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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_POOLING_H_
#define SRC_MODEL_LAYER_POOLING_H_
#include <cfloat>
#include <stack>
#include <string>
#include <utility>
#include <vector>
#include "singa/model/layer.h"
namespace singa {
class Pooling : public Layer {
public:
/// \copydoc Layer::layer_type()
// const std::string layer_type() const override { return "Pooling"; }
/// \copydoc Layer::Setup(const LayerConf&);
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_;
}
/// \copydoc Layer::Forward(int flag, const Tensor&)
const Tensor Forward(int flag, const Tensor& input) override;
/// \copydoc Layer::Backward(int, const Tensor&, const Tensor&);
const std::pair<Tensor, vector<Tensor>> Backward(int flag,
const Tensor& grad) override;
void ForwardMaxPooling(const float* bottom, const int num, const int channels,
const int height, const int width,
const int pooled_h, const int pooled_w,
const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w,
const int stride_h, const int stride_w, float* top,
float* mask);
void BackwardMaxPooling(const float* top, const float* mask, const int num,
const int channels, const int height, const int width,
const int pooled_h, const int pooled_w,
const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w,
const int stride_h, const int stride_w,
float* bottom);
void ForwardAvgPooling(const float* bottom, const int num, const int channels,
const int height, const int width,
const int pooled_h, const int pooled_w,
const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w,
const int stride_h, const int stride_w,
float* top);
void BackwardAvgPooling(const float* top, const int num, const int channels,
const int height, const int width,
const int pooled_h, const int pooled_w,
const int kernel_h, const int kernel_w,
const int pad_h, const int pad_w,
const int stride_h, const int stride_w,
float* bottom);
size_t kernel_w() const { return kernel_w_; }
size_t kernel_h() const { return kernel_h_; }
size_t pad_w() const { return pad_w_; }
size_t pad_h() const { return pad_h_; }
size_t stride_w() const { return stride_w_; }
size_t stride_h() const { return stride_h_; }
PoolingConf_PoolMethod pool_method() const { return pool_; }
size_t channels() const { return channels_; }
size_t height() const { return height_; }
size_t width() const { return width_; }
protected:
size_t kernel_w_, pad_w_, stride_w_;
size_t kernel_h_, pad_h_, stride_h_;
size_t channels_, height_, width_, pooled_height_, pooled_width_;
PoolingConf_PoolMethod pool_;
// To store the input and output(of forward) tensors
std::stack<Tensor> buf_;
Shape out_sample_shape_;
};
} // namespace singa
#endif // SRC_MODEL_LAYER_POOLING_H_