Headers are important

src/coco.c

@@ -110,13 +110,12 @@ void train_coco(char *cfgfile, char *weightfile)
             save_weights(net, buff);
             return;
         }
-        if(i%1000==0 || 1){
+        if(i%1000==0){
             char buff[256];
             sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
             save_weights(net, buff);
         }
         free_data(train);
-        return;
     }
     char buff[256];
     sprintf(buff, "%s/%s_final.weights", backup_directory, base);

src/col2im.c

@@ -1,6 +1,6 @@
 #include <stdio.h>
 #include <math.h>
-inline void col2im_add_pixel(float *im, int height, int width, int channels,
+void col2im_add_pixel(float *im, int height, int width, int channels,
                         int row, int col, int channel, int pad, float val)
 {
     row -= pad;

src/im2col.c

@@ -1,6 +1,6 @@
 #include "im2col.h"
 #include <stdio.h>
-inline float im2col_get_pixel(float *im, int height, int width, int channels,
+float im2col_get_pixel(float *im, int height, int width, int channels,
                         int row, int col, int channel, int pad)
 {
     row -= pad;

src/imagenet.c

@@ -47,7 +47,7 @@ void train_imagenet(char *cfgfile, char *weightfile)
         avg_loss = avg_loss*.9 + loss*.1;
         printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), net.seen);
         free_data(train);
-        if((i % 35000) == 0) net.learning_rate *= .1;
+        if((i % 30000) == 0) net.learning_rate *= .1;
         if(i%1000==0){
             char buff[256];
             sprintf(buff, "/home/pjreddie/imagenet_backup/%s_%d.weights",base, i);

src/network.c

@@ -4,6 +4,7 @@
 #include "image.h"
 #include "data.h"
 #include "utils.h"
+#include "blas.h"
 
 #include "crop_layer.h"
 #include "connected_layer.h"

src/parser.c

@@ -236,6 +236,9 @@ dropout_layer parse_dropout(list *options, size_params params)
 {
     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;
 }