MLIR  19.0.0git
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mlir::sparse_tensor::SparseTensorType Class Reference

A wrapper around RankedTensorType, which has three goals: More...

#include "mlir/Dialect/SparseTensor/IR/SparseTensorType.h"

Public Member Functions

 SparseTensorType (RankedTensorType rtp)
 
 SparseTensorType (ShapedType stp, SparseTensorEncodingAttr enc)
 
SparseTensorTypeoperator= (const SparseTensorType &)=delete
 
 SparseTensorType (const SparseTensorType &)=default
 
SparseTensorType withEncoding (SparseTensorEncodingAttr newEnc) const
 
SparseTensorType withDimToLvl (AffineMap dimToLvl) const
 
SparseTensorType withDimToLvl (SparseTensorEncodingAttr dimToLvlEnc) const
 
SparseTensorType withDimToLvl (const SparseTensorType &dimToLvlSTT) const
 
SparseTensorType withoutDimToLvl () const
 
SparseTensorType withBitWidths (unsigned posWidth, unsigned crdWidth) const
 
SparseTensorType withoutBitWidths () const
 
SparseTensorType withExplicitVal (Attribute explicitVal) const
 
SparseTensorType withoutExplicitVal () const
 
SparseTensorType withImplicitVal (Attribute implicitVal) const
 
SparseTensorType withoutImplicitVal () const
 
SparseTensorType withDimSlices (ArrayRef< SparseTensorDimSliceAttr > dimSlices) const
 
SparseTensorType withoutDimSlices () const
 
template<typename T , typename = std::enable_if_t< std::is_convertible_v<RankedTensorType, T>>>
 operator T () const
 Allow implicit conversion to RankedTensorType, ShapedType, and Type. More...
 
RankedTensorType getRankedTensorType () const
 Explicitly convert to RankedTensorType. More...
 
bool operator== (const SparseTensorType &other) const
 
bool operator!= (const SparseTensorType &other) const
 
MLIRContextgetContext () const
 
Type getElementType () const
 
SparseTensorEncodingAttr getEncoding () const
 
bool hasEncoding () const
 Returns true for tensors which have an encoding, and false for those which do not. More...
 
bool isAllDense () const
 Returns true for tensors where every level is dense. More...
 
bool isAllOrdered () const
 Returns true for tensors where every level is ordered. More...
 
ValueRange translateCrds (OpBuilder &builder, Location loc, ValueRange crds, CrdTransDirectionKind dir) const
 Translates between level / dimension coordinate space. More...
 
bool isPermutation () const
 Returns true if the dimToLvl mapping is a permutation. More...
 
bool isIdentity () const
 Returns true if the dimToLvl mapping is the identity. More...
 
AffineMap getDimToLvl () const
 Returns the dimToLvl mapping (or the null-map for the identity). More...
 
AffineMap getLvlToDim () const
 Returns the lvlToDiml mapping (or the null-map for the identity). More...
 
AffineMap getExpandedDimToLvl () const
 Returns the dimToLvl mapping, where the identity map is expanded out into a full AffineMap. More...
 
bool hasSameDimToLvl (const SparseTensorType &other) const
 Returns true iff the two types have the same mapping. More...
 
Dimension getDimRank () const
 Returns the dimension-rank. More...
 
Level getLvlRank () const
 Returns the level-rank. More...
 
ArrayRef< SizegetDimShape () const
 Returns the dimension-shape. More...
 
SmallVector< SizegetLvlShape () const
 Returns the level-shape. More...
 
unsigned getBatchLvlRank () const
 Returns the batched level-rank. More...
 
SmallVector< SizegetBatchLvlShape () const
 Returns the batched level-shape. More...
 
RankedTensorType getDemappedType () const
 Returns the type with an identity mapping. More...
 
Size getDynamicDimSize (Dimension d) const
 Safely looks up the requested dimension-DynSize. More...
 
bool hasStaticDimShape () const
 Returns true if no dimension has dynamic size. More...
 
bool hasDynamicDimShape () const
 Returns true if any dimension has dynamic size. More...
 
bool isDynamicDim (Dimension d) const
 Returns true if the given dimension has dynamic size. More...
 
int64_t getNumDynamicDims () const
 Returns the number of dimensions which have dynamic sizes. More...
 
