llvm-project/mlir/test/lib/Transforms/TestLinalgTransforms.cpp
River Riddle b6eb26fd0e [mlir][NFC] Move around the code related to PatternRewriting to improve layering
There are several pieces of pattern rewriting infra in IR/ that really shouldn't be there. This revision moves those pieces to a better location such that they are easier to evolve in the future(e.g. with PDL). More concretely this revision does the following:

* Create a Transforms/GreedyPatternRewriteDriver.h and move the apply*andFold methods there.
The definitions for these methods are already in Transforms/ so it doesn't make sense for the declarations to be in IR.

* Create a new lib/Rewrite library and move PatternApplicator there.
This new library will be focused on applying rewrites, and will also include compiling rewrites with PDL.

Differential Revision: https://reviews.llvm.org/D89103
2020-10-26 18:01:06 -07:00

508 lines
21 KiB
C++

//===- TestLinalgTransforms.cpp - Test Linalg transformation 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 transformations.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/GPU/GPUDialect.h"
#include "mlir/Dialect/Linalg/IR/LinalgOps.h"
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
#include "mlir/Dialect/Linalg/Utils/Utils.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/Dialect/Vector/VectorOps.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
#include "llvm/ADT/SetVector.h"
using namespace mlir;
using namespace mlir::linalg;
namespace {
struct TestLinalgTransforms
: public PassWrapper<TestLinalgTransforms, FunctionPass> {
TestLinalgTransforms() = default;
TestLinalgTransforms(const TestLinalgTransforms &pass) {}
void getDependentDialects(DialectRegistry &registry) const override {
// clang-format off
registry.insert<AffineDialect,
scf::SCFDialect,
StandardOpsDialect,
vector::VectorDialect,
gpu::GPUDialect>();
// clang-format on
}
void runOnFunction() override;
Option<bool> testPatterns{*this, "test-patterns",
llvm::cl::desc("Test a mixed set of patterns"),
llvm::cl::init(false)};
Option<bool> testMatmulToVectorPatterns1dTiling{
*this, "test-matmul-to-vector-patterns-tile-1d",
llvm::cl::desc(
"Test a fused pass that applies patterns from matmul to vectors via "
"1-d tiling"),
llvm::cl::init(false)};
Option<bool> testMatmulToVectorPatterns2dTiling{
*this, "test-matmul-to-vector-patterns-tile-2d",
llvm::cl::desc(
"Test a fused pass that applies patterns from matmul to vectors via "
"2-d tiling"),
llvm::cl::init(false)};
Option<bool> testPromotionOptions{*this, "test-linalg-promotion-options",
llvm::cl::desc("Test promotion options"),
llvm::cl::init(false)};
Option<bool> testTileAndDistributionOptions{
*this, "test-tile-and-distribute-options",
llvm::cl::desc("Test tile and distribute options"),
llvm::cl::init(false)};
Option<bool> testVectorTransferForwardingPatterns{
*this, "test-vector-transfer-forwarding-patterns",
llvm::cl::desc(
"Test a fused pass that forwards linalg.copy to vector.transfer"),
llvm::cl::init(false)};
Option<bool> testGenericToVectorPattern{
*this, "test-contraction-to-vector-patterns",
llvm::cl::desc("Test a set of patterns that rewrite a linalg contraction "
"in vector.contract form"),
llvm::cl::init(false)};
Option<bool> testAffineMinSCFCanonicalizationPatterns{
*this, "test-affine-min-scf-canonicalization-patterns",
llvm::cl::desc("Test affine-min + scf canonicalization patterns."),
llvm::cl::init(false)};
};
} // end anonymous namespace
static void applyPatterns(FuncOp funcOp) {
MLIRContext *ctx = funcOp.getContext();
OwningRewritePatternList patterns;
//===--------------------------------------------------------------------===//
// Linalg tiling patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({2000, 3000, 4000}),
LinalgMarker(Identifier::get("MEM", ctx), Identifier::get("L3", ctx)));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({200, 300, 400}),
LinalgMarker(Identifier::get("L3", ctx), Identifier::get("L2", ctx)));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({20, 30, 40}),
LinalgMarker(Identifier::get("L2", ctx), Identifier::get("L1", ctx)));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({2, 3, 4}),
