mlir::vector Namespace Reference

Namespaces
	detail

Classes
struct	ScalableValueBoundsConstraintSet
	A version of ValueBoundsConstraintSet that can solve for scalable bounds. More...
struct	VectorDim
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	VscaleRange
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	ConstantMaskKind { AllFalse = 0 , AllTrue }
	Predefined constant_mask kinds. More...
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< VectorDim, VectorDim > *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< Value >	getAsValues (OpBuilder &builder, Location loc, ArrayRef< OpFoldResult > foldResults)
	Convert foldResults into Values. More...
std::optional< int64_t >	getConstantVscaleMultiplier (Value value)
	If value is a constant multiple of vector.vscale (e.g. 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...
Operation *	maskOperation (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	populateVectorStepLoweringPatterns (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...
void	populateVectorRankReducingFMAPattern (RewritePatternSet &patterns)
	Populates a pattern that rank-reduces n-D FMAs into (n-1)-D FMAs where n > 1. More...
std::unique_ptr< Pass >	createLowerVectorMaskPass ()
	Creates an instance of the vector.mask lowering pass. More...
std::unique_ptr< Pass >	createLowerVectorMultiReductionPass (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	populateSinkVectorOpsPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
	Patterns that remove redundant Vector Ops by re-ordering them with e.g. 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 (const arith::NarrowTypeEmulationConverter &typeConverter, RewritePatternSet &patterns)
	Appends patterns for emulating vector operations over narrow types with ops over wider types. More...
FailureOr< Value >	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. More...
FailureOr< Value >	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. 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 (const 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< Value >	castAwayContractionLeadingOneDim (vector::ContractionOp contractOp, MaskingOpInterface maskingOp, RewriterBase &rewriter)
	Cast away the leading unit dim, if exists, for the given contract op. More...
void	eliminateVectorMasks (IRRewriter &rewriter, FunctionOpInterface function, std::optional< VscaleRange > vscaleRange={})
	Attempts to eliminate redundant vector masks by replacing them with all-true constants at the top of the function (which results in the masks folding away). 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< StaticTileOffsetRange >	createUnrollIterator (VectorType vType, int64_t targetRank=1)
	Returns an iterator for all positions in the leading dimensions of vType up to the targetRank. More...
auto	makeVscaleConstantBuilder (PatternRewriter &rewriter, Location loc)
	Returns a functor (int64_t -> Value) which returns a constant vscale multiple. More...
auto	getDims (VectorType vType)
	Returns a range over the dims (size and scalability) of a VectorType. More...
SmallVector< OpFoldResult >	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). 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

using mlir::vector::ConstantOrScalableBound = typedef ScalableValueBoundsConstraintSet::ConstantOrScalableBound

Definition at line 103 of file ScalableValueBoundsConstraintSet.h.

DistributionMapFn

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

Definition at line 44 of file VectorDistribution.h.

Enumeration Type Documentation

BroadcastableToResult

enum mlir::vector::BroadcastableToResult

strong

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

Enumerator
Success
SourceRankHigher
DimensionMismatch
SourceTypeNotAVector

Definition at line 68 of file VectorOps.h.

ConstantMaskKind

enum mlir::vector::ConstantMaskKind

strong

Predefined constant_mask kinds.

Enumerator
AllFalse
AllTrue

Definition at line 60 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 125 of file VectorOps.cpp.

References mlir::OpBuilder::create().

castAwayContractionLeadingOneDim()

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

Cast away the leading unit dim, if exists, for the given contract op.

Return success if the transformation applies; return failure otherwise.

Definition at line 333 of file VectorDropLeadUnitDim.cpp.

References mlir::OpBuilder::create(), mlir::OpBuilder::createOrFold(), mlir::detail::enumerate(), mlir::AffineMap::get(), mlir::Builder::getAffineDimExpr(), mlir::Builder::getAffineMapArrayAttr(), mlir::Builder::getArrayAttr(), mlir::Operation::getResults(), isParallelIterator(), maskOperation(), and splatZero().

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 329 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.

eliminateVectorMasks()

void mlir::vector::eliminateVectorMasks	(	IRRewriter &	rewriter,
		FunctionOpInterface	function,
		std::optional< VscaleRange >	vscaleRange = {}
	)

Attempts to eliminate redundant vector masks by replacing them with all-true constants at the top of the function (which results in the masks folding away).

Note: Currently, this only runs for vector.create_mask ops and requires vscaleRange. If vscaleRange is not provided this transform does nothing. This is because these redundant masks are much more likely for scalable code which requires memref/tensor dynamic sizes, whereas fixed-size code has static sizes, so simpler folds remove the masks.

Definition at line 97 of file VectorMaskElimination.cpp.

References mlir::OpBuilder::setInsertionPointToStart().

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 326 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 314 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 338 of file VectorOps.cpp.

References mlir::OpBuilder::create().

getConstantVscaleMultiplier()

std::optional< int64_t > mlir::vector::getConstantVscaleMultiplier

(

Value

value

)

If value is a constant multiple of vector.vscale (e.g.

cst * vector.vscale), return the multiplier (cst). Otherwise, return std::nullopt.

Definition at line 354 of file VectorOps.cpp.

References mlir::getConstantIntValue(), and mlir::Value::getDefiningOp().

getDims()

auto mlir::vector::getDims ( VectorType  vType )

inline

Returns a range over the dims (size and scalability) of a VectorType.

Definition at line 124 of file VectorUtils.h.

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 153 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 624 of file VectorOps.cpp.

References mlir::OpBuilder::create(), mlir::emitOptionalError(), mlir::Value::getLoc(), and MINUI.

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 446 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 442 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 4121 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< VectorDim, VectorDim > *	mismatchingDims = nullptr
	)

Definition at line 2443 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 219 of file VectorOps.cpp.

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

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 283 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 147 of file VectorOps.h.

Referenced by castAwayContractionLeadingOneDim(), and gpuMmaUnrollOrder().

isReductionIterator()

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

inline

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

Definition at line 152 of file VectorOps.h.

Referenced by 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.

References areDimsTransposedIn2DSlice(), and mlir::detail::enumerate().

Referenced by TransposeOpLowering::matchAndRewrite().

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 371 of file VectorUtils.cpp.

References LDBG.

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.

Referenced by createContractArithOp().

makeVscaleConstantBuilder()

auto mlir::vector::makeVscaleConstantBuilder ( PatternRewriter &  rewriter, Location  loc  )

inline

Returns a functor (int64_t -> Value) which returns a constant vscale multiple.

Example:

 {c++}
auto createVscaleMultiple = makeVscaleConstantBuilder(rewriter, loc);
auto c4Vscale = createVscaleMultiple(4); // 4 * vector.vscale

Definition at line 113 of file VectorUtils.h.

References mlir::OpBuilder::create().

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 2120 of file VectorTransforms.cpp.

References mlir::patterns.

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 2068 of file VectorTransforms.cpp.

References mlir::patterns.

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 572 of file VectorDropLeadUnitDim.cpp.

References mlir::patterns, and populateShapeCastFoldingPatterns().

Referenced by mlir::spirv::unrollVectorsInFuncBodies().

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 2113 of file VectorTransforms.cpp.

References mlir::PatternBenefit::getBenefit(), and mlir::patterns.

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 2056 of file VectorTransforms.cpp.

References mlir::patterns.

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 2127 of file VectorTransforms.cpp.

References mlir::patterns.

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 982 of file VectorTransferOpTransforms.cpp.

References mlir::patterns, 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 2034 of file VectorTransforms.cpp.

References mlir::patterns.

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 965 of file VectorTransferOpTransforms.cpp.

References mlir::patterns.

populateShapeCastFoldingPatterns()

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

Collect a set of vector.shape_cast folding patterns.

Definition at line 2051 of file VectorTransforms.cpp.

References mlir::patterns.

Referenced by populateCastAwayVectorLeadingOneDimPatterns(), populateFlattenVectorTransferPatterns(), and populateVectorTransferDropUnitDimsPatterns().

populateSinkVectorOpsPatterns()

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

Patterns that remove redundant Vector Ops by re-ordering them with e.g.

elementwise Ops:

%at = vector.transpose %a, [1, 0]: vector<4x2xf32> to vector<2x4xf32>
%bt = vector.transpose %b, [1, 0]: vector<4x2xf32> to vector<2x4xf32>
%r = arith.addf %at, %bt : vector<2x4xf32>

gets converted to:

%0 = arith.addf %a, %b : vector<4x2xf32>
%r = vector.transpose %0, [1, 0] : vector<2x4xf32>

At the moment, these patterns are limited to vector.broadcast and vector.transpose.

Definition at line 2106 of file VectorTransforms.cpp.

References mlir::patterns.

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 87 of file LowerVectorBitCast.cpp.

References mlir::patterns.

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 156 of file LowerVectorBroadcast.cpp.

References mlir::patterns.

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 2083 of file VectorTransforms.cpp.

References mlir::patterns.

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 1384 of file LowerVectorContract.cpp.

References options, and mlir::patterns.

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 318 of file VectorInsertExtractStridedSliceRewritePatterns.cpp.

References mlir::patterns.

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 268 of file LowerVectorGather.cpp.

References mlir::patterns.

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 312 of file VectorInsertExtractStridedSliceRewritePatterns.cpp.

References mlir::patterns.

Referenced by populateVectorInsertExtractStridedSliceTransforms(), and mlir::spirv::unrollVectorsInFuncBodies().

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 327 of file VectorInsertExtractStridedSliceRewritePatterns.cpp.

References mlir::patterns, and populateVectorInsertExtractStridedSliceDecompositionPatterns().

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 183 of file LowerVectorInterleave.cpp.

References mlir::patterns.

populateVectorInterleaveToShufflePatterns()

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

Definition at line 189 of file LowerVectorInterleave.cpp.

References mlir::patterns.

populateVectorLinearizeShuffleLikeOpsPatterns()

void mlir::vector::populateVectorLinearizeShuffleLikeOpsPatterns	(	const 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 464 of file VectorLinearize.cpp.

References mlir::TypeConverter::addArgumentMaterialization(), mlir::TypeConverter::addConversion(), mlir::TypeConverter::addSourceMaterialization(), mlir::TypeConverter::addTargetMaterialization(), mlir::OpBuilder::create(), mlir::get(), mlir::Operation::hasTrait(), mlir::TypeConverter::isLegal(), isLessThanTargetBitWidth(), isLinearizableVector(), mlir::ConversionTarget::markUnknownOpDynamicallyLegal(), and mlir::patterns.

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::patterns.

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::patterns.

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 2041 of file VectorTransforms.cpp.

References mlir::patterns.

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::patterns.

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 500 of file LowerVectorMultiReduction.cpp.

References options, and mlir::patterns.

populateVectorNarrowTypeEmulationPatterns()

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

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

Definition at line 1560 of file VectorEmulateNarrowType.cpp.

References mlir::patterns.

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 1570 of file VectorEmulateNarrowType.cpp.

References mlir::PatternBenefit::getBenefit(), and mlir::patterns.

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 1394 of file LowerVectorContract.cpp.

References mlir::patterns.

populateVectorRankReducingFMAPattern()

void mlir::vector::populateVectorRankReducingFMAPattern

(

RewritePatternSet &

patterns

)

Populates a pattern that rank-reduces n-D FMAs into (n-1)-D FMAs where n > 1.

Definition at line 1900 of file ConvertVectorToLLVM.cpp.

References mlir::patterns.

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 2091 of file VectorTransforms.cpp.

References mlir::patterns.

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 191 of file LowerVectorScan.cpp.

References mlir::patterns.

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 353 of file LowerVectorShapeCast.cpp.

References mlir::patterns.

Referenced by mlir::spirv::unrollVectorsInFuncBodies().

populateVectorStepLoweringPatterns()

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

Populate the pattern set with the following patterns:

[StepToArithConstantOp] Convert vector.step op into arith ops if not using scalable vectors

Definition at line 46 of file LowerVectorStep.cpp.

References mlir::patterns.

Referenced by mlir::populateSparseVectorizationPatterns().

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 2098 of file VectorTransforms.cpp.

References mlir::patterns.

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 974 of file VectorTransferOpTransforms.cpp.

References mlir::patterns, 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 options, and mlir::patterns.

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 642 of file LowerVectorTransfer.cpp.

References mlir::patterns.

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 385 of file LowerVectorTransfer.cpp.

References mlir::patterns.

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 522 of file LowerVectorTranspose.cpp.

References options, and mlir::patterns.

Referenced by mlir::spirv::unrollVectorsInFuncBodies().

populateVectorTransposeNarrowTypeRewritePatterns()

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

Appends patterns for emulating a sub-byte vector transpose.

Definition at line 1588 of file VectorEmulateNarrowType.cpp.

References mlir::patterns.

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 options, and mlir::patterns.

Referenced by mlir::spirv::unrollVectorsInFuncBodies().

populateWarpExecuteOnLane0OpToScfForPattern()

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

Definition at line 1746 of file VectorDistribute.cpp.

References options, and mlir::patterns.

registerBufferizableOpInterfaceExternalModels()

void mlir::vector::registerBufferizableOpInterfaceExternalModels

(

DialectRegistry &

registry

)

Definition at line 318 of file BufferizableOpInterfaceImpl.cpp.

References mlir::DialectRegistry::addExtension().

Referenced by mlir::registerAllDialects().

registerSubsetOpInterfaceExternalModels()

void mlir::vector::registerSubsetOpInterfaceExternalModels

(

DialectRegistry &

registry

)

Definition at line 70 of file SubsetOpInterfaceImpl.cpp.

References mlir::DialectRegistry::addExtension().

Referenced by mlir::registerAllDialects().

registerTransformDialectExtension()

void mlir::vector::registerTransformDialectExtension

(

DialectRegistry &

registry

)

Definition at line 237 of file VectorTransformOps.cpp.

References mlir::DialectRegistry::addExtensions().

Referenced by mlir::registerAllExtensions().

registerValueBoundsOpInterfaceExternalModels()

void mlir::vector::registerValueBoundsOpInterfaceExternalModels

(

DialectRegistry &

registry

)

Definition at line 45 of file ValueBoundsOpInterfaceImpl.cpp.

References mlir::DialectRegistry::addExtension().

Referenced by mlir::registerAllDialects().

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.

Referenced by createContractArithOp().

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::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(), and splitFullAndPartialTransferPrecondition().

transferOpflowOpt()

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

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

Definition at line 948 of file VectorTransferOpTransforms.cpp.

References mlir::Operation::walk().