Namespaces
	detail

Classes
class	Aliases
	A very primitive alias analysis which just records for each view, either: More...

struct	CodegenStrategy
	Codegen strategy controls how a Linalg op is progressively lowered. More...

struct	CopyVectorizationPattern
	`filter` controls LinalgTransformMarker matching and update when specified. More...

struct	Decompose
	Represent one application of createLinalgStrategyDecomposePass. More...

struct	DownscaleDepthwiseConv2DNhwcHwcOp
	Rewrites 2-D depthwise convolution ops with size-1 (w, kw) or (h, kh) dimensions into 1-D depthwise convolution ops. More...

struct	DownscaleSizeOneWindowed2DConvolution
	Rewrites 2-D convolution ops with size-1 window dimensions into 1-D convolution ops. More...

struct	ExtractSliceOfPadTensorSwapPattern
	Rewrite extract_slice(tensor.pad(x)) into tensor.pad(extract_slice(x)). More...

struct	ForeachThreadTilingResult
	Rewrite a TilingInterface `op` to a tiled `scf.foreach_thread`, applying tiling by `numThreads`. More...

struct	FusionInfo
	A struct containing the Linalg producer before and after fusion. More...

struct	GeneralizePadOpPattern
	Rewrite a tensor::PadOp into a sequence of EmptyOp, FillOp and InsertSliceOp. More...

struct	GenerateLoopNest
	Utility class used to generate nested loops with ranges described by `loopRanges` and loop type described by the `iteratorTypes`. More...

struct	LinalgCopyVTRForwardingPattern
	Match and rewrite for the pattern: ``` alloc = ... More...

struct	LinalgCopyVTWForwardingPattern
	Match and rewrite for the pattern: ``` alloc = ... More...

class	LinalgDependenceGraph
	Data structure for holding a dependence graph that operates on LinalgOp and views as SSA values. More...

struct	LinalgEnablingOptions
	Options to control the application of enabling transformations. More...

struct	LinalgGeneralizationPattern
	Linalg generalization pattern. More...

struct	LinalgLoopDistributionOptions
	Options that allow distribution of loops generated in Linalg transforms to processors while generating the loops. More...

struct	LinalgLoweringPattern

class	LinalgOpToLibraryCallRewrite

struct	LinalgPaddingOptions

struct	LinalgPaddingPattern
	Linalg padding pattern. More...

struct	LinalgPromotionOptions

struct	LinalgTileAndFuseTensorOpsPattern
	Linalg tile and fuse tensor ops pattern. More...

struct	LinalgTilingAndFusionOptions

struct	LinalgTilingOptions

struct	LinalgTilingPattern
	Linalg tiling pattern. More...

struct	LinalgTransformationFilter
	Helper class to control application of linalg transformation patterns. More...

struct	LinalgTransforms

struct	LinalgVectorizationOptions
	Linalg vectorization patterns. More...

struct	MultiSizeSpecification
	A description of a multi-size tiling comprising tile sizes and numbers of tiles, expressed as Values which may or may not be constant. More...

struct	OpOperandVector
	OpOperand vector that implicitly converts to a Value vector. More...

struct	Pad
	Represent one application of LinalgStrategyPadPass. More...

struct	PadOpTransformationPattern
	tensor::PadOp is not canonicalized away yet, so we provide a transformation to `linalg.generic`. More...

struct	ProcInfo
	Callback function type used to get processor ID, and number of processors used for distribution for all parallel loops generated. More...

struct	PromotionInfo
	Create a new buffer using the `allocationFn` provided. More...

struct	RegionMatcher
	A struct containing common matchers over linalg op's region. More...

struct	SliceParameters
	A struct containg offsets-sizes-strides arguments of the tiled shape. More...

struct	SplitReductionOptions
	Split Reduction options. More...

struct	SplitReductionResult
	Filterless version of the above. More...

struct	Tile
	Represent one application of LinalgStrategyTilePass. More...

struct	TileAndFuse
	Represent one application of LinalgStrategyTileAndFusePass. More...

struct	TiledLinalgOp
	Perform standalone tiling of a single LinalgOp by `tileSizes`. More...

class	TileLoopNest
	A struct to manage the tile loop nest specific information. More...

class	TilingPatterns

class	TilingPatterns< OpTy, OpTypes... >

class	TilingPatterns<>

struct	Transformation
	Abstract Transformation class applied in a sequence that also handles state through markers. More...

class	VectorizationPatterns

class	VectorizationPatterns<>

Typedefs
using	LinalgLoops = SmallVector< Operation *, 4 >

using	ControlFusionFn = std::function< bool(OpOperand *fusedOperand)>
	Function type which is used to control when to stop fusion. More...

using	AllocBufferCallbackFn = std::function< Optional< Value >(OpBuilder &b, memref::SubViewOp subView, ArrayRef< Value > boundingSubViewSize, DataLayout &layout)>
	Callback function type used to perform the allocation for the promoted `subView`. More...

using	DeallocBufferCallbackFn = std::function< LogicalResult(OpBuilder &b, Value buffer)>
	Callback function type used to deallocate the buffers used to hold the promoted subview. More...

using	CopyCallbackFn = std::function< LogicalResult(OpBuilder &b, Value src, Value dst)>
	Callback function type used to insert copy from original subview to subview of the promoted region for the read operands/subview of promoted region to original subview for the results. More...

using	TileSizeComputationFunction = std::function< SmallVector< Value, 4 >(OpBuilder &, Operation *)>

using	LoopIndexToRangeIndexMap = DenseMap< int, int >
	Creates a number of ranges equal to the number of non-zero in `tileSizes`. More...

using	OptimizeCopyFn = std::function< LogicalResult(PatternRewriter &, tensor::PadOp, Value)>

using	ControlSplitReductionFn = std::function< SplitReductionOptions(LinalgOp op)>
	Function signature to control reduction splitting. More...

using	FusableOpDependencesTy = llvm::MapVector< Operation *, SmallVector< LinalgDependenceGraph::LinalgDependenceGraphElem, 1 > >

using	ProcInfoCallBackFn = std::function< SmallVector< ProcInfo >(OpBuilder &b, Location loc, ArrayRef< Range > parallelLoopRanges)>

Enumerations
enum	LinalgLoweringType { LinalgLoweringType::LibraryCall = 0, LinalgLoweringType::Loops = 1, LinalgLoweringType::AffineLoops = 2, LinalgLoweringType::ParallelLoops = 3 }
	Linalg lowering patterns. More...

enum	LinalgTilingLoopType { LinalgTilingLoopType::Loops = 0, LinalgTilingLoopType::AffineLoops = 1, LinalgTilingLoopType::ParallelLoops = 2 }
	The type of loops to be generated during tiling. More...

enum	DistributionMethod { DistributionMethod::Cyclic = 0, DistributionMethod::CyclicNumProcsGeNumIters = 1, DistributionMethod::CyclicNumProcsEqNumIters = 2, DistributionMethod::None = 3 }
	Scheme used to distribute loops to processors. More...

Functions
void	populateLinalgToStandardConversionPatterns (RewritePatternSet &patterns)
	Populate the given list with patterns that convert from Linalg to Standard. More...

std::string	generateLibraryCallName (Operation *op)
	Returns the name mangled library call name to disambiguate between different overloads at the C level. More...

SmallVector< AffineExpr, 4 >	makeAffineDimExprs (unsigned num, unsigned &startIdx, MLIRContext *context)
	Returns `num` AffineDimExpr dimensions at positions [startIdx, startIdx + num) and increments `startIdx` to `startIdx + num`. More...

AffineMap	extractOrIdentityMap (Optional< AffineMap > maybeMap, unsigned rank, MLIRContext *context)
	Returns `maybeMap.get()` if `maybeMap` is set, otherwise returns the symbol-less identity map of `rank`. More...

SmallVector< AffineExpr, 4 >	concat (ArrayRef< AffineExpr > a, ArrayRef< AffineExpr > b)
	Return the vector that is the concatenation of `a` and `b`. More...

bool	isaContractionOpInterface (LinalgOp linalgOp)
	Checks whether `linalgOp` conforms to ContractionOpInterface. More...

void	registerTransformDialectExtension (DialectRegistry &registry)

void	registerBufferizableOpInterfaceExternalModels (DialectRegistry &registry)

void	hoistRedundantVectorTransfers (func::FuncOp func)
	Hoist vector.transfer_read/vector.transfer_write on buffers pairs out of immediately enclosing scf::ForOp iteratively, if the following conditions are true: More...

void	hoistRedundantVectorTransfersOnTensor (func::FuncOp func)
	Same behavior as `hoistRedundantVectorTransfers` but works on tensors instead of buffers. More...

FailureOr< Value >	hoistPaddingOnTensors (tensor::PadOp opToHoist, int numLoops, ArrayRef< int64_t > transposeVector, tensor::PadOp &hoistedOp, SmallVectorImpl< GenericOp > &transposeOps)
	Mechanically hoist padding operations on tensors by `numLoops` into a new, generally larger tensor. More...

void	registerTilingInterfaceExternalModels (DialectRegistry &registry)

void	populatePadTensorTilingPatterns (RewritePatternSet &patterns, const LinalgTilingOptions &options)

void	populateDecomposeLinalgOpsPattern (RewritePatternSet &patterns)
	Populate patterns for splitting a `LinalgOp` with multiple statements within its payload into multiple `GenericOp` that have a single statement. More...

void	populateConvolutionVectorizationPatterns (RewritePatternSet &patterns, PatternBenefit benefit=1)
	Populate patterns for vectorizing low-D convolution ops. More...

void	populateElementwiseToLinalgConversionPatterns (RewritePatternSet &patterns)
	Populate patterns that convert `ElementwiseMappable` ops to linalg parallel loops. More...

void	populateSparseTensorRewriting (RewritePatternSet &patterns)
	Populate patterns that are only useful in the context of sparse tensors. More...

void	populateElementwiseOpsFusionPatterns (RewritePatternSet &patterns, const ControlFusionFn &controlElementwiseOpFusion)
	Patterns for fusing linalg operation on tensors. More...

void	populateFoldReshapeOpsByExpansionPatterns (RewritePatternSet &patterns, const ControlFusionFn &controlFoldingReshapes)
	Patterns to fold an expanding (collapsing) tensor_reshape operation with its producer (consumer) generic operation by expanding the dimensionality of the loop in the generic op. More...

void	populateFoldReshapeOpsByCollapsingPatterns (RewritePatternSet &patterns, const ControlFusionFn &controlFoldingReshapes)
	Patterns to fold an expanding tensor.expand_shape operation with its producer generic operation by collapsing the dimensions of the generic op. More...

void	populateConstantFoldLinalgOperations (RewritePatternSet &patterns, const ControlFusionFn &controlFn)
	Patterns to constant fold Linalg operations. More...

void	populateFuseTensorPadWithProducerLinalgOpPatterns (RewritePatternSet &patterns)
	Pattern to fuse a `tensor.pad` operation with the producer of its source, if the producer is a `linalg` operation with all parallel iterator types. More...

void	populateLinalgNamedOpConversionPatterns (RewritePatternSet &patterns)
	Patterns to convert from one named op to another. More...

void	populateFoldUnitExtentDimsPatterns (RewritePatternSet &patterns)
	Patterns to fold unit-extent dimensions in operands/results of linalg ops on tensors. More...

void	populateInlineConstantOperandsPatterns (RewritePatternSet &patterns)
	Patterns that are used to inline constant operands into linalg generic ops. More...

void	populateBubbleUpExtractSliceOpPatterns (RewritePatternSet &patterns)
	Patterns that are used to bubble up extract slice op above linalg op. More...

void	populateSwapExtractSliceWithFillPatterns (RewritePatternSet &patterns)
	Adds patterns that waps tensor.extract_slice(linalg.fill(cst, init)) into linalg.fill(cst, tensor.extract_slice(init)). More...

bool	areElementwiseOpsFusable (OpOperand *fusedOperand)
	Return true if two `linalg.generic` operations with producer/consumer relationship through `fusedOperand` can be fused using elementwise op fusion. More...

FailureOr< Operation * >	fuseElementwiseOps (RewriterBase &rewriter, OpOperand *fusedOperand)
	Fuse two `linalg.generic` operations that have a producer-consumer relationship captured through `fusedOperand`. More...

std::pair< TilingInterface, TilingInterface >	splitOp (RewriterBase &rewriter, TilingInterface op, unsigned dimension, OpFoldResult splitPoint)
	Split the given `op` into two parts along the given iteration space `dimension` at the specified `splitPoint`, and return the two parts. More...

FailureOr< TiledLinalgOp >	tileLinalgOp (RewriterBase &b, LinalgOp op, const LinalgTilingOptions &options)

void	peelLoops (RewriterBase &rewriter, ArrayRef< scf::ForOp > loops)
	Peel and canonicalize 'loops'. More...

void	peelTiledLinalgOp (RewriterBase &rewriter, TiledLinalgOp &res, ArrayRef< int64_t > peeledLoops, LinalgTilingLoopType loopType)
	Peel the loops of a TiledLinalgOp. More...

FailureOr< GenericOp >	interchangeGenericOp (RewriterBase &rewriter, GenericOp genericOp, ArrayRef< unsigned > interchangeVector)
	Interchange the `iterator_types` and `iterator_maps` dimensions and adapts the index accesses of `op`. More...

FailureOr< GenericOp >	generalizeNamedOp (RewriterBase &rewriter, LinalgOp namedOp)
	Create a GenericOp from the given named operation `namedOp` and replace namedOp. More...

