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// Copyright 2014 BVLC and contributors.
#include <iostream> // NOLINT(readability/streams)
#include <vector>
#include "caffe/layer.hpp"
#include "caffe/vision_layers.hpp"
namespace caffe {
template <typename Dtype>
void PaddingLayer<Dtype>::SetUp(const vector<Blob<Dtype>*>& bottom,
vector<Blob<Dtype>*>* top) {
// DEPRECATION
LOG(WARNING) << "Padding layers are deprecated in favor of padding-aware "
"convolutions and WILL BE REMOVED. Please update your model "
"prototxt to replace padding layers with pad fields. "
"See https://github.com/BVLC/caffe/pull/128.";
PAD_ = this->layer_param_.pad();
CHECK_EQ(bottom.size(), 1) << "Padding Layer takes a single blob as input.";
CHECK_EQ(top->size(), 1) << "Padding Layer takes a single blob as output.";
NUM_ = bottom[0]->num();
CHANNEL_ = bottom[0]->channels();
HEIGHT_IN_ = bottom[0]->height();
WIDTH_IN_ = bottom[0]->width();
HEIGHT_OUT_ = HEIGHT_IN_ + PAD_ * 2;
WIDTH_OUT_ = WIDTH_IN_ + PAD_ * 2;
(*top)[0]->Reshape(NUM_, CHANNEL_, HEIGHT_OUT_, WIDTH_OUT_);
}
template <typename Dtype>
Dtype PaddingLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
vector<Blob<Dtype>*>* top) {
Dtype* top_data = (*top)[0]->mutable_cpu_data();
const Dtype* bottom_data = bottom[0]->cpu_data();
memset(top_data, 0, sizeof(Dtype) * (*top)[0]->count());
// In short, top[n, c, h, w] = bottom[n, c, h-pad, w-pad] if in range
for (int n = 0; n < NUM_; ++n) {
for (int c = 0; c < CHANNEL_; ++c) {
for (int h = 0; h < HEIGHT_IN_; ++h) {
// copy the width part
memcpy(
top_data + ((n * CHANNEL_ + c) * HEIGHT_OUT_ + h + PAD_)
* WIDTH_OUT_ + PAD_,
bottom_data + ((n * CHANNEL_ + c) * HEIGHT_IN_ + h) * WIDTH_IN_,
sizeof(Dtype) * WIDTH_IN_);
}
}
}
return Dtype(0.);
}
template <typename Dtype>
void PaddingLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
const bool propagate_down, vector<Blob<Dtype>*>* bottom) {
const Dtype* top_diff = top[0]->cpu_diff();
Dtype* bottom_diff = (*bottom)[0]->mutable_cpu_diff();
for (int n = 0; n < NUM_; ++n) {
for (int c = 0; c < CHANNEL_; ++c) {
for (int h = 0; h < HEIGHT_IN_; ++h) {
// copy the width part
memcpy(
bottom_diff + ((n * CHANNEL_ + c) * HEIGHT_IN_ + h) * WIDTH_IN_,
top_diff + ((n * CHANNEL_ + c) * HEIGHT_OUT_ + h + PAD_)
* WIDTH_OUT_ + PAD_,
sizeof(Dtype) * WIDTH_IN_);
}
}
}
}
INSTANTIATE_CLASS(PaddingLayer);
} // namespace caffe
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