LinalgMarker(Identifier::get("L1", ctx), Identifier::get("REG", ctx)));
patterns.insert<LinalgTilingPattern<MatvecOp>>(
ctx,
LinalgTilingOptions().setTileSizes({5, 6}).setLoopType(
LinalgTilingLoopType::ParallelLoops),
LinalgMarker({}, Identifier::get("L1", ctx)));
patterns.insert<LinalgTilingPattern<DotOp>>(
ctx, LinalgTilingOptions().setTileSizes(8000),
LinalgMarker(ArrayRef<Identifier>{Identifier::get("MEM", ctx),
Identifier::get("L3", ctx),
Identifier::get("L2", ctx)},
Identifier::get("REG", ctx)));
//===--------------------------------------------------------------------===//
// Linalg tiling and permutation patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx,
LinalgTilingOptions()
.setTileSizes({2000, 3000, 4000})
.setInterchange({1, 2, 0}),
LinalgMarker(Identifier::get("__with_perm__", ctx),
Identifier::get("L2__with_perm__", ctx)));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx,
LinalgTilingOptions()
.setTileSizes({200, 300, 400})
.setInterchange({1, 0, 2}),
LinalgMarker(Identifier::get("L2__with_perm__", ctx),
Identifier::get("L1__with_perm__", ctx)));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({20, 30, 40}),
LinalgMarker(Identifier::get("L1__with_perm__", ctx),
Identifier::get("REG__with_perm__", ctx)));
patterns.insert<LinalgTilingPattern<MatvecOp>>(
ctx, LinalgTilingOptions().setTileSizes({5, 6}).setInterchange({1, 0}),
LinalgMarker(Identifier::get("__with_perm__", ctx),
Identifier::get("L1__with_perm__", ctx)));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx,
LinalgTilingOptions()
.setTileSizes({16, 8, 4})
.setInterchange({1, 2, 0})
.setLoopType(LinalgTilingLoopType::ParallelLoops),
LinalgMarker(Identifier::get("par__with_perm__", ctx),
Identifier::get("after_par__with_perm__", ctx)));
//===--------------------------------------------------------------------===//
// Linalg to loops patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgLoweringPattern<DotOp>>(
ctx,
/*loweringType=*/LinalgLoweringType::Loops,
LinalgMarker(Identifier::get("REG", ctx)));
//===--------------------------------------------------------------------===//
// Linalg distribution patterns.
//===--------------------------------------------------------------------===//
LinalgLoopDistributionOptions distributionOptions;
//===--------------------------------------------------------------------===//
// Linalg to vector contraction patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgVectorizationPattern<MatmulOp>,
LinalgVectorizationPattern<FillOp>,
LinalgVectorizationPattern<CopyOp>,
LinalgVectorizationPattern<GenericOp>>(
ctx, LinalgMarker(Identifier::get("VECTORIZE", ctx)));
//===--------------------------------------------------------------------===//
// Linalg generic permutation patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgInterchangePattern<GenericOp>>(
ctx,
/*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
LinalgMarker({}, Identifier::get("PERMUTED", ctx)));
patterns.insert<LinalgInterchangePattern<IndexedGenericOp>>(
ctx,
/*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
LinalgMarker({}, Identifier::get("PERMUTED", ctx)));
//===--------------------------------------------------------------------===//
// Linalg subview operands promotion.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgPromotionPattern<MatmulOp>>(
ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
LinalgMarker(Identifier::get("_promote_views_", ctx),
Identifier::get("_views_promoted_", ctx)));
patterns.insert<LinalgPromotionPattern<MatmulOp>>(
ctx,
LinalgPromotionOptions()
.setOperandsToPromote({0})
.setUseFullTileBuffersByDefault(true),
LinalgMarker(Identifier::get("_promote_first_view_", ctx),
Identifier::get("_first_view_promoted_", ctx)));
patterns.insert<LinalgPromotionPattern<FillOp>>(
ctx,
LinalgPromotionOptions()
.setOperandsToPromote({0})
.setUseFullTileBuffers({true})
.setAlignment(32),
LinalgMarker(Identifier::get("_promote_views_aligned_", ctx),
Identifier::get("_views_aligned_promoted_", ctx)));
applyPatternsAndFoldGreedily(funcOp, patterns);
// Drop the marker.
