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|
//===- BuiltinTypes.cpp - MLIR Builtin 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/BuiltinTypes.h"
#include "TypeDetail.h"
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/BuiltinAttributes.h"
#include "mlir/IR/BuiltinDialect.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/IR/Dialect.h"
#include "mlir/IR/TensorEncoding.h"
#include "mlir/IR/TypeUtilities.h"
#include "llvm/ADT/APFloat.h"
#include "llvm/ADT/BitVector.h"
#include "llvm/ADT/Sequence.h"
#include "llvm/ADT/Twine.h"
#include "llvm/ADT/TypeSwitch.h"
using namespace mlir;
using namespace mlir::detail;
//===----------------------------------------------------------------------===//
/// Tablegen Type Definitions
//===----------------------------------------------------------------------===//
#define GET_TYPEDEF_CLASSES
#include "mlir/IR/BuiltinTypes.cpp.inc"
//===----------------------------------------------------------------------===//
// BuiltinDialect
//===----------------------------------------------------------------------===//
void BuiltinDialect::registerTypes() {
addTypes<
#define GET_TYPEDEF_LIST
#include "mlir/IR/BuiltinTypes.cpp.inc"
>();
}
//===----------------------------------------------------------------------===//
/// ComplexType
//===----------------------------------------------------------------------===//
/// Verify the construction of an integer type.
LogicalResult ComplexType::verify(function_ref<InFlightDiagnostic()> emitError,
Type elementType) {
if (!elementType.isIntOrFloat())
return emitError() << "invalid element type for complex";
return success();
}
//===----------------------------------------------------------------------===//
// Integer Type
//===----------------------------------------------------------------------===//
/// Verify the construction of an integer type.
LogicalResult IntegerType::verify(function_ref<InFlightDiagnostic()> emitError,
unsigned width,
SignednessSemantics signedness) {
if (width > IntegerType::kMaxWidth) {
return emitError() << "integer bitwidth is limited to "
<< IntegerType::kMaxWidth << " bits";
}
return success();
}
unsigned IntegerType::getWidth() const { return getImpl()->width; }
IntegerType::SignednessSemantics IntegerType::getSignedness() const {
return getImpl()->signedness;
}
IntegerType IntegerType::scaleElementBitwidth(unsigned scale) {
if (!scale)
return IntegerType();
return IntegerType::get(getContext(), scale * getWidth(), getSignedness());
}
//===----------------------------------------------------------------------===//
// Float Type
//===----------------------------------------------------------------------===//
unsigned FloatType::getWidth() {
if (llvm::isa<Float8E5M2Type, Float8E4M3FNType, Float8E5M2FNUZType,
Float8E4M3FNUZType, Float8E4M3B11FNUZType>(*this))
return 8;
if (llvm::isa<Float16Type, BFloat16Type>(*this))
return 16;
if (llvm::isa<Float32Type, FloatTF32Type>(*this))
return 32;
if (llvm::isa<Float64Type>(*this))
return 64;
if (llvm::isa<Float80Type>(*this))
return 80;
if (llvm::isa<Float128Type>(*this))
return 128;
llvm_unreachable("unexpected float type");
}
/// Returns the floating semantics for the given type.
const llvm::fltSemantics &FloatType::getFloatSemantics() {
if (llvm::isa<Float8E5M2Type>(*this))
return APFloat::Float8E5M2();
if (llvm::isa<Float8E4M3FNType>(*this))
return APFloat::Float8E4M3FN();
if (llvm::isa<Float8E5M2FNUZType>(*this))
return APFloat::Float8E5M2FNUZ();
if (llvm::isa<Float8E4M3FNUZType>(*this))
return APFloat::Float8E4M3FNUZ();
if (llvm::isa<Float8E4M3B11FNUZType>(*this))
return APFloat::Float8E4M3B11FNUZ();
if (llvm::isa<BFloat16Type>(*this))
return APFloat::BFloat();
if (llvm::isa<Float16Type>(*this))
return APFloat::IEEEhalf();
if (llvm::isa<FloatTF32Type>(*this))
return APFloat::FloatTF32();
if (llvm::isa<Float32Type>(*this))
return APFloat::IEEEsingle();
if (llvm::isa<Float64Type>(*this))
return APFloat::IEEEdouble();
if (llvm::isa<Float80Type>(*this))
return APFloat::x87DoubleExtended();
if (llvm::isa<Float128Type>(*this))
return APFloat::IEEEquad();
llvm_unreachable("non-floating point type used");
}
FloatType FloatType::scaleElementBitwidth(unsigned scale) {
if (!scale)
return FloatType();
MLIRContext *ctx = getContext();
if (isF16() || isBF16()) {
if (scale == 2)
return FloatType::getF32(ctx);
if (scale == 4)
return FloatType::getF64(ctx);
}
if (isF32())
if (scale == 2)
return FloatType::getF64(ctx);
return FloatType();
}
unsigned FloatType::getFPMantissaWidth() {
return APFloat::semanticsPrecision(getFloatSemantics());
}
//===----------------------------------------------------------------------===//
// FunctionType
//===----------------------------------------------------------------------===//
unsigned FunctionType::getNumInputs() const { return getImpl()->numInputs; }
ArrayRef<Type> FunctionType::getInputs() const {
return getImpl()->getInputs();
}
unsigned FunctionType::getNumResults() const { return getImpl()->numResults; }
ArrayRef<Type> FunctionType::getResults() const {
return getImpl()->getResults();
}
FunctionType FunctionType::clone(TypeRange inputs, TypeRange results) const {
return get(getContext(), inputs, results);
}
/// Returns a new function type with the specified arguments and results
/// inserted.
