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

Ignoring revisions in .git-blame-ignore-revs. Click here to bypass and see the normal blame view.

847 lines
32 KiB
C++
Raw Normal View History

//===- MLIRContext.cpp - MLIR Type Classes --------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "mlir/IR/MLIRContext.h"
#include "AffineExprDetail.h"
#include "AffineMapDetail.h"
#include "AttributeDetail.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/Diagnostics.h"
#include "mlir/IR/Dialect.h"
#include "mlir/IR/Function.h"
#include "mlir/IR/Identifier.h"
#include "mlir/IR/IntegerSet.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/Module.h"
#include "mlir/IR/Types.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/StringSet.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Support/Allocator.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/RWMutex.h"
#include "llvm/Support/raw_ostream.h"
#include <memory>
using namespace mlir;
using namespace mlir::detail;
using llvm::hash_combine;
using llvm::hash_combine_range;
//===----------------------------------------------------------------------===//
// MLIRContext CommandLine Options
//===----------------------------------------------------------------------===//
namespace {
/// This struct contains command line options that can be used to initialize
/// various bits of an MLIRContext. This uses a struct wrapper to avoid the need
/// for global command line options.
struct MLIRContextOptions {
llvm::cl::opt<bool> disableThreading{
"mlir-disable-threading",
llvm::cl::desc("Disabling multi-threading within MLIR")};
llvm::cl::opt<bool> printOpOnDiagnostic{
"mlir-print-op-on-diagnostic",
llvm::cl::desc("When a diagnostic is emitted on an operation, also print "
"the operation as an attached note"),
llvm::cl::init(true)};
llvm::cl::opt<bool> printStackTraceOnDiagnostic{
"mlir-print-stacktrace-on-diagnostic",
llvm::cl::desc("When a diagnostic is emitted, also print the stack trace "
"as an attached note")};
};
} // end anonymous namespace
static llvm::ManagedStatic<MLIRContextOptions> clOptions;
/// Register a set of useful command-line options that can be used to configure
/// various flags within the MLIRContext. These flags are used when constructing
/// an MLIR context for initialization.
void mlir::registerMLIRContextCLOptions() {
// Make sure that the options struct has been initialized.
*clOptions;
}
//===----------------------------------------------------------------------===//
// Builtin Dialect
//===----------------------------------------------------------------------===//
namespace {
/// A builtin dialect to define types/etc that are necessary for the validity of
/// the IR.
struct BuiltinDialect : public Dialect {
BuiltinDialect(MLIRContext *context) : Dialect(/*name=*/"", context) {
addAttributes<AffineMapAttr, ArrayAttr, BoolAttr, DenseIntOrFPElementsAttr,
DenseStringElementsAttr, DictionaryAttr, FloatAttr,
SymbolRefAttr, IntegerAttr, IntegerSetAttr, OpaqueAttr,
OpaqueElementsAttr, SparseElementsAttr, StringAttr, TypeAttr,
UnitAttr>();
addAttributes<CallSiteLoc, FileLineColLoc, FusedLoc, NameLoc, OpaqueLoc,
UnknownLoc>();
addTypes<ComplexType, FloatType, FunctionType, IndexType, IntegerType,
MemRefType, UnrankedMemRefType, NoneType, OpaqueType,
RankedTensorType, TupleType, UnrankedTensorType, VectorType>();
// TODO: These operations should be moved to a different dialect when they
// have been fully decoupled from the core.
addOperations<FuncOp, ModuleOp, ModuleTerminatorOp>();
}
};
} // end anonymous namespace.
