Move generic tree representation proto to tensorflow/contrib.

PiperOrigin-RevId: 158838465

5 files changed, 260 insertions, 0 deletions

diff --git a/tensorflow/contrib/decision_trees/BUILD b/tensorflow/contrib/decision_trees/BUILD
new file mode 100644
index 0000000000..4045b92f10
--- /dev/null
+++ b/tensorflow/contrib/decision_trees/BUILD
@@ -0,0 +1,19 @@
+# Files common to decision-tree algorithms.
+package(default_visibility = [
+    "//visibility:public",
+])
+
+licenses(["notice"])  # Apache 2.0
+
+exports_files(["LICENSE"])
+
+filegroup(
+    name = "all_files",
+    srcs = glob(
+        ["**/*"],
+        exclude = [
+            "**/OWNERS",
+        ],
+    ),
+    visibility = ["//tensorflow:__subpackages__"],
+)
diff --git a/tensorflow/contrib/decision_trees/proto/BUILD b/tensorflow/contrib/decision_trees/proto/BUILD
new file mode 100644
index 0000000000..86174c5865
--- /dev/null
+++ b/tensorflow/contrib/decision_trees/proto/BUILD
@@ -0,0 +1,26 @@
+package(default_visibility = ["//visibility:public"])
+
+licenses(["notice"])  # Apache 2.0
+
+exports_files([
+    "LICENSE",
+    "generic_tree_model_proto.swig",
+])
+
+load("//tensorflow/core:platform/default/build_config.bzl", "tf_proto_library")
+
+tf_proto_library(
+    name = "generic_tree_model",
+    srcs = ["generic_tree_model.proto"],
+    cc_api_version = 2,
+    go_api_version = 2,
+    java_api_version = 2,
+)
+
+tf_proto_library(
+    name = "generic_tree_model_extensions",
+    srcs = ["generic_tree_model_extensions.proto"],
+    cc_api_version = 2,
+    go_api_version = 2,
+    protodeps = [":generic_tree_model"],
+)
diff --git a/tensorflow/contrib/decision_trees/proto/generic_tree_model.proto b/tensorflow/contrib/decision_trees/proto/generic_tree_model.proto
new file mode 100644
index 0000000000..dd80b37f52
--- /dev/null
+++ b/tensorflow/contrib/decision_trees/proto/generic_tree_model.proto
@@ -0,0 +1,183 @@
+// Generic representation of tree-based models.
+
+// This proto establishes a shared standard: "fully compatible" projects should
+// provide support for all reasonable models expressed through it. Therefore,
+// it should be kept as simple as possible, and should never contain
+// project-specific design choices.
+
+// Status: work in progress. This proto can change anytime without notice.
+
+syntax = "proto3";
+option cc_enable_arenas = true;
+
+package tensorflow.decision_trees;
+
+import "google/protobuf/any.proto";
+import "google/protobuf/wrappers.proto";
+
+// A generic handle for any type of model.
+message Model {
+  oneof model {
+    DecisionTree decision_tree = 1;
+    Ensemble ensemble = 2;
+    google.protobuf.Any custom_model = 3;
+  }
+  repeated google.protobuf.Any additional_data = 4;
+}
+
+message ModelAndFeatures {
+  message Feature {
+    // TODO(jonasz): Remove this field, as it's confusing. Ctx: cr/153569450.
+    FeatureId feature_id = 1 [deprecated = true];
+    repeated google.protobuf.Any additional_data = 2;
+  };
+  // Given a FeatureId feature_id, the feature's description is in
+  // features[feature_id.id.value].
+  map<string, Feature> features = 1;
+  Model model = 2;
+  repeated google.protobuf.Any additional_data = 3;
+}
+
+// An ordered sequence of models. This message can be used to express bagged or
+// boosted models, as well as custom ensembles.
+message Ensemble {
+  message Member {
+    Model submodel = 1;
+    google.protobuf.Int32Value submodel_id = 2;
+    repeated google.protobuf.Any additional_data = 3;
+  }
+  repeated Member members = 100; // A higher id for more readable printing.
+
+  // The presence of a certain combination_technique indicates how to combine
+  // the outputs of member models in order to compute the ensemble's output.
+  oneof combination_technique {
+    Summation summation_combination_technique = 1;
+    Averaging averaging_combination_technique = 2;
+    google.protobuf.Any custom_combination_technique = 3;
+  }
+  repeated google.protobuf.Any additional_data = 4;
+}
+
+// When present, the Ensemble's output is the sum of member models' outputs.
+message Summation {
+  repeated google.protobuf.Any additional_data = 1;
+};
+
+
+// When present, the Ensemble's output is the average of member models' outputs.
+message Averaging {
+  repeated google.protobuf.Any additional_data = 1;
+};
+
+
+message DecisionTree {
+  repeated TreeNode nodes = 1;
+  repeated google.protobuf.Any additional_data = 2;
+};
+
+
+message TreeNode {
+  // Following fields are provided for convenience and better readability.
+  // Filling them in is not required.
+  google.protobuf.Int32Value node_id = 1;
+  google.protobuf.Int32Value depth = 2;