ArrayRef< LevelTypegetLvlTypes () const
 
LevelType getLvlType (Level l) const
 
bool isDenseLvl (Level l) const
 
bool isCompressedLvl (Level l) const
 
bool isLooseCompressedLvl (Level l) const
 
bool isSingletonLvl (Level l) const
 
bool isNOutOfMLvl (Level l) const
 
bool isOrderedLvl (Level l) const
 
bool isUniqueLvl (Level l) const
 
bool isWithPos (Level l) const
 
bool isWithCrd (Level l) const
 
unsigned getCrdWidth () const
 Returns the coordinate-overhead bitwidth, defaulting to zero. More...
 
unsigned getPosWidth () const
 Returns the position-overhead bitwidth, defaulting to zero. More...
 
Attribute getExplicitVal () const
 Returns the explicit value, defaulting to null Attribute for unset. More...
 
Attribute getImplicitVal () const
 Returns the implicit value, defaulting to null Attribute for 0. More...
 
Type getCrdType () const
 Returns the coordinate-overhead MLIR type, defaulting to IndexType. More...
 
Type getPosType () const
 Returns the position-overhead MLIR type, defaulting to IndexType. More...
 
bool isCOOType (Level startLvl=0, bool isUnique=true) const
 Returns true iff this sparse tensor type has a trailing COO region starting at the given level. More...
 
Level getAoSCOOStart () const
 Returns the starting level of this sparse tensor type for a trailing COO region that spans at least two levels. More...
 
RankedTensorType getCOOType (bool ordered) const
 Returns [un]ordered COO type for this sparse tensor type. More...
 
SmallVector< COOSegmentgetCOOSegments () const
 Returns a list of COO segments in the sparse tensor types. More...
 

Detailed Description

A wrapper around RankedTensorType, which has three goals:

(1) To provide a uniform API for querying aspects of sparse-tensor types; in particular, to make the "dimension" vs "level" distinction overt (i.e., explicit everywhere). Thus, throughout the sparsifier this class should be preferred over using RankedTensorType or ShapedType directly, since the methods of the latter do not make the "dimension" vs "level" distinction overt.

(2) To provide a uniform abstraction over both sparse-tensor types (i.e., RankedTensorType with SparseTensorEncodingAttr) and dense-tensor types (i.e., RankedTensorType without an encoding). That is, we want to manipulate dense-tensor types using the same API that we use for manipulating sparse-tensor types; both to keep the "dimension" vs "level" distinction overt, and to avoid needing to handle certain cases specially in the sparsifier.

(3) To provide uniform handling of "defaults". In particular this means that dense-tensors should always return the same answers as sparse-tensors with a default encoding. But it additionally means that the answers should be normalized, so that there's no way to distinguish between non-provided data (which is filled in by default) vs explicitly-provided data which equals the defaults.

Definition at line 46 of file SparseTensorType.h.

Constructor & Destructor Documentation

◆ SparseTensorType() [1/3]

mlir::sparse_tensor::SparseTensorType::SparseTensorType ( RankedTensorType  rtp)
inline

Definition at line 50 of file SparseTensorType.h.

References getDimRank(), and isIdentity().

Referenced by withEncoding().

◆ SparseTensorType() [2/3]

mlir::sparse_tensor::SparseTensorType::SparseTensorType ( ShapedType  stp,
SparseTensorEncodingAttr  enc 
)
inline

Definition at line 59 of file SparseTensorType.h.

◆ SparseTensorType() [3/3]

mlir::sparse_tensor::SparseTensorType::SparseTensorType ( const SparseTensorType )
default

Member Function Documentation

◆ getAoSCOOStart()

Level mlir::sparse_tensor::SparseTensorType::getAoSCOOStart ( ) const
inline

Returns the starting level of this sparse tensor type for a trailing COO region that spans at least two levels.

If no such COO region is found, then returns the level-rank.

DEPRECATED: use getCOOSegment instead;

Definition at line 353 of file SparseTensorType.h.

References getEncoding().

Referenced by createAllocFields(), mlir::sparse_tensor::SparseTensorDescriptorImpl< ValueArrayRef >::getAOSMemRef(), and inferSparseBufferType().

