74 lines
2.6 KiB
C++
74 lines
2.6 KiB
C++
//===- DenseBufferizationPass.cpp - Dense bufferization pass --------------===//
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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 "mlir/Dialect/SparseTensor/Transforms/Passes.h"
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#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
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#include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
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#include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
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using namespace mlir;
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using namespace mlir::func;
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namespace mlir {
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namespace sparse_tensor {
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/// Return `true` if one of the given types is a sparse tensor type.
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static bool containsSparseTensor(TypeRange types) {
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for (Type t : types)
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if (getSparseTensorEncoding(t))
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return true;
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return false;
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}
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/// A pass that bufferizes only dense tensor ops and ignores all sparse tensor
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/// ops. No buffer copies are inserted. All tensor OpOperands must be
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/// inplacable.
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class BufferizeDenseOpsPass
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: public PassWrapper<BufferizeDenseOpsPass, OperationPass<ModuleOp>> {
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public:
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BufferizeDenseOpsPass(
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const bufferization::OneShotBufferizationOptions &options)
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: options(options) {}
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void runOnOperation() override {
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// Disallow all sparse tensor ops, so that only dense tensor ops are
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// bufferized.
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bufferization::OpFilter opFilter;
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opFilter.allowOperation([&](Operation *op) {
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if (containsSparseTensor(TypeRange(op->getResults())) ||
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containsSparseTensor(TypeRange(op->getOperands())))
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return false;
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if (auto funcOp = dyn_cast<func::FuncOp>(op)) {
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FunctionType funcType = funcOp.getFunctionType();
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if (containsSparseTensor(funcType.getInputs()) ||
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containsSparseTensor(funcType.getResults()))
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return false;
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}
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return true;
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});
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if (failed(bufferization::bufferizeOp(getOperation(), options,
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/*copyBeforeWrite=*/false,
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&opFilter)))
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signalPassFailure();
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}
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private:
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bufferization::OneShotBufferizationOptions options;
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};
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} // namespace sparse_tensor
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} // namespace mlir
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std::unique_ptr<Pass> mlir::createDenseBufferizationPass(
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const bufferization::OneShotBufferizationOptions &options) {
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return std::make_unique<mlir::sparse_tensor::BufferizeDenseOpsPass>(options);
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}
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