mirror of
https://github.com/intel/llvm.git
synced 2026-01-26 12:26:52 +08:00
0f304ef017
This helps to prevent tsan failures when users inadvertantly mutate the context in a non-safe way. Differential Revision: https://reviews.llvm.org/D112021
349 lines
14 KiB
C++
349 lines
14 KiB
C++
//===- TestLinalgFusionTransforms.cpp - Test Linalg fusion patterns -------===//
|
|
//
|
|
// 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 logic for testing Linalg fusion patterns.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include "mlir/Dialect/Func/IR/FuncOps.h"
|
|
#include "mlir/Dialect/Linalg/Analysis/DependenceAnalysis.h"
|
|
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
|
|
#include "mlir/Dialect/SCF/Transforms.h"
|
|
#include "mlir/Pass/Pass.h"
|
|
#include "mlir/Pass/PassManager.h"
|
|
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
|
|
#include "mlir/Transforms/Passes.h"
|
|
|
|
using namespace mlir;
|
|
using namespace mlir::linalg;
|
|
|
|
template <LinalgTilingLoopType LoopType>
|
|
static void fillFusionPatterns(MLIRContext *context,
|
|
const LinalgDependenceGraph &dependenceGraph,
|
|
RewritePatternSet &patterns) {
|
|
patterns.add<LinalgTileAndFusePattern<MatmulOp>,
|
|
LinalgTileAndFusePattern<Conv2DOp>>(
|
|
context, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes({32, 64, 16}).setLoopType(LoopType),
|
|
LinalgFusionOptions().setIndicesToFuse({2}),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "basic_fusion"),
|
|
StringAttr::get(context, "after_basic_fusion")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_basic_fusion_producer")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_basic_fusion_original")));
|
|
|
|
patterns.add<LinalgTileAndFusePattern<MatmulOp>>(
|
|
context, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes({32, 64, 16}).setLoopType(LoopType),
|
|
LinalgFusionOptions().setIndicesToFuse({0}),
|
|
LinalgTransformationFilter(StringAttr::get(context, "lhs_fusion"),
|
|
StringAttr::get(context, "after_lhs_fusion")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_lhs_fusion_producer")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_lhs_fusion_original")));
|
|
|
|
patterns.add<LinalgTileAndFusePattern<MatmulOp>>(
|
|
context, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes({32, 64, 16}).setLoopType(LoopType),
|
|
LinalgFusionOptions().setIndicesToFuse({2}),
|
|
LinalgTransformationFilter(StringAttr::get(context, "out_fusion"),
|
|
StringAttr::get(context, "after_out_fusion")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_out_fusion_producer")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_out_fusion_original")));
|
|
|
|
patterns.add<LinalgTileAndFusePattern<MatmulOp>>(
|
|
context, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes({32, 64, 16}).setLoopType(LoopType),
|
|
LinalgFusionOptions().setIndicesToFuse({1}),
|
|
LinalgTransformationFilter(StringAttr::get(context, "rhs_fusion"),
|
|
StringAttr::get(context, "after_rhs_fusion")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_rhs_fusion_producer")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_rhs_fusion_original")));
|
|
|
|
patterns.add<LinalgTileAndFusePattern<MatmulOp>>(
|
|
context, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes({32, 64, 16}).setLoopType(LoopType),
|
|
LinalgFusionOptions().setIndicesToFuse({0, 2}),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "two_operand_fusion"),
|
|
StringAttr::get(context, "after_two_operand_fusion")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_two_operand_fusion_producer")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_two_operand_fusion_original")));
