129d6e554e
This is almost entirely mechanical. Differential Revision: https://reviews.llvm.org/D93357
79 lines
2.7 KiB
C++
79 lines
2.7 KiB
C++
//===- Bufferize.cpp - Bufferization for `tensor` dialect ops -------------===//
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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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//
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// This file implements bufferization of `tensor` dialect ops
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Transforms/Bufferize.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/Tensor/IR/Tensor.h"
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#include "mlir/Dialect/Tensor/Transforms/Passes.h"
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#include "mlir/Transforms/DialectConversion.h"
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using namespace mlir;
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namespace {
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class BufferizeCastOp : public OpConversionPattern<tensor::CastOp> {
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public:
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(tensor::CastOp op, ArrayRef<Value> operands,
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ConversionPatternRewriter &rewriter) const override {
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auto resultType = getTypeConverter()->convertType(op.getType());
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rewriter.replaceOpWithNewOp<MemRefCastOp>(op, resultType, operands[0]);
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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 BufferizeExtractOp : public OpConversionPattern<tensor::ExtractOp> {
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public:
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(tensor::ExtractOp op, ArrayRef<Value> operands,
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ConversionPatternRewriter &rewriter) const override {
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tensor::ExtractOp::Adaptor adaptor(operands);
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rewriter.replaceOpWithNewOp<LoadOp>(op, adaptor.tensor(),
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adaptor.indices());
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return success();
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}
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};
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} // namespace
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void mlir::populateTensorBufferizePatterns(
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MLIRContext *context, BufferizeTypeConverter &typeConverter,
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OwningRewritePatternList &patterns) {
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patterns.insert<BufferizeCastOp, BufferizeExtractOp>(typeConverter, context);
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}
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namespace {
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struct TensorBufferizePass : public TensorBufferizeBase<TensorBufferizePass> {
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void runOnFunction() override {
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auto *context = &getContext();
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BufferizeTypeConverter typeConverter;
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OwningRewritePatternList patterns;
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ConversionTarget target(*context);
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populateTensorBufferizePatterns(context, typeConverter, patterns);
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target.addIllegalOp<tensor::CastOp, tensor::ExtractOp>();
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target.addLegalDialect<StandardOpsDialect>();
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if (failed(
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applyPartialConversion(getFunction(), target, std::move(patterns))))
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signalPassFailure();
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}
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};
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} // namespace
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std::unique_ptr<Pass> mlir::createTensorBufferizePass() {
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return std::make_unique<TensorBufferizePass>();
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}
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