◆ getBatchLvlRank()

unsigned mlir::sparse_tensor::SparseTensorType::getBatchLvlRank ( ) const
inline

Returns the batched level-rank.

Definition at line 254 of file SparseTensorType.h.

References getEncoding().

Referenced by getBatchLvlShape().

◆ getBatchLvlShape()

SmallVector<Size> mlir::sparse_tensor::SparseTensorType::getBatchLvlShape ( ) const
inline

Returns the batched level-shape.

Definition at line 257 of file SparseTensorType.h.

References getBatchLvlRank(), getDimShape(), and getEncoding().

Referenced by inferSparseBufferType().

◆ getContext()

MLIRContext* mlir::sparse_tensor::SparseTensorType::getContext ( ) const
inline

Definition at line 168 of file SparseTensorType.h.

Referenced by getExpandedDimToLvl(), and inferSparseBufferType().

◆ getCOOSegments()

SmallVector<COOSegment> mlir::sparse_tensor::SparseTensorType::getCOOSegments ( ) const
inline

Returns a list of COO segments in the sparse tensor types.

Definition at line 359 of file SparseTensorType.h.

References getEncoding().

◆ getCOOType()

RankedTensorType mlir::sparse_tensor::SparseTensorType::getCOOType ( bool  ordered) const

Returns [un]ordered COO type for this sparse tensor type.

Definition at line 1010 of file SparseTensorDialect.cpp.

References mlir::sparse_tensor::buildLevelType(), mlir::sparse_tensor::Compressed, mlir::get(), getContext(), getElementType(), and mlir::sparse_tensor::Singleton.

Referenced by getBufferType().

◆ getCrdType()

Type mlir::sparse_tensor::SparseTensorType::getCrdType ( ) const
inline

Returns the coordinate-overhead MLIR type, defaulting to IndexType.

Definition at line 338 of file SparseTensorType.h.

Referenced by mlir::sparse_tensor::foreachFieldAndTypeInSparseTensor(), and inferSparseBufferType().

◆ getCrdWidth()

unsigned mlir::sparse_tensor::SparseTensorType::getCrdWidth ( ) const
inline

Returns the coordinate-overhead bitwidth, defaulting to zero.

Definition at line 322 of file SparseTensorType.h.

◆ getDemappedType()

RankedTensorType mlir::sparse_tensor::SparseTensorType::getDemappedType ( ) const
inline

Returns the type with an identity mapping.

Definition at line 265 of file SparseTensorType.h.

References mlir::get(), getElementType(), and getLvlShape().

◆ getDimRank()

Dimension mlir::sparse_tensor::SparseTensorType::getDimRank ( ) const
inline

◆ getDimShape()

ArrayRef<Size> mlir::sparse_tensor::SparseTensorType::getDimShape ( ) const
inline

◆ getDimToLvl()

AffineMap mlir::sparse_tensor::SparseTensorType::getDimToLvl ( ) const
inline

Returns the dimToLvl mapping (or the null-map for the identity).

If you intend to compare the results of this method for equality, see hasSameDimToLvl instead.

Definition at line 212 of file SparseTensorType.h.

Referenced by mlir::sparse_tensor::genMapBuffers().

◆ getDynamicDimSize()

Size mlir::sparse_tensor::SparseTensorType::getDynamicDimSize ( Dimension  d) const
inline

Safely looks up the requested dimension-DynSize.

If you intend to check the result with ShapedType::isDynamic, then see the getStaticDimSize method instead.

Definition at line 273 of file SparseTensorType.h.

References getDimRank(), and getDimShape().

Referenced by isDynamicDim().

◆ getElementType()

Type mlir::sparse_tensor::SparseTensorType::getElementType ( ) const
inline

◆ getEncoding()

SparseTensorEncodingAttr mlir::sparse_tensor::SparseTensorType::getEncoding ( ) const
inline

◆ getExpandedDimToLvl()

AffineMap mlir::sparse_tensor::SparseTensorType::getExpandedDimToLvl ( ) const
inline

Returns the dimToLvl mapping, where the identity map is expanded out into a full AffineMap.

This method is provided as a convenience, but for most purposes other methods (isIdentity, getDimToLvl, etc) will be more helpful.

Definition at line 221 of file SparseTensorType.h.

References getContext(), getDimRank(), and mlir::AffineMap::getMultiDimIdentityMap().

