c7e24db412
This is work towards: https://github.com/llvm/llvm-project/issues/51652 This differential sets up the options and threads them through everywhere, but doesn't actually use them yet. The differential that finally makes use of them is D122061, which is the final differential in the chain that fixes bug 51652. Reviewed By: aartbik Differential Revision: https://reviews.llvm.org/D122054
68 lines
3.0 KiB
C++
68 lines
3.0 KiB
C++
//===- SparseTensorPipelines.cpp - Pipelines for sparse tensor code -------===//
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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/Pipelines/Passes.h"
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#include "mlir/Conversion/Passes.h"
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#include "mlir/Dialect/Arithmetic/Transforms/Passes.h"
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#include "mlir/Dialect/Bufferization/Transforms/Passes.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/Func/Transforms/Passes.h"
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#include "mlir/Dialect/Linalg/Passes.h"
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#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
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#include "mlir/Dialect/SparseTensor/Transforms/Passes.h"
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#include "mlir/Dialect/Tensor/Transforms/Passes.h"
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#include "mlir/Dialect/Vector/Transforms/Passes.h"
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#include "mlir/Pass/PassManager.h"
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using namespace mlir;
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using namespace mlir::sparse_tensor;
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//===----------------------------------------------------------------------===//
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// Pipeline implementation.
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//===----------------------------------------------------------------------===//
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void mlir::sparse_tensor::buildSparseCompiler(
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OpPassManager &pm, const SparseCompilerOptions &options) {
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// TODO(wrengr): ensure the original `pm` is for ModuleOp
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pm.addNestedPass<FuncOp>(createLinalgGeneralizationPass());
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pm.addPass(createLinalgElementwiseOpFusionPass());
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pm.addPass(createSparsificationPass(options.sparsificationOptions()));
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pm.addPass(createSparseTensorConversionPass(
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options.sparseTensorConversionOptions()));
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pm.addNestedPass<FuncOp>(createLinalgBufferizePass());
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pm.addNestedPass<FuncOp>(vector::createVectorBufferizePass());
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pm.addNestedPass<FuncOp>(createConvertLinalgToLoopsPass());
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pm.addNestedPass<FuncOp>(createConvertVectorToSCFPass());
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pm.addNestedPass<FuncOp>(createConvertSCFToCFPass());
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pm.addPass(func::createFuncBufferizePass());
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pm.addPass(arith::createConstantBufferizePass());
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pm.addNestedPass<FuncOp>(createTensorBufferizePass());
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pm.addNestedPass<FuncOp>(
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mlir::bufferization::createFinalizingBufferizePass());
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pm.addPass(createLowerAffinePass());
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pm.addPass(createConvertVectorToLLVMPass(options.lowerVectorToLLVMOptions()));
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pm.addPass(createMemRefToLLVMPass());
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pm.addNestedPass<FuncOp>(createConvertMathToLLVMPass());
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pm.addPass(createConvertFuncToLLVMPass());
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pm.addPass(createReconcileUnrealizedCastsPass());
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}
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//===----------------------------------------------------------------------===//
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// Pipeline registration.
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//===----------------------------------------------------------------------===//
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void mlir::sparse_tensor::registerSparseTensorPipelines() {
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PassPipelineRegistration<SparseCompilerOptions>(
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"sparse-compiler",
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"The standard pipeline for taking sparsity-agnostic IR using the"
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" sparse-tensor type, and lowering it to LLVM IR with concrete"
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" representations and algorithms for sparse tensors.",
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buildSparseCompiler);
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}
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