Function LRN_AcrossChannel

software/custom/custom_class.cpp:21–68

#include <string.h>

void LRN_AcrossChannel(  const float* src, float *dst, const vector<int> dim, const int local_size,
		const float alpha, const float beta)
{
	int batch = 1;//dim[0];
	int channels = dim[1];
	int height = dim[2];
	int width = dim[3];
	int dst_cnt = 0;
	int N = batch*channels*height*width;

	float a_by_n = alpha / (static_cast<float>(local_size));
	int half_size = local_size / 2;
	int channel_size = height * width;
	int batch_size = channels * channel_size;

	//vector<float> dst; dst.reserve(N);

	// Square the input
	vector<float> sq; sq.reserve(N);
	for(int i=0; i<N; ++i)
		sq.push_back(src[i]*src[i]);

	// Do sliding window (1 + a/n * x.sum()) ^ b
	for(int b=0; b<batch; ++b) {
		for(int c=0; c<channels; ++c) {
			for(int h=0; h<height; ++h) {
				for(int w=0; w<width; ++w) {
					// For each output pixel, iterate over the sliding window
					int start_c = max(0, c-half_size);
					int end_c = min(channels-1, c+half_size);
					float sum = 0.0f;
					for(int kc=start_c; kc<=end_c; ++kc) {
						int ind = b*batch_size + kc*channel_size + h*width + w;
						float val= sq[ind];
						sum += val;
					}
					float tmp = 1.0f + a_by_n * sum;
					float tmp2= powf(tmp, beta);
					float res = src[b*batch_size + c*channel_size + h*width + w] / tmp2;
					//dst.push_back(res);
					dst[dst_cnt++] = res;
				}
			}
		}
	}

	//return dst;
}


void Frcnn_LRN(const float *src, float *dst,const vector<int> dim, const int local_size=3,