|
|
|
|
patterns.add<LinalgTileAndFusePattern<GenericOp>>(
|
|
context, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes({32, 64}).setLoopType(LoopType),
|
|
LinalgFusionOptions().setIndicesToFuse({0, 1}),
|
|
LinalgTransformationFilter(
|
|
StringAttr::get(context, "transpose_fusion"),
|
|
StringAttr::get(context, "after_transpose_fusion")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_transpose_fusion_producer")),
|
|
LinalgTransformationFilter(
|
|
ArrayRef<StringAttr>(),
|
|
StringAttr::get(context, "after_transpose_fusion_original")));
|
|
}
|
|
|
|
namespace {
|
|
template <LinalgTilingLoopType LoopType>
|
|
struct TestLinalgFusionTransforms
|
|
: public PassWrapper<TestLinalgFusionTransforms<LoopType>,
|
|
OperationPass<FuncOp>> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestLinalgFusionTransforms)
|
|
|
|
void getDependentDialects(DialectRegistry ®istry) const override {
|
|
registry.insert<AffineDialect, linalg::LinalgDialect, memref::MemRefDialect,
|
|
scf::SCFDialect>();
|
|
}
|
|
TestLinalgFusionTransforms() = default;
|
|
TestLinalgFusionTransforms(const TestLinalgFusionTransforms &pass) {}
|
|
|
|
void runOnOperation() override {
|
|
MLIRContext *context = &this->getContext();
|
|
FuncOp funcOp = this->getOperation();
|
|
RewritePatternSet fusionPatterns(context);
|
|
Aliases alias;
|
|
LinalgDependenceGraph dependenceGraph =
|
|
LinalgDependenceGraph::buildDependenceGraph(alias, funcOp);
|
|
fillFusionPatterns<LoopType>(context, dependenceGraph, fusionPatterns);
|
|
(void)applyPatternsAndFoldGreedily(funcOp, std::move(fusionPatterns));
|
|
}
|
|
};
|
|
|
|
struct TestLinalgFusionTransformsParallelLoops
|
|
: public TestLinalgFusionTransforms<LinalgTilingLoopType::ParallelLoops> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(
|
|
TestLinalgFusionTransformsParallelLoops)
|
|
|
|
StringRef getArgument() const final {
|
|
return "test-linalg-fusion-transform-patterns";
|
|
}
|
|
StringRef getDescription() const final {
|
|
return "Test Linalg fusion transformation patterns by applying them "
|
|
"greedily.";
|
|
}
|
|
};
|
|
|
|
struct TestLinalgFusionTransformsLoops
|
|
: public TestLinalgFusionTransforms<LinalgTilingLoopType::Loops> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestLinalgFusionTransformsLoops)
|
|
|
|
StringRef getArgument() const final {
|
|
return "test-linalg-tensor-fusion-transform-patterns";
|
|
}
|
|
StringRef getDescription() const final {
|
|
return "Test Linalg on tensor fusion transformation "
|
|
"patterns by applying them greedily.";
|
|
}
|
|
};
|
|
|
|
struct TestLinalgFusionTransformsTiledLoops
|
|
: public TestLinalgFusionTransforms<LinalgTilingLoopType::TiledLoops> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(
|
|
TestLinalgFusionTransformsTiledLoops)
|
|
|
|
StringRef getArgument() const final {
|
|
return "test-linalg-tiled-loop-fusion-transform-patterns";
|
|
}
|
|
StringRef getDescription() const final {
|
|
return "Test Linalg on tensor fusion transformation "
|
|
"patterns by applying them greedily.";
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
static LogicalResult fuseLinalgOpsGreedily(FuncOp f) {
|
|
OpBuilder b(f);
|
|
DenseSet<Operation *> eraseSet;
|
|
|
|
// Save original Linalg ops, we only want to make a pass over those.
|
|
SmallVector<LinalgOp, 8> linalgOps;
|
|
f.walk([&](LinalgOp op) {
|
|
// TODO: support multi-results.
|
|
if (op->getNumResults() <= 1)
|
|
linalgOps.push_back(op);
|
|
});
|
|
|
|
// Tile and Fuse for tensors inputs (TODO: all tensor operands).
