MLIR  19.0.0git
Namespaces | Classes | Typedefs | Enumerations | Functions
mlir::vector Namespace Reference

Namespaces

 detail
 

Classes

struct  ScalableValueBoundsConstraintSet
 A version of ValueBoundsConstraintSet that can solve for scalable bounds. More...
 
struct  LowerVectorsOptions
 Helper structure used to hold the different options of LowerVectorsOp. More...
 
struct  WarpExecuteOnLane0LoweringOptions
 
struct  UnrollVectorOptions
 Options that control the vector unrolling. More...
 
struct  VectorTransformsOptions
 Structure to control the behavior of vector transform patterns. More...
 
struct  MaskableOpRewritePattern
 A pattern for ops that implement MaskableOpInterface and that might be masked (i.e. More...
 

Typedefs

using ConstantOrScalableBound = ScalableValueBoundsConstraintSet::ConstantOrScalableBound
 
using DistributionMapFn = std::function< AffineMap(Value)>
 

Enumerations

enum class  BroadcastableToResult { Success = 0 , SourceRankHigher = 1 , DimensionMismatch = 2 , SourceTypeNotAVector = 3 }
 Return whether srcType can be broadcast to dstVectorType under the semantics of the vector.broadcast op. More...
 

Functions

void registerValueBoundsOpInterfaceExternalModels (DialectRegistry &registry)
 
void buildTerminatedBody (OpBuilder &builder, Location loc)
 Default callback to build a region with a 'vector.yield' terminator with no arguments. More...
 
BroadcastableToResult isBroadcastableTo (Type srcType, VectorType dstVectorType, std::pair< int, int > *mismatchingDims=nullptr)
 
void populateVectorToVectorCanonicalizationPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of vector-to-vector canonicalization patterns. More...
 
void populateFoldArithExtensionPatterns (RewritePatternSet &patterns)
 Collect a set of patterns that fold arithmetic extension on floating point into vector contract for the backends with native support. More...
 
void populateElementwiseToVectorOpsPatterns (RewritePatternSet &patterns)
 Collect a set of patterns that fold elementwise op on vectors to the vector dialect. More...
 
IntegerType getVectorSubscriptType (Builder &builder)
 Returns the integer type required for subscripts in the vector dialect. More...
 
ArrayAttr getVectorSubscriptAttr (Builder &b, ArrayRef< int64_t > values)
 Returns an integer array attribute containing the given values using the integer type required for subscripts in the vector dialect. More...
 
Value getVectorReductionOp (arith::AtomicRMWKind op, OpBuilder &builder, Location loc, Value vector)
 Returns the value obtained by reducing the vector into a scalar using the operation kind associated with a binary AtomicRMWKind op. More...
 
AffineMap getTransferMinorIdentityMap (ShapedType shapedType, VectorType vectorType)
 Build the default minor identity map suitable for a vector transfer. More...
 
bool checkSameValueRAW (TransferWriteOp defWrite, TransferReadOp read)
 Return true if the transfer_write fully writes the data accessed by the transfer_read. More...
 
bool checkSameValueWAW (TransferWriteOp write, TransferWriteOp priorWrite)
 Return true if the write op fully over-write the priorWrite transfer_write op. More...
 
bool isDisjointTransferIndices (VectorTransferOpInterface transferA, VectorTransferOpInterface transferB, bool testDynamicValueUsingBounds=false)
 Return true if we can prove that the transfer operations access disjoint memory, without requring the accessed tensor/memref to be the same. More...
 
bool isDisjointTransferSet (VectorTransferOpInterface transferA, VectorTransferOpInterface transferB, bool testDynamicValueUsingBounds=false)
 Return true if we can prove that the transfer operations access disjoint memory, requiring the operations to access the same tensor/memref. More...
 
Value makeArithReduction (OpBuilder &b, Location loc, CombiningKind kind, Value v1, Value acc, arith::FastMathFlagsAttr fastmath=nullptr, Value mask=nullptr)
 Returns the result value of reducing two scalar/vector values with the corresponding arith operation. More...
 
bool isParallelIterator (Attribute attr)
 Returns true if attr has "parallel" iterator type semantics. More...
 
bool isReductionIterator (Attribute attr)
 Returns true if attr has "reduction" iterator type semantics. More...
 
SmallVector< int64_t > getAsIntegers (ArrayRef< Value > values)
 Returns the integer numbers in values. More...
 
SmallVector< int64_t > getAsIntegers (ArrayRef< OpFoldResult > foldResults)
 Returns the integer numbers in foldResults. More...
 
SmallVector< ValuegetAsValues (OpBuilder &builder, Location loc, ArrayRef< OpFoldResult > foldResults)
 Convert foldResults into Values. More...
 
SmallVector< arith::ConstantIndexOpgetAsConstantIndexOps (ArrayRef< Value > values)
 Returns the constant index ops in values. More...
 
VectorType inferTransferOpMaskType (VectorType vecType, AffineMap permMap)
 Infers the mask type for a transfer op given its vector type and permutation map. More...
 
void createMaskOpRegion (OpBuilder &builder, Operation *maskableOp)
 Create the vector.yield-ended region of a vector.mask op with maskableOp as masked operation. More...
 
OperationmaskOperation (OpBuilder &builder, Operation *maskableOp, Value mask, Value passthru=Value())
 Creates a vector.mask operation around a maskable operation. More...
 
Value selectPassthru (OpBuilder &builder, Value mask, Value newValue, Value passthru)
 Creates a vector select operation that picks values from newValue or passthru for each result vector lane based on mask. More...
 
void registerTransformDialectExtension (DialectRegistry &registry)
 
void registerBufferizableOpInterfaceExternalModels (DialectRegistry &registry)
 
void populateVectorContractLoweringPatterns (RewritePatternSet &patterns, VectorTransformsOptions options, PatternBenefit benefit=1, bool disableOuterProductLowering=false)
 Populate the pattern set with the following patterns: More...
 
void populateVectorOuterProductLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorMultiReductionLoweringPatterns (RewritePatternSet &patterns, VectorMultiReductionLowering options, PatternBenefit benefit=1)
 Collect a set of patterns to convert vector.multi_reduction op into a sequence of vector.reduction ops. More...
 
void populateVectorBroadcastLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorMaskOpLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateScalarVectorTransferLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit, bool allowMultipleUses)
 Collects patterns that lower scalar vector transfer ops to memref loads and stores when beneficial. More...
 
void populateVectorShapeCastLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorTransposeLoweringPatterns (RewritePatternSet &patterns, VectorTransformsOptions options, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorTransferLoweringPatterns (RewritePatternSet &patterns, std::optional< unsigned > maxTransferRank=std::nullopt, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorTransferPermutationMapLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of transfer read/write lowering patterns that simplify the permutation map (e.g., converting it to a minor identity map) by inserting broadcasts and transposes. More...
 
void populateVectorScanLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorGatherLoweringPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorMaskLoweringPatternsForSideEffectingOps (RewritePatternSet &patterns)
 Populates instances of MaskOpRewritePattern to lower masked operations with vector.mask. More...
 
void populateVectorMaskedLoadStoreEmulationPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorInterleaveLoweringPatterns (RewritePatternSet &patterns, int64_t targetRank=1, PatternBenefit benefit=1)
 Populate the pattern set with the following patterns: More...
 
void populateVectorInterleaveToShufflePatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 
void populateVectorBitCastLoweringPatterns (RewritePatternSet &patterns, int64_t targetRank=1, PatternBenefit benefit=1)
 Populates the pattern set with the following patterns: More...
 
std::unique_ptr< PasscreateLowerVectorMaskPass ()
 Creates an instance of the vector.mask lowering pass. More...
 
std::unique_ptr< PasscreateLowerVectorMultiReductionPass (VectorMultiReductionLowering option=VectorMultiReductionLowering::InnerParallel)
 Creates an instance of the vector.multi_reduction lowering pass. More...
 
