[Dolphin] Remove the distinction between conditional and zero-state.

Previously, we had two copies of each Record, Train, and Rank method for
the ranker and each predictor: one that took a query and one that didn't.
The idea was that predictors (and therefore the ranker) was set up to
either work in a zero-state or condition-based environment, and clients
should only call the appropriate methods.

This has limitations, in particular, zero-state predictors can't be used
in an ensemble model along with condition-based ones. This CL removes
the distinction between these methods.

Specific changes are as follows:

1. Predictors now only have Train(target, condition) and
   Rank(condition) methods. The non-condition versions have been
   deleted.

2. The Ranker's zero-state Train and Rank methods are now just
   shortcuts for having an empty-string condition.

3. All predictors labelled ZeroStateX have been renamed to just X. It
   seems most of our predictors won't use the condition and, in order
   to incorporate a condition, will be wrapped in some kind of
   ConditionalPredictor. So it makes sense for the default naming to not
   specify zero-state-ness, as the current names are very verbose.

Bug: 921444
Change-Id: I5273715501319cda951b717d755e1abb559d4dd6
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/1670668
Commit-Queue: Tony Yeoman <tby@chromium.org>
Reviewed-by: Charles . <charleszhao@chromium.org>
Cr-Commit-Position: refs/heads/master@{#671894}

chrome/browser/ui/app_list/search/search_result_ranker/app_launch_predictor_test_util.h

@@ -229,10 +229,9 @@ DEFINE_EQUIVTO_PROTO_LITE_3(FrecencyStoreProto_ValueData,
                             last_score,
                             last_num_updates);
 
-DEFINE_EQUIVTO_PROTO_LITE_1(ZeroStateHourBinPredictorProto,
-                            binned_frequency_table);
+DEFINE_EQUIVTO_PROTO_LITE_1(HourBinPredictorProto, binned_frequency_table);
 
-DEFINE_EQUIVTO_PROTO_LITE_2(ZeroStateHourBinPredictorProto_FrequencyTable,
+DEFINE_EQUIVTO_PROTO_LITE_2(HourBinPredictorProto_FrequencyTable,
                             total_counts,
                             frequency);
 
@@ -245,7 +244,7 @@ DEFINE_EQUIVTO_PROTO_LITE_2(HourAppLaunchPredictorProto_FrequencyTable,
 
 DEFINE_EQUIVTO_PROTO_LITE_2(RecurrencePredictorProto,
                             fake_predictor,
-                            zero_state_frecency_predictor);
+                            frecency_predictor);
 
 DEFINE_EQUIVTO_PROTO_LITE_2(RecurrenceRankerProto, config_hash, predictor);
 
@@ -257,11 +256,9 @@ DEFINE_EQUIVTO_PROTO_LITE_2(SerializedMrfuAppLaunchPredictorProto_Score,
                             num_of_trains_at_last_update,
                             last_score);
 
-DEFINE_EQUIVTO_PROTO_LITE_2(ZeroStateFrecencyPredictorProto,
-                            targets,
-                            num_updates);
+DEFINE_EQUIVTO_PROTO_LITE_2(FrecencyPredictorProto, targets, num_updates);
 
-DEFINE_EQUIVTO_PROTO_LITE_2(ZeroStateFrecencyPredictorProto_TargetData,
+DEFINE_EQUIVTO_PROTO_LITE_2(FrecencyPredictorProto_TargetData,
                             last_score,
                             last_num_updates);
 

chrome/browser/ui/app_list/search/search_result_ranker/histogram_util.h

@@ -29,9 +29,9 @@ enum class SerializationError {
   kTargetsMissingError = 5,
   kConditionsMissingError = 6,
   kFakePredictorLoadingError = 7,
-  kZeroStateFrecencyPredictorLoadingError = 8,
-  kZeroStateHourBinnedPredictorLoadingError = 9,
-  kMaxValue = kZeroStateHourBinnedPredictorLoadingError,
+  kFrecencyPredictorLoadingError = 8,
+  kHourBinnedPredictorLoadingError = 9,
+  kMaxValue = kHourBinnedPredictorLoadingError,
 };
 
 // Represents errors where a RecurrenceRanker is used in a way not supported by

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_predictor.cc

@@ -15,29 +15,6 @@ constexpr int kHoursADay = 24;
 