//===----------------------------------------------------------------------===//
// Locking Utilities
//===----------------------------------------------------------------------===//
namespace {
/// Utility reader lock that takes a runtime flag that specifies if we really
/// need to lock.
struct ScopedReaderLock {
ScopedReaderLock(llvm::sys::SmartRWMutex<true> &mutexParam, bool shouldLock)
: mutex(shouldLock ? &mutexParam : nullptr) {
if (mutex)
mutex->lock_shared();
}
~ScopedReaderLock() {
if (mutex)
mutex->unlock_shared();
}
llvm::sys::SmartRWMutex<true> *mutex;
};
/// Utility writer lock that takes a runtime flag that specifies if we really
/// need to lock.
struct ScopedWriterLock {
ScopedWriterLock(llvm::sys::SmartRWMutex<true> &mutexParam, bool shouldLock)
: mutex(shouldLock ? &mutexParam : nullptr) {
if (mutex)
mutex->lock();
}
~ScopedWriterLock() {
if (mutex)
mutex->unlock();
}
llvm::sys::SmartRWMutex<true> *mutex;
};
} // end anonymous namespace.
//===----------------------------------------------------------------------===//
// AffineMap and IntegerSet hashing
//===----------------------------------------------------------------------===//
/// A utility function to safely get or create a uniqued instance within the
/// given set container.
template <typename ValueT, typename DenseInfoT, typename KeyT,
typename ConstructorFn>
static ValueT safeGetOrCreate(DenseSet<ValueT, DenseInfoT> &container,
KeyT &&key, llvm::sys::SmartRWMutex<true> &mutex,
bool threadingIsEnabled,
ConstructorFn &&constructorFn) {
// Check for an existing instance in read-only mode.
if (threadingIsEnabled) {
llvm::sys::SmartScopedReader<true> instanceLock(mutex);
auto it = container.find_as(key);
if (it != container.end())
return *it;
}
// Acquire a writer-lock so that we can safely create the new instance.
ScopedWriterLock instanceLock(mutex, threadingIsEnabled);
// Check for an existing instance again here, because another writer thread
// may have already created one. Otherwise, construct a new instance.
auto existing = container.insert_as(ValueT(), key);
if (existing.second)
return *existing.first = constructorFn();
return *existing.first;
}
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>>;
using DenseMapInfo<AffineMap>::isEqual;
static unsigned getHashValue(const AffineMap &key) {
return getHashValue(
KeyTy(key.getNumDims(), key.getNumSymbols(), key.getResults()));
}
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()));
}
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());
}
};
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());
}
};
} // end anonymous namespace.
//===----------------------------------------------------------------------===//
// MLIRContextImpl
//===----------------------------------------------------------------------===//
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:
//===--------------------------------------------------------------------===//
// Identifier uniquing
//===--------------------------------------------------------------------===//
// Identifier allocator and mutex for thread safety.
llvm::BumpPtrAllocator identifierAllocator;
llvm::sys::SmartRWMutex<true> identifierMutex;
//===--------------------------------------------------------------------===//
// Diagnostics
//===--------------------------------------------------------------------===//
DiagnosticEngine diagEngine;
//===--------------------------------------------------------------------===//
// Options
//===--------------------------------------------------------------------===//
/// In most cases, creating operation in unregistered dialect is not desired
/// and indicate a misconfiguration of the compiler. This option enables to
/// detect such use cases
bool allowUnregisteredDialects = false;
/// Enable support for multi-threading within MLIR.
bool threadingIsEnabled = true;
/// If the operation should be attached to diagnostics printed via the
/// Operation::emit methods.
bool printOpOnDiagnostic = true;
/// If the current stack trace should be attached when emitting diagnostics.
bool printStackTraceOnDiagnostic = false;
//===--------------------------------------------------------------------===//
// Other
//===--------------------------------------------------------------------===//
/// A general purpose mutex to lock access to parts of the context that do not
/// have a more specific mutex, e.g. registry operations.
llvm::sys::SmartRWMutex<true> contextMutex;
/// 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.
llvm::StringMap<AbstractOperation> registeredOperations;
/// This is a mapping from type id to Dialect for registered attributes and
/// types.