void registerSubsetOpInterfaceExternalModels (DialectRegistry &registry)
 
void populateWarpExecuteOnLane0OpToScfForPattern (RewritePatternSet &patterns, const WarpExecuteOnLane0LoweringOptions &options, PatternBenefit benefit=1)
 
void populateVectorContractCanonicalizeMatmulToMMT (RewritePatternSet &patterns, std::function< LogicalResult(vector::ContractionOp)> constraint=[](vector::ContractionOp) { return success();}, PatternBenefit=1)
 Canonicalization of a vector.contraction a, b, c with row-major matmul semantics to a contraction with MMT semantics (matrix matrix multiplication with the RHS transposed). More...
 
void populateVectorReductionToContractPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect patterns to convert reduction op to vector.contract and fold transpose/broadcast ops into the contract. More...
 
void populateVectorTransferFullPartialPatterns (RewritePatternSet &patterns, const VectorTransformsOptions &options)
 Populate patterns with the following patterns. More...
 
void populateVectorTransferCollapseInnerMostContiguousDimsPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of patterns to reduce the rank of the operands of vector transfer ops to operate on the largest contigious vector. More...
 
void populateSinkVectorBroadcastPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Patterns that remove redundant vector broadcasts. More...
 
void populateChainedVectorReductionFoldingPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Patterns that fold chained vector reductions. More...
 
void populateBreakDownVectorReductionPatterns (RewritePatternSet &patterns, unsigned maxNumElementsToExtract=2, PatternBenefit benefit=1)
 Patterns to break down vector reductions into a series of arith reductions over vector elements. More...
 
void populateVectorInsertExtractStridedSliceDecompositionPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate patterns with the following patterns. More...
 
void populateVectorExtractStridedSliceToExtractInsertChainPatterns (RewritePatternSet &patterns, std::function< bool(ExtractStridedSliceOp)> controlFn=nullptr, PatternBenefit benefit=1)
 Populate patterns with a pattern to breaks down 1-D extract_strided_slice ops into a chain of Extract ops to extract each element from the source, and then a chain of Insert ops to insert to the target vector. More...
 
void populateBreakDownVectorBitCastOpPatterns (RewritePatternSet &patterns, std::function< bool(BitCastOp)> controlFn=nullptr, PatternBenefit benefit=1)
 Populate patterns with a pattern to break down 1-D vector.bitcast ops based on the destination vector shape. More...
 
void populateVectorInsertExtractStridedSliceTransforms (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Populate patterns with the following patterns. More...
 
void populateVectorUnrollPatterns (RewritePatternSet &patterns, const UnrollVectorOptions &options, PatternBenefit benefit=1)
 Collect a set of pattern to unroll vector operations to a smaller shapes. More...
 
void populateShapeCastFoldingPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of vector.shape_cast folding patterns. More...
 
void populateCastAwayVectorLeadingOneDimPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of leading one dimension removal patterns. More...
 
void populateVectorTransferDropUnitDimsPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of one dimension removal patterns. More...
 
void populateDropUnitDimWithShapeCastPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of patterns that use vector.shape_cast to help fold unit dims. More...
 
void populateFlattenVectorTransferPatterns (RewritePatternSet &patterns, unsigned targetVectorBitwidth=std::numeric_limits< unsigned >::max(), PatternBenefit benefit=1)
 Collect a set of patterns to flatten n-D vector transfers on contiguous memref. More...
 
void populateBubbleVectorBitCastOpPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Collect a set of patterns that bubble up/down bitcast ops. More...
 
void populateVectorMaskMaterializationPatterns (RewritePatternSet &patterns, bool force32BitVectorIndices, PatternBenefit benefit=1)
 These patterns materialize masks for various vector ops such as transfers. More...
 
void populateVectorNarrowTypeEmulationPatterns (arith::NarrowTypeEmulationConverter &typeConverter, RewritePatternSet &patterns)
 Appends patterns for emulating vector operations over narrow types with ops over wider types. More...
 
FailureOr< ValuerewriteBitCastOfTruncI (RewriterBase &rewriter, vector::BitCastOp bitCastOp, arith::TruncIOp truncOp, vector::BroadcastOp maybeBroadcastOp)
 Rewrite a vector bitcast(trunci) to use a more efficient sequence of vector operations comprising shuffle and bitwise ops. More...
 
FailureOr< ValuerewriteExtOfBitCast (RewriterBase &rewriter, Operation *extOp, vector::BitCastOp bitCastOp, vector::BroadcastOp maybeBroadcastOp)
 Rewrite a vector ext(bitcast) to use a more efficient sequence of vector operations comprising shuffle and bitwise ops. More...
 
void populateVectorNarrowTypeRewritePatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Appends patterns for rewriting vector operations over narrow types with ops over wider types. More...
 
void populateVectorTransposeNarrowTypeRewritePatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
 Appends patterns for emulating a sub-byte vector transpose. More...
 
void populateVectorLinearizeTypeConversionsAndLegality (TypeConverter &typeConverter, RewritePatternSet &patterns, ConversionTarget &target, unsigned targetBitWidth)
 Populates patterns for ND vectors (N >= 2) linearization and sets up the provided ConversionTarget with the appropriate legality configuration for the ops to get converted properly. More...
 
void populateVectorLinearizeShuffleLikeOpsPatterns (TypeConverter &typeConverter, RewritePatternSet &patterns, ConversionTarget &target, unsigned targetBitWidth)
 Populates patterns for linearizing ND (N >= 2) vector operations to 1D vector shuffle operations. More...
 
LogicalResult splitFullAndPartialTransfer (RewriterBase &b, VectorTransferOpInterface xferOp, VectorTransformsOptions options=VectorTransformsOptions(), scf::IfOp *ifOp=nullptr)
 Split a vector.transfer operation into an in-bounds (i.e., no out-of-bounds masking) fastpath and a slowpath. More...
 
void transferOpflowOpt (RewriterBase &rewriter, Operation *rootOp)
 Implements transfer op write to read forwarding and dead transfer write optimizations. More...
 
FailureOr< ValuecastAwayContractionLeadingOneDim (vector::ContractionOp contractOp, MaskingOpInterface maskingOp, RewriterBase &rewriter)
 Cast away the leading unit dim, if exists, for the given contract op. More...
 
Value createOrFoldDimOp (OpBuilder &b, Location loc, Value source, int64_t dim)
 Helper function that creates a memref::DimOp or tensor::DimOp depending on the type of source. More...
 
FailureOr< std::pair< int, int > > isTranspose2DSlice (vector::TransposeOp op)
 Returns two dims that are greater than one if the transposition is applied on a 2D slice. More...
 
bool isContiguousSlice (MemRefType memrefType, VectorType vectorType)
 Return true if vectorType is a contiguous slice of memrefType. More...
 
std::optional< StaticTileOffsetRangecreateUnrollIterator (VectorType vType, int64_t targetRank=1)
 Returns an iterator for all positions in the leading dimensions of vType up to the targetRank. More...
 
SmallVector< OpFoldResultgetMixedSizesXfer (bool hasTensorSemantics, Operation *xfer, RewriterBase &rewriter)
 A wrapper for getMixedSizes for vector.transfer_read and vector.transfer_write Ops (for source and destination, respectively). More...
 
bool isLinearizableVector (VectorType type)
 Returns true if the input Vector type can be linearized. More...
 
Value createReadOrMaskedRead (OpBuilder &builder, Location loc, Value source, ArrayRef< int64_t > readShape, Value padValue, bool useInBoundsInsteadOfMasking)
 Create a TransferReadOp from source with static shape readShape. More...
 
LogicalResult isValidMaskedInputVector (ArrayRef< int64_t > shape, ArrayRef< int64_t > inputVectorSizes)
 Returns success if inputVectorSizes is a valid masking configuraion for given shape, i.e., it meets: More...
 

Typedef Documentation

◆ ConstantOrScalableBound

Definition at line 103 of file ScalableValueBoundsConstraintSet.h.

◆ DistributionMapFn

using mlir::vector::DistributionMapFn = typedef std::function<AffineMap(Value)>

Definition at line 43 of file VectorDistribution.h.

Enumeration Type Documentation

◆ BroadcastableToResult

Return whether srcType can be broadcast to dstVectorType under the semantics of the vector.broadcast op.

Enumerator
Success 
SourceRankHigher 
DimensionMismatch 
SourceTypeNotAVector 

Definition at line 65 of file VectorOps.h.