FunctionType FunctionType::getWithArgsAndResults(
ArrayRef<unsigned> argIndices, TypeRange argTypes,
ArrayRef<unsigned> resultIndices, TypeRange resultTypes) {
SmallVector<Type> argStorage, resultStorage;
TypeRange newArgTypes =
insertTypesInto(getInputs(), argIndices, argTypes, argStorage);
TypeRange newResultTypes =
insertTypesInto(getResults(), resultIndices, resultTypes, resultStorage);
return clone(newArgTypes, newResultTypes);
}
/// Returns a new function type without the specified arguments and results.
FunctionType
FunctionType::getWithoutArgsAndResults(const BitVector &argIndices,
const BitVector &resultIndices) {
SmallVector<Type> argStorage, resultStorage;
TypeRange newArgTypes = filterTypesOut(getInputs(), argIndices, argStorage);
TypeRange newResultTypes =
filterTypesOut(getResults(), resultIndices, resultStorage);
return clone(newArgTypes, newResultTypes);
}
//===----------------------------------------------------------------------===//
// OpaqueType
//===----------------------------------------------------------------------===//
/// Verify the construction of an opaque type.
LogicalResult OpaqueType::verify(function_ref<InFlightDiagnostic()> emitError,
StringAttr dialect, StringRef typeData) {
if (!Dialect::isValidNamespace(dialect.strref()))
return emitError() << "invalid dialect namespace '" << dialect << "'";
// Check that the dialect is actually registered.
MLIRContext *context = dialect.getContext();
if (!context->allowsUnregisteredDialects() &&
!context->getLoadedDialect(dialect.strref())) {
return emitError()
<< "`!" << dialect << "<\"" << typeData << "\">"
<< "` type created with unregistered dialect. If this is "
"intended, please call allowUnregisteredDialects() on the "
"MLIRContext, or use -allow-unregistered-dialect with "
"the MLIR opt tool used";
}
return success();
}
//===----------------------------------------------------------------------===//
// VectorType
//===----------------------------------------------------------------------===//
LogicalResult VectorType::verify(function_ref<InFlightDiagnostic()> emitError,
ArrayRef<int64_t> shape, Type elementType,
ArrayRef<bool> scalableDims) {
if (!isValidElementType(elementType))
return emitError()
<< "vector elements must be int/index/float type but got "
<< elementType;
if (any_of(shape, [](int64_t i) { return i <= 0; }))
return emitError()
<< "vector types must have positive constant sizes but got "
<< shape;
if (scalableDims.size() != shape.size())
return emitError() << "number of dims must match, got "
<< scalableDims.size() << " and " << shape.size();
return success();
}
VectorType VectorType::scaleElementBitwidth(unsigned scale) {
if (!scale)
return VectorType();
if (auto et = llvm::dyn_cast<IntegerType>(getElementType()))
if (auto scaledEt = et.scaleElementBitwidth(scale))
return VectorType::get(getShape(), scaledEt, getScalableDims());
if (auto et = llvm::dyn_cast<FloatType>(getElementType()))
if (auto scaledEt = et.scaleElementBitwidth(scale))
return VectorType::get(getShape(), scaledEt, getScalableDims());
return VectorType();
}
VectorType VectorType::cloneWith(std::optional<ArrayRef<int64_t>> shape,
Type elementType) const {
return VectorType::get(shape.value_or(getShape()), elementType,
getScalableDims());
}
//===----------------------------------------------------------------------===//
// TensorType
//===----------------------------------------------------------------------===//
Type TensorType::getElementType() const {
return llvm::TypeSwitch<TensorType, Type>(*this)
.Case<RankedTensorType, UnrankedTensorType>(
[](auto type) { return type.getElementType(); });
}
bool TensorType::hasRank() const { return !llvm::isa<UnrankedTensorType>(*this); }
ArrayRef<int64_t> TensorType::getShape() const {