FailureOr< PromotionInfo >	promoteSubviewAsNewBuffer (OpBuilder &b, Location loc, memref::SubViewOp subView, const AllocBufferCallbackFn &allocationFn, DataLayout &layout)

FailureOr< LinalgOp >	promoteSubViews (OpBuilder &b, LinalgOp op, const LinalgPromotionOptions &options)
	Promote the `subViews` into a new buffer allocated at the insertion point `b`. More...

LogicalResult	vectorize (RewriterBase &builder, LinalgOp linalgOp)
	Emit a suitable vector form for a Linalg op with fully static shape. More...

LogicalResult	vectorizeCopy (RewriterBase &builder, memref::CopyOp copyOp)
	Emit a suitable vector form for a Copy op with fully static shape. More...

FailureOr< LinalgLoops >	linalgOpToLoops (PatternRewriter &rewriter, LinalgOp linalgOp)
	Emit a loop nest of `scf.for` with the proper body for `linalgOp`. More...

FailureOr< LinalgLoops >	linalgOpToParallelLoops (PatternRewriter &rewriter, LinalgOp linalgOp)
	Emit a loop nest of `scf.parallel` with the proper body for `linalgOp`. More...

FailureOr< LinalgLoops >	linalgOpToAffineLoops (PatternRewriter &rewriter, LinalgOp linalgOp)
	Emit a loop nest of `affine.for` with the proper body for `linalgOp`. More...

LogicalResult	promoteSubviewsPrecondition (Operation *op, LinalgPromotionOptions options)
	Promote memref.subviews feeding linalg-on-buffers operations. More...

std::tuple< SmallVector< Range, 4 >, LoopIndexToRangeIndexMap >	makeTiledLoopRanges (RewriterBase &b, Location loc, AffineMap map, ArrayRef< OpFoldResult > allShapeSizes, ArrayRef< OpFoldResult > allTileSizes)

FailureOr< MultiSizeSpecification >	computeMultiTileSizes (OpBuilder &builder, LinalgOp op, unsigned dimension, OpFoldResult targetSize, OpFoldResult divisor, bool emitAssertions=true)
	Emits the IR computing the multi-sized tiling specification with two tile sizes not exceeding `targetSize`, each divisible by `sizeDivisor`, such that there exist numbers of tiles with these sizes that fully cover the given iteration space `dimension` of the structured `op`. More...

FailureOr< ForeachThreadTilingResult >	tileToForeachThreadOp (RewriterBase &builder, TilingInterface op, ArrayRef< OpFoldResult > numThreads, ArrayRef< int64_t > threadDimMapping={})

FailureOr< ForeachThreadTilingResult >	tileToForeachThreadOpUsingTileSizes (RewriterBase &builder, TilingInterface op, ArrayRef< OpFoldResult > tileSizes, ArrayRef< int64_t > threadDimMapping={})
	Same as `tileToForeachThreadOp`, but calculate the number of threads required using the given tileSizes. More...

void	transformIndexOps (RewriterBase &b, LinalgOp op, SmallVectorImpl< Value > &ivs, const LoopIndexToRangeIndexMap &loopIndexToRangeIndex)
	All indices returned by IndexOp should be invariant with respect to tiling. More...

RewritePatternSet	getLinalgTilingCanonicalizationPatterns (MLIRContext *ctx)
	Canonicalization patterns relevant to apply after tiling patterns. More...

void	populateLinalgTilingCanonicalizationPatterns (RewritePatternSet &patterns)

llvm::Optional< vector::CombiningKind >	getCombinerOpKind (Operation *combinerOp)
	Return vector::CombiningKind for the given op. More...

void	populateLinalgNamedOpsGeneralizationPatterns (RewritePatternSet &patterns, const LinalgTransformationFilter &filter=LinalgTransformationFilter())
	Linalg generalization patterns. More...

void	populateDecomposeConvolutionPatterns (RewritePatternSet &patterns, const LinalgTransformationFilter &filter=LinalgTransformationFilter(), PatternBenefit benefit=1)
	Linalg decompose convolutions patterns. More...

FailureOr< SmallVector< Value > >	rewriteAsPaddedOp (OpBuilder &b, LinalgOp opToPad, ArrayRef< int64_t > paddingDimensions, ArrayRef< Attribute > paddingValues, ArrayRef< bool > packPaddings, LinalgOp &paddedOp)
	Pad the iterator dimensions `paddingDimensions` of all `opToPad` operands to a static bounding box. More...

void	populatePadOpVectorizationPatterns (RewritePatternSet &patterns, PatternBenefit baseBenefit=1)
	Populates `patterns` with patterns that vectorize tensor.pad. More...

LogicalResult	applyStagedPatterns (Operation op, ArrayRef< FrozenRewritePatternSet > stage1Patterns, const FrozenRewritePatternSet &stage2Patterns, function_ref< LogicalResult(Operation )> stage3Lambda=nullptr)
	Helper function to allow applying rewrite patterns, interleaved with more global transformations, in a staged fashion: More...

void	populateSplitReductionPattern (RewritePatternSet &patterns, const ControlSplitReductionFn &controlSplitReductionFn, const LinalgTransformationFilter &f=LinalgTransformationFilter(), bool useAlloc=false)
	Patterns to apply `splitReduction` below. More...

FailureOr< LinalgOp >	splitReduction (PatternRewriter &b, LinalgOp op, const ControlSplitReductionFn &controlSplitReductionFn, const LinalgTransformationFilter &f, bool useAlloc=false)
	Apply transformation to split the single linalg op reduction into a parallel and reduction dimension. More...

FailureOr< SplitReductionResult >	splitReduction (PatternRewriter &b, LinalgOp op, const ControlSplitReductionFn &controlSplitReductionFn, bool useAlloc=false)

FailureOr< SplitReductionResult >	splitReductionByScaling (PatternRewriter &b, LinalgOp op, const ControlSplitReductionFn &controlSplitReductionFn, bool useAlloc=false)
	Scaling-based implementation of the split reduction transformation. More...

bool	allIndexingsAreProjectedPermutation (LinalgOp op)
	Check if all indexing maps are projected permutations. More...

bool	hasOnlyScalarElementwiseOp (Region &r)
	Detect whether `r` has only ConstantOp, ElementwiseMappable and YieldOp. More...

bool	isElementwise (LinalgOp op)
	Check if a LinalgOp is an element-wise operation. More...

bool	isPermutation (ArrayRef< int64_t > permutation)
	Check if `permutation` is a permutation of the range `[0, permutation.size())`. More...

bool	isParallelIterator (StringRef iteratorType)
	Check if iterator type has "parallel" semantics. More...

bool	isReductionIterator (StringRef iteratorType)
	Check if iterator type has "reduction" semantics. 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...

OpFoldResult	createFoldedDimOp (OpBuilder &b, Location loc, Value source, int64_t dim)

SmallVector< Value, 4 >	getDynOperands (Location loc, Value val, OpBuilder &b)
	Given an operation, retrieves the value of each dynamic dimension through constructing the necessary DimOp operators. More...

void	getUpperBoundForIndex (Value value, AffineMap &boundMap, SmallVectorImpl< Value > &boundOperands, bool constantRequired=false)
	Computes an upper bound for the result `value` of an index computation. More...

FailureOr< int64_t >	getConstantUpperBoundForIndex (Value value)
	Returns a constant upper bound for the result `value` of an index computation. More...

Value	makeComposedPadHighOp (OpBuilder &b, Location loc, RankedTensorType type, Value source, Value pad, bool nofold)
	Create a tensor::PadOp that pads `source` to the size of the statically sized `type` whose static sizes are assumed to be greater than the dynamic `source` size. More...

GenericOp	makeTransposeOp (OpBuilder &b, Location loc, Value inputTensor, Value outputTensor, ArrayRef< int64_t > transposeVector)
	Returns a GenericOp that tansposes `inputTensor` into `outputTensor` using `transposeVector` to permute the `inputTensor` dimensions. More...

GenericOp	makeMemRefCopyOp (OpBuilder &b, Location loc, Value from, Value to)
	Returns GenericOp that copies an n-D memref. More...

Optional< SmallVector< ReassociationIndices > >	getReassociationMapForFoldingUnitDims (ArrayRef< OpFoldResult > mixedSizes)
	Get the reassociation maps to fold the result of a extract_slice (or source of a insert_slice) operation with given offsets, and sizes to its rank-reduced version. More...

bool	isProducerLastWriteOfView (const LinalgDependenceGraph &graph, LinalgOp consumer, Value consumedView, LinalgOp producer)
	Checks whether the specific `producer` is the last write to exactly the whole `consumedView`. More...

bool	isFusableInto (const LinalgDependenceGraph &graph, LinalgOp consumer, Value consumedView, LinalgOp producer)
	Checks whether fusing the specific `producer` of the `consumedView` is feasible. More...

SmallVector< OpFoldResult >	computeTileOffsets (OpBuilder &b, Location loc, ArrayRef< OpFoldResult > ivs, ArrayRef< OpFoldResult > tileSizes)
	Computes tile offsets, given a list of loop `ivs` and `tileSizes`. More...

SmallVector< OpFoldResult >	computeTileSizes (OpBuilder &b, Location loc, ArrayRef< OpFoldResult > tileSizes, ArrayRef< OpFoldResult > sizeBounds)
	Computes tile sizes, given a list of `tileSizes` and dimension sizes (`sizeBounds`). More...

SmallVector< Type >	getTensorOutputTypes (LinalgOp op, ValueRange operands)
	Returns the list of tensor output types produced when the given structured operation `op` is applied to the given `operands`. More...

SmallVector< Value >	insertSlicesBack (OpBuilder &builder, Location loc, LinalgOp op, ValueRange operands, ValueRange results)
	Creates `insert_slice` ops that insert `results` back into larger tensors they were originally extracted from with `extract_slice` before being passed as `operands` to the given structured operation `op` or its clone. More...

SliceParameters	computeSliceParameters (OpBuilder &builder, Location loc, Value valueToTile, ArrayRef< OpFoldResult > tileSizes, AffineMap map, ArrayRef< OpFoldResult > lbs, ArrayRef< OpFoldResult > ubs, ArrayRef< OpFoldResult > subShapeSizes, bool omitPartialTileCheck)
	Computes SliceParameters for a single `valueToTile` assuming that its user is being tiled with the given loop bounds `lbs` and `ubs` and the tile sizes `tileSizes`. More...

SmallVector< Optional< SliceParameters > >	computeAllSliceParameters (OpBuilder &builder, Location loc, LinalgOp linalgOp, ValueRange valuesToTile, ArrayRef< OpFoldResult > ivs, ArrayRef< OpFoldResult > tileSizes, ArrayRef< OpFoldResult > sizeBounds, bool omitPartialTileCheck)
	Computes SliceParamaters for all `valuesToTile` of the given `linalgOp`, assuming `linalgOp` is being fused into a loop nest. More...

Value	makeTiledShape (OpBuilder &builder, Location loc, Value valueToTile, ArrayRef< OpFoldResult > tileSizes, AffineMap map, ArrayRef< OpFoldResult > lbs, ArrayRef< OpFoldResult > ubs, ArrayRef< OpFoldResult > subShapeSizes, bool omitPartialTileCheck)
	Creates an extract_slice/subview op for a single `valueToTile` with `builder`. More...

SmallVector< Value >	makeTiledShapes (OpBuilder &builder, Location loc, LinalgOp linalgOp, ValueRange valuesToTile, ArrayRef< OpFoldResult > ivs, ArrayRef< OpFoldResult > tileSizes, ArrayRef< OpFoldResult > sizeBounds, bool omitPartialTileCheck)
	Creates extract_slice/subview ops for all `valuesToTile` of the given `linalgOp` with `builder`, assuming `linalgOp` is being fused into a loop nest for tiling with the given induction variables `ivs` and tile sizes `tileSizes`. More...

void	offsetIndices (OpBuilder &b, LinalgOp linalgOp, ArrayRef< OpFoldResult > offests)
	Add the specified offsets to any `linalg.index` ops contained in the given `linalgOp`. More...

void	offsetIndices (RewriterBase &b, LinalgOp linalgOp, ArrayRef< OpFoldResult > offests)

FusableOpDependencesTy	findAllFusableDependences (ArrayRef< LinalgOp > ops, const LinalgDependenceGraph &dependenceGraph)

FailureOr< FusionInfo >	fuseProducerOfBuffer (OpBuilder &b, OpOperand &consumerOpOperand, const LinalgDependenceGraph &graph)
	Fuses producer into consumer if the producer is structurally feasible and the fusion would not violate dependencies. More...

FailureOr< FusionInfo >	fuseProducerOfTensor (OpBuilder &b, OpOperand &consumerOpOperand)
	Tensor counterpart of `fuseProducerOfBuffer`. More...

FailureOr< FusionInfo >	fuseProducerOfTensor (OpBuilder &b, OpResult producerOpResult, OpOperand &consumerOpOperand)
	Tensor counterpart of `fuseProducerOfBuffer`. More...

void	updateBoundsForCyclicDistribution (OpBuilder &builder, Location loc, Value procId, Value nprocs, Value &lb, Value &ub, Value &step)
	Update the `lb`, `ub` and `step` to get per processor `lb`, `ub` and `step`. More...