|
|
bool changed = false;
|
|
for (LinalgOp linalgOp : llvm::reverse(linalgOps)) {
|
|
for (OpOperand *opOperand : linalgOp.getInputAndOutputOperands()) {
|
|
if (opOperand->get().getType().isa<MemRefType>()) {
|
|
// TODO: LinalgDependenceGraph should be able to update itself.
|
|
// The current naive and expensive reconstruction of the graph should be
|
|
// removed.
|
|
linalg::Aliases aliases;
|
|
linalg::LinalgDependenceGraph graph(aliases, linalgOps);
|
|
auto info = fuseProducerOfBuffer(b, *opOperand, graph);
|
|
if (failed(info))
|
|
continue;
|
|
auto *originalOp = info->originalProducer.getOperation();
|
|
eraseSet.insert(originalOp);
|
|
auto *originalOpInLinalgOpsVector =
|
|
std::find(linalgOps.begin(), linalgOps.end(), originalOp);
|
|
*originalOpInLinalgOpsVector = info->fusedProducer.getOperation();
|
|
changed = true;
|
|
} else if (opOperand->get().getType().isa<RankedTensorType>()) {
|
|
// Tile and Fuse tensor input.
|
|
if (opOperand->getOperandNumber() >= linalgOp.getNumInputs())
|
|
continue;
|
|
auto info = fuseProducerOfTensor(b, *opOperand);
|
|
if (failed(info))
|
|
continue;
|
|
auto *originalOp = info->originalProducer.getOperation();
|
|
auto *originalOpInLinalgOpsVector =
|
|
std::find(linalgOps.begin(), linalgOps.end(), originalOp);
|
|
*originalOpInLinalgOpsVector = info->fusedProducer.getOperation();
|
|
// Don't mark for erasure in the tensor case, let DCE handle this.
|
|
changed = true;
|
|
}
|
|
}
|
|
}
|
|
// The `fuseProducerOfBuffer` function performs structural checks and in
|
|
// particular that no covering read or write exist between the consumer and
|
|
// the producer. As a consequence, the only fusions that may occur preserve
|
|
// subsequent dependences and are guaranteed by construction to produce the
|
|
// whole view. We may thus erase the producer once it is fused.
|
|
for (auto *e : eraseSet)
|
|
e->erase();
|
|
|
|
return changed ? success() : failure();
|
|
}
|
|
|
|
namespace {
|
|
struct TestLinalgGreedyFusion
|
|
: public PassWrapper<TestLinalgGreedyFusion, OperationPass<FuncOp>> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestLinalgGreedyFusion)
|
|
|
|
void getDependentDialects(DialectRegistry ®istry) const override {
|
|
registry.insert<AffineDialect, linalg::LinalgDialect, memref::MemRefDialect,
|
|
scf::SCFDialect>();
|
|
}
|
|
StringRef getArgument() const final { return "test-linalg-greedy-fusion"; }
|
|
StringRef getDescription() const final {
|
|
return "Test Linalg fusion by applying a greedy test transformation.";
|
|
}
|
|
void runOnOperation() override {
|
|
MLIRContext *context = &getContext();
|
|
RewritePatternSet patterns =
|
|
linalg::getLinalgTilingCanonicalizationPatterns(context);
|
|
patterns.add<ExtractSliceOfPadTensorSwapPattern>(context);
|
|
scf::populateSCFForLoopCanonicalizationPatterns(patterns);
|
|
FrozenRewritePatternSet frozenPatterns(std::move(patterns));
|
|
OpPassManager pm(FuncOp::getOperationName());
|
|
pm.addPass(createLoopInvariantCodeMotionPass());
|
|
pm.addPass(createCanonicalizerPass());
|
|
pm.addPass(createCSEPass());
|
|
do {
|
|
(void)applyPatternsAndFoldGreedily(getOperation(), frozenPatterns);
|
|
if (failed(runPipeline(pm, getOperation())))
|
|
this->signalPassFailure();
|
|
} while (succeeded(fuseLinalgOpsGreedily(getOperation())));
|
|
}
|
|
};
|
|
|
|
/// Pass to test tile and fuse of sequence of operations. Intended only for
|
|
/// testing.