Function Documentation

◆ buildTerminatedBody()

void mlir::vector::buildTerminatedBody ( OpBuilder builder,
Location  loc 
)

Default callback to build a region with a 'vector.yield' terminator with no arguments.

Definition at line 126 of file VectorOps.cpp.

References mlir::OpBuilder::create().

◆ castAwayContractionLeadingOneDim()

FailureOr< Value > mlir::vector::castAwayContractionLeadingOneDim ( vector::ContractionOp  contractOp,
MaskingOpInterface  maskingOp,
RewriterBase rewriter 
)

◆ checkSameValueRAW()

bool mlir::vector::checkSameValueRAW ( TransferWriteOp  defWrite,
TransferReadOp  read 
)

Return true if the transfer_write fully writes the data accessed by the transfer_read.

◆ checkSameValueWAW()

bool mlir::vector::checkSameValueWAW ( TransferWriteOp  write,
TransferWriteOp  priorWrite 
)

Return true if the write op fully over-write the priorWrite transfer_write op.

◆ createLowerVectorMaskPass()

std::unique_ptr< Pass > mlir::vector::createLowerVectorMaskPass ( )

Creates an instance of the vector.mask lowering pass.

Definition at line 309 of file LowerVectorMask.cpp.

◆ createLowerVectorMultiReductionPass()

std::unique_ptr<Pass> mlir::vector::createLowerVectorMultiReductionPass ( VectorMultiReductionLowering  option = VectorMultiReductionLowering::InnerParallel)

Creates an instance of the vector.multi_reduction lowering pass.

◆ createMaskOpRegion()

void mlir::vector::createMaskOpRegion ( OpBuilder builder,
Operation maskableOp 
)

Create the vector.yield-ended region of a vector.mask op with maskableOp as masked operation.

◆ createOrFoldDimOp()

Value mlir::vector::createOrFoldDimOp ( OpBuilder b,
Location  loc,
Value  source,
int64_t  dim 
)

Helper function that creates a memref::DimOp or tensor::DimOp depending on the type of source.

Definition at line 41 of file VectorUtils.cpp.

References mlir::OpBuilder::createOrFold(), and mlir::Value::getType().

◆ createReadOrMaskedRead()

Value mlir::vector::createReadOrMaskedRead ( OpBuilder builder,
Location  loc,
Value  source,
ArrayRef< int64_t >  readShape,
Value  padValue,
bool  useInBoundsInsteadOfMasking 
)

Create a TransferReadOp from source with static shape readShape.

If the vector type for the read is not the same as the type of source, then a mask is created on the read, if use of mask is specified or the bounds on a dimension are different.

useInBoundsInsteadOfMasking if false, the inBoundsVal values are set properly, based on the rank dimensions of the source and destination tensors. And that is what determines if masking is done.

Note that the internal vector::TransferReadOp always read at indices zero for each dimension of the passed in tensor.

Definition at line 330 of file VectorUtils.cpp.

References mlir::OpBuilder::create(), mlir::get(), mlir::Builder::getI1Type(), mlir::tensor::getMixedSizes(), mlir::Operation::getResult(), mlir::Value::getType(), and maskOperation().

Referenced by vectorizeAsTensorPackOp(), vectorizeAsTensorPadOp(), and vectorizeAsTensorUnpackOp().

◆ createUnrollIterator()

std::optional< StaticTileOffsetRange > mlir::vector::createUnrollIterator ( VectorType  vType,
int64_t  targetRank = 1 
)

Returns an iterator for all positions in the leading dimensions of vType up to the targetRank.

If any leading dimension before the targetRank is scalable (so cannot be unrolled), it will return an iterator for positions up to the first scalable dimension.

If no leading dimensions can be unrolled an empty optional will be returned.

Examples:

For vType = vector<2x3x4> and targetRank = 1

The resulting iterator will yield: [0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2]

For vType = vector<3x[4]x5> and targetRank = 0

The scalable dimension blocks unrolling so the iterator yields only: [0], [1], [2]

Definition at line 287 of file VectorUtils.cpp.

◆ getAsConstantIndexOps()

SmallVector<arith::ConstantIndexOp> mlir::vector::getAsConstantIndexOps ( ArrayRef< Value values)

Returns the constant index ops in values.

values are expected to be constant operations.

◆ getAsIntegers() [1/2]

SmallVector< int64_t > mlir::vector::getAsIntegers ( ArrayRef< OpFoldResult foldResults)

Returns the integer numbers in foldResults.

foldResults are expected to be constant operations.

Definition at line 327 of file VectorOps.cpp.

◆ getAsIntegers() [2/2]

SmallVector< int64_t > mlir::vector::getAsIntegers ( ArrayRef< Value values)

Returns the integer numbers in values.

values are expected to be constant operations.

Definition at line 315 of file VectorOps.cpp.

References mlir::Value::getDefiningOp().

◆ getAsValues()

SmallVector< Value > mlir::vector::getAsValues ( OpBuilder builder,
Location  loc,
ArrayRef< OpFoldResult foldResults 
)

Convert foldResults into Values.

Integer attributes are converted to constant op.

Definition at line 339 of file VectorOps.cpp.

References mlir::OpBuilder::create().

◆ getMixedSizesXfer()

SmallVector< OpFoldResult > mlir::vector::getMixedSizesXfer ( bool  hasTensorSemantics,
Operation xfer,
RewriterBase rewriter 
)

A wrapper for getMixedSizes for vector.transfer_read and vector.transfer_write Ops (for source and destination, respectively).

Tensor and MemRef types implement their own, very similar version of getMixedSizes. This method will call the appropriate version (depending on hasTensorSemantics). It will also automatically extract the operand for which to call it on (source for "read" and destination for "write" ops).

Definition at line 308 of file VectorUtils.cpp.

References mlir::Operation::getLoc(), mlir::memref::getMixedSizes(), mlir::tensor::getMixedSizes(), and mlir::bufferization::hasTensorSemantics().

◆ getTransferMinorIdentityMap()

AffineMap mlir::vector::getTransferMinorIdentityMap ( ShapedType  shapedType,
VectorType  vectorType 
)

Build the default minor identity map suitable for a vector transfer.

This also handles the case memref<... x vector<...>> -> vector<...> in which the rank of the identity map must take the vector element type into account.

Definition at line 154 of file VectorOps.cpp.

References mlir::AffineMap::get(), mlir::getAffineConstantExpr(), and mlir::AffineMap::getMinorIdentityMap().

◆ getVectorReductionOp()

Value mlir::vector::getVectorReductionOp ( arith::AtomicRMWKind  op,
OpBuilder builder,
Location  loc,
Value  vector 
)

Returns the value obtained by reducing the vector into a scalar using the operation kind associated with a binary AtomicRMWKind op.

Definition at line 609 of file VectorOps.cpp.

◆ getVectorSubscriptAttr()

ArrayAttr mlir::vector::getVectorSubscriptAttr ( Builder b,
ArrayRef< int64_t >  values 
)

Returns an integer array attribute containing the given values using the integer type required for subscripts in the vector dialect.

Definition at line 432 of file VectorOps.cpp.

References mlir::Builder::getI64ArrayAttr().

◆ getVectorSubscriptType()

IntegerType mlir::vector::getVectorSubscriptType ( Builder builder)

Returns the integer type required for subscripts in the vector dialect.

Definition at line 428 of file VectorOps.cpp.

References mlir::Builder::getIntegerType().

◆ inferTransferOpMaskType()

VectorType mlir::vector::inferTransferOpMaskType ( VectorType  vecType,
AffineMap  permMap 
)

Infers the mask type for a transfer op given its vector type and permutation map.

The mask in a transfer op operation applies to the tensor/buffer part of it and its type should match the vector shape before any permutation or broadcasting. For example,

vecType = vector<1x2x3xf32>, permMap = affine_map<(d0, d1, d2) -> (d1, d0)>

Has inferred mask type:

maskType = vector<2x1xi1>

Definition at line 3987 of file VectorOps.cpp.

References mlir::applyPermutationMap(), mlir::AffineMap::compose(), mlir::compressUnusedDims(), mlir::get(), mlir::AffineMap::getContext(), and mlir::inversePermutation().