FailureOr< TileLoopNest >	tileConsumerAndFuseProducers (OpBuilder &b, LinalgOp consumerOp, ArrayRef< int64_t > tileSizes, ArrayRef< int64_t > tileInterchange, const Optional< LinalgLoopDistributionOptions > &tileDistribution)
	Tiles `consumerOp` and fuses its dependencies if possible. More...

template<typename OpTy >
SmallVector< NamedAttribute >	getPrunedAttributeList (OpTy op)
	Returns an attribute list that excludes pre-defined attributes. More...

static void	generateParallelLoopNest (OpBuilder &b, Location loc, ValueRange lbs, ValueRange ubs, ValueRange steps, ArrayRef< StringRef > iteratorTypes, ArrayRef< linalg::ProcInfo > procInfo, function_ref< void(OpBuilder &, Location, ValueRange)> bodyBuilderFn, SmallVectorImpl< Value > &ivStorage)
	Generates a loop nest consisting of scf.parallel and scf.for, depending on the `iteratorTypes. More...

static Value	materializeTiledShape (OpBuilder &builder, Location loc, Value valueToTile, const SliceParameters &sliceParams)

Typedef Documentation

◆ AllocBufferCallbackFn

using mlir::linalg::AllocBufferCallbackFn = typedef std::function<Optional<Value>( OpBuilder &b, memref::SubViewOp subView, ArrayRef<Value> boundingSubViewSize, DataLayout &layout)>

Callback function type used to perform the allocation for the promoted subView.

In boundingSubViewsize a best attempt is made to find the smallest constant value for the size of the buffer needed for each dimension. If that is not possible, contains the dynamic size of the subview. The call back should return the buffer to use.

Definition at line 216 of file Transforms.h.

◆ ControlFusionFn

using mlir::linalg::ControlFusionFn = typedef std::function<bool(OpOperand *fusedOperand)>

Function type which is used to control when to stop fusion.

It is expected that OpOperand is not modified in the callback. The OpOperand is not marked as const to allow callers to use non-const methods.

Definition at line 69 of file Transforms.h.

◆ ControlSplitReductionFn

using mlir::linalg::ControlSplitReductionFn = typedef std::function<SplitReductionOptions(LinalgOp op)>

Function signature to control reduction splitting.

This returns SplitReductionOptions.

Definition at line 1222 of file Transforms.h.

◆ CopyCallbackFn

using mlir::linalg::CopyCallbackFn = typedef std::function<LogicalResult(OpBuilder &b, Value src, Value dst)>

Callback function type used to insert copy from original subview to subview of the promoted region for the read operands/subview of promoted region to original subview for the results.

The copy has to happen from src to dst.

Definition at line 228 of file Transforms.h.

◆ DeallocBufferCallbackFn

using mlir::linalg::DeallocBufferCallbackFn = typedef std::function<LogicalResult(OpBuilder &b, Value buffer)>

Callback function type used to deallocate the buffers used to hold the promoted subview.

Definition at line 221 of file Transforms.h.

◆ FusableOpDependencesTy

using mlir::linalg::FusableOpDependencesTy = typedef llvm::MapVector< Operation *, SmallVector<LinalgDependenceGraph::LinalgDependenceGraphElem, 1> >

Definition at line 272 of file Utils.h.

◆ LinalgLoops

using mlir::linalg::LinalgLoops = typedef SmallVector<Operation *, 4>

Definition at line 44 of file Transforms.h.

◆ LoopIndexToRangeIndexMap

using mlir::linalg::LoopIndexToRangeIndexMap = typedef DenseMap<int, int>

Creates a number of ranges equal to the number of non-zero in tileSizes.

One for each loop of the LinalgOp that is tiled. The tileSizes argument has one entry per surrounding loop. It uses zero as the convention that a particular loop is not tiled. This convention simplifies implementations by avoiding affine map manipulations. The returned ranges correspond to the loop ranges, in the proper order, that are tiled and for which new loops will be created. Also the function returns a map from loop indices of the LinalgOp to the corresponding non-empty range indices of newly created loops.

Definition at line 424 of file Transforms.h.

◆ OptimizeCopyFn

using mlir::linalg::OptimizeCopyFn = typedef std::function<LogicalResult(PatternRewriter &, tensor::PadOp, Value)>

Definition at line 1038 of file Transforms.h.

◆ ProcInfoCallBackFn

using mlir::linalg::ProcInfoCallBackFn = typedef std::function<SmallVector<ProcInfo>( OpBuilder &b, Location loc, ArrayRef<Range> parallelLoopRanges)>

Definition at line 366 of file Utils.h.

◆ TileSizeComputationFunction

using mlir::linalg::TileSizeComputationFunction = typedef std::function<SmallVector<Value, 4>(OpBuilder &, Operation *)>

Definition at line 413 of file Transforms.h.

Enumeration Type Documentation

◆ DistributionMethod

enum mlir::linalg::DistributionMethod

strong

Scheme used to distribute loops to processors.

Enumerator
Cyclic	Cyclic distribution where no assumption is made about the dynamic relationship between number of processors and number of iterations of the distributed loop. Distributes the following loop scf.parallel (iv) = (lb) to (ub) step (step) to scf.parallel(iv)= (lb + procId * step) to (ub) step (step * nprocs)
CyclicNumProcsGeNumIters	Cyclic distribution where the number of processors can be assumed to be more than or equal to the number of iterations of the distributed loop. In such cases, a simple in-bounds check is enough (instead of materializing a loop). Distributes the following loop scf.parallel (iv) = (lb) to (ub) step (step) to iv = lb + procId * step cond = arith.cmpi "slt", iv, ub scf.if cond { ... }
CyclicNumProcsEqNumIters	Cyclic distribution where the number of processors can be assumed to be equal to the number of iterations of the distributed loop. In such cases, no bounds check is needed. Distributes the following loop scf.parallel (iv) = (lb) to (ub) step (step) to iv = lb + procId * step
None	No Distribution.

Definition at line 315 of file Utils.h.

◆ LinalgLoweringType

enum mlir::linalg::LinalgLoweringType

strong

Linalg lowering patterns.

Apply the linalgLowerOpToLoops transformation as a pattern. filter controls LinalgTransformMarker matching and update when specified. See linalgLowerOpToLoops for more details.

Enumerator
LibraryCall
Loops
AffineLoops
ParallelLoops

Definition at line 939 of file Transforms.h.

◆ LinalgTilingLoopType

enum mlir::linalg::LinalgTilingLoopType

strong

The type of loops to be generated during tiling.

Enumerator
Loops
AffineLoops
ParallelLoops

Definition at line 149 of file Utils.h.

Function Documentation

◆ allIndexingsAreProjectedPermutation()

bool mlir::linalg::allIndexingsAreProjectedPermutation ( LinalgOp op )

Check if all indexing maps are projected permutations.

Definition at line 154 of file Utils.cpp.

Referenced by isElementwise(), and vectorizeStaticLinalgOpPrecondition().

◆ applyStagedPatterns()

LogicalResult mlir::linalg::applyStagedPatterns	(	Operation *	op,
		ArrayRef< FrozenRewritePatternSet >	stage1Patterns,
		const FrozenRewritePatternSet &	stage2Patterns,
		function_ref< LogicalResult(Operation *)>	stage3Lambda = `nullptr`
	)

Helper function to allow applying rewrite patterns, interleaved with more global transformations, in a staged fashion:

the first stage consists of a list of FrozenRewritePatternSet. Each FrozenRewritePatternSet in this list is applied once, in order.
the second stage consists of a single RewritePattern that is applied greedily until convergence.
the third stage consists of applying a lambda, generally used for non-local transformation effects. This allows creating custom fused transformations where patterns can be ordered and applied at a finer granularity than a sequence of traditional compiler passes.

Definition at line 569 of file Transforms.cpp.

References mlir::applyPatternsAndFoldGreedily(), DBGS, mlir::failed(), mlir::failure(), and mlir::success().

◆ areElementwiseOpsFusable()

bool mlir::linalg::areElementwiseOpsFusable ( OpOperand * fusedOperand )

Return true if two linalg.generic operations with producer/consumer relationship through fusedOperand can be fused using elementwise op fusion.

Conditions for elementwise fusion of generic operations.

Definition at line 74 of file ElementwiseOpFusion.cpp.

References mlir::IROperand< DerivedT, IRValueT >::get(), mlir::Value::getDefiningOp(), getIndexingMapOfProducerOperandsInCoordinatesOfFusedOp(), mlir::AffineMap::getNumResults(), mlir::detail::IROperandBase::getOwner(), and mlir::AffineMap::isPermutation().

Referenced by fuseElementwiseOps().

◆ computeAllSliceParameters()

SmallVector< Optional< SliceParameters > > mlir::linalg::computeAllSliceParameters	(	OpBuilder &	builder,
		Location	loc,
		LinalgOp	linalgOp,
		ValueRange	valuesToTile,
		ArrayRef< OpFoldResult >	ivs,
		ArrayRef< OpFoldResult >	tileSizes,
		ArrayRef< OpFoldResult >	sizeBounds,
		bool	omitPartialTileCheck
	)

Computes SliceParamaters for all valuesToTile of the given linalgOp, assuming linalgOp is being fused into a loop nest.

Calls computeSliceParameters for every individual value.

Note that a constant zero in tileSizes means no tiling at that implicit loop. The number of non-zero values in tileSizes should be equal to the number of values in ivs.

Some of the valuesToTile won't be affected by tiling. For these values, llvm::None will be returned.

Definition at line 943 of file Utils.cpp.

References computeSliceParameters(), computeTileOffsets(), computeTileSizes(), isTiled(), isZero(), and mlir::presburger::None.

Referenced by makeTiledShapes().

◆ computeMultiTileSizes()

FailureOr< MultiSizeSpecification > mlir::linalg::computeMultiTileSizes	(	OpBuilder &	builder,
		LinalgOp	op,
		unsigned	dimension,
		OpFoldResult	targetSize,
		OpFoldResult	divisor,
		bool	emitAssertions = `true`
	)

Emits the IR computing the multi-sized tiling specification with two tile sizes not exceeding targetSize, each divisible by sizeDivisor, such that there exist numbers of tiles with these sizes that fully cover the given iteration space dimension of the structured op.

The computation is as follows:

b = originalTripCount floordiv sizeDivisor t = (targetSize + sizeDivisor - 1) floordiv sizeDivisor d = (b + t - 1) floordiv t s = (b floordiv d) * sizeDivisor v = b % d u = d - v

where the tile sizes are s and s + sizeDivisor, and the numbers of the corresponding tiles are u and v, respectively. Alternatively,

s * u + (s + sizeDivisor) * v == original size, where s mod sizeDivisor = 0.

Expects all values to be positive. In some cases with the target tile size sufficiently close to the dimension shape and non-unit divisor, it is impossible to compute such sizes. If emitAssertion is set, also emit the assertion that size computation succeeded.

Returns the specification consisting of both tile values and the number of tiles of each size.

Definition at line 117 of file Tiling.cpp.

References mlir::ImplicitLocOpBuilder::create(), emitIsPositiveIndexAssertion(), mlir::failure(), mlir::floorDiv(), mlir::Builder::getAffineSymbolExpr(), mlir::ImplicitLocOpBuilder::getLoc(), mlir::Builder::getStringAttr(), mlir::getValueOrCreateConstantIndexOp(), mlir::linalg::MultiSizeSpecification::lowTileSize, mlir::makeComposedAffineApply(), and mlir::makeComposedFoldedMultiResultAffineApply().

◆ computeSliceParameters()

SliceParameters mlir::linalg::computeSliceParameters	(	OpBuilder &	builder,
		Location	loc,
		Value	valueToTile,
		ArrayRef< OpFoldResult >	tileSizes,
		AffineMap	map,
		ArrayRef< OpFoldResult >	lbs,
		ArrayRef< OpFoldResult >	ubs,
		ArrayRef< OpFoldResult >	subShapeSizes,
		bool	omitPartialTileCheck
	)

Computes SliceParameters for a single valueToTile assuming that its user is being tiled with the given loop bounds lbs and ubs and the tile sizes tileSizes.

omitPartialTileCheck controls whether to omit the partial/boundary tile condition check in cases where we statically know that it is unnecessary.

Definition at line 770 of file Utils.cpp.

References mlir::bindDims(), createFoldedDimOp(), mlir::Type::dyn_cast(), mlir::getAffineSymbolExpr(), mlir::getConstantIntValue(), mlir::Builder::getContext(), mlir::Builder::getIndexAttr(), mlir::AffineMap::getSubMap(), mlir::Value::getType(), mlir::AffineMap::inferFromExprList(), isTiled(), mlir::makeComposedFoldedAffineApply(), mlir::makeComposedFoldedAffineMin(), mlir::linalg::SliceParameters::offsets, mlir::linalg::SliceParameters::sizes, and mlir::linalg::SliceParameters::strides.

Referenced by computeAllSliceParameters(), inlinePayload(), and makeTiledShape().

◆ computeTileOffsets()

SmallVector< OpFoldResult > mlir::linalg::computeTileOffsets	(	OpBuilder &	b,
		Location	loc,
		ArrayRef< OpFoldResult >	ivs,
		ArrayRef< OpFoldResult >	tileSizes
	)

Computes tile offsets, given a list of loop ivs and tileSizes.

In case a tile size is zero (i.e., no tiling), the corresponding offset is also zero.

Definition at line 877 of file Utils.cpp.

References mlir::Builder::getIndexAttr(), isTiled(), and isZero().

Referenced by computeAllSliceParameters(), and tilePadOp().