return llvm::cast<RankedTensorType>(*this).getShape();
}
TensorType TensorType::cloneWith(std::optional<ArrayRef<int64_t>> shape,
Type elementType) const {
if (llvm::dyn_cast<UnrankedTensorType>(*this)) {
if (shape)
return RankedTensorType::get(*shape, elementType);
return UnrankedTensorType::get(elementType);
}
auto rankedTy = llvm::cast<RankedTensorType>(*this);
if (!shape)
return RankedTensorType::get(rankedTy.getShape(), elementType,
rankedTy.getEncoding());
return RankedTensorType::get(shape.value_or(rankedTy.getShape()), elementType,
rankedTy.getEncoding());
}
RankedTensorType TensorType::clone(::llvm::ArrayRef<int64_t> shape,
Type elementType) const {
return ::llvm::cast<RankedTensorType>(cloneWith(shape, elementType));
}
RankedTensorType TensorType::clone(::llvm::ArrayRef<int64_t> shape) const {
return ::llvm::cast<RankedTensorType>(cloneWith(shape, getElementType()));
}
// Check if "elementType" can be an element type of a tensor.
static LogicalResult
checkTensorElementType(function_ref<InFlightDiagnostic()> emitError,
Type elementType) {
if (!TensorType::isValidElementType(elementType))
return emitError() << "invalid tensor element type: " << elementType;
return success();
}
/// Return true if the specified element type is ok in a tensor.
bool TensorType::isValidElementType(Type type) {
// Note: Non standard/builtin types are allowed to exist within tensor
// types. Dialects are expected to verify that tensor types have a valid
// element type within that dialect.
return llvm::isa<ComplexType, FloatType, IntegerType, OpaqueType, VectorType,
IndexType>(type) ||
!llvm::isa<BuiltinDialect>(type.getDialect());
}
//===----------------------------------------------------------------------===//
// RankedTensorType
//===----------------------------------------------------------------------===//
LogicalResult
RankedTensorType::verify(function_ref<InFlightDiagnostic()> emitError,
ArrayRef<int64_t> shape, Type elementType,
Attribute encoding) {
for (int64_t s : shape)
if (s < 0 && !ShapedType::isDynamic(s))
return emitError() << "invalid tensor dimension size";
if (auto v = llvm::dyn_cast_or_null<VerifiableTensorEncoding>(encoding))
if (failed(v.verifyEncoding(shape, elementType, emitError)))
return failure();
return checkTensorElementType(emitError, elementType);
}
//===----------------------------------------------------------------------===//
// UnrankedTensorType
//===----------------------------------------------------------------------===//
LogicalResult
UnrankedTensorType::verify(function_ref<InFlightDiagnostic()> emitError,
Type elementType) {
return checkTensorElementType(emitError, elementType);
}
//===----------------------------------------------------------------------===//
// BaseMemRefType
//===----------------------------------------------------------------------===//
Type BaseMemRefType::getElementType() const {
return llvm::TypeSwitch<BaseMemRefType, Type>(*this)
.Case<MemRefType, UnrankedMemRefType>(
[](auto type) { return type.getElementType(); });
}
bool BaseMemRefType::hasRank() const { return !llvm::isa<UnrankedMemRefType>(*this); }
ArrayRef<int64_t> BaseMemRefType::getShape() const {
return llvm::cast<MemRefType>(*this).getShape();
}
BaseMemRefType BaseMemRefType::cloneWith(std::optional<ArrayRef<int64_t>> shape,
Type elementType) const {
if (llvm::dyn_cast<UnrankedMemRefType>(*this)) {
if (!shape)
return UnrankedMemRefType::get(elementType, getMemorySpace());
MemRefType::Builder builder(*shape, elementType);
builder.setMemorySpace(getMemorySpace());
return builder;
}
MemRefType::Builder builder(llvm::cast<MemRefType>(*this));
if (shape)
builder.setShape(*shape);
builder.setElementType(elementType);
return builder;
}
MemRefType BaseMemRefType::clone(::llvm::ArrayRef<int64_t> shape,