DenseMap<TypeID, Dialect *> registeredDialectSymbols;
/// These are identifiers uniqued into this MLIRContext.
llvm::StringSet<llvm::BumpPtrAllocator &> identifiers;
//===--------------------------------------------------------------------===//
// Affine uniquing
//===--------------------------------------------------------------------===//
// Affine allocator and mutex for thread safety.
llvm::BumpPtrAllocator affineAllocator;
llvm::sys::SmartRWMutex<true> affineMutex;
// Affine map uniquing.
using AffineMapSet = DenseSet<AffineMap, AffineMapKeyInfo>;
AffineMapSet affineMaps;
// Integer set uniquing.
using IntegerSets = DenseSet<IntegerSet, IntegerSetKeyInfo>;
IntegerSets integerSets;
// Affine expression uniquing.
StorageUniquer affineUniquer;
//===--------------------------------------------------------------------===//
// Type uniquing
//===--------------------------------------------------------------------===//
StorageUniquer typeUniquer;
/// Cached Type Instances.
FloatType bf16Ty, f16Ty, f32Ty, f64Ty;
IndexType indexTy;
IntegerType int1Ty, int8Ty, int16Ty, int32Ty, int64Ty, int128Ty;
NoneType noneType;
//===--------------------------------------------------------------------===//
// Attribute uniquing
//===--------------------------------------------------------------------===//
StorageUniquer attributeUniquer;
/// Cached Attribute Instances.
BoolAttr falseAttr, trueAttr;
UnitAttr unitAttr;
UnknownLoc unknownLocAttr;
public:
MLIRContextImpl() : identifiers(identifierAllocator) {}
};
} // end namespace mlir
MLIRContext::MLIRContext() : impl(new MLIRContextImpl()) {
// Initialize values based on the command line flags if they were provided.
if (clOptions.isConstructed()) {
disableMultithreading(clOptions->disableThreading);
printOpOnDiagnostic(clOptions->printOpOnDiagnostic);
printStackTraceOnDiagnostic(clOptions->printStackTraceOnDiagnostic);
}
// Register dialects with this context.
new BuiltinDialect(this);
registerAllDialects(this);
// Initialize several common attributes and types to avoid the need to lock
// the context when accessing them.
//// Types.
/// Floating-point Types.
impl->bf16Ty = TypeUniquer::get<FloatType>(this, StandardTypes::BF16);
impl->f16Ty = TypeUniquer::get<FloatType>(this, StandardTypes::F16);
impl->f32Ty = TypeUniquer::get<FloatType>(this, StandardTypes::F32);
impl->f64Ty = TypeUniquer::get<FloatType>(this, StandardTypes::F64);
/// Index Type.
impl->indexTy = TypeUniquer::get<IndexType>(this, StandardTypes::Index);
/// Integer Types.
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
impl->int1Ty = TypeUniquer::get<IntegerType>(this, StandardTypes::Integer, 1,
IntegerType::Signless);
impl->int8Ty = TypeUniquer::get<IntegerType>(this, StandardTypes::Integer, 8,
IntegerType::Signless);
impl->int16Ty = TypeUniquer::get<IntegerType>(this, StandardTypes::Integer,
16, IntegerType::Signless);
impl->int32Ty = TypeUniquer::get<IntegerType>(this, StandardTypes::Integer,
32, IntegerType::Signless);
impl->int64Ty = TypeUniquer::get<IntegerType>(this, StandardTypes::Integer,
64, IntegerType::Signless);
impl->int128Ty = TypeUniquer::get<IntegerType>(this, StandardTypes::Integer,
128, IntegerType::Signless);
/// None Type.
impl->noneType = TypeUniquer::get<NoneType>(this, StandardTypes::None);
//// Attributes.
//// Note: These must be registered after the types as they may generate one
//// of the above types internally.
/// Bool Attributes.