◆ getExplicitVal()

Attribute mlir::sparse_tensor::SparseTensorType::getExplicitVal ( ) const
inline

Returns the explicit value, defaulting to null Attribute for unset.

Definition at line 328 of file SparseTensorType.h.

◆ getImplicitVal()

Attribute mlir::sparse_tensor::SparseTensorType::getImplicitVal ( ) const
inline

Returns the implicit value, defaulting to null Attribute for 0.

Definition at line 333 of file SparseTensorType.h.

◆ getLvlRank()

Level mlir::sparse_tensor::SparseTensorType::getLvlRank ( ) const
inline

◆ getLvlShape()

SmallVector<Size> mlir::sparse_tensor::SparseTensorType::getLvlShape ( ) const
inline

Returns the level-shape.

Definition at line 248 of file SparseTensorType.h.

References getDimShape(), and getEncoding().

Referenced by getDemappedType().

◆ getLvlToDim()

AffineMap mlir::sparse_tensor::SparseTensorType::getLvlToDim ( ) const
inline

Returns the lvlToDiml mapping (or the null-map for the identity).

Definition at line 215 of file SparseTensorType.h.

Referenced by mlir::sparse_tensor::genMapBuffers().

◆ getLvlType()

LevelType mlir::sparse_tensor::SparseTensorType::getLvlType ( Level  l) const
inline

◆ getLvlTypes()

ArrayRef<LevelType> mlir::sparse_tensor::SparseTensorType::getLvlTypes ( ) const
inline

Definition at line 298 of file SparseTensorType.h.

◆ getNumDynamicDims()

int64_t mlir::sparse_tensor::SparseTensorType::getNumDynamicDims ( ) const
inline

Returns the number of dimensions which have dynamic sizes.

The return type is int64_t to maintain consistency with ShapedType::Trait<T>::getNumDynamicDims.

Definition at line 296 of file SparseTensorType.h.

◆ getPosType()

Type mlir::sparse_tensor::SparseTensorType::getPosType ( ) const
inline

Returns the position-overhead MLIR type, defaulting to IndexType.

Definition at line 341 of file SparseTensorType.h.

Referenced by allocSchemeForRank(), createAllocFields(), mlir::sparse_tensor::foreachFieldAndTypeInSparseTensor(), genEndInsert(), and inferSparseBufferType().

◆ getPosWidth()

unsigned mlir::sparse_tensor::SparseTensorType::getPosWidth ( ) const
inline

Returns the position-overhead bitwidth, defaulting to zero.

Definition at line 325 of file SparseTensorType.h.

◆ getRankedTensorType()

RankedTensorType mlir::sparse_tensor::SparseTensorType::getRankedTensorType ( ) const
inline

Explicitly convert to RankedTensorType.

This method is a convenience for resolving overload-ambiguity issues with implicit conversion.

Definition at line 156 of file SparseTensorType.h.

Referenced by getBufferType().

◆ hasDynamicDimShape()

bool mlir::sparse_tensor::SparseTensorType::hasDynamicDimShape ( ) const
inline

Returns true if any dimension has dynamic size.

Definition at line 282 of file SparseTensorType.h.

References hasStaticDimShape().

Referenced by mlir::sparse_tensor::genReader().

◆ hasEncoding()

bool mlir::sparse_tensor::SparseTensorType::hasEncoding ( ) const
inline

Returns true for tensors which have an encoding, and false for those which do not.

Therefore tensors with an all-dense encoding return true.

Definition at line 181 of file SparseTensorType.h.

Referenced by convertSparseTensorType(), and mlir::sparse_tensor::foreachFieldAndTypeInSparseTensor().

◆ hasSameDimToLvl()

bool mlir::sparse_tensor::SparseTensorType::hasSameDimToLvl ( const SparseTensorType other) const
inline

Returns true iff the two types have the same mapping.

This method takes care to handle identity maps properly, so it should be preferred over using getDimToLvl followed by AffineMap::operator==.

Definition at line 230 of file SparseTensorType.h.

References isIdentity().

◆ hasStaticDimShape()

bool mlir::sparse_tensor::SparseTensorType::hasStaticDimShape ( ) const
inline

Returns true if no dimension has dynamic size.

