[mlgo] Remove the protobuf dependency

The dependency was due to the log format. This change switches to the
previously-introduced (D139370) "dependency-free" logger instead of the
protobuf-based one.

A subsequent change will clean out the unnecessary abstraction left
behind.

This change drops the logger unittest, we have sufficient test coverage
via lit tests, and a unit test would require adding, unnecesarily, a log
reader (the reader is expected to be python, for the ML side, and there
is a reader for that under Analysis/models, used for tests).

Differential Revision: https://reviews.llvm.org/D141720

diff --git a/llvm/CMakeLists.txt b/llvm/CMakeLists.txt
index 58fc885..fb486bd 100644 (file)
--- a/llvm/CMakeLists.txt
+++ b/llvm/CMakeLists.txt
@@ -974,10 +974,7 @@ endif()
 # the bot setup script: https://github.com/google/ml-compiler-opt/blob/main/buildbot/buildbot_init.sh
 set(LLVM_HAVE_TFLITE "" CACHE BOOL "Use tflite")
 if (LLVM_HAVE_TFLITE)
-  find_package(protobuf REQUIRED)
   find_package(tensorflow-lite REQUIRED)
-  set(LLVM_PROTOBUF_OUT_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/protobuf_gen)
-  include_directories(${LLVM_PROTOBUF_OUT_DIR})
 endif()
 
 # For up-to-date instructions for installing the Tensorflow dependency, refer to
@@ -993,13 +990,7 @@ if (NOT TENSORFLOW_AOT_PATH STREQUAL "")
   set(TENSORFLOW_AOT_COMPILER
     "${TENSORFLOW_AOT_PATH}/../../../../bin/saved_model_cli"
     CACHE PATH "Path to the Tensorflow AOT compiler")
-  # This needs to happen to avoid clashing protobuf codegen when building both AOT and development mode.
-  # We plan to replace protobuf with a simpler alternative, so this will go away.
-  file(COPY ${TENSORFLOW_AOT_PATH}/include DESTINATION ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/tensorflow
-    NO_SOURCE_PERMISSIONS
-    PATTERN "google/*" EXCLUDE
-    PATTERN "*.pb.h" EXCLUDE)
-  include_directories(${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/tensorflow/include)
+  include_directories(${TENSORFLOW_AOT_PATH}/include)
   add_subdirectory(${TENSORFLOW_AOT_PATH}/xla_aot_runtime_src
     ${CMAKE_ARCHIVE_OUTPUT_DIRECTORY}/tf_runtime)
   install(TARGETS tf_xla_runtime EXPORT LLVMExports

diff --git a/llvm/cmake/modules/TensorFlowCompile.cmake b/llvm/cmake/modules/TensorFlowCompile.cmake
index 45ec3fe..d5ff44c 100644 (file)
--- a/llvm/cmake/modules/TensorFlowCompile.cmake
+++ b/llvm/cmake/modules/TensorFlowCompile.cmake
@@ -116,18 +116,3 @@ function(tf_find_and_compile model default_url default_path test_model_generator
   set(MLLinkDeps ${MLLinkDeps} tf_xla_runtime PARENT_SCOPE)
   add_definitions(-DLLVM_HAVE_TF_AOT_${fname_allcaps})
 endfunction()
-
-function(build_proto)
-  foreach (P ${ARGV})
-    set(PB_SRCS ${PB_SRCS} ${LLVM_PROTOBUF_OUT_DIR}/${P}.pb.cc)
-    set(PB_HDRS ${PB_HDRS} ${LLVM_PROTOBUF_OUT_DIR}/${P}.pb.h)
-    set(PBS ${PBS} ${TENSORFLOW_SRC_DIR}/${P}.proto)
-  endforeach()
-  add_custom_command(OUTPUT ${PB_SRCS} ${PB_HDRS}
-    COMMAND protobuf::protoc 
-    ARGS --proto_path=${TENSORFLOW_SRC_DIR} --cpp_out=${LLVM_PROTOBUF_OUT_DIR} ${PBS})
-  set_source_files_properties(${PB_SRCS} PROPERTIES
-    GENERATED 1)
-  set(GeneratedMLSources ${GeneratedMLSources} ${PB_SRCS} PARENT_SCOPE)
-  set(MLDeps ${MLDeps} ${MLDeps} PARENT_SCOPE)
-endfunction()

diff --git a/llvm/include/llvm/Analysis/Utils/TrainingLogger.h b/llvm/include/llvm/Analysis/Utils/TrainingLogger.h
index 040fcf2..34f8a3f 100644 (file)
--- a/llvm/include/llvm/Analysis/Utils/TrainingLogger.h
+++ b/llvm/include/llvm/Analysis/Utils/TrainingLogger.h
@@ -11,7 +11,6 @@
 
 #include "llvm/Config/llvm-config.h"
 
-#ifdef LLVM_HAVE_TFLITE
 #include "llvm/ADT/StringMap.h"
 #include "llvm/Analysis/TensorSpec.h"
 #include "llvm/IR/LLVMContext.h"
@@ -23,8 +22,7 @@
 namespace llvm {
 
 /// Logging utility - given an ordered specification of features, and assuming
-/// a scalar reward, allow logging feature values and rewards, and then print
-/// as tf.train.SequenceExample text protobuf.
+/// a scalar reward, allow logging feature values and rewards.
 /// The assumption is that, for an event to be logged (i.e. a set of feature
 /// values and a reward), the user calls the log* API for each feature exactly
 /// once, providing the index matching the position in the feature spec list
@@ -42,7 +40,7 @@ namespace llvm {
 ///   ...
 ///   logFloatReward(...)
 ///
-/// At the end, call print to generate the protobuf.
+/// At the end, call print to generate the log.
 /// Alternatively, don't call logReward at the end of each event, just
 /// log{Float|Int32|Int64}FinalReward at the end.
 class LoggerDataImpl;
@@ -86,7 +84,7 @@ public:
   void flush(raw_ostream &OS);
 
   // Flush a set of logs that are produced from the same module, e.g.
-  // per-function regalloc traces, as a google::protobuf::Struct message.
+  // per-function regalloc traces.
   static void flushLogs(raw_ostream &OS,
                         const StringMap<std::unique_ptr<Logger>> &Loggers);
 
@@ -98,6 +96,4 @@ private:
 };
 