// Note: The context is also used within the BoolAttrStorage.
impl->falseAttr = AttributeUniquer::get<BoolAttr>(
this, StandardAttributes::Bool, this, false);
impl->trueAttr = AttributeUniquer::get<BoolAttr>(
this, StandardAttributes::Bool, this, true);
/// Unit Attribute.
impl->unitAttr =
AttributeUniquer::get<UnitAttr>(this, StandardAttributes::Unit);
/// Unknown Location Attribute.
impl->unknownLocAttr = AttributeUniquer::get<UnknownLoc>(
this, StandardAttributes::UnknownLocation);
}
MLIRContext::~MLIRContext() {}
/// Copy the specified array of elements into memory managed by the provided
/// bump pointer allocator. This assumes the elements are all PODs.
template <typename T>
static ArrayRef<T> copyArrayRefInto(llvm::BumpPtrAllocator &allocator,
ArrayRef<T> elements) {
auto result = allocator.Allocate<T>(elements.size());
std::uninitialized_copy(elements.begin(), elements.end(), result);
return ArrayRef<T>(result, elements.size());
}
//===----------------------------------------------------------------------===//
// Diagnostic Handlers
//===----------------------------------------------------------------------===//
/// Returns the diagnostic engine for this context.
DiagnosticEngine &MLIRContext::getDiagEngine() { return getImpl().diagEngine; }
//===----------------------------------------------------------------------===//
// Dialect and Operation Registration
//===----------------------------------------------------------------------===//
/// Return information about all registered IR dialects.
std::vector<Dialect *> MLIRContext::getRegisteredDialects() {
// Lock access to the context registry.
ScopedReaderLock registryLock(impl->contextMutex, impl->threadingIsEnabled);
std::vector<Dialect *> result;
result.reserve(impl->dialects.size());
for (auto &dialect : impl->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) {
// Lock access to the context registry.
ScopedReaderLock registryLock(impl->contextMutex, impl->threadingIsEnabled);
// Dialects are sorted by name, so we can use binary search for lookup.
auto it = llvm::lower_bound(
impl->dialects, name,
[](const auto &lhs, StringRef rhs) { return lhs->getNamespace() < rhs; });
return (it != impl->dialects.end() && (*it)->getNamespace() == name)
? (*it).get()
: nullptr;
}
/// Register this dialect object with the specified context. The context
/// takes ownership of the heap allocated dialect.
void Dialect::registerDialect(MLIRContext *context) {
auto &impl = context->getImpl();
std::unique_ptr<Dialect> dialect(this);
// Lock access to the context registry.
ScopedWriterLock registryLock(impl.contextMutex, impl.threadingIsEnabled);
// Get the correct insertion position sorted by namespace.
auto insertPt = llvm::lower_bound(
impl.dialects, dialect, [](const auto &lhs, const auto &rhs) {
return lhs->getNamespace() < rhs->getNamespace();
});
// Abort if dialect with namespace has already been registered.
if (insertPt != impl.dialects.end() &&
(*insertPt)->getNamespace() == getNamespace()) {
llvm::report_fatal_error("a dialect with namespace '" + getNamespace() +
"' has already been registered");
}
impl.dialects.insert(insertPt, std::move(dialect));
}
bool MLIRContext::allowsUnregisteredDialects() {
return impl->allowUnregisteredDialects;
}
void MLIRContext::allowUnregisteredDialects(bool allowing) {
impl->allowUnregisteredDialects = allowing;
}
/// Return true if multi-threading is disabled by the context.
bool MLIRContext::isMultithreadingEnabled() {
return impl->threadingIsEnabled && llvm::llvm_is_multithreaded();
}
/// Set the flag specifying if multi-threading is disabled by the context.
void MLIRContext::disableMultithreading(bool disable) {
impl->threadingIsEnabled = !disable;
// Update the threading mode for each of the uniquers.
impl->affineUniquer.disableMultithreading(disable);
impl->attributeUniquer.disableMultithreading(disable);
impl->typeUniquer.disableMultithreading(disable);
}
/// Return true if we should attach the operation to diagnostics emitted via
/// Operation::emit.