+  google.protobuf.Int32Value subtree_size = 3;
+
+  oneof node_type {
+    BinaryNode binary_node = 4;
+    Leaf leaf = 5;
+    google.protobuf.Any custom_node_type = 6;
+  }
+
+  repeated google.protobuf.Any additional_data = 7;
+}
+
+
+message BinaryNode {
+  google.protobuf.Int32Value left_child_id = 1;
+  google.protobuf.Int32Value right_child_id = 2;
+  enum Direction {
+    LEFT = 0;
+    RIGHT = 1;
+  }
+  // When left_child_test is undefined for a particular datapoint (e.g. because
+  // it's not defined when feature value is missing), the datapoint should go
+  // in this direction.
+  Direction default_direction = 3;
+  // When a datapoint satisfies the test, it should be propagated to the left
+  // child.
+  oneof left_child_test {
+    InequalityTest inequality_left_child_test = 4;
+    google.protobuf.Any custom_left_child_test = 5;
+  }
+};
+
+// A SparseVector represents a vector in which only certain select elements
+// are non-zero.  Maps labels to values (e.g. class id to probability or count).
+message SparseVector {
+  map<int64, Value> sparse_value = 1;
+}
+
+message Vector {
+  repeated Value value = 1;
+}
+
+message Leaf {
+  oneof leaf {
+    // The interpretation of the values held in the leaves of a decision tree
+    // is application specific, but some common cases are:
+    // 1) len(vector) = 1, and the floating point value[0] holds the class 0
+    //    probability in a two class classification problem.
+    // 2) len(vector) = 1, and the integer value[0] holds the class prediction.
+    // 3) The floating point value[i] holds the class i probability prediction.
+    // 4) The floating point value[i] holds the i-th component of the
+    //    vector prediction in a regression problem.
+    // 5) sparse_vector holds the sparse class predictions for a classification
+    //    problem with a large number of classes.
+    Vector vector = 1;
+    SparseVector sparse_vector = 2;
+  }
+  // For non-standard handling of leaves.
+  repeated google.protobuf.Any additional_data = 3;
+};
+
+
+message FeatureId {
+  google.protobuf.StringValue id = 1;
+  repeated google.protobuf.Any additional_data = 2;
+};
+
+message ObliqueFeatures {
+  // total value is sum(features[i] * weights[i]).
+  repeated FeatureId features = 1;
+  repeated float weights = 2;
+}
+
+
+message InequalityTest {
+  // When the feature is missing, the test's outcome is undefined.
+  oneof FeatureSum {
+    FeatureId feature_id = 1;
+    ObliqueFeatures oblique = 4;
+  }
+  enum Type {
+    LESS_OR_EQUAL = 0;
+    LESS_THAN = 1;
+    GREATER_OR_EQUAL = 2;
+    GREATER_THAN = 3;
+  };
+  Type type = 2;
+  Value threshold = 3;
+};
+
+
+// Represents a single value of any type, e.g. 5 or "abc".
+message Value {
+  oneof value {
+    float float_value = 1;
+    double double_value = 2;
+    int32 int32_value = 3;
+    int64 int64_value = 4;
+    google.protobuf.Any custom_value = 5;
+  }
+};
diff --git a/tensorflow/contrib/decision_trees/proto/generic_tree_model_extensions.proto b/tensorflow/contrib/decision_trees/proto/generic_tree_model_extensions.proto
new file mode 100644
index 0000000000..4c0cceaddc
--- /dev/null
+++ b/tensorflow/contrib/decision_trees/proto/generic_tree_model_extensions.proto
@@ -0,0 +1,18 @@
+// Messages in this file are not part of the basic standard established by
+// generic_tree_model.proto (see the toplevel comment in that file).
+
+syntax = "proto3";
+
+package tensorflow.decision_trees;
+
+import "tensorflow/contrib/decision_trees/proto/generic_tree_model.proto";
+
+// Used in generic_tree_model.BinaryNode.left_child_test.
+// Tests whether the feature's value belongs to the specified list,
+// (or does not belong if inverse=True).
+message MatchingValuesTest {
+  // When the feature is missing, the test's outcome is undefined.
+  FeatureId feature_id = 1;
+  repeated Value value = 2;
+  bool inverse = 3;
+}
diff --git a/tensorflow/contrib/decision_trees/proto/generic_tree_model_proto.swig b/tensorflow/contrib/decision_trees/proto/generic_tree_model_proto.swig
new file mode 100644
index 0000000000..d3d201afd5
--- /dev/null
+++ b/tensorflow/contrib/decision_trees/proto/generic_tree_model_proto.swig
@@ -0,0 +1,14 @@
+////////// SWIG INCLUDE //////////
+
+%include "net/proto/swig/protofunc.swig"
+
+#ifndef MUST_USE_RESULT
+#error Use this file only as a %include or %import after google.swig.
+#endif
+
+%{
+#include "third_party/tensorflow/contrib/decision_trees/proto/generic_tree_model.pb.h"
+%}
+
+PROTO_INPUT(tensorflow::decision_trees::DecisionTree, decision_tree);
+PROTO_IN_OUT(tensorflow::decision_trees::DecisionTree, decision_tree);