 } // namespace llvm
-
-#endif // LLVM_HAVE_TFLITE
 #endif // LLVM_ANALYSIS_UTILS_TRAININGLOGGER_H

diff --git a/llvm/lib/Analysis/CMakeLists.txt b/llvm/lib/Analysis/CMakeLists.txt
index 9330371..b2c2377 100644 (file)
--- a/llvm/lib/Analysis/CMakeLists.txt
+++ b/llvm/lib/Analysis/CMakeLists.txt
@@ -18,13 +18,8 @@ if (DEFINED LLVM_HAVE_TF_AOT OR LLVM_HAVE_TFLITE)
   endif()
 
   if (LLVM_HAVE_TFLITE)
-    build_proto(
-      tensorflow/core/protobuf/error_codes
-      tensorflow/core/example/feature
-      tensorflow/core/example/example)
     list(APPEND MLLinkDeps
-      tensorflow-lite::tensorflow-lite
-      protobuf::libprotobuf)
+      tensorflow-lite::tensorflow-lite)
   endif()
 endif()
 

diff --git a/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp b/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
index 0fb6d60..63aa4ca 100644 (file)
--- a/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
+++ b/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
@@ -93,13 +93,7 @@ struct InlineEvent {
   int64_t Reward = 0;
 };
 
-/// Collect data we may use for training a model, and write it as a textual
-/// Tensorflow SequenceExample
-/// (https://www.tensorflow.org/api_docs/python/tf/train/SequenceExample)
-/// protobuf (https://developers.google.com/protocol-buffers).
-/// Because this is a protobuf, we cannot just stream the events as they come.
-/// Internally, TrainingLogger stores data in column-major format, because that
-/// lines up with how TF SequenceExample represents it.
+/// Collect data we may use for training a model.
 class TrainingLogger final {
 public:
   TrainingLogger(StringRef LogFileName, const ModelUnderTrainingRunner *MUTR);

diff --git a/llvm/lib/Analysis/TrainingLogger.cpp b/llvm/lib/Analysis/TrainingLogger.cpp
index b87b620..e1cfe54 100644 (file)
--- a/llvm/lib/Analysis/TrainingLogger.cpp
+++ b/llvm/lib/Analysis/TrainingLogger.cpp
@@ -12,11 +12,9 @@
 //===----------------------------------------------------------------------===//
 #include "llvm/Analysis/TensorSpec.h"
 #include "llvm/Config/config.h"
-#if defined(LLVM_HAVE_TFLITE)
 
 #include "llvm/ADT/Twine.h"
 #include "llvm/Analysis/Utils/TrainingLogger.h"
-#include "llvm/Support/Base64.h"
 #include "llvm/Support/CommandLine.h"
 #include "llvm/Support/Debug.h"
 #include "llvm/Support/JSON.h"
@@ -24,36 +22,16 @@
 #include "llvm/Support/Path.h"
 #include "llvm/Support/raw_ostream.h"
 
-#include "google/protobuf/struct.pb.h"
-#include "google/protobuf/text_format.h"
-#include "tensorflow/core/example/example.pb.h"
 #include <cassert>
 #include <numeric>
 
 using namespace llvm;
 
-using google::protobuf::Message;
-using google::protobuf::TextFormat;
-
-static cl::opt<bool>
-    ProtobufTextMode("tfutils-text-log", cl::init(false), cl::Hidden,
-                     cl::desc("Output textual (human-readable) protobuf."));
-
+// FIXME(mtrofin): remove the flag altogether
 static cl::opt<bool>
-    UseSimpleLogger("tfutils-use-simplelogger", cl::init(false), cl::Hidden,
+    UseSimpleLogger("tfutils-use-simplelogger", cl::init(true), cl::Hidden,
                     cl::desc("Output simple (non-protobuf) log."));
 
-namespace {
-
-void serialize(const Message &SE, std::string *OutStr) {
-  if (ProtobufTextMode) {
-    TextFormat::PrintToString(SE, OutStr);
-  } else {
-    *OutStr = SE.SerializeAsString();
-  }
-}
-} // namespace
-
 namespace llvm {
 
 class LoggerDataImpl {
@@ -216,113 +194,14 @@ public:
     return OS;
   }
 };
-
-class TFSequenceExampleLoggerDataImpl : public LoggerDataImpl {
-  std::vector<tensorflow::FeatureList> FeatureLists;
-  tensorflow::FeatureList Reward;
-
-  bool isSelfConsistent(const tensorflow::SequenceExample &SE,
-                        size_t NrRecords) const {
-    bool Ret = true;
-    for (const auto &TSpecs : LoggedFeatureSpecs) {
-      const auto &Name = TSpecs.name();
-      const auto &FL = SE.feature_lists().feature_list().at(Name).feature();
-      if (NrRecords != static_cast<size_t>(FL.size())) {
-        dbgs() << "[TF-UTILS]: " << Name << " has missing records. Expected "
-               << NrRecords << " got " << FL.size() << "\n";
-        Ret = false;
-      }
-    }
-    if (IncludeReward && static_cast<size_t>(SE.feature_lists()
-                                                 .feature_list()
-                                                 .at(RewardSpec.name())
-                                                 .feature()
-                                                 .size()) != NrRecords) {
-      dbgs() << "[TF-UTILS]: reward is missing records.\n";
-      Ret = false;
-    }
-    return Ret;
-  }
-
-  void transferLog(tensorflow::SequenceExample &SE) {
-    auto *FL = SE.mutable_feature_lists()->mutable_feature_list();
-    if (IncludeReward)
-      (*FL)[RewardSpec.name()] = std::move(Reward);
-    assert(FeatureLists.size() == LoggedFeatureSpecs.size());
-    for (size_t I = 0; I < FeatureLists.size(); ++I) {
-      const auto &LFS = LoggedFeatureSpecs[I];
-      (*FL)[LFS.name()] = std::move(FeatureLists[I]);
-    }
-  }
-
-public:
-  TFSequenceExampleLoggerDataImpl(const std::vector<TensorSpec> &LoggedSpecs,
-                                  const TensorSpec &RewardSpec,
-                                  bool IncludeReward)
-      : LoggerDataImpl(LoggedSpecs, RewardSpec, IncludeReward),
-        FeatureLists(LoggedFeatureSpecs.size()) {}
-
-  // flush the logged info to a stream and clear the log contents.
-  void flush(std::string *Str) override {
-    size_t NrRecords = getNrRecords();
-    (void)NrRecords;
-    tensorflow::SequenceExample SE;
-    transferLog(SE);
-    assert(isSelfConsistent(SE, NrRecords));
-    serialize(SE, Str);
-  }
-
-  char *addNewTensor(size_t FeatureID) override {
-    const auto &Spec = LoggedFeatureSpecs[FeatureID];
-    if (Spec.isElementType<float>()) {
-      auto *RF = FeatureLists[FeatureID]
-                     .add_feature()
-                     ->mutable_float_list()
-                     ->mutable_value();
-      RF->Resize(Spec.getElementCount(), 0.0);
-      return reinterpret_cast<char *>(RF->mutable_data());
-    } else if (Spec.isElementType<int32_t>() || Spec.isElementType<int64_t>()) {
-      auto *RF = FeatureLists[FeatureID]
-                     .add_feature()
-                     ->mutable_int64_list()
-                     ->mutable_value();
-      RF->Resize(Spec.getElementCount(), 0);
-      return reinterpret_cast<char *>(RF->mutable_data());
-    }
-    llvm_unreachable("Unsupported tensor type.");
-  }
-
-  void logRewardImpl(const char *Value, size_t Size) override {
-    assert(IncludeReward);
-    if (RewardSpec.isElementType<float>())
-      Reward.add_feature()->mutable_float_list()->add_value(
-          *reinterpret_cast<const float *>(Value));
-    else if (RewardSpec.isElementType<int32_t>())
-      Reward.add_feature()->mutable_int64_list()->add_value(
-          *reinterpret_cast<const int32_t *>(Value));
-    else if (RewardSpec.isElementType<int64_t>())
-      Reward.add_feature()->mutable_int64_list()->add_value(
-          *reinterpret_cast<const int64_t *>(Value));
-    else
-      llvm_unreachable("Unsupported tensor type.");
-  }
-
-  size_t getNrRecords() const override {
-    return FeatureLists.empty() ? 0 : FeatureLists[0].feature().size();
-  }
-};
 } // namespace llvm
 
