torch-mlir/lib/Dialect/TorchConversion/IR/TorchConversionOps.cpp

102 lines
3.5 KiB
C++

//===----------------------------------------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// Also available under a BSD-style license. See LICENSE.
//
//===----------------------------------------------------------------------===//
#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionOps.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/TypeUtilities.h"
#include "torch-mlir/Dialect/Torch/IR/TorchTypes.h"
#include "llvm/ADT/StringMap.h"
using namespace mlir;
using namespace mlir::torch;
using namespace mlir::torch::TorchConversion;
using namespace mlir::torch;
static bool haveSameSizeAndElementType(TensorType lhs, TensorType rhs) {
if (lhs.hasRank() != rhs.hasRank())
return false;
bool sameSize = lhs.hasRank() ? lhs.getShape().equals(rhs.getShape()) : true;
bool sameElementType = lhs.getElementType() == rhs.getElementType();
return sameElementType && sameSize;
}
//===----------------------------------------------------------------------===//
// ToBuiltinTensorOp
//===----------------------------------------------------------------------===//
LogicalResult ToBuiltinTensorOp::verify() {
auto resultType = getResult().getType().cast<TensorType>();
auto operandType =
getOperand().getType().cast<Torch::ValueTensorType>().toBuiltinTensor();
if (!haveSameSizeAndElementType(resultType, operandType)) {
return emitError()
<< "operand and result must have the same size and dtype";
}
return success();
}
LogicalResult ToBuiltinTensorOp::inferReturnTypes(
MLIRContext *context, Optional<Location> location, ValueRange operands,
DictionaryAttr attributes, RegionRange regions,
SmallVectorImpl<Type> &inferredReturnTypes) {
auto resultType =
operands[0].getType().cast<Torch::ValueTensorType>().toBuiltinTensor();
if (!resultType)
return failure();
inferredReturnTypes.push_back(resultType);
return success();
}
//===----------------------------------------------------------------------===//
// FromBuiltinTensorOp
//===----------------------------------------------------------------------===//
LogicalResult FromBuiltinTensorOp::verify() {
auto resultType =
getResult().getType().cast<Torch::ValueTensorType>().toBuiltinTensor();
auto operandType = getOperand().getType().cast<TensorType>();
if (!haveSameSizeAndElementType(resultType, operandType)) {
return emitError()
<< "operand and result must have the same size and dtype";
}
return success();
}
//===----------------------------------------------------------------------===//
// FromI64Op
//===----------------------------------------------------------------------===//
OpFoldResult FromI64Op::fold(llvm::ArrayRef<mlir::Attribute> operands) {
auto attr = operands[0].dyn_cast_or_null<mlir::IntegerAttr>();
if (attr) {
return attr;
} else {
return nullptr;
}
}
//===----------------------------------------------------------------------===//
// ToI64Op
//===----------------------------------------------------------------------===//
OpFoldResult ToI64Op::fold(llvm::ArrayRef<mlir::Attribute> operands) {
auto attr = operands[0].dyn_cast_or_null<mlir::IntegerAttr>();
if (attr) {
return attr;
} else {
return nullptr;
}
}
#define GET_OP_CLASSES
#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionOps.cpp.inc"