MLIR  19.0.0git
Macros | Functions
TosaOps.cpp File Reference
#include "mlir/Dialect/Tosa/IR/TosaOps.h"
#include "mlir/Dialect/Mesh/Interfaces/ShardingInterface.h"
#include "mlir/Dialect/Quant/QuantOps.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Tosa/Utils/QuantUtils.h"
#include "mlir/Dialect/Tosa/Utils/ShapeUtils.h"
#include "mlir/Dialect/Utils/IndexingUtils.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/DialectImplementation.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/TypeUtilities.h"
#include "mlir/Interfaces/InferTypeOpInterface.h"
#include "mlir/Transforms/InliningUtils.h"
#include "llvm/ADT/APFloat.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/TypeSwitch.h"
#include "mlir/Dialect/Tosa/IR/TosaOpsDialect.cpp.inc"
#include "mlir/Dialect/Tosa/IR/TosaInterfaces.cpp.inc"
#include "mlir/Dialect/Tosa/IR/TosaDialectBytecode.cpp.inc"
#include "mlir/Dialect/Tosa/IR/TosaOps.cpp.inc"
#include "mlir/Dialect/Tosa/IR/TosaAttributes.cpp.inc"

Go to the source code of this file.

Macros

#define GET_OP_LIST
 
#define GET_ATTRDEF_LIST
 
#define COMPATIBLE_RETURN_TYPES(OP)
 
#define REDUCE_SHAPE_INFER(OP)
 
#define NARY_SHAPE_INFER(OP)
 
#define GET_ATTRDEF_CLASSES
 
#define GET_OP_CLASSES
 

Functions

static bool hasZeroDimension (ShapedType shapedType)
 
template<typename T >
static LogicalResult verifyConvOp (T op)
 
static void buildConvOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input, Value weight, Value bias, DenseI64ArrayAttr pad, DenseI64ArrayAttr stride, DenseI64ArrayAttr dilation)
 This builder is called on all convolution operators except TransposeConv, which has specialized output shape semantics. More...
 
static void buildTransConvOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input, Value weight, Value bias, DenseI64ArrayAttr outpad, DenseI64ArrayAttr stride, DenseI64ArrayAttr outputShape)
 Handles tosa.transpose_conv2d which has outpad and output shape attributes. More...
 
static void buildFCOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input, Value weight, Value bias)
 The tosa.fully_connected op has its own builder as it does not have strides/dilation/padding. More...
 
static void buildMatMulOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value a, Value b)
 The tosa.matmul op is also intended to be generated where a fully_connected op must be constructed where the weight is not a constant. More...
 
static void buildAvgPool2dOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input, DenseArrayAttr kernel, DenseArrayAttr stride, DenseArrayAttr pad, TypeAttr accType)
 Both the tosa.avg_pool2d and unary ops use the same UnaruOpQuantizationAttr but avg_pool operator has its own builder as it has additional parameters not part of the unary ops. More...
 
static void buildUnaryOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input)
 This builder is called on single-parameter unary operators that have scale relationship between their input and output, expressed by the UnaryOpQuantizationAttr. More...
 
static void buildPadOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input, Value paddings)
 This builder is called on TOSA pad operator that needs to create its own OptionalAttr quantization_attr parameter to scale the padding values correctly. More...
 
static void buildExplicitValuePadOpWithQuantInfo (OpBuilder &builder, OperationState &result, Type outputType, Value input, Value paddings, Value padConst)
 This builder is called on TOSA pad operator when an explicit pad_const value is passed in. More...
 
static LogicalResult resolveBroadcastShape (const ValueShapeRange &operands, SmallVector< int64_t > &outShape)
 
static SmallVector< int64_t > convertToMlirShape (ArrayRef< int64_t > shape)
 
static LogicalResult ReduceInferReturnTypes (ShapeAdaptor operandShape, Type inputType, IntegerAttr axis, SmallVectorImpl< ShapedTypeComponents > &inferredReturnShapes)
 
template<typename T >
static LogicalResult verifyReduceOp (T op)
 
static LogicalResult NAryInferReturnTypes (const ValueShapeRange &operands, SmallVectorImpl< ShapedTypeComponents > &inferredReturnShapes)
 
static LogicalResult poolingInferReturnTypes (ShapeAdaptor inputShape, ArrayRef< int64_t > kernel, ArrayRef< int64_t > stride, ArrayRef< int64_t > pad, SmallVectorImpl< ShapedTypeComponents > &inferredReturnShapes)
 
static void printInitializationList (OpAsmPrinter &parser, Block::BlockArgListType blocksArgs, ValueRange initializers, StringRef prefix="")
 

