AffineDimExprStorage>();
// Initialize the memory using placement new.
new (result) AffineDimExprStorage{{AffineExprKind::DimId, context}, position};
return result;
}
AffineExpr mlir::getAffineSymbolExpr(unsigned position, MLIRContext *context) {
auto &impl = context->getImpl();
// Check if we need to resize.
if (position >= impl.symbolExprs.size())
impl.symbolExprs.resize(position + 1, nullptr);
auto *&result = impl.symbolExprs[position];
if (result)
return result;
result = impl.allocator.Allocate<AffineSymbolExprStorage>();
// Initialize the memory using placement new.
new (result)
AffineSymbolExprStorage{{AffineExprKind::SymbolId, context}, position};
return result;
}
AffineExpr mlir::getAffineConstantExpr(int64_t constant, MLIRContext *context) {
auto &impl = context->getImpl();
auto *&result = impl.constExprs[constant];
if (result)
return result;
result = impl.allocator.Allocate<AffineConstantExprStorage>();
// Initialize the memory using placement new.
new (result)
AffineConstantExprStorage{{AffineExprKind::Constant, context}, constant};
return result;
}
//===----------------------------------------------------------------------===//
// Integer Sets: these are allocated into the bump pointer, and are immutable.
// Unlike AffineMap's, these are uniqued only if they are small.
//===----------------------------------------------------------------------===//
IntegerSet IntegerSet::get(unsigned dimCount, unsigned symbolCount,
ArrayRef<AffineExpr> constraints,
ArrayRef<bool> eqFlags) {
// The number of constraints can't be zero.
assert(!constraints.empty());
assert(constraints.size() == eqFlags.size());
bool unique = constraints.size() < IntegerSet::kUniquingThreshold;
auto &impl = constraints[0].getContext()->getImpl();
std::pair<DenseSet<IntegerSet, IntegerSetKeyInfo>::Iterator, bool> existing;
if (unique) {
// Check if we already have this integer set.
auto key = std::make_tuple(dimCount, symbolCount, constraints, eqFlags);
existing = impl.integerSets.insert_as(IntegerSet(nullptr), key);
// If we already have it, return that value.
if (!existing.second)
return *existing.first;
}
// On the first use, we allocate them into the bump pointer.
auto *res = impl.allocator.Allocate<detail::IntegerSetStorage>();
// Copy the results and equality flags into the bump pointer.
constraints = impl.copyInto(constraints);
eqFlags = impl.copyInto(eqFlags);
// Initialize the memory using placement new.
new (res)
detail::IntegerSetStorage{dimCount, symbolCount, constraints, eqFlags};
if (unique)
// Cache and return it.
return *existing.first = IntegerSet(res);
return IntegerSet(res);
}