◆ isBroadcastableTo()

BroadcastableToResult mlir::vector::isBroadcastableTo ( Type  srcType,
VectorType  dstVectorType,
std::pair< int, int > *  mismatchingDims = nullptr 
)

Definition at line 2376 of file VectorOps.cpp.

References mlir::getElementTypeOrSelf(), and mlir::Type::isIntOrIndexOrFloat().

Referenced by broadcastIfNeeded().

◆ isContiguousSlice()

bool mlir::vector::isContiguousSlice ( MemRefType  memrefType,
VectorType  vectorType 
)

Return true if vectorType is a contiguous slice of memrefType.

Only the N = vectorType.getRank() trailing dims of memrefType are checked (the other dims are not relevant). Note that for vectorType to be a contiguous slice of memrefType, the trailing dims of the latter have to be contiguous - this is checked by looking at the corresponding strides.

There might be some restriction on the leading dim of VectorType:

Case 1. If all the trailing dims of vectorType match the trailing dims of memrefType then the leading dim of vectorType can be arbitrary.

Ex. 1.1 contiguous slice, perfect match vector<4x3x2xi32> from memref<5x4x3x2xi32> Ex. 1.2 contiguous slice, the leading dim does not match (2 != 4) vector<2x3x2xi32> from memref<5x4x3x2xi32>

Case 2. If an "internal" dim of vectorType does not match the corresponding trailing dim in memrefType then the remaining leading dims of vectorType have to be 1 (the first non-matching dim can be arbitrary).

Ex. 2.1 non-contiguous slice, 2 != 3 and the leading dim != <1> vector<2x2x2xi32> from memref<5x4x3x2xi32> Ex. 2.2 contiguous slice, 2 != 3 and the leading dim == <1> vector<1x2x2xi32> from memref<5x4x3x2xi32> Ex. 2.3. contiguous slice, 2 != 3 and the leading dims == <1x1> vector<1x1x2x2xi32> from memref<5x4x3x2xi32> Ex. 2.4. non-contiguous slice, 2 != 3 and the leading dims != <1x1> vector<2x1x2x2xi32> from memref<5x4x3x2xi32>)

Definition at line 257 of file VectorUtils.cpp.

References mlir::trailingNDimsContiguous(), and vectorShape().

◆ isDisjointTransferIndices()

bool mlir::vector::isDisjointTransferIndices ( VectorTransferOpInterface  transferA,
VectorTransferOpInterface  transferB,
bool  testDynamicValueUsingBounds = false 
)

Return true if we can prove that the transfer operations access disjoint memory, without requring the accessed tensor/memref to be the same.

If testDynamicValueUsingBounds is true, tries to test dynamic values via ValueBoundsOpInterface.

Definition at line 220 of file VectorOps.cpp.

References mlir::presburger::abs(), mlir::ValueBoundsConstraintSet::areEqual(), mlir::ValueBoundsConstraintSet::computeConstantDelta(), mlir::affine::fullyComposeAndComputeConstantDelta(), mlir::getConstantIntValue(), and mlir::succeeded().

Referenced by isDisjointTransferSet().

◆ isDisjointTransferSet()

bool mlir::vector::isDisjointTransferSet ( VectorTransferOpInterface  transferA,
VectorTransferOpInterface  transferB,
bool  testDynamicValueUsingBounds = false 
)

Return true if we can prove that the transfer operations access disjoint memory, requiring the operations to access the same tensor/memref.

If testDynamicValueUsingBounds is true, tries to test dynamic values via ValueBoundsOpInterface.

Definition at line 284 of file VectorOps.cpp.

References isDisjointTransferIndices().

Referenced by mlir::linalg::hoistRedundantVectorTransfers().

◆ isLinearizableVector()

bool mlir::vector::isLinearizableVector ( VectorType  type)

Returns true if the input Vector type can be linearized.

Linearization is meant in the sense of flattening vectors, e.g.:

  • vector<NxMxKxi32> -> vector<N*M*Kxi32> In this sense, Vectors that are either:
  • already linearized, or
  • contain more than 1 scalable dimensions, are not linearizable.

Definition at line 325 of file VectorUtils.cpp.

Referenced by populateVectorLinearizeTypeConversionsAndLegality().

◆ isParallelIterator()

bool mlir::vector::isParallelIterator ( Attribute  attr)
inline

Returns true if attr has "parallel" iterator type semantics.

Definition at line 139 of file VectorOps.h.

Referenced by castAwayContractionLeadingOneDim(), contractSupportsMMAMatrixType(), and gpuMmaUnrollOrder().

◆ isReductionIterator()

bool mlir::vector::isReductionIterator ( Attribute  attr)
inline

Returns true if attr has "reduction" iterator type semantics.

Definition at line 144 of file VectorOps.h.

Referenced by contractSupportsMMAMatrixType(), getReductionIndex(), and gpuMmaUnrollOrder().

◆ isTranspose2DSlice()

FailureOr< std::pair< int, int > > mlir::vector::isTranspose2DSlice ( vector::TransposeOp  op)

Returns two dims that are greater than one if the transposition is applied on a 2D slice.

Otherwise, returns a failure.

Definition at line 84 of file VectorUtils.cpp.

◆ isValidMaskedInputVector()

LogicalResult mlir::vector::isValidMaskedInputVector ( ArrayRef< int64_t >  shape,
ArrayRef< int64_t >  inputVectorSizes 
)

Returns success if inputVectorSizes is a valid masking configuraion for given shape, i.e., it meets:

  1. The numbers of elements in both array are equal.
  2. inputVectorSizes does not have dynamic dimensions.
  3. All the values in inputVectorSizes are greater than or equal to static sizes in shape.

Definition at line 372 of file VectorUtils.cpp.

References mlir::failure(), LDBG, and mlir::success().

Referenced by vectorizeLinalgOpPrecondition(), vectorizePackOpPrecondition(), vectorizePadOpPrecondition(), and vectorizeUnPackOpPrecondition().

◆ makeArithReduction()

Value mlir::vector::makeArithReduction ( OpBuilder b,
Location  loc,
CombiningKind  kind,
Value  v1,
Value  acc,
arith::FastMathFlagsAttr  fastmath = nullptr,
Value  mask = nullptr 
)

Returns the result value of reducing two scalar/vector values with the corresponding arith operation.

◆ maskOperation()

Operation* mlir::vector::maskOperation ( OpBuilder builder,
Operation maskableOp,
Value  mask,
Value  passthru = Value() 
)

Creates a vector.mask operation around a maskable operation.

Returns the vector.mask operation if the mask provided is valid. Otherwise, returns the maskable operation itself.

Referenced by castAwayContractionLeadingOneDim(), createReadOrMaskedRead(), createWriteOrMaskedWrite(), and VectorizationState::maskOperation().

◆ populateBreakDownVectorBitCastOpPatterns()

void mlir::vector::populateBreakDownVectorBitCastOpPatterns ( RewritePatternSet patterns,
std::function< bool(BitCastOp)>  controlFn = nullptr,
PatternBenefit  benefit = 1 
)

Populate patterns with a pattern to break down 1-D vector.bitcast ops based on the destination vector shape.

Bitcasts from a lower bitwidth element type to a higher bitwidth one are extracted from the lower bitwidth based on the native destination vector shape and inserted based on the ratio of the bitwidths.

This acts as a last resort way to break down vector.bitcast ops to smaller vector sizes. Because this pattern composes until it is bitcasting to a single element of the higher bitwidth, the is an optional control function. If controlFn is not nullptr, the pattern will only apply to ops where controlFn returns true, otherwise applies to all bitcast ops.

◆ populateBreakDownVectorReductionPatterns()

void mlir::vector::populateBreakDownVectorReductionPatterns ( RewritePatternSet patterns,
unsigned  maxNumElementsToExtract = 2,
PatternBenefit  benefit = 1 
)

Patterns to break down vector reductions into a series of arith reductions over vector elements.

This is intended to be simplify code with reductions over small vector types and avoid more specialized reduction lowering when possible.

Example:

%a = vector.reduction <add> %x : vector<2xf32> into f32

is transformed into:

%y = vector.extract %x[0] : f32 from vector<2xf32>
%z = vector.extract %x[1] : f32 from vector<2xf32>
%a = arith.addf %y, %z : f32

Definition at line 1974 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateBubbleVectorBitCastOpPatterns()

void mlir::vector::populateBubbleVectorBitCastOpPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of patterns that bubble up/down bitcast ops.

