diff --git a/paddle/fluid/operators/yolov3_loss_op.h b/paddle/fluid/operators/yolov3_loss_op.h
index 46617472618d6ec7cdea5a929de6431199abb288..d0064a81902b81e6ab2605bb7dd1af5f164ec73d 100644
--- a/paddle/fluid/operators/yolov3_loss_op.h
+++ b/paddle/fluid/operators/yolov3_loss_op.h
@@ -152,13 +152,10 @@ static inline void CalcSCEGradWithWeight(const T* loss_grad, Tensor* grad,
   const T* label_data = label.data<T>();
   const T* weight_data = weight.data<T>();
 
-  // LOG(ERROR) << "SCE grad start";
   for (int i = 0; i < n; i++) {
     for (int j = 0; j < stride; j++) {
       grad_data[j] = (1.0 / (1.0 + std::exp(-x_data[j])) - label_data[j]) *
                      weight_data[j] * loss_grad[i];
-      // if (j == 18) LOG(ERROR) << x_data[j] << " " << label_data[j] << " " <<
-      // weight_data[j] << " " << loss_grad[i];
     }
     grad_data += stride;
     x_data += stride;
@@ -258,8 +255,7 @@ static void PreProcessGTBox(const Tensor& gt_box, const Tensor& gt_label,
 
   for (int i = 0; i < n; i++) {
     for (int j = 0; j < b; j++) {
-      if (isZero<T>(gt_box_t(i, j, 0)) && isZero<T>(gt_box_t(i, j, 1)) &&
-          isZero<T>(gt_box_t(i, j, 2)) && isZero<T>(gt_box_t(i, j, 3))) {
+      if (isZero<T>(gt_box_t(i, j, 2)) && isZero<T>(gt_box_t(i, j, 3))) {
         continue;
       }
 
@@ -425,12 +421,6 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
                          loss_weight_conf_notarget, loss_data);
     CalcSCEWithWeight<T>(pred_class, tclass, obj_mask_expand, loss_weight_class,
                          loss_data);
-
-    // loss_data[0] = (loss_weight_xy * (loss_x + loss_y) +
-    //                loss_weight_wh * (loss_w + loss_h) +
-    //                loss_weight_conf_target * loss_conf_target +
-    //                loss_weight_conf_notarget * loss_conf_notarget +
-    //                loss_weight_class * loss_class) / n;
   }
 };
 
@@ -494,8 +484,6 @@ class Yolov3LossGradKernel : public framework::OpKernel<T> {
     auto tweight_t = EigenTensor<T, 4>::From(tweight);
     obj_weight_t = obj_mask_t * tweight_t;
 
-    // LOG(ERROR) << obj_mask_t;
-
     Tensor obj_mask_expand;
     obj_mask_expand.mutable_data<T>({n, an_num, h, w, class_num},
                                     ctx.GetPlace());