 }  // namespace
 
-void RecurrencePredictor::Train(unsigned int target) {
-  LogUsageError(UsageError::kInvalidTrainCall);
-  NOTREACHED();
-}
-
-void RecurrencePredictor::Train(unsigned int target, unsigned int condition) {
-  LogUsageError(UsageError::kInvalidTrainCall);
-  NOTREACHED();
-}
-
-base::flat_map<unsigned int, float> RecurrencePredictor::Rank() {
-  LogUsageError(UsageError::kInvalidRankCall);
-  NOTREACHED();
-  return {};
-}
-
-base::flat_map<unsigned int, float> RecurrencePredictor::Rank(
-    unsigned int condition) {
-  LogUsageError(UsageError::kInvalidRankCall);
-  NOTREACHED();
-  return {};
-}
-
 FakePredictor::FakePredictor(const FakePredictorConfig& config) {
   // The fake predictor should only be used for testing, not in production.
   // Record an error so we know if it is being used.
@@ -51,11 +28,12 @@ const char* FakePredictor::GetPredictorName() const {
   return kPredictorName;
 }
 
-void FakePredictor::Train(unsigned int target) {
+void FakePredictor::Train(unsigned int target, unsigned int condition) {
   counts_[target] += 1.0f;
 }
 
-base::flat_map<unsigned int, float> FakePredictor::Rank() {
+base::flat_map<unsigned int, float> FakePredictor::Rank(
+    unsigned int condition) {
   return counts_;
 }
 
@@ -70,15 +48,23 @@ void FakePredictor::FromProto(const RecurrencePredictorProto& proto) {
     LogSerializationError(SerializationError::kFakePredictorLoadingError);
     return;
   }
-  auto predictor = proto.fake_predictor();
 
-  for (const auto& pair : predictor.counts())
+  for (const auto& pair : proto.fake_predictor().counts())
     counts_[pair.first] = pair.second;
 }
 
 DefaultPredictor::DefaultPredictor(const DefaultPredictorConfig& config) {}
 DefaultPredictor::~DefaultPredictor() {}
 
+void DefaultPredictor::Train(unsigned int target, unsigned int condition) {}
+
+base::flat_map<unsigned int, float> DefaultPredictor::Rank(
+    unsigned int condition) {
+  LogUsageError(UsageError::kInvalidRankCall);
+  NOTREACHED();
+  return {};
+}
+
 const char DefaultPredictor::kPredictorName[] = "DefaultPredictor";
 const char* DefaultPredictor::GetPredictorName() const {
   return kPredictorName;
@@ -88,25 +74,24 @@ void DefaultPredictor::ToProto(RecurrencePredictorProto* proto) const {}
 
 void DefaultPredictor::FromProto(const RecurrencePredictorProto& proto) {}
 
-ZeroStateFrecencyPredictor::ZeroStateFrecencyPredictor(
-    const ZeroStateFrecencyPredictorConfig& config)
+FrecencyPredictor::FrecencyPredictor(const FrecencyPredictorConfig& config)
     : decay_coeff_(config.decay_coeff()) {}
-ZeroStateFrecencyPredictor::~ZeroStateFrecencyPredictor() = default;
+FrecencyPredictor::~FrecencyPredictor() = default;
 
-const char ZeroStateFrecencyPredictor::kPredictorName[] =
-    "ZeroStateFrecencyPredictor";
-const char* ZeroStateFrecencyPredictor::GetPredictorName() const {
+const char FrecencyPredictor::kPredictorName[] = "FrecencyPredictor";
+const char* FrecencyPredictor::GetPredictorName() const {
   return kPredictorName;
 }
 
-void ZeroStateFrecencyPredictor::Train(unsigned int target) {
+void FrecencyPredictor::Train(unsigned int target, unsigned int condition) {
   ++num_updates_;
   TargetData& data = targets_[target];
   DecayScore(&data);
   data.last_score += 1.0f - decay_coeff_;
 }
 
