From 2f62fe33c913cd9484fe7f2486889d12292c66e0 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Sat, 07 Feb 2015 02:53:53 +0000
Subject: [PATCH] saving weight files as binaries, hell yeah
---
src/utils.h | 2
Makefile | 6
src/convolutional_layer.c | 3
src/connected_layer.c | 2
src/parser.c | 80 +++++++++++++++++++
src/parser.h | 2
src/server.c | 22 -----
src/darknet.c | 55 ++++++++++---
src/utils.c | 22 +++++
9 files changed, 147 insertions(+), 47 deletions(-)
diff --git a/Makefile b/Makefile
index f685bb4..879ff8e 100644
--- a/Makefile
+++ b/Makefile
@@ -12,13 +12,13 @@
LDFLAGS=`pkg-config --libs opencv` -lm -pthread
COMMON=`pkg-config --cflags opencv` -I/usr/local/cuda/include/
CFLAGS=-Wall -Wfatal-errors
-CFLAGS+=$(OPTS)
ifeq ($(DEBUG), 1)
-COMMON+=-O0 -g
-CFLAGS+=-O0 -g
+OPTS=-O0 -g
endif
+CFLAGS+=$(OPTS)
+
ifeq ($(GPU), 1)
COMMON+=-DGPU
CFLAGS+=-DGPU
diff --git a/src/connected_layer.c b/src/connected_layer.c
index 1a5fc2b..642570c 100644
--- a/src/connected_layer.c
+++ b/src/connected_layer.c
@@ -36,14 +36,12 @@
float scale = 1./sqrt(inputs);
- //scale = .01;
for(i = 0; i < inputs*outputs; ++i){
layer->weights[i] = scale*rand_normal();
}
for(i = 0; i < outputs; ++i){
layer->biases[i] = scale;
- // layer->biases[i] = 1;
}
#ifdef GPU
diff --git a/src/convolutional_layer.c b/src/convolutional_layer.c
index 62118e4..6a172aa 100644
--- a/src/convolutional_layer.c
+++ b/src/convolutional_layer.c
@@ -66,12 +66,9 @@
layer->biases = calloc(n, sizeof(float));
layer->bias_updates = calloc(n, sizeof(float));
float scale = 1./sqrt(size*size*c);
- //scale = .01;
for(i = 0; i < c*n*size*size; ++i) layer->filters[i] = scale*rand_normal();
for(i = 0; i < n; ++i){
- //layer->biases[i] = rand_normal()*scale + scale;
layer->biases[i] = scale;
- //layer->biases[i] = 1;
}
int out_h = convolutional_out_height(*layer);
int out_w = convolutional_out_width(*layer);
diff --git a/src/darknet.c b/src/darknet.c
index cc3fc07..ab4c7ad 100644
--- a/src/darknet.c
+++ b/src/darknet.c
@@ -222,13 +222,16 @@
return c;
}
-void train_imagenet(char *cfgfile)
+void train_imagenet(char *cfgfile, char *weightfile)
{
float avg_loss = -1;
srand(time(0));
char *base = basename(cfgfile);
printf("%s\n", base);
network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
//test_learn_bias(*(convolutional_layer *)net.layers[1]);
//set_learning_network(&net, net.learning_rate, 0, net.decay);
printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
@@ -259,16 +262,19 @@
free_data(train);
if(i%100==0){
char buff[256];
- sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.cfg",base, i);
- save_network(net, buff);
+ sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);
+ save_weights(net, buff);
}
}
}
-void validate_imagenet(char *filename)
+void validate_imagenet(char *filename, char *weightfile)
{
int i = 0;
network net = parse_network_cfg(filename);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
srand(time(0));
char **labels = get_labels("/home/pjreddie/data/imagenet/cls.val.labels.list");
@@ -370,14 +376,14 @@
float *X = im.data;
network net = parse_network_cfg(cfgfile);
set_batch_network(&net, 1);
- float *predictions = network_predict(net, X);
+ network_predict(net, X);
image crop = get_network_image_layer(net, 0);
- //show_image(crop, "cropped");
- // print_image(crop);
- //show_image(im, "orig");
+ show_image(crop, "cropped");
+ print_image(crop);
+ show_image(im, "orig");
float * inter = get_network_output(net);
pm(1000, 1, inter);
- //cvWaitKey(0);
+ cvWaitKey(0);
}
void test_imagenet(char *cfgfile)
@@ -586,7 +592,6 @@
float *in = calloc(size, sizeof(float));
int i;
for(i = 0; i < size; ++i) in[i] = rand_normal();
- float *in_gpu = cuda_make_array(in, size);
convolutional_layer layer = *(convolutional_layer *)net.layers[0];
int out_size = convolutional_out_height(layer)*convolutional_out_width(layer)*layer.batch;
cuda_compare(layer.output_gpu, layer.output, out_size, "nothing");
@@ -703,14 +708,18 @@
{
int i;
for(i = index; i < argc-1; ++i) argv[i] = argv[i+1];
+ argv[i] = 0;
}
int find_arg(int argc, char* argv[], char *arg)
{
int i;
- for(i = 0; i < argc; ++i) if(0==strcmp(argv[i], arg)) {
- del_arg(argc, argv, i);
- return 1;
+ for(i = 0; i < argc; ++i) {
+ if(!argv[i]) continue;
+ if(0==strcmp(argv[i], arg)) {
+ del_arg(argc, argv, i);
+ return 1;
+ }
}
return 0;
}
@@ -719,6 +728,7 @@
{
int i;
for(i = 0; i < argc-1; ++i){
+ if(!argv[i]) continue;
if(0==strcmp(argv[i], arg)){
def = atoi(argv[i+1]);
del_arg(argc, argv, i);
@@ -729,6 +739,20 @@
return def;
}
+void scale_rate(char *filename, float scale)
+{
+ // Ready for some weird shit??
