llvm/lib/Analysis/TrainingLogger.cpp

   1 //===- TrainingLogger.cpp - mlgo feature/reward logging -------------------===//
   2 //
   3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
   4 // See https://llvm.org/LICENSE.txt for license information.
   5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
   6 //
   7 //===----------------------------------------------------------------------===//
   8 //
   9 // This file implements logging infrastructure for extracting features and
  10 // rewards for mlgo policy training.
  11 //
  12 //===----------------------------------------------------------------------===//
  13 #include "llvm/Analysis/TensorSpec.h"
  14 #include "llvm/Config/config.h"
  15
  16 #include "llvm/ADT/Twine.h"
  17 #include "llvm/Analysis/Utils/TrainingLogger.h"
  18 #include "llvm/Support/CommandLine.h"
  19 #include "llvm/Support/Debug.h"
  20 #include "llvm/Support/JSON.h"
  21 #include "llvm/Support/MemoryBuffer.h"
  22 #include "llvm/Support/Path.h"
  23 #include "llvm/Support/raw_ostream.h"
  24
  25 #include <cassert>
  26 #include <numeric>
  27
  28 using namespace llvm;
  29
  30 void Logger::writeHeader(std::optional<TensorSpec> AdviceSpec) {
  31   json::OStream JOS(*OS);
  32   JOS.object([&]() {
  33     JOS.attributeArray("features", [&]() {
  34       for (const auto &TS : FeatureSpecs)
  35         TS.toJSON(JOS);
  36     });
  37     if (IncludeReward) {
  38       JOS.attributeBegin("score");
  39       RewardSpec.toJSON(JOS);
  40       JOS.attributeEnd();
  41     }
  42     if (AdviceSpec.has_value()) {
  43       JOS.attributeBegin("advice");
  44       AdviceSpec->toJSON(JOS);
  45       JOS.attributeEnd();
  46     }
  47   });
  48   *OS << "\n";
  49 }
  50
  51 void Logger::switchContext(StringRef Name) {
  52   CurrentContext = Name.str();
  53   json::OStream JOS(*OS);
  54   JOS.object([&]() { JOS.attribute("context", Name); });
  55   *OS << "\n";
  56 }
  57
  58 void Logger::startObservation() {
  59   auto I = ObservationIDs.insert({CurrentContext, 0});
  60   size_t NewObservationID = I.second ? 0 : ++I.first->second;
  61   json::OStream JOS(*OS);
  62   JOS.object([&]() {
  63     JOS.attribute("observation", static_cast<int64_t>(NewObservationID));
  64   });
  65   *OS << "\n";
  66 }
  67
  68 void Logger::endObservation() { *OS << "\n"; }
  69
  70 void Logger::logRewardImpl(const char *RawData) {
  71   assert(IncludeReward);
  72   json::OStream JOS(*OS);
  73   JOS.object([&]() {
  74     JOS.attribute("outcome", static_cast<int64_t>(
  75                                  ObservationIDs.find(CurrentContext)->second));
  76   });
  77   *OS << "\n";
  78   writeTensor(RewardSpec, RawData);
  79   *OS << "\n";
  80 }
  81
  82 Logger::Logger(std::unique_ptr<raw_ostream> OS,
  83                const std::vector<TensorSpec> &FeatureSpecs,
  84                const TensorSpec &RewardSpec, bool IncludeReward,
  85                std::optional<TensorSpec> AdviceSpec)
  86     : OS(std::move(OS)), FeatureSpecs(FeatureSpecs), RewardSpec(RewardSpec),
  87       IncludeReward(IncludeReward) {
  88   writeHeader(AdviceSpec);
  89 }