 Logger::Logger(const std::vector<TensorSpec> &FeatureSpecs,
                const TensorSpec &RewardSpec, bool IncludeReward)
     : FeatureSpecs(FeatureSpecs), RewardSpec(RewardSpec),
       IncludeReward(IncludeReward) {
-  if (UseSimpleLogger)
-    LoggerData = std::make_unique<SimpleLoggerDataImpl>(
-        FeatureSpecs, RewardSpec, IncludeReward);
-  else
-    LoggerData = std::make_unique<TFSequenceExampleLoggerDataImpl>(
-        FeatureSpecs, RewardSpec, IncludeReward);
+  LoggerData = std::make_unique<SimpleLoggerDataImpl>(FeatureSpecs, RewardSpec,
+                                                      IncludeReward);
 }
 
 Logger::~Logger() {}
@@ -398,31 +277,11 @@ void Logger::flush(raw_ostream &OS) {
 
 void Logger::flushLogs(raw_ostream &OS,
                        const StringMap<std::unique_ptr<Logger>> &Loggers) {
-  if (UseSimpleLogger) {
-    bool IsFirst = true;
-    for (const auto &NamedLogger : Loggers) {
-      auto *Impl = NamedLogger.second->LoggerData.get();
-      reinterpret_cast<const SimpleLoggerDataImpl *>(Impl)->flush(
-          OS, IsFirst, NamedLogger.first());
-      IsFirst = false;
-    }
-  } else {
-    google::protobuf::Struct Msg;
-    for (const auto &NamedLogger : Loggers) {
-      tensorflow::SequenceExample SE;
-      const auto &Logger = NamedLogger.second;
-      std::string Unencoded;
-      if (Logger->LoggerData->getNrRecords() > 0)
-        Logger->flush(&Unencoded);
-
-      (*Msg.mutable_fields())[NamedLogger.first().str()]
-          .mutable_string_value()
-          ->append(ProtobufTextMode ? Unencoded : encodeBase64(Unencoded));
-    }
-
-    std::string OutStr;
-    serialize(Msg, &OutStr);
-    OS << OutStr;
+  bool IsFirst = true;
+  for (const auto &NamedLogger : Loggers) {
+    auto *Impl = NamedLogger.second->LoggerData.get();
+    reinterpret_cast<const SimpleLoggerDataImpl *>(Impl)->flush(
+        OS, IsFirst, NamedLogger.first());
+    IsFirst = false;
   }
 }
-#endif // defined(LLVM_HAVE_TFLITE)

diff --git a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-log-noml.txt b/llvm/test/CodeGen/MLRegalloc/Inputs/reference-log-noml.txt
index 2e8eb96..284a992 100644 (file)
--- a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-log-noml.txt
+++ b/llvm/test/CodeGen/MLRegalloc/Inputs/reference-log-noml.txt
@@ -1,443 +1,409 @@
-fields {
- key: "SyFgets"
- value {
- string_value: "feature_lists {
- feature_list {
- key: \"end_bb_freq_by_max\"  value {
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 2.27244862e-10  value: 8.80573836e-10  value: 0.97600925  value: 0.97600925  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0  value: 0.97600925  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 8.80573836e-10  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 0.97600925  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 0  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0.97600925  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.51107651  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 2.27244862e-10  value: 0.97600925  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 0  value: 0.97600925  value: 0  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 2.27244862e-10  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.652218044  value: 0.636570811  value: 0.636570811  value: 0.333333343  value: 0.636570811  value: 1.48213192e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.97600925  value: 0.97600925  value: 0.51107651  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 0.97600925  value: 0.97600925  value: 0.51107651  value: 0.97600925  value: 2.27244862e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.0239907894  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 0.636570811  value: 0.636570811  value: 0.333333343  value: 0.636570811  value: 1.48213192e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 2.77899731e-10  }  }
- feature {  float_list {  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 1  value: 0.636570811  value: 0.636570811  value: 0.333333343  value: 0.636570811  value: 1.48213192e-10  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0  value: 0.636570811  }  }
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- feature_list {
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- }
-}
+context: SyFgets
+observation: 0
+mask: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
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+nr_broken_hints: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+is_hint: 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+is_local: 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+nr_rematerializable: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
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diff --git a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt b/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
index 719e330..2d43fcb 100644 (file)
--- a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
+++ b/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
@@ -1,351 +1,403 @@
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diff --git a/llvm/test/CodeGen/MLRegalloc/dev-mode-extra-features-logging.ll b/llvm/test/CodeGen/MLRegalloc/dev-mode-extra-features-logging.ll
index b7009ed..89ee30b 100644 (file)
--- a/llvm/test/CodeGen/MLRegalloc/dev-mode-extra-features-logging.ll
+++ b/llvm/test/CodeGen/MLRegalloc/dev-mode-extra-features-logging.ll
@@ -6,61 +6,43 @@
 ;
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
 ; RUN:   -regalloc-enable-advisor=development \
-; RUN:   -regalloc-training-log=%t1 -tfutils-text-log \
+; RUN:   -regalloc-training-log=%t1 \
 ; RUN:   -regalloc-enable-development-features < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t1
-; RUN: sed -i 's/\\n key:/\n key:/g' %t1
-; RUN: sed -i 's/\\n feature/\n feature/g' %t1
-; RUN: sed -i 's/\\n/ /g' %t1
-; RUN: FileCheck --input-file %t1 %s
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t1 > %t1.readable
+; RUN: FileCheck --input-file %t1.readable %s
 
