Add hasProfileData() to check if a function has profile data. NFC.

[eraman]

Summary

This replaces calls to getEntryCount().hasValue() with hasProfileData
that does the same thing. This refactoring is useful to do before adding
synthetic function entry counts but also a useful cleanup IMO even
otherwise. I have used hasProfileData instead of hasRealProfileData as
David had earlier suggested since I think profile implies "real" and I
use the phrase "synthetic entry count" and not "synthetic profile count"
but I am fine calling it hasRealProfileData if you prefer.

[vsk]

Looks like a nice cleanup to me.

[davidxl]

I prefer hasProfileData to be hasRealProfileData -- unless we want to make hasProfileData to mean has real profile data and ignores synthetic entry count later.

[davidxl]

LGTM

Perhaps change the new interface documentation slightly to reflect that it is for real profile data.

[eraman]

In D41461#962311, @davidxl wrote:

LGTM

Perhaps change the new interface documentation slightly to reflect that it is for real profile data.

Expanded the comments to indicate that this returns true if entry counts from a profile run are present. Once I add synthetic counts, I can make it clear that we are looking for real counts.

Will submit with this comment change.

include/llvm/IR/Function.h

void setEntryCount(uint64_t Count,
                      const DenseSet<GlobalValue::GUID> *Imports = nullptr);
 
   /// \brief Get the entry count for this function.
   ///
   /// Entry count is the number of times the function was executed based on
   /// pgo data.
   Optional<uint64_t> getEntryCount() const;
 
+  /// \brief Return true if the function is annotated with profile data.
+  bool hasProfileData() const { return getEntryCount().hasValue(); }
+
   /// Returns the set of GUIDs that needs to be imported to the function for
   /// sample PGO, to enable the same inlines as the profiled optimized binary.
   DenseSet<GlobalValue::GUID> getImportGUIDs() const;
 
   /// Set the section prefix for this function.
   void setSectionPrefix(StringRef Prefix);
 
   /// Get the section prefix for this function.

lib/Analysis/ModuleSummaryAnalysis.cpp

ModuleSummaryIndex llvm::buildModuleSummaryIndex(
   for (auto &F : M) {
     if (F.isDeclaration())
       continue;
 
     BlockFrequencyInfo *BFI = nullptr;
     std::unique_ptr<BlockFrequencyInfo> BFIPtr;
     if (GetBFICallback)
       BFI = GetBFICallback(F);
-    else if (F.getEntryCount().hasValue()) {
+    else if (F.hasProfileData()) {
       LoopInfo LI{DominatorTree(const_cast<Function &>(F))};
       BranchProbabilityInfo BPI{F, LI};
       BFIPtr = llvm::make_unique<BlockFrequencyInfo>(F, BPI, LI);
       BFI = BFIPtr.get();
     }
 
     computeFunctionSummary(Index, M, F, BFI, PSI,
                            !LocalsUsed.empty() || HasLocalInlineAsmSymbol,

lib/Analysis/ProfileSummaryInfo.cpp

bool ProfileSummaryInfo::isColdCallSite(const CallSite &CS,
   if (C)
     return isColdCount(*C);
 
   // In SamplePGO, if the caller has been sampled, and there is no profile
   // annotatedon the callsite, we consider the callsite as cold.
   // If there is no profile for the caller, and we know the profile is
   // accurate, we consider the callsite as cold.
   return (hasSampleProfile() &&
-          (CS.getCaller()->getEntryCount() || ProfileSampleAccurate ||
+          (CS.getCaller()->hasProfileData() || ProfileSampleAccurate ||
            CS.getCaller()->hasFnAttribute("profile-sample-accurate")));
 }
 
 INITIALIZE_PASS(ProfileSummaryInfoWrapperPass, "profile-summary-info",
                 "Profile summary info", false, true)
 
