| | |
| | | int classes = option_find_int(options, "classes", 20); |
| | | int num = option_find_int(options, "num", 1); |
| | | |
| | | params.w = option_find_int(options, "side", params.w); |
| | | params.h = option_find_int(options, "side", params.h); |
| | | |
| | | layer l = make_region_layer(params.batch, params.w, params.h, num, classes, coords); |
| | | assert(l.outputs == params.inputs); |
| | | |
| | |
| | | n = n->next; |
| | | int count = 0; |
| | | free_section(s); |
| | | fprintf(stderr, "layer filters size input output\n"); |
| | | while(n){ |
| | | params.index = count; |
| | | fprintf(stderr, "%d: ", count); |
| | | fprintf(stderr, "%5d ", count); |
| | | s = (section *)n->val; |
| | | options = s->options; |
| | | layer l = {0}; |
| | |
| | | //return; |
| | | } |
| | | int num = l.n*l.c*l.size*l.size; |
| | | if(0){ |
| | | fread(l.biases + ((l.n != 1374)?0:5), sizeof(float), l.n, fp); |
| | | if (l.batch_normalize && (!l.dontloadscales)){ |
| | | fread(l.scales + ((l.n != 1374)?0:5), sizeof(float), l.n, fp); |
| | | fread(l.rolling_mean + ((l.n != 1374)?0:5), sizeof(float), l.n, fp); |
| | | fread(l.rolling_variance + ((l.n != 1374)?0:5), sizeof(float), l.n, fp); |
| | | fread(l.biases, sizeof(float), l.n, fp); |
| | | if (l.batch_normalize && (!l.dontloadscales)){ |
| | | fread(l.scales, sizeof(float), l.n, fp); |
| | | fread(l.rolling_mean, sizeof(float), l.n, fp); |
| | | fread(l.rolling_variance, sizeof(float), l.n, fp); |
| | | if(0){ |
| | | int i; |
| | | for(i = 0; i < l.n; ++i){ |
| | | printf("%g, ", l.rolling_mean[i]); |
| | | } |
| | | printf("\n"); |
| | | for(i = 0; i < l.n; ++i){ |
| | | printf("%g, ", l.rolling_variance[i]); |
| | | } |
| | | printf("\n"); |
| | | } |
| | | fread(l.weights + ((l.n != 1374)?0:5*l.c*l.size*l.size), sizeof(float), num, fp); |
| | | }else{ |
| | | fread(l.biases, sizeof(float), l.n, fp); |
| | | if (l.batch_normalize && (!l.dontloadscales)){ |
| | | fread(l.scales, sizeof(float), l.n, fp); |
| | | fread(l.rolling_mean, sizeof(float), l.n, fp); |
| | | fread(l.rolling_variance, sizeof(float), l.n, fp); |
| | | if(0){ |
| | | fill_cpu(l.n, 0, l.rolling_mean, 1); |
| | | fill_cpu(l.n, 0, l.rolling_variance, 1); |
| | | } |
| | | fread(l.weights, sizeof(float), num, fp); |
| | | } |
| | | fread(l.weights, sizeof(float), num, fp); |
| | | if(l.adam){ |
| | | fread(l.m, sizeof(float), num, fp); |
| | | fread(l.v, sizeof(float), num, fp); |