mirror of https://github.com/llvm/torch-mlir
94 lines
3.3 KiB
C++
94 lines
3.3 KiB
C++
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//===----------------------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v3.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-1.0 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/TorchToTensor/TorchToTensor.h"
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#include "../PassDetail.h"
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#include "mlir/Dialect/Arith/IR/Arith.h"
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#include "mlir/Dialect/Tensor/IR/Tensor.h"
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#include "mlir/Dialect/Traits.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/Transforms/DialectConversion.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/Torch/Utils/Utils.h"
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#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionDialect.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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namespace {
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class ConvertAtenShapeToTensorPatternOp
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: public OpConversionPattern<Aten_ShapeAsTensorOp> {
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public:
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using OpConversionPattern<Aten_ShapeAsTensorOp>::OpConversionPattern;
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using OpAdaptor = typename Aten_ShapeAsTensorOp::Adaptor;
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LogicalResult
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matchAndRewrite(Aten_ShapeAsTensorOp op, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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auto loc = op.getLoc();
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auto operand = adaptor.getOperands()[0];
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auto operandTy = operand.getType().cast<RankedTensorType>();
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auto resultTy =
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getTypeConverter()->convertType(op.getType()).cast<RankedTensorType>();
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int64_t rank = operandTy.getRank();
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SmallVector<Value> dims;
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for (int i = 0; i < rank; ++i) {
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Value dim = rewriter.createOrFold<tensor::DimOp>(loc, operand, i);
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dim = rewriter.createOrFold<arith::IndexCastOp>(
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loc, resultTy.getElementType(), dim);
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dims.push_back(dim);
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}
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Value tensor =
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rewriter.createOrFold<tensor::FromElementsOp>(op.getLoc(), dims);
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rewriter.replaceOp(op, tensor);
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return success();
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}
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};
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class ConvertTorchToTensor
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: public ConvertTorchToTensorBase<ConvertTorchToTensor> {
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public:
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void getDependentDialects(DialectRegistry ®istry) const override {
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registry.insert<tensor::TensorDialect>();
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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<arith::ArithDialect>();
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target.addLegalDialect<tensor::TensorDialect>();
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target.addIllegalOp<Torch::Aten_ShapeAsTensorOp>();
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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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patterns.add<ConvertAtenShapeToTensorPatternOp>(typeConverter, context);
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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::createConvertTorchToTensorPass() {
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return std::make_unique<ConvertTorchToTensor>();
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}
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