Macro Definition Documentation

◆ COMPATIBLE_RETURN_TYPES

#define COMPATIBLE_RETURN_TYPES (   OP)
Value:
bool OP::isCompatibleReturnTypes(TypeRange l, TypeRange r) { \
if (l.size() != r.size() || l.size() != 1) \
return false; \
return false; \
return succeeded(verifyCompatibleShape(l[0], r[0])); \
}
This class provides an abstraction over the various different ranges of value types.
Definition: TypeRange.h:36
bool succeeded(LogicalResult result)
Utility function that returns true if the provided LogicalResult corresponds to a success value.
Definition: LogicalResult.h:68
Type getElementTypeOrSelf(Type type)
Return the element type or return the type itself.
LogicalResult verifyCompatibleShape(ArrayRef< int64_t > shape1, ArrayRef< int64_t > shape2)
Returns success if the given two shapes are compatible.

Definition at line 1261 of file TosaOps.cpp.

◆ GET_ATTRDEF_CLASSES

#define GET_ATTRDEF_CLASSES

Definition at line 1995 of file TosaOps.cpp.

◆ GET_ATTRDEF_LIST

#define GET_ATTRDEF_LIST

◆ GET_OP_CLASSES

#define GET_OP_CLASSES

Definition at line 2002 of file TosaOps.cpp.

◆ GET_OP_LIST

#define GET_OP_LIST

◆ NARY_SHAPE_INFER

#define NARY_SHAPE_INFER (   OP)
Value:
LogicalResult OP::inferReturnTypeComponents( \
MLIRContext *context, ::std::optional<Location> location, \
ValueShapeRange operands, DictionaryAttr attributes, \
OpaqueProperties properties, RegionRange regions, \
SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) { \
return NAryInferReturnTypes(operands, inferredReturnShapes); \
}
static LogicalResult NAryInferReturnTypes(const ValueShapeRange &operands, SmallVectorImpl< ShapedTypeComponents > &inferredReturnShapes)
Definition: TosaOps.cpp:1351
MLIRContext is the top-level object for a collection of MLIR operations.
Definition: MLIRContext.h:60
Simple wrapper around a void* in order to express generically how to pass in op properties through AP...
This class provides an abstraction over the different types of ranges over Regions.
Definition: Region.h:346
Range of values and shapes (corresponding effectively to Shapes dialect's ValueShape type concept).
This class represents an efficient way to signal success or failure.
Definition: LogicalResult.h:26

Definition at line 1363 of file TosaOps.cpp.

◆ REDUCE_SHAPE_INFER

#define REDUCE_SHAPE_INFER (   OP)
Value:
LogicalResult OP::inferReturnTypeComponents( \
MLIRContext *context, ::std::optional<Location> location, \
OP::Adaptor adaptor, \
SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) { \
Type inputType = \
llvm::cast<TensorType>(adaptor.getInput().getType()).getElementType(); \
ShapeAdaptor inputShape(adaptor.getInput().getType()); \
const Properties &prop = adaptor.getProperties(); \
return ReduceInferReturnTypes(inputShape, inputType, prop.axis, \
inferredReturnShapes); \
} \
COMPATIBLE_RETURN_TYPES(OP)
static LogicalResult ReduceInferReturnTypes(ShapeAdaptor operandShape, Type inputType, IntegerAttr axis, SmallVectorImpl< ShapedTypeComponents > &inferredReturnShapes)
Definition: TosaOps.cpp:1245

Definition at line 1270 of file TosaOps.cpp.

Function Documentation

◆ buildAvgPool2dOpWithQuantInfo()

static void buildAvgPool2dOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input,
DenseArrayAttr  kernel,
DenseArrayAttr  stride,
DenseArrayAttr  pad,
TypeAttr  accType 
)
static

Both the tosa.avg_pool2d and unary ops use the same UnaruOpQuantizationAttr but avg_pool operator has its own builder as it has additional parameters not part of the unary ops.

Definition at line 464 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::tosa::buildUnaryOpQuantizationAttr(), and mlir::OperationState::types.

◆ buildConvOpWithQuantInfo()

static void buildConvOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input,
Value  weight,
Value  bias,
DenseI64ArrayAttr  pad,
DenseI64ArrayAttr  stride,
DenseI64ArrayAttr  dilation 
)
static

This builder is called on all convolution operators except TransposeConv, which has specialized output shape semantics.

The builder also defines the bitwidth of the output given the bit width of the input & weight content.

Definition at line 365 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::OperationState::addTypes(), mlir::tosa::buildConvOpQuantizationAttr(), and mlir::tosa::buildConvOpResultTypeInfo().

◆ buildExplicitValuePadOpWithQuantInfo()

static void buildExplicitValuePadOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input,
Value  paddings,
Value  padConst 
)
static

This builder is called on TOSA pad operator when an explicit pad_const value is passed in.

It also optionally constructs quantization_attr.

Definition at line 507 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::tosa::buildPadOpQuantizationAttr(), and mlir::OperationState::types.