Type elementType) const {
return ::llvm::cast<MemRefType>(cloneWith(shape, elementType));
}
MemRefType BaseMemRefType::clone(::llvm::ArrayRef<int64_t> shape) const {
return ::llvm::cast<MemRefType>(cloneWith(shape, getElementType()));
}
Attribute BaseMemRefType::getMemorySpace() const {
if (auto rankedMemRefTy = llvm::dyn_cast<MemRefType>(*this))
return rankedMemRefTy.getMemorySpace();
return llvm::cast<UnrankedMemRefType>(*this).getMemorySpace();
}
unsigned BaseMemRefType::getMemorySpaceAsInt() const {
if (auto rankedMemRefTy = llvm::dyn_cast<MemRefType>(*this))
return rankedMemRefTy.getMemorySpaceAsInt();
return llvm::cast<UnrankedMemRefType>(*this).getMemorySpaceAsInt();
}
//===----------------------------------------------------------------------===//
// MemRefType
//===----------------------------------------------------------------------===//
/// Given an `originalShape` and a `reducedShape` assumed to be a subset of
/// `originalShape` with some `1` entries erased, return the set of indices
/// that specifies which of the entries of `originalShape` are dropped to obtain
/// `reducedShape`. The returned mask can be applied as a projection to
/// `originalShape` to obtain the `reducedShape`. This mask is useful to track
/// which dimensions must be kept when e.g. compute MemRef strides under
/// rank-reducing operations. Return std::nullopt if reducedShape cannot be
/// obtained by dropping only `1` entries in `originalShape`.
std::optional<llvm::SmallDenseSet<unsigned>>
mlir::computeRankReductionMask(ArrayRef<int64_t> originalShape,
ArrayRef<int64_t> reducedShape) {
size_t originalRank = originalShape.size(), reducedRank = reducedShape.size();
llvm::SmallDenseSet<unsigned> unusedDims;
unsigned reducedIdx = 0;
for (unsigned originalIdx = 0; originalIdx < originalRank; ++originalIdx) {
// Greedily insert `originalIdx` if match.
if (reducedIdx < reducedRank &&
originalShape[originalIdx] == reducedShape[reducedIdx]) {
reducedIdx++;
continue;
}
unusedDims.insert(originalIdx);
// If no match on `originalIdx`, the `originalShape` at this dimension
// must be 1, otherwise we bail.
if (originalShape[originalIdx] != 1)
return std::nullopt;
}
// The whole reducedShape must be scanned, otherwise we bail.
if (reducedIdx != reducedRank)
return std::nullopt;
return unusedDims;
}
SliceVerificationResult
mlir::isRankReducedType(ShapedType originalType,
ShapedType candidateReducedType) {
if (originalType == candidateReducedType)
return SliceVerificationResult::Success;
ShapedType originalShapedType = llvm::cast<ShapedType>(originalType);
ShapedType candidateReducedShapedType =
llvm::cast<ShapedType>(candidateReducedType);
// Rank and size logic is valid for all ShapedTypes.
ArrayRef<int64_t> originalShape = originalShapedType.getShape();
ArrayRef<int64_t> candidateReducedShape =
candidateReducedShapedType.getShape();
unsigned originalRank = originalShape.size(),
candidateReducedRank = candidateReducedShape.size();
if (candidateReducedRank > originalRank)
return SliceVerificationResult::RankTooLarge;
auto optionalUnusedDimsMask =
computeRankReductionMask(originalShape, candidateReducedShape);
// Sizes cannot be matched in case empty vector is returned.
if (!optionalUnusedDimsMask)
return SliceVerificationResult::SizeMismatch;
if (originalShapedType.getElementType() !=
candidateReducedShapedType.getElementType())
return SliceVerificationResult::ElemTypeMismatch;
return SliceVerificationResult::Success;
}
bool mlir::detail::isSupportedMemorySpace(Attribute memorySpace) {
// Empty attribute is allowed as default memory space.
if (!memorySpace)
return true;
// Supported built-in attributes.
if (llvm::isa<IntegerAttr, StringAttr, DictionaryAttr>(memorySpace))
return true;
// Allow custom dialect attributes.
