From 8bcdee86585f496afe1a8a38d608ea0504a11243 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Tue, 01 Sep 2015 18:22:03 +0000
Subject: [PATCH] Some bug fixes, random stuff
---
src/parser.c | 73 ++++++++++++++++++++++++++++++++++--
1 files changed, 69 insertions(+), 4 deletions(-)
diff --git a/src/parser.c b/src/parser.c
index 9670715..ad324e9 100644
--- a/src/parser.c
+++ b/src/parser.c
@@ -14,6 +14,7 @@
#include "softmax_layer.h"
#include "dropout_layer.h"
#include "detection_layer.h"
+#include "region_layer.h"
#include "avgpool_layer.h"
#include "route_layer.h"
#include "list.h"
@@ -37,6 +38,7 @@
int is_crop(section *s);
int is_cost(section *s);
int is_detection(section *s);
+int is_region(section *s);
int is_route(section *s);
list *read_cfg(char *filename);
@@ -167,11 +169,22 @@
int rescore = option_find_int(options, "rescore", 0);
int joint = option_find_int(options, "joint", 0);
int objectness = option_find_int(options, "objectness", 0);
- int background = option_find_int(options, "background", 0);
+ int background = 0;
detection_layer layer = make_detection_layer(params.batch, params.inputs, classes, coords, joint, rescore, background, objectness);
return layer;
}
+region_layer parse_region(list *options, size_params params)
+{
+ int coords = option_find_int(options, "coords", 1);
+ int classes = option_find_int(options, "classes", 1);
+ int rescore = option_find_int(options, "rescore", 0);
+ int num = option_find_int(options, "num", 1);
+ int side = option_find_int(options, "side", 7);
+ region_layer layer = make_region_layer(params.batch, params.inputs, num, side, classes, coords, rescore);
+ return layer;
+}
+
cost_layer parse_cost(list *options, size_params params)
{
char *type_s = option_find_str(options, "type", "sse");
@@ -236,6 +249,9 @@
{
float probability = option_find_float(options, "probability", .5);
dropout_layer layer = make_dropout_layer(params.batch, params.inputs, probability);
+ layer.out_w = params.w;
+ layer.out_h = params.h;
+ layer.out_c = params.c;
return layer;
}
@@ -295,7 +311,6 @@
net->learning_rate = option_find_float(options, "learning_rate", .001);
net->momentum = option_find_float(options, "momentum", .9);
net->decay = option_find_float(options, "decay", .0001);
- net->seen = option_find_int(options, "seen",0);
int subdivs = option_find_int(options, "subdivisions",1);
net->batch /= subdivs;
net->subdivisions = subdivs;
@@ -328,6 +343,7 @@
n = n->next;
int count = 0;
+ free_section(s);
while(n){
fprintf(stderr, "%d: ", count);
s = (section *)n->val;
@@ -345,6 +361,8 @@
l = parse_cost(options, params);
}else if(is_detection(s)){
l = parse_detection(options, params);
+ }else if(is_region(s)){
+ l = parse_region(options, params);
}else if(is_softmax(s)){
l = parse_softmax(options, params);
}else if(is_normalization(s)){
@@ -397,6 +415,10 @@
{
return (strcmp(s->type, "[detection]")==0);
}
+int is_region(section *s)
+{
+ return (strcmp(s->type, "[region]")==0);
+}
int is_deconvolutional(section *s)
{
return (strcmp(s->type, "[deconv]")==0
@@ -501,7 +523,46 @@
return sections;
}
-void save_weights(network net, char *filename)
+void save_weights_double(network net, char *filename)
+{
+ fprintf(stderr, "Saving doubled 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,j,k;
+ for(i = 0; i < net.n; ++i){
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+#ifdef GPU
+ if(gpu_index >= 0){
+ pull_convolutional_layer(l);
+ }
+#endif
+ float zero = 0;
+ fwrite(l.biases, sizeof(float), l.n, fp);
+ fwrite(l.biases, sizeof(float), l.n, fp);
+
+ for (j = 0; j < l.n; ++j){
+ int index = j*l.c*l.size*l.size;
+ fwrite(l.filters+index, sizeof(float), l.c*l.size*l.size, fp);
+ for (k = 0; k < l.c*l.size*l.size; ++k) fwrite(&zero, sizeof(float), 1, fp);
+ }
+ for (j = 0; j < l.n; ++j){
+ int index = j*l.c*l.size*l.size;
+ for (k = 0; k < l.c*l.size*l.size; ++k) fwrite(&zero, sizeof(float), 1, fp);
+ fwrite(l.filters+index, sizeof(float), l.c*l.size*l.size, fp);
+ }
+ }
+ }
+ fclose(fp);
+}
+
+void save_weights_upto(network net, char *filename, int cutoff)
{
fprintf(stderr, "Saving weights to %s\n", filename);
FILE *fp = fopen(filename, "w");
@@ -513,7 +574,7 @@
fwrite(&net.seen, sizeof(int), 1, fp);
int i;
- for(i = 0; i < net.n; ++i){
+ for(i = 0; i < net.n && i < cutoff; ++i){
layer l = net.layers[i];
if(l.type == CONVOLUTIONAL){
#ifdef GPU
@@ -547,6 +608,10 @@
}
fclose(fp);
}
+void save_weights(network net, char *filename)
+{
+ save_weights_upto(net, filename, net.n);
+}
void load_weights_upto(network *net, char *filename, int cutoff)
{
--
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