Definition at line 279 of file SparseTensorType.h.

Referenced by hasDynamicDimShape().

◆ isAllDense()

bool mlir::sparse_tensor::SparseTensorType::isAllDense ( ) const
inline

Returns true for tensors where every level is dense.

(This is always true for dense-tensors.)

Definition at line 185 of file SparseTensorType.h.

Referenced by createAllocFields(), and mlir::sparse_tensor::CodegenEnv::isAdmissibleTensorExp().

◆ isAllOrdered()

bool mlir::sparse_tensor::SparseTensorType::isAllOrdered ( ) const
inline

Returns true for tensors where every level is ordered.

(This is always true for dense-tensors.)

Definition at line 189 of file SparseTensorType.h.

◆ isCompressedLvl()

bool mlir::sparse_tensor::SparseTensorType::isCompressedLvl ( Level  l) const
inline

Definition at line 310 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isCompressedLT().

Referenced by createAllocFields().

◆ isCOOType()

bool mlir::sparse_tensor::SparseTensorType::isCOOType ( Level  startLvl = 0,
bool  isUnique = true 
) const

Returns true iff this sparse tensor type has a trailing COO region starting at the given level.

By default, it tests for a unique COO type at top level.

Definition at line 994 of file SparseTensorDialect.cpp.

References isUnique().

◆ isDenseLvl()

bool mlir::sparse_tensor::SparseTensorType::isDenseLvl ( Level  l) const
inline

Definition at line 309 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isDenseLT().

Referenced by createAllocFields().

◆ isDynamicDim()

bool mlir::sparse_tensor::SparseTensorType::isDynamicDim ( Dimension  d) const
inline

Returns true if the given dimension has dynamic size.

If you intend to call getDynamicDimSize based on the result, then see the getStaticDimSize method instead.

Definition at line 287 of file SparseTensorType.h.

References getDynamicDimSize().

Referenced by mlir::sparse_tensor::genReader().

◆ isIdentity()

bool mlir::sparse_tensor::SparseTensorType::isIdentity ( ) const
inline

Returns true if the dimToLvl mapping is the identity.

(This is always true for dense-tensors.)

Definition at line 203 of file SparseTensorType.h.

Referenced by mlir::sparse_tensor::genMapBuffers(), hasSameDimToLvl(), and SparseTensorType().

◆ isLooseCompressedLvl()

bool mlir::sparse_tensor::SparseTensorType::isLooseCompressedLvl ( Level  l) const
inline

Definition at line 311 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isLooseCompressedLT().

◆ isNOutOfMLvl()

bool mlir::sparse_tensor::SparseTensorType::isNOutOfMLvl ( Level  l) const
inline

Definition at line 315 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isNOutOfMLT().

◆ isOrderedLvl()

bool mlir::sparse_tensor::SparseTensorType::isOrderedLvl ( Level  l) const
inline

Definition at line 316 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isOrderedLT().

◆ isPermutation()

bool mlir::sparse_tensor::SparseTensorType::isPermutation ( ) const
inline

Returns true if the dimToLvl mapping is a permutation.

(This is always true for dense-tensors.)

Definition at line 199 of file SparseTensorType.h.

◆ isSingletonLvl()

bool mlir::sparse_tensor::SparseTensorType::isSingletonLvl ( Level  l) const
inline

Definition at line 314 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isSingletonLT().

◆ isUniqueLvl()

bool mlir::sparse_tensor::SparseTensorType::isUniqueLvl ( Level  l) const
inline

Definition at line 317 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isUniqueLT().

Referenced by genCompressed().

◆ isWithCrd()

bool mlir::sparse_tensor::SparseTensorType::isWithCrd ( Level  l) const
inline

Definition at line 319 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isWithCrdLT().

◆ isWithPos()

bool mlir::sparse_tensor::SparseTensorType::isWithPos ( Level  l) const
inline

Definition at line 318 of file SparseTensorType.h.

References getLvlType(), and mlir::sparse_tensor::isWithPosLT().

◆ operator T()

template<typename T , typename = std::enable_if_t< std::is_convertible_v<RankedTensorType, T>>>
mlir::sparse_tensor::SparseTensorType::operator T ( ) const
inline

Allow implicit conversion to RankedTensorType, ShapedType, and Type.