These patterns move vector.bitcast ops to be before insert ops or after extract ops where suitable. With them, bitcast will happen on smaller vectors and there are more chances to share extract/insert ops.

Definition at line 1922 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateCastAwayVectorLeadingOneDimPatterns()

void mlir::vector::populateCastAwayVectorLeadingOneDimPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of leading one dimension removal patterns.

These patterns insert vector.shape_cast to remove leading one dimensions to expose more canonical forms of read/write/insert/extract operations. With them, there are more chances that we can cancel out extract-insert pairs or forward write-read pairs.

Definition at line 574 of file VectorDropLeadUnitDim.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and populateShapeCastFoldingPatterns().

◆ populateChainedVectorReductionFoldingPatterns()

void mlir::vector::populateChainedVectorReductionFoldingPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Patterns that fold chained vector reductions.

These patterns assume that elementwise operations (e.g., arith.addf with vector operands) are cheaper than vector reduction. Note that these patterns change the order of reduction which may not always produce bit-identical results on some floating point inputs.

Example:

%a = vector.reduction <add> %x, %acc
%b = vector.reduction <add> %y, %a

is transformed into:

%a = arith.addf %x, %y
%b = vector.reduction <add> %a, %acc

Definition at line 1967 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), mlir::PatternBenefit::getBenefit(), and mlir::RewritePatternSet::getContext().

◆ populateDropUnitDimWithShapeCastPatterns()

void mlir::vector::populateDropUnitDimWithShapeCastPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of patterns that use vector.shape_cast to help fold unit dims.

These patterns use vector.shape_cast to remove unit dims from e.g. arithmetic operations on Vectors. The newly inserted shape_casts will either cancel each other out or will be folded away when combined with other patterns.

Definition at line 1916 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

Referenced by populateFlattenVectorTransferPatterns().

◆ populateElementwiseToVectorOpsPatterns()

void mlir::vector::populateElementwiseToVectorOpsPatterns ( RewritePatternSet patterns)

Collect a set of patterns that fold elementwise op on vectors to the vector dialect.

Definition at line 1981 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateFlattenVectorTransferPatterns()

void mlir::vector::populateFlattenVectorTransferPatterns ( RewritePatternSet patterns,
unsigned  targetVectorBitwidth = std::numeric_limits<unsigned>::max(),
PatternBenefit  benefit = 1 
)

Collect a set of patterns to flatten n-D vector transfers on contiguous memref.

These patterns insert memref.collapse_shape + vector.shape_cast patterns to transform multiple small n-D transfers into a larger 1-D transfer where the memref contiguity properties allow it.

Flattening is only applied if the bitwidth of the trailing vector dimension is smaller or equal to targetVectorBitwidth.

Definition at line 964 of file VectorTransferOpTransforms.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), populateDropUnitDimWithShapeCastPatterns(), and populateShapeCastFoldingPatterns().

◆ populateFoldArithExtensionPatterns()

void mlir::vector::populateFoldArithExtensionPatterns ( RewritePatternSet patterns)

Collect a set of patterns that fold arithmetic extension on floating point into vector contract for the backends with native support.

Definition at line 1896 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateScalarVectorTransferLoweringPatterns()

void mlir::vector::populateScalarVectorTransferLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit,
bool  allowMultipleUses 
)

Collects patterns that lower scalar vector transfer ops to memref loads and stores when beneficial.

If allowMultipleUses is set to true, the patterns are applied to vector transfer reads with any number of uses. Otherwise, only vector transfer reads with a single use will be lowered.

Definition at line 947 of file VectorTransferOpTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateShapeCastFoldingPatterns()

void mlir::vector::populateShapeCastFoldingPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

◆ populateSinkVectorBroadcastPatterns()

void mlir::vector::populateSinkVectorBroadcastPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Patterns that remove redundant vector broadcasts.

Definition at line 1961 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorBitCastLoweringPatterns()

void mlir::vector::populateVectorBitCastLoweringPatterns ( RewritePatternSet patterns,
int64_t  targetRank = 1,
PatternBenefit  benefit = 1 
)

Populates the pattern set with the following patterns:

[UnrollBitCastOp] A one-shot unrolling of BitCastOp to (one or more) ExtractOp + BitCastOp (of targetRank) + InsertOp.

Definition at line 88 of file LowerVectorBitCast.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorBroadcastLoweringPatterns()

void mlir::vector::populateVectorBroadcastLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[TransferReadToVectorLoadLowering] Progressive lowering of BroadcastOp to ExtractOp + InsertOp + lower-D BroadcastOp until dim 1.

Definition at line 152 of file LowerVectorBroadcast.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorContractCanonicalizeMatmulToMMT()

void mlir::vector::populateVectorContractCanonicalizeMatmulToMMT ( RewritePatternSet patterns,
std::function< LogicalResult(vector::ContractionOp)>  constraint = [](vector::ContractionOp) { return success(); },
PatternBenefit  benefit = 1 
)

Canonicalization of a vector.contraction a, b, c with row-major matmul semantics to a contraction with MMT semantics (matrix matrix multiplication with the RHS transposed).

This specific form is meant to have the vector operands are organized such that the reduction dimension is contiguous. Example:

vector.contract {indexing_maps = [affine_map<(m, n, k) -> (m, k)>,
affine_map<(m, n, k) -> (n, k)>,
affine_map<(m, n, k) -> (m, n)>],
iterator_types = ["parallel", "parallel", "reduction"],
kind = #vector.kind<add>} %a, %b, %c : ...

The constraint predicate is used to decide which vector.contraction ops to filter out.

Definition at line 1937 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

Referenced by mlir::populatePrepareVectorToMMAPatterns().

◆ populateVectorContractLoweringPatterns()

void mlir::vector::populateVectorContractLoweringPatterns ( RewritePatternSet patterns,
VectorTransformsOptions  options,
PatternBenefit  benefit = 1,
bool  disableOuterProductLowering = false 
)

Populate the pattern set with the following patterns:

[OuterProductOpLowering] Progressively lower a vector.outerproduct to linearized vector.extract + vector.fma + vector.insert.

[ContractionOpLowering] Progressive lowering of ContractionOp. One: x = vector.contract with at least one free/batch dimension is replaced by: a = vector.contract with one less free/batch dimension b = vector.contract with one less free/batch dimension

[ContractionOpToMatmulOpLowering] Progressively lower a vector.contract with row-major matmul semantics to linearized vector.shape_cast + vector.matmul on the way to llvm.matrix.multiply.

[ContractionOpToDotLowering] Progressively lower a vector.contract with row-major matmul semantics to linearized vector.extract + vector.reduce + vector.insert.

[ContractionOpToOuterProductOpLowering] Progressively lower a vector.contract with row-major matmul semantics to linearized vector.extract + vector.outerproduct + vector.insert.

Definition at line 1378 of file LowerVectorContract.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and options.

◆ populateVectorExtractStridedSliceToExtractInsertChainPatterns()

void mlir::vector::populateVectorExtractStridedSliceToExtractInsertChainPatterns ( RewritePatternSet patterns,
std::function< bool(ExtractStridedSliceOp)>  controlFn = nullptr,
PatternBenefit  benefit = 1 
)

Populate patterns with a pattern to breaks down 1-D extract_strided_slice ops into a chain of Extract ops to extract each element from the source, and then a chain of Insert ops to insert to the target vector.

If controlFn is not nullptr, the pattern will only be invoked on ops that controlFn returns true. Otherwise runs on ops.

Definition at line 339 of file VectorInsertExtractStridedSliceRewritePatterns.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorGatherLoweringPatterns()

void mlir::vector::populateVectorGatherLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[FlattenGather] Flattens 2 or more dimensional vector.gather ops by unrolling the outermost dimension.

[Gather1DToConditionalLoads] Turns 1-d vector.gather into a scalarized sequence of vector.loads or tensor.extracts. To avoid out-of-bounds memory accesses, these loads/extracts are made conditional using scf.if ops.

Definition at line 263 of file LowerVectorGather.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorInsertExtractStridedSliceDecompositionPatterns()

void mlir::vector::populateVectorInsertExtractStridedSliceDecompositionPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate patterns with the following patterns.

