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//===- Operation.cpp - MLIR Operation Class -------------------------------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
#include "mlir/IR/Operation.h"
#include "AttributeListStorage.h"
#include "mlir/IR/CFGFunction.h"
#include "mlir/IR/Instructions.h"
#include "mlir/IR/MLFunction.h"
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/OpDefinition.h"
#include "mlir/IR/OpImplementation.h"
#include "mlir/IR/OperationSet.h"
#include "mlir/IR/Statements.h"
using namespace mlir;
/// Form the OperationName for an op with the specified string. This either is
/// a reference to an AbstractOperation if one is known, or a uniqued Identifier
/// if not.
OperationName::OperationName(StringRef name, MLIRContext *context) {
if (auto *op = OperationSet::get(context).lookup(name))
representation = op;
else
representation = Identifier::get(name, context);
}
/// Return the name of this operation. This always succeeds.
StringRef OperationName::getStringRef() const {
if (auto *op = representation.dyn_cast<const AbstractOperation *>())
return op->name;
return representation.get<Identifier>().strref();
}
const AbstractOperation *OperationName::getAbstractOperation() const {
return representation.dyn_cast<const AbstractOperation *>();
}
OperationName OperationName::getFromOpaquePointer(void *pointer) {
return OperationName(RepresentationUnion::getFromOpaqueValue(pointer));
}
//===----------------------------------------------------------------------===//
// Operation class
//===----------------------------------------------------------------------===//
Operation::Operation(bool isInstruction, OperationName name,
ArrayRef<NamedAttribute> attrs, MLIRContext *context)
: nameAndIsInstruction(name, isInstruction) {
this->attrs = AttributeListStorage::get(attrs, context);
#ifndef NDEBUG
for (auto elt : attrs)
assert(elt.second != nullptr && "Attributes cannot have null entries");
#endif
}
Operation::~Operation() {}
/// Return the context this operation is associated with.
MLIRContext *Operation::getContext() const {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getContext();
return llvm::cast<OperationStmt>(this)->getContext();
}
/// The source location the operation was defined or derived from. Note that
/// it is possible for this pointer to be null.
Location *Operation::getLoc() const {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getLoc();
return llvm::cast<OperationStmt>(this)->getLoc();
}
/// Return the function this operation is defined in.
Function *Operation::getOperationFunction() {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getFunction();
return llvm::cast<OperationStmt>(this)->findFunction();
}
/// Return the number of operands this operation has.
unsigned Operation::getNumOperands() const {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getNumOperands();
return llvm::cast<OperationStmt>(this)->getNumOperands();
}
SSAValue *Operation::getOperand(unsigned idx) {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getOperand(idx);
return llvm::cast<OperationStmt>(this)->getOperand(idx);
}
void Operation::setOperand(unsigned idx, SSAValue *value) {
if (auto *inst = llvm::dyn_cast<OperationInst>(this)) {
inst->setOperand(idx, llvm::cast<CFGValue>(value));
} else {
auto *stmt = llvm::cast<OperationStmt>(this);
stmt->setOperand(idx, llvm::cast<MLValue>(value));
}
}
/// Return the number of results this operation has.
unsigned Operation::getNumResults() const {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getNumResults();
return llvm::cast<OperationStmt>(this)->getNumResults();
}
/// Return the indicated result.
SSAValue *Operation::getResult(unsigned idx) {
if (auto *inst = llvm::dyn_cast<OperationInst>(this))
return inst->getResult(idx);
return llvm::cast<OperationStmt>(this)->getResult(idx);
}
/// Return true if there are no users of any results of this operation.
bool Operation::use_empty() const {
for (auto *result : getResults())
if (!result->use_empty())
return false;
return true;
}
ArrayRef<NamedAttribute> Operation::getAttrs() const {
if (!attrs)
return {};
return attrs->getElements();
}
/// If an attribute exists with the specified name, change it to the new
/// value. Otherwise, add a new attribute with the specified name/value.
void Operation::setAttr(Identifier name, Attribute *value) {
assert(value && "attributes may never be null");
auto origAttrs = getAttrs();
SmallVector<NamedAttribute, 8> newAttrs(origAttrs.begin(), origAttrs.end());
auto *context = getContext();
// If we already have this attribute, replace it.
