torch-mlir/lib/Conversion/TorchToLinalg/TorchToLinalg.cpp

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4.4 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/Conversion/TorchToLinalg/TorchToLinalg.h"
#include "../PassDetail.h"
#include "PopulatePatterns.h"
#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
#include "mlir/Dialect/ControlFlow/IR/ControlFlow.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "torch-mlir/Dialect/Torch/IR/TorchDialect.h"
#include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionDialect.h"
#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionOps.h"
#include "torch-mlir/Dialect/TorchConversion/Transforms/BackendTypeConversion.h"
using namespace mlir;
using namespace mlir::torch;
using namespace mlir::torch::Torch;
// -----------------------------------------------------------------------------
// The pass
// -----------------------------------------------------------------------------
// Patterns for individual ops should live in one of the other files, and
// added via the relevant `populate*PatternsAndLegality` functions.
// This file is just for the pass definition itself.
namespace {
class ConvertTorchToLinalg
: public ConvertTorchToLinalgBase<ConvertTorchToLinalg> {
public:
void getDependentDialects(DialectRegistry &registry) const override {
registry.insert<linalg::LinalgDialect>();
registry.insert<math::MathDialect>();
registry.insert<func::FuncDialect>();
registry.insert<tensor::TensorDialect>();
registry.insert<arith::ArithmeticDialect>();
registry.insert<cf::ControlFlowDialect>();
TorchConversion::getBackendTypeConversionDependentDialects(registry);
}
void runOnOperation() override {
MLIRContext *context = &getContext();
ConversionTarget target(*context);
target.addLegalDialect<linalg::LinalgDialect, func::FuncDialect,
cf::ControlFlowDialect, math::MathDialect,
tensor::TensorDialect, arith::ArithmeticDialect>();
target.addLegalOp<TorchConversion::GetNextSeedOp>();
TypeConverter typeConverter;
typeConverter.addConversion([](Type type) { return type; });
TorchConversion::setupBackendTypeConversion(target, typeConverter);
RewritePatternSet patterns(context);
#ifdef TORCH_MLIR_CUSTOM_OP_EXAMPLE
torch_to_linalg::populateCustomOpExamplePatternsAndLegality(
typeConverter, patterns, target);
#endif // TORCH_MLIR_CUSTOM_OP_EXAMPLE
torch_to_linalg::populateTensorScalarInteropPatternsAndLegality(
typeConverter, patterns, target);
torch_to_linalg::populateLinearPatternsAndLegality(typeConverter, patterns,
target);
torch_to_linalg::populatePoolingPatternsAndLegality(typeConverter, patterns,
target);
torch_to_linalg::populateRandomPatternsAndLegality(typeConverter, patterns,
target);
torch_to_linalg::populateUncategorizedPatternsAndLegality(typeConverter,
patterns, target);
torch_to_linalg::populateReductionPatternsAndLegality(typeConverter,
patterns, target);
torch_to_linalg::populateDataMovementPatternsAndLegality(typeConverter,
patterns, target);
torch_to_linalg::populateIndirectDataMovementPatternsAndLegality(
typeConverter, patterns, target);
torch_to_linalg::populateTensorConstructorsPatternsAndLegality(
typeConverter, patterns, target);
if (failed(applyPartialConversion(getOperation(), target,
std::move(patterns))))
return signalPassFailure();
}
};
} // namespace
std::unique_ptr<OperationPass<func::FuncOp>>
mlir::torch::createConvertTorchToLinalgPass() {
return std::make_unique<ConvertTorchToLinalg>();
}