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Added sequential subdivisions

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pull/749/head^2
AlexeyAB 6 years ago
parent 31dc6c8680
commit a7e5976c1b
8 changed files with 1257 additions and 5 deletions
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  1. 2
      include/darknet.h
  2. 1162
      src/conv_lstm_layer.c
  3. 33
      src/conv_lstm_layer.h
  4. 10
      src/detector.c
  5. 34
      src/network.c
  6. 3
      src/network.h
  7. 6
      src/network_kernels.cu
  8. 12
      src/parser.c

2
include/darknet.h
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@ -559,6 +559,7 @@ typedef struct network {
int time_steps;
int step;
int max_batches;
float *seq_scales;
float *scales;
int *steps;
int num_steps;
@ -591,6 +592,7 @@ typedef struct network {
int track;
int augment_speed;
int sequential_subdivisions;
int init_sequential_subdivisions;
int current_subdivision;
int try_fix_nan;

1162
src/conv_lstm_layer.c
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File diff suppressed because it is too large Load Diff

33
src/conv_lstm_layer.h
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@ -0,0 +1,33 @@
#ifndef CONV_LSTM_LAYER_H
#define CONV_LSTM_LAYER_H
#include "activations.h"
#include "layer.h"
#include "network.h"
#define USET
#ifdef __cplusplus
extern "C" {
#endif
layer make_conv_lstm_layer(int batch, int h, int w, int c, int output_filters, int steps, int size, int stride, int pad, ACTIVATION activation, int batch_normalize, int peephole, int xnor);
void resize_conv_lstm_layer(layer *l, int w, int h);
void free_state_conv_lstm(layer l);
void randomize_state_conv_lstm(layer l);
void remember_state_conv_lstm(layer l);
void restore_state_conv_lstm(layer l);
void forward_conv_lstm_layer(layer l, network_state state);
void backward_conv_lstm_layer(layer l, network_state state);
void update_conv_lstm_layer(layer l, int batch, float learning_rate, float momentum, float decay);
#ifdef GPU
void forward_conv_lstm_layer_gpu(layer l, network_state state);
void backward_conv_lstm_layer_gpu(layer l, network_state state);
void update_conv_lstm_layer_gpu(layer l, int batch, float learning_rate, float momentum, float decay);
#endif
#ifdef __cplusplus
}
#endif
#endif // CONV_LSTM_LAYER_H

10
src/detector.c
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@ -191,6 +191,11 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
time = what_time_is_it_now();
pthread_join(load_thread, 0);
train = buffer;
if (net.track) {
net.sequential_subdivisions = get_current_seq_subdivisions(net);
args.threads = net.sequential_subdivisions * ngpus;
printf(" sequential_subdivisions = %d \n", net.sequential_subdivisions);
}
load_thread = load_data(args);
/*
@ -662,7 +667,7 @@ float validate_detector_map(char *datacfg, char *cfgfile, char *weightfile, floa
char *train_images = option_find_str(options, "train", "data/train.txt");
valid_images = option_find_str(options, "valid", train_images);
net = *existing_net;
remember_network_recurrent_state(*existing_net);
//remember_network_recurrent_state(*existing_net);
free_network_recurrent_state(*existing_net);
}
else {
@ -1073,7 +1078,8 @@ float validate_detector_map(char *datacfg, char *cfgfile, char *weightfile, floa
if (existing_net) {
//set_batch_network(&net, initial_batch);
//free_network_recurrent_state(*existing_net);
restore_network_recurrent_state(*existing_net);
//restore_network_recurrent_state(*existing_net);
randomize_network_recurrent_state(*existing_net);
}
else {
free_network(net);