◆ computeTileSizes()

SmallVector< OpFoldResult > mlir::linalg::computeTileSizes	(	OpBuilder &	b,
		Location	loc,
		ArrayRef< OpFoldResult >	tileSizes,
		ArrayRef< OpFoldResult >	sizeBounds
	)

Computes tile sizes, given a list of tileSizes and dimension sizes (sizeBounds).

In case a tile size is zero (i.e., no tiling), the corresponding result size is the corresponding value from sizeBounds. Note: The returned tile sizes are closed intervals.

Definition at line 891 of file Utils.cpp.

References mlir::getAffineDimExpr(), mlir::Builder::getContext(), isTiled(), isZero(), and mlir::makeComposedFoldedAffineApply().

Referenced by computeAllSliceParameters(), and tilePadOp().

◆ concat()

SmallVector< AffineExpr, 4 > mlir::linalg::concat	(	ArrayRef< AffineExpr >	a,
		ArrayRef< AffineExpr >	b
	)

Return the vector that is the concatenation of a and b.

Definition at line 1512 of file LinalgOps.cpp.

Referenced by convertOmpThreadprivate(), and mlir::presburger::Simplex::makeProduct().

◆ createFoldedDimOp()

OpFoldResult mlir::linalg::createFoldedDimOp	(	OpBuilder &	b,
		Location	loc,
		Value	source,
		int64_t	dim
	)

Definition at line 220 of file Utils.cpp.

References mlir::Type::cast(), createOrFoldDimOp(), mlir::Builder::getIndexAttr(), and mlir::Value::getType().

Referenced by fuse().

◆ createOrFoldDimOp()

Value mlir::linalg::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 212 of file Utils.cpp.

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

Referenced by createFoldedDimOp(), createInBoundsCond(), createSubViewIntersection(), genBuffers(), getResultsPositionInLoopsToShapeMap(), mlir::sparse_tensor::SparseTensorLoopEmitter::initializeLoopEmit(), and MaterializeTransferMask< ConcreteOp >::matchAndRewrite().

◆ extractOrIdentityMap()

AffineMap mlir::linalg::extractOrIdentityMap	(	Optional< AffineMap >	maybeMap,
		unsigned	rank,
		MLIRContext *	context
	)

Returns maybeMap.get() if maybeMap is set, otherwise returns the symbol-less identity map of rank.

Definition at line 1492 of file LinalgOps.cpp.

References mlir::AffineMap::get(), and mlir::AffineMap::getMultiDimIdentityMap().

◆ findAllFusableDependences()

FusableOpDependencesTy mlir::linalg::findAllFusableDependences	(	ArrayRef< LinalgOp >	ops,
		const LinalgDependenceGraph &	dependenceGraph
	)

◆ fuseElementwiseOps()

FailureOr< Operation * > mlir::linalg::fuseElementwiseOps	(	RewriterBase &	rewriter,
		OpOperand *	fusedOperand
	)

Fuse two linalg.generic operations that have a producer-consumer relationship captured through fusedOperand.

The method expects that areElementwiseOpsFusable returns true for the given fusedOperand.

Definition at line 262 of file ElementwiseOpFusion.cpp.

References areElementwiseOpsFusable(), mlir::Value::cast(), mlir::AffineMap::compose(), mlir::OpBuilder::create(), mlir::RewriterBase::eraseOp(), mlir::failure(), generateFusedElementwiseOpRegion(), mlir::IROperand< DerivedT, IRValueT >::get(), mlir::Builder::getAffineMapArrayAttr(), getIndexingMapOfProducerOperandsInCoordinatesOfFusedOp(), mlir::detail::IROperandBase::getOwner(), mlir::inversePermutation(), mlir::RewriterBase::notifyMatchFailure(), mlir::RewriterBase::replaceOp(), mlir::succeeded(), and mlir::success().

◆ fuseProducerOfBuffer()

FailureOr< FusionInfo > mlir::linalg::fuseProducerOfBuffer	(	OpBuilder &	b,
		OpOperand &	consumerOpOperand,
		const LinalgDependenceGraph &	graph
	)

Fuses producer into consumer if the producer is structurally feasible and the fusion would not violate dependencies.

Implements the fusion part of the "tileAndFuse on buffers" transformation and thus requires the consumerOpOperand to be a subview op (generally obtained by applying the tiling transformation).

Definition at line 331 of file Fusion.cpp.

References mlir::failure(), findFusableProducer(), fuse(), mlir::IROperand< DerivedT, IRValueT >::get(), mlir::Value::getDefiningOp(), mlir::detail::IROperandBase::getOwner(), mlir::Value::getParentBlock(), and mlir::OpBuilder::setInsertionPoint().

◆ fuseProducerOfTensor() [1/2]

FailureOr< FusionInfo > mlir::linalg::fuseProducerOfTensor	(	OpBuilder &	b,
		OpOperand &	consumerOpOperand
	)

Tensor counterpart of fuseProducerOfBuffer.

This implements the fusion part of the "tileAndFuse on tensors" transformation and thus requires the consumerOpOperand to be a extract_slice op (generally obtained by applying the tiling transformation).

Definition at line 401 of file Fusion.cpp.

References mlir::failure(), mlir::IROperand< DerivedT, IRValueT >::get(), and getProducerOfTensor().

◆ fuseProducerOfTensor() [2/2]

FailureOr< FusionInfo > mlir::linalg::fuseProducerOfTensor	(	OpBuilder &	b,
		OpResult	producerOpResult,
		OpOperand &	consumerOpOperand
	)

Tensor counterpart of fuseProducerOfBuffer.

This implements the fusion part of the "tileAndFuse on tensors" transformation and thus requires the consumerOpOperand to be a extract_slice op (generally obtained by applying the tiling transformation). Assumes producerOfTensor is a Linalg op that produces consumerOpOperand.

Definition at line 413 of file Fusion.cpp.

References mlir::OpBuilder::create(), mlir::failure(), fuse(), mlir::IROperand< DerivedT, IRValueT >::get(), mlir::Value::getDefiningOp(), mlir::detail::IROperandBase::getOwner(), mlir::OpResult::getOwner(), mlir::Value::getParentBlock(), mlir::OpResult::getResultNumber(), mlir::Value::getType(), mlir::IROperand< DerivedT, IRValueT >::set(), and mlir::OpBuilder::setInsertionPoint().

◆ generalizeNamedOp()

FailureOr< GenericOp > mlir::linalg::generalizeNamedOp	(	RewriterBase &	rewriter,
		LinalgOp	namedOp
	)

Create a GenericOp from the given named operation namedOp and replace namedOp.

Return failure if namedOp is a GenericOp or misses a region builder.

Definition at line 48 of file Generalization.cpp.

References mlir::applyPatternsAndFoldGreedily(), mlir::OpBuilder::create(), mlir::failed(), generalizeNamedOpPrecondition(), mlir::RewriterBase::inlineRegionBefore(), mlir::RewriterBase::notifyMatchFailure(), populateLinalgNamedOpsGeneralizationPatterns(), and mlir::RewriterBase::replaceOp().

Referenced by mlir::linalg::LinalgGeneralizationPattern::returningMatchAndRewrite().

◆ generateLibraryCallName()

std::string mlir::linalg::generateLibraryCallName ( Operation * op )

Returns the name mangled library call name to disambiguate between different overloads at the C level.

The name mangling scheme is basic and uses MLIR type names:

form a string which is the concatenation of the linalg op name with all the operand type names, separate by underscores;
drop the linalg. prefix, and the <, >, ? symbols from the type. Assumes op is a LinalgOp.

Examples:

linalg.fill(f, A) : f32, memref<f32> name mangles into linalg_fill_f32_viewf32
linalg.dot A, B, C : (memref<?xf32, stride_specification>, memref<?xf32, stride_specification>, memref<f32>) name mangles into linalg_dot_viewxf32_viewxf32_viewf32
linalg.matmul(...) : memref<?x?xf32, stride_specification>, memref<?x?xf32, stride_specification>, memref<?x?xf32, stride_specification> name mangles into linalg_matmul_viewxxf32_viewxxf32_viewxxf32

Definition at line 1541 of file LinalgOps.cpp.

◆ generateParallelLoopNest()

static void mlir::linalg::generateParallelLoopNest	(	OpBuilder &	b,
		Location	loc,
		ValueRange	lbs,
		ValueRange	ubs,
		ValueRange	steps,
		ArrayRef< StringRef >	iteratorTypes,
		ArrayRef< linalg::ProcInfo >	procInfo,
		function_ref< void(OpBuilder &, Location, ValueRange)>	bodyBuilderFn,
		SmallVectorImpl< Value > &	ivStorage
	)

static

Generates a loop nest consisting of scf.parallel and scf.for, depending on the `iteratorTypes.

` Consecutive parallel loops create a single scf.parallel operation; each sequential loop creates a new scf.for operation. The body of the innermost loop is populated by bodyBuilderFn that accepts a range of induction variables for all loops. ivStorage is used to store the partial list of induction variables.

Definition at line 576 of file Utils.cpp.

References mlir::ArithBuilder::_and(), mlir::scf::buildLoopNest(), mlir::OpBuilder::create(), mlir::linalg::ProcInfo::distributionMethod, isParallelIterator(), mlir::presburger::None, and mlir::ArithBuilder::slt().

Referenced by mlir::linalg::GenerateLoopNest< LoopTy >::doit().

◆ getCombinerOpKind()

llvm::Optional< vector::CombiningKind > mlir::linalg::getCombinerOpKind ( Operation * combinerOp )

Return vector::CombiningKind for the given op.

Definition at line 122 of file Vectorization.cpp.

References None.

Referenced by bindShapeDims(), buildMultiDimReduce(), and reductionPreconditions().

◆ getConstantUpperBoundForIndex()

FailureOr< int64_t > mlir::linalg::getConstantUpperBoundForIndex ( Value value )

Returns a constant upper bound for the result value of an index computation.

Calls getUpperBoundForIndex and returns a constant upper bound if the result of boundMap is a constant expression and failure otherwise.

Example:

%0 = affine.min affine.map<(d0) -> (40, d0)> (%d0)

%1 = affine.apply affine.map<(d0) -> (d0 + 2)> (%0)

getConstantUpperBoundForIndex(%1) returns 42 (boundsMap = affine.map<() -> (42)>)

Definition at line 340 of file Utils.cpp.

References mlir::failure(), mlir::AffineMap::getResults(), and getUpperBoundForIndex().

Referenced by padOperandToSmallestStaticBoundingBox(), and promoteSubviewAsNewBuffer().

◆ getDynOperands()

SmallVector< Value, 4 > mlir::linalg::getDynOperands	(	Location	loc,
		Value	val,
		OpBuilder &	b
	)

Given an operation, retrieves the value of each dynamic dimension through constructing the necessary DimOp operators.

Definition at line 230 of file Utils.cpp.

References mlir::Type::cast(), createOrFoldDimOp(), mlir::detail::enumerate(), and mlir::Value::getType().

◆ getLinalgTilingCanonicalizationPatterns()

RewritePatternSet mlir::linalg::getLinalgTilingCanonicalizationPatterns ( MLIRContext * ctx )

Canonicalization patterns relevant to apply after tiling patterns.

These are applied automatically by the tiling pass but need to be applied manually when tiling is called programmatically.

Definition at line 701 of file Tiling.cpp.

References populateLinalgTilingCanonicalizationPatterns().

Referenced by applyExtractSliceOfPadTensorSwapPattern(), and mlir::linalg::LinalgTilingOptions::setPeeledLoops().

◆ getPrunedAttributeList()

template<typename OpTy >

SmallVector<NamedAttribute> mlir::linalg::getPrunedAttributeList ( OpTy op )

Returns an attribute list that excludes pre-defined attributes.

Definition at line 500 of file Utils.h.

Referenced by matchAndReplaceDepthwiseConv().

◆ getReassociationMapForFoldingUnitDims()

Optional< SmallVector< ReassociationIndices > > mlir::linalg::getReassociationMapForFoldingUnitDims ( ArrayRef< OpFoldResult > mixedSizes )

Get the reassociation maps to fold the result of a extract_slice (or source of a insert_slice) operation with given offsets, and sizes to its rank-reduced version.

This is only done for the cases where the size is 1 and offset is 0. Strictly speaking the offset 0 is not required in general, but non-zero offsets are not handled by SPIR-V backend at this point (and potentially cannot be handled).

Definition at line 1047 of file Utils.cpp.

References mlir::detail::enumerate().

◆ getTensorOutputTypes()

SmallVector< Type > mlir::linalg::getTensorOutputTypes	(	LinalgOp	op,
		ValueRange	operands
	)

Returns the list of tensor output types produced when the given structured operation op is applied to the given operands.

Note that operands are not necessarily the actual operands of op.

Definition at line 907 of file Utils.cpp.

References mlir::ValueRange::getType().

◆ getUpperBoundForIndex()

void mlir::linalg::getUpperBoundForIndex	(	Value	value,
		AffineMap &	boundMap,
		SmallVectorImpl< Value > &	boundOperands,
		bool	constantRequired = `false`
	)

Computes an upper bound for the result value of an index computation.

Translates AffineMinOps and AffineApplyOps along the use-def chains of the index computation to affine constraints and projects out intermediate values. The method sets boundMap to an affine map that given boundOperands evaluates to an upper bound for the index computation.

If constantRequired is true, only returns the constant bounds (potentially over-approximating) and fails when not possible.

