| | |
| | | { |
| | | char *type_s = option_find_str(options, "type", "sse"); |
| | | COST_TYPE type = get_cost_type(type_s); |
| | | cost_layer layer = make_cost_layer(params.batch, params.inputs, type); |
| | | float scale = option_find_float_quiet(options, "scale",1); |
| | | cost_layer layer = make_cost_layer(params.batch, params.inputs, type, scale); |
| | | return layer; |
| | | } |
| | | |
| | |
| | | return layer; |
| | | } |
| | | |
| | | learning_rate_policy get_policy(char *s) |
| | | { |
| | | if (strcmp(s, "poly")==0) return POLY; |
| | | if (strcmp(s, "constant")==0) return CONSTANT; |
| | | if (strcmp(s, "step")==0) return STEP; |
| | | if (strcmp(s, "exp")==0) return EXP; |
| | | fprintf(stderr, "Couldn't find policy %s, going with constant\n", s); |
| | | return CONSTANT; |
| | | } |
| | | |
| | | void parse_net_options(list *options, network *net) |
| | | { |
| | | net->batch = option_find_int(options, "batch",1); |
| | |
| | | net->w = option_find_int_quiet(options, "width",0); |
| | | net->c = option_find_int_quiet(options, "channels",0); |
| | | net->inputs = option_find_int_quiet(options, "inputs", net->h * net->w * net->c); |
| | | |
| | | if(!net->inputs && !(net->h && net->w && net->c)) error("No input parameters supplied"); |
| | | |
| | | char *policy_s = option_find_str(options, "policy", "constant"); |
| | | net->policy = get_policy(policy_s); |
| | | if(net->policy == STEP){ |
| | | net->step = option_find_int(options, "step", 1); |
| | | net->gamma = option_find_float(options, "gamma", 1); |
| | | } else if (net->policy == EXP){ |
| | | net->gamma = option_find_float(options, "gamma", 1); |
| | | } else if (net->policy == POLY){ |
| | | net->power = option_find_float(options, "power", 1); |
| | | } |
| | | net->max_batches = option_find_int(options, "max_batches", 0); |
| | | } |
| | | |
| | | network parse_network_cfg(char *filename) |
| | |
| | | fwrite(&net.learning_rate, sizeof(float), 1, fp); |
| | | fwrite(&net.momentum, sizeof(float), 1, fp); |
| | | fwrite(&net.decay, sizeof(float), 1, fp); |
| | | fwrite(&net.seen, sizeof(int), 1, fp); |
| | | fwrite(net.seen, sizeof(int), 1, fp); |
| | | |
| | | int i,j,k; |
| | | for(i = 0; i < net.n; ++i){ |
| | |
| | | fwrite(&net.learning_rate, sizeof(float), 1, fp); |
| | | fwrite(&net.momentum, sizeof(float), 1, fp); |
| | | fwrite(&net.decay, sizeof(float), 1, fp); |
| | | fwrite(&net.seen, sizeof(int), 1, fp); |
| | | fwrite(net.seen, sizeof(int), 1, fp); |
| | | |
| | | int i; |
| | | for(i = 0; i < net.n && i < cutoff; ++i){ |
| | |
| | | FILE *fp = fopen(filename, "r"); |
| | | if(!fp) file_error(filename); |
| | | |
| | | fread(&net->learning_rate, sizeof(float), 1, fp); |
| | | fread(&net->momentum, sizeof(float), 1, fp); |
| | | fread(&net->decay, sizeof(float), 1, fp); |
| | | fread(&net->seen, sizeof(int), 1, fp); |
| | | float garbage; |
| | | fread(&garbage, sizeof(float), 1, fp); |
| | | fread(&garbage, sizeof(float), 1, fp); |
| | | fread(&garbage, sizeof(float), 1, fp); |
| | | fread(net->seen, sizeof(int), 1, fp); |
| | | |
| | | int i; |
| | | for(i = 0; i < net->n && i < cutoff; ++i){ |