 ProfileSummaryInfoWrapperPass::ProfileSummaryInfoWrapperPass()
     : ImmutablePass(ID) {

lib/Bitcode/Writer/BitcodeWriter.cpp

void ModuleBitcodeWriterBase::writePerModuleFunctionSummaryRecord(
   NameVals.push_back(getEncodedGVSummaryFlags(FS->flags()));
   NameVals.push_back(FS->instCount());
   NameVals.push_back(getEncodedFFlags(FS->fflags()));
   NameVals.push_back(FS->refs().size());
 
   for (auto &RI : FS->refs())
     NameVals.push_back(VE.getValueID(RI.getValue()));
 
-  bool HasProfileData = F.getEntryCount().hasValue();
+  bool HasProfileData = F.hasProfileData();
   for (auto &ECI : FS->calls()) {
     NameVals.push_back(getValueId(ECI.first));
     if (HasProfileData)
       NameVals.push_back(static_cast<uint8_t>(ECI.second.Hotness));
   }
 
   unsigned FSAbbrev = (HasProfileData ? FSCallsProfileAbbrev : FSCallsAbbrev);
   unsigned Code =

lib/CodeGen/MachineBlockPlacement.cpp

for (auto &ChainPair : TriangleChainMap) {
     }
   }
 }
 
 // When profile is not present, return the StaticLikelyProb.
 // When profile is available, we need to handle the triangle-shape CFG.
 static BranchProbability getLayoutSuccessorProbThreshold(
       const MachineBasicBlock *BB) {
-  if (!BB->getParent()->getFunction()->getEntryCount())
+  if (!BB->getParent()->getFunction()->hasProfileData())
     return BranchProbability(StaticLikelyProb, 100);
   if (BB->succ_size() == 2) {
     const MachineBasicBlock *Succ1 = *BB->succ_begin();
     const MachineBasicBlock *Succ2 = *(BB->succ_begin() + 1);
     if (Succ1->isSuccessor(Succ2) || Succ2->isSuccessor(Succ1)) {
       /* See case 1 below for the cost analysis. For BB->Succ to
        * be taken with smaller cost, the following needs to hold:
        *   Prob(BB->Succ) > 2 * Prob(BB->Pred)
MachineBlockPlacement::collectLoopBlockSet(const MachineLoop &L) {
   // Collect the sum of frequencies of incoming edges to the loop header from
   // outside. If we treat the loop as a super block, this is the frequency of
   // the loop. Then for each block in the loop, we calculate the ratio between
   // its frequency and the frequency of the loop block. When it is too small,
   // don't add it to the loop chain. If there are outer loops, then this block
   // will be merged into the first outer loop chain for which this block is not
   // cold anymore. This needs precise profile data and we only do this when
   // profile data is available.
-  if (F->getFunction()->getEntryCount() || ForceLoopColdBlock) {
+  if (F->getFunction()->hasProfileData() || ForceLoopColdBlock) {
     BlockFrequency LoopFreq(0);
     for (auto LoopPred : L.getHeader()->predecessors())
       if (!L.contains(LoopPred))
         LoopFreq += MBFI->getBlockFreq(LoopPred) *
                     MBPI->getEdgeProbability(LoopPred, L.getHeader());
 
     for (MachineBasicBlock *LoopBB : L.getBlocks()) {
       auto Freq = MBFI->getBlockFreq(LoopBB).getFrequency();
assert(EHPadWorkList.empty() &&
          "EHPadWorkList not empty when starting to build loop chains.");
   BlockFilterSet LoopBlockSet = collectLoopBlockSet(L);
 
   // Check if we have profile data for this function. If yes, we will rotate
   // this loop by modeling costs more precisely which requires the profile data
   // for better layout.
   bool RotateLoopWithProfile =
       ForcePreciseRotationCost ||
-      (PreciseRotationCost && F->getFunction()->getEntryCount());
+      (PreciseRotationCost && F->getFunction()->hasProfileData());
 