 ; RUN: rm -rf %t && mkdir %t
 ; RUN: %python %S/../../../lib/Analysis/models/gen-regalloc-eviction-test-model.py %t_savedmodel
 ; RUN: %python %S/../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
 ; RUN:   -regalloc-enable-advisor=development \
-; RUN:   -regalloc-training-log=%t2 -tfutils-text-log -regalloc-model=%t \
+; RUN:   -regalloc-training-log=%t2 -regalloc-model=%t \
 ; RUN:   -regalloc-enable-development-features < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t2
-; RUN: sed -i 's/\\n key:/\n key:/g' %t2
-; RUN: sed -i 's/\\n feature/\n feature/g' %t2
-; RUN: sed -i 's/\\n/ /g' %t2
-; RUN: FileCheck --input-file %t2 %s
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t2 > %t2.readable
+; RUN: FileCheck --input-file %t2.readable %s
 
 ; CHECK-NOT: nan
-; CHECK-LABEL: key: \"instructions\"
 ; Check the first five opcodes in the first eviction problem
-; CHECK-NEXT: value: 19
-; CHECK-SAME: value: {{([0-9]{4})}}
-; CHECK-SAME: value: 12{{([0-9]{2})}}
-; CHECK-SAME: value: 12{{([0-9]{2})}}
-; The first eviction problem is significantly less than 300 instructions. Check
-; that there is a zero value
-; CHECK-SAME: value: 0
+; Also, the first eviction problem is significantly less than 300 instructions. Check
+; that there is a zero value.
+; Note: we're regex-ing some of the opcodes to avoid test flakyness.
+; CHECK: instructions: 19,{{([0-9]{4})}},12{{([0-9]{2})}},12{{([0-9]{2})}},{{.*}},0,
 ; Only the candidate virtreg and the 10th LR are included in this problem. Make
-; sure the other LRs have values of zero.
-; CHECK-LABEL: key: \"instructions_mapping\"
-; CHECK-COUNT-2700: value: 0
-; CHECK-SAME: value: 1
+; sure the other LRs have values of zero. There are 2700 0s followed by some 1s.
+; There's a limit to how many repetitions can be matched.
+; CHECK: instructions_mapping: {{(((0,){27}){100})}}
+; CHECK-SAME: 1
 ; Indexing 300 back from where the candidate vr actual resides due to the fact
 ; that not all the values between the 10th LR and the candidate are zero.
-; CHECK-COUNT-6600: value: 0
-; CHECK-SAME: value: 1
+; CHECK-SAME-COUNT-6600: 0,
+; CHECK-SAME: 1
 ; Ensure that we can still go through the mapping matrices for the rest of the
 ; eviction problems to make sure we haven't hit the end of the matrix above.
 ; There are a total of 23 eviction problems with this test.
-; CHECK-COUNT-15: int64_list
-; CHECK: key: \"is_free\"
+; CHECK-LABEL: observation: 16
 ; Make sure that we're exporting the mbb_frequencies. Don't actually check
 ; values due to all values being floating point/liable to change very easily.
-; CHECK: key: \"mbb_frequencies\"
+; CHECK: mbb_frequencies:
 ; Make sure that we have the mbb_mapping feature, and that the first couple
 ; of values are correct.
-; CHECK: key: \"mbb_mapping\"
-; CHECK-NEXT: 0
-; CHECK-SAME: 0
-; CHECK-SAME: 0
-; CHECK-SAME: 0
-; CHECK-SAME: 0
-; CHECK-SAME: 1
-; CHECK-SAME: 1
+; CHECK: mbb_mapping: 0,0,0,0,0,1,1

diff --git a/llvm/test/CodeGen/MLRegalloc/dev-mode-log-2-fcts.ll b/llvm/test/CodeGen/MLRegalloc/dev-mode-log-2-fcts.ll
index c53da24..aeda971 100644 (file)
--- a/llvm/test/CodeGen/MLRegalloc/dev-mode-log-2-fcts.ll
+++ b/llvm/test/CodeGen/MLRegalloc/dev-mode-log-2-fcts.ll
@@ -4,22 +4,14 @@
 ; Check that we can log more than 1 function.
 ;
 ; RUN: llc -mtriple=x86_64-linux-unknown -regalloc=greedy -regalloc-enable-advisor=development \
-; RUN:   -regalloc-training-log=%t1 -tfutils-text-log < %s
-; RUN: sed -i 's/ \+/ /g' %t1
-; RUN: sed -i 's/\\n key:/\n key:/g' %t1
-; RUN: sed -i 's/\\n feature/\n feature/g' %t1
-; RUN: sed -i 's/\\n/ /g' %t1
+; RUN:   -regalloc-training-log=%t1 < %s
 ; RUN: FileCheck --input-file %t1 %s
 
 ; RUN: rm -rf %t %t_savedmodel
 ; RUN: %python %S/../../../lib/Analysis/models/gen-regalloc-eviction-test-model.py %t_savedmodel
 ; RUN: %python %S/../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ; RUN: llc -mtriple=x86_64-linux-unknown -regalloc=greedy -regalloc-enable-advisor=development \
-; RUN:   -regalloc-training-log=%t2 -tfutils-text-log -regalloc-model=%t < %s
-; RUN: sed -i 's/ \+/ /g' %t2
-; RUN: sed -i 's/\\n key:/\n key:/g' %t2
-; RUN: sed -i 's/\\n feature/\n feature/g' %t2
-; RUN: sed -i 's/\\n/ /g' %t2
+; RUN:   -regalloc-training-log=%t2 -regalloc-model=%t < %s
 ; RUN: FileCheck --input-file %t2 %s
 
 declare void @f();
@@ -37,8 +29,8 @@ define void @f2(i64 %lhs, i64 %rhs, i64* %addr) !prof !16 {
   ret void
 }
 
-; CHECK:  key: "f1"
-; CHECK:  key: "f2"
+; CHECK:  {"context":"f1"}
+; CHECK:  {"context":"f2"}
 
 !llvm.module.flags = !{!1}
 !1 = !{i32 1, !"ProfileSummary", !2}

diff --git a/llvm/test/CodeGen/MLRegalloc/dev-mode-logging.ll b/llvm/test/CodeGen/MLRegalloc/dev-mode-logging.ll
index c73a71c..d60f563 100644 (file)
--- a/llvm/test/CodeGen/MLRegalloc/dev-mode-logging.ll
+++ b/llvm/test/CodeGen/MLRegalloc/dev-mode-logging.ll
@@ -4,51 +4,47 @@
 ; Check that we log correctly, both with a learned policy, and the default policy
 ;
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
-; RUN:   -regalloc-enable-advisor=development -regalloc-training-log=%t1 \
-; RUN:   -tfutils-text-log < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t1
-; RUN: sed -i 's/\\n key:/\n key:/g' %t1
-; RUN: sed -i 's/\\n feature/\n feature/g' %t1
-; RUN: sed -i 's/\\n/ /g' %t1
-; RUN: FileCheck --input-file %t1 %s --check-prefixes=CHECK,NOML
-; RUN: diff %t1 %S/Inputs/reference-log-noml.txt
+; RUN:   -regalloc-enable-advisor=development -regalloc-training-log=%t1 < %S/Inputs/input.ll
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t1 > %t1.readable
+; RUN: FileCheck --input-file %t1.readable %s --check-prefixes=CHECK,NOML
+; RUN: diff %t1.readable %S/Inputs/reference-log-noml.txt
 
