blob: 592e892f9a3486ffdaf2f80a3b558bb0f391cd2c [file] [log] [blame]
/**
* 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.
*/
#include "singa/model/layer.h"
#include "./flatten.h"
namespace singa {
RegisterLayerClass(singa_flatten, Flatten);
RegisterLayerClass(singacpp_flatten, Flatten);
RegisterLayerClass(singacuda_flatten, Flatten);
RegisterLayerClass(singacl_flatten, Flatten);
void Flatten::Setup(const Shape& in_sample, const LayerConf &conf) {
Layer::Setup(in_sample, conf);
axis_ = conf.flatten_conf().axis();
size_t len = 1;
if (axis_ > 0)
for (size_t i = axis_ - 1; i < in_sample.size(); i++)
len *= in_sample.at(i);
out_sample_shape_.push_back(len);
}
const Tensor Flatten::Forward(int flag, const Tensor &input) {
Tensor output;
input_shape_ = input.shape();
if (axis_ == 0)
output = Reshape(input, vector<size_t>{input.Size()});
else
output =
Reshape(input, vector<size_t>{input.Size() / out_sample_shape_.at(0),
out_sample_shape_.at(0)});
return output;
}
const std::pair<Tensor, vector<Tensor> > Flatten::Backward(int flag,
const Tensor &grad) {
vector<Tensor> param_grad;
Tensor input_grad = Reshape(grad, input_shape_);
return std::make_pair(input_grad, param_grad);
}
} // namespace singa