if (!isa<BuiltinDialect>(memorySpace.getDialect()))
return true;
return false;
}
Attribute mlir::detail::wrapIntegerMemorySpace(unsigned memorySpace,
MLIRContext *ctx) {
if (memorySpace == 0)
return nullptr;
return IntegerAttr::get(IntegerType::get(ctx, 64), memorySpace);
}
Attribute mlir::detail::skipDefaultMemorySpace(Attribute memorySpace) {
IntegerAttr intMemorySpace = llvm::dyn_cast_or_null<IntegerAttr>(memorySpace);
if (intMemorySpace && intMemorySpace.getValue() == 0)
return nullptr;
return memorySpace;
}
unsigned mlir::detail::getMemorySpaceAsInt(Attribute memorySpace) {
if (!memorySpace)
return 0;
assert(llvm::isa<IntegerAttr>(memorySpace) &&
"Using `getMemorySpaceInteger` with non-Integer attribute");
return static_cast<unsigned>(llvm::cast<IntegerAttr>(memorySpace).getInt());
}
unsigned MemRefType::getMemorySpaceAsInt() const {
return detail::getMemorySpaceAsInt(getMemorySpace());
}
MemRefType MemRefType::get(ArrayRef<int64_t> shape, Type elementType,
MemRefLayoutAttrInterface layout,
Attribute memorySpace) {
// Use default layout for empty attribute.
if (!layout)
layout = AffineMapAttr::get(AffineMap::getMultiDimIdentityMap(
shape.size(), elementType.getContext()));
// Drop default memory space value and replace it with empty attribute.
memorySpace = skipDefaultMemorySpace(memorySpace);
return Base::get(elementType.getContext(), shape, elementType, layout,
memorySpace);
}
MemRefType MemRefType::getChecked(
function_ref<InFlightDiagnostic()> emitErrorFn, ArrayRef<int64_t> shape,
Type elementType, MemRefLayoutAttrInterface layout, Attribute memorySpace) {
// Use default layout for empty attribute.
if (!layout)
layout = AffineMapAttr::get(AffineMap::getMultiDimIdentityMap(
shape.size(), elementType.getContext()));
// Drop default memory space value and replace it with empty attribute.
memorySpace = skipDefaultMemorySpace(memorySpace);
return Base::getChecked(emitErrorFn, elementType.getContext(), shape,
elementType, layout, memorySpace);
}
MemRefType MemRefType::get(ArrayRef<int64_t> shape, Type elementType,
AffineMap map, Attribute memorySpace) {
// Use default layout for empty map.
if (!map)
map = AffineMap::getMultiDimIdentityMap(shape.size(),
elementType.getContext());
// Wrap AffineMap into Attribute.
auto layout = AffineMapAttr::get(map);
// Drop default memory space value and replace it with empty attribute.
memorySpace = skipDefaultMemorySpace(memorySpace);
return Base::get(elementType.getContext(), shape, elementType, layout,
memorySpace);
}
MemRefType
MemRefType::getChecked(function_ref<InFlightDiagnostic()> emitErrorFn,
ArrayRef<int64_t> shape, Type elementType, AffineMap map,
Attribute memorySpace) {
// Use default layout for empty map.
if (!map)
map = AffineMap::getMultiDimIdentityMap(shape.size(),
elementType.getContext());
// Wrap AffineMap into Attribute.
auto layout = AffineMapAttr::get(map);
// Drop default memory space value and replace it with empty attribute.
memorySpace = skipDefaultMemorySpace(memorySpace);
return Base::getChecked(emitErrorFn, elementType.getContext(), shape,
elementType, layout, memorySpace);
}
MemRefType MemRefType::get(ArrayRef<int64_t> shape, Type elementType,
AffineMap map, unsigned memorySpaceInd) {
// Use default layout for empty map.
if (!map)
map = AffineMap::getMultiDimIdentityMap(shape.size(),
elementType.getContext());
// Wrap AffineMap into Attribute.
auto layout = AffineMapAttr::get(map);
// Convert deprecated integer-like memory space to Attribute.
Attribute memorySpace =
wrapIntegerMemorySpace(memorySpaceInd, elementType.getContext());
return Base::get(elementType.getContext(), shape, elementType, layout,
memorySpace);
}
MemRefType
MemRefType::getChecked(function_ref<InFlightDiagnostic()> emitErrorFn,
ArrayRef<int64_t> shape, Type elementType, AffineMap map,
unsigned memorySpaceInd) {
// Use default layout for empty map.
if (!map)
map = AffineMap::getMultiDimIdentityMap(shape.size(),
elementType.getContext());
// Wrap AffineMap into Attribute.
auto layout = AffineMapAttr::get(map);
// Convert deprecated integer-like memory space to Attribute.