34
src/network.c
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@ -91,6 +91,30 @@ void reset_rnn(network *net)
reset_network_state(net, 0);
}
float get_current_seq_subdivisions(network net)
{
int sequence_subdivisions = net.init_sequential_subdivisions;
if (net.policy)
{
int batch_num = get_current_batch(net);
int i;
for (i = 0; i < net.num_steps; ++i) {
if (net.steps[i] > batch_num) break;
sequence_subdivisions *= net.seq_scales[i];
}
}
return sequence_subdivisions;
}
int get_sequence_value(network net)
{
int sequence = 1;
if (net.sequential_subdivisions != 0) sequence = net.subdivisions / net.sequential_subdivisions;
if (sequence < 1) sequence = 1;
return sequence;
}
float get_current_rate(network net)
{
int batch_num = get_current_batch(net);
@ -928,6 +952,7 @@ void free_network(network net)
}
free(net.layers);
free(net.seq_scales);
free(net.scales);
free(net.steps);
free(net.seen);
@ -1124,6 +1149,15 @@ void free_network_recurrent_state(network net)
}
}
void randomize_network_recurrent_state(network net)
{
int k;
for (k = 0; k < net.n; ++k) {
if (net.layers[k].type == CONV_LSTM) randomize_state_conv_lstm(net.layers[k]);
if (net.layers[k].type == CRNN) free_state_crnn(net.layers[k]);
}
}
void remember_network_recurrent_state(network net)
{

3
src/network.h
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@ -104,6 +104,8 @@ void backward_network_gpu(network net, network_state state);
void update_network_gpu(network net);
#endif
float get_current_seq_subdivisions(network net);
int get_sequence_value(network net);
float get_current_rate(network net);
int get_current_batch(network net);
void free_network(network net);
@ -164,6 +166,7 @@ int get_network_background(network net);
network combine_train_valid_networks(network net_train, network net_map);
void copy_weights_net(network net_train, network *net_map);
void free_network_recurrent_state(network net);
void randomize_network_recurrent_state(network net);
void remember_network_recurrent_state(network net);
void restore_network_recurrent_state(network net);

6
src/network_kernels.cu
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@ -126,7 +126,7 @@ void update_network_gpu(network net)
{
cuda_set_device(net.gpu_index);
int i;
int update_batch = net.batch*net.subdivisions;
int update_batch = net.batch*net.subdivisions * get_sequence_value(net);
float rate = get_current_rate(net);
for(i = 0; i < net.n; ++i){
layer l = net.layers[i];
@ -200,7 +200,9 @@ float train_network_datum_gpu(network net, float *x, float *y)
*net.seen += net.batch;
forward_backward_network_gpu(net, x, y);
float error = get_network_cost(net);
if (((*net.seen) / net.batch) % net.subdivisions == 0) update_network_gpu(net);
//if (((*net.seen) / net.batch) % net.subdivisions == 0) update_network_gpu(net);
const int sequence = get_sequence_value(net);
if (((*net.seen) / net.batch) % (net.subdivisions*sequence) == 0) update_network_gpu(net);
return error;
}

12
src/parser.c
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@ -672,7 +672,7 @@ void parse_net_options(list *options, network *net)
net->time_steps = option_find_int_quiet(options, "time_steps",1);
net->track = option_find_int_quiet(options, "track", 0);
net->augment_speed = option_find_int_quiet(options, "augment_speed", 2);
net->sequential_subdivisions = option_find_int_quiet(options, "sequential_subdivisions", 0);
net->init_sequential_subdivisions = net->sequential_subdivisions = option_find_int_quiet(options, "sequential_subdivisions", subdivs);
net->try_fix_nan = option_find_int_quiet(options, "try_fix_nan", 0);
net->batch /= subdivs;
net->batch *= net->time_steps;
@ -721,6 +721,7 @@ void parse_net_options(list *options, network *net)
} else if (net->policy == STEPS){
char *l = option_find(options, "steps");
char *p = option_find(options, "scales");
char *s = option_find(options, "seq_scales");
if(!l || !p) error("STEPS policy must have steps and scales in cfg file");
int len = strlen(l);
@ -731,6 +732,14 @@ void parse_net_options(list *options, network *net)
}
int* steps = (int*)calloc(n, sizeof(int));
float* scales = (float*)calloc(n, sizeof(float));
float* seq_scales = (float*)calloc(n, sizeof(float));
for (i = 0; i < n; ++i) {
if (s) {
seq_scales[i] = atof(s);
s = strchr(s, ',') + 1;
} else
seq_scales[i] = 1;
}
for(i = 0; i < n; ++i){
int step = atoi(l);
float scale = atof(p);
@ -741,6 +750,7 @@ void parse_net_options(list *options, network *net)
}
net->scales = scales;
net->steps = steps;
net->seq_scales = seq_scales;
net->num_steps = n;
} else if (net->policy == EXP){
net->gamma = option_find_float(options, "gamma", 1);

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