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// Copyright 2017 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
#include "tensorflow/contrib/tensor_forest/kernels/v4/decision_node_evaluator.h"
#include "tensorflow/core/lib/strings/numbers.h"
namespace tensorflow {
namespace tensorforest {
std::unique_ptr<DecisionNodeEvaluator> CreateDecisionNodeEvaluator(
const decision_trees::TreeNode& node) {
const decision_trees::BinaryNode& bnode = node.binary_node();
return CreateBinaryDecisionNodeEvaluator(bnode, bnode.left_child_id().value(),
bnode.right_child_id().value());
}
std::unique_ptr<DecisionNodeEvaluator> CreateBinaryDecisionNodeEvaluator(
const decision_trees::BinaryNode& bnode, int32 left, int32 right) {
if (bnode.has_inequality_left_child_test()) {
const auto& test = bnode.inequality_left_child_test();
if (test.has_oblique()) {
return std::unique_ptr<ObliqueInequalityDecisionNodeEvaluator>(
new ObliqueInequalityDecisionNodeEvaluator(test, left, right));
} else {
return std::unique_ptr<InequalityDecisionNodeEvaluator>(
new InequalityDecisionNodeEvaluator(test, left, right));
}
} else {
decision_trees::MatchingValuesTest test;
if (bnode.custom_left_child_test().UnpackTo(&test)) {
return std::unique_ptr<MatchingValuesDecisionNodeEvaluator>(
new MatchingValuesDecisionNodeEvaluator(test, left, right));
} else {
LOG(ERROR) << "Unknown split test: " << bnode.DebugString();
return nullptr;
}
}
}
InequalityDecisionNodeEvaluator::InequalityDecisionNodeEvaluator(
const decision_trees::InequalityTest& test, int32 left, int32 right)
: BinaryDecisionNodeEvaluator(left, right) {
CHECK(safe_strto32(test.feature_id().id().value(), &feature_num_))
<< "Invalid feature ID: [" << test.feature_id().id().value() << "]";
threshold_ = test.threshold().float_value();
_test_type = test.type();
}
int32 InequalityDecisionNodeEvaluator::Decide(
const std::unique_ptr<TensorDataSet>& dataset, int example) const {
const float val = dataset->GetExampleValue(example, feature_num_);
switch (_test_type) {
case decision_trees::InequalityTest::LESS_OR_EQUAL:
return val <= threshold_ ? left_child_id_ : right_child_id_;
case decision_trees::InequalityTest::LESS_THAN:
return val < threshold_ ? left_child_id_ : right_child_id_;
case decision_trees::InequalityTest::GREATER_OR_EQUAL:
return val >= threshold_ ? left_child_id_ : right_child_id_;
case decision_trees::InequalityTest::GREATER_THAN:
return val > threshold_ ? left_child_id_ : right_child_id_;
default:
LOG(ERROR) << "Unknown split test type: " << _test_type;
return -1;
}
}
ObliqueInequalityDecisionNodeEvaluator::ObliqueInequalityDecisionNodeEvaluator(
const decision_trees::InequalityTest& test, int32 left, int32 right)
: BinaryDecisionNodeEvaluator(left, right) {
for (int i = 0; i < test.oblique().features_size(); ++i) {
int32 val;
CHECK(safe_strto32(test.oblique().features(i).id().value(), &val))
<< "Invalid feature ID: [" << test.oblique().features(i).id().value()
<< "]";
feature_num_.push_back(val);
feature_weights_.push_back(test.oblique().weights(i));
}
threshold_ = test.threshold().float_value();
}
int32 ObliqueInequalityDecisionNodeEvaluator::Decide(
const std::unique_ptr<TensorDataSet>& dataset, int example) const {
float val = 0;
for (int i = 0; i < feature_num_.size(); ++i) {
val += feature_weights_[i] *
dataset->GetExampleValue(example, feature_num_[i]);
}
if (val <= threshold_) {
return left_child_id_;
} else {
return right_child_id_;
}
}
MatchingValuesDecisionNodeEvaluator::MatchingValuesDecisionNodeEvaluator(
const decision_trees::MatchingValuesTest& test, int32 left, int32 right)
: BinaryDecisionNodeEvaluator(left, right) {
CHECK(safe_strto32(test.feature_id().id().value(), &feature_num_))
<< "Invalid feature ID: [" << test.feature_id().id().value() << "]";
for (const auto& val : test.value()) {
values_.push_back(val.float_value());
}
inverse_ = test.inverse();
}
int32 MatchingValuesDecisionNodeEvaluator::Decide(
const std::unique_ptr<TensorDataSet>& dataset, int example) const {
const float val = dataset->GetExampleValue(example, feature_num_);
for (float testval : values_) {
if (val == testval) {
return inverse_ ? right_child_id_ : left_child_id_;
}
}
return inverse_ ? left_child_id_ : right_child_id_;
}
} // namespace tensorforest
} // namespace tensorflow
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