-base::flat_map<unsigned int, float> ZeroStateFrecencyPredictor::Rank() {
+base::flat_map<unsigned int, float> FrecencyPredictor::Rank(
+    unsigned int condition) {
   base::flat_map<unsigned int, float> result;
   for (auto& pair : targets_) {
     DecayScore(&pair.second);
@@ -115,9 +100,8 @@ base::flat_map<unsigned int, float> ZeroStateFrecencyPredictor::Rank() {
   return result;
 }
 
-void ZeroStateFrecencyPredictor::ToProto(
-    RecurrencePredictorProto* proto) const {
-  auto* predictor = proto->mutable_zero_state_frecency_predictor();
+void FrecencyPredictor::ToProto(RecurrencePredictorProto* proto) const {
+  auto* predictor = proto->mutable_frecency_predictor();
 
   predictor->set_num_updates(num_updates_);
 
@@ -129,14 +113,12 @@ void ZeroStateFrecencyPredictor::ToProto(
   }
 }
 
-void ZeroStateFrecencyPredictor::FromProto(
-    const RecurrencePredictorProto& proto) {
-  if (!proto.has_zero_state_frecency_predictor()) {
-    LogSerializationError(
-        SerializationError::kZeroStateFrecencyPredictorLoadingError);
+void FrecencyPredictor::FromProto(const RecurrencePredictorProto& proto) {
+  if (!proto.has_frecency_predictor()) {
+    LogSerializationError(SerializationError::kFrecencyPredictorLoadingError);
     return;
   }
-  const auto& predictor = proto.zero_state_frecency_predictor();
+  const auto& predictor = proto.frecency_predictor();
 
   num_updates_ = predictor.num_updates();
 
@@ -148,7 +130,7 @@ void ZeroStateFrecencyPredictor::FromProto(
   targets_.swap(targets);
 }
 
-void ZeroStateFrecencyPredictor::DecayScore(TargetData* data) {
+void FrecencyPredictor::DecayScore(TargetData* data) {
   int time_since_update = num_updates_ - data->last_num_updates;
 
   if (time_since_update > 0) {
@@ -157,25 +139,22 @@ void ZeroStateFrecencyPredictor::DecayScore(TargetData* data) {
   }
 }
 
-ZeroStateHourBinPredictor::ZeroStateHourBinPredictor(
-    const ZeroStateHourBinPredictorConfig& config)
+HourBinPredictor::HourBinPredictor(const HourBinPredictorConfig& config)
     : config_(config) {
   if (!proto_.has_last_decay_timestamp())
     SetLastDecayTimestamp(
         base::Time::Now().ToDeltaSinceWindowsEpoch().InDays());
 }
 
-ZeroStateHourBinPredictor::~ZeroStateHourBinPredictor() = default;
+HourBinPredictor::~HourBinPredictor() = default;
 
-const char ZeroStateHourBinPredictor::kPredictorName[] =
-    "ZeroStateHourBinPredictor";
+const char HourBinPredictor::kPredictorName[] = "HourBinPredictor";
 
-const char* ZeroStateHourBinPredictor::GetPredictorName() const {
+const char* HourBinPredictor::GetPredictorName() const {
   return kPredictorName;
 }
 
-int ZeroStateHourBinPredictor::GetBinFromHourDifference(
-    int hour_difference) const {
+int HourBinPredictor::GetBinFromHourDifference(int hour_difference) const {
   base::Time shifted_time =
       base::Time::Now() + base::TimeDelta::FromHours(hour_difference);
   base::Time::Exploded exploded_time;
@@ -193,18 +172,19 @@ int ZeroStateHourBinPredictor::GetBinFromHourDifference(
   }
 }
 
-int ZeroStateHourBinPredictor::GetBin() const {
+int HourBinPredictor::GetBin() const {
   return GetBinFromHourDifference(0);
 }
 
-void ZeroStateHourBinPredictor::Train(unsigned int target) {
+void HourBinPredictor::Train(unsigned int target, unsigned int condition) {
   int hour = GetBin();
   auto& frequency_table = (*proto_.mutable_binned_frequency_table())[hour];
   frequency_table.set_total_counts(frequency_table.total_counts() + 1);
   (*frequency_table.mutable_frequency())[target] += 1;
 }
 
