#include "region_layer.h"
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#include "activations.h"
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#include "softmax_layer.h"
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#include "blas.h"
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#include "box.h"
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#include "cuda.h"
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#include "utils.h"
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#include <stdio.h>
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#include <assert.h>
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#include <string.h>
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#include <stdlib.h>
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region_layer make_region_layer(int batch, int inputs, int n, int side, int classes, int coords, int rescore)
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{
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region_layer l = {0};
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l.type = REGION;
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l.n = n;
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l.batch = batch;
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l.inputs = inputs;
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l.classes = classes;
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l.coords = coords;
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l.rescore = rescore;
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l.side = side;
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assert(side*side*((1 + l.coords)*l.n + l.classes) == inputs);
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l.cost = calloc(1, sizeof(float));
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l.outputs = l.inputs;
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l.truths = l.side*l.side*(1+l.coords+l.classes);
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l.output = calloc(batch*l.outputs, sizeof(float));
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l.delta = calloc(batch*l.outputs, sizeof(float));
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#ifdef GPU
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l.output_gpu = cuda_make_array(l.output, batch*l.outputs);
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l.delta_gpu = cuda_make_array(l.delta, batch*l.outputs);
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#endif
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fprintf(stderr, "Region Layer\n");
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srand(0);
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return l;
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}
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void forward_region_layer(const region_layer l, network_state state)
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{
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int locations = l.side*l.side;
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int i,j;
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memcpy(l.output, state.input, l.outputs*l.batch*sizeof(float));
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for(i = 0; i < l.batch*locations; ++i){
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int index = i*((1+l.coords)*l.n + l.classes);
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if(l.softmax){
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activate_array(l.output + index, l.n*(1+l.coords), LOGISTIC);
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int offset = l.n*(1+l.coords);
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softmax_array(l.output + index + offset, l.classes,
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l.output + index + offset);
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}
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}
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if(state.train){
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float avg_iou = 0;
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float avg_cat = 0;
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float avg_obj = 0;
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float avg_anyobj = 0;
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int count = 0;
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*(l.cost) = 0;
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int size = l.inputs * l.batch;
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memset(l.delta, 0, size * sizeof(float));
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for (i = 0; i < l.batch*locations; ++i) {
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int index = i*((1+l.coords)*l.n + l.classes);
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for(j = 0; j < l.n; ++j){
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int prob_index = index + j*(1 + l.coords);
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l.delta[prob_index] = (1./l.n)*(0-l.output[prob_index]);
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if(l.softmax){
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l.delta[prob_index] = 1./(l.n*l.side)*(0-l.output[prob_index]);
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}
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*(l.cost) += (1./l.n)*pow(l.output[prob_index], 2);
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//printf("%f\n", l.output[prob_index]);
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avg_anyobj += l.output[prob_index];
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}
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int truth_index = i*(1 + l.coords + l.classes);
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int best_index = -1;
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float best_iou = 0;
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float best_rmse = 4;
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int bg = !state.truth[truth_index];
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if(bg) {
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continue;
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}
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int class_index = index + l.n*(1+l.coords);
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for(j = 0; j < l.classes; ++j) {
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l.delta[class_index+j] = state.truth[truth_index+1+j] - l.output[class_index+j];
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*(l.cost) += pow(state.truth[truth_index+1+j] - l.output[class_index+j], 2);
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if(state.truth[truth_index + 1 + j]) avg_cat += l.output[class_index+j];
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}
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truth_index += l.classes + 1;
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box truth = {state.truth[truth_index+0], state.truth[truth_index+1], state.truth[truth_index+2], state.truth[truth_index+3]};
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truth.x /= l.side;
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truth.y /= l.side;
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for(j = 0; j < l.n; ++j){
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int out_index = index + j*(1+l.coords);
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box out = {l.output[out_index+1], l.output[out_index+2], l.output[out_index+3], l.output[out_index+4]};
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out.x /= l.side;
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out.y /= l.side;
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if (l.sqrt){
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out.w = out.w*out.w;
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out.h = out.h*out.h;
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}
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float iou = box_iou(out, truth);
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float rmse = box_rmse(out, truth);
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if(best_iou > 0 || iou > 0){
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if(iou > best_iou){
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best_iou = iou;
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best_index = j;
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}
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}else{
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if(rmse < best_rmse){
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best_rmse = rmse;
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best_index = j;
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}
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}
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}
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//printf("%d", best_index);
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int in_index = index + best_index*(1+l.coords);
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*(l.cost) -= pow(l.output[in_index], 2);
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*(l.cost) += pow(1-l.output[in_index], 2);
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avg_obj += l.output[in_index];
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l.delta[in_index+0] = (1.-l.output[in_index]);
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if(l.softmax){
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l.delta[in_index+0] = 5*(1.-l.output[in_index]);
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}
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//printf("%f\n", l.output[in_index]);
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l.delta[in_index+1] = 5*(state.truth[truth_index+0] - l.output[in_index+1]);
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l.delta[in_index+2] = 5*(state.truth[truth_index+1] - l.output[in_index+2]);
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if(l.sqrt){
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l.delta[in_index+3] = 5*(sqrt(state.truth[truth_index+2]) - l.output[in_index+3]);
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l.delta[in_index+4] = 5*(sqrt(state.truth[truth_index+3]) - l.output[in_index+4]);
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}else{
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l.delta[in_index+3] = 5*(state.truth[truth_index+2] - l.output[in_index+3]);
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l.delta[in_index+4] = 5*(state.truth[truth_index+3] - l.output[in_index+4]);
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}
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*(l.cost) += pow(1-best_iou, 2);
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avg_iou += best_iou;
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++count;
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if(l.softmax){
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gradient_array(l.output + index, l.n*(1+l.coords), LOGISTIC, l.delta + index);
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}
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}
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printf("Avg IOU: %f, Avg Cat Pred: %f, Avg Obj: %f, Avg Any: %f, count: %d\n", avg_iou/count, avg_cat/count, avg_obj/count, avg_anyobj/(l.batch*locations*l.n), count);
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}
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}
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void backward_region_layer(const region_layer l, network_state state)
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{
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axpy_cpu(l.batch*l.inputs, 1, l.delta, 1, state.delta, 1);
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}
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#ifdef GPU
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void forward_region_layer_gpu(const region_layer l, network_state state)
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{
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float *in_cpu = calloc(l.batch*l.inputs, sizeof(float));
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float *truth_cpu = 0;
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if(state.truth){
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int num_truth = l.batch*l.side*l.side*(1+l.coords+l.classes);
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truth_cpu = calloc(num_truth, sizeof(float));
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cuda_pull_array(state.truth, truth_cpu, num_truth);
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}
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cuda_pull_array(state.input, in_cpu, l.batch*l.inputs);
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network_state cpu_state;
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cpu_state.train = state.train;
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cpu_state.truth = truth_cpu;
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cpu_state.input = in_cpu;
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forward_region_layer(l, cpu_state);
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cuda_push_array(l.output_gpu, l.output, l.batch*l.outputs);
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cuda_push_array(l.delta_gpu, l.delta, l.batch*l.inputs);
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free(cpu_state.input);
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if(cpu_state.truth) free(cpu_state.truth);
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}
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void backward_region_layer_gpu(region_layer l, network_state state)
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{
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axpy_ongpu(l.batch*l.inputs, 1, l.delta_gpu, 1, state.delta, 1);
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//copy_ongpu(l.batch*l.inputs, l.delta_gpu, 1, state.delta, 1);
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}
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#endif
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