funcOp.walk([](LinalgOp op) {
op.removeAttr(LinalgTransforms::kLinalgTransformMarker);
});
}
static void fillL1TilingAndMatmulToVectorPatterns(
FuncOp funcOp, StringRef startMarker,
SmallVectorImpl<OwningRewritePatternList> &patternsVector) {
MLIRContext *ctx = funcOp.getContext();
patternsVector.emplace_back(LinalgTilingPattern<MatmulOp>(
ctx,
LinalgTilingOptions().setTileSizes({8, 12, 16}).setInterchange({1, 0, 2}),
LinalgMarker(Identifier::get(startMarker, ctx),
Identifier::get("L1", ctx))));
patternsVector.emplace_back(LinalgPromotionPattern<MatmulOp>(
ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
LinalgMarker(Identifier::get("L1", ctx), Identifier::get("VEC", ctx))));
patternsVector.emplace_back(LinalgVectorizationPattern<MatmulOp>(
ctx, LinalgMarker(Identifier::get("VEC", ctx))));
patternsVector.back()
.insert<LinalgVectorizationPattern<FillOp>,
LinalgVectorizationPattern<CopyOp>>(ctx);
}
//===----------------------------------------------------------------------===//
// Test promotion callbacks
//===----------------------------------------------------------------------===//
// Allocation call back
static Optional<Value> allocCallBackFn(OpBuilder &b, SubViewOp subView,
ArrayRef<Value> boundingSubViewSize,
OperationFolder *folder) {
SmallVector<int64_t, 4> shape(boundingSubViewSize.size(), -1);
return b
.create<AllocOp>(subView.getLoc(),
MemRefType::get(shape,
subView.getType().getElementType(),
/*affineMapComposition =*/{}, 3),
boundingSubViewSize)
.getResult();
}
// Deallocation callback
static LogicalResult deallocCallBackFn(OpBuilder &b, Value buffer) {
b.create<DeallocOp>(buffer.getLoc(), buffer);
return success();
}
// Copy in call back
static LogicalResult copyCallBackFn(OpBuilder &b, Value src, Value dst,
bool isOutput) {
auto floatType = src.getType().cast<MemRefType>().getElementType();
if (!floatType.isa<FloatType>())
return failure();
if (!isOutput)
b.create<FillOp>(
src.getLoc(), dst,
b.create<ConstantOp>(src.getLoc(), FloatAttr::get(floatType, 42.0)));
b.create<CopyOp>(src.getLoc(), src, dst);
return success();
}
static void fillPromotionCallBackPatterns(MLIRContext *ctx,
OwningRewritePatternList &patterns) {
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({16, 16, 16}),
LinalgMarker(Identifier::get("START", ctx),
Identifier::get("PROMOTE", ctx)));
patterns.insert<LinalgPromotionPattern<MatmulOp>>(
ctx,
LinalgPromotionOptions()
.setOperandsToPromote({0, 2})
.setUseFullTileBuffers({false, false})
.setAllocationDeallocationFns(allocCallBackFn, deallocCallBackFn)
.setCopyInOutFns(
[](OpBuilder &b, Value src, Value dst) -> LogicalResult {
copyCallBackFn(b, src, dst, false);
return success();
},
[](OpBuilder &b, Value src, Value dst) -> LogicalResult {
copyCallBackFn(b, src, dst, true);
return success();
}),
LinalgMarker(Identifier::get("PROMOTE", ctx)));
}
template <typename IdOp, typename NProcsOp>
static SmallVector<ProcInfo, 2>
getGpuProcIds(OpBuilder &b, Location loc, ArrayRef<Range> parallelLoopRanges) {
Type indexType = b.getIndexType();
SmallVector<ProcInfo, 2> procInfo(2);
procInfo[0] = {b.create<IdOp>(loc, indexType, b.getStringAttr("y")),
b.create<NProcsOp>(loc, indexType, b.getStringAttr("y"))};
procInfo[1] = {b.create<IdOp>(loc, indexType, b.getStringAttr("x")),
b.create<NProcsOp>(loc, indexType, b.getStringAttr("x"))};
return procInfo;
}
static void fillTileAndDistributePatterns(MLIRContext *context,
