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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 TENSORFLOW_CONTRIB_TENSOR_FOREST_KERNELS_V4_TEST_UTILS_H_
#define TENSORFLOW_CONTRIB_TENSOR_FOREST_KERNELS_V4_TEST_UTILS_H_
#include "tensorflow/contrib/tensor_forest/kernels/v4/input_data.h"
#include "tensorflow/contrib/tensor_forest/kernels/v4/input_target.h"
namespace tensorflow {
namespace tensorforest {
class TestableInputTarget : public StoredInputTarget<std::vector<float>> {
public:
TestableInputTarget(const std::vector<float>& t, const std::vector<float>& w,
int num_t)
: StoredInputTarget(new std::vector<float>(t), new std::vector<float>(w),
num_t) {}
int NumItems() const {
return target_->size();
}
int32 GetTargetAsClassIndex(int example_index,
int target_index) const override {
return static_cast<int32>(
GetTargetAsContinuous(example_index, target_index));
}
float GetTargetWeight(int example_index) const override {
const size_t num_weights = weight_->size();
return num_weights > 0 && example_index < num_weights
? (*weight_)[example_index]
: 1.0;
}
float GetTargetAsContinuous(int example_index,
int target_index) const override {
QCHECK_LT(target_index, num_targets_);
return (*target_)[example_index * num_targets_ + target_index];
}
};
class TestableDataSet : public TensorDataSet {
public:
TestableDataSet(const std::vector<float>& data, int num_features)
: TensorDataSet(TensorForestDataSpec(), 11),
num_features_(num_features),
data_(data) {}
float GetExampleValue(int example, int32 feature_id) const override {
return data_[example * num_features_ + feature_id];
}
protected:
int num_features_;
std::vector<float> data_;
};
} // namespace tensorforest
} // namespace tensorflow
#endif // TENSORFLOW_CONTRIB_TENSOR_FOREST_KERNELS_V4_TEST_UTILS_H_
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