Attribute memorySpace =
wrapIntegerMemorySpace(memorySpaceInd, elementType.getContext());
return Base::getChecked(emitErrorFn, elementType.getContext(), shape,
elementType, layout, memorySpace);
}
LogicalResult MemRefType::verify(function_ref<InFlightDiagnostic()> emitError,
ArrayRef<int64_t> shape, Type elementType,
MemRefLayoutAttrInterface layout,
Attribute memorySpace) {
if (!BaseMemRefType::isValidElementType(elementType))
return emitError() << "invalid memref element type";
// Negative sizes are not allowed except for `kDynamic`.
for (int64_t s : shape)
if (s < 0 && !ShapedType::isDynamic(s))
return emitError() << "invalid memref size";
assert(layout && "missing layout specification");
if (failed(layout.verifyLayout(shape, emitError)))
return failure();
if (!isSupportedMemorySpace(memorySpace))
return emitError() << "unsupported memory space Attribute";
return success();
}
//===----------------------------------------------------------------------===//
// UnrankedMemRefType
//===----------------------------------------------------------------------===//
unsigned UnrankedMemRefType::getMemorySpaceAsInt() const {
return detail::getMemorySpaceAsInt(getMemorySpace());
}
LogicalResult
UnrankedMemRefType::verify(function_ref<InFlightDiagnostic()> emitError,
Type elementType, Attribute memorySpace) {
if (!BaseMemRefType::isValidElementType(elementType))
return emitError() << "invalid memref element type";
if (!isSupportedMemorySpace(memorySpace))
return emitError() << "unsupported memory space Attribute";
return success();
}
// Fallback cases for terminal dim/sym/cst that are not part of a binary op (
// i.e. single term). Accumulate the AffineExpr into the existing one.
static void extractStridesFromTerm(AffineExpr e,
AffineExpr multiplicativeFactor,
MutableArrayRef<AffineExpr> strides,
AffineExpr &offset) {
if (auto dim = dyn_cast<AffineDimExpr>(e))
strides[dim.getPosition()] =
strides[dim.getPosition()] + multiplicativeFactor;
else
offset = offset + e * multiplicativeFactor;
}
/// Takes a single AffineExpr `e` and populates the `strides` array with the
/// strides expressions for each dim position.
/// The convention is that the strides for dimensions d0, .. dn appear in
/// order to make indexing intuitive into the result.
static LogicalResult extractStrides(AffineExpr e,
AffineExpr multiplicativeFactor,
MutableArrayRef<AffineExpr> strides,
AffineExpr &offset) {
auto bin = dyn_cast<AffineBinaryOpExpr>(e);
if (!bin) {
extractStridesFromTerm(e, multiplicativeFactor, strides, offset);
return success();
}
if (bin.getKind() == AffineExprKind::CeilDiv ||
bin.getKind() == AffineExprKind::FloorDiv ||
bin.getKind() == AffineExprKind::Mod)
return failure();
if (bin.getKind() == AffineExprKind::Mul) {
auto dim = dyn_cast<AffineDimExpr>(bin.getLHS());
if (dim) {
strides[dim.getPosition()] =
strides[dim.getPosition()] + bin.getRHS() * multiplicativeFactor;
return success();
}
// LHS and RHS may both contain complex expressions of dims. Try one path
// and if it fails try the other. This is guaranteed to succeed because
// only one path may have a `dim`, otherwise this is not an AffineExpr in
// the first place.
if (bin.getLHS().isSymbolicOrConstant())
return extractStrides(bin.getRHS(), multiplicativeFactor * bin.getLHS(),
strides, offset);
return extractStrides(bin.getLHS(), multiplicativeFactor * bin.getRHS(),
strides, offset);
}
if (bin.getKind() == AffineExprKind::Add) {
auto res1 =
extractStrides(bin.getLHS(), multiplicativeFactor, strides, offset);
auto res2 =
extractStrides(bin.getRHS(), multiplicativeFactor, strides, offset);
return success(succeeded(res1) && succeeded(res2));
}
llvm_unreachable("unexpected binary operation");
}
/// A stride specification is a list of integer values that are either static
/// or dynamic (encoded with ShapedType::kDynamic). Strides encode
/// the distance in the number of elements between successive entries along a
/// particular dimension.
