| | |
| | | |
| | | l.biases = calloc(n, sizeof(float)); |
| | | l.bias_updates = calloc(n, sizeof(float)); |
| | | float scale = 1./sqrt(size*size*c); |
| | | //float scale = 1./sqrt(size*size*c); |
| | | float scale = sqrt(2./(size*size*c)); |
| | | for(i = 0; i < c*n*size*size; ++i) l.filters[i] = 2*scale*rand_uniform() - scale; |
| | | for(i = 0; i < n; ++i){ |
| | | l.biases[i] = scale; |
| | |
| | | return float_to_image(w,h,c,l.filters+i*h*w*c); |
| | | } |
| | | |
| | | void rgbgr_filters(convolutional_layer l) |
| | | { |
| | | int i; |
| | | for(i = 0; i < l.n; ++i){ |
| | | image im = get_convolutional_filter(l, i); |
| | | if (im.c == 3) rgbgr_image(im); |
| | | } |
| | | } |
| | | |
| | | image *get_filters(convolutional_layer l) |
| | | { |
| | | image *filters = calloc(l.n, sizeof(image)); |