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darknet
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cifar and go stuff

This commit is contained in:
Joseph Redmon 2016-03-14 15:08:56 -07:00
parent 3439232730
commit bfa9705606
6 changed files with 282 additions and 13 deletions
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4
Makefile
View File

@ -1,5 +1,5 @@
GPU=0
OPENCV=0
GPU=1
OPENCV=1
DEBUG=0
ARCH= --gpu-architecture=compute_20 --gpu-code=compute_20

126
cfg/cifar.cfg Normal file
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@ -0,0 +1,126 @@
[net]
batch=128
subdivisions=1
height=32
width=32
channels=3
momentum=0.9
decay=0.0005
learning_rate=0.4
policy=poly
power=4
max_batches = 50000
[crop]
crop_width=28
crop_height=28
flip=1
angle=0
saturation = 1
exposure = 1
noadjust=1
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[dropout]
probability=.5
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[dropout]
probability=.5
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[dropout]
probability=.5
[convolutional]
filters=10
size=1
stride=1
pad=1
activation=leaky
[avgpool]
[softmax]
groups=1
[cost]

119
cfg/cifar.test.cfg Normal file
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@ -0,0 +1,119 @@
[net]
batch=128
subdivisions=1
height=32
width=32
channels=3
momentum=0.9
decay=0.0005
learning_rate=0.4
policy=poly
power=4
max_batches = 50000
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[dropout]
probability=.5
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[dropout]
probability=.5
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[dropout]
probability=.5
[convolutional]
filters=10
size=1
stride=1
pad=1
activation=leaky
[avgpool]
[softmax]
groups=1
temperature=3
[cost]

2
src/classifier.c
View File

@ -410,7 +410,7 @@ void validate_classifier_multi(char *datacfg, char *filename, char *weightfile)
char **labels = get_labels(label_list);
list *plist = get_paths(valid_list);
int scales[] = {192, 224, 288, 320, 352};
int scales[] = {160, 192, 224, 288, 320, 352, 384};
int nscales = sizeof(scales)/sizeof(scales[0]);
char **paths = (char **)list_to_array(plist);

6
src/data.c
View File

@ -917,8 +917,8 @@ data load_all_cifar10()
data load_go(char *filename)
{
FILE *fp = fopen(filename, "rb");
matrix X = make_matrix(128, 361);
matrix y = make_matrix(128, 361);
matrix X = make_matrix(3363059, 361);
matrix y = make_matrix(3363059, 361);
int row, col;
if(!fp) file_error(filename);
@ -943,6 +943,8 @@ data load_go(char *filename)
X.vals[count][i] = val;
}
++count;
free(label);
free(board);
}
X = resize_matrix(X, count);
y = resize_matrix(y, count);

38
src/go.c
View File

@ -23,7 +23,11 @@ void train_go(char *cfgfile, char *weightfile)
char *backup_directory = "/home/pjreddie/backup/";
data train = load_go("/home/pjreddie/backup/go.train");
char buff[256];
sprintf(buff, "/home/pjreddie/go.train.%02d", rand()%10);
data train = load_go(buff);
int N = train.X.rows;
int epoch = (*net.seen)/N;
while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
@ -58,6 +62,10 @@ void train_go(char *cfgfile, char *weightfile)
char buff[256];
sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
save_weights(net, buff);
free_data(train);
sprintf(buff, "/home/pjreddie/go.train.%02d", epoch%10);
train = load_go(buff);
}
if(get_current_batch(net)%100 == 0){
char buff[256];
@ -65,7 +73,6 @@ void train_go(char *cfgfile, char *weightfile)
save_weights(net, buff);
}
}
char buff[256];
sprintf(buff, "%s/%s.weights", backup_directory, base);
save_weights(net, buff);
@ -122,9 +129,9 @@ void update_board(float *board)
free(l);
}
void print_board(float *board, int swap)
void print_board(float *board, int swap, int *indexes)
{
int i,j;
int i,j,n;
printf("\n\n");
printf(" ");
for(i = 0; i < 19; ++i){
@ -135,9 +142,21 @@ void print_board(float *board, int swap)
printf("%2d ", 19-j);
for(i = 0; i < 19; ++i){
int index = j*19 + i;
if(indexes){
int found = 0;
for(n = 0; n < 3; ++n){
if(index == indexes[n]){
found = 1;
if(n == 0) printf("\uff11");
else if(n == 1) printf("\uff12");
else if(n == 2) printf("\uff13");
}
}
if(found) continue;
}
if(board[index]*-swap > 0) printf("\u25C9 ");
else if(board[index]*-swap < 0) printf("\u25EF ");
else printf(" ");
else printf("\uFF0b");
}
printf("\n");
}
@ -166,7 +185,7 @@ void test_go(char *filename, char *weightfile)
float *output = network_predict(net, board);
copy_cpu(19*19, output, 1, move, 1);
int i;
#ifdef GPU
#ifdef GPU
image bim = float_to_image(19, 19, 1, board);
for(i = 1; i < 8; ++i){
rotate_image_cw(bim, i);
@ -184,7 +203,7 @@ void test_go(char *filename, char *weightfile)
rotate_image_cw(bim, -i);
}
scal_cpu(19*19, 1./8., move, 1);
#endif
#endif
for(i = 0; i < 19*19; ++i){
if(board[i]) move[i] = 0;
}
@ -192,7 +211,7 @@ void test_go(char *filename, char *weightfile)
int indexes[3];
int row, col;
top_k(move, 19*19, 3, indexes);
print_board(board, color);
print_board(board, color, indexes);
for(i = 0; i < 3; ++i){
int index = indexes[i];
row = index / 19;
@ -217,6 +236,7 @@ void test_go(char *filename, char *weightfile)
if (c == 'p'){
flip_board(board);
color = -color;
free(line);
continue;
}else{
char g;
@ -232,8 +252,10 @@ void test_go(char *filename, char *weightfile)
if (col > 7) col -= 1;
board[row*19 + col] = 1;
}else{
free(line);
continue;
}
free(line);
update_board(board);
flip_board(board);
color = -color;