Example:

%dim0 = dim %tensor, %c0
%dim1 = dim %tensor, %c1
%0 = affine.min affine.map<(d0) -> (40, d0)> (%dim0)
%1 = affine.apply affine.map<(d0, d1) -> (d0 + d1)> (%0, %dim1)

getUpperBoundForIndex(%1, boundMap, boundOperands) set the output parameters to:

boundMap = affine.map<(d0) -> (d0 + 40)>
boundOperands = [dim1]

Definition at line 240 of file Utils.cpp.

References mlir::FlatAffineValueConstraints::addBound(), mlir::FlatAffineValueConstraints::appendDimVar(), mlir::canonicalizeMapAndOperands(), mlir::FlatAffineValueConstraints::computeAlignedMap(), mlir::FlatAffineValueConstraints::containsVar(), mlir::presburger::IntegerRelation::EQ, mlir::failed(), mlir::FlatAffineValueConstraints::findVar(), mlir::FlatAffineValueConstraints::getAllValues(), mlir::getBackwardSlice(), mlir::presburger::IntegerRelation::getConstantBound64(), mlir::AffineMap::getConstantMap(), mlir::Value::getContext(), mlir::Value::getDefiningOp(), mlir::AffineMap::getMultiDimIdentityMap(), mlir::presburger::IntegerRelation::getNumDimVars(), mlir::Operation::getOperands(), mlir::Operation::getResults(), mlir::FlatAffineValueConstraints::getSliceBounds(), mlir::Value::getType(), mlir::Type::isIndex(), mlir::presburger::IntegerRelation::UB, and value.

Referenced by getConstantUpperBoundForIndex(), and HoistingAnalysis::getPackedTensorSizes().

◆ hasOnlyScalarElementwiseOp()

bool mlir::linalg::hasOnlyScalarElementwiseOp ( Region & r )

Detect whether r has only ConstantOp, ElementwiseMappable and YieldOp.

Definition at line 160 of file Utils.cpp.

References mlir::Region::front(), and mlir::OpTrait::hasElementwiseMappableTraits().

Referenced by isElementwise().

◆ hoistPaddingOnTensors()

FailureOr< Value > mlir::linalg::hoistPaddingOnTensors	(	tensor::PadOp	opToHoist,
		int	numLoops,
		ArrayRef< int64_t >	transposeVector,
		tensor::PadOp &	hoistedOp,
		SmallVectorImpl< GenericOp > &	transposeOps
	)

Mechanically hoist padding operations on tensors by numLoops into a new, generally larger tensor.

This achieves packing of multiple padding ops into a larger tensor. On success, opToHoist is replaced by the cloned version in the packing loop so the caller can continue reasoning about the padding operation. If transposeVector is non-empty, hoist padding introduces a GenericOp to transpose the padded tensor before inserting it into the packed tensor. A transposeVector can change the storage order of the padded tensor but does not change the order of the pack or compute loops.

Example in pseudo-mlir:

If hoistPaddingOnTensors is called with nLoops = 2 on the following IR.

scf.for (%i, %j, %k)
  %st0 = tensor.extract_slice f(%i, %k) : ... to tensor<?x?xf32>
  %0 = tensor.pad %st0 low[0, 0] high[...] {
  ^bb0( ... ):
    linalg.yield %pad
  } : tensor<?x?xf32> to tensor<4x8xf32>
  compute(%0)

IR resembling the following is produced:

scf.for (%i) {
  %packed_init = tensor.empty range(%j) : tensor<?x4x8xf32>
  %packed = scf.for (%k) iter_args(%p : %packed_init) {
    %st0 = tensor.extract_slice f(%i, %k) : ... to tensor<?x?xf32>
    %0 = tensor.pad %st0 low[0, 0] high[...] {
    ^bb0( ... ):
      linalg.yield %pad
    } : tensor<?x?xf32> to tensor<4x8xf32>
    %1 = tensor.insert_slice %0 ...
        : tensor<4x8xf32> to tensor<?x4x8xf32>
    scf.yield %1: tensor<?x4x8xf32>
  } -> tensor<?x4x8xf32>
  scf.for (%j, %k) {
    %st0 = tensor.extract_slice %packed [%k, 0, 0][1, 4, 8][1, 1, 1] :
             tensor<?x4x8xf32> to tensor<4x8xf32>
    compute(%st0)
  }
}

Definition at line 397 of file HoistPadding.cpp.

References HoistingAnalysis::backwardSlice, buildLoopIterationCount(), computeTransposedType(), DBGS, mlir::failed(), mlir::failure(), mlir::scf::getForInductionVarOwner(), HoistingAnalysis::getPackedTensorSizes(), HoistingAnalysis::isValid(), mlir::BlockAndValueMapping::lookup(), mlir::BlockAndValueMapping::lookupOrDefault(), makeTransposeOp(), mlir::BlockAndValueMapping::map(), HoistingAnalysis::outermostEnclosingForOp, and HoistingAnalysis::packingLoops.

Referenced by mlir::linalg::LinalgPaddingPattern::returningMatchAndRewrite().

◆ hoistRedundantVectorTransfers()

void mlir::linalg::hoistRedundantVectorTransfers ( func::FuncOp func )

Hoist vector.transfer_read/vector.transfer_write on buffers pairs out of immediately enclosing scf::ForOp iteratively, if the following conditions are true:

The two ops access the same memref with the same indices.
All operands are invariant under the enclosing scf::ForOp.
No uses of the memref either dominate the transfer_read or are dominated by the transfer_write (i.e. no aliasing between the write and the read across the loop) To improve hoisting opportunities, call the moveLoopInvariantCode helper function on the candidate loop above which to hoist. Hoisting the transfers results in scf::ForOp yielding the value that originally transited through memory.

Definition at line 413 of file Hoisting.cpp.

References mlir::WalkResult::advance(), DBGS, mlir::getForwardSlice(), mlir::WalkResult::interrupt(), mlir::vector::isDisjointTransferSet(), mlir::moveLoopInvariantCode(), mlir::DominanceInfo::properlyDominates(), and mlir::replaceLoopWithNewYields().

◆ hoistRedundantVectorTransfersOnTensor()

void mlir::linalg::hoistRedundantVectorTransfersOnTensor ( func::FuncOp func )

Same behavior as hoistRedundantVectorTransfers but works on tensors instead of buffers.

Definition at line 361 of file Hoisting.cpp.

References mlir::WalkResult::advance(), mlir::applyPatternsAndFoldGreedily(), DBGS, mlir::detail::enumerate(), findMatchingTransferRead(), getLoopInvariantTransferWriteOpDefining(), mlir::Operation::getOpOperand(), hoistReadWrite(), mlir::WalkResult::interrupt(), and tensorChunkAccessedByUnknownOp().

◆ insertSlicesBack()

SmallVector< Value > mlir::linalg::insertSlicesBack	(	OpBuilder &	builder,
		Location	loc,
		LinalgOp	op,
		ValueRange	operands,
		ValueRange	results
	)

Creates insert_slice ops that insert results back into larger tensors they were originally extracted from with extract_slice before being passed as operands to the given structured operation op or its clone.

Note that operands are not necessarily the actual operands of op, the operation serves only as metadata container for operand types and positions.

Definition at line 916 of file Utils.cpp.

References mlir::OpBuilder::create(), and mlir::Value::getDefiningOp().

◆ interchangeGenericOp()

FailureOr< GenericOp > mlir::linalg::interchangeGenericOp	(	RewriterBase &	rewriter,
		GenericOp	genericOp,
		ArrayRef< unsigned >	interchangeVector
	)

Interchange the iterator_types and iterator_maps dimensions and adapts the index accesses of op.

This is an in-place transformation controlled by interchangeVector. An empty vector is interpreted as the identity permutation and the transformation returns early.

E.g. the permutation (i,j,k) -> (j,k,i) is expressed with interchangeVector = [1,2,0]. All values in interchangeVector must be integers, in the range 0..op.rank without duplications (i.e. [1,1,2] is an invalid permutation).

Return failure if the permutation is not valid.

Definition at line 51 of file Interchange.cpp.

References mlir::applyPermutationToVector(), mlir::AffineMap::compose(), mlir::OpBuilder::create(), mlir::failed(), mlir::RewriterBase::finalizeRootUpdate(), mlir::Builder::getAffineMapArrayAttr(), mlir::getIndexingMapsAttrName(), mlir::getIteratorTypesAttrName(), mlir::AffineMap::getPermutationMap(), mlir::AffineMap::getSubMap(), interchangeGenericOpPrecondition(), mlir::inversePermutation(), mlir::AffineMap::isEmpty(), mlir::RewriterBase::notifyMatchFailure(), mlir::RewriterBase::replaceOpWithNewOp(), mlir::OpBuilder::setInsertionPoint(), and mlir::RewriterBase::startRootUpdate().

◆ isaContractionOpInterface()

bool mlir::linalg::isaContractionOpInterface ( LinalgOp linalgOp )

Checks whether linalgOp conforms to ContractionOpInterface.

Definition at line 140 of file LinalgInterfaces.cpp.

References isContractionInterfaceImpl(), and Success.

◆ isElementwise()

bool mlir::linalg::isElementwise ( LinalgOp op )

Check if a LinalgOp is an element-wise operation.

Definition at line 174 of file Utils.cpp.

References allIndexingsAreProjectedPermutation(), and hasOnlyScalarElementwiseOp().

Referenced by vectorizeStaticLinalgOpPrecondition().

◆ isFusableInto()

bool mlir::linalg::isFusableInto	(	const LinalgDependenceGraph &	graph,
		LinalgOp	consumer,
		Value	consumedView,
		LinalgOp	producer
	)

Checks whether fusing the specific producer of the consumedView is feasible.

This checks producer is the last write of consumedView and that no interleaved dependence would be violated (RAW, WAR or WAW).

Definition at line 250 of file Fusion.cpp.

References mlir::linalg::LinalgDependenceGraph::findCoveringDependences(), and isProducerLastWriteOfView().

Referenced by findFusableProducer().

◆ isParallelIterator()

bool mlir::linalg::isParallelIterator ( StringRef iteratorType )

Check if iterator type has "parallel" semantics.

Definition at line 202 of file Utils.cpp.

References mlir::getParallelIteratorTypeName().

Referenced by generateParallelLoopNest(), getCollapsableIterationSpaceDims(), tileConsumerAndFuseProducers(), and tileLinalgOpImpl().

◆ isPermutation()

bool mlir::linalg::isPermutation ( ArrayRef< int64_t > permutation )

Check if permutation is a permutation of the range [0, permutation.size()).

Definition at line 189 of file Utils.cpp.

Referenced by computeTransposedType(), mlir::AffineMap::getPermutedPosition(), mlir::AffineMap::insertResult(), makeTransposeOp(), mlir::linalg::LinalgTileAndFuseTensorOpsPattern::returningMatchAndRewrite(), and tileConsumerAndFuseProducers().

◆ isProducerLastWriteOfView()

bool mlir::linalg::isProducerLastWriteOfView	(	const LinalgDependenceGraph &	graph,
		LinalgOp	consumer,
		Value	consumedView,
		LinalgOp	producer
	)

Checks whether the specific producer is the last write to exactly the whole consumedView.

This checks structural dominance, that the dependence is a RAW without any interleaved write to any piece of consumedView.

Definition at line 226 of file Fusion.cpp.

References mlir::linalg::LinalgDependenceGraph::findCoveringWrites(), and isStructurallyFusableProducer().

Referenced by isFusableInto().

◆ isReductionIterator()

bool mlir::linalg::isReductionIterator ( StringRef iteratorType )

Check if iterator type has "reduction" semantics.

Definition at line 206 of file Utils.cpp.

References mlir::getReductionIteratorTypeName().

Referenced by genFor(), getCollapsableIterationSpaceDims(), getReductionMask(), reductionPreconditions(), and topSortOptimal().

◆ linalgOpToAffineLoops()

FailureOr< LinalgLoops > mlir::linalg::linalgOpToAffineLoops	(	PatternRewriter &	rewriter,
		LinalgOp	linalgOp
	)

Emit a loop nest of affine.for with the proper body for linalgOp.

Emits a loop nest of affine.for with the proper body for linalgOp.

Definition at line 366 of file Loops.cpp.

Referenced by mlir::linalg::LinalgLoweringPattern< OpTy >::matchAndRewrite().

◆ linalgOpToLoops()

FailureOr< LinalgLoops > mlir::linalg::linalgOpToLoops	(	PatternRewriter &	rewriter,
		LinalgOp	linalgOp
	)

Emit a loop nest of scf.for with the proper body for linalgOp.

Emits a loop nest of scf.for with the proper body for linalgOp.

Definition at line 372 of file Loops.cpp.

Referenced by mlir::linalg::LinalgLoweringPattern< OpTy >::matchAndRewrite().

◆ linalgOpToParallelLoops()

FailureOr< LinalgLoops > mlir::linalg::linalgOpToParallelLoops	(	PatternRewriter &	rewriter,
		LinalgOp	linalgOp
	)

Emit a loop nest of scf.parallel with the proper body for linalgOp.

Emits a loop nest of scf.parallel with the proper body for linalgOp.

Definition at line 379 of file Loops.cpp.

Referenced by mlir::linalg::LinalgLoweringPattern< OpTy >::matchAndRewrite().

◆ makeAffineDimExprs()

SmallVector< AffineExpr, 4 > mlir::linalg::makeAffineDimExprs	(	unsigned	num,
		unsigned &	startIdx,
		MLIRContext *	context
	)

Returns num AffineDimExpr dimensions at positions [startIdx, startIdx + num) and increments startIdx to startIdx + num.