-base::flat_map<unsigned int, float> ZeroStateHourBinPredictor::Rank() {
+base::flat_map<unsigned int, float> HourBinPredictor::Rank(
+    unsigned int condition) {
   base::flat_map<unsigned int, float> ranks;
   const auto& frequency_table_map = proto_.binned_frequency_table();
   for (const auto& hour_and_weight : config_.bin_weights_map()) {
@@ -229,27 +209,26 @@ base::flat_map<unsigned int, float> ZeroStateHourBinPredictor::Rank() {
   return ranks;
 }
 
-void ZeroStateHourBinPredictor::ToProto(RecurrencePredictorProto* proto) const {
-  *proto->mutable_zero_state_hour_bin_predictor() = proto_;
+void HourBinPredictor::ToProto(RecurrencePredictorProto* proto) const {
+  *proto->mutable_hour_bin_predictor() = proto_;
 }
 
-void ZeroStateHourBinPredictor::FromProto(
-    const RecurrencePredictorProto& proto) {
-  if (!proto.has_zero_state_hour_bin_predictor())
+void HourBinPredictor::FromProto(const RecurrencePredictorProto& proto) {
+  if (!proto.has_hour_bin_predictor())
     return;
 
-  proto_ = proto.zero_state_hour_bin_predictor();
+  proto_ = proto.hour_bin_predictor();
   if (ShouldDecay())
     DecayAll();
 }
 
-bool ZeroStateHourBinPredictor::ShouldDecay() {
+bool HourBinPredictor::ShouldDecay() {
   const int today = base::Time::Now().ToDeltaSinceWindowsEpoch().InDays();
   // Check if we should decay the frequency
   return today - proto_.last_decay_timestamp() > 7;
 }
 
-void ZeroStateHourBinPredictor::DecayAll() {
+void HourBinPredictor::DecayAll() {
   SetLastDecayTimestamp(base::Time::Now().ToDeltaSinceWindowsEpoch().InDays());
   auto& frequency_table_map = *proto_.mutable_binned_frequency_table();
   for (auto it_table = frequency_table_map.begin();

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_predictor.h

@@ -19,10 +19,10 @@ namespace app_list {
 using FakePredictorConfig = RecurrenceRankerConfigProto::FakePredictorConfig;
 using DefaultPredictorConfig =
     RecurrenceRankerConfigProto::DefaultPredictorConfig;
-using ZeroStateFrecencyPredictorConfig =
-    RecurrenceRankerConfigProto::ZeroStateFrecencyPredictorConfig;
-using ZeroStateHourBinPredictorConfig =
-    RecurrenceRankerConfigProto::ZeroStateHourBinPredictorConfig;
+using FrecencyPredictorConfig =
+    RecurrenceRankerConfigProto::FrecencyPredictorConfig;
+using HourBinPredictorConfig =
+    RecurrenceRankerConfigProto::HourBinPredictorConfig;
 
 // |RecurrencePredictor| is the interface for all predictors used by
 // |RecurrenceRanker| to drive rankings. If a predictor has some form of
@@ -34,16 +34,12 @@ class RecurrencePredictor {
 
   // Train the predictor on an occurrence of |target| coinciding with
   // |condition|. The predictor will collect its own contextual information, eg.
-  // time of day, as part of training. Zero-state predictors should use the
-  // one-argument version.
-  virtual void Train(unsigned int target);
-  virtual void Train(unsigned int target, unsigned int condition);
+  // time of day, as part of training.
+  virtual void Train(unsigned int target, unsigned int condition) = 0;
 
   // Return a map of all known targets to their scores for the given condition
-  // under this predictor. Scores must be within the range [0,1]. Zero-state
-  // predictors should use the zero-argument version.
-  virtual base::flat_map<unsigned int, float> Rank();
-  virtual base::flat_map<unsigned int, float> Rank(unsigned int condition);
+  // under this predictor. Scores must be within the range [0,1].
+  virtual base::flat_map<unsigned int, float> Rank(unsigned int condition) = 0;
 
   virtual void ToProto(RecurrencePredictorProto* proto) const = 0;
   virtual void FromProto(const RecurrencePredictorProto& proto) = 0;
@@ -62,8 +58,8 @@ class FakePredictor : public RecurrencePredictor {
   ~FakePredictor() override;
 
