[llvm] 5898be1 - [mlgo] Remove the protobuf dependency
Florian Hahn via llvm-commits
llvm-commits at lists.llvm.org
Tue Jan 17 14:01:34 PST 2023
Hi,
It looks like this breaks the build on macOS. Please take a look and revert the patch if it is not a straightforward fix.
In file included from /Users/florianhahn/projects/llvm-project/llvm/lib/Analysis/TrainingLogger.cpp:13:
In file included from /Users/florianhahn/projects/llvm-project/llvm/include/llvm/Analysis/TensorSpec.h:16:
/Users/florianhahn/projects/llvm-project/llvm/include/llvm/Support/JSON.h:353:29: error: non-constant-expression cannot be narrowed from type 'unsigned long' to 'int64_t' (aka 'long long') in initializer list [-Wc++11-narrowing]
create<int64_t>(int64_t{I});
^
/Users/florianhahn/projects/llvm-project/llvm/lib/Analysis/TrainingLogger.cpp:133:53: note: in instantiation of function template specialization 'llvm::json::Value::Value<unsigned long, void, void, void>' requested here
JOS.object([&]() { JOS.attribute("observation", Nr); });
^
/Users/florianhahn/projects/llvm-project/llvm/include/llvm/Support/JSON.h:353:29: note: insert an explicit cast to silence this issue
create<int64_t>(int64_t{I});
^
static_cast<int64_t>( )
> On 17 Jan 2023, at 21:12, Mircea Trofin via llvm-commits <llvm-commits at lists.llvm.org> wrote:
>
>
> 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 } }
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> +nr_broken_hints: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0
> +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: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3333333432674408
> +nr_defs_and_uses: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4375,1.0,0.1875,0.3125,0.5625,0.4375,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0416666679084301
> +weighed_reads_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.16428154706954956,0.44343796372413635,0.15784737467765808,0.03242195025086403,1.0,0.011257563717663288,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.00294744991697371
> +weighed_writes_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9071193337440491,0.5188189148902893,0.07705120742321014,1.0,0.03852560371160507,0.19948309659957886,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02568373642861843
> +weighed_read_writes_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.029022665694355965,0.07131929695606232,1.0,0.0,0.0,3.113496960249762e-11,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
> +weighed_indvars_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9434669613838196,0.0,1.0,1.0,0.0,0.07131929695606232,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
> +hint_weights_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7606054544448853,1.0,0.0,0.8061813116073608,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.021535413339734077
> +start_bb_freq_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.46601226925849915,1.0,0.3333333432674408,0.1666666716337204,0.1666666716337204,0.1666666716337204,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3333333432674408
> +end_bb_freq_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.6365708112716675,0.6365708112716675,0.3333333432674408,0.6365708112716675,1.482131917196483e-10,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6365708112716675
> +hottest_bb_freq_by_max: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2631579041481018,0.2813863754272461,0.27892643213272095,0.27892643213272095,1.0,0.01989283785223961,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02235277369618416
> +liverange_size: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2789115607738495,1.0,0.7954931855201721,0.49659863114356995,0.7240646481513977,0.9723639488220215,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8524659872055054
> +use_def_density: 0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.33287474513053894,0.7775528430938721,0.7709200978279114,0.378161758184433,0.04348048195242882,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.007036312483251095
> +max_stage: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4
> +min_stage: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4
> +progress: 0.07692307978868484
> +index_to_evict: 32
> +reward: 36.64127731323242
>
> 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
> @@ -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 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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