These are implicit to help alleviate the impedance mismatch for code that has not been converted to use SparseTensorType directly. Once more uses have been converted to SparseTensorType, we may want to make these explicit instead.

WARNING: This user-defined-conversion method causes overload ambiguity whenever passing a SparseTensorType directly to a function which is overloaded to accept either Type or TypeRange. In particular, this includes RewriterBase::replaceOpWithNewOp<OpTy> and OpBuilder::create<OpTy> whenever the OpTy::build is overloaded thus. This happens because the TypeRange<T>(T&&) ctor is implicit as well, and there's no SFINAE we can add to this method that would block subsequent application of that ctor. The only way to fix the overload ambiguity is to avoid implicit conversion at the callsite: e.g., by using static_cast to make the conversion explicit, by assigning the SparseTensorType to a temporary variable of the desired type, etc.

Definition at line 149 of file SparseTensorType.h.

◆ operator!=()

bool mlir::sparse_tensor::SparseTensorType::operator!= ( const SparseTensorType other) const
inline

Definition at line 164 of file SparseTensorType.h.

◆ operator=()

SparseTensorType& mlir::sparse_tensor::SparseTensorType::operator= ( const SparseTensorType )
delete

◆ operator==()

bool mlir::sparse_tensor::SparseTensorType::operator== ( const SparseTensorType other) const
inline

Definition at line 158 of file SparseTensorType.h.

◆ translateCrds()

ValueRange mlir::sparse_tensor::SparseTensorType::translateCrds ( OpBuilder builder,
Location  loc,
ValueRange  crds,
CrdTransDirectionKind  dir 
) const
inline

Translates between level / dimension coordinate space.

Definition at line 192 of file SparseTensorType.h.

◆ withBitWidths()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withBitWidths ( unsigned  posWidth,
unsigned  crdWidth 
) const
inline

Definition at line 91 of file SparseTensorType.h.

References withEncoding().

◆ withDimSlices()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withDimSlices ( ArrayRef< SparseTensorDimSliceAttr >  dimSlices) const
inline

Definition at line 116 of file SparseTensorType.h.

References withEncoding().

◆ withDimToLvl() [1/3]

SparseTensorType mlir::sparse_tensor::SparseTensorType::withDimToLvl ( AffineMap  dimToLvl) const
inline

Definition at line 75 of file SparseTensorType.h.

References withEncoding().

Referenced by withDimToLvl().

◆ withDimToLvl() [2/3]

SparseTensorType mlir::sparse_tensor::SparseTensorType::withDimToLvl ( const SparseTensorType dimToLvlSTT) const
inline

Definition at line 83 of file SparseTensorType.h.

References getEncoding(), and withDimToLvl().

◆ withDimToLvl() [3/3]

SparseTensorType mlir::sparse_tensor::SparseTensorType::withDimToLvl ( SparseTensorEncodingAttr  dimToLvlEnc) const
inline

Definition at line 79 of file SparseTensorType.h.

References withEncoding().

◆ withEncoding()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withEncoding ( SparseTensorEncodingAttr  newEnc) const
inline

◆ withExplicitVal()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withExplicitVal ( Attribute  explicitVal) const
inline

Definition at line 99 of file SparseTensorType.h.

References withEncoding().

◆ withImplicitVal()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withImplicitVal ( Attribute  implicitVal) const
inline

Definition at line 107 of file SparseTensorType.h.

References withEncoding().

◆ withoutBitWidths()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withoutBitWidths ( ) const
inline

Definition at line 95 of file SparseTensorType.h.

References withEncoding().

◆ withoutDimSlices()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withoutDimSlices ( ) const
inline

Definition at line 120 of file SparseTensorType.h.

References withEncoding().

◆ withoutDimToLvl()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withoutDimToLvl ( ) const
inline

Definition at line 87 of file SparseTensorType.h.

References withEncoding().

◆ withoutExplicitVal()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withoutExplicitVal ( ) const
inline

Definition at line 103 of file SparseTensorType.h.

References withEncoding().

◆ withoutImplicitVal()

SparseTensorType mlir::sparse_tensor::SparseTensorType::withoutImplicitVal ( ) const
inline

Definition at line 111 of file SparseTensorType.h.

References withEncoding().


The documentation for this class was generated from the following files: