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/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 SRC_MODEL_LAYER_MERGE_H_
#define SRC_MODEL_LAYER_MERGE_H_
#include <string>
#include <utility>
#include <vector>
#include "singa/model/layer.h"
namespace singa {
/// Sum features of all input layers
class Merge : public Layer {
public:
// const std::string layer_type() const override { return "Merge"; }
/// the sample shape of all input tesnors should be the same
void Setup(const Shape &in_sample, const LayerConf &conf) override;
const Shape GetOutputSampleShape() const override {
CHECK(out_sample_shape_.size()) << "You may haven't call Setup()";
return out_sample_shape_;
}
/// Sum all tensors in 'inputs'
/// Return a vector including the result of the summation
const vector<Tensor> Forward(int flag,
const vector<Tensor> &inputs) override;
/// 'grads' should include only one tensor
/// the first result vector includes the gradients for each input layer
/// the second result vector is empty
const std::pair<vector<Tensor>, vector<Tensor> >
Backward(int flag, const vector<Tensor> &grads) override;
protected:
Shape out_sample_shape_;
size_t input_size_ = 1u;
};
} // namespace singa
#endif // SRC_MODEL_LAYER_MERGE_H_