+ FILE *fp = fopen(filename, "r+b");
+ if(!fp) file_error(filename);
+ float rate = 0;
+ fread(&rate, sizeof(float), 1, fp);
+ printf("Scaling learning rate from %f to %f\n", rate, rate*scale);
+ rate = rate*scale;
+ fseek(fp, 0, SEEK_SET);
+ fwrite(&rate, sizeof(float), 1, fp);
+ fclose(fp);
+}
+
int main(int argc, char **argv)
{
//test_convolutional_layer();
@@ -765,12 +789,12 @@
else if(0==strcmp(argv[1], "ctrain")) train_cifar10(argv[2]);
else if(0==strcmp(argv[1], "nist")) train_nist(argv[2]);
else if(0==strcmp(argv[1], "ctest")) test_cifar10(argv[2]);
- else if(0==strcmp(argv[1], "train")) train_imagenet(argv[2]);
+ else if(0==strcmp(argv[1], "train")) train_imagenet(argv[2], (argc > 3)? argv[3] : 0);
//else if(0==strcmp(argv[1], "client")) train_imagenet_distributed(argv[2]);
else if(0==strcmp(argv[1], "detect")) test_detection(argv[2]);
else if(0==strcmp(argv[1], "init")) test_init(argv[2]);
else if(0==strcmp(argv[1], "visualize")) test_visualize(argv[2]);
- else if(0==strcmp(argv[1], "valid")) validate_imagenet(argv[2]);
+ else if(0==strcmp(argv[1], "valid")) validate_imagenet(argv[2], (argc > 3)? argv[3] : 0);
else if(0==strcmp(argv[1], "testnist")) test_nist(argv[2]);
else if(0==strcmp(argv[1], "validetect")) validate_detection_net(argv[2]);
else if(argc < 4){
@@ -778,6 +802,7 @@
return 0;
}
else if(0==strcmp(argv[1], "compare")) compare_nist(argv[2], argv[3]);
+ else if(0==strcmp(argv[1], "scale")) scale_rate(argv[2], atof(argv[3]));
fprintf(stderr, "Success!\n");
return 0;
}
diff --git a/src/parser.c b/src/parser.c
index a00feec..6a107cc 100644
--- a/src/parser.c
+++ b/src/parser.c
@@ -103,7 +103,7 @@
parse_data(weights, layer->filters, c*n*size*size);
parse_data(biases, layer->biases, n);
#ifdef GPU
- push_convolutional_layer(*layer);
+ if(weights || biases) push_convolutional_layer(*layer);
#endif
option_unused(options);
return layer;
@@ -137,7 +137,7 @@
parse_data(biases, layer->biases, output);
parse_data(weights, layer->weights, input*output);
#ifdef GPU
- push_connected_layer(*layer);
+ if(weights || biases) push_connected_layer(*layer);
#endif
option_unused(options);
return layer;
@@ -597,6 +597,82 @@
fprintf(fp, "\n");
}
+void save_weights(network net, char *filename)
+{
+ printf("Saving weights to %s\n", filename);
+ FILE *fp = fopen(filename, "w");
+ if(!fp) file_error(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);
+
+ int i;
+ for(i = 0; i < net.n; ++i){
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *) net.layers[i];
+ #ifdef GPU
+ if(gpu_index >= 0){
+ pull_convolutional_layer(layer);
+ }
+ #endif
+ int num = layer.n*layer.c*layer.size*layer.size;
+ fwrite(layer.biases, sizeof(float), layer.n, fp);
+ fwrite(layer.filters, sizeof(float), num, fp);
+ }
+ if(net.types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *) net.layers[i];
+ #ifdef GPU
+ if(gpu_index >= 0){
+ pull_connected_layer(layer);
+ }
+ #endif
+ fwrite(layer.biases, sizeof(float), layer.outputs, fp);
+ fwrite(layer.weights, sizeof(float), layer.outputs*layer.inputs, fp);
+ }
+ }
+ fclose(fp);
+}
+
+void load_weights(network *net, char *filename)