|
|
struct TestLinalgTileAndFuseSequencePass
|
|
: public PassWrapper<TestLinalgTileAndFuseSequencePass,
|
|
OperationPass<FuncOp>> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(
|
|
TestLinalgTileAndFuseSequencePass)
|
|
|
|
StringRef getArgument() const final { return "test-linalg-tile-and-fuse"; }
|
|
StringRef getDescription() const final {
|
|
return "Test Linalg tiling and fusion of a sequence of Linalg operations.";
|
|
}
|
|
TestLinalgTileAndFuseSequencePass() = default;
|
|
TestLinalgTileAndFuseSequencePass(
|
|
const TestLinalgTileAndFuseSequencePass &pass)
|
|
: PassWrapper(pass){};
|
|
|
|
ListOption<int64_t> tileSizes{*this, "tile-sizes",
|
|
llvm::cl::desc("Tile sizes to use for ops"),
|
|
llvm::cl::ZeroOrMore};
|
|
|
|
void getDependentDialects(DialectRegistry ®istry) const override {
|
|
registry.insert<AffineDialect, linalg::LinalgDialect, memref::MemRefDialect,
|
|
scf::SCFDialect>();
|
|
}
|
|
|
|
void runOnOperation() override {
|
|
FuncOp funcOp = getOperation();
|
|
auto &blocks = funcOp.getBody().getBlocks();
|
|
if (!llvm::hasSingleElement(blocks)) {
|
|
return;
|
|
}
|
|
SmallVector<LinalgOp, 2> linalgOps =
|
|
llvm::to_vector<2>(blocks.front().getOps<LinalgOp>());
|
|
Aliases aliases;
|
|
LinalgDependenceGraph dependenceGraph(aliases, linalgOps);
|
|
OpBuilder builder(funcOp.getContext());
|
|
linalg::LinalgTilingLoopType loopType = LinalgTilingLoopType::ParallelLoops;
|
|
if (llvm::any_of(linalgOps, [](LinalgOp linalgOp) {
|
|
return linalgOp.hasTensorSemantics();
|
|
}))
|
|
loopType = LinalgTilingLoopType::Loops;
|
|
Optional<TiledAndFusedLinalgOps> tileAndFuseOps = tileAndFuseLinalgOps(
|
|
builder, linalgOps, dependenceGraph,
|
|
LinalgTilingOptions().setTileSizes(tileSizes).setLoopType(loopType));
|
|
if (!tileAndFuseOps)
|
|
return signalPassFailure();
|
|
if (linalgOps.back().hasTensorSemantics()) {
|
|
linalgOps.back().getOperation()->replaceAllUsesWith(
|
|
tileAndFuseOps->fusedLoops.front());
|
|
}
|
|
for (auto op : linalgOps)
|
|
if (op.hasBufferSemantics())
|
|
op.erase();
|
|
}
|
|
};
|
|
|
|
} // namespace
|
|
|
|
namespace mlir {
|
|
namespace test {
|
|
void registerTestLinalgFusionTransforms() {
|
|
PassRegistration<TestLinalgFusionTransformsParallelLoops>();
|
|
}
|
|
void registerTestLinalgTensorFusionTransforms() {
|
|
PassRegistration<TestLinalgFusionTransformsLoops>();
|
|
}
|
|
void registerTestLinalgTiledLoopFusionTransforms() {
|
|
PassRegistration<TestLinalgFusionTransformsTiledLoops>();
|
|
}
|
|
void registerTestLinalgGreedyFusion() {
|
|
PassRegistration<TestLinalgGreedyFusion>();
|
|
}
|
|
void registerTestLinalgTileAndFuseSequencePass() {
|
|
PassRegistration<TestLinalgTileAndFuseSequencePass>();
|
|
}
|
|
|
|
} // namespace test
|
|
} // namespace mlir
|