   // RecurrencePredictor:
-  void Train(unsigned int target) override;
-  base::flat_map<unsigned int, float> Rank() override;
+  void Train(unsigned int target, unsigned int condition) override;
+  base::flat_map<unsigned int, float> Rank(unsigned int condition) override;
   void ToProto(RecurrencePredictorProto* proto) const override;
   void FromProto(const RecurrencePredictorProto& proto) override;
   const char* GetPredictorName() const override;
@@ -85,6 +81,8 @@ class DefaultPredictor : public RecurrencePredictor {
   ~DefaultPredictor() override;
 
   // RecurrencePredictor:
+  void Train(unsigned int target, unsigned int condition) override;
+  base::flat_map<unsigned int, float> Rank(unsigned int condition) override;
   void ToProto(RecurrencePredictorProto* proto) const override;
   void FromProto(const RecurrencePredictorProto& proto) override;
   const char* GetPredictorName() const override;
@@ -95,16 +93,15 @@ class DefaultPredictor : public RecurrencePredictor {
   DISALLOW_COPY_AND_ASSIGN(DefaultPredictor);
 };
 
-// ZeroStateFrecencyPredictor ranks targets according to their frecency, and
+// FrecencyPredictor ranks targets according to their frecency, and
 // can only be used for zero-state predictions. This predictor allows for
 // frecency-based rankings with different configuration to that of the ranker's
 // FrecencyStore. If frecency-based rankings with the same configuration as the
 // store are needed, the DefaultPredictor should be used instead.
-class ZeroStateFrecencyPredictor : public RecurrencePredictor {
+class FrecencyPredictor : public RecurrencePredictor {
  public:
-  explicit ZeroStateFrecencyPredictor(
-      const ZeroStateFrecencyPredictorConfig& config);
-  ~ZeroStateFrecencyPredictor() override;
+  explicit FrecencyPredictor(const FrecencyPredictorConfig& config);
+  ~FrecencyPredictor() override;
 
   // Records all information about a target: its id and score, along with the
   // number of updates that had occurred when the score was last calculated.
@@ -115,8 +112,8 @@ class ZeroStateFrecencyPredictor : public RecurrencePredictor {
   };
 
   // RecurrencePredictor:
-  void Train(unsigned int target) override;
-  base::flat_map<unsigned int, float> Rank() override;
+  void Train(unsigned int target, unsigned int condition) override;
+  base::flat_map<unsigned int, float> Rank(unsigned int condition) override;
   void ToProto(RecurrencePredictorProto* proto) const override;
   void FromProto(const RecurrencePredictorProto& proto) override;
   const char* GetPredictorName() const override;
@@ -139,23 +136,22 @@ class ZeroStateFrecencyPredictor : public RecurrencePredictor {
 
   // This stores all the data of the frecency predictor.
   // TODO(tby): benchmark which map is best in practice for our use.
-  base::flat_map<unsigned int, ZeroStateFrecencyPredictor::TargetData> targets_;
+  base::flat_map<unsigned int, FrecencyPredictor::TargetData> targets_;
 
-  DISALLOW_COPY_AND_ASSIGN(ZeroStateFrecencyPredictor);
+  DISALLOW_COPY_AND_ASSIGN(FrecencyPredictor);
 };
 
-// |ZeroStateHourBinPredictor| ranks targets according to their frequency during
+// |HourBinPredictor| ranks targets according to their frequency during
 // the current and neighbor hour bins. It can only be used for zero-state
 // predictions.
-class ZeroStateHourBinPredictor : public RecurrencePredictor {
+class HourBinPredictor : public RecurrencePredictor {
  public:
-  explicit ZeroStateHourBinPredictor(
-      const ZeroStateHourBinPredictorConfig& config);
-  ~ZeroStateHourBinPredictor() override;
+  explicit HourBinPredictor(const HourBinPredictorConfig& config);
+  ~HourBinPredictor() override;
 
