| | |
| | | |
| | | convolutional_layer *parse_convolutional(list *options, network *net, int count) |
| | | { |
| | | int i; |
| | | int h,w,c; |
| | | float learning_rate, momentum, decay; |
| | | int n = option_find_int(options, "filters",1); |
| | |
| | | if(h == 0) error("Layer before convolutional layer must output image."); |
| | | } |
| | | convolutional_layer *layer = make_convolutional_layer(net->batch,h,w,c,n,size,stride,pad,activation,learning_rate,momentum,decay); |
| | | char *data = option_find_str(options, "data", 0); |
| | | if(data){ |
| | | char *curr = data; |
| | | char *next = data; |
| | | for(i = 0; i < n; ++i){ |
| | | while(*++next !='\0' && *next != ','); |
| | | *next = '\0'; |
| | | sscanf(curr, "%g", &layer->biases[i]); |
| | | curr = next+1; |
| | | } |
| | | for(i = 0; i < c*n*size*size; ++i){ |
| | | while(*++next !='\0' && *next != ','); |
| | | *next = '\0'; |
| | | sscanf(curr, "%g", &layer->filters[i]); |
| | | curr = next+1; |
| | | } |
| | | } |
| | | char *weights = option_find_str(options, "weights", 0); |
| | | char *biases = option_find_str(options, "biases", 0); |
| | | parse_data(biases, layer->biases, n); |
| | | parse_data(weights, layer->filters, c*n*size*size); |
| | | parse_data(biases, layer->biases, n); |
| | | #ifdef GPU |
| | | push_convolutional_layer(*layer); |
| | | #endif |
| | | option_unused(options); |
| | | return layer; |
| | | } |
| | | |
| | | connected_layer *parse_connected(list *options, network *net, int count) |
| | | { |
| | | int i; |
| | | int input; |
| | | float learning_rate, momentum, decay; |
| | | int output = option_find_int(options, "output",1); |
| | |
| | | input = get_network_output_size_layer(*net, count-1); |
| | | } |
| | | connected_layer *layer = make_connected_layer(net->batch, input, output, activation,learning_rate,momentum,decay); |
| | | char *data = option_find_str(options, "data", 0); |
| | | if(data){ |
| | | char *curr = data; |
| | | char *next = data; |
| | | for(i = 0; i < output; ++i){ |
| | | while(*++next !='\0' && *next != ','); |
| | | *next = '\0'; |
| | | sscanf(curr, "%g", &layer->biases[i]); |
| | | curr = next+1; |
| | | } |
| | | for(i = 0; i < input*output; ++i){ |
| | | while(*++next !='\0' && *next != ','); |
| | | *next = '\0'; |
| | | sscanf(curr, "%g", &layer->weights[i]); |
| | | curr = next+1; |
| | | } |
| | | } |
| | | char *weights = option_find_str(options, "weights", 0); |
| | | char *biases = option_find_str(options, "biases", 0); |
| | | parse_data(biases, layer->biases, output); |
| | | parse_data(weights, layer->weights, input*output); |
| | | #ifdef GPU |
| | | push_connected_layer(*layer); |
| | | #endif |
| | | option_unused(options); |
| | | return layer; |
| | | } |