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//===- InitTensorToAllocTensor.cpp - Lower tensor.empty to alloc_tensor ---===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Bufferization/Transforms/Passes.h"
#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
#include "mlir/Dialect/Bufferization/Transforms/Transforms.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
namespace mlir {
namespace bufferization {
#define GEN_PASS_DEF_EMPTYTENSORTOALLOCTENSOR
#include "mlir/Dialect/Bufferization/Transforms/Passes.h.inc"
} // namespace bufferization
} // namespace mlir
using namespace mlir;
using namespace mlir::bufferization;
using namespace mlir::tensor;
namespace {
struct EmptyTensorLoweringPattern : public OpRewritePattern<tensor::EmptyOp> {
using OpRewritePattern<tensor::EmptyOp>::OpRewritePattern;
LogicalResult matchAndRewrite(tensor::EmptyOp op,
PatternRewriter &rewriter) const override {
rewriter.replaceOpWithNewOp<bufferization::AllocTensorOp>(
op, op.getType(), op.getDynamicSizes());
return success();
}
};
struct EmptyTensorToAllocTensor
: public bufferization::impl::EmptyTensorToAllocTensorBase<
EmptyTensorToAllocTensor> {
EmptyTensorToAllocTensor() = default;
void runOnOperation() override;
void getDependentDialects(DialectRegistry ®istry) const override {
registry
.insert<tensor::TensorDialect, bufferization::BufferizationDialect>();
}
};
} // namespace
void bufferization::populateEmptyTensorToAllocTensorPattern(
RewritePatternSet &patterns) {
patterns.insert<EmptyTensorLoweringPattern>(patterns.getContext());
}
void EmptyTensorToAllocTensor::runOnOperation() {
Operation *op = getOperation();
RewritePatternSet patterns(op->getContext());
populateEmptyTensorToAllocTensorPattern(patterns);
if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns))))
signalPassFailure();
}
std::unique_ptr<Pass>
mlir::bufferization::createEmptyTensorToAllocTensorPass() {
return std::make_unique<EmptyTensorToAllocTensor>();
}
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