Files
clang-p2996/mlir/lib/Dialect/StandardOps/Transforms/Bufferize.cpp
River Riddle 4157455425 [mlir][Pass] Deprecate FunctionPass in favor of OperationPass<FuncOp>
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
2022-01-18 19:52:44 -08:00

79 lines
2.9 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/Dialect/Bufferization/Transforms/Bufferize.h"
#include "PassDetail.h"
#include "mlir/Dialect/Bufferization/IR/Bufferization.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(
bufferization::BufferizeTypeConverter &typeConverter,
RewritePatternSet &patterns) {
patterns.add<BufferizeSelectOp>(typeConverter, patterns.getContext());
}
namespace {
struct StdBufferizePass : public StdBufferizeBase<StdBufferizePass> {
void runOnOperation() override {
auto *context = &getContext();
bufferization::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(getOperation(), target,
std::move(patterns))))
signalPassFailure();
}
};
} // namespace
std::unique_ptr<Pass> mlir::createStdBufferizePass() {
return std::make_unique<StdBufferizePass>();
}