◆ buildFCOpWithQuantInfo()

static void buildFCOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input,
Value  weight,
Value  bias 
)
static

The tosa.fully_connected op has its own builder as it does not have strides/dilation/padding.

Definition at line 408 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::OperationState::addTypes(), mlir::tosa::buildConvOpQuantizationAttr(), and mlir::tosa::buildConvOpResultTypeInfo().

◆ buildMatMulOpWithQuantInfo()

static void buildMatMulOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  a,
Value  b 
)
static

The tosa.matmul op is also intended to be generated where a fully_connected op must be constructed where the weight is not a constant.

In this case, the fully_connected op must be expressed using matmul. TODO: Add link to the leglization document explaining this.

Definition at line 427 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::OperationState::addTypes(), mlir::tosa::buildMatMulOpQuantizationAttr(), mlir::Builder::getI32Type(), mlir::Builder::getIntegerType(), and mlir::Value::getType().

◆ buildPadOpWithQuantInfo()

static void buildPadOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input,
Value  paddings 
)
static

This builder is called on TOSA pad operator that needs to create its own OptionalAttr quantization_attr parameter to scale the padding values correctly.

No pad_const is interpreted as zero-padding.

Definition at line 495 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::tosa::buildPadOpQuantizationAttr(), and mlir::OperationState::types.

◆ buildTransConvOpWithQuantInfo()

static void buildTransConvOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input,
Value  weight,
Value  bias,
DenseI64ArrayAttr  outpad,
DenseI64ArrayAttr  stride,
DenseI64ArrayAttr  outputShape 
)
static

Handles tosa.transpose_conv2d which has outpad and output shape attributes.

Definition at line 387 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::OperationState::addTypes(), mlir::tosa::buildConvOpQuantizationAttr(), and mlir::tosa::buildConvOpResultTypeInfo().

◆ buildUnaryOpWithQuantInfo()

static void buildUnaryOpWithQuantInfo ( OpBuilder builder,
OperationState result,
Type  outputType,
Value  input 
)
static

This builder is called on single-parameter unary operators that have scale relationship between their input and output, expressed by the UnaryOpQuantizationAttr.

Definition at line 482 of file TosaOps.cpp.

References mlir::OperationState::addAttribute(), mlir::OperationState::addOperands(), mlir::tosa::buildUnaryOpQuantizationAttr(), and mlir::OperationState::types.

◆ convertToMlirShape()

static SmallVector<int64_t> convertToMlirShape ( ArrayRef< int64_t >  shape)
static

Definition at line 820 of file TosaOps.cpp.

◆ hasZeroDimension()

static bool hasZeroDimension ( ShapedType  shapedType)
static

Definition at line 207 of file TosaOps.cpp.

◆ NAryInferReturnTypes()

static LogicalResult NAryInferReturnTypes ( const ValueShapeRange operands,
SmallVectorImpl< ShapedTypeComponents > &  inferredReturnShapes 
)
static

Definition at line 1351 of file TosaOps.cpp.

References mlir::failed(), resolveBroadcastShape(), and mlir::success().

◆ poolingInferReturnTypes()

static LogicalResult poolingInferReturnTypes ( ShapeAdaptor  inputShape,
ArrayRef< int64_t >  kernel,
ArrayRef< int64_t >  stride,
ArrayRef< int64_t >  pad,
SmallVectorImpl< ShapedTypeComponents > &  inferredReturnShapes 
)
static

Definition at line 1414 of file TosaOps.cpp.

References mlir::ShapeAdaptor::getDimSize(), and mlir::success().

◆ printInitializationList()

static void printInitializationList ( OpAsmPrinter parser,
Block::BlockArgListType  blocksArgs,
ValueRange  initializers,
StringRef  prefix = "" 
)
static

Definition at line 1963 of file TosaOps.cpp.

◆ ReduceInferReturnTypes()

static LogicalResult ReduceInferReturnTypes ( ShapeAdaptor  operandShape,
Type  inputType,
IntegerAttr  axis,
SmallVectorImpl< ShapedTypeComponents > &  inferredReturnShapes 
)
static

◆ resolveBroadcastShape()

static LogicalResult resolveBroadcastShape ( const ValueShapeRange operands,
SmallVector< int64_t > &  outShape 
)
static

Definition at line 523 of file TosaOps.cpp.

References mlir::failure(), mlir::ValueShapeRange::getShape(), and mlir::success().

Referenced by NAryInferReturnTypes().

◆ verifyConvOp()

template<typename T >
static LogicalResult verifyConvOp ( op)
static

Definition at line 224 of file TosaOps.cpp.

◆ verifyReduceOp()

template<typename T >
static LogicalResult verifyReduceOp ( op)
static

Definition at line 1295 of file TosaOps.cpp.