Files
clang-p2996/mlir/lib/Transforms/Vectorization/VectorizerTestPass.cpp
Nicolas Vasilache c6f798a976 Introduce AffineMap::compose(AffineMap)
This CL is the 2nd on the path to simplifying AffineMap composition.
This CL uses the now accepted `AffineExpr::compose(AffineMap)` to
implement `AffineMap::compose(AffineMap)`.

Implications of keeping the simplification function in
Analysis are documented where relevant.

PiperOrigin-RevId: 228276646
2019-03-29 15:04:20 -07:00

305 lines
10 KiB
C++

//===- VectorizerTestPass.cpp - VectorizerTestPass Pass Impl --------------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
//
// This file implements a simple testing pass for vectorization functionality.
//
//===----------------------------------------------------------------------===//
#include "mlir/Analysis/AffineAnalysis.h"
#include "mlir/Analysis/MLFunctionMatcher.h"
#include "mlir/Analysis/SliceAnalysis.h"
#include "mlir/Analysis/VectorAnalysis.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/Pass.h"
#include "mlir/Support/Functional.h"
#include "mlir/Support/STLExtras.h"
#include "mlir/Transforms/Passes.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#define DEBUG_TYPE "vectorizer-test"
using namespace mlir;
using llvm::outs;
using llvm::SetVector;
using functional::map;
static llvm::cl::list<int> clTestVectorShapeRatio(
"vector-shape-ratio",
llvm::cl::desc("Specify the HW vector size for vectorization"),
llvm::cl::ZeroOrMore);
static llvm::cl::opt<bool> clTestForwardSlicingAnalysis(
"forward-slicing",
llvm::cl::desc(
"Specify to enable testing forward static slicing and topological sort "
"functionalities"));
static llvm::cl::opt<bool> clTestBackwardSlicingAnalysis(
"backward-slicing",
llvm::cl::desc("Specify to enable testing backward static slicing and "
"topological sort functionalities"));
static llvm::cl::opt<bool> clTestSlicingAnalysis(
"slicing",
llvm::cl::desc(
"Specify to enable testing static slicing and topological sort "
"functionalities"));
static llvm::cl::opt<bool> clTestComposeMaps(
"compose-maps",
llvm::cl::desc(
"Specify to enable testing the composition of AffineMap where each "
"AffineMap in the composition is specified as the affine_map attribute "
"in a constant op."));
static llvm::cl::opt<bool> clTestNormalizeMaps(
"normalize-maps",
llvm::cl::desc(
"Specify to enable testing the normalization of AffineAffineApplyOp "
"where each AffineAffineApplyOp in the composition is a single output "
"instruction."));
namespace {
struct VectorizerTestPass : public FunctionPass {
static constexpr auto kTestAffineMapOpName = "test_affine_map";
static constexpr auto kTestAffineMapAttrName = "affine_map";
VectorizerTestPass() : FunctionPass(&VectorizerTestPass::passID) {}
PassResult runOnFunction(Function *f) override;
void testVectorShapeRatio(Function *f);
void testForwardSlicing(Function *f);
void testBackwardSlicing(Function *f);
void testSlicing(Function *f);
void testComposeMaps(Function *f);
void testNormalizeMaps(Function *f);
// Thread-safe RAII contexts local to pass, BumpPtrAllocator freed on exit.
MLFunctionMatcherContext MLContext;
static char passID;
};
} // end anonymous namespace
char VectorizerTestPass::passID = 0;
void VectorizerTestPass::testVectorShapeRatio(Function *f) {
using matcher::Op;
SmallVector<int, 8> shape(clTestVectorShapeRatio.begin(),
clTestVectorShapeRatio.end());
auto subVectorType = VectorType::get(shape, Type::getF32(f->getContext()));
// Only filter instructions that operate on a strict super-vector and have one
// return. This makes testing easier.
auto filter = [subVectorType](const Instruction &inst) {
auto *opInst = dyn_cast<OperationInst>(&inst);
if (!opInst) {
return false;
}
assert(subVectorType.getElementType() ==
Type::getF32(subVectorType.getContext()) &&
"Only f32 supported for now");
if (!matcher::operatesOnSuperVectors(*opInst, subVectorType)) {
return false;
}
if (opInst->getNumResults() != 1) {
return false;
}
return true;
};
auto pat = Op(filter);
auto matches = pat.match(f);
for (auto m : matches) {
auto *opInst = cast<OperationInst>(m.first);
// This is a unit test that only checks and prints shape ratio.
// As a consequence we write only Ops with a single return type for the
// purpose of this test. If we need to test more intricate behavior in the
// future we can always extend.
auto superVectorType = opInst->getResult(0)->getType().cast<VectorType>();
auto ratio = shapeRatio(superVectorType, subVectorType);
if (!ratio.hasValue()) {
opInst->emitNote("NOT MATCHED");
} else {
outs() << "\nmatched: " << *opInst << " with shape ratio: ";