 ; RUN: rm -rf %t_savedmodel %t
 ; RUN: %python %S/../../../lib/Analysis/models/gen-regalloc-eviction-test-model.py %t_savedmodel
 ; RUN: %python %S/../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
 ; RUN:   -regalloc-enable-advisor=development -regalloc-training-log=%t2 \
-; RUN:   -tfutils-text-log -regalloc-model=%t < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t2
-; RUN: sed -i 's/\\n key:/\n key:/g' %t2
-; RUN: sed -i 's/\\n feature/\n feature/g' %t2
-; RUN: sed -i 's/\\n/ /g' %t2
-; RUN: FileCheck --input-file %t2 %s --check-prefixes=CHECK,ML
+; RUN:   -regalloc-model=%t < %S/Inputs/input.ll
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t2 > %t2.readable
+; RUN: FileCheck --input-file %t2.readable %s --check-prefixes=CHECK,ML
 
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
-; RUN:   -regalloc-enable-advisor=development -regalloc-training-log=%t3.log \
-; RUN:   -tfutils-use-simplelogger < %S/Inputs/two-large-fcts.ll
-; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t3.log | FileCheck %s --check-prefixes=CHECK-LOG
+; RUN:   -regalloc-enable-advisor=development -regalloc-training-log=%t3.log < %S/Inputs/two-large-fcts.ll
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t3.log | FileCheck %s --check-prefixes=CHECK-TWO-FCTS
 
 ; CHECK-NOT: nan
-; CHECK-LABEL: key: \"index_to_evict\"
-; ML-NEXT:    value: 9
-; NOML-NEXT:  value: 12
-; CHECK-LABEL: key: \"reward\"
-; ML:   value: 37.06
-; NOML: value: 36.64
-; CHECK-NEXT: feature_list
-; CHECK-NEXT: key: \"start_bb_freq_by_max\"
+; CHECK-LABEL: context: SyFgets
+; CHECK-NEXT: observation: 0
+; ML: index_to_evict: 9
+; NOML: index_to_evict: 12
+; CHECK-NEXT: reward: 0
+; CHECK-NEXT: observation: 1
+; CHECK-NEXT: mask:
+; NOML:      observation: 16
+; ML:      observation: 83
+; ML: reward: 37.06
+; NOML: reward: 36.64
 
-; CHECK-LOG: context: SyFgetsCopy
-; CHECK-LOG-NEXT: observation: 0
-; CHECK-LOG-NEXT: mask: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
-; CHECK-LOG: index_to_evict: 12
-; CHECK-LOG: observation: 16
-; CHECK-LOG: reward: 36.64
-; CHECK-LOG: context: SyFgets
-; CHECK-LOG-NEXT: observation: 0
-; CHECK-LOG-NEXT: mask: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
-; CHECK-LOG: index_to_evict: 12
-; CHECK-LOG: observation: 16
-; CHECK-LOG: reward: 36.64
+
+; CHECK-TWO-FCTS: context: SyFgetsCopy
+; CHECK-TWO-FCTS-NEXT: observation: 0
+; CHECK-TWO-FCTS-NEXT: mask: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
+; CHECK-TWO-FCTS: index_to_evict: 12
+; CHECK-TWO-FCTS: observation: 16
+; CHECK-TWO-FCTS: reward: 36.64
+; CHECK-TWO-FCTS: context: SyFgets
+; CHECK-TWO-FCTS-NEXT: observation: 0
+; CHECK-TWO-FCTS-NEXT: mask: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
+; CHECK-TWO-FCTS: index_to_evict: 12
+; CHECK-TWO-FCTS: observation: 16
+; CHECK-TWO-FCTS: reward: 36.64

diff --git a/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll b/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
index 79bf2c7..3257195 100644 (file)
--- a/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
+++ b/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
@@ -5,30 +5,24 @@
 ;
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
 ; RUN:   -regalloc-enable-priority-advisor=development \
-; RUN:   -regalloc-priority-training-log=%t1 -tfutils-text-log \
+; RUN:   -regalloc-priority-training-log=%t1 \
 ; RUN:   < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t1
-; RUN: sed -i 's/\\n key:/\n key:/g' %t1
-; RUN: sed -i 's/\\n feature/\n feature/g' %t1
-; RUN: sed -i 's/\\n/ /g' %t1
-; RUN: FileCheck --input-file %t1 %s --check-prefixes=CHECK,NOML
-; RUN: diff %t1 %S/Inputs/reference-prio-log-noml.txt
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t1 > %t1.readable
+; RUN: FileCheck --input-file %t1.readable %s --check-prefixes=CHECK,NOML
+; RUN: diff %t1.readable %S/Inputs/reference-prio-log-noml.txt
 
 ; RUN: rm -rf %t && mkdir %t
 ; RUN: %python %S/../../../lib/Analysis/models/gen-regalloc-priority-test-model.py %t_savedmodel
 ; RUN: %python %S/../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ; RUN: llc -o /dev/null -mtriple=x86_64-linux-unknown -regalloc=greedy \
 ; RUN:   -regalloc-enable-priority-advisor=development \
-; RUN:   -regalloc-priority-training-log=%t2 -tfutils-text-log \
+; RUN:   -regalloc-priority-training-log=%t2 \
 ; RUN:   -regalloc-priority-model=%t < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t2
-; RUN: sed -i 's/\\n key:/\n key:/g' %t2
-; RUN: sed -i 's/\\n feature/\n feature/g' %t2
-; RUN: sed -i 's/\\n/ /g' %t2
-; RUN: FileCheck --input-file %t2 %s --check-prefixes=CHECK,ML
+; RUN: %python %S/../../../lib/Analysis/models/log_reader.py %t2 > %t2.readable
+; RUN: FileCheck --input-file %t2.readable %s --check-prefixes=CHECK,ML
 
