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//===- Bufferize.cpp - Bufferization for `tensor` dialect 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 `tensor` dialect ops
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Tensor/Transforms/BufferizableOpInterfaceImpl.h"
#include "mlir/Dialect/Tensor/Transforms/Passes.h"
#include "mlir/IR/ImplicitLocOpBuilder.h"
#include "mlir/Transforms/DialectConversion.h"
namespace mlir {
namespace tensor {
#define GEN_PASS_DEF_TENSORBUFFERIZE
#include "mlir/Dialect/Tensor/Transforms/Passes.h.inc"
} // namespace tensor
} // namespace mlir
using namespace mlir;
using namespace bufferization;
namespace {
struct TensorBufferizePass
: public tensor::impl::TensorBufferizeBase<TensorBufferizePass> {
void runOnOperation() override {
BufferizationOptions options = getPartialBufferizationOptions();
options.opFilter.allowDialect<tensor::TensorDialect>();
if (failed(bufferizeOp(getOperation(), options)))
signalPassFailure();
}
void getDependentDialects(DialectRegistry ®istry) const override {
registry
.insert<bufferization::BufferizationDialect, memref::MemRefDialect,
tensor::TensorDialect, scf::SCFDialect, arith::ArithDialect>();
tensor::registerBufferizableOpInterfaceExternalModels(registry);
}
};
} // namespace
std::unique_ptr<Pass> mlir::tensor::createTensorBufferizePass() {
return std::make_unique<TensorBufferizePass>();
}
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