   // RecurrencePredictor:
-  void Train(unsigned int target) override;
-  base::flat_map<unsigned int, float> Rank() override;
+  void Train(unsigned int target, unsigned int condition) override;
+  base::flat_map<unsigned int, float> Rank(unsigned int condition) override;
   void ToProto(RecurrencePredictorProto* proto) const override;
   void FromProto(const RecurrencePredictorProto& proto) override;
   const char* GetPredictorName() const override;
@@ -163,13 +159,11 @@ class ZeroStateHourBinPredictor : public RecurrencePredictor {
   static const char kPredictorName[];
 
  private:
-  FRIEND_TEST_ALL_PREFIXES(ZeroStateHourBinPredictorTest, GetTheRightBin);
-  FRIEND_TEST_ALL_PREFIXES(ZeroStateHourBinPredictorTest,
-                           TrainAndRankSingleBin);
-  FRIEND_TEST_ALL_PREFIXES(ZeroStateHourBinPredictorTest,
-                           TrainAndRankMultipleBin);
-  FRIEND_TEST_ALL_PREFIXES(ZeroStateHourBinPredictorTest, ToProto);
-  FRIEND_TEST_ALL_PREFIXES(ZeroStateHourBinPredictorTest, FromProtoDecays);
+  FRIEND_TEST_ALL_PREFIXES(HourBinPredictorTest, GetTheRightBin);
+  FRIEND_TEST_ALL_PREFIXES(HourBinPredictorTest, TrainAndRankSingleBin);
+  FRIEND_TEST_ALL_PREFIXES(HourBinPredictorTest, TrainAndRankMultipleBin);
+  FRIEND_TEST_ALL_PREFIXES(HourBinPredictorTest, ToProto);
+  FRIEND_TEST_ALL_PREFIXES(HourBinPredictorTest, FromProtoDecays);
   // Return the bin index that is |hour_difference| away from the current bin
   // index.
   int GetBinFromHourDifference(int hour_difference) const;
@@ -182,9 +176,9 @@ class ZeroStateHourBinPredictor : public RecurrencePredictor {
   void SetLastDecayTimestamp(float value) {
     proto_.set_last_decay_timestamp(value);
   }
-  ZeroStateHourBinPredictorProto proto_;
-  ZeroStateHourBinPredictorConfig config_;
-  DISALLOW_COPY_AND_ASSIGN(ZeroStateHourBinPredictor);
+  HourBinPredictorProto proto_;
+  HourBinPredictorConfig config_;
+  DISALLOW_COPY_AND_ASSIGN(HourBinPredictor);
 };
 
 }  // namespace app_list

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_predictor.proto

@@ -14,8 +14,7 @@ message FakePredictorProto {
   map<uint32, float> counts = 1;
 }
 
-// Zero-state frecency predictor.
-message ZeroStateFrecencyPredictorProto {
+message FrecencyPredictorProto {
   // Field 1 (targets) has been deleted.
   reserved 1;
 
@@ -34,8 +33,7 @@ message ZeroStateFrecencyPredictorProto {
   required uint32 num_updates = 5;
 }
 
-// Zero-state hour bin predictor
-message ZeroStateHourBinPredictorProto {
+message HourBinPredictorProto {
   // Records all data related to a single hour bin.
   message FrequencyTable {
     // Total number of training counts in a bin.
@@ -53,7 +51,7 @@ message ZeroStateHourBinPredictorProto {
 message RecurrencePredictorProto {
   oneof predictor {
     FakePredictorProto fake_predictor = 1;
-    ZeroStateFrecencyPredictorProto zero_state_frecency_predictor = 2;
-    ZeroStateHourBinPredictorProto zero_state_hour_bin_predictor = 3;
+    FrecencyPredictorProto frecency_predictor = 2;
+    HourBinPredictorProto hour_bin_predictor = 3;
   }
 }

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_ranker.cc

@@ -81,12 +81,10 @@ std::unique_ptr<RecurrencePredictor> MakePredictor(
     return std::make_unique<FakePredictor>(config.fake_predictor());
   if (config.has_default_predictor())
     return std::make_unique<DefaultPredictor>(config.default_predictor());
-  if (config.has_zero_state_frecency_predictor())
-    return std::make_unique<ZeroStateFrecencyPredictor>(
-        config.zero_state_frecency_predictor());
-  if (config.has_zero_state_hour_bin_predictor())
-    return std::make_unique<ZeroStateHourBinPredictor>(
-        config.zero_state_hour_bin_predictor());
+  if (config.has_frecency_predictor())
+    return std::make_unique<FrecencyPredictor>(config.frecency_predictor());
+  if (config.has_hour_bin_predictor())
+    return std::make_unique<HourBinPredictor>(config.hour_bin_predictor());
 