 ; CHECK-NOT: nan
-; CHECK-LABEL: key: \"priority\"
-; NOML-NEXT: feature {  float_list {  value: 2.68435814e+09  }  }
-; ML-NEXT: feature {  float_list {  value: 3551  }  }
-; CHECK-LABEL: key: \"reward\"
+; CHECK-LABEL: priority:
+; NOML-SAME: 2684358144.0
+; ML-SAME: 3551
+; CHECK-LABEL: reward:

diff --git a/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll b/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
index a78f452..0cd61c8 100644 (file)
--- a/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
+++ b/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
@@ -13,18 +13,22 @@
 ; RUN: %python %S/../../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ;
 ; When the bounds are very wide ("no bounds"), all inlinings happen.
-; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=- -tfutils-text-log -enable-ml-inliner=development -ml-advisor-size-increase-threshold=10.0 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=NOBOUNDS
+; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=%t1 -enable-ml-inliner=development -ml-advisor-size-increase-threshold=10.0 -S < %s | FileCheck %s --check-prefixes=NOBOUNDS-OUT,CHECK
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t1 | FileCheck %s --check-prefix=NOBOUNDS
 ;
 ; When the bounds are very restrictive, the first inlining happens but it's
 ; considered as "bad" (since it trips over the bounds) and its reward is a
 ; penalty. However, the mandatory inlining, which is considered next, happens.
 ; No other inlinings happend.
-; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=- -tfutils-text-log -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.0 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=BOUNDS
+; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=%t2 -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.0 -S < %s | FileCheck %s --check-prefixes=BOUNDS-OUT,CHECK
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t2 | FileCheck %s --check-prefix=BOUNDS
 ;
 ; With more restrictive bounds, the first inlining happens and is OK. The
 ; mandatory inlining happens next, and it trips over the bounds, which then
 ; forces no further inlinings.
-; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=- -tfutils-text-log -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.1 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=RELAXED-BOUNDS
+; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=%t3 -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.1 -S < %s | FileCheck %s --check-prefixes=RELAXED-BOUNDS-OUT,CHECK
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t3 | FileCheck %s --check-prefix=RELAXED-BOUNDS
+
 target datalayout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128"
 target triple = "x86_64-grtev4-linux-gnu"
 declare i64 @f1()
@@ -47,29 +51,22 @@ define i64 @top() {
   ret i64 %r5
 }
 attributes #0 = { alwaysinline }
-; CHECK:       key: "delta_size"
-; CHECK-NEXT:     value {
-; CHECK-NEXT:       feature {
-; CHECK-NEXT:         int64_list {
-; NOBOUNDS-NEXT:        value: 6
-; RELAXED-BOUNDS-NEXT:  value: 6
-; NOBOUNDS-NEXT:      }
-; NOBOUNDS-NEXT:    }
-; NOBOUNDS-NEXT:    feature {
-; NOBOUNDS-NEXT:      int64_list {
-; NOBOUNDS-NEXT:        value: -11
-; NOBOUNDS-NEXT:      }
-; NOBOUNDS-NEXT:    }
-; NOBOUNDS-NEXT:    feature {
-; NOBOUNDS-NEXT:      int64_list {
-; NOBOUNDS-NEXT:        value: 4
-; BOUNDS-NEXT:          value: 2147483647
-; CHECK-NEXT:         }
+; NOBOUNDS: observation: 0
+; NOBOUNDS: delta_size: 6
+; RELAXED-BOUNDS: delta_size: 6
+; BOUNDS: delta_size: 2147483647
+; NOBOUNDS: observation: 1
+; BOUNDS-NOT: observation
+; RELAXED-BOUNDS-NOT: observation
+; NOBOUNDS: delta_size: -11
+; NOBOUNDS: observation: 2
+; NOBOUNDS: delta_size: 4
+
 ; CHECK-LABEL: @top
 ; must_be_inlined must always be inlined, so we won't find a call to it in @top()
 ; CHECK-NOT: call i64 @must_be_inlined
 ; @some-function isn't mandatory, and when we set the increase threshold too low,
 ; it won't be inlined.
-; NOBOUNDS-NOT: @may_not_be_inlined
-; RELAXED-BOUNDS: call i64 @may_not_be_inlined
-; BOUNDS: call i64 @may_not_be_inlined
+; NOBOUNDS-OUT-NOT: @may_not_be_inlined
+; RELAXED-BOUNDS-OUT: call i64 @may_not_be_inlined
+; BOUNDS-OUT: call i64 @may_not_be_inlined

diff --git a/llvm/test/Transforms/Inline/ML/dev-mode-log-deleted.ll b/llvm/test/Transforms/Inline/ML/dev-mode-log-deleted.ll
index 4a389a8..50cedcc 100644 (file)
--- a/llvm/test/Transforms/Inline/ML/dev-mode-log-deleted.ll
+++ b/llvm/test/Transforms/Inline/ML/dev-mode-log-deleted.ll
@@ -1,6 +1,7 @@
 ; REQUIRES: have_tflite
 ; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner \
-; RUN:     -training-log=- -tfutils-text-log  -S < %s | FileCheck %s 
+; RUN:     -training-log=%t -S < %s 
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t | FileCheck %s 
 
 define i32 @top() {
     %a = call i32 @to_be_deleted()
@@ -17,16 +18,7 @@ define i32 @externally_visible() {
     ret i32 2
 }
 
-; CHECK:        key: "inlining_decision"
-; CHECK-NEXT:   value {
-; CHECK-NEXT:     feature {
-; CHECK-NEXT:       int64_list {
-; CHECK-NEXT:         value: 1
-; CHECK-NEXT:       }
-; CHECK-NEXT:     }
-; CHECK-NEXT:     feature {
-; CHECK-NEXT:       int64_list {
-; CHECK-NEXT:         value: 1
-; CHECK-NEXT:       }
-; CHECK-NEXT:     }
-; CHECK-NEXT:   }
\ No newline at end of file
+; CHECK: observation: 0
+; CHECK: inlining_decision: 1
+; CHECK: observation: 1
+; CHECK: inlining_decision: 1

