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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.
// =============================================================================
#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TENSOR_FOREST_KERNELS_V4_DECISION_NODE_EVALUATOR_H_
#define THIRD_PARTY_TENSORFLOW_CONTRIB_TENSOR_FOREST_KERNELS_V4_DECISION_NODE_EVALUATOR_H_
#include "tensorflow/contrib/decision_trees/proto/generic_tree_model.pb.h"
#include "tensorflow/contrib/decision_trees/proto/generic_tree_model_extensions.pb.h"
#include "tensorflow/contrib/tensor_forest/kernels/v4/input_data.h"
namespace tensorflow {
namespace tensorforest {
// Base class for evaluators of decision nodes that effectively copy proto
// contents into C++ structures for faster execution.
class DecisionNodeEvaluator {
public:
virtual ~DecisionNodeEvaluator() {}
// Returns the index of the child node.
virtual int32 Decide(const std::unique_ptr<TensorDataSet>& dataset,
int example) const = 0;
};
// An evaluator for binary decisions with left and right children.
class BinaryDecisionNodeEvaluator : public DecisionNodeEvaluator {
protected:
BinaryDecisionNodeEvaluator(int32 left, int32 right)
: left_child_id_(left), right_child_id_(right) {}
int32 left_child_id_;
int32 right_child_id_;
};
// Evaluator for basic inequality decisions (f[x] <= T).
class InequalityDecisionNodeEvaluator : public BinaryDecisionNodeEvaluator {
public:
InequalityDecisionNodeEvaluator(const decision_trees::InequalityTest& test,
int32 left, int32 right);
int32 Decide(const std::unique_ptr<TensorDataSet>& dataset,
int example) const override;
protected:
int32 feature_num_;
float threshold_;
// If decision is '<=' as opposed to '<'.
bool include_equals_;
};
// Evalutor for splits with multiple weighted features.
class ObliqueInequalityDecisionNodeEvaluator
: public BinaryDecisionNodeEvaluator {
public:
ObliqueInequalityDecisionNodeEvaluator(
const decision_trees::InequalityTest& test, int32 left, int32 right);
int32 Decide(const std::unique_ptr<TensorDataSet>& dataset,
int example) const override;
protected:
std::vector<int32> feature_num_;
std::vector<float> feature_weights_;
float threshold_;
};
// Evaluator for contains-in-set decisions. Also supports inverse (not-in-set).
class MatchingValuesDecisionNodeEvaluator : public BinaryDecisionNodeEvaluator {
public:
MatchingValuesDecisionNodeEvaluator(
const decision_trees::MatchingValuesTest& test, int32 left, int32 right);
int32 Decide(const std::unique_ptr<TensorDataSet>& dataset,
int example) const override;
protected:
int32 feature_num_;
std::vector<float> values_;
bool inverse_;
};
std::unique_ptr<DecisionNodeEvaluator> CreateDecisionNodeEvaluator(
const decision_trees::TreeNode& node);
std::unique_ptr<DecisionNodeEvaluator> CreateBinaryDecisionNodeEvaluator(
const decision_trees::BinaryNode& node, int32 left, int32 right);
struct CandidateEvalatorCollection {
std::vector<std::unique_ptr<DecisionNodeEvaluator>> splits;
};
} // namespace tensorforest
} // namespace tensorflow
#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TENSOR_FOREST_KERNELS_V4_DECISION_NODE_EVALUATOR_H_
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