   LogConfigurationError(ConfigurationError::kInvalidPredictor);
   NOTREACHED();
@@ -215,34 +213,12 @@ void RecurrenceRanker::OnLoadProtoFromDiskComplete(
     LogSerializationError(SerializationError::kConditionsMissingError);
 }
 
-void RecurrenceRanker::Record(const std::string& target) {
-  if (!load_from_disk_completed_)
-    return;
-
-  if (predictor_->GetPredictorName() == DefaultPredictor::kPredictorName) {
-    targets_->Update(target);
-  } else {
-    predictor_->Train(targets_->Update(target));
-  }
-
-  MaybeSave();
-}
-
 void RecurrenceRanker::Record(const std::string& target,
                               const std::string& condition) {
   if (!load_from_disk_completed_)
     return;
 
-  if (predictor_->GetPredictorName() == DefaultPredictor::kPredictorName) {
-    // TODO(921444): The default predictor does not support queries, so we fail
-    // here. Once we have a suitable query-based default predictor implemented,
-    // change this.
-    LogUsageError(UsageError::kInvalidTrainCall);
-    NOTREACHED();
-  } else {
-    predictor_->Train(targets_->Update(target), conditions_->Update(condition));
-  }
-
+  predictor_->Train(targets_->Update(target), conditions_->Update(condition));
   MaybeSave();
 }
 
@@ -282,43 +258,23 @@ void RecurrenceRanker::RemoveCondition(const std::string& condition) {
   MaybeSave();
 }
 
-base::flat_map<std::string, float> RecurrenceRanker::Rank() {
-  if (!load_from_disk_completed_)
-    return {};
-
-  if (predictor_->GetPredictorName() == DefaultPredictor::kPredictorName)
-    return GetScoresFromFrecencyStore(targets_->GetAll());
-  return ZipTargetsWithScores(targets_->GetAll(), predictor_->Rank());
-}
-
 base::flat_map<std::string, float> RecurrenceRanker::Rank(
     const std::string& condition) {
   if (!load_from_disk_completed_)
     return {};
+  // Special case the default predictor, and return the scores from the target
+  // frecency store.
+  if (predictor_->GetPredictorName() == DefaultPredictor::kPredictorName)
+    return GetScoresFromFrecencyStore(targets_->GetAll());
 
   base::Optional<unsigned int> condition_id = conditions_->GetId(condition);
   if (condition_id == base::nullopt)
     return {};
 
-  if (predictor_->GetPredictorName() == DefaultPredictor::kPredictorName) {
-    // TODO(921444): The default predictor does not support queries, so we fail
-    // here. Once we have a suitable query-based default predictor implemented,
-    // change this.
-    LogUsageError(UsageError::kInvalidRankCall);
-    NOTREACHED();
-    return {};
-  }
   return ZipTargetsWithScores(targets_->GetAll(),
                               predictor_->Rank(condition_id.value()));
 }
 
-std::vector<std::pair<std::string, float>> RecurrenceRanker::RankTopN(int n) {
-  if (!load_from_disk_completed_)
-    return {};
-
-  return SortAndTruncateRanks(n, Rank());
-}
-
 std::vector<std::pair<std::string, float>> RecurrenceRanker::RankTopN(
     int n,
     const std::string& condition) {

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_ranker.h

@@ -33,12 +33,11 @@ class RecurrenceRanker {
                    bool is_ephemeral_user);
   ~RecurrenceRanker();
 
-  // Record the use of a given target, and train the predictor on it. The
-  // one-argument version should be used for zero-state predictions, and the
-  // two-argument version for condition-based predictions. This may save to
-  // disk, but is not guaranteed to.
-  void Record(const std::string& target);
-  void Record(const std::string& target, const std::string& condition);
+  // Record the use of a given target, and train the predictor on it. This may
+  // save to disk, but is not guaranteed to. The user-supplied |condition| can
+  // be ignored if it isn't needed.
+  void Record(const std::string& target,
+              const std::string& condition = std::string());
 
