#include "mlir/Dialect/Linalg/Passes.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
#include "mlir/Dialect/Linalg/Utils/Utils.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Dialect/Linalg/Passes.h.inc"

Namespaces
namespace	mlir
	Include the generated interface declarations.

Macros
#define	GEN_PASS_DEF_CONVERTELEMENTWISETOLINALGPASS

Functions
static bool	isScalarLike (Type t)
static bool	isElementwiseMappableOpOnRankedTensors (Operation *op)
static SmallVector< Value, 4 >	getOrCreateOperandsMatchingResultTypes (OpBuilder &b, Operation *op)
	Given op assumed isElementwiseMappableOpOnRankedTensors, iterate over the result types and return a list of values such that, for each result type t and value v at the same index idx:

Macro Definition Documentation

◆ GEN_PASS_DEF_CONVERTELEMENTWISETOLINALGPASS

#define GEN_PASS_DEF_CONVERTELEMENTWISETOLINALGPASS

Definition at line 17 of file ElementwiseToLinalg.cpp.

Function Documentation

◆ getOrCreateOperandsMatchingResultTypes()

SmallVector< Value, 4 > getOrCreateOperandsMatchingResultTypes	(	OpBuilder &	b,
		Operation *	op )

static

Given op assumed isElementwiseMappableOpOnRankedTensors, iterate over the result types and return a list of values such that, for each result type t and value v at the same index idx:

v.getType() == t
If an operand of op has type t, let operand_first be the first such operand. Thenv == operand_first.
Otherwise, v is a newly created tensor::EmptyOp with: a. Static and dynamic dims extracted from the first operand of op. b. Elemental type equal to the elemental type of t.

This is sufficient because ElementwiseMappable guarantees that "The static types of all vector (resp. tensor) operands and results must have the same shape".

Definition at line 59 of file ElementwiseToLinalg.cpp.

References b, mlir::Operation::getLoc(), mlir::tensor::getMixedSizes(), mlir::Operation::getOperands(), mlir::Operation::getResultTypes(), and isElementwiseMappableOpOnRankedTensors().