diff --git a/llvm/test/Transforms/Inline/ML/development-training-log.ll b/llvm/test/Transforms/Inline/ML/development-training-log.ll
index 5f942a3..b53b6bc 100644 (file)
--- a/llvm/test/Transforms/Inline/ML/development-training-log.ll
+++ b/llvm/test/Transforms/Inline/ML/development-training-log.ll
@@ -5,11 +5,16 @@
 ; RUN: %python %S/../../../../lib/Analysis/models/gen-inline-oz-test-model.py %t_savedmodel
 ; RUN: %python %S/../../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ;
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -tfutils-text-log -ml-inliner-model-under-training=%t -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s 
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -tfutils-text-log -ml-inliner-model-under-training=%t -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-output-spec-override=%S/Inputs/test_output_spec.json -S < %s | FileCheck %s --check-prefixes=EXTRA-OUTPUTS,CHECK
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -tfutils-text-log -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -tfutils-text-log -ml-inliner-model-under-training=%t -S < %s | FileCheck %s --check-prefix=NOREWARD
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -tfutils-text-log -S < %s | FileCheck %s --check-prefix=NOREWARD
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=%t1 -ml-inliner-model-under-training=%t -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t1 | FileCheck %s
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=%t2 -ml-inliner-model-under-training=%t -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-output-spec-override=%S/Inputs/test_output_spec.json -S < %s
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t2 | FileCheck %s --check-prefixes=EXTRA-OUTPUTS,CHECK
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=%t3 -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t3 | FileCheck %s
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=%t4 -ml-inliner-model-under-training=%t -S < %s
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t4 | FileCheck %s --check-prefix=NOREWARD
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=%t5 -S < %s
+; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t5| FileCheck %s --check-prefix=NOREWARD
 target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
 target triple = "x86_64-pc-linux-gnu"
 declare i32 @f1(i32)
@@ -35,23 +40,9 @@ define dso_local i32 @top() {
 !llvm.ident = !{!1}
 !0 = !{i32 1, !"wchar_size", i32 4}
 !1 = !{!"clang version 7.0.0-6 (tags/RELEASE_700/final)"}
-; Check we produce a protobuf that has inlining decisions and rewards.
-; CHECK:                  key: "delta_size"
-; CHECK-NEXT:               value {
-; CHECK-NEXT:                 feature {
-; CHECK-NEXT:                   int64_list {
-; CHECK-NEXT:                     value: 0
-; CHECK-NEXT:                   }
-; CHECK-NEXT:                 }
-; CHECK-NOT: fake_extra_output
-; EXTRA-OUTPUTS:          key: "fake_extra_output"
-; EXTRA-OUTPUTS-NEXT:       value {
-; EXTRA-OUTPUTS-NEXT:         feature {
-; EXTRA-OUTPUTS-NEXT:           int64_list {
-; EXTRA-OUTPUTS-NEXT:             value: {{[0-9]+}}
-; CHECK:                  key: "inlining_decision"
-; CHECK-NEXT:               value {
-; CHECK-NEXT:                 feature {
-; CHECK-NEXT:                   int64_list {
-; CHECK-NEXT:                     value: 1
-; NOREWARD-NOT: key: "delta_size"
+; Check we produce a log that has inlining decisions and rewards.
+; CHECK-NOT:        fake_extra_output:
+; EXTRA-OUTPUTS:    fake_extra_output: {{[0-9]+}}
+; CHECK:            inlining_decision: 1
+; CHECK:            delta_size: 0
+; NOREWARD-NOT:     delta_size:

diff --git a/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll b/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
index e5aece6..89f6c9c 100644 (file)
--- a/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
+++ b/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
@@ -12,7 +12,7 @@
 ; RUN: %python %S/../../../../lib/Analysis/models/saved-model-to-tflite.py %t_savedmodel %t
 ; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=default -S < %S/Inputs/test-module.ll 2>&1 | FileCheck %S/Inputs/test-module.ll --check-prefix=DEFAULT
 ; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=development -ml-inliner-model-under-training=%t -S < %S/Inputs/test-module.ll 2>&1 | FileCheck %S/Inputs/test-module.ll --check-prefix=CHECK
-; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=development -training-log=%t.log -tfutils-use-simplelogger -S < %S/Inputs/test-module.ll 2>&1
+; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=development -training-log=%t.log -S < %S/Inputs/test-module.ll 2>&1
 ; RUN: %python %S/../../../../lib/Analysis/models/log_reader.py %t.log | FileCheck %s --check-prefix=CHECK-LOG
 
 CHECK-LOG: observation: 0

diff --git a/llvm/unittests/Analysis/CMakeLists.txt b/llvm/unittests/Analysis/CMakeLists.txt
index 02b5978..7b9f942 100644 (file)
--- a/llvm/unittests/Analysis/CMakeLists.txt
+++ b/llvm/unittests/Analysis/CMakeLists.txt
@@ -57,7 +57,7 @@ set(ANALYSIS_TEST_SOURCES
 # complain about unused file.
 set(LLVM_OPTIONAL_SOURCES InlineAdvisorPlugin.cpp)
 
-set(MLGO_TESTS TFUtilsTest.cpp TrainingLoggerTest.cpp)
+set(MLGO_TESTS TFUtilsTest.cpp)
 if (LLVM_HAVE_TFLITE)
   LIST(APPEND ANALYSIS_TEST_SOURCES ${MLGO_TESTS})
 else()