+{
+ printf("Loading weights from %s\n", filename);
+ 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);
+ set_learning_network(net, net->learning_rate, net->momentum, net->decay);
+
+ int i;
+ for(i = 0; i < net->n; ++i){
+ if(net->types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *) net->layers[i];
+ int num = layer.n*layer.c*layer.size*layer.size;
+ fread(layer.biases, sizeof(float), layer.n, fp);
+ fread(layer.filters, sizeof(float), num, fp);
+ #ifdef GPU
+ if(gpu_index >= 0){
+ push_convolutional_layer(layer);
+ }
+ #endif
+ }
+ if(net->types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *) net->layers[i];
+ fread(layer.biases, sizeof(float), layer.outputs, fp);
+ fread(layer.weights, sizeof(float), layer.outputs*layer.inputs, fp);
+ #ifdef GPU
+ if(gpu_index >= 0){
+ push_connected_layer(layer);
+ }
+ #endif
+ }
+ }
+ fclose(fp);
+}
void save_network(network net, char *filename)
{
diff --git a/src/parser.h b/src/parser.h
index 891e658..2e8190e 100644
--- a/src/parser.h
+++ b/src/parser.h
@@ -4,5 +4,7 @@
network parse_network_cfg(char *filename);
void save_network(network net, char *filename);
+void save_weights(network net, char *filename);
+void load_weights(network *net, char *filename);
#endif
diff --git a/src/server.c b/src/server.c
index 788ac87..6e5105e 100644
--- a/src/server.c
+++ b/src/server.c
@@ -50,28 +50,6 @@
network net;
} connection_info;
-void read_all(int fd, char *buffer, size_t bytes)
-{
- //printf("Want %d\n", bytes);
- size_t n = 0;
- while(n < bytes){
- int next = read(fd, buffer + n, bytes-n);
- if(next <= 0) error("read failed");
- n += next;
- }
-}
-
-void write_all(int fd, char *buffer, size_t bytes)
-{
- //printf("Writ %d\n", bytes);
- size_t n = 0;
- while(n < bytes){
- int next = write(fd, buffer + n, bytes-n);
- if(next <= 0) error("write failed");
- n += next;
- }
-}
-
void read_and_add_into(int fd, float *a, int n)
{
float *buff = calloc(n, sizeof(float));
diff --git a/src/utils.c b/src/utils.c
index 8261682..bf02ff3 100644
--- a/src/utils.c
+++ b/src/utils.c
@@ -2,6 +2,7 @@
#include <stdlib.h>
#include <string.h>
#include <math.h>
+#include <unistd.h>
#include <float.h>
#include <limits.h>
@@ -148,6 +149,27 @@
return line;
}
+void read_all(int fd, char *buffer, size_t bytes)
+{
+ size_t n = 0;
+ while(n < bytes){
+ int next = read(fd, buffer + n, bytes-n);
+ if(next <= 0) error("read failed");
+ n += next;
+ }
+}
+
+void write_all(int fd, char *buffer, size_t bytes)
+{
+ size_t n = 0;
+ while(n < bytes){
+ size_t next = write(fd, buffer + n, bytes-n);
+ if(next <= 0) error("write failed");
+ n += next;
+ }
+}
+
+
char *copy_string(char *s)
{
char *copy = malloc(strlen(s)+1);
diff --git a/src/utils.h b/src/utils.h
index daf3a41..e233da8 100644
--- a/src/utils.h
+++ b/src/utils.h
@@ -4,6 +4,8 @@
#include <time.h>
#include "list.h"
+void read_all(int fd, char *buffer, size_t bytes);
+void write_all(int fd, char *buffer, size_t bytes);
char *find_replace(char *str, char *orig, char *rep);
void error(const char *s);
void malloc_error();
--
Gitblit v1.10.0