[MLGO] Remove Extra Dev Mode Features (#167273)

These essentially embedded the MIR into tensors that we could then
process on the ML side. We have not used this for any experimentation in
the past year or two and the work has largely been superseded by
MIR2Vec, which is what we are going to experiment with going forward.

Author: boomanaiden154

llvm/lib/CodeGen/MLRegAllocEvictAdvisor.cpp

@@ -83,13 +83,6 @@ static cl::opt<std::string> ModelUnderTraining(
     "regalloc-model", cl::Hidden,
     cl::desc("The model being trained for register allocation eviction"));
 
-static cl::opt<bool> EnableDevelopmentFeatures(
-    "regalloc-enable-development-features", cl::Hidden,
-    cl::desc("Whether or not to enable features under development for the ML "
-             "regalloc advisor"));
-
-#else
-static const bool EnableDevelopmentFeatures = false;
 #endif // #ifdef LLVM_HAVE_TFLITE
 
 /// The score injection pass.
@@ -212,23 +205,6 @@ static const std::vector<int64_t> PerLiveRangeShape{1, NumberOfInterferences};
     "lowest stage of an interval in this LR")                                  \
   M(float, progress, {1}, "ratio of current queue size to initial size")
 
-#ifdef LLVM_HAVE_TFLITE
-#define RA_EVICT_FIRST_DEVELOPMENT_FEATURE(M)                                  \
-  M(int64_t, instructions, InstructionsShape,                                  \
-    "Opcodes of the instructions covered by the eviction problem")
-
-#define RA_EVICT_REST_DEVELOPMENT_FEATURES(M)                                  \
-  M(int64_t, instructions_mapping, InstructionsMappingShape,                   \
-    "A binary matrix mapping LRs to instruction opcodes")                      \
-  M(float, mbb_frequencies, MBBFrequencyShape,                                 \
-    "A vector of machine basic block frequencies")                             \
-  M(int64_t, mbb_mapping, InstructionsShape,                                   \
-    "A vector of indices mapping instructions to MBBs")
-#else
-#define RA_EVICT_FIRST_DEVELOPMENT_FEATURE(M)
-#define RA_EVICT_REST_DEVELOPMENT_FEATURES(M)
-#endif
-
 // The model learns to pick one of the mask == 1 interferences. This is the
 // name of the output tensor. The contract with the model is that the output
 // will be guaranteed to be to a mask == 1 position. Using a macro here to
@@ -242,12 +218,6 @@ enum FeatureIDs {
 #define _FEATURE_IDX_SIMPLE(_, name, __, ___) name
 #define _FEATURE_IDX(A, B, C, D) _FEATURE_IDX_SIMPLE(A, B, C, D),
   RA_EVICT_FEATURES_LIST(_FEATURE_IDX) FeatureCount,
-#ifdef LLVM_HAVE_TFLITE
-  RA_EVICT_FIRST_DEVELOPMENT_FEATURE(_FEATURE_IDX_SIMPLE) = FeatureCount,
-#else
-  RA_EVICT_FIRST_DEVELOPMENT_FEATURE(_FEATURE_IDX)
-#endif // #ifdef LLVM_HAVE_TFLITE
-  RA_EVICT_REST_DEVELOPMENT_FEATURES(_FEATURE_IDX) FeaturesWithDevelopmentCount
 #undef _FEATURE_IDX
 #undef _FEATURE_IDX_SIMPLE
 };
@@ -268,11 +238,7 @@ void resetInputs(MLModelRunner &Runner) {
   std::memset(Runner.getTensorUntyped(FeatureIDs::NAME), 0,                    \
               getTotalSize<TYPE>(SHAPE));
   RA_EVICT_FEATURES_LIST(_RESET)
-  if (EnableDevelopmentFeatures) {
-    RA_EVICT_FIRST_DEVELOPMENT_FEATURE(_RESET)
-    RA_EVICT_REST_DEVELOPMENT_FEATURES(_RESET)
 #undef _RESET
-  }
 }
 