///
/// For example, `memref<42x16xf32, (64 * d0 + d1)>` specifies a view into a
/// non-contiguous memory region of `42` by `16` `f32` elements in which the
/// distance between two consecutive elements along the outer dimension is `1`
/// and the distance between two consecutive elements along the inner dimension
/// is `64`.
///
/// The convention is that the strides for dimensions d0, .. dn appear in
/// order to make indexing intuitive into the result.
static LogicalResult getStridesAndOffset(MemRefType t,
SmallVectorImpl<AffineExpr> &strides,
AffineExpr &offset) {
AffineMap m = t.getLayout().getAffineMap();
if (m.getNumResults() != 1 && !m.isIdentity())
return failure();
auto zero = getAffineConstantExpr(0, t.getContext());
auto one = getAffineConstantExpr(1, t.getContext());
offset = zero;
strides.assign(t.getRank(), zero);
// Canonical case for empty map.
if (m.isIdentity()) {
// 0-D corner case, offset is already 0.
if (t.getRank() == 0)
return success();
auto stridedExpr =
makeCanonicalStridedLayoutExpr(t.getShape(), t.getContext());
if (succeeded(extractStrides(stridedExpr, one, strides, offset)))
return success();
assert(false && "unexpected failure: extract strides in canonical layout");
}
// Non-canonical case requires more work.
auto stridedExpr =
simplifyAffineExpr(m.getResult(0), m.getNumDims(), m.getNumSymbols());
if (failed(extractStrides(stridedExpr, one, strides, offset))) {
offset = AffineExpr();
strides.clear();
return failure();
}
// Simplify results to allow folding to constants and simple checks.
unsigned numDims = m.getNumDims();
unsigned numSymbols = m.getNumSymbols();
offset = simplifyAffineExpr(offset, numDims, numSymbols);
for (auto &stride : strides)
stride = simplifyAffineExpr(stride, numDims, numSymbols);
// In practice, a strided memref must be internally non-aliasing. Test
// against 0 as a proxy.
// TODO: static cases can have more advanced checks.
// TODO: dynamic cases would require a way to compare symbolic
// expressions and would probably need an affine set context propagated
// everywhere.
if (llvm::any_of(strides, [](AffineExpr e) {
return e == getAffineConstantExpr(0, e.getContext());
})) {
offset = AffineExpr();
strides.clear();
return failure();
}
return success();
}
LogicalResult mlir::getStridesAndOffset(MemRefType t,
SmallVectorImpl<int64_t> &strides,
int64_t &offset) {
// Happy path: the type uses the strided layout directly.
if (auto strided = llvm::dyn_cast<StridedLayoutAttr>(t.getLayout())) {
llvm::append_range(strides, strided.getStrides());
offset = strided.getOffset();
return success();
}
// Otherwise, defer to the affine fallback as layouts are supposed to be
// convertible to affine maps.
AffineExpr offsetExpr;
SmallVector<AffineExpr, 4> strideExprs;
if (failed(::getStridesAndOffset(t, strideExprs, offsetExpr)))
return failure();
if (auto cst = dyn_cast<AffineConstantExpr>(offsetExpr))
offset = cst.getValue();
else
offset = ShapedType::kDynamic;
for (auto e : strideExprs) {
if (auto c = dyn_cast<AffineConstantExpr>(e))
strides.push_back(c.getValue());
else
strides.push_back(ShapedType::kDynamic);
}
return success();
}
std::pair<SmallVector<int64_t>, int64_t>
mlir::getStridesAndOffset(MemRefType t) {
SmallVector<int64_t> strides;
int64_t offset;
LogicalResult status = getStridesAndOffset(t, strides, offset);
(void)status;
assert(succeeded(status) && "Invalid use of check-free getStridesAndOffset");
return {strides, offset};
}
//===----------------------------------------------------------------------===//
/// TupleType
//===----------------------------------------------------------------------===//
/// Return the elements types for this tuple.
ArrayRef<Type> TupleType::getTypes() const { return getImpl()->getTypes(); }
/// Accumulate the types contained in this tuple and tuples nested within it.
