Internal change

PiperOrigin-RevId: 374448559

CHANGELOG.md

@@ -1,5 +1,11 @@
 # Changelog
 
+## 0.1.2 - 2021-05-18
+
+### Features
+
+-   Inference engines: QuickScorer Extended and Pred
+
 ## 0.1.1 - 2021-05-17
 
 ### Features

README.md

@@ -95,8 +95,8 @@ Download one of the build, and then run `examples/beginner.{sh,bat}`.
 
 Target  | Version | Link
 ------- | ------- | ----
-Linux   | 0.1.1   | [CLI](https://github.com/google/yggdrasil-decision-forests/releases/download/0.1.1/cli_linux.zip)
-Windows | 0.1.1   | [CLI](https://github.com/google/yggdrasil-decision-forests/releases/download/0.1.1/cli_windows.zip)
+Linux   | 0.1.0   | [CLI](https://github.com/google/yggdrasil-decision-forests/releases/download/0.1.0/cli_linux.zip)
+Windows | 0.1.0   | [CLI](https://github.com/google/yggdrasil-decision-forests/releases/download/0.1.0/cli_windows.zip)
 
 ## Installation from Source
 

yggdrasil_decision_forests/cli/benchmark_inference.cc

@@ -45,8 +45,9 @@
 //   batch_size : 100  num_runs : 20
 //   time/example(µs)  time/batch(µs)  method
 //   ----------------------------------------
-//   interface] 9.179           917.9  GradientBoostedTreesGeneric [virtual
-//   interface] 21.547          2154.8  Generic slow engine
+//   0.79025         79.025  GradientBoostedTreesQuickScorerExtended
+//   9.179           917.9   GradientBoostedTreesGeneric
+//   21.547          2154.8  Generic slow engine
 //   ----------------------------------------
 //
 #include "absl/flags/flag.h"

yggdrasil_decision_forests/learner/gradient_boosted_trees/gradient_boosted_trees_test.cc

@@ -721,6 +721,28 @@ TEST_F(GradientBoostedTreesOnAdult, RandomCategorical) {
   EXPECT_TRUE(gbt_model->IsMissingValueConditionResultFollowGlobalImputation());
 }
 
+// Train and test a model on the adult dataset with too much nodes for the
+// QuickScorer serving algorithm.
+TEST_F(GradientBoostedTreesOnAdult, BaseNoQuickScorer) {
+  auto* gbt_config = train_config_.MutableExtension(
+      gradient_boosted_trees::proto::gradient_boosted_trees_config);
+  gbt_config->set_num_trees(100);
+  gbt_config->mutable_decision_tree()->set_max_depth(10);
+  gbt_config->set_shrinkage(0.1f);
+  gbt_config->set_subsample(0.9f);
+  TrainAndEvaluateModel();
+
+  // Note: Accuracy is similar as RF (see :random_forest_test). However logloss
+  // is significantly better (which is expected as, unlike RF,  GBT is
+  // calibrated).
+  EXPECT_NEAR(metric::Accuracy(evaluation_), 0.8549, 0.015);
+  EXPECT_NEAR(metric::LogLoss(evaluation_), 0.320, 0.04);
+
+  auto* gbt_model =
+      dynamic_cast<const GradientBoostedTreesModel*>(model_.get());
+  EXPECT_TRUE(gbt_model->IsMissingValueConditionResultFollowGlobalImputation());
+}
+
 // Train and test a model on the adult dataset.
 TEST_F(GradientBoostedTreesOnAdult, BaseConcurrentDeprecated) {
   auto* gbt_config = train_config_.MutableExtension(

yggdrasil_decision_forests/serving/decision_forest/BUILD

@@ -16,6 +16,7 @@ cc_library(
     ],
     deps = [
         ":decision_forest",
+        ":quick_scorer_extended",
         "//yggdrasil_decision_forests/model:abstract_model",
         "//yggdrasil_decision_forests/model/gradient_boosted_trees",
         "//yggdrasil_decision_forests/serving:example_set_model_wrapper",
@@ -49,6 +50,28 @@ cc_library(
     ],
 )
 