OwningRewritePatternList &patterns) {
{
LinalgLoopDistributionOptions cyclicNprocsEqNiters;
cyclicNprocsEqNiters.distributionMethod.resize(
2, DistributionMethod::CyclicNumProcsEqNumIters);
cyclicNprocsEqNiters.procInfo =
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
patterns.insert<LinalgTilingPattern<MatmulOp>>(
context,
LinalgTilingOptions()
.setTileSizes({8, 8, 4})
.setLoopType(LinalgTilingLoopType::ParallelLoops)
.setDistributionOptions(cyclicNprocsEqNiters),
LinalgMarker(Identifier::get("distribute1", context),
Identifier::get("after_distribute1", context)));
}
{
LinalgLoopDistributionOptions cyclicNprocsGeNiters;
cyclicNprocsGeNiters.distributionMethod.resize(
2, DistributionMethod::CyclicNumProcsGeNumIters);
cyclicNprocsGeNiters.procInfo =
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
patterns.insert<LinalgTilingPattern<MatmulOp>>(
context,
LinalgTilingOptions()
.setTileSizes({8, 8, 4})
.setLoopType(LinalgTilingLoopType::ParallelLoops)
.setDistributionOptions(cyclicNprocsGeNiters),
LinalgMarker(Identifier::get("distribute2", context),
Identifier::get("after_distribute2", context)));
}
{
LinalgLoopDistributionOptions cyclicNprocsDefault;
cyclicNprocsDefault.distributionMethod.resize(2,
DistributionMethod::Cyclic);
cyclicNprocsDefault.procInfo =
getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
patterns.insert<LinalgTilingPattern<MatmulOp>>(
context,
LinalgTilingOptions()
.setTileSizes({8, 8, 4})
.setLoopType(LinalgTilingLoopType::ParallelLoops)
.setDistributionOptions(cyclicNprocsDefault),
LinalgMarker(Identifier::get("distribute3", context),
Identifier::get("after_distribute3", context)));
}
{
LinalgLoopDistributionOptions cyclicNprocsMixed1;
cyclicNprocsMixed1.distributionMethod = {
DistributionMethod::CyclicNumProcsEqNumIters,
DistributionMethod::CyclicNumProcsGeNumIters};
cyclicNprocsMixed1.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
patterns.insert<LinalgTilingPattern<MatmulOp>>(
context,
LinalgTilingOptions()
.setTileSizes({8, 8, 4})
.setLoopType(LinalgTilingLoopType::ParallelLoops)
.setDistributionOptions(cyclicNprocsMixed1),
LinalgMarker(Identifier::get("distribute4", context),
Identifier::get("after_distribute4", context)));
}
{
LinalgLoopDistributionOptions cyclicNprocsMixed2;
cyclicNprocsMixed2.distributionMethod = {
DistributionMethod::CyclicNumProcsGeNumIters,
DistributionMethod::Cyclic};
cyclicNprocsMixed2.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
patterns.insert<LinalgTilingPattern<MatmulOp>>(
context,
LinalgTilingOptions()
.setTileSizes({8, 8, 4})
.setLoopType(LinalgTilingLoopType::ParallelLoops)
.setDistributionOptions(cyclicNprocsMixed2),
LinalgMarker(Identifier::get("distribute5", context),
Identifier::get("after_distribute5", context)));
}
{
LinalgLoopDistributionOptions cyclicNprocsMixed3;
cyclicNprocsMixed3.distributionMethod = {
DistributionMethod::Cyclic,
DistributionMethod::CyclicNumProcsEqNumIters};
cyclicNprocsMixed3.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>;
patterns.insert<LinalgTilingPattern<MatmulOp>>(
context,
LinalgTilingOptions()
.setTileSizes({8, 8, 4})
.setLoopType(LinalgTilingLoopType::ParallelLoops)
.setDistributionOptions(cyclicNprocsMixed3),
LinalgMarker(Identifier::get("distribute6", context),
Identifier::get("after_distribute6", context)));
}
}
static void
applyMatmulToVectorPatterns(FuncOp funcOp,
bool testMatmulToVectorPatterns1dTiling,