[DecomposeDifferentRankInsertStridedSlice]

RewritePattern for InsertStridedSliceOp where source and destination vectors have different ranks.

When ranks are different, InsertStridedSlice needs to extract a properly ranked vector from the destination vector into which to insert. This pattern only takes care of this extraction part and forwards the rest to [VectorInsertStridedSliceOpSameRankRewritePattern].

For a k-D source and n-D destination vector (k < n), we emit:

  1. ExtractOp to extract the (unique) (n-1)-D subvector into which to insert the k-D source.
  2. k-D -> (n-1)-D InsertStridedSlice op
  3. InsertOp that is the reverse of 1.

[DecomposeNDExtractStridedSlice]

For such cases, we can rewrite it to ExtractOp/ExtractElementOp + lower rank ExtractStridedSliceOp + InsertOp/InsertElementOp for the n-D case.

Definition at line 333 of file VectorInsertExtractStridedSliceRewritePatterns.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

Referenced by populateVectorInsertExtractStridedSliceTransforms().

◆ populateVectorInsertExtractStridedSliceTransforms()

void mlir::vector::populateVectorInsertExtractStridedSliceTransforms ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate patterns with the following patterns.

Populate the given list with patterns that convert from Vector to LLVM.

Patterns in populateVectorInsertExtractStridedSliceDecompositionPatterns();

[ConvertSameRankInsertStridedSliceIntoShuffle]

RewritePattern for InsertStridedSliceOp where source and destination vectors have the same rank. For each outermost index in the slice: begin end stride [offset : offset+size*stride : stride]

  1. ExtractOp one (k-1)-D source subvector and one (n-1)-D dest subvector.
  2. InsertStridedSlice (k-1)-D into (n-1)-D
  3. the destination subvector is inserted back in the proper place
  1. InsertOp that is the reverse of 1.

[Convert1DExtractStridedSliceIntoShuffle]

For such cases, we can lower it to a ShuffleOp.

Definition at line 348 of file VectorInsertExtractStridedSliceRewritePatterns.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and populateVectorInsertExtractStridedSliceDecompositionPatterns().

Referenced by mlir::populateVectorToLLVMConversionPatterns().

◆ populateVectorInterleaveLoweringPatterns()

void mlir::vector::populateVectorInterleaveLoweringPatterns ( RewritePatternSet patterns,
int64_t  targetRank = 1,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[UnrollInterleaveOp] A one-shot unrolling of InterleaveOp to (one or more) ExtractOp + InterleaveOp (of targetRank) + InsertOp.

Definition at line 184 of file LowerVectorInterleave.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorInterleaveToShufflePatterns()

void mlir::vector::populateVectorInterleaveToShufflePatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

◆ populateVectorLinearizeShuffleLikeOpsPatterns()

void mlir::vector::populateVectorLinearizeShuffleLikeOpsPatterns ( TypeConverter typeConverter,
RewritePatternSet patterns,
ConversionTarget target,
unsigned  targetBitWidth 
)

Populates patterns for linearizing ND (N >= 2) vector operations to 1D vector shuffle operations.

◆ populateVectorLinearizeTypeConversionsAndLegality()

void mlir::vector::populateVectorLinearizeTypeConversionsAndLegality ( TypeConverter typeConverter,
RewritePatternSet patterns,
ConversionTarget target,
unsigned  targetBitWidth 
)

Populates patterns for ND vectors (N >= 2) linearization and sets up the provided ConversionTarget with the appropriate legality configuration for the ops to get converted properly.

Definition at line 467 of file VectorLinearize.cpp.

References mlir::TypeConverter::addArgumentMaterialization(), mlir::TypeConverter::addConversion(), mlir::TypeConverter::addSourceMaterialization(), mlir::TypeConverter::addTargetMaterialization(), mlir::OpBuilder::create(), mlir::get(), isLinearizableVector(), and mlir::ConversionTarget::markUnknownOpDynamicallyLegal().

◆ populateVectorMaskedLoadStoreEmulationPatterns()

void mlir::vector::populateVectorMaskedLoadStoreEmulationPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[VectorMaskedLoadOpConverter] Turns vector.maskedload to scf.if + memref.load

[VectorMaskedStoreOpConverter] Turns vector.maskedstore to scf.if + memref.store

Definition at line 157 of file VectorEmulateMaskedLoadStore.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorMaskLoweringPatternsForSideEffectingOps()

void mlir::vector::populateVectorMaskLoweringPatternsForSideEffectingOps ( RewritePatternSet patterns)

Populates instances of MaskOpRewritePattern to lower masked operations with vector.mask.

Patterns should rewrite the vector.mask operation and not its nested MaskableOpInterface.

Definition at line 303 of file LowerVectorMask.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorMaskMaterializationPatterns()

void mlir::vector::populateVectorMaskMaterializationPatterns ( RewritePatternSet patterns,
bool  force32BitVectorIndices,
PatternBenefit  benefit = 1 
)

These patterns materialize masks for various vector ops such as transfers.

Definition at line 1901 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorMaskOpLoweringPatterns()

void mlir::vector::populateVectorMaskOpLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[CreateMaskOp] Progressive lowering of CreateMaskOp to lower-D CreateMaskOp until dim 1.

[ConstantMaskOp] Progressive lowering of ConstantMaskOp to lower-D ConstantMaskOp until dim 1.

Definition at line 162 of file LowerVectorMask.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorMultiReductionLoweringPatterns()

void mlir::vector::populateVectorMultiReductionLoweringPatterns ( RewritePatternSet patterns,
VectorMultiReductionLowering  options,
PatternBenefit  benefit = 1 
)

Collect a set of patterns to convert vector.multi_reduction op into a sequence of vector.reduction ops.

The patterns comprise:

[InnerOuterDimReductionConversion] Rewrites vector.multi_reduction such that all reduction dimensions are either innermost or outermost, by adding the proper vector.transpose operations.

[ReduceMultiDimReductionRank] Once in innermost or outermost reduction form, rewrites n-D vector.multi_reduction into 2-D vector.multi_reduction, by introducing vector.shape_cast ops to collapse + multi-reduce + expand back.

[TwoDimMultiReductionToElementWise] Once in 2-D vector.multi_reduction form, with an outermost reduction dimension, unroll the outer dimension to obtain a sequence of 1-D vector ops. This also has an opportunity for tree-reduction (in the future).

[TwoDimMultiReductionToReduction] Once in 2-D vector.multi_reduction form, with an innermost reduction dimension, unroll the outer dimension to obtain a sequence of extract + vector.reduction + insert. This can further lower to horizontal reduction ops.

[OneDimMultiReductionToTwoDim] For cases that reduce to 1-D vector<k> reduction (and are thus missing either a parallel or a reduction), we lift them back up to 2-D with a simple vector.shape_cast to vector<1xk> so that the other patterns can kick in, thus fully exiting out of the vector.multi_reduction abstraction.

Definition at line 504 of file LowerVectorMultiReduction.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and options.

◆ populateVectorNarrowTypeEmulationPatterns()

void mlir::vector::populateVectorNarrowTypeEmulationPatterns ( arith::NarrowTypeEmulationConverter typeConverter,
RewritePatternSet patterns 
)

Appends patterns for emulating vector operations over narrow types with ops over wider types.

Definition at line 1263 of file VectorEmulateNarrowType.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorNarrowTypeRewritePatterns()

void mlir::vector::populateVectorNarrowTypeRewritePatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Appends patterns for rewriting vector operations over narrow types with ops over wider types.

Warning: these patterns currently only work for little endian targets.

Definition at line 1273 of file VectorEmulateNarrowType.cpp.

References mlir::RewritePatternSet::add(), mlir::PatternBenefit::getBenefit(), and mlir::RewritePatternSet::getContext().

◆ populateVectorOuterProductLoweringPatterns()

void mlir::vector::populateVectorOuterProductLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[OuterProductOpLowering] Progressively lower a vector.outerproduct to linearized vector.extract + vector.fma + vector.insert.

Definition at line 1388 of file LowerVectorContract.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorReductionToContractPatterns()

void mlir::vector::populateVectorReductionToContractPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect patterns to convert reduction op to vector.contract and fold transpose/broadcast ops into the contract.