   // First check to see if there is an obviously preferable top block for the
   // loop. This will default to the header, but may end up as one of the
   // predecessors to the header if there is one which will result in strictly
   // fewer branches in the loop body.
   // When we use profile data to rotate the loop, this is unnecessary.
   MachineBasicBlock *LoopTop =
       RotateLoopWithProfile ? L.getHeader() : findBestLoopTop(L, LoopBlockSet);

lib/Transforms/IPO/PartialInlining.cpp

while (OutliningInfo->GetNumInlinedBlocks() < MaxNumInlineBlocks) {
     Entries.insert(Cand);
   }
 
   return OutliningInfo;
 }
 
 // Check if there is PGO data or user annoated branch data:
 static bool hasProfileData(Function *F, FunctionOutliningInfo *OI) {
-  if (F->getEntryCount())
+  if (F->hasProfileData())
     return true;
   // Now check if any of the entry block has MD_prof data:
   for (auto *E : OI->Entries) {
     BranchInst *BR = dyn_cast<BranchInst>(E->getTerminator());
     if (!BR || BR->isUnconditional())
       continue;
     uint64_t T, F;
     if (BR->extractProfMetadata(T, F))
std::pair<bool, Function *> PartialInlinerImpl::unswitchFunction(Function *F) {
 
   if (F->user_begin() == F->user_end())
     return {false, nullptr};
 
   auto &ORE = (*GetORE)(*F);
 
   // Only try to outline cold regions if we have a profile summary, which
   // implies we have profiling information.
-  if (PSI->hasProfileSummary() && F->getEntryCount().hasValue() &&
+  if (PSI->hasProfileSummary() && F->hasProfileData() &&
       !DisableMultiRegionPartialInline) {
     std::unique_ptr<FunctionOutliningMultiRegionInfo> OMRI =
         computeOutliningColdRegionsInfo(F);
     if (OMRI) {
       FunctionCloner Cloner(F, OMRI.get(), ORE);
 
 #ifndef NDEBUG
       if (TracePartialInlining) {
bool PartialInlinerImpl::tryPartialInline(FunctionCloner &Cloner) {
 
   assert(Cloner.OrigFunc->user_begin() == Cloner.OrigFunc->user_end() &&
          "F's users should all be replaced!");
 
   std::vector<User *> Users(Cloner.ClonedFunc->user_begin(),
                             Cloner.ClonedFunc->user_end());
 
   DenseMap<User *, uint64_t> CallSiteToProfCountMap;
-  if (Cloner.OrigFunc->getEntryCount())
+  auto CalleeEntryCount = Cloner.OrigFunc->getEntryCount();
+  if (CalleeEntryCount)
     computeCallsiteToProfCountMap(Cloner.ClonedFunc, CallSiteToProfCountMap);
 
-  auto CalleeEntryCount = Cloner.OrigFunc->getEntryCount();
   uint64_t CalleeEntryCountV = (CalleeEntryCount ? *CalleeEntryCount : 0);
 
   bool AnyInline = false;
   for (User *User : Users) {
     CallSite CS = getCallSite(User);
 
     if (IsLimitReached())
       continue;

lib/Transforms/Scalar/JumpThreading.cpp

 bool JumpThreading::runOnFunction(Function &F) {
   if (skipFunction(F))
     return false;
   auto TLI = &getAnalysis<TargetLibraryInfoWrapperPass>().getTLI();
   auto LVI = &getAnalysis<LazyValueInfoWrapperPass>().getLVI();
   auto AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
   std::unique_ptr<BlockFrequencyInfo> BFI;
   std::unique_ptr<BranchProbabilityInfo> BPI;
-  bool HasProfileData = F.getEntryCount().hasValue();
+  bool HasProfileData = F.hasProfileData();
   if (HasProfileData) {
     LoopInfo LI{DominatorTree(F)};
     BPI.reset(new BranchProbabilityInfo(F, LI, TLI));
     BFI.reset(new BlockFrequencyInfo(F, *BPI, LI));
   }
 
   bool Changed = Impl.runImpl(F, TLI, LVI, AA, HasProfileData, std::move(BFI),
                               std::move(BPI));
   if (PrintLVIAfterJumpThreading) {
     dbgs() << "LVI for function '" << F.getName() << "':\n";
     LVI->printLVI(F, getAnalysis<DominatorTreeWrapperPass>().getDomTree(),
                   dbgs());
   }
   return Changed;
 }
 
