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//===- 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/AffineOps/AffineOps.h"
#include "mlir/Analysis/AffineAnalysis.h"
#include "mlir/Analysis/NestedMatcher.h"
#include "mlir/Analysis/SliceAnalysis.h"
#include "mlir/Analysis/VectorAnalysis.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Support/Functional.h"
#include "mlir/Support/STLExtras.h"
#include "mlir/Transforms/Passes.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#define DEBUG_TYPE "affine-vectorizer-test"
using namespace mlir;
using llvm::SetVector;
using functional::map;
static llvm::cl::OptionCategory clOptionsCategory(DEBUG_TYPE " options");
static llvm::cl::list<int> clTestVectorShapeRatio(
"vector-shape-ratio",
llvm::cl::desc("Specify the HW vector size for vectorization"),
llvm::cl::ZeroOrMore, llvm::cl::cat(clOptionsCategory));
static llvm::cl::opt<bool> clTestForwardSlicingAnalysis(
"forward-slicing",
llvm::cl::desc("Enable testing forward static slicing and topological sort "
"functionalities"),
llvm::cl::cat(clOptionsCategory));
static llvm::cl::opt<bool> clTestBackwardSlicingAnalysis(
"backward-slicing",
llvm::cl::desc("Enable testing backward static slicing and "
"topological sort functionalities"),
llvm::cl::cat(clOptionsCategory));
static llvm::cl::opt<bool> clTestSlicingAnalysis(
"slicing",
llvm::cl::desc("Enable testing static slicing and topological sort "
"functionalities"),
llvm::cl::cat(clOptionsCategory));
static llvm::cl::opt<bool> clTestComposeMaps(
"compose-maps",
llvm::cl::desc(
"Enable testing the composition of AffineMap where each "
"AffineMap in the composition is specified as the affine_map attribute "
"in a constant op."),
llvm::cl::cat(clOptionsCategory));
static llvm::cl::opt<bool> clTestNormalizeMaps(
"normalize-maps",
llvm::cl::desc(
"Enable testing the normalization of AffineAffineApplyOp "
"where each AffineAffineApplyOp in the composition is a single output "
"operation."),
llvm::cl::cat(clOptionsCategory));
namespace {
struct VectorizerTestPass : public FunctionPass<VectorizerTestPass> {
static constexpr auto kTestAffineMapOpName = "test_affine_map";
static constexpr auto kTestAffineMapAttrName = "affine_map";
void runOnFunction() override;
void testVectorShapeRatio(llvm::raw_ostream &outs);
void testForwardSlicing(llvm::raw_ostream &outs);
void testBackwardSlicing(llvm::raw_ostream &outs);
void testSlicing(llvm::raw_ostream &outs);
void testComposeMaps(llvm::raw_ostream &outs);
void testNormalizeMaps();
};
} // end anonymous namespace
void VectorizerTestPass::testVectorShapeRatio(llvm::raw_ostream &outs) {
auto *f = &getFunction();
using matcher::Op;
SmallVector<int64_t, 8> shape(clTestVectorShapeRatio.begin(),
clTestVectorShapeRatio.end());
auto subVectorType =
VectorType::get(shape, FloatType::getF32(f->getContext()));
// Only filter operations that operate on a strict super-vector and have one
// return. This makes testing easier.
auto filter = [subVectorType](Operation &op) {
assert(subVectorType.getElementType() ==
FloatType::getF32(subVectorType.getContext()) &&
"Only f32 supported for now");
if (!matcher::operatesOnSuperVectorsOf(op, subVectorType)) {
return false;
}
if (op.getNumResults() != 1) {
return false;
}
return true;
};
auto pat = Op(filter);
SmallVector<NestedMatch, 8> matches;
pat.match(f, &matches);
for (auto m : matches) {
auto *opInst = m.getMatchedOperation();
// 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->emitRemark("NOT MATCHED");
} else {
outs << "\nmatched: " << *opInst << " with shape ratio: ";
interleaveComma(MutableArrayRef<unsigned>(*ratio), outs);
}
}
}
static std::string toString(Operation *op) {
std::string res;
llvm::raw_string_ostream os(res);
op->print(os);
return res;
}
static NestedPattern patternTestSlicingOps() {
using functional::map;
using matcher::Op;
// Match all operations with the kTestSlicingOpName name.
auto filter = [](Operation &op) {
// Just use a custom op name for this test, it makes life easier.