Definition at line 1945 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorScanLoweringPatterns()

void mlir::vector::populateVectorScanLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[ScanToArithOps] Convert vector.scan op into arith ops and vector.insert_strided_slice / vector.extract_strided_slice.

Definition at line 192 of file LowerVectorScan.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorShapeCastLoweringPatterns()

void mlir::vector::populateVectorShapeCastLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[ShapeCastOp2DDownCastRewritePattern] ShapeOp 2D -> 1D downcast serves the purpose of flattening 2-D to 1-D vectors progressively.

[ShapeCastOp2DUpCastRewritePattern] ShapeOp 1D -> 2D upcast serves the purpose of unflattening 2-D from 1-D vectors progressively.

[ShapeCastOpRewritePattern] Reference lowering to fully unrolled sequences of single element ExtractOp + InsertOp. Note that applying this pattern can almost always be considered a performance bug.

Definition at line 354 of file LowerVectorShapeCast.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorToVectorCanonicalizationPatterns()

void mlir::vector::populateVectorToVectorCanonicalizationPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of vector-to-vector canonicalization patterns.

◆ populateVectorTransferCollapseInnerMostContiguousDimsPatterns()

void mlir::vector::populateVectorTransferCollapseInnerMostContiguousDimsPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of patterns to reduce the rank of the operands of vector transfer ops to operate on the largest contigious vector.

These patterns are useful when lowering to dialects with 1d vector type such as llvm and it will result fewer memory reads.

Definition at line 1953 of file VectorTransforms.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorTransferDropUnitDimsPatterns()

void mlir::vector::populateVectorTransferDropUnitDimsPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of one dimension removal patterns.

These patterns insert rank-reducing memref.subview ops to remove one dimensions. With them, there are more chances that we can avoid potentially expensive vector.shape_cast operations.

Definition at line 956 of file VectorTransferOpTransforms.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and populateShapeCastFoldingPatterns().

◆ populateVectorTransferFullPartialPatterns()

void mlir::vector::populateVectorTransferFullPartialPatterns ( RewritePatternSet patterns,
const VectorTransformsOptions options 
)

Populate patterns with the following patterns.

  • VectorTransferFullPartialRewriter

Split a vector.transfer operation into an in-bounds (i.e., no out-of-bounds masking) fast path and a slow path.

Example (a 2-D vector.transfer_read): ``` %1 = vector.transfer_read %0[...], pad : memref<A...>, vector<...> ``` is transformed into: ``` %1:3 = scf.if (inBounds) { // fast path, direct cast memref.cast A: memref<A...> to compatibleMemRefType scf.yield view : compatibleMemRefType, index, index } else { // slow path, not in-bounds vector.transfer or linalg.copy. memref.cast alloc: memref<B...> to compatibleMemRefType scf.yield %4 : compatibleMemRefType, index, index */ // } /** %0 = vector.transfer_read %1#0[%1#1, %1#2] {in_bounds = [true ... true]} `` wherealloc` is a top of the function alloca'ed buffer of one vector.

Preconditions:

  1. xferOp.permutation_map() must be a minor identity map
  2. the rank of the xferOp.memref() and the rank of the xferOp.vector() must be equal. This will be relaxed in the future but requires rank-reducing subviews.

Definition at line 671 of file VectorTransferSplitRewritePatterns.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and options.

◆ populateVectorTransferLoweringPatterns()

void mlir::vector::populateVectorTransferLoweringPatterns ( RewritePatternSet patterns,
std::optional< unsigned >  maxTransferRank = std::nullopt,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[TransferReadToVectorLoadLowering] Progressive lowering of transfer_read.This pattern supports lowering of vector.transfer_read to a combination of vector.load and vector.broadcast

[TransferWriteToVectorStoreLowering] Progressive lowering of transfer_write. This pattern supports lowering of vector.transfer_write to vector.store

[VectorLoadToMemrefLoadLowering] Replace a 0-d vector.load with a memref.load + vector.broadcast.

[VectorStoreToMemrefStoreLowering] Replace a 0-d vector.store with a vector.extractelement + memref.store.

These patterns lower transfer ops to simpler ops like vector.load, vector.store and vector.broadcast. Only transfers with a transfer rank of a most maxTransferRank are lowered. This is useful when combined with VectorToSCF, which reduces the rank of vector transfer ops.

Definition at line 668 of file LowerVectorTransfer.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

Referenced by mlir::populateVectorToLLVMConversionPatterns().

◆ populateVectorTransferPermutationMapLoweringPatterns()

void mlir::vector::populateVectorTransferPermutationMapLoweringPatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Collect a set of transfer read/write lowering patterns that simplify the permutation map (e.g., converting it to a minor identity map) by inserting broadcasts and transposes.

More specifically:

[TransferReadPermutationLowering] Lower transfer_read op with permutation into a transfer_read with a permutation map composed of leading zeros followed by a minor identity + vector.transpose op. Ex: vector.transfer_read ... permutation_map: (d0, d1, d2) -> (0, d1) into: v = vector.transfer_read ... permutation_map: (d0, d1, d2) -> (d1, 0) vector.transpose v, [1, 0]

vector.transfer_read ... permutation_map: (d0, d1, d2, d3) -> (0, 0, 0, d1, d3) into: v = vector.transfer_read ... permutation_map: (d0, d1, d2, d3) -> (0, 0, d1, 0, d3) vector.transpose v, [0, 1, 3, 2, 4] Note that an alternative is to transform it to linalg.transpose + vector.transfer_read to do the transpose in memory instead.

[TransferWritePermutationLowering] Lower transfer_write op with permutation into a transfer_write with a minor identity permutation map. (transfer_write ops cannot have broadcasts.) Ex: vector.transfer_write v ... permutation_map: (d0, d1, d2) -> (d2, d0, d1) into: tmp = vector.transpose v, [2, 0, 1] vector.transfer_write tmp ... permutation_map: (d0, d1, d2) -> (d0, d1, d2)

vector.transfer_write v ... permutation_map: (d0, d1, d2, d3) -> (d3, d2) into: tmp = vector.transpose v, [1, 0] v = vector.transfer_write tmp ... permutation_map: (d0, d1, d2, d3) -> (d2, d3)

[TransferOpReduceRank] Lower transfer_read op with broadcast in the leading dimensions into transfer_read of lower rank + vector.broadcast. Ex: vector.transfer_read ... permutation_map: (d0, d1, d2, d3) -> (0, d1, 0, d3) into: v = vector.transfer_read ... permutation_map: (d0, d1, d2, d3) -> (d1, 0, d3) vector.broadcast v

Definition at line 410 of file LowerVectorTransfer.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorTransposeLoweringPatterns()

void mlir::vector::populateVectorTransposeLoweringPatterns ( RewritePatternSet patterns,
VectorTransformsOptions  options,
PatternBenefit  benefit = 1 
)

Populate the pattern set with the following patterns:

[TransposeOpLowering]

[TransposeOp2DToShuffleLowering]

Definition at line 523 of file LowerVectorTranspose.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and options.

◆ populateVectorTransposeNarrowTypeRewritePatterns()

void mlir::vector::populateVectorTransposeNarrowTypeRewritePatterns ( RewritePatternSet patterns,
PatternBenefit  benefit = 1 
)

Appends patterns for emulating a sub-byte vector transpose.

Definition at line 1289 of file VectorEmulateNarrowType.cpp.

References mlir::RewritePatternSet::add(), and mlir::RewritePatternSet::getContext().

◆ populateVectorUnrollPatterns()

void mlir::vector::populateVectorUnrollPatterns ( RewritePatternSet patterns,
const UnrollVectorOptions options,
PatternBenefit  benefit = 1 
)

Collect a set of pattern to unroll vector operations to a smaller shapes.

options structure controls which operations are unrolled and the target shape. op is unrolled to the targetShape as follows, for each of its operands:

  1. the unrolled type unrolledVectorType and number of unrolled instances numUnrolledInstances are computed from the targetShape. For now it is assumed the unrolling factors divide the vector sizes.
  2. ExtractStridedSlice are created to break-up the vector operands.
  3. the original op is cloned numUnrolledInstances times, once for each result.
  4. InsertStridedSlice are inserted to re-assemble the slices into the original vectore shape.

