mirror of https://github.com/llvm/torch-mlir
97 lines
4.3 KiB
C++
97 lines
4.3 KiB
C++
//===----------------------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// Also available under a BSD-style license. See LICENSE.
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//
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//===----------------------------------------------------------------------===//
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#include "torch-mlir/Conversion/TorchToLinalg/TorchToLinalg.h"
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#include "../PassDetail.h"
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#include "PopulatePatterns.h"
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#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
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#include "mlir/Dialect/ControlFlow/IR/ControlFlow.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/Linalg/IR/Linalg.h"
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#include "mlir/Dialect/Math/IR/Math.h"
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#include "mlir/Dialect/Tensor/IR/Tensor.h"
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#include "torch-mlir/Dialect/Torch/IR/TorchDialect.h"
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#include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
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#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionDialect.h"
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#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionOps.h"
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#include "torch-mlir/Dialect/TorchConversion/Transforms/BackendTypeConversion.h"
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using namespace mlir;
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using namespace mlir::torch;
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using namespace mlir::torch::Torch;
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// -----------------------------------------------------------------------------
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// The pass
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// -----------------------------------------------------------------------------
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// Patterns for individual ops should live in one of the other files, and
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// added via the relevant `populate*PatternsAndLegality` functions.
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// This file is just for the pass definition itself.
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namespace {
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class ConvertTorchToLinalg
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: public ConvertTorchToLinalgBase<ConvertTorchToLinalg> {
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public:
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void getDependentDialects(DialectRegistry ®istry) const override {
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registry.insert<linalg::LinalgDialect>();
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registry.insert<math::MathDialect>();
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registry.insert<func::FuncDialect>();
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registry.insert<tensor::TensorDialect>();
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registry.insert<arith::ArithmeticDialect>();
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registry.insert<cf::ControlFlowDialect>();
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TorchConversion::getBackendTypeConversionDependentDialects(registry);
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}
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void runOnOperation() override {
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MLIRContext *context = &getContext();
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ConversionTarget target(*context);
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target.addLegalDialect<linalg::LinalgDialect, func::FuncDialect,
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cf::ControlFlowDialect, math::MathDialect,
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tensor::TensorDialect, arith::ArithmeticDialect>();
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target.addLegalOp<TorchConversion::GetNextSeedOp>();
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TypeConverter typeConverter;
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typeConverter.addConversion([](Type type) { return type; });
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TorchConversion::setupBackendTypeConversion(target, typeConverter);
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RewritePatternSet patterns(context);
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//torch_to_linalg::populateCustomOpExamplePatternsAndLegality(
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// typeConverter, patterns, target);
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torch_to_linalg::populateTensorScalarInteropPatternsAndLegality(
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typeConverter, patterns, target);
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torch_to_linalg::populateLinearPatternsAndLegality(typeConverter, patterns,
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target);
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torch_to_linalg::populatePoolingPatternsAndLegality(typeConverter, patterns,
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target);
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torch_to_linalg::populateRandomPatternsAndLegality(typeConverter, patterns,
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target);
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torch_to_linalg::populateUncategorizedPatternsAndLegality(typeConverter,
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patterns, target);
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torch_to_linalg::populateReductionPatternsAndLegality(typeConverter,
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patterns, target);
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torch_to_linalg::populateDataMovementPatternsAndLegality(typeConverter,
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patterns, target);
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torch_to_linalg::populateIndirectDataMovementPatternsAndLegality(
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typeConverter, patterns, target);
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torch_to_linalg::populateTensorConstructorsPatternsAndLegality(
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typeConverter, patterns, target);
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if (failed(applyPartialConversion(getOperation(), target,
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std::move(patterns))))
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return signalPassFailure();
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}
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};
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} // namespace
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std::unique_ptr<OperationPass<func::FuncOp>>
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mlir::torch::createConvertTorchToLinalgPass() {
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return std::make_unique<ConvertTorchToLinalg>();
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}
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