darknet/src/go.c

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C
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2016-03-14 09:18:42 +03:00
#include "network.h"
#include "utils.h"
#include "parser.h"
#include "option_list.h"
#include "blas.h"
#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
#endif
void train_go(char *cfgfile, char *weightfile)
{
data_seed = time(0);
srand(time(0));
float avg_loss = -1;
char *base = basecfg(cfgfile);
printf("%s\n", base);
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
char *backup_directory = "/home/pjreddie/backup/";
data train = load_go("/home/pjreddie/backup/go.train");
int N = train.X.rows;
int epoch = (*net.seen)/N;
while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
clock_t time=clock();
data batch = get_random_data(train, net.batch);
int i;
for(i = 0; i < batch.X.rows; ++i){
int flip = rand()%2;
int rotate = rand()%4;
image in = float_to_image(19, 19, 1, batch.X.vals[i]);
image out = float_to_image(19, 19, 1, batch.y.vals[i]);
//show_image_normalized(in, "in");
//show_image_normalized(out, "out");
if(flip){
flip_image(in);
flip_image(out);
}
rotate_image_cw(in, rotate);
rotate_image_cw(out, rotate);
//show_image_normalized(in, "in2");
//show_image_normalized(out, "out2");
//cvWaitKey(0);
}
float loss = train_network(net, batch);
free_data(batch);
if(avg_loss == -1) avg_loss = loss;
avg_loss = avg_loss*.95 + loss*.05;
printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
if(*net.seen/N > epoch){
epoch = *net.seen/N;
char buff[256];
sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
save_weights(net, buff);
}
if(get_current_batch(net)%100 == 0){
char buff[256];
sprintf(buff, "%s/%s.backup",backup_directory,base);
save_weights(net, buff);
}
}
char buff[256];
sprintf(buff, "%s/%s.weights", backup_directory, base);
save_weights(net, buff);
free_network(net);
free(base);
free_data(train);
}
void propagate_liberty(float *board, int *lib, int *visited, int row, int col, int num, int side)
{
if (!num) return;
if (row < 0 || row > 18 || col < 0 || col > 18) return;
int index = row*19 + col;
if (board[index] != side) return;
if (visited[index]) return;
visited[index] = 1;
lib[index] += num;
propagate_liberty(board, lib, visited, row+1, col, num, side);
propagate_liberty(board, lib, visited, row-1, col, num, side);
propagate_liberty(board, lib, visited, row, col+1, num, side);
propagate_liberty(board, lib, visited, row, col-1, num, side);
}
int *calculate_liberties(float *board)
{
int *lib = calloc(19*19, sizeof(int));
int visited[361];
int i, j;
for(j = 0; j < 19; ++j){
for(i = 0; i < 19; ++i){
memset(visited, 0, 19*19*sizeof(int));
int index = j*19 + i;
if(board[index]){
int side = board[index];
int num = 0;
if (i > 0 && board[j*19 + i - 1] == 0) ++num;
if (i < 18 && board[j*19 + i + 1] == 0) ++num;
if (j > 0 && board[j*19 + i - 19] == 0) ++num;
if (j < 18 && board[j*19 + i + 19] == 0) ++num;
propagate_liberty(board, lib, visited, j, i, num, side);
}
}
}
return lib;
}
void update_board(float *board)
{
int i;
int *l = calculate_liberties(board);
for(i = 0; i < 19*19; ++i){
if (board[i] && !l[i]) board[i] = 0;
}
free(l);
}
void print_board(float *board)
{
int i,j;
printf("\n\n");
printf(" ");
for(i = 0; i < 19; ++i){
printf("%c ", 'A' + i + 1*(i > 7));
}
printf("\n");
for(j = 0; j < 19; ++j){
printf("%2d ", 19-j);
for(i = 0; i < 19; ++i){
int index = j*19 + i;
if(board[index] > 0) printf("\u25C9 ");
else if(board[index] < 0) printf("\u25EF ");
else printf(" ");
}
printf("\n");
}
}
void flip_board(float *board)
{
int i;
for(i = 0; i < 19*19; ++i){
board[i] = -board[i];
}
}
void test_go(char *filename, char *weightfile)
{
network net = parse_network_cfg(filename);
if(weightfile){
load_weights(&net, weightfile);
}
srand(time(0));
set_batch_network(&net, 1);
float *board = calloc(19*19, sizeof(float));
float *move = calloc(19*19, sizeof(float));
image bim = float_to_image(19, 19, 1, board);
while(1){
float *output = network_predict(net, board);
copy_cpu(19*19, output, 1, move, 1);
int i;
for(i = 1; i < 8; ++i){
rotate_image_cw(bim, i);
if(i >= 4) flip_image(bim);
float *output = network_predict(net, board);
image oim = float_to_image(19, 19, 1, output);
if(i >= 4) flip_image(oim);
rotate_image_cw(oim, -i);
axpy_cpu(19*19, 1, output, 1, move, 1);
if(i >= 4) flip_image(bim);
rotate_image_cw(bim, -i);
}
scal_cpu(19*19, 1./8., move, 1);
for(i = 0; i < 19*19; ++i){
if(board[i]) move[i] = 0;
}
int indexes[3];
int row, col;
top_k(move, 19*19, 3, indexes);
print_board(board);
for(i = 0; i < 3; ++i){
int index = indexes[i];
row = index / 19;
col = index % 19;
printf("Suggested: %c %d, %.2f%%\n", col + 'A' + 1*(col > 7), 19 - row, move[index]*100);
}
int index = indexes[0];
row = index / 19;
col = index % 19;
printf("\u25C9 Enter move: ");
char c;
char *line = fgetl(stdin);
int num = sscanf(line, "%c %d", &c, &row);
if (c < 'A' || c > 'T'){
if (c == 'p'){
board[row*19 + col] = 1;
}else{
char g;
num = sscanf(line, "%c %c %d", &g, &c, &row);
row = 19 - row;
col = c - 'A';
if (col > 7) col -= 1;
board[row*19 + col] = 0;
}
} else {
row = 19 - row;
col = c - 'A';
if (col > 7) col -= 1;
if(num == 2) board[row*19 + col] = 1;
}
update_board(board);
flip_board(board);
}
}
void run_go(int argc, char **argv)
{
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
return;
}
char *cfg = argv[3];
char *weights = (argc > 4) ? argv[4] : 0;
if(0==strcmp(argv[2], "train")) train_go(cfg, weights);
else if(0==strcmp(argv[2], "test")) test_go(cfg, weights);
}