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implementation MirrorPad of TF for both mode=REFLECT and mode=SYMMETRIC
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‎include/caffe/layers/mirror_pad_layer.hpp‎

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#ifndef CAFFE_MIRROR_PAD_LAYER_HPP_
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#define CAFFE_MIRROR_PAD_LAYER_HPP_
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#include <vector>
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#include "caffe/blob.hpp"
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#include "caffe/layer.hpp"
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#include "caffe/proto/caffe.pb.h"
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namespace caffe {
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template <typename Dtype>
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class MirrorPadLayer : public Layer<Dtype> {
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public:
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explicit MirrorPadLayer(const LayerParameter& param)
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: Layer<Dtype>(param) {}
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virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
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const vector<Blob<Dtype>*>& top);
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virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
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const vector<Blob<Dtype>*>& top);
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virtual inline const char* type() const { return "MirrorPad"; }
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virtual inline int ExactNumBottomBlobs() const { return 1; }
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virtual inline int ExactNumTopBlobs() const { return 1; }
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protected:
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virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
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const vector<Blob<Dtype>*>& top);
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/// @brief Not implemented (non-differentiable function)
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virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
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const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {
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NOT_IMPLEMENTED;
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}
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inline vector<int> indices(int offset, const vector<int> & shape) const;
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inline int offset(const vector<int>& indices, const vector<int> & shape) const;
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vector<int> paddings_;
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float constant_values_;
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string mode_;
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};
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} // namespace caffe
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#endif // CAFFE_MIRROR_PAD_LAYER_HPP_

