4157455425
The only benefit of FunctionPass is that it filters out function declarations. This isn't enough to justify carrying it around, as we can simplify filter out declarations when necessary within the pass. We can also explore with better scheduling primitives to filter out declarations at the pipeline level in the future. The definition of FunctionPass is left intact for now to allow time for downstream users to migrate. Differential Revision: https://reviews.llvm.org/D117182
69 lines
2.3 KiB
C++
69 lines
2.3 KiB
C++
//===- Bufferize.cpp - Bufferization for Arithmetic ops ---------*- 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 "PassDetail.h"
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#include "mlir/Dialect/Arithmetic/Transforms/Passes.h"
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#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
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#include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
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#include "mlir/Dialect/MemRef/IR/MemRef.h"
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using namespace mlir;
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namespace {
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/// Bufferize arith.index_cast.
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struct BufferizeIndexCastOp : public OpConversionPattern<arith::IndexCastOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(arith::IndexCastOp op, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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auto tensorType = op.getType().cast<RankedTensorType>();
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rewriter.replaceOpWithNewOp<arith::IndexCastOp>(
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op, adaptor.getIn(),
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MemRefType::get(tensorType.getShape(), tensorType.getElementType()));
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return success();
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}
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};
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/// Pass to bufferize Arithmetic ops.
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struct ArithmeticBufferizePass
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: public ArithmeticBufferizeBase<ArithmeticBufferizePass> {
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void runOnOperation() override {
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bufferization::BufferizeTypeConverter typeConverter;
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RewritePatternSet patterns(&getContext());
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ConversionTarget target(getContext());
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target.addLegalDialect<arith::ArithmeticDialect, memref::MemRefDialect>();
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arith::populateArithmeticBufferizePatterns(typeConverter, patterns);
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target.addDynamicallyLegalOp<arith::IndexCastOp>(
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[&](arith::IndexCastOp op) {
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return typeConverter.isLegal(op.getType());
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});
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if (failed(applyPartialConversion(getOperation(), target,
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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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void mlir::arith::populateArithmeticBufferizePatterns(
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bufferization::BufferizeTypeConverter &typeConverter,
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RewritePatternSet &patterns) {
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patterns.add<BufferizeIndexCastOp>(typeConverter, patterns.getContext());
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}
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std::unique_ptr<Pass> mlir::arith::createArithmeticBufferizePass() {
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return std::make_unique<ArithmeticBufferizePass>();
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}
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