diff --git a/llvm/unittests/Analysis/TrainingLoggerTest.cpp b/llvm/unittests/Analysis/TrainingLoggerTest.cpp
deleted file mode 100644 (file)
index 07b9959..0000000
--- a/llvm/unittests/Analysis/TrainingLoggerTest.cpp
+++ /dev/null
@@ -1,192 +0,0 @@
-//===- TrainingLoggerTest.cpp - test for TrainingLogger -------------------===//
-//
-// 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
-//
-//===----------------------------------------------------------------------===//
-
-#include "llvm/Analysis/Utils/TrainingLogger.h"
-#include "google/protobuf/struct.pb.h"
-#include "tensorflow/core/example/example.pb.h"
-#include "tensorflow/core/example/feature.pb.h"
-#include "llvm/Analysis/TensorSpec.h"
-#include "llvm/AsmParser/Parser.h"
-#include "llvm/IR/Dominators.h"
-#include "llvm/IR/Instructions.h"
-#include "llvm/IR/LLVMContext.h"
-#include "llvm/IR/Module.h"
-#include "llvm/Support/Path.h"
-#include "llvm/Support/SourceMgr.h"
-#include "llvm/Testing/Support/SupportHelpers.h"
-#include "gtest/gtest.h"
-
-using namespace llvm;
-
-extern const char *TestMainArgv0;
-
-// NOTE! This test model is currently also used by test/Transforms/Inline/ML
-// tests
-//- relevant if updating this model.
-
-#define PROTO_CHECKER(FNAME, TYPE, INDEX, EXP)                                 \
-  do {                                                                         \
-    const auto &V = Expected.feature_lists()                                   \
-                        .feature_list()                                        \
-                        .at(FNAME)                                             \
-                        .feature(INDEX)                                        \
-                        .TYPE()                                                \
-                        .value();                                              \
-    for (auto I = 0; I < V.size(); ++I)                                        \
-      EXPECT_EQ(V.at(I), EXP[I]);                                              \
-  } while (false)
-
-TEST(TrainingLoggerTest, Logger) {
-  std::vector<TensorSpec> Features{
-      TensorSpec::createSpec<float>("the_float", {2, 3}),
-      TensorSpec::createSpec<int64_t>("alternate_name", {2})};
-
-  auto Rewards = TensorSpec::createSpec<float>("reward", {1});
-  Logger L(Features, Rewards, true);
-  const float F00[]{0.0, 0.1, 0.2, 0.3, 0.4, 0.5};
-  const int64_t F01[]{2, 3};
-
-  L.logFloatValue(0, F00);
-  L.logInt64Value(1, F01);
-  L.logFloatReward(3.4);
-  const float F10[]{0.0, 1.0, 2.0, 3.0, 4.0, 5.0};
-  const int64_t F11[]{-2, -3};
-  L.logFloatValue(0, F10);
-  L.logInt64Value(1, F11);
-  L.logFloatReward(-3.0);
-  std::string Result;
-  raw_string_ostream OS(Result);
-  L.flush(OS);
-
-  tensorflow::SequenceExample Expected;
-  ASSERT_TRUE(Expected.ParseFromString(Result));
-  PROTO_CHECKER("the_float", float_list, 0, F00);
-  PROTO_CHECKER("the_float", float_list, 1, F10);
-  PROTO_CHECKER("alternate_name", int64_list, 0, F01);
-  PROTO_CHECKER("alternate_name", int64_list, 1, F11);
-  float R0[]{3.4};
-  float R1[]{-3.0};
-  PROTO_CHECKER("reward", float_list, 0, R0);
-  PROTO_CHECKER("reward", float_list, 1, R1);
-}
-
-TEST(TrainingLoggerTest, LoggerInt32FeaturesAndReward) {
-  std::vector<TensorSpec> Features{
-      TensorSpec::createSpec<float>("the_float", {2, 3}),
-      TensorSpec::createSpec<int32_t>("alternate_name", {2})};
-
-  auto Rewards = TensorSpec::createSpec<int32_t>("reward", {1});
-  Logger L(Features, Rewards, true);
-  const float F00[]{0.0, 0.1, 0.2, 0.3, 0.4, 0.5};
-  const int32_t F01[]{2, 3};
-
-  L.logFloatValue(0, F00);
-  L.logInt32Value(1, F01);
-  L.logInt32Reward(3);
-  const float F10[]{0.0, 1.0, 2.0, 3.0, 4.0, 5.0};
-  const int32_t F11[]{-2, -3};
-  L.logFloatValue(0, F10);
-  L.logInt32Value(1, F11);
-  L.logInt32Reward(-3);
-  std::string Result;
-  raw_string_ostream OS(Result);
-  L.flush(OS);
-
-  tensorflow::SequenceExample Expected;
-  ASSERT_TRUE(Expected.ParseFromString(Result));
-  PROTO_CHECKER("the_float", float_list, 0, F00);
-  PROTO_CHECKER("the_float", float_list, 1, F10);
-  PROTO_CHECKER("alternate_name", int64_list, 0, F01);
-  PROTO_CHECKER("alternate_name", int64_list, 1, F11);
-  int32_t R0[]{3};
-  int32_t R1[]{-3};
-  PROTO_CHECKER("reward", int64_list, 0, R0);
-  PROTO_CHECKER("reward", int64_list, 1, R1);
-}
-
-TEST(TrainingLoggerTest, LoggerNoReward) {
-  std::vector<TensorSpec> Features{
-      TensorSpec::createSpec<float>("the_float", {2, 3}),
-      TensorSpec::createSpec<int64_t>("alternate_name", {2})};
-
-  auto Rewards = TensorSpec::createSpec<float>("reward", {1});
-  Logger L(Features, Rewards, false);
-  const float F00[]{0.0, 0.1, 0.2, 0.3, 0.4, 0.5};
-  const int64_t F01[]{2, 3};
-
-  L.logFloatValue(0, F00);
-  L.logInt64Value(1, F01);
-  const float F10[]{0.0, 1.0, 2.0, 3.0, 4.0, 5.0};
-  const int64_t F11[]{-2, -3};
-  L.logFloatValue(0, F10);
-  L.logInt64Value(1, F11);
-
-  std::string Result;
-  raw_string_ostream OS(Result);
-  L.flush(OS);
-  tensorflow::SequenceExample Expected;
-  ASSERT_TRUE(Expected.ParseFromString(Result));
-  PROTO_CHECKER("the_float", float_list, 0, F00);
-  PROTO_CHECKER("the_float", float_list, 1, F10);
-  PROTO_CHECKER("alternate_name", int64_list, 0, F01);
-  PROTO_CHECKER("alternate_name", int64_list, 1, F11);
-}
-
-TEST(TrainingLoggerTest, LoggerFinalReward) {
-  std::vector<TensorSpec> Features{
-      TensorSpec::createSpec<float>("the_float", {1}),
-      TensorSpec::createSpec<int64_t>("the_int", {1})};
-
-  auto Rewards = TensorSpec::createSpec<float>("reward", {1});
-  Logger L(Features, Rewards, true);
-  for (int64_t I = 0; I < 3; ++I) {
-    float F = static_cast<float>(I);
-    L.logFloatValue(0, &F);
-    L.logInt64Value(1, &I);
-  }
-  L.logFloatFinalReward(3.14);
-  std::string Result;
-  raw_string_ostream OS(Result);
-  L.flush(OS);
-  const float Zero[]{0.0};
-  const float R[]{3.14};
-  tensorflow::SequenceExample Expected;
-  ASSERT_TRUE(Expected.ParseFromString(Result));
-  PROTO_CHECKER("reward", float_list, 0, Zero);
-  PROTO_CHECKER("reward", float_list, 1, Zero);
-  PROTO_CHECKER("reward", float_list, 2, R);
-}
-
-TEST(TrainingLoggerTest, LoggerGroup) {
-  std::vector<TensorSpec> Features{
-      TensorSpec::createSpec<float>("the_float", {1}),
-      TensorSpec::createSpec<int64_t>("the_int", {1})};
-
-  auto Rewards = TensorSpec::createSpec<float>("reward", {1});
-  StringMap<std::unique_ptr<Logger>> Loggers;
-  std::vector<std::string> Names{"a", "b"};
-  size_t Bump = 0;
-  for (auto Name : Names) {
-    auto L = std::make_unique<Logger>(Features, Rewards, true);
-    for (int64_t I = 0; I < 3; ++I) {
-      float F = static_cast<float>(I) + Bump;
-      L->logFloatValue(0, &F);
-      L->logInt64Value(1, &I);
-    }
-    L->logFloatFinalReward(3.14 + Bump);
-    Loggers.insert(std::make_pair(Name, std::move(L)));
-  }
-  std::string Result;
-  raw_string_ostream OS(Result);
-  Logger::flushLogs(OS, Loggers);
-  google::protobuf::Struct Expected;
-  ASSERT_TRUE(Expected.ParseFromString(Result));
-  EXPECT_EQ(Expected.fields_size(), 2);
-  EXPECT_TRUE(Expected.fields().contains("a"));
-  EXPECT_TRUE(Expected.fields().contains("b"));
-}