   // Rename a target, while keeping learned information on it. This may save to
   // disk, but is not guaranteed to.
@@ -56,22 +55,19 @@ class RecurrenceRanker {
   // Returns a map of target to score.
   //  - Higher scores are better.
   //  - Score are guaranteed to be in the range [0,1].
-  // The zero-argument version should be used for zero-state predictions, and
-  // the one-argument version for condition-based predictions.
-  base::flat_map<std::string, float> Rank();
-  base::flat_map<std::string, float> Rank(const std::string& condition);
+  // The user-supplied |condition| can be ignored if it isn't needed.
+  base::flat_map<std::string, float> Rank(
+      const std::string& condition = std::string());
 
   // Returns a sorted vector of <target, score> pairs.
   //  - Higher scores are better.
   //  - Score are guaranteed to be in the range [0,1].
   //  - Pairs are sorted in descending order of score.
   //  - At most n results will be returned.
-  // The zero-argument version should be used for zero-state predictions, and
-  // the one-argument version for condition-based predictions.
-  std::vector<std::pair<std::string, float>> RankTopN(int n);
+  // The user-supplied |condition| can be ignored if it isn't needed.
   std::vector<std::pair<std::string, float>> RankTopN(
       int n,
-      const std::string& condition);
+      const std::string& condition = std::string());
 
   // TODO(921444): Create a system for cleaning up internal predictor state that
   // is stored indepent of the target/condition frecency stores.

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_ranker_config.proto

@@ -28,14 +28,14 @@ message RecurrenceRankerConfigProto {
   message DefaultPredictorConfig {}
 
   // Config for a frecency predictor.
-  message ZeroStateFrecencyPredictorConfig {
+  message FrecencyPredictorConfig {
     // The frecency parameter used to control the frequency-recency tradeoff
     // that determines when targets are removed. Must be in [0.5, 1.0], with 0.5
     // meaning only-recency and 1.0 meaning only-frequency.
     required float decay_coeff = 1;
   }
 
-  message ZeroStateHourBinPredictorConfig {
+  message HourBinPredictorConfig {
     // The decay coeffficient number that control the decay rate. The decay is
     // once a week.
     required float weekly_decay_coeff = 1;
@@ -45,8 +45,8 @@ message RecurrenceRankerConfigProto {
   // The choice of which kind of predictor to use, and its configuration.
   oneof predictor_config {
     FakePredictorConfig fake_predictor = 10001;
-    ZeroStateFrecencyPredictorConfig zero_state_frecency_predictor = 10002;
+    FrecencyPredictorConfig frecency_predictor = 10002;
     DefaultPredictorConfig default_predictor = 10003;
-    ZeroStateHourBinPredictorConfig zero_state_hour_bin_predictor = 10004;
+    HourBinPredictorConfig hour_bin_predictor = 10004;
   }
 }

chrome/browser/ui/app_list/search/search_result_ranker/recurrence_ranker_unittest.cc

@@ -104,13 +104,19 @@ class RecurrenceRankerTest : public testing::Test {
     value_data.set_last_num_updates(4);
     (*target_values)["C"] = value_data;
 
-    // Make empty conditions frecency store.
+    // Make conditions frecency store.
     auto* conditions = proto.mutable_conditions();
-    conditions->set_value_limit(0u);
-    conditions->set_decay_coeff(0.0f);
+    conditions->set_value_limit(10u);
+    conditions->set_decay_coeff(0.5f);
     conditions->set_num_updates(0);
     conditions->set_next_id(0);
-    conditions->mutable_values();
+
+    auto* condition_values = conditions->mutable_values();
+
+    value_data.set_id(0u);
+    value_data.set_last_score(0.5f);
+    value_data.set_last_num_updates(1);
+    (*condition_values)[""] = value_data;
 
     // Make FakePredictor counts.
     auto* counts =
@@ -369,7 +375,7 @@ TEST_F(RecurrenceRankerTest, IntegrationWithDefaultPredictor) {
 TEST_F(RecurrenceRankerTest, IntegrationWithZeroStateFrecencyPredictor) {
   RecurrenceRankerConfigProto config;
   PartiallyPopulateConfig(&config);
-  auto* predictor = config.mutable_zero_state_frecency_predictor();
+  auto* predictor = config.mutable_frecency_predictor();
   predictor->set_decay_coeff(0.5f);
 
   RecurrenceRanker ranker(ranker_filepath_, config, false);