return op.getName().getStringRef() == "slicing-test-op";
};
return Op(filter);
}
void VectorizerTestPass::testBackwardSlicing(llvm::raw_ostream &outs) {
auto *f = &getFunction();
SmallVector<NestedMatch, 8> matches;
patternTestSlicingOps().match(f, &matches);
for (auto m : matches) {
SetVector<Operation *> backwardSlice;
getBackwardSlice(m.getMatchedOperation(), &backwardSlice);
auto strs = map(toString, backwardSlice);
outs << "\nmatched: " << *m.getMatchedOperation()
<< " backward static slice: ";
for (const auto &s : strs) {
outs << "\n" << s;
}
}
}
void VectorizerTestPass::testForwardSlicing(llvm::raw_ostream &outs) {
auto *f = &getFunction();
SmallVector<NestedMatch, 8> matches;
patternTestSlicingOps().match(f, &matches);
for (auto m : matches) {
SetVector<Operation *> forwardSlice;
getForwardSlice(m.getMatchedOperation(), &forwardSlice);
auto strs = map(toString, forwardSlice);
outs << "\nmatched: " << *m.getMatchedOperation()
<< " forward static slice: ";
for (const auto &s : strs) {
outs << "\n" << s;
}
}
}
void VectorizerTestPass::testSlicing(llvm::raw_ostream &outs) {
auto *f = &getFunction();
SmallVector<NestedMatch, 8> matches;
patternTestSlicingOps().match(f, &matches);
for (auto m : matches) {
SetVector<Operation *> staticSlice = getSlice(m.getMatchedOperation());
auto strs = map(toString, staticSlice);
outs << "\nmatched: " << *m.getMatchedOperation() << " static slice: ";
for (const auto &s : strs) {
outs << "\n" << s;
}
}
}
static bool customOpWithAffineMapAttribute(Operation &op) {
return op.getName().getStringRef() ==
VectorizerTestPass::kTestAffineMapOpName;
}
void VectorizerTestPass::testComposeMaps(llvm::raw_ostream &outs) {
auto *f = &getFunction();
using matcher::Op;
auto pattern = Op(customOpWithAffineMapAttribute);
SmallVector<NestedMatch, 8> matches;
pattern.match(f, &matches);
SmallVector<AffineMap, 4> maps;
maps.reserve(matches.size());
for (auto m : llvm::reverse(matches)) {
auto *opInst = m.getMatchedOperation();
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: ");
}
static bool affineApplyOp(Operation &op) { return op.isa<AffineApplyOp>(); }
static bool singleResultAffineApplyOpWithoutUses(Operation &op) {
auto app = op.dyn_cast<AffineApplyOp>();
return app && app.use_empty();
}
void VectorizerTestPass::testNormalizeMaps() {
using matcher::Op;
auto *f = &getFunction();
// Save matched AffineApplyOp that all need to be erased in the end.
auto pattern = Op(affineApplyOp);
SmallVector<NestedMatch, 8> toErase;
pattern.match(f, &toErase);
{
// Compose maps.
auto pattern = Op(singleResultAffineApplyOpWithoutUses);
SmallVector<NestedMatch, 8> matches;
pattern.match(f, &matches);
for (auto m : matches) {
auto app = m.getMatchedOperation()->cast<AffineApplyOp>();
FuncBuilder b(m.getMatchedOperation());
SmallVector<Value *, 8> operands(app.getOperands());
makeComposedAffineApply(&b, app.getLoc(), app.getAffineMap(), operands);
}
}
// We should now be able to erase everything in reverse order in this test.
for (auto m : llvm::reverse(toErase)) {
m.getMatchedOperation()->erase();
}
}
void VectorizerTestPass::runOnFunction() {
// Thread-safe RAII local context, BumpPtrAllocator freed on exit.
NestedPatternContext mlContext;
// Only support single block functions at this point.
Function &f = getFunction();
if (f.getBlocks().size() != 1)
return;
std::string str;
llvm::raw_string_ostream outs(str);
if (!clTestVectorShapeRatio.empty())
testVectorShapeRatio(outs);
if (clTestForwardSlicingAnalysis)
testForwardSlicing(outs);
if (clTestBackwardSlicingAnalysis)
testBackwardSlicing(outs);
if (clTestSlicingAnalysis)
testSlicing(outs);
if (clTestComposeMaps)
testComposeMaps(outs);
if (clTestNormalizeMaps)
testNormalizeMaps();
if (!outs.str().empty()) {
getContext().emitRemark(UnknownLoc::get(&getContext()), outs.str());
}
}
FunctionPassBase *mlir::createVectorizerTestPass() {
return new VectorizerTestPass();
}
static PassRegistration<VectorizerTestPass>
pass("affine-vectorizer-test",
"Tests vectorizer standalone functionality.");
#undef DEBUG_TYPE