Esempi in C++ (Cpp) per save_batchnorm_weights

Esempio n. 1

File: parser.c Progetto: Zumbalamambo/darknetFaceID

void save_weights_upto(network net, char *filename, int cutoff)
{
#ifdef GPU
    if(net.gpu_index >= 0){
        cuda_set_device(net.gpu_index);
    }
#endif
    fprintf(stderr, "Saving weights to %s\n", filename);
    FILE *fp = fopen(filename, "wb");
    if(!fp) file_error(filename);

    int major = 0;
    int minor = 1;
    int revision = 0;
    fwrite(&major, sizeof(int), 1, fp);
    fwrite(&minor, sizeof(int), 1, fp);
    fwrite(&revision, sizeof(int), 1, fp);
    fwrite(net.seen, sizeof(int), 1, fp);

    int i;
    for(i = 0; i < net.n && i < cutoff; ++i){
        layer l = net.layers[i];
        if(l.type == CONVOLUTIONAL){
            save_convolutional_weights(l, fp);
        } if(l.type == CONNECTED){
            save_connected_weights(l, fp);
        } if(l.type == BATCHNORM){
            save_batchnorm_weights(l, fp);
        } if(l.type == RNN){
            save_connected_weights(*(l.input_layer), fp);
            save_connected_weights(*(l.self_layer), fp);
            save_connected_weights(*(l.output_layer), fp);
        } if(l.type == GRU){
            save_connected_weights(*(l.input_z_layer), fp);
            save_connected_weights(*(l.input_r_layer), fp);
            save_connected_weights(*(l.input_h_layer), fp);
            save_connected_weights(*(l.state_z_layer), fp);
            save_connected_weights(*(l.state_r_layer), fp);
            save_connected_weights(*(l.state_h_layer), fp);
        } if(l.type == CRNN){
            save_convolutional_weights(*(l.input_layer), fp);
            save_convolutional_weights(*(l.self_layer), fp);
            save_convolutional_weights(*(l.output_layer), fp);
        } if(l.type == LOCAL){
#ifdef GPU
            if(gpu_index >= 0){
                pull_local_layer(l);
            }
#endif
            int locations = l.out_w*l.out_h;
            int size = l.size*l.size*l.c*l.n*locations;
            fwrite(l.biases, sizeof(float), l.outputs, fp);
            fwrite(l.weights, sizeof(float), size, fp);
        }
    }
    fclose(fp);
}

Esempio n. 2

File: parser.c Progetto: iscaswcm/darknet

void save_weights_upto(network *net, char *filename, int cutoff)
{
#ifdef GPU
    if(net->gpu_index >= 0){
        cuda_set_device(net->gpu_index);
    }
#endif
    fprintf(stderr, "Saving weights to %s\n", filename);
    FILE *fp = fopen(filename, "wb");
    if(!fp) file_error(filename);

    int major = 0;
    int minor = 2;
    int revision = 0;
    fwrite(&major, sizeof(int), 1, fp);
    fwrite(&minor, sizeof(int), 1, fp);
    fwrite(&revision, sizeof(int), 1, fp);
    fwrite(net->seen, sizeof(size_t), 1, fp);

    int i;
    for(i = 0; i < net->n && i < cutoff; ++i){
        layer l = net->layers[i];
        if (l.dontsave) continue;
        if(l.type == CONVOLUTIONAL || l.type == DECONVOLUTIONAL){
            save_convolutional_weights(l, fp);
        } if(l.type == CONNECTED){
            save_connected_weights(l, fp);
        } if(l.type == BATCHNORM){
            save_batchnorm_weights(l, fp);
        } if(l.type == RNN){
            save_connected_weights(*(l.input_layer), fp);
            save_connected_weights(*(l.self_layer), fp);
            save_connected_weights(*(l.output_layer), fp);
        } if (l.type == LSTM) {
            save_connected_weights(*(l.wi), fp);
            save_connected_weights(*(l.wf), fp);
            save_connected_weights(*(l.wo), fp);
            save_connected_weights(*(l.wg), fp);
            save_connected_weights(*(l.ui), fp);
            save_connected_weights(*(l.uf), fp);
            save_connected_weights(*(l.uo), fp);
            save_connected_weights(*(l.ug), fp);
        } if (l.type == GRU) {
            if(1){
                save_connected_weights(*(l.wz), fp);
                save_connected_weights(*(l.wr), fp);
                save_connected_weights(*(l.wh), fp);
                save_connected_weights(*(l.uz), fp);
                save_connected_weights(*(l.ur), fp);
                save_connected_weights(*(l.uh), fp);
            }else{
                save_connected_weights(*(l.reset_layer), fp);
                save_connected_weights(*(l.update_layer), fp);
                save_connected_weights(*(l.state_layer), fp);
            }
        }  if(l.type == CRNN){
            save_convolutional_weights(*(l.input_layer), fp);
            save_convolutional_weights(*(l.self_layer), fp);
            save_convolutional_weights(*(l.output_layer), fp);
        } if(l.type == LOCAL){
#ifdef GPU
            if(gpu_index >= 0){
                pull_local_layer(l);
            }
#endif
            int locations = l.out_w*l.out_h;
            int size = l.size*l.size*l.c*l.n*locations;
            fwrite(l.biases, sizeof(float), l.outputs, fp);
            fwrite(l.weights, sizeof(float), size, fp);
        }
    }
    fclose(fp);
}