[llvm] 5898be1 - [mlgo] Remove the protobuf dependency
Mircea Trofin via llvm-commits
llvm-commits at lists.llvm.org
Tue Jan 17 13:12:38 PST 2023
Author: Mircea Trofin
Date: 2023-01-17T13:12:27-08:00
New Revision: 5898be19e66d97662e9d87c526105c6ebd961cba
URL: https://github.com/llvm/llvm-project/commit/5898be19e66d97662e9d87c526105c6ebd961cba
DIFF: https://github.com/llvm/llvm-project/commit/5898be19e66d97662e9d87c526105c6ebd961cba.diff
LOG: [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
Added:
Modified:
llvm/CMakeLists.txt
llvm/cmake/modules/TensorFlowCompile.cmake
llvm/include/llvm/Analysis/Utils/TrainingLogger.h
llvm/lib/Analysis/CMakeLists.txt
llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
llvm/lib/Analysis/TrainingLogger.cpp
llvm/test/CodeGen/MLRegalloc/Inputs/reference-log-noml.txt
llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
llvm/test/CodeGen/MLRegalloc/dev-mode-extra-features-logging.ll
llvm/test/CodeGen/MLRegalloc/dev-mode-log-2-fcts.ll
llvm/test/CodeGen/MLRegalloc/dev-mode-logging.ll
llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
llvm/test/Transforms/Inline/ML/dev-mode-log-deleted.ll
llvm/test/Transforms/Inline/ML/development-training-log.ll
llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
llvm/unittests/Analysis/CMakeLists.txt
Removed:
llvm/unittests/Analysis/TrainingLoggerTest.cpp
################################################################################
diff --git a/llvm/CMakeLists.txt b/llvm/CMakeLists.txt
index 58fc88541573b..fb486bdfcb2fc 100644
--- 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 45ec3fe7c327e..d5ff44c9330d1 100644
--- 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 040fcf2f9d8b2..34f8a3f9fd6f9 100644
--- 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 @@ class Logger final {
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 @@ class Logger final {
};
} // 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 93303719ccfb3..b2c237797ceb5 100644
--- 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 0fb6d604bfe2f..63aa4ca3301f6 100644
--- 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 b87b6201e44c6..e1cfe54ff31a5 100644
--- 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 @@ class SimpleLoggerDataImpl : public LoggerDataImpl {
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 2e8eb96659e0d..284a992b999d4 100644
--- 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 } }
- 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 } } } }
- feature_list {
- key: \"hint_weights_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: 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 value: 0 value: 0 value: 0 value: 0 value: 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 719e330818dc6..2d43fcbfd0f9b 100644
--- a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
+++ b/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
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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 b7009ed8ac564..89ee30bde7fbf 100644
--- 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 c53da24410e4d..aeda97156fc64 100644
--- 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 c73a71c7bc32c..d60f563c2741f 100644
--- 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 79bf2c73daad1..3257195d8cbc6 100644
--- 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 a78f4523b2137..0cd61c8a232d9 100644
--- 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 4a389a8277684..50cedcc7efb09 100644
--- 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 5f942a310fa05..b53b6bc95ef11 100644
--- 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 e5aece66f6dc9..89f6c9ceb2463 100644
--- 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 02b59789660c4..7b9f942be6977 100644
--- 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
index 07b9959cb8566..0000000000000
--- 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"));
-}
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