//===----------------------------------------------------------------------===// // // 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/Arith/IR/Arith.h" #include "mlir/Dialect/Complex/IR/Complex.h" #include "mlir/Dialect/ControlFlow/IR/ControlFlow.h" #include "mlir/Dialect/Linalg/IR/Linalg.h" #include "mlir/Dialect/Math/IR/Math.h" #include "mlir/Dialect/SCF/IR/SCF.h" #include "mlir/Dialect/SparseTensor/IR/SparseTensor.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 { public: void getDependentDialects(DialectRegistry ®istry) const override { registry.insert(); registry.insert(); registry.insert(); registry.insert(); registry.insert(); registry.insert(); registry.insert(); registry.insert(); TorchConversion::getBackendTypeConversionDependentDialects(registry); } void runOnOperation() override { MLIRContext *context = &getContext(); ConversionTarget target(*context); target.addLegalDialect< linalg::LinalgDialect, func::FuncDialect, cf::ControlFlowDialect, math::MathDialect, scf::SCFDialect, sparse_tensor::SparseTensorDialect, tensor::TensorDialect, arith::ArithDialect, complex::ComplexDialect>(); target.addLegalOp(); TypeConverter typeConverter; typeConverter.addConversion([](Type type) { return type; }); TorchConversion::setupBackendTypeConversion(target, typeConverter); RewritePatternSet patterns(context); 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> mlir::torch::createConvertTorchToLinalgPass() { return std::make_unique(); }