bool testMatmulToVectorPatterns2dTiling) {
MLIRContext *ctx = funcOp.getContext();
SmallVector<OwningRewritePatternList, 4> stage1Patterns;
if (testMatmulToVectorPatterns1dTiling) {
fillL1TilingAndMatmulToVectorPatterns(funcOp, Identifier::get("START", ctx),
stage1Patterns);
} else if (testMatmulToVectorPatterns2dTiling) {
stage1Patterns.emplace_back(LinalgTilingPattern<MatmulOp>(
ctx,
LinalgTilingOptions()
.setTileSizes({768, 264, 768})
.setInterchange({1, 2, 0}),
LinalgMarker(Identifier::get("START", ctx),
Identifier::get("L2", ctx))));
fillL1TilingAndMatmulToVectorPatterns(funcOp, Identifier::get("L2", ctx),
stage1Patterns);
}
OwningRewritePatternList stage2Patterns =
getLinalgTilingCanonicalizationPatterns(ctx);
applyStagedPatterns(funcOp, stage1Patterns, stage2Patterns);
}
static void applyVectorTransferForwardingPatterns(FuncOp funcOp) {
OwningRewritePatternList forwardPattern;
forwardPattern.insert<LinalgCopyVTRForwardingPattern>(funcOp.getContext());
forwardPattern.insert<LinalgCopyVTWForwardingPattern>(funcOp.getContext());
applyPatternsAndFoldGreedily(funcOp, forwardPattern);
}
static void applyContractionToVectorPatterns(FuncOp funcOp) {
OwningRewritePatternList patterns;
patterns.insert<LinalgVectorizationPattern<BatchMatmulOp>,
LinalgVectorizationPattern<MatmulOp>,
LinalgVectorizationPattern<MatvecOp>,
LinalgVectorizationPattern<VecmatOp>,
LinalgVectorizationPattern<DotOp>,
LinalgVectorizationPattern<GenericOp>>(funcOp.getContext());
applyPatternsAndFoldGreedily(funcOp, patterns);
}
static void applyAffineMinSCFCanonicalizationPatterns(FuncOp funcOp) {
OwningRewritePatternList foldPattern;
foldPattern.insert<AffineMinSCFCanonicalizationPattern>(funcOp.getContext());
// Explicitly walk and apply the pattern locally to avoid more general folding
// on the rest of the IR.
funcOp.walk([&foldPattern](AffineMinOp minOp) {
applyOpPatternsAndFold(minOp, foldPattern);
});
}
/// Apply transformations specified as patterns.
void TestLinalgTransforms::runOnFunction() {
auto lambda = [&](void *) {
getFunction().walk([](LinalgOp op) {
op.removeAttr(LinalgTransforms::kLinalgTransformMarker);
});
};
std::unique_ptr<void, decltype(lambda)> cleanupGuard{(void *)1, lambda};
if (testPromotionOptions) {
OwningRewritePatternList patterns;
fillPromotionCallBackPatterns(&getContext(), patterns);
applyPatternsAndFoldGreedily(getFunction(), patterns);
return;
}
if (testTileAndDistributionOptions) {
OwningRewritePatternList patterns;
fillTileAndDistributePatterns(&getContext(), patterns);
applyPatternsAndFoldGreedily(getFunction(), patterns);
return;
}
if (testPatterns)
return applyPatterns(getFunction());
if (testMatmulToVectorPatterns1dTiling || testMatmulToVectorPatterns2dTiling)
return applyMatmulToVectorPatterns(getFunction(),
testMatmulToVectorPatterns1dTiling,
testMatmulToVectorPatterns2dTiling);
if (testVectorTransferForwardingPatterns)
return applyVectorTransferForwardingPatterns(getFunction());
if (testGenericToVectorPattern)
return applyContractionToVectorPatterns(getFunction());
if (testAffineMinSCFCanonicalizationPatterns)
return applyAffineMinSCFCanonicalizationPatterns(getFunction());
}
namespace mlir {
void registerTestLinalgTransforms() {
PassRegistration<TestLinalgTransforms> testTransformPatternsPass(
"test-linalg-transform-patterns",
"Test Linalg transformation patterns by applying them greedily.");
}
} // namespace mlir