for (auto &elt : newAttrs)
if (elt.first == name) {
elt.second = value;
attrs = AttributeListStorage::get(newAttrs, context);
return;
}
// Otherwise, add it.
newAttrs.push_back({name, value});
attrs = AttributeListStorage::get(newAttrs, context);
}
/// Remove the attribute with the specified name if it exists. The return
/// value indicates whether the attribute was present or not.
auto Operation::removeAttr(Identifier name) -> RemoveResult {
auto origAttrs = getAttrs();
for (unsigned i = 0, e = origAttrs.size(); i != e; ++i) {
if (origAttrs[i].first == name) {
SmallVector<NamedAttribute, 8> newAttrs;
newAttrs.reserve(origAttrs.size() - 1);
newAttrs.append(origAttrs.begin(), origAttrs.begin() + i);
newAttrs.append(origAttrs.begin() + i + 1, origAttrs.end());
attrs = AttributeListStorage::get(newAttrs, getContext());
return RemoveResult::Removed;
}
}
return RemoveResult::NotFound;
}
/// Emit a note about this operation, reporting up to any diagnostic
/// handlers that may be listening.
void Operation::emitNote(const Twine &message) const {
getContext()->emitDiagnostic(getLoc(), message,
MLIRContext::DiagnosticKind::Note);
}
/// Emit a warning about this operation, reporting up to any diagnostic
/// handlers that may be listening.
void Operation::emitWarning(const Twine &message) const {
getContext()->emitDiagnostic(getLoc(), message,
MLIRContext::DiagnosticKind::Warning);
}
/// Emit an error about fatal conditions with this operation, reporting up to
/// any diagnostic handlers that may be listening. NOTE: This may terminate
/// the containing application, only use when the IR is in an inconsistent
/// state.
void Operation::emitError(const Twine &message) const {
getContext()->emitDiagnostic(getLoc(), message,
MLIRContext::DiagnosticKind::Error);
}
/// Emit an error with the op name prefixed, like "'dim' op " which is
/// convenient for verifiers.
bool Operation::emitOpError(const Twine &message) const {
emitError(Twine('\'') + getName().getStringRef() + "' op " + message);
return true;
}
/// Attempt to constant fold this operation with the specified constant
/// operand values. If successful, this returns false and fills in the
/// results vector. If not, this returns true and results is unspecified.
bool Operation::constantFold(ArrayRef<Attribute *> operands,
SmallVectorImpl<Attribute *> &results) const {
// If we have a registered operation definition matching this one, use it to
// try to constant fold the operation.
if (auto *abstractOp = getAbstractOperation())
if (!abstractOp->constantFoldHook(this, operands, results))
return false;
// TODO: Otherwise, fall back on the dialect hook to handle it.
return true;
}
//===----------------------------------------------------------------------===//
// OpState trait class.
//===----------------------------------------------------------------------===//
/// Emit an error about fatal conditions with this operation, reporting up to
/// any diagnostic handlers that may be listening. NOTE: This may terminate
/// the containing application, only use when the IR is in an inconsistent
/// state.
void OpState::emitError(const Twine &message) const {
getOperation()->emitError(message);
}
/// Emit an error with the op name prefixed, like "'dim' op " which is
/// convenient for verifiers.
bool OpState::emitOpError(const Twine &message) const {
return getOperation()->emitOpError(message);
}
/// Emit a warning about this operation, reporting up to any diagnostic
/// handlers that may be listening.
void OpState::emitWarning(const Twine &message) const {
getOperation()->emitWarning(message);
}
/// Emit a note about this operation, reporting up to any diagnostic
/// handlers that may be listening.