bool MLIRContext::shouldPrintOpOnDiagnostic() {
return impl->printOpOnDiagnostic;
}
/// Set the flag specifying if we should attach the operation to diagnostics
/// emitted via Operation::emit.
void MLIRContext::printOpOnDiagnostic(bool enable) {
impl->printOpOnDiagnostic = enable;
}
/// Return true if we should attach the current stacktrace to diagnostics when
/// emitted.
bool MLIRContext::shouldPrintStackTraceOnDiagnostic() {
return impl->printStackTraceOnDiagnostic;
}
/// Set the flag specifying if we should attach the current stacktrace when
/// emitting diagnostics.
void MLIRContext::printStackTraceOnDiagnostic(bool enable) {
impl->printStackTraceOnDiagnostic = enable;
}
/// 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() {
std::vector<std::pair<StringRef, AbstractOperation *>> opsToSort;
{ // Lock access to the context registry.
ScopedReaderLock registryLock(impl->contextMutex, impl->threadingIsEnabled);
// 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.
llvm::StringMap<AbstractOperation> &registeredOps =
impl->registeredOperations;
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((getNamespace().empty() ||
opInfo.name.split('.').first == getNamespace()) &&
"op name doesn't start with dialect namespace");
assert(&opInfo.dialect == this && "Dialect object mismatch");
auto &impl = context->getImpl();
// Lock access to the context registry.
ScopedWriterLock registryLock(impl.contextMutex, impl.threadingIsEnabled);
if (!impl.registeredOperations.insert({opInfo.name, opInfo}).second) {
llvm::errs() << "error: operation named '" << opInfo.name
<< "' is already registered.\n";
abort();
}
}
/// Register a dialect-specific symbol(e.g. type) with the current context.
void Dialect::addSymbol(TypeID typeID) {
auto &impl = context->getImpl();
// Lock access to the context registry.
ScopedWriterLock registryLock(impl.contextMutex, impl.threadingIsEnabled);
if (!impl.registeredDialectSymbols.insert({typeID, this}).second) {
llvm::errs() << "error: dialect symbol already registered.\n";
abort();
}
}
/// 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();
// Lock access to the context registry.
ScopedReaderLock registryLock(impl.contextMutex, impl.threadingIsEnabled);
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, MLIRContext *context) {
auto &impl = context->getImpl();
// Check for an existing identifier in read-only mode.
if (context->isMultithreadingEnabled()) {
llvm::sys::SmartScopedReader<true> contextLock(impl.identifierMutex);
auto it = impl.identifiers.find(str);
if (it != impl.identifiers.end())
return Identifier(&*it);
}
// Check invariants after seeing if we already have something in the
// identifier table - if we already had it in the table, then it already
// passed invariant checks.
assert(!str.empty() && "Cannot create an empty identifier");
assert(str.find('\0') == StringRef::npos &&
"Cannot create an identifier with a nul character");
// Acquire a writer-lock so that we can safely create the new instance.
ScopedWriterLock contextLock(impl.identifierMutex, impl.threadingIsEnabled);
auto it = impl.identifiers.insert(str).first;
return Identifier(&*it);
}
//===----------------------------------------------------------------------===//
// Type uniquing
//===----------------------------------------------------------------------===//
static Dialect &lookupDialectForSymbol(MLIRContext *ctx, TypeID typeID) {
auto &impl = ctx->getImpl();
auto it = impl.registeredDialectSymbols.find(typeID);
assert(it != impl.registeredDialectSymbols.end() &&
"symbol is not registered.");
return *it->second;
}
/// Returns the storage uniquer used for constructing type storage instances.
/// This should not be used directly.
StorageUniquer &MLIRContext::getTypeUniquer() { return getImpl().typeUniquer; }
/// Get the dialect that registered the type with the provided typeid.
