forked from OSchip/llvm-project
94 lines
4.1 KiB
C++
94 lines
4.1 KiB
C++
//===- SparseTensorPipelines.cpp - Pipelines for sparse tensor code -------===//
|
|
//
|
|
// 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/SparseTensor/Pipelines/Passes.h"
|
|
|
|
#include "mlir/Conversion/Passes.h"
|
|
#include "mlir/Dialect/Arith/Transforms/Passes.h"
|
|
#include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
|
|
#include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
|
|
#include "mlir/Dialect/Bufferization/Transforms/Passes.h"
|
|
#include "mlir/Dialect/Func/IR/FuncOps.h"
|
|
#include "mlir/Dialect/Linalg/Passes.h"
|
|
#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
|
|
#include "mlir/Dialect/SparseTensor/Transforms/Passes.h"
|
|
#include "mlir/Pass/PassManager.h"
|
|
#include "mlir/Transforms/Passes.h"
|
|
|
|
using namespace mlir;
|
|
using namespace mlir::sparse_tensor;
|
|
|
|
/// Return configuration options for One-Shot Bufferize.
|
|
static bufferization::OneShotBufferizationOptions
|
|
getBufferizationOptions(bool analysisOnly) {
|
|
using namespace bufferization;
|
|
OneShotBufferizationOptions options;
|
|
options.bufferizeFunctionBoundaries = true;
|
|
// TODO(springerm): To spot memory leaks more easily, returning dense allocs
|
|
// should be disallowed.
|
|
options.allowReturnAllocs = true;
|
|
options.functionBoundaryTypeConversion = LayoutMapOption::IdentityLayoutMap;
|
|
options.unknownTypeConverterFn = [](Value value, Attribute memorySpace,
|
|
const BufferizationOptions &options) {
|
|
return getMemRefTypeWithStaticIdentityLayout(
|
|
value.getType().cast<TensorType>(), memorySpace);
|
|
};
|
|
if (analysisOnly) {
|
|
options.testAnalysisOnly = true;
|
|
options.printConflicts = true;
|
|
}
|
|
return options;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Pipeline implementation.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
void mlir::sparse_tensor::buildSparseCompiler(
|
|
OpPassManager &pm, const SparseCompilerOptions &options) {
|
|
pm.addNestedPass<func::FuncOp>(createLinalgGeneralizationPass());
|
|
pm.addPass(createSparsificationAndBufferizationPass(
|
|
getBufferizationOptions(options.testBufferizationAnalysisOnly),
|
|
options.sparsificationOptions(), options.sparseTensorConversionOptions(),
|
|
options.enableRuntimeLibrary, options.enableBufferInitialization));
|
|
if (options.testBufferizationAnalysisOnly)
|
|
return;
|
|
pm.addNestedPass<func::FuncOp>(createCanonicalizerPass());
|
|
pm.addNestedPass<func::FuncOp>(
|
|
mlir::bufferization::createFinalizingBufferizePass());
|
|
// TODO(springerm): Add sparse support to the BufferDeallocation pass and add
|
|
// it to this pipeline.
|
|
pm.addNestedPass<func::FuncOp>(createConvertLinalgToLoopsPass());
|
|
pm.addNestedPass<func::FuncOp>(createConvertVectorToSCFPass());
|
|
pm.addNestedPass<func::FuncOp>(createConvertSCFToCFPass());
|
|
pm.addPass(createLowerAffinePass());
|
|
pm.addPass(createConvertVectorToLLVMPass(options.lowerVectorToLLVMOptions()));
|
|
pm.addPass(createMemRefToLLVMConversionPass());
|
|
pm.addNestedPass<func::FuncOp>(createConvertComplexToStandardPass());
|
|
pm.addNestedPass<mlir::func::FuncOp>(mlir::arith::createArithExpandOpsPass());
|
|
pm.addNestedPass<func::FuncOp>(createConvertMathToLLVMPass());
|
|
pm.addPass(createConvertMathToLibmPass());
|
|
pm.addPass(createConvertComplexToLibmPass());
|
|
pm.addPass(createConvertComplexToLLVMPass());
|
|
pm.addPass(createConvertFuncToLLVMPass());
|
|
pm.addPass(createReconcileUnrealizedCastsPass());
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Pipeline registration.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
void mlir::sparse_tensor::registerSparseTensorPipelines() {
|
|
PassPipelineRegistration<SparseCompilerOptions>(
|
|
"sparse-compiler",
|
|
"The standard pipeline for taking sparsity-agnostic IR using the"
|
|
" sparse-tensor type, and lowering it to LLVM IR with concrete"
|
|
" representations and algorithms for sparse tensors.",
|
|
buildSparseCompiler);
|
|
}
|