/// Note that this only flattens nested tuples, not any other container type,
/// e.g. a tuple<i32, tensor<i32>, tuple<f32, tuple<i64>>> is flattened to
/// (i32, tensor<i32>, f32, i64)
void TupleType::getFlattenedTypes(SmallVectorImpl<Type> &types) {
for (Type type : getTypes()) {
if (auto nestedTuple = llvm::dyn_cast<TupleType>(type))
nestedTuple.getFlattenedTypes(types);
else
types.push_back(type);
}
}
/// Return the number of element types.
size_t TupleType::size() const { return getImpl()->size(); }
//===----------------------------------------------------------------------===//
// Type Utilities
//===----------------------------------------------------------------------===//
/// Return a version of `t` with identity layout if it can be determined
/// statically that the layout is the canonical contiguous strided layout.
/// Otherwise pass `t`'s layout into `simplifyAffineMap` and return a copy of
/// `t` with simplified layout.
/// If `t` has multiple layout maps or a multi-result layout, just return `t`.
MemRefType mlir::canonicalizeStridedLayout(MemRefType t) {
AffineMap m = t.getLayout().getAffineMap();
// Already in canonical form.
if (m.isIdentity())
return t;
// Can't reduce to canonical identity form, return in canonical form.
if (m.getNumResults() > 1)
return t;
// Corner-case for 0-D affine maps.
if (m.getNumDims() == 0 && m.getNumSymbols() == 0) {
if (auto cst = dyn_cast<AffineConstantExpr>(m.getResult(0)))
if (cst.getValue() == 0)
return MemRefType::Builder(t).setLayout({});
return t;
}
// 0-D corner case for empty shape that still have an affine map. Example:
// `memref<f32, affine_map<()[s0] -> (s0)>>`. This is a 1 element memref whose
// offset needs to remain, just return t.
if (t.getShape().empty())
return t;
// If the canonical strided layout for the sizes of `t` is equal to the
// simplified layout of `t` we can just return an empty layout. Otherwise,
// just simplify the existing layout.
AffineExpr expr =
makeCanonicalStridedLayoutExpr(t.getShape(), t.getContext());
auto simplifiedLayoutExpr =
simplifyAffineExpr(m.getResult(0), m.getNumDims(), m.getNumSymbols());
if (expr != simplifiedLayoutExpr)
return MemRefType::Builder(t).setLayout(AffineMapAttr::get(AffineMap::get(
m.getNumDims(), m.getNumSymbols(), simplifiedLayoutExpr)));
return MemRefType::Builder(t).setLayout({});
}
AffineExpr mlir::makeCanonicalStridedLayoutExpr(ArrayRef<int64_t> sizes,
ArrayRef<AffineExpr> exprs,
MLIRContext *context) {
// Size 0 corner case is useful for canonicalizations.
if (sizes.empty())
return getAffineConstantExpr(0, context);
assert(!exprs.empty() && "expected exprs");
auto maps = AffineMap::inferFromExprList(exprs);
assert(!maps.empty() && "Expected one non-empty map");
unsigned numDims = maps[0].getNumDims(), nSymbols = maps[0].getNumSymbols();
AffineExpr expr;
bool dynamicPoisonBit = false;
int64_t runningSize = 1;
for (auto en : llvm::zip(llvm::reverse(exprs), llvm::reverse(sizes))) {
int64_t size = std::get<1>(en);
AffineExpr dimExpr = std::get<0>(en);
AffineExpr stride = dynamicPoisonBit
? getAffineSymbolExpr(nSymbols++, context)
: getAffineConstantExpr(runningSize, context);
expr = expr ? expr + dimExpr * stride : dimExpr * stride;
if (size > 0) {
runningSize *= size;
assert(runningSize > 0 && "integer overflow in size computation");
} else {
dynamicPoisonBit = true;
}
}
return simplifyAffineExpr(expr, numDims, nSymbols);
}
AffineExpr mlir::makeCanonicalStridedLayoutExpr(ArrayRef<int64_t> sizes,
MLIRContext *context) {
SmallVector<AffineExpr, 4> exprs;
exprs.reserve(sizes.size());
for (auto dim : llvm::seq<unsigned>(0, sizes.size()))
exprs.push_back(getAffineDimExpr(dim, context));
return makeCanonicalStridedLayoutExpr(sizes, exprs, context);
}
bool mlir::isStrided(MemRefType t) {
int64_t offset;
SmallVector<int64_t, 4> strides;
auto res = getStridesAndOffset(t, strides, offset);
return succeeded(res);
}
bool mlir::isLastMemrefDimUnitStride(MemRefType type) {
int64_t offset;
SmallVector<int64_t> strides;
auto successStrides = getStridesAndOffset(type, strides, offset);
return succeeded(successStrides) && (strides.empty() || strides.back() == 1);
}
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