yolov4.cfg is fixed for stable training without Nan

build/darknet/x64/cfg/yolov4.cfg

@@ -14,7 +14,7 @@ saturation = 1.5
 exposure = 1.5
 hue=.1
 
-learning_rate=0.00261
+learning_rate=0.0013
 burn_in=1000
 max_batches = 500500
 policy=steps
@@ -977,6 +977,7 @@ iou_normalizer=0.07
 iou_loss=ciou
 nms_kind=greedynms
 beta_nms=0.6
+max_delta=5
 
 
 [route]
@@ -1064,6 +1065,7 @@ iou_normalizer=0.07
 iou_loss=ciou
 nms_kind=greedynms
 beta_nms=0.6
+max_delta=5
 
 
 [route]
@@ -1152,4 +1154,5 @@ iou_normalizer=0.07
 iou_loss=ciou
 nms_kind=greedynms
 beta_nms=0.6
+max_delta=5
 

cfg/yolov4.cfg

@@ -14,7 +14,7 @@ saturation = 1.5
 exposure = 1.5
 hue=.1
 
-learning_rate=0.00261
+learning_rate=0.0013
 burn_in=1000
 max_batches = 500500
 policy=steps
@@ -977,6 +977,7 @@ iou_normalizer=0.07
 iou_loss=ciou
 nms_kind=greedynms
 beta_nms=0.6
+max_delta=5
 
 
 [route]
@@ -1064,6 +1065,7 @@ iou_normalizer=0.07
 iou_loss=ciou
 nms_kind=greedynms
 beta_nms=0.6
+max_delta=5
 
 
 [route]
@@ -1152,4 +1154,5 @@ iou_normalizer=0.07
 iou_loss=ciou
 nms_kind=greedynms
 beta_nms=0.6
+max_delta=5
 

src/layer.c

@@ -188,7 +188,7 @@ void free_layer_custom(layer l, int keep_cudnn_desc)
     if (l.scale_updates_gpu)       cuda_free(l.scale_updates_gpu), l.scale_updates_gpu = NULL;
     if (l.input_antialiasing_gpu)  cuda_free(l.input_antialiasing_gpu), l.input_antialiasing_gpu = NULL;
     if (l.optimized_memory < 2) {
-        if (l.x_gpu)                   cuda_free(l.x_gpu);  l.x_gpu = NULL;
+        if (l.x_gpu)                   cuda_free(l.x_gpu),  l.x_gpu = NULL;
         if (l.output_gpu)              cuda_free(l.output_gpu), l.output_gpu = NULL;
         if (l.output_avg_gpu)          cuda_free(l.output_avg_gpu), l.output_avg_gpu = NULL;
         if (l.activation_input_gpu)    cuda_free(l.activation_input_gpu), l.activation_input_gpu = NULL;