 // Per-live interval components that get aggregated into the feature values
@@ -398,13 +364,7 @@ class ReleaseModeEvictionAdvisorProvider final
 public:
   ReleaseModeEvictionAdvisorProvider(LLVMContext &Ctx)
       : RegAllocEvictionAdvisorProvider(AdvisorMode::Release, Ctx) {
-    if (EnableDevelopmentFeatures) {
-      InputFeatures = {RA_EVICT_FEATURES_LIST(
-          _DECL_FEATURES) RA_EVICT_FIRST_DEVELOPMENT_FEATURE(_DECL_FEATURES)
-                           RA_EVICT_REST_DEVELOPMENT_FEATURES(_DECL_FEATURES)};
-    } else {
-      InputFeatures = {RA_EVICT_FEATURES_LIST(_DECL_FEATURES)};
-    }
+    InputFeatures = {RA_EVICT_FEATURES_LIST(_DECL_FEATURES)};
   }
   // support for isa<> and dyn_cast.
   static bool classof(const RegAllocEvictionAdvisorProvider *R) {
@@ -500,25 +460,12 @@ class DevelopmentModeEvictionAdvisorProvider final
 public:
   DevelopmentModeEvictionAdvisorProvider(LLVMContext &Ctx)
       : RegAllocEvictionAdvisorProvider(AdvisorMode::Development, Ctx) {
-    if (EnableDevelopmentFeatures) {
-      InputFeatures = {RA_EVICT_FEATURES_LIST(
-          _DECL_FEATURES) RA_EVICT_FIRST_DEVELOPMENT_FEATURE(_DECL_FEATURES)
-                           RA_EVICT_REST_DEVELOPMENT_FEATURES(_DECL_FEATURES)};
-      TrainingInputFeatures = {
-          RA_EVICT_FEATURES_LIST(_DECL_TRAIN_FEATURES)
-              RA_EVICT_FIRST_DEVELOPMENT_FEATURE(_DECL_TRAIN_FEATURES)
-                  RA_EVICT_REST_DEVELOPMENT_FEATURES(_DECL_TRAIN_FEATURES)
-                      TensorSpec::createSpec<float>("action_discount", {1}),
-          TensorSpec::createSpec<int32_t>("action_step_type", {1}),
-          TensorSpec::createSpec<float>("action_reward", {1})};
-    } else {
-      InputFeatures = {RA_EVICT_FEATURES_LIST(_DECL_FEATURES)};
-      TrainingInputFeatures = {
-          RA_EVICT_FEATURES_LIST(_DECL_TRAIN_FEATURES)
-              TensorSpec::createSpec<float>("action_discount", {1}),
-          TensorSpec::createSpec<int32_t>("action_step_type", {1}),
-          TensorSpec::createSpec<float>("action_reward", {1})};
-    }
+    InputFeatures = {RA_EVICT_FEATURES_LIST(_DECL_FEATURES)};
+    TrainingInputFeatures = {
+        RA_EVICT_FEATURES_LIST(_DECL_TRAIN_FEATURES)
+            TensorSpec::createSpec<float>("action_discount", {1}),
+        TensorSpec::createSpec<int32_t>("action_step_type", {1}),
+        TensorSpec::createSpec<float>("action_reward", {1})};
     if (ModelUnderTraining.empty() && TrainingLog.empty()) {
       Ctx.emitError("Regalloc development mode should be requested with at "
                     "least logging enabled and/or a training model");
@@ -814,34 +761,6 @@ MCRegister MLEvictAdvisor::tryFindEvictionCandidate(
                     /*NumUrgent*/ 0.0, LRPosInfo);
   assert(InitialQSize > 0.0 && "We couldn't have gotten here if we had "
                                "nothing to allocate initially.");
-#ifdef LLVM_HAVE_TFLITE
-  if (EnableDevelopmentFeatures) {
-    extractInstructionFeatures(
-        LRPosInfo, Runner,
-        [this](SlotIndex InputIndex) -> int {
-          auto *CurrentMachineInstruction =
-              LIS->getInstructionFromIndex(InputIndex);
-          if (!CurrentMachineInstruction) {
-            return -1;
-          }
-          return CurrentMachineInstruction->getOpcode();
-        },
-        [this](SlotIndex InputIndex) -> float {
-          auto *CurrentMachineInstruction =
-              LIS->getInstructionFromIndex(InputIndex);
-          return MBFI.getBlockFreqRelativeToEntryBlock(
-              CurrentMachineInstruction->getParent());
-        },
-        [this](SlotIndex InputIndex) -> MachineBasicBlock * {
-          auto *CurrentMachineInstruction =
-              LIS->getInstructionFromIndex(InputIndex);
-          return CurrentMachineInstruction->getParent();
-        },
-        FeatureIDs::instructions, FeatureIDs::instructions_mapping,
-        FeatureIDs::mbb_frequencies, FeatureIDs::mbb_mapping,
-        LIS->getSlotIndexes()->getLastIndex());
-  }
-#endif // #ifdef LLVM_HAVE_TFLITE
   // Normalize the features.
   for (auto &V : Largest)
     V = V ? V : 1.0;
@@ -987,13 +906,6 @@ void MLEvictAdvisor::extractFeatures(
 
     HintWeights += LIFC.HintWeights;
     NumRematerializable += LIFC.IsRemat;
-
-    if (EnableDevelopmentFeatures) {
-      for (auto CurrentSegment : LI) {
-        LRPosInfo.push_back(
-            LRStartEndInfo{CurrentSegment.start, CurrentSegment.end, Pos});
-      }
-    }
   }
   size_t Size = 0;
   if (!Intervals.empty()) {
@@ -1209,9 +1121,7 @@ int64_t DevelopmentModeEvictAdvisor::tryFindEvictionCandidatePosition(
 
   Log->startObservation();
   size_t CurrentFeature = 0;
-  size_t FeatureCount = EnableDevelopmentFeatures
-                            ? FeatureIDs::FeaturesWithDevelopmentCount
-                            : FeatureIDs::FeatureCount;
+  size_t FeatureCount = FeatureIDs::FeatureCount;
   for (; CurrentFeature < FeatureCount; ++CurrentFeature) {
     Log->logTensorValue(CurrentFeature,
                         reinterpret_cast<const char *>(