Files
clang-p2996/mlir/lib/Dialect/StandardOps/Transforms/Bufferize.cpp
Jacques Pienaar cfb72fd3a0 [mlir] Switch arith, llvm, std & shape dialects to accessors prefixed both form.
Following
https://llvm.discourse.group/t/psa-ods-generated-accessors-will-change-to-have-a-get-prefix-update-you-apis/4476,
this follows flipping these dialects to _Both prefixed form. This
changes the accessors to have a prefix. This was possibly mostly without
breaking breaking changes if the existing convenience methods were used.

(https://github.com/jpienaar/llvm-project/blob/main/clang-tools-extra/clang-tidy/misc/AddGetterCheck.cpp
was used to migrate the callers post flipping, using the output from
Operator.cpp)

Differential Revision: https://reviews.llvm.org/D112383
2021-10-24 18:36:33 -07:00

77 lines
2.8 KiB
C++

//===- Bufferize.cpp - Bufferization for std ops --------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file implements bufferization of std ops.
//
//===----------------------------------------------------------------------===//
#include "mlir/Transforms/Bufferize.h"
#include "PassDetail.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/SCF.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/Dialect/StandardOps/Transforms/Passes.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/IR/BlockAndValueMapping.h"
#include "mlir/Transforms/DialectConversion.h"
using namespace mlir;
namespace {
class BufferizeSelectOp : public OpConversionPattern<SelectOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(SelectOp op, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override {
if (!op.getCondition().getType().isa<IntegerType>())
return rewriter.notifyMatchFailure(op, "requires scalar condition");
rewriter.replaceOpWithNewOp<SelectOp>(op, adaptor.getCondition(),
adaptor.getTrueValue(),
adaptor.getFalseValue());
return success();
}
};
} // namespace
void mlir::populateStdBufferizePatterns(BufferizeTypeConverter &typeConverter,
RewritePatternSet &patterns) {
patterns.add<BufferizeSelectOp>(typeConverter, patterns.getContext());
}
namespace {
struct StdBufferizePass : public StdBufferizeBase<StdBufferizePass> {
void runOnFunction() override {
auto *context = &getContext();
BufferizeTypeConverter typeConverter;
RewritePatternSet patterns(context);
ConversionTarget target(*context);
target.addLegalDialect<scf::SCFDialect, StandardOpsDialect,
memref::MemRefDialect>();
populateStdBufferizePatterns(typeConverter, patterns);
// We only bufferize the case of tensor selected type and scalar condition,
// as that boils down to a select over memref descriptors (don't need to
// touch the data).
target.addDynamicallyLegalOp<SelectOp>([&](SelectOp op) {
return typeConverter.isLegal(op.getType()) ||
!op.getCondition().getType().isa<IntegerType>();
});
if (failed(
applyPartialConversion(getFunction(), target, std::move(patterns))))
signalPassFailure();
}
};
} // namespace
std::unique_ptr<Pass> mlir::createStdBufferizePass() {
return std::make_unique<StdBufferizePass>();
}