#include "IterationGraphSorter.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
#include "mlir/Dialect/Utils/StructuredOpsUtils.h"
#include "mlir/IR/AffineExprVisitor.h"
#include "mlir/IR/BuiltinTypes.h"
#include "llvm/ADT/DenseSet.h"

Functions
static bool	includesAny (SortMask mask1, SortMask mask2)
static bool	includesDenseInput (SortMask mask)
static bool	includesDenseOutput (SortMask mask)
static unsigned	getLoopSparsityRank (unsigned loop, ArrayRef< Value > allTensors, ArrayRef< AffineMap > allMaps, bool preferDenseOuter)
	Returns a sparsity rank for loop ordering: lower values indicate dimensions that should be placed in outer loops.
static SmallVector< unsigned >	getLoopUseCounts (linalg::GenericOp genericOp)
	Count distinct input accesses whose indexing expressions use each loop.

Function Documentation

◆ getLoopSparsityRank()

unsigned getLoopSparsityRank	(	unsigned	loop,
		ArrayRef< Value >	allTensors,
		ArrayRef< AffineMap >	allMaps,
		bool	preferDenseOuter )

static

Returns a sparsity rank for loop ordering: lower values indicate dimensions that should be placed in outer loops.

When preferDenseOuter is true the ranking is 0 = Dense, 1 = Compressed, 2 = Singleton, 3 = Other/Unknown. Otherwise 0 = Singleton, 1 = Compressed, 2 = Dense, 3 = Other/Unknown.

Definition at line 90 of file IterationGraphSorter.cpp.

References mlir::sparse_tensor::getSparseTensorEncoding(), mlir::sparse_tensor::isCompressedLT(), mlir::sparse_tensor::isDenseLT(), and mlir::sparse_tensor::isSingletonLT().