Definition at line 1503 of file LinalgOps.cpp.

◆ makeComposedPadHighOp()

Value mlir::linalg::makeComposedPadHighOp	(	OpBuilder &	b,
		Location	loc,
		RankedTensorType	type,
		Value	source,
		Value	pad,
		bool	nofold
	)

Create a tensor::PadOp that pads source to the size of the statically sized type whose static sizes are assumed to be greater than the dynamic source size.

The padding introduces trailing pad values until the target size is met. If source is defined by one or more LinalgOps that have been padded with the same value and sizes, return their padded result instead of creating a tensor::PadOp.

Example:

%0 = tensor.extract_slice %arg0 [%iv0, %iv1] [%sz0, %sz1]
%1 = tensor.pad %0 low[0, 0] high[...] { tensor.yield %cst }
%2 = linalg.matmul ins(...) outs(%1)
%3 = tensor.extract_slice %2 [0, 0] [%sz0, %sz1]

makeComposedPadHighOp(source=%3, pad=cst) returns %2 makeComposedPadHighOp(source=%3, pad=other_cst) returns %4

%4 = tensor.pad %3 low[0, 0] high[...] { tensor.yield %other_cst }

Definition at line 359 of file Utils.cpp.

References mlir::Value::cast(), mlir::tensor::createPadHighOp(), mlir::getConstantIntValue(), mlir::Value::getDefiningOp(), mlir::OpResult::getResultNumber(), mlir::isEqualConstantIntOrValue(), mlir::m_Constant(), and mlir::matchPattern().

Referenced by padOperandToSmallestStaticBoundingBox().

◆ makeMemRefCopyOp()

GenericOp mlir::linalg::makeMemRefCopyOp	(	OpBuilder &	b,
		Location	loc,
		Value	from,
		Value	to
	)

Returns GenericOp that copies an n-D memref.

Unlike the current implementation of memref::CopyOp, this op can further tile, lower to loops or vectorize.

Definition at line 458 of file Utils.cpp.

References mlir::Type::cast(), mlir::OpBuilder::create(), mlir::Builder::getContext(), mlir::AffineMap::getMultiDimIdentityMap(), mlir::getParallelIteratorTypeName(), and mlir::Value::getType().

◆ makeTiledLoopRanges()

std::tuple< SmallVector< Range, 4 >, LoopIndexToRangeIndexMap > mlir::linalg::makeTiledLoopRanges	(	RewriterBase &	b,
		Location	loc,
		AffineMap	map,
		ArrayRef< OpFoldResult >	allShapeSizes,
		ArrayRef< OpFoldResult >	allTileSizes
	)

Definition at line 56 of file Tiling.cpp.

References mlir::AffineMap::getNumResults(), isZero(), and mlir::makeComposedFoldedMultiResultAffineApply().

Referenced by tileLinalgOpImpl().

◆ makeTiledShape()

Value mlir::linalg::makeTiledShape	(	OpBuilder &	builder,
		Location	loc,
		Value	valueToTile,
		ArrayRef< OpFoldResult >	tileSizes,
		AffineMap	map,
		ArrayRef< OpFoldResult >	lbs,
		ArrayRef< OpFoldResult >	ubs,
		ArrayRef< OpFoldResult >	subShapeSizes,
		bool	omitPartialTileCheck
	)

Creates an extract_slice/subview op for a single valueToTile with builder.

This new operation extracts a tile of valueToTile, starting at offsets lbs and with sizes subShapeSizes. omitPartialTileCheck controls whether to omit the partial/boundary tile condition check in cases where we statically know that it is unnecessary.

Definition at line 758 of file Utils.cpp.

References computeSliceParameters(), and materializeTiledShape().

Referenced by tilePadOp().

◆ makeTiledShapes()

SmallVector< Value > mlir::linalg::makeTiledShapes	(	OpBuilder &	builder,
		Location	loc,
		LinalgOp	linalgOp,
		ValueRange	valuesToTile,
		ArrayRef< OpFoldResult >	ivs,
		ArrayRef< OpFoldResult >	tileSizes,
		ArrayRef< OpFoldResult >	sizeBounds,
		bool	omitPartialTileCheck
	)

Creates extract_slice/subview ops for all valuesToTile of the given linalgOp with builder, assuming linalgOp is being fused into a loop nest for tiling with the given induction variables ivs and tile sizes tileSizes.

sizeBounds are the iteration space bounds for all the implicit loops in linalgOp. omitPartialTileCheck controls whether to omit the partial/boundary tile condition check in cases where we statically know that it is unnecessary.

Note that a constant zero in tileSizes means no tiling at that implicit loop. The number of non-zero values in tileSizes should be equal to the number of values in ivs.

Definition at line 990 of file Utils.cpp.

References computeAllSliceParameters(), and materializeTiledShape().

Referenced by fuse(), getTiledProducer(), and inlinePayload().

◆ makeTransposeOp()

GenericOp mlir::linalg::makeTransposeOp	(	OpBuilder &	b,
		Location	loc,
		Value	inputTensor,
		Value	outputTensor,
		ArrayRef< int64_t >	transposeVector
	)

Returns a GenericOp that tansposes inputTensor into outputTensor using transposeVector to permute the inputTensor dimensions.

Definition at line 419 of file Utils.cpp.

References mlir::Type::cast(), mlir::OpBuilder::create(), mlir::Builder::getAffineMapArrayAttr(), mlir::Builder::getContext(), mlir::AffineMap::getMultiDimIdentityMap(), mlir::getParallelIteratorTypeName(), mlir::AffineMap::getPermutationMap(), mlir::Builder::getStrArrayAttr(), mlir::Value::getType(), mlir::inversePermutation(), isPermutation(), mlir::Region::push_back(), and mlir::OpBuilder::setInsertionPointToEnd().

Referenced by hoistPaddingOnTensors().

◆ materializeTiledShape()

static Value mlir::linalg::materializeTiledShape	(	OpBuilder &	builder,
		Location	loc,
		Value	valueToTile,
		const SliceParameters &	sliceParams
	)

static

Definition at line 737 of file Utils.cpp.

References mlir::OpBuilder::create(), mlir::Type::dyn_cast(), mlir::Value::getType(), mlir::linalg::SliceParameters::offsets, mlir::linalg::SliceParameters::sizes, and mlir::linalg::SliceParameters::strides.

Referenced by makeTiledShape(), and makeTiledShapes().

◆ offsetIndices() [1/2]

void mlir::linalg::offsetIndices	(	OpBuilder &	b,
		LinalgOp	linalgOp,
		ArrayRef< OpFoldResult >	offests
	)

Add the specified offsets to any linalg.index ops contained in the given linalgOp.

The offsets are provided in the same order as iteration space dimensions. Null offests are assumed to be zero.

Definition at line 1011 of file Utils.cpp.

Referenced by fuse(), getTiledProducer(), inlinePayload(), and transformIndexOps().

◆ offsetIndices() [2/2]

void mlir::linalg::offsetIndices	(	RewriterBase &	b,
		LinalgOp	linalgOp,
		ArrayRef< OpFoldResult >	offests
	)

Definition at line 1017 of file Utils.cpp.

References mlir::bindDims(), mlir::getAsOpFoldResult(), mlir::Builder::getContext(), mlir::detail::IROperandBase::getOwner(), mlir::getValueOrCreateConstantIndexOp(), mlir::makeComposedFoldedAffineApply(), mlir::RewriterBase::replaceOpWithIf(), and mlir::OpBuilder::setInsertionPointAfter().

◆ peelLoops()

void mlir::linalg::peelLoops	(	RewriterBase &	rewriter,
		ArrayRef< scf::ForOp >	loops
	)

Peel and canonicalize 'loops'.

Definition at line 332 of file Transforms.cpp.

References peelLoop().

◆ peelTiledLinalgOp()

void mlir::linalg::peelTiledLinalgOp	(	RewriterBase &	rewriter,
		TiledLinalgOp &	res,
		ArrayRef< int64_t >	peeledLoops,
		LinalgTilingLoopType	loopType
	)

Peel the loops of a TiledLinalgOp.

Peel loops after tiling.

Definition at line 341 of file Transforms.cpp.

◆ populateBubbleUpExtractSliceOpPatterns()

void mlir::linalg::populateBubbleUpExtractSliceOpPatterns ( RewritePatternSet & patterns )

Patterns that are used to bubble up extract slice op above linalg op.

Definition at line 134 of file BubbleUpExtractSlice.cpp.

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

◆ populateConstantFoldLinalgOperations()

void mlir::linalg::populateConstantFoldLinalgOperations	(	RewritePatternSet &	patterns,
		const ControlFusionFn &	controlFn
	)

Patterns to constant fold Linalg operations.

Definition at line 302 of file ConstantFold.cpp.

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

Referenced by populateElementwiseOpsFusionPatterns().

◆ populateConvolutionVectorizationPatterns()

void mlir::linalg::populateConvolutionVectorizationPatterns	(	RewritePatternSet &	patterns,
		PatternBenefit	benefit = `1`
	)

Populate patterns for vectorizing low-D convolution ops.

This is a step in progressive lowering for convolution ops, it assume high-D convolution ops were decomposed previously.

Definition at line 1782 of file Vectorization.cpp.

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

◆ populateDecomposeConvolutionPatterns()

void mlir::linalg::populateDecomposeConvolutionPatterns	(	RewritePatternSet &	patterns,
		const LinalgTransformationFilter &	filter = `LinalgTransformationFilter()`,
		PatternBenefit	benefit = `1`
	)

Linalg decompose convolutions patterns.

Populates patterns to decompose high-D convolution ops into low-D ones. This is a step in progressive lowering for convolution ops, afterwards we can vectorize the low-D convolution ops.

Definition at line 950 of file Transforms.cpp.

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

Referenced by mlir::linalg::LinalgLoweringPattern< OpTy >::matchAndRewrite().

◆ populateDecomposeLinalgOpsPattern()

void mlir::linalg::populateDecomposeLinalgOpsPattern ( RewritePatternSet & patterns )

Populate patterns for splitting a LinalgOp with multiple statements within its payload into multiple GenericOp that have a single statement.

Definition at line 379 of file DecomposeLinalgOps.cpp.

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

◆ populateElementwiseOpsFusionPatterns()

void mlir::linalg::populateElementwiseOpsFusionPatterns	(	RewritePatternSet &	patterns,
		const ControlFusionFn &	controlElementwiseOpFusion
	)

Patterns for fusing linalg operation on tensors.

Pattern to fuse linalg.generic -> linalg.generic operations when both operations are fusable elementwise operations.

Definition at line 1737 of file ElementwiseOpFusion.cpp.

References mlir::RewritePatternSet::add(), mlir::applyPatternsAndFoldGreedily(), mlir::Operation::getContext(), mlir::RewritePatternSet::getContext(), mlir::MLIRContext::getLoadedDialect(), mlir::Operation::getRegions(), mlir::Operation::hasOneUse(), populateConstantFoldLinalgOperations(), populateFoldReshapeOpsByExpansionPatterns(), and mlir::GreedyRewriteConfig::useTopDownTraversal.

◆ populateElementwiseToLinalgConversionPatterns()

void mlir::linalg::populateElementwiseToLinalgConversionPatterns ( RewritePatternSet & patterns )

Populate patterns that convert ElementwiseMappable ops to linalg parallel loops.

Definition at line 120 of file ElementwiseToLinalg.cpp.

References mlir::RewritePatternSet::add(), mlir::applyPartialConversion(), mlir::failed(), mlir::RewritePatternSet::getContext(), isElementwiseMappableOpOnRankedTensors(), and mlir::ConversionTarget::markUnknownOpDynamicallyLegal().

◆ populateFoldReshapeOpsByCollapsingPatterns()

void mlir::linalg::populateFoldReshapeOpsByCollapsingPatterns	(	RewritePatternSet &	patterns,
		const ControlFusionFn &	controlFoldingReshapes
	)

Patterns to fold an expanding tensor.expand_shape operation with its producer generic operation by collapsing the dimensions of the generic op.

Definition at line 1730 of file ElementwiseOpFusion.cpp.

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

◆ populateFoldReshapeOpsByExpansionPatterns()

void mlir::linalg::populateFoldReshapeOpsByExpansionPatterns	(	RewritePatternSet &	patterns,
		const ControlFusionFn &	controlFoldingReshapes
	)

Patterns to fold an expanding (collapsing) tensor_reshape operation with its producer (consumer) generic operation by expanding the dimensionality of the loop in the generic op.

Definition at line 1721 of file ElementwiseOpFusion.cpp.

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

Referenced by populateElementwiseOpsFusionPatterns().

◆ populateFoldUnitExtentDimsPatterns()

void mlir::linalg::populateFoldUnitExtentDimsPatterns ( RewritePatternSet & patterns )

Patterns to fold unit-extent dimensions in operands/results of linalg ops on tensors.

Patterns that are used to canonicalize the use of unit-extent dims for broadcasting.

Definition at line 535 of file DropUnitDims.cpp.

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

◆ populateFuseTensorPadWithProducerLinalgOpPatterns()

void mlir::linalg::populateFuseTensorPadWithProducerLinalgOpPatterns ( RewritePatternSet & patterns )

Pattern to fuse a tensor.pad operation with the producer of its source, if the producer is a linalg operation with all parallel iterator types.

Definition at line 124 of file FusePadOpWithLinalgProducer.cpp.