Dialect &TypeUniquer::lookupDialectForType(MLIRContext *ctx, TypeID typeID) {
return lookupDialectForSymbol(ctx, typeID);
}
FloatType FloatType::get(StandardTypes::Kind kind, MLIRContext *context) {
assert(kindof(kind) && "Not a FP kind.");
switch (kind) {
case StandardTypes::BF16:
return context->getImpl().bf16Ty;
case StandardTypes::F16:
return context->getImpl().f16Ty;
case StandardTypes::F32:
return context->getImpl().f32Ty;
case StandardTypes::F64:
return context->getImpl().f64Ty;
default:
llvm_unreachable("unexpected floating-point kind");
}
}
/// Get an instance of the IndexType.
IndexType IndexType::get(MLIRContext *context) {
return context->getImpl().indexTy;
}
/// Return an existing integer type instance if one is cached within the
/// context.
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
static IntegerType
getCachedIntegerType(unsigned width,
IntegerType::SignednessSemantics signedness,
MLIRContext *context) {
if (signedness != IntegerType::Signless)
return IntegerType();
switch (width) {
case 1:
return context->getImpl().int1Ty;
case 8:
return context->getImpl().int8Ty;
case 16:
return context->getImpl().int16Ty;
case 32:
return context->getImpl().int32Ty;
case 64:
return context->getImpl().int64Ty;
case 128:
return context->getImpl().int128Ty;
default:
return IntegerType();
}
}
IntegerType IntegerType::get(unsigned width, MLIRContext *context) {
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
return get(width, IntegerType::Signless, context);
}
IntegerType IntegerType::get(unsigned width,
IntegerType::SignednessSemantics signedness,
MLIRContext *context) {
if (auto cached = getCachedIntegerType(width, signedness, context))
return cached;
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
return Base::get(context, StandardTypes::Integer, width, signedness);
}
IntegerType IntegerType::getChecked(unsigned width, Location location) {
return getChecked(width, IntegerType::Signless, location);
}
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
IntegerType IntegerType::getChecked(unsigned width,
SignednessSemantics signedness,
Location location) {
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
if (auto cached =
getCachedIntegerType(width, signedness, location->getContext()))
return cached;
[mlir] Add a signedness semantics bit to IntegerType Thus far IntegerType has been signless: a value of IntegerType does not have a sign intrinsically and it's up to the specific operation to decide how to interpret those bits. For example, std.addi does two's complement arithmetic, and std.divis/std.diviu treats the first bit as a sign. This design choice was made some time ago when we did't have lots of dialects and dialects were more rigid. Today we have much more extensible infrastructure and different dialect may want different modelling over integer signedness. So while we can say we want signless integers in the standard dialect, we cannot dictate for others. Requiring each dialect to model the signedness semantics with another set of custom types is duplicating the functionality everywhere, considering the fundamental role integer types play. This CL extends the IntegerType with a signedness semantics bit. This gives each dialect an option to opt in signedness semantics if that's what they want and helps code sharing. The parser is modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as signed and unsigned integer types, respectively, leaving the original `i[1-9][0-9]*` to continue to mean no indication over signedness semantics. All existing dialects are not affected (yet) as this is a feature to opt in. More discussions can be found at: https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ Differential Revision: https://reviews.llvm.org/D72533
2020-01-11 03:48:24 +08:00
return Base::getChecked(location, StandardTypes::Integer, width, signedness);
}
/// Get an instance of the NoneType.
NoneType NoneType::get(MLIRContext *context) {
return context->getImpl().noneType;
}
//===----------------------------------------------------------------------===//
// Attribute uniquing
//===----------------------------------------------------------------------===//
/// Returns the storage uniquer used for constructing attribute storage
/// instances. This should not be used directly.