Example:

opA(operand0, operand1) // numUnrolledInstances = 3

    operand0                   operand1
       |                          |
     fork                       fork
<----------gather all fork ops --------->
      /|\                        /|\
  f00 f01 f02                f10 f11 f12
<---------- clone op 3 times --------->
  opA0(f00, f10), opA1(f01, f11), opA2(f02, f12)
         \            |            /

<-----------------— join ----------------------—>

Other local patterns then kick in iteratively (including DCE) and compose to combine the ExtractStridedSlice/InsertStridedSlice.

Definition at line 622 of file VectorUnroll.cpp.

References mlir::RewritePatternSet::add(), mlir::RewritePatternSet::getContext(), and options.

◆ populateWarpExecuteOnLane0OpToScfForPattern()

void mlir::vector::populateWarpExecuteOnLane0OpToScfForPattern ( RewritePatternSet patterns,
const WarpExecuteOnLane0LoweringOptions options,
PatternBenefit  benefit = 1 
)

◆ registerBufferizableOpInterfaceExternalModels()

void mlir::vector::registerBufferizableOpInterfaceExternalModels ( DialectRegistry registry)

◆ registerSubsetOpInterfaceExternalModels()

void mlir::vector::registerSubsetOpInterfaceExternalModels ( DialectRegistry registry)

◆ registerTransformDialectExtension()

void mlir::vector::registerTransformDialectExtension ( DialectRegistry registry)

◆ registerValueBoundsOpInterfaceExternalModels()

void mlir::vector::registerValueBoundsOpInterfaceExternalModels ( DialectRegistry registry)

◆ rewriteBitCastOfTruncI()

FailureOr<Value> mlir::vector::rewriteBitCastOfTruncI ( RewriterBase rewriter,
vector::BitCastOp  bitCastOp,
arith::TruncIOp  truncOp,
vector::BroadcastOp  maybeBroadcastOp 
)

Rewrite a vector bitcast(trunci) to use a more efficient sequence of vector operations comprising shuffle and bitwise ops.

Warning: these patterns currently only work for little endian targets.

◆ rewriteExtOfBitCast()

FailureOr<Value> mlir::vector::rewriteExtOfBitCast ( RewriterBase rewriter,
Operation extOp,
vector::BitCastOp  bitCastOp,
vector::BroadcastOp  maybeBroadcastOp 
)

Rewrite a vector ext(bitcast) to use a more efficient sequence of vector operations comprising shuffle and bitwise ops.

Warning: these patterns currently only work for little endian targets.

◆ selectPassthru()

Value mlir::vector::selectPassthru ( OpBuilder builder,
Value  mask,
Value  newValue,
Value  passthru 
)

Creates a vector select operation that picks values from newValue or passthru for each result vector lane based on mask.

This utility is used to propagate the pass-thru value for masked-out or expeculatively executed lanes. VP intrinsics do not support pass-thru values and every mask-out lane is set to poison. LLVM backends are usually able to match op + select patterns and fold them into a native target instructions.

◆ splitFullAndPartialTransfer()

LogicalResult mlir::vector::splitFullAndPartialTransfer ( RewriterBase b,
VectorTransferOpInterface  xferOp,
VectorTransformsOptions  options = VectorTransformsOptions(),
scf::IfOp *  ifOp = nullptr 
)

Split a vector.transfer operation into an in-bounds (i.e., no out-of-bounds masking) fastpath and a slowpath.

If ifOp is not null and the result is success, theifOp` points to the newly created conditional upon function return. To accomodate for the fact that the original vector.transfer indexing may be arbitrary and the slow path indexes @[0...0] in the temporary buffer, the scf.if op returns a view and values of type index. At this time, only vector.transfer_read case is implemented.

Example (a 2-D vector.transfer_read): ``` %1 = vector.transfer_read %0[...], pad : memref<A...>, vector<...> ``` is transformed into: ``` %1:3 = scf.if (inBounds) { // fastpath, direct cast memref.cast A: memref<A...> to compatibleMemRefType scf.yield view : compatibleMemRefType, index, index } else { // slowpath, not in-bounds vector.transfer or linalg.copy. memref.cast alloc: memref<B...> to compatibleMemRefType scf.yield %4 : compatibleMemRefType, index, index */ // } /** %0 = vector.transfer_read %1#0[%1#1, %1#2] {in_bounds = [true ... true]} `` wherealloc` is a top of the function alloca'ed buffer of one vector.

Preconditions:

  1. xferOp.permutation_map() must be a minor identity map
  2. the rank of the xferOp.memref() and the rank of the xferOp.vector() must be equal. This will be relaxed in the future but requires rank-reducing subviews.

For vector.transfer_read: If ifOp is not null and the result is success, theifOp` points to the newly created conditional upon function return. To accomodate for the fact that the original vector.transfer indexing may be arbitrary and the slow path indexes @[0...0] in the temporary buffer, the scf.if op returns a view and values of type index.

Example (a 2-D vector.transfer_read): ``` %1 = vector.transfer_read %0[...], pad : memref<A...>, vector<...> ``` is transformed into: ``` %1:3 = scf.if (inBounds) { // fastpath, direct cast memref.cast A: memref<A...> to compatibleMemRefType scf.yield view : compatibleMemRefType, index, index } else { // slowpath, not in-bounds vector.transfer or linalg.copy. memref.cast alloc: memref<B...> to compatibleMemRefType scf.yield %4 : compatibleMemRefType, index, index */ // } /** %0 = vector.transfer_read %1#0[%1#1, %1#2] {in_bounds = [true ... true]} `` wherealloc` is a top of the function alloca'ed buffer of one vector.

For vector.transfer_write: There are 2 conditional blocks. First a block to decide which memref and indices to use for an unmasked, inbounds write. Then a conditional block to further copy a partial buffer into the final result in the slow path case.

Example (a 2-D vector.transfer_write): ``` vector.transfer_write arg, %0[...], pad : memref<A...>, vector<...> ``` is transformed into: ``` %1:3 = scf.if (inBounds) { memref.cast A: memref<A...> to compatibleMemRefType scf.yield view : compatibleMemRefType, index, index } else { memref.cast alloc: memref<B...> to compatibleMemRefType scf.yield %4 : compatibleMemRefType, index, index } %0 = vector.transfer_write arg, %1#0[%1#1, %1#2] {in_bounds = [true ... true]} scf.if (notInBounds) { // slowpath: not in-bounds vector.transfer or linalg.copy. } `` wherealloc` is a top of the function alloca'ed buffer of one vector.

Preconditions:

  1. xferOp.getPermutationMap() must be a minor identity map
  2. the rank of the xferOp.getSource() and the rank of the xferOp.getVector() must be equal. This will be relaxed in the future but requires rank-reducing subviews.

Definition at line 519 of file VectorTransferSplitRewritePatterns.cpp.

References mlir::clone(), mlir::OpBuilder::clone(), mlir::OpBuilder::create(), createFullPartialLinalgCopy(), createFullPartialVectorTransferRead(), createFullPartialVectorTransferWrite(), createInBoundsCond(), mlir::RewriterBase::eraseOp(), mlir::failure(), mlir::Region::front(), mlir::get(), getAutomaticAllocationScope(), mlir::Builder::getBoolArrayAttr(), getCastCompatibleMemRefType(), mlir::Builder::getI64IntegerAttr(), mlir::Builder::getIndexType(), mlir::Operation::getLoc(), getLocationToWriteFullVec(), mlir::Operation::getNumRegions(), mlir::Operation::getRegion(), mlir::Value::getType(), mlir::IRMapping::map(), mlir::RewriterBase::modifyOpInPlace(), None, options, mlir::Operation::setAttr(), mlir::OpBuilder::setInsertionPoint(), mlir::OpBuilder::setInsertionPointToStart(), splitFullAndPartialTransferPrecondition(), mlir::succeeded(), and mlir::success().

◆ transferOpflowOpt()

void mlir::vector::transferOpflowOpt ( RewriterBase rewriter,
Operation rootOp 
)

Implements transfer op write to read forwarding and dead transfer write optimizations.

Definition at line 930 of file VectorTransferOpTransforms.cpp.

References mlir::Operation::walk().