 PreservedAnalyses JumpThreadingPass::run(Function &F,
                                          FunctionAnalysisManager &AM) {
   auto &TLI = AM.getResult<TargetLibraryAnalysis>(F);
   auto &LVI = AM.getResult<LazyValueAnalysis>(F);
   auto &AA = AM.getResult<AAManager>(F);
 
   std::unique_ptr<BlockFrequencyInfo> BFI;
   std::unique_ptr<BranchProbabilityInfo> BPI;
-  bool HasProfileData = F.getEntryCount().hasValue();
-  if (HasProfileData) {
+  if (F.hasProfileData()) {
     LoopInfo LI{DominatorTree(F)};
     BPI.reset(new BranchProbabilityInfo(F, LI, &TLI));
     BFI.reset(new BlockFrequencyInfo(F, *BPI, LI));
   }
 
   bool Changed = runImpl(F, &TLI, &LVI, &AA, HasProfileData, std::move(BFI),
                          std::move(BPI));
 

lib/Transforms/Scalar/LoopSink.cpp

static bool sinkLoopInvariantInstructions(Loop &L, AAResults &AA, LoopInfo &LI,
                                           BlockFrequencyInfo &BFI,
                                           ScalarEvolution *SE) {
   BasicBlock *Preheader = L.getLoopPreheader();
   if (!Preheader)
     return false;
 
   // Enable LoopSink only when runtime profile is available.
   // With static profile, the sinking decision may be sub-optimal.
-  if (!Preheader->getParent()->getEntryCount())
+  if (!Preheader->getParent()->hasProfileData())
     return false;
 
   const BlockFrequency PreheaderFreq = BFI.getBlockFreq(Preheader);
   // If there are no basic blocks with lower frequency than the preheader then
   // we can avoid the detailed analysis as we will never find profitable sinking
   // opportunities.
   if (all_of(L.blocks(), [&](const BasicBlock *BB) {
         return BFI.getBlockFreq(BB) > PreheaderFreq;

lib/Transforms/Scalar/LoopUnrollPass.cpp

static bool computeUnrollCount(
   // 6th priority is runtime unrolling.
   // Don't unroll a runtime trip count loop when it is disabled.
   if (HasRuntimeUnrollDisablePragma(L)) {
     UP.Count = 0;
     return false;
   }
   
   // Check if the runtime trip count is too small when profile is available.
-  if (L->getHeader()->getParent()->getEntryCount()) {
+  if (L->getHeader()->getParent()->hasProfileData()) {
     if (auto ProfileTripCount = getLoopEstimatedTripCount(L)) {
       if (*ProfileTripCount < FlatLoopTripCountThreshold)
         return false;
       else
         UP.AllowExpensiveTripCount = true;
     }
   }  
 

lib/Transforms/Utils/LoopUnrollPeel.cpp

if (UserPeelCount) {
     return;
   }
 
   // If we don't know the trip count, but have reason to believe the average
   // trip count is low, peeling should be beneficial, since we will usually
   // hit the peeled section.
   // We only do this in the presence of profile information, since otherwise
   // our estimates of the trip count are not reliable enough.
-  if (UP.AllowPeeling && L->getHeader()->getParent()->getEntryCount()) {
+  if (UP.AllowPeeling && L->getHeader()->getParent()->hasProfileData()) {
     Optional<unsigned> PeelCount = getLoopEstimatedTripCount(L);
     if (!PeelCount)
       return;
 
     DEBUG(dbgs() << "Profile-based estimated trip count is " << *PeelCount
                  << "\n");
 
     if (*PeelCount) {