void OpState::emitNote(const Twine &message) const {
getOperation()->emitNote(message);
}
//===----------------------------------------------------------------------===//
// Op Trait implementations
//===----------------------------------------------------------------------===//
bool OpTrait::impl::verifyZeroOperands(const Operation *op) {
if (op->getNumOperands() != 0)
return op->emitOpError("requires zero operands");
return false;
}
bool OpTrait::impl::verifyOneOperand(const Operation *op) {
if (op->getNumOperands() != 1)
return op->emitOpError("requires a single operand");
return false;
}
bool OpTrait::impl::verifyNOperands(const Operation *op, unsigned numOperands) {
if (op->getNumOperands() != numOperands) {
return op->emitOpError("expected " + Twine(numOperands) +
" operands, but found " +
Twine(op->getNumOperands()));
}
return false;
}
bool OpTrait::impl::verifyAtLeastNOperands(const Operation *op,
unsigned numOperands) {
if (op->getNumOperands() < numOperands)
return op->emitOpError("expected " + Twine(numOperands) +
" or more operands");
return false;
}
bool OpTrait::impl::verifyZeroResult(const Operation *op) {
if (op->getNumResults() != 0)
return op->emitOpError("requires zero results");
return false;
}
bool OpTrait::impl::verifyOneResult(const Operation *op) {
if (op->getNumResults() != 1)
return op->emitOpError("requires one result");
return false;
}
bool OpTrait::impl::verifyNResults(const Operation *op, unsigned numOperands) {
if (op->getNumResults() != numOperands)
return op->emitOpError("expected " + Twine(numOperands) + " results");
return false;
}
bool OpTrait::impl::verifyAtLeastNResults(const Operation *op,
unsigned numOperands) {
if (op->getNumResults() < numOperands)
return op->emitOpError("expected " + Twine(numOperands) +
" or more results");
return false;
}
bool OpTrait::impl::verifySameOperandsAndResult(const Operation *op) {
auto *type = op->getResult(0)->getType();
for (unsigned i = 1, e = op->getNumResults(); i < e; ++i) {
if (op->getResult(i)->getType() != type)
return op->emitOpError(
"requires the same type for all operands and results");
}
for (unsigned i = 0, e = op->getNumOperands(); i < e; ++i) {
if (op->getOperand(i)->getType() != type)
return op->emitOpError(
"requires the same type for all operands and results");
}
return false;
}
/// If this is a vector type, or a tensor type, return the scalar element type
/// that it is built around, otherwise return the type unmodified.
static Type *getTensorOrVectorElementType(Type *type) {
if (auto *vec = dyn_cast<VectorType>(type))
return vec->getElementType();
// Look through tensor<vector<...>> to find the underlying element type.
if (auto *tensor = dyn_cast<TensorType>(type))
return getTensorOrVectorElementType(tensor->getElementType());
return type;
}
bool OpTrait::impl::verifyResultsAreFloatLike(const Operation *op) {
for (auto *result : op->getResults()) {
if (!isa<FloatType>(getTensorOrVectorElementType(result->getType())))
return op->emitOpError("requires a floating point type");
}
return false;
}
bool OpTrait::impl::verifyResultsAreIntegerLike(const Operation *op) {
for (auto *result : op->getResults()) {
if (!isa<IntegerType>(getTensorOrVectorElementType(result->getType())))
return op->emitOpError("requires an integer type");
}
return false;
}
//===----------------------------------------------------------------------===//
// BinaryOp implementation
//===----------------------------------------------------------------------===//
// These functions are out-of-line implementations of the methods in BinaryOp,
// which avoids them being template instantiated/duplicated.
void impl::buildBinaryOp(Builder *builder, OperationState *result,
SSAValue *lhs, SSAValue *rhs) {
assert(lhs->getType() == rhs->getType());
result->addOperands({lhs, rhs});
result->types.push_back(lhs->getType());
}
bool impl::parseBinaryOp(OpAsmParser *parser, OperationState *result) {
SmallVector<OpAsmParser::OperandType, 2> ops;
Type *type;
return parser->parseOperandList(ops, 2) ||
parser->parseOptionalAttributeDict(result->attributes) ||
parser->parseColonType(type) ||
parser->resolveOperands(ops, type, result->operands) ||
parser->addTypeToList(type, result->types);
}
void impl::printBinaryOp(const Operation *op, OpAsmPrinter *p) {
*p << op->getName() << " " << *op->getOperand(0) << ", "
<< *op->getOperand(1);
p->printOptionalAttrDict(op->getAttrs());
*p << " : " << *op->getResult(0)->getType();
}
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