TrimmedConvolution/mtranspose_layer.cpp at master · limuhit/TrimmedConvolution · GitHub

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#include <vector>

#include "caffe/blob.hpp"
#include "caffe/common.hpp"
#include "caffe/filler.hpp"
#include "caffe/layer.hpp"
#include "caffe/util/math_functions.hpp"
#include "mtranspose_layer.hpp"

namespace caffe {

	template <typename Dtype>
	void MTransposeLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
		const vector<Blob<Dtype>*>& top) {
		MTransposeParameter mp = this->layer_param_.mtranspose_param();
		groups_ = mp.groups();

	}
	template <typename Dtype>
	void MTransposeLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom,
		const vector<Blob<Dtype>*>& top) {
		width_ = bottom[0]->width();
		height_ = bottom[0]->height();
		channel_ = bottom[0]->channels();
		num_ = bottom[0]->num();
		inner_size_ = width_*height_;
		vector<int> shape;
		shape.push_back(num_*channel_*height_*width_ / groups_);
		shape.push_back(groups_);
		top[0]->Reshape(shape);
	}
	template <typename Dtype>
	void mtranspose_forward_cpu_kernel(const int num, const Dtype * const bottom, Dtype * const top,
		const int inner_size, const int channel, const int groups) {
		for (int i = 0; i < num; i++) {
			int pn = i / inner_size / channel;
			int pc = (i / inner_size) % channel;
			int ps = i % inner_size;
			int tidx = (pn*inner_size*channel/groups + pc/groups*inner_size+ps)*groups+pc%groups;
			top[tidx] = bottom[i];
		}
	}
	template <typename Dtype>
	void MTransposeLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
		const vector<Blob<Dtype>*>& top) {
		const Dtype* bottom_data = bottom[0]->cpu_data();

		mtranspose_forward_cpu_kernel<Dtype>(bottom[0]->count(), bottom_data,
			top[0]->mutable_cpu_data(), inner_size_, channel_, groups_);

	}
	template <typename Dtype>
	void mtranspose_backward_cpu_kernel(const int num, Dtype * const bottom, const Dtype * const top,
		const int inner_size, const int channel, const int groups) {
		for (int i = 0; i < num; i++) {
			int pn = i / inner_size / channel;
			int pc = (i / inner_size) % channel;
			int ps = i % inner_size;
			int tidx = (pn*inner_size*channel / groups + pc / groups*inner_size + ps)*groups + pc%groups;
			bottom[i]=top[tidx];
		}
	}
	template <typename Dtype>
	void MTransposeLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
		const vector<bool>& propagate_down,
		const vector<Blob<Dtype>*>& bottom) {
		Dtype* bottom_diff = bottom[0]->mutable_cpu_diff();
		mtranspose_backward_cpu_kernel<Dtype>(bottom[0]->count(), bottom_diff,
			top[0]->cpu_diff(), inner_size_, channel_, groups_);

	}

#ifdef CPU_ONLY
	STUB_GPU(MTransposeLayer);
#endif

	INSTANTIATE_CLASS(MTransposeLayer);
	REGISTER_LAYER_CLASS(MTranspose);

}  // namespace caffe