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

◆ populateInlineConstantOperandsPatterns()

void mlir::linalg::populateInlineConstantOperandsPatterns ( RewritePatternSet & patterns )

Patterns that are used to inline constant operands into linalg generic ops.

Definition at line 94 of file InlineScalarOperands.cpp.

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

◆ populateLinalgNamedOpConversionPatterns()

void mlir::linalg::populateLinalgNamedOpConversionPatterns ( RewritePatternSet & patterns )

Patterns to convert from one named op to another.

These can be seen as canonicalizations of named ops into another named op.

Definition at line 160 of file NamedOpConversions.cpp.

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

Referenced by matchAndReplaceDepthwiseConv().

◆ populateLinalgNamedOpsGeneralizationPatterns()

void mlir::linalg::populateLinalgNamedOpsGeneralizationPatterns	(	RewritePatternSet &	patterns,
		const LinalgTransformationFilter &	filter = `LinalgTransformationFilter()`
	)

Linalg generalization patterns.

Populates patterns with patterns to convert spec-generated named ops to linalg.generic ops.

Definition at line 88 of file Generalization.cpp.

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

Referenced by generalizeNamedOp(), and mlir::linalg::LinalgLoweringPattern< OpTy >::matchAndRewrite().

◆ populateLinalgTilingCanonicalizationPatterns()

void mlir::linalg::populateLinalgTilingCanonicalizationPatterns ( RewritePatternSet & patterns )

Definition at line 707 of file Tiling.cpp.

References mlir::RewritePatternSet::getContext().

Referenced by getLinalgTilingCanonicalizationPatterns(), and mlir::linalg::LinalgTilingOptions::setPeeledLoops().

◆ populateLinalgToStandardConversionPatterns()

void mlir::linalg::populateLinalgToStandardConversionPatterns ( RewritePatternSet & patterns )

Populate the given list with patterns that convert from Linalg to Standard.

Definition at line 127 of file LinalgToStandard.cpp.

References mlir::RewritePatternSet::add(), mlir::ConversionTarget::addLegalDialect(), mlir::ConversionTarget::addLegalOp(), mlir::applyFullConversion(), mlir::failed(), and mlir::RewritePatternSet::getContext().

◆ populatePadOpVectorizationPatterns()

void mlir::linalg::populatePadOpVectorizationPatterns	(	RewritePatternSet &	patterns,
		PatternBenefit	baseBenefit = `1`
	)

Populates patterns with patterns that vectorize tensor.pad.

These patterns are meant to apply in a complementary fashion. Benefits are used to encode a certain ordering of pattern application. To avoid scattering magic constants throughout the code base, the patterns must be added with this function. baseBenefit can be used to offset the benefit of all tensor::PadOp vectorization patterns by a certain value.

Definition at line 1087 of file Vectorization.cpp.

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

Referenced by mlir::transform::tileToForeachThreadOpImpl().

◆ populatePadTensorTilingPatterns()

void mlir::linalg::populatePadTensorTilingPatterns	(	RewritePatternSet &	patterns,
		const LinalgTilingOptions &	options
	)

Definition at line 748 of file Tiling.cpp.

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

◆ populateSparseTensorRewriting()

void mlir::linalg::populateSparseTensorRewriting ( RewritePatternSet & patterns )

Populate patterns that are only useful in the context of sparse tensors.

◆ populateSplitReductionPattern()

void mlir::linalg::populateSplitReductionPattern	(	RewritePatternSet &	patterns,
		const ControlSplitReductionFn &	controlSplitReductionFn,
		const LinalgTransformationFilter &	f = `LinalgTransformationFilter()`,
		bool	useAlloc = `false`
	)

Patterns to apply splitReduction below.

Definition at line 504 of file SplitReduction.cpp.

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

◆ populateSwapExtractSliceWithFillPatterns()

void mlir::linalg::populateSwapExtractSliceWithFillPatterns ( RewritePatternSet & patterns )

Adds patterns that waps tensor.extract_slice(linalg.fill(cst, init)) into linalg.fill(cst, tensor.extract_slice(init)).

Definition at line 38 of file SwapExtractSliceWithFillPatterns.cpp.

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

◆ promoteSubviewAsNewBuffer()

FailureOr< PromotionInfo > mlir::linalg::promoteSubviewAsNewBuffer	(	OpBuilder &	b,
		Location	loc,
		memref::SubViewOp	subView,
		const AllocBufferCallbackFn &	allocationFn,
		DataLayout &	layout
	)

Definition at line 210 of file Promotion.cpp.

References mlir::OpBuilder::create(), mlir::OpBuilder::createOrFold(), mlir::detail::enumerate(), mlir::failed(), mlir::failure(), getConstantUpperBoundForIndex(), mlir::Builder::getIndexAttr(), and mlir::getValueOrCreateConstantIndexOp().

Referenced by promoteSubViews().

◆ promoteSubViews()

FailureOr< LinalgOp > mlir::linalg::promoteSubViews	(	OpBuilder &	b,
		LinalgOp	op,
		const LinalgPromotionOptions &	options
	)

Promote the subViews into a new buffer allocated at the insertion point b.

Promotion occurs in 3 steps:

Create a new buffer for a full tile (i.e. not clipped at the boundary).
Take a full view on the buffer.
Take a partial slice of the full view in step 2. and copy into it.

Return the modified linalg op (the modification happens in place) as well as all the copy ops created.

Definition at line 389 of file Promotion.cpp.

References mlir::DataLayout::closest().

Referenced by promoteSubViews().

◆ promoteSubviewsPrecondition()

LogicalResult mlir::linalg::promoteSubviewsPrecondition	(	Operation *	op,
		LinalgPromotionOptions	options
	)

Promote memref.subviews feeding linalg-on-buffers operations.

Definition at line 367 of file Promotion.cpp.

References mlir::failure(), mlir::linalg::LinalgPromotionOptions::operandsToPromote, and mlir::success().

◆ registerBufferizableOpInterfaceExternalModels()

void mlir::linalg::registerBufferizableOpInterfaceExternalModels ( DialectRegistry & registry )

Definition at line 148 of file BufferizableOpInterfaceImpl.cpp.

References mlir::DialectRegistry::addExtension().

Referenced by mlir::registerAllDialects().

◆ registerTilingInterfaceExternalModels()

void mlir::linalg::registerTilingInterfaceExternalModels ( DialectRegistry & registry )

Definition at line 267 of file TilingInterfaceImpl.cpp.

References mlir::DialectRegistry::addExtension(), and registerAll().

Referenced by mlir::registerAllDialects().

◆ registerTransformDialectExtension()

void mlir::linalg::registerTransformDialectExtension ( DialectRegistry & registry )

Definition at line 1412 of file LinalgTransformOps.cpp.

References mlir::DialectRegistry::addExtensions().

Referenced by mlir::registerAllDialects().

◆ rewriteAsPaddedOp()

FailureOr< SmallVector< Value > > mlir::linalg::rewriteAsPaddedOp	(	OpBuilder &	b,
		LinalgOp	opToPad,
		ArrayRef< int64_t >	paddingDimensions,
		ArrayRef< Attribute >	paddingValues,
		ArrayRef< bool >	packPaddings,
		LinalgOp &	paddedOp
	)

Pad the iterator dimensions paddingDimensions of all opToPad operands to a static bounding box.

Use paddingValues and packPaddings to set padding value and nofold attribute of the created tensor::PadOps, respectively. Update paddedOp to the cloned operation with statically shaped paddingDimensions and return the extracted dynamically shaped results. If padding fails, return failure.

Definition at line 260 of file Transforms.cpp.

References mlir::Type::cast(), mlir::OpBuilder::create(), mlir::detail::enumerate(), mlir::failed(), mlir::failure(), mlir::getAsOpFoldResult(), mlir::Builder::getIndexAttr(), mlir::Value::getType(), padOperandToSmallestStaticBoundingBox(), and mlir::OpBuilder::setInsertionPointAfter().

Referenced by mlir::linalg::LinalgPaddingPattern::returningMatchAndRewrite().

◆ splitOp()

std::pair< TilingInterface, TilingInterface > mlir::linalg::splitOp	(	RewriterBase &	rewriter,
		TilingInterface	op,
		unsigned	dimension,
		OpFoldResult	splitPoint
	)

Split the given op into two parts along the given iteration space dimension at the specified splitPoint, and return the two parts.

For example, the following op:

linalg.matmul ins(%0, %1 : tensor<128x32xf32>, tensor<32x64xf32>) outs(%2 : tensor<128x64xf32>)

split along the first dimension at position 42 will result in:

%3 = tensor.extract_slice %0[0, 0][42, 32][1, 1] %4 = tensor.extract_slice %2[0, 0][42, 64][1, 1] %5 = linalg.matmul ins(%3, %1 : tensor<42x32xf32>, tensor<32x64xf32>) outs(%5 : tensor<42x64xf32>) %6 = tensor.insert_slice %5 into %2[0, 0][42, 64][1, 1]

%7 = tensor.extract_slice %0[42, 0][86, 32][1, 1] %8 = tensor.extract_slice %6[42, 0][86, 64][1, 1] %9 = linalg.matmul ins(%7, %1 : tensor<86x32xf32>, tensor<32x64xf32>) outs(%8 : tensor<86x64xf32>) tensor.insert_slice %5 into %6[42, 0][86, 64][1, 1]

Note that there is no simplification other than constant propagation applied to slice extraction and insertion.

Definition at line 67 of file Split.cpp.

References mlir::bindDims(), createSplitPart(), mlir::Builder::getContext(), mlir::AffineMap::inferFromExprList(), mlir::makeComposedFoldedAffineApply(), mlir::makeComposedFoldedAffineMin(), mlir::Range::offset, mlir::RewriterBase::replaceOp(), mlir::Range::size, and mlir::RewriterBase::updateRootInPlace().

◆ splitReduction() [1/2]

FailureOr< LinalgOp > mlir::linalg::splitReduction	(	PatternRewriter &	b,
		LinalgOp	op,
		const ControlSplitReductionFn &	controlSplitReductionFn,
		const LinalgTransformationFilter &	f,
		bool	useAlloc = `false`
	)

Apply transformation to split the single linalg op reduction into a parallel and reduction dimension.

Then create a new linalg.generic op doing the rest of the reduction. Return the new linalg op with an extra parallel dimension or failure if the transformation didn't happen. Example:

%r = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>,
                                      affine_map<(d0) -> ()>],
     iterator_types = ["reduction"]}
ins(%in : tensor<32xf32>)
outs(%out : tensor<f32>) {
^bb0(%arg1: f32, %arg2: f32):
  %y = arith.addf %arg1, %arg2 : f32
  linalg.yield %y : f32
} -> tensor<f32>

To:

 %cst = arith.constant 0.000000e+00 : f32
 %0 = tensor.expand_shape %in [[0, 1]] : tensor<32xf32> into tensor<4x8xf32>
 %1 = tensor.empty [4] : tensor<4xf32>
 %2 = linalg.fill ins(%cst : f32) outs(%1 : tensor<4xf32>) -> tensor<4xf32>
 %3 = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>,
                                       affine_map<(d0, d1) -> (d0)>],
   iterator_types = ["parallel", "reduction"]}
   ins(%0 : tensor<4x8xf32>) outs(%2 : tensor<4xf32>) {
   ^bb0(%arg3: f32, %arg5: f32):
   %5 = arith.addf %arg3, %arg4 : f32
   linalg.yield %5 : f32
 } -> tensor<4xf32>
%r = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>,
                                      affine_map<(d0) -> ()>],
  iterator_types = ["reduction"]}
  ins(%3 : tensor<4xf32>) outs(%out : tensor<f32>) {
  ^bb0(%arg3: f32, %arg4: f32):
  %5 = arith.addf %arg3, %arg4 : f32
  linalg.yield %5 : f32
} -> tensor<f32>

Definition at line 61 of file SplitReduction.cpp.

References mlir::linalg::LinalgTransformationFilter::checkAndNotify(), mlir::failed(), and mlir::RewriterBase::notifyMatchFailure().

Referenced by splitReductionByScaling().

◆ splitReduction() [2/2]

FailureOr< SplitReductionResult > mlir::linalg::splitReduction	(	PatternRewriter &	b,
		LinalgOp	op,
		const ControlSplitReductionFn &	controlSplitReductionFn,
		bool	useAlloc = `false`
	)

Definition at line 81 of file SplitReduction.cpp.

References mlir::OpBuilder::clone(), mlir::OpBuilder::create(), mlir::detail::enumerate(), mlir::AffineMap::get(), mlir::Builder::getAffineDimExpr(), mlir::Value::getDefiningOp(), mlir::AffineMap::getDimPosition(), getElementType(), mlir::Builder::getMultiDimIdentityMap(), getNeutralElement(), mlir::AffineMap::getNumDims(), mlir::AffineMap::getNumResults(), mlir::getParallelIteratorTypeName(), mlir::getReductionIteratorTypeName(), mlir::Operation::getResult(), mlir::Value::getType(), mlir::linalg::SplitReductionOptions::index, mlir::RewriterBase::inlineRegionBefore(), mlir::linalg::SplitReductionOptions::innerParallel, mlir::matchReduction(), mlir::RewriterBase::notifyMatchFailure(), mlir::linalg::SplitReductionOptions::ratio, mlir::OpBuilder::setInsertionPoint(), and mlir::Operation::setOperand().

◆ splitReductionByScaling()

FailureOr< SplitReductionResult > mlir::linalg::splitReductionByScaling	(	PatternRewriter &	b,
		LinalgOp	op,
		const ControlSplitReductionFn &	controlSplitReductionFn,
		bool	useAlloc = `false`
	)

Scaling-based implementation of the split reduction transformation.

Core rewrite implementation.

Instead of introducing an ExpandShapeOp, this rewrites a reduction dimension k into k * scale + kk.

Example: ``` %0 = linalg.matmul ins(A, B: tensor<16x256xf32>, tensor<256x32xf32>) outs(C: tensor<16x32xf32>) -> tensor<16x32xf32> ```

Is transformed to:

``` #map0 = affine_map<(d0, d1, d2, d3) -> (d0, d2 * 4 + d3)> #map1 = affine_map<(d0, d1, d2, d3) -> (d2 * 4 + d3, d1)> #map2 = affine_map<(d0, d1, d2, d3) -> (d2, d3)> #map3 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)> #map4 = affine_map<(d0, d1, d2) -> (d0, d1, d2)> #map5 = affine_map<(d0, d1, d2) -> (d0, d1)> %0 = tensor.empty [16, 32, 64] : tensor<16x32x64xf32> cst = arith.constant 0.000000e+00 : f32 %1 = linalg.fill ins(cst : f32) outs(%0 : tensor<16x32x64xf32>) -> tensor<16x32x64xf32> %2 = tensor.empty [64, 4] : tensor<64x4xi1>

%3 = linalg.generic {indexing_maps = [#map0, #map1, #map2, #map3], iterator_types = ["parallel", "parallel", "parallel", "reduction"]} ins(A, B, %2 : tensor<16x256xf32>, tensor<256x32xf32>, tensor<64x4xi1>) outs(%1 : tensor<16x32x64xf32>) { ^bb0(arg3: f32, arg4: f32, arg5: i1, arg6: f32): %5 = arith.mulf arg3, arg4 : f32 %6 = arith.addf arg6, %5 : f32 linalg.yield %6 : f32 } -> tensor<16x32x64xf32>

%4 = linalg.generic {indexing_maps = [#map4, #map5], iterator_types = ["parallel", "parallel", "reduction"]} */ // ins(%3 : tensor<16x32x64xf32>) /** outs(C : tensor<16x32xf32>) { ^bb0(arg3: f32, arg4: f32): %5 = arith.addf arg3, arg4 : f32 linalg.yield %5 : f32 } -> tensor<16x32xf32>

return %4 : tensor<16x32xf32> ```

Definition at line 298 of file SplitReduction.cpp.

References mlir::Type::cast(), mlir::Operation::clone(), mlir::OpBuilder::create(), mlir::tensor::createDynamicDimValues(), mlir::AffineMap::get(), mlir::getAffineDimExpr(), mlir::Value::getDefiningOp(), mlir::Builder::getIntegerType(), mlir::Builder::getMultiDimIdentityMap(), getNeutralElement(), mlir::getParallelIteratorTypeName(), mlir::getReductionIteratorTypeName(), mlir::Operation::getResult(), mlir::Value::getType(), mlir::ValueRange::getTypes(), mlir::linalg::SplitReductionOptions::index, mlir::RewriterBase::inlineRegionBefore(), mlir::linalg::SplitReductionOptions::innerParallel, mlir::RankedTensorType::Builder::insertDim(), insertParallelDim(), mlir::matchReduction(), mlir::RewriterBase::notifyMatchFailure(), mlir::linalg::SplitReductionOptions::ratio, mlir::RewriterBase::replaceOp(), scaleReductionDim(), mlir::OpBuilder::setInsertionPoint(), mlir::Operation::setOperand(), and splitReduction().

◆ tileConsumerAndFuseProducers()

FailureOr< TileLoopNest > mlir::linalg::tileConsumerAndFuseProducers	(	OpBuilder &	b,
		LinalgOp	consumerOp,
		ArrayRef< int64_t >	tileSizes,
		ArrayRef< int64_t >	tileInterchange,
		const Optional< LinalgLoopDistributionOptions > &	tileDistribution
	)

Tiles consumerOp and fuses its dependencies if possible.

Uses the tileSizes, tileInterchange, and tileDistribution parameters to control the tiling.

Definition at line 422 of file FusionOnTensors.cpp.

References mlir::applyPermutationToVector(), mlir::failed(), mlir::failure(), mlir::linalg::TileLoopNest::fuseProducer(), mlir::linalg::TileLoopNest::getRootOp(), mlir::linalg::TileLoopNest::isEmpty(), isParallelIterator(), isPermutation(), and mlir::linalg::TileLoopNest::tileRootOp().

Referenced by mlir::linalg::TileLoopNest::getLoopOps(), and mlir::linalg::LinalgTileAndFuseTensorOpsPattern::returningMatchAndRewrite().

◆ tileLinalgOp()

FailureOr< TiledLinalgOp > mlir::linalg::tileLinalgOp	(	RewriterBase &	b,
		LinalgOp	op,
		const LinalgTilingOptions &	options
	)

Definition at line 578 of file Tiling.cpp.

References mlir::failure(), Loops, mlir::linalg::LinalgTilingOptions::loopType, options, and ParallelLoops.

Referenced by mlir::linalg::TileLoopNest::tileRootOp().

◆ tileToForeachThreadOp()

FailureOr< ForeachThreadTilingResult > mlir::linalg::tileToForeachThreadOp	(	RewriterBase &	builder,
		TilingInterface	op,
		ArrayRef< OpFoldResult >	numThreads,
		ArrayRef< int64_t >	threadDimMapping = `{}`
	)

Definition at line 360 of file Tiling.cpp.

References None, and tileToForeachThreadOpImpl().

Referenced by mlir::transform::tileToForeachThreadOpImpl().

◆ tileToForeachThreadOpUsingTileSizes()

FailureOr< ForeachThreadTilingResult > mlir::linalg::tileToForeachThreadOpUsingTileSizes	(	RewriterBase &	builder,
		TilingInterface	op,
		ArrayRef< OpFoldResult >	tileSizes,
		ArrayRef< int64_t >	threadDimMapping = `{}`
	)

Same as tileToForeachThreadOp, but calculate the number of threads required using the given tileSizes.

Definition at line 369 of file Tiling.cpp.

References mlir::bindSymbols(), mlir::AffineExpr::ceilDiv(), mlir::Builder::getContext(), mlir::isConstantIntValue(), mlir::makeComposedFoldedAffineApply(), and tileToForeachThreadOpImpl().

Referenced by mlir::transform::tileToForeachThreadOpImpl().

◆ transformIndexOps()

void mlir::linalg::transformIndexOps	(	RewriterBase &	b,
		LinalgOp	op,
		SmallVectorImpl< Value > &	ivs,
		const LoopIndexToRangeIndexMap &	loopIndexToRangeIndex
	)

All indices returned by IndexOp should be invariant with respect to tiling.

Therefore, if an operation is tiled, we have to transform the indices accordingly, i.e. offset them by the values of the corresponding induction variables that are captured implicitly in the body of the op.

Example. linalg.generic before tiling:

#id_2d = (i, j) -> (i, j) #pointwise_2d_trait = { indexing_maps = [#id_2d, #id_2d], iterator_types = ["parallel", "parallel"] } linalg.generic #pointwise_2d_trait operand, result { ^bb0(operand_in: f32, result_in: f32): i = linalg.index 0 : index j = linalg.index 1 : index <some operations that use i, j> }: memref<50x100xf32>, memref<50x100xf32>

After tiling pass with tiles sizes 10 and 25:

#strided = (i, j)[s0, s1, s2] -> (i * s1 + s0 + j * s2)

c1 = arith.constant 1 : index c0 = arith.constant 0 : index c25 = arith.constant 25 : index c10 = arith.constant 10 : index operand_dim_0 = dim operand, 0 : memref<50x100xf32> operand_dim_1 = dim operand, 1 : memref<50x100xf32> scf.for k = c0 to operand_dim_0 step c10 { scf.for l = c0 to operand_dim_1 step c25 { %4 = memref.subview operand[k, l][c10, c25][c1, c1] : memref<50x100xf32> to memref<?x?xf32, #strided> %5 = memref.subview result[k, l][c10, c25][c1, c1] : memref<50x100xf32> to memref<?x?xf32, #strided> linalg.generic pointwise_2d_trait %4, %5 { ^bb0(operand_in: f32, result_in: f32): i = linalg.index 0 : index j = linalg.index 1 : index // Indices k and l are implicitly captured in the body. transformed_i = arith.addi i, k : index // index i is offset by k transformed_j = arith.addi j, l : index // index j is offset by l // Every use of i, j is replaced with transformed_i, transformed_j <some operations that use transformed_i, transformed_j> }: memref<?x?xf32, #strided>, memref<?x?xf32, #strided> } }

TODO: Investigate whether mixing implicit and explicit indices does not lead to losing information.

Definition at line 84 of file Tiling.cpp.

References mlir::detail::enumerate(), mlir::getAsOpFoldResult(), and offsetIndices().

◆ updateBoundsForCyclicDistribution()

void mlir::linalg::updateBoundsForCyclicDistribution	(	OpBuilder &	builder,
		Location	loc,
		Value	procId,
		Value	nprocs,
		Value &	lb,
		Value &	ub,
		Value &	step
	)

Update the lb, ub and step to get per processor lb, ub and step.

Definition at line 556 of file Utils.cpp.

References mlir::bindDims(), mlir::getAffineSymbolExpr(), mlir::Builder::getContext(), and mlir::makeComposedAffineApply().

Referenced by mlir::linalg::GenerateLoopNest< LoopTy >::doit().

◆ vectorize()

LogicalResult mlir::linalg::vectorize	(	RewriterBase &	builder,
		LinalgOp	linalgOp
	)

Emit a suitable vector form for a Linalg op with fully static shape.

Definition at line 599 of file Vectorization.cpp.

References mlir::RewriterBase::eraseOp(), mlir::failed(), mlir::failure(), LDBG, mlir::RewriterBase::replaceOp(), mlir::succeeded(), mlir::success(), vectorizeAsLinalgGeneric(), vectorizeConvolution(), and vectorizeLinalgOpPrecondition().

Referenced by mlir::transform::tileToForeachThreadOpImpl().

◆ vectorizeCopy()

LogicalResult mlir::linalg::vectorizeCopy	(	RewriterBase &	builder,
		memref::CopyOp	copyOp
	)

Emit a suitable vector form for a Copy op with fully static shape.

Definition at line 626 of file Vectorization.cpp.

References mlir::OpBuilder::create(), mlir::failure(), mlir::getElementTypeOrSelf(), mlir::Builder::getMultiDimIdentityMap(), mlir::RewriterBase::replaceOp(), and mlir::success().

Referenced by mlir::linalg::CopyVectorizationPattern::matchAndRewrite().

Namespaces

Classes

Typedefs

Enumerations

Functions

Typedef Documentation

◆ AllocBufferCallbackFn

◆ ControlFusionFn

◆ ControlSplitReductionFn

◆ CopyCallbackFn

◆ DeallocBufferCallbackFn

◆ FusableOpDependencesTy

◆ LinalgLoops

◆ LoopIndexToRangeIndexMap

◆ OptimizeCopyFn

◆ ProcInfoCallBackFn

◆ TileSizeComputationFunction

Enumeration Type Documentation

◆ DistributionMethod

◆ LinalgLoweringType

◆ LinalgTilingLoopType

Function Documentation

◆ allIndexingsAreProjectedPermutation()

◆ applyStagedPatterns()

◆ areElementwiseOpsFusable()

◆ computeAllSliceParameters()

◆ computeMultiTileSizes()

◆ computeSliceParameters()

◆ computeTileOffsets()

◆ computeTileSizes()

◆ concat()

◆ createFoldedDimOp()

◆ createOrFoldDimOp()

◆ extractOrIdentityMap()

◆ findAllFusableDependences()

◆ fuseElementwiseOps()

◆ fuseProducerOfBuffer()

◆ fuseProducerOfTensor() [1/2]

◆ fuseProducerOfTensor() [2/2]

◆ generalizeNamedOp()

◆ generateLibraryCallName()

◆ generateParallelLoopNest()

◆ getCombinerOpKind()

◆ getConstantUpperBoundForIndex()

◆ getDynOperands()

◆ getLinalgTilingCanonicalizationPatterns()

◆ getPrunedAttributeList()

◆ getReassociationMapForFoldingUnitDims()

◆ getTensorOutputTypes()

◆ getUpperBoundForIndex()

◆ hasOnlyScalarElementwiseOp()

◆ hoistPaddingOnTensors()

Example in pseudo-mlir:

◆ hoistRedundantVectorTransfers()

◆ hoistRedundantVectorTransfersOnTensor()

◆ insertSlicesBack()

◆ interchangeGenericOp()

◆ isaContractionOpInterface()

◆ isElementwise()

◆ isFusableInto()

◆ isParallelIterator()

◆ isPermutation()

◆ isProducerLastWriteOfView()

◆ isReductionIterator()

◆ linalgOpToAffineLoops()

◆ linalgOpToLoops()

◆ linalgOpToParallelLoops()

◆ makeAffineDimExprs()

◆ makeComposedPadHighOp()

◆ makeMemRefCopyOp()

◆ makeTiledLoopRanges()

◆ makeTiledShape()

◆ makeTiledShapes()

◆ makeTransposeOp()

◆ materializeTiledShape()

◆ offsetIndices() [1/2]

◆ offsetIndices() [2/2]

◆ peelLoops()

◆ peelTiledLinalgOp()

◆ populateBubbleUpExtractSliceOpPatterns()