+cc_library(
+    name = "quick_scorer_extended",
+    srcs = [
+        "quick_scorer_extended.cc",
+    ],
+    hdrs = [
+        "quick_scorer_extended.h",
+    ],
+    deps = [
+        ":utils",
+        "@com_google_absl//absl/base:config",
+        "@com_google_absl//absl/status",
+        "//yggdrasil_decision_forests/model/decision_tree",
+        "//yggdrasil_decision_forests/model/gradient_boosted_trees",
+        "//yggdrasil_decision_forests/model/gradient_boosted_trees:gradient_boosted_trees_cc_proto",
+        "//yggdrasil_decision_forests/serving:example_set",
+        "//yggdrasil_decision_forests/utils:bitmap",
+        "//yggdrasil_decision_forests/utils:compatibility",
+        "//yggdrasil_decision_forests/utils:usage",
+    ],
+)
+
 cc_library(
     name = "utils",
     srcs = [
@@ -84,6 +107,7 @@ cc_test(
     shard_count = 10,
     deps = [
         ":decision_forest",
+        ":quick_scorer_extended",
         ":register_engines",
         "@com_google_googletest//:gtest_main",
         "@com_google_absl//absl/flags:flag",
@@ -108,3 +132,15 @@ cc_test(
         "//yggdrasil_decision_forests/utils:test_utils",
     ],
 )
+
+cc_test(
+    name = "quick_scorer_extended_test",
+    srcs = ["quick_scorer_extended_test.cc"],
+    deps = [
+        ":quick_scorer_extended",
+        "@com_google_googletest//:gtest_main",
+        "//yggdrasil_decision_forests/model/decision_tree",
+        "//yggdrasil_decision_forests/model/gradient_boosted_trees",
+        "//yggdrasil_decision_forests/utils:test",
+    ],
+)

yggdrasil_decision_forests/serving/decision_forest/decision_forest.h

@@ -214,6 +214,10 @@ struct FlatNodeModel {
   using NodeType = Node;
   using FeaturesDefinition = FeaturesDefinitionNumericalOrCategoricalFlat;
 
+  using ExampleSet =
+      ExampleSetNumericalOrCategoricalFlat<FlatNodeModel<Node, Value>,
+                                           ExampleFormat::FORMAT_EXAMPLE_MAJOR>;
+
   const FeaturesDefinition& features() const { return internal_features; }
 
   FeaturesDefinition* mutable_features() { return &internal_features; }
@@ -555,6 +559,14 @@ void Predict(const GradientBoostedTreesRankingNumericalAndCategorical& model,
              const std::vector<NumericalOrCategoricalValue>& examples,
              int num_examples, std::vector<float>* predictions);
 
+template <typename Model>
+void PredictWithExampleSet(const Model& model,
+                           const typename Model::ExampleSet& examples,
+                           int num_examples, std::vector<float>* predictions) {
+  Predict(model, examples.InternalCategoricalAndNumericalValues(), num_examples,
+          predictions);
+}
+
 // Note: Requires for the number of trees to be a multiple of 8.
 void PredictOptimizedV1(
     const RandomForestBinaryClassificationNumericalFeatures& model,

yggdrasil_decision_forests/serving/decision_forest/decision_forest_test.cc

@@ -38,6 +38,7 @@
 #include "yggdrasil_decision_forests/model/gradient_boosted_trees/gradient_boosted_trees.pb.h"
 #include "yggdrasil_decision_forests/model/model_library.h"
 #include "yggdrasil_decision_forests/model/prediction.pb.h"
+#include "yggdrasil_decision_forests/serving/decision_forest/quick_scorer_extended.h"
 #include "yggdrasil_decision_forests/utils/csv.h"
 #include "yggdrasil_decision_forests/utils/distribution.pb.h"
 #include "yggdrasil_decision_forests/utils/filesystem.h"