‎src/caffe/layers/mirror_pad_layer.cpp‎

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#include <algorithm>
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#include <functional>
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#include <utility>
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#include <vector>
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#include "caffe/layers/mirror_pad_layer.hpp"
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namespace caffe {
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using namespace std;
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template <typename Dtype>
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void MirrorPadLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype> *> &bottom,
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const vector<Blob<Dtype> *> &top) {
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const MirrorPadParameter &mirror_pad_param =
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this->layer_param_.mirror_pad_param();
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constant_values_ = mirror_pad_param.constant_values();
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mode_ = mirror_pad_param.mode();
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paddings_.clear();
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std::copy(mirror_pad_param.paddings().begin(),
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mirror_pad_param.paddings().end(), std::back_inserter(paddings_));
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int pad_dim = paddings_.size();
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CHECK_EQ(pad_dim % 2, 0)
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<< "Paddings for each dimension should have 2 values!";
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CHECK_EQ(pad_dim / 2, bottom[0]->num_axes())
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<< "Paddings' num should be 2 times of bottom dimension!";
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// CHECK_LE(bottom[0]->num_axes(), 4) << "Not support more than 4D paddings!";
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}
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template <typename Dtype>
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void MirrorPadLayer<Dtype>::Reshape(const vector<Blob<Dtype> *> &bottom,
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const vector<Blob<Dtype> *> &top) {
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int num_top_axes = bottom[0]->num_axes();
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std::vector<int> shape(num_top_axes, 1);
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shape = bottom[0]->shape();
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for (int i = 0; i < num_top_axes; i++) {
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shape[i] = shape[i] + paddings_[2 * i] + paddings_[2 * i + 1];
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}
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top[0]->Reshape(shape);
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}
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template <typename Dtype>
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inline vector<int>
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MirrorPadLayer<Dtype>::indices(int offset, const vector<int> &shape) const {
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vector<int> indices(shape.size());
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int r = offset;
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for (int i = shape.size() - 1; i >= 0; i--) {
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indices[i] = r % shape[i];
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r /= shape[i];
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}
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return indices;
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}
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template <typename Dtype>
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inline int MirrorPadLayer<Dtype>::offset(const vector<int> &indices,
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const vector<int> &shape) const {
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int offset = 0;
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for (int i = 0; i < shape.size(); ++i) {
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offset *= shape[i];
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offset += indices[i];
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}
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return offset;
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}
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template <typename Dtype>
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void MirrorPadLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype> *> &bottom,
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const vector<Blob<Dtype> *> &top) {
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const Dtype *bottom_data = bottom[0]->cpu_data();
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Dtype *top_data = top[0]->mutable_cpu_data();
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auto bottom_shape = bottom[0]->shape();
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auto top_shape = top[0]->shape();
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int strides = bottom_shape.back();
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caffe_set(top[0]->count(), Dtype(constant_values_), top_data);
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for (int position = 0; position < bottom[0]->count() / strides; position++) {
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vector<int> coord_bottom = indices(position * strides, bottom_shape);
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vector<int> coord_pad(coord_bottom);
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for (int i = 0; i < top_shape.size(); i++)
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coord_pad[i] += paddings_[2 * i];
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int position_top = offset(coord_pad, top_shape);
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copy_n(bottom_data + position * strides, strides, top_data + position_top);
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}
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if (mode_ == "REFLECT") {
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strides = 1;
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for (int i = top_shape.size() - 1; i >= 0; i--) {
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int inner_strides = strides;
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strides *= top_shape[i];
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for (int position = 0; position < top[0]->count() / strides; position++) {
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for (int j = 1; j <= paddings_[2 * i]; j++) {
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copy_n(top_data + position*strides + inner_strides * (paddings_[2 * i] + j),
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inner_strides,
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top_data + position*strides + inner_strides * (paddings_[2 * i] - j));
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}
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for (int j = 1; j <= paddings_[2 * i + 1]; j++) {
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copy_n(top_data + position*strides + inner_strides * (bottom_shape[i] + paddings_[2 * i] - 1 - j),
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inner_strides,
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top_data + position*strides + inner_strides * (bottom_shape[i] + paddings_[2 * i] - 1 + j));
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}
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}
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}
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} else if (mode_ == "SYMMETRIC") {
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strides = 1;
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for (int i = top_shape.size() - 1; i >= 0; i--) {
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int inner_strides = strides;
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strides *= top_shape[i];
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for (int position = 0; position < top[0]->count() / strides; position++) {
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for (int j = 0; j < paddings_[2 * i]; j++) {
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copy_n(top_data + position*strides + inner_strides * (paddings_[2 * i] + j),
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inner_strides,
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top_data + position*strides + inner_strides * (paddings_[2 * i] - j - 1));
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}
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for (int j = 0; j < paddings_[2 * i + 1]; j++) {
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copy_n(top_data + position*strides + inner_strides * (bottom_shape[i] + paddings_[2 * i] - 1 - j),
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inner_strides,
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top_data + position*strides + inner_strides * (bottom_shape[i] + paddings_[2 * i] + j));
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}
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}
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}
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}
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}
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INSTANTIATE_CLASS(MirrorPadLayer);
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REGISTER_LAYER_CLASS(MirrorPad);
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} // namespace caffe

‎src/caffe/proto/caffe.proto‎

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@@ -460,7 +460,7 @@ message ParamSpec {
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// NOTE
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// Update the next available ID when you add a new LayerParameter field.
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//
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// LayerParameter next available layer-specific ID: 237 (last added: xlu_param)
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// LayerParameter next available layer-specific ID: 238 (last added: mirror_pad_param)
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message LayerParameter {
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optional string name = 1; // the layer name
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optional string type = 2; // the layer type
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optional UnstackParameter unstack_param = 234;
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optional BatchToSpaceNDParameter batch_to_space_nd_param = 235;
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optional SpaceToBatchNDParameter space_to_batch_nd_param = 236;
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optional MirrorPadParameter mirror_pad_param = 238;
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}
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message AccumParameter {
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optional float constant_values = 2 [default = 0.0];
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}
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message MirrorPadParameter{
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repeated uint32 paddings = 1;
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optional float constant_values = 2 [default = 0.0];
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optional string mode = 3 [default = "CONSTANT"];
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}
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message StackParameter{
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optional int32 axis = 1 [default = 0];
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}

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