StorageUniquer &MLIRContext::getAttributeUniquer() {
return getImpl().attributeUniquer;
}
/// Initialize the given attribute storage instance.
void AttributeUniquer::initializeAttributeStorage(AttributeStorage *storage,
MLIRContext *ctx,
TypeID attrID) {
storage->initializeDialect(lookupDialectForSymbol(ctx, attrID));
// If the attribute did not provide a type, then default to NoneType.
if (!storage->getType())
storage->setType(NoneType::get(ctx));
}
BoolAttr BoolAttr::get(bool value, MLIRContext *context) {
return value ? context->getImpl().trueAttr : context->getImpl().falseAttr;
}
UnitAttr UnitAttr::get(MLIRContext *context) {
return context->getImpl().unitAttr;
}
Location UnknownLoc::get(MLIRContext *context) {
return context->getImpl().unknownLocAttr;
}
//===----------------------------------------------------------------------===//
// AffineMap uniquing
//===----------------------------------------------------------------------===//
StorageUniquer &MLIRContext::getAffineUniquer() {
return getImpl().affineUniquer;
}
AffineMap AffineMap::getImpl(unsigned dimCount, unsigned symbolCount,
ArrayRef<AffineExpr> results,
MLIRContext *context) {
auto &impl = context->getImpl();
auto key = std::make_tuple(dimCount, symbolCount, results);
// Safely get or create an AffineMap instance.
return safeGetOrCreate(
impl.affineMaps, key, impl.affineMutex, impl.threadingIsEnabled, [&] {
auto *res = impl.affineAllocator.Allocate<detail::AffineMapStorage>();
// Copy the results into the bump pointer.
results = copyArrayRefInto(impl.affineAllocator, results);
// Initialize the memory using placement new.
new (res)
detail::AffineMapStorage{dimCount, symbolCount, results, context};
return AffineMap(res);
});
}
AffineMap AffineMap::get(MLIRContext *context) {
return getImpl(/*dimCount=*/0, /*symbolCount=*/0, /*results=*/{}, context);
}
AffineMap AffineMap::get(unsigned dimCount, unsigned symbolCount,
MLIRContext *context) {
return getImpl(dimCount, symbolCount, /*results=*/{}, context);
}
AffineMap AffineMap::get(unsigned dimCount, unsigned symbolCount,
AffineExpr result) {
return getImpl(dimCount, symbolCount, {result}, result.getContext());
}
AffineMap AffineMap::get(unsigned dimCount, unsigned symbolCount,
ArrayRef<AffineExpr> results, MLIRContext *context) {
return getImpl(dimCount, symbolCount, results, context);
}
//===----------------------------------------------------------------------===//
// 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());
auto &impl = constraints[0].getContext()->getImpl();
// A utility function to construct a new IntegerSetStorage instance.
auto constructorFn = [&] {
auto *res = impl.affineAllocator.Allocate<detail::IntegerSetStorage>();
// Copy the results and equality flags into the bump pointer.
constraints = copyArrayRefInto(impl.affineAllocator, constraints);
eqFlags = copyArrayRefInto(impl.affineAllocator, eqFlags);
// Initialize the memory using placement new.
new (res)
detail::IntegerSetStorage{dimCount, symbolCount, constraints, eqFlags};
return IntegerSet(res);
};
// If this instance is uniqued, then we handle it separately so that multiple
// threads may simultaneously access existing instances.
if (constraints.size() < IntegerSet::kUniquingThreshold) {
auto key = std::make_tuple(dimCount, symbolCount, constraints, eqFlags);
return safeGetOrCreate(impl.integerSets, key, impl.affineMutex,
impl.threadingIsEnabled, constructorFn);
}
// Otherwise, acquire a writer-lock so that we can safely create the new
// instance.
ScopedWriterLock affineLock(impl.affineMutex, impl.threadingIsEnabled);
return constructorFn();
}
//===----------------------------------------------------------------------===//
// StorageUniquerSupport
//===----------------------------------------------------------------------===//
/// Utility method to generate a default location for use when checking the
/// construction invariants of a storage object. This is defined out-of-line to
/// avoid the need to include Location.h.
const AttributeStorage *
mlir::detail::generateUnknownStorageLocation(MLIRContext *ctx) {
return reinterpret_cast<const AttributeStorage *>(
ctx->getImpl().unknownLocAttr.getAsOpaquePointer());
}