interleaveComma(MutableArrayRef<unsigned>(*ratio), outs());
}
}
}
static std::string toString(Instruction *inst) {
std::string res;
auto os = llvm::raw_string_ostream(res);
inst->print(os);
return res;
}
static MLFunctionMatches matchTestSlicingOps(Function *f) {
// Just use a custom op name for this test, it makes life easier.
constexpr auto kTestSlicingOpName = "slicing-test-op";
using functional::map;
using matcher::Op;
// Match all OpInstructions with the kTestSlicingOpName name.
auto filter = [](const Instruction &inst) {
const auto &opInst = cast<OperationInst>(inst);
return opInst.getName().getStringRef() == kTestSlicingOpName;
};
auto pat = Op(filter);
return pat.match(f);
}
void VectorizerTestPass::testBackwardSlicing(Function *f) {
auto matches = matchTestSlicingOps(f);
for (auto m : matches) {
SetVector<Instruction *> backwardSlice;
getBackwardSlice(m.first, &backwardSlice);
auto strs = map(toString, backwardSlice);
outs() << "\nmatched: " << *m.first << " backward static slice: ";
for (const auto &s : strs) {
outs() << "\n" << s;
}
}
}
void VectorizerTestPass::testForwardSlicing(Function *f) {
auto matches = matchTestSlicingOps(f);
for (auto m : matches) {
SetVector<Instruction *> forwardSlice;
getForwardSlice(m.first, &forwardSlice);
auto strs = map(toString, forwardSlice);
outs() << "\nmatched: " << *m.first << " forward static slice: ";
for (const auto &s : strs) {
outs() << "\n" << s;
}
}
}
void VectorizerTestPass::testSlicing(Function *f) {
auto matches = matchTestSlicingOps(f);
for (auto m : matches) {
SetVector<Instruction *> staticSlice = getSlice(m.first);
auto strs = map(toString, staticSlice);
outs() << "\nmatched: " << *m.first << " static slice: ";
for (const auto &s : strs) {
outs() << "\n" << s;
}
}
}
bool customOpWithAffineMapAttribute(const Instruction &inst) {
const auto &opInst = cast<OperationInst>(inst);
return opInst.getName().getStringRef() ==
VectorizerTestPass::kTestAffineMapOpName;
}
void VectorizerTestPass::testComposeMaps(Function *f) {
using matcher::Op;
auto pattern = Op(customOpWithAffineMapAttribute);
auto matches = pattern.match(f);
SmallVector<AffineMap, 4> maps;
maps.reserve(matches.size());
std::reverse(matches.begin(), matches.end());
for (auto m : matches) {
auto *opInst = cast<OperationInst>(m.first);
auto map = opInst->getAttr(VectorizerTestPass::kTestAffineMapAttrName)
.cast<AffineMapAttr>()
.getValue();
maps.push_back(map);
}
AffineMap res;
for (auto m : maps) {
res = res ? res.compose(m) : m;
}
simplifyAffineMap(res).print(outs() << "\nComposed map: ");
}
bool affineApplyOp(const Instruction &inst) {
const auto &opInst = cast<OperationInst>(inst);
return opInst.isa<AffineApplyOp>();
}
bool singleResultAffineApplyOpWithoutUses(const Instruction &inst) {
const auto &opInst = cast<OperationInst>(inst);
auto app = opInst.dyn_cast<AffineApplyOp>();
return app && (app->getNumResults() == 1) &&
app->getResult(0)->getUses().end() ==
app->getResult(0)->getUses().begin();
}
void VectorizerTestPass::testNormalizeMaps(Function *f) {
using matcher::Op;
// Save matched AffineApplyOp that all need to be erased in the end.
auto pattern = Op(affineApplyOp);
auto toErase = pattern.match(f);
std::reverse(toErase.begin(), toErase.end());
{
// Compose maps.
auto pattern = Op(singleResultAffineApplyOpWithoutUses);
for (auto m : pattern.match(f)) {
auto app = cast<OperationInst>(m.first)->cast<AffineApplyOp>();
FuncBuilder b(m.first);
using ValueTy = decltype(*(app->getOperands().begin()));
SmallVector<Value *, 8> operands =
functional::map([](ValueTy v) { return static_cast<Value *>(v); },
app->getOperands().begin(), app->getOperands().end());
makeNormalizedAffineApply(&b, app->getLoc(), app->getAffineMap(),
operands);
}
}
// We should now be able to erase everything in reverse order in this test.
for (auto m : toErase) {
m.first->erase();
}
}
PassResult VectorizerTestPass::runOnFunction(Function *f) {
// Only support single block functions at this point.
if (f->getBlocks().size() != 1)
return success();
if (!clTestVectorShapeRatio.empty()) {
testVectorShapeRatio(f);
}
if (clTestForwardSlicingAnalysis) {
testForwardSlicing(f);
}
if (clTestBackwardSlicingAnalysis) {
testBackwardSlicing(f);
}
if (clTestSlicingAnalysis) {
testSlicing(f);
}
if (clTestComposeMaps) {
testComposeMaps(f);
}
if (clTestNormalizeMaps) {
testNormalizeMaps(f);
}
return PassResult::Success;
}
FunctionPass *mlir::createVectorizerTestPass() {
return new VectorizerTestPass();
}
static PassRegistration<VectorizerTestPass>
pass("vectorizer-test", "Tests vectorizer standalone functionality.");
#undef DEBUG_TYPE