mirror of https://github.com/llvm/torch-mlir
122 lines
4.5 KiB
C++
122 lines
4.5 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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//
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//===----------------------------------------------------------------------===//
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#include "npcomp/Conversion/TorchToStd/TorchToStd.h"
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#include "../PassDetail.h"
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#include "mlir/Dialect/StandardOps/IR/Ops.h"
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#include "mlir/Dialect/Traits.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "npcomp/Dialect/Torch/IR/TorchDialect.h"
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#include "npcomp/Dialect/Torch/IR/TorchOps.h"
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#include "npcomp/Dialect/Torch/Transforms/BackendTypeConversion.h"
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using namespace mlir;
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using namespace mlir::NPCOMP;
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using namespace mlir::NPCOMP::Torch;
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// -----------------------------------------------------------------------------
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// Patterns (as this grows, it should be organized into multiple files)
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// -----------------------------------------------------------------------------
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// This is going to eventually be O(#torch operators), which is in the 100s.
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namespace {
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// Note: Confusingly, ATen's "dim" means "number of dimensions" which is what
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// MLIR calls "rank".
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class ConvertAtenDimOp : public OpConversionPattern<AtenDimOp> {
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public:
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(AtenDimOp op, ArrayRef<Value> operands,
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ConversionPatternRewriter &rewriter) const override {
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auto rank = rewriter.create<RankOp>(op->getLoc(), operands[0]);
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rewriter.replaceOpWithNewOp<IndexCastOp>(
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op, getTypeConverter()->convertType(op.getType()), rank);
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return success();
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}
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};
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} // namespace
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namespace {
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class ConvertAtenNeIntOp : public OpConversionPattern<AtenNeIntOp> {
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public:
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(AtenNeIntOp op, ArrayRef<Value> operands,
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ConversionPatternRewriter &rewriter) const override {
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rewriter.replaceOpWithNewOp<CmpIOp>(op, CmpIPredicate::ne, operands[0],
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operands[1]);
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return success();
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}
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};
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} // namespace
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namespace {
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class ConvertAtenGtIntOp : public OpConversionPattern<AtenGtIntOp> {
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public:
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(AtenGtIntOp op, ArrayRef<Value> operands,
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ConversionPatternRewriter &rewriter) const override {
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rewriter.replaceOpWithNewOp<CmpIOp>(op, CmpIPredicate::sgt, operands[0],
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operands[1]);
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return success();
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}
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};
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} // namespace
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LogicalResult convertTensorOp(TensorOp op, PatternRewriter &rewriter) {
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auto constant = rewriter.create<ConstantOp>(op->getLoc(), op.value());
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auto vtensor = rewriter.create<FromBuiltinTensorOp>(op->getLoc(), constant);
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Value result = copyTensorToType(rewriter, op->getLoc(),
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op.getType().cast<BaseTensorType>(), vtensor);
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rewriter.replaceOp(op, {result});
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return success();
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}
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// -----------------------------------------------------------------------------
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// The pass
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// -----------------------------------------------------------------------------
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namespace {
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class ConvertTorchToStd : public ConvertTorchToStdBase<ConvertTorchToStd> {
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public:
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void getDependentDialects(DialectRegistry ®istry) const override {
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registry.insert<StandardOpsDialect>();
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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<Torch::TorchDialect, StandardOpsDialect>();
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TypeConverter typeConverter;
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typeConverter.addConversion([](Type type) { return type; });
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setupBackendTypeConversion(target, typeConverter);
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RewritePatternSet patterns(context);
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target.addIllegalOp<AtenDimOp>();
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patterns.add<ConvertAtenDimOp>(typeConverter, context);
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target.addIllegalOp<AtenNeIntOp>();
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patterns.add<ConvertAtenNeIntOp>(typeConverter, context);
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target.addIllegalOp<AtenGtIntOp>();
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patterns.add<ConvertAtenGtIntOp>(typeConverter, context);
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target.addIllegalOp<TensorOp>();
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patterns.add(convertTensorOp);
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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<FuncOp>>
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mlir::NPCOMP::createConvertTorchToStdPass() {
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return std::make_unique<ConvertTorchToStd>();
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}
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