Fix the backward transpiler bug in ssd_loss API. (#8648)

python/paddle/fluid/layers/detection.py

@@ -496,10 +496,15 @@ def ssd_loss(location,
     # 5.1 Compute confidence loss.
     target_label = __reshape_to_2d(target_label)
     target_label = tensor.cast(x=target_label, dtype='int64')
+
     conf_loss = nn.softmax_with_cross_entropy(confidence, target_label)
     target_conf_weight = __reshape_to_2d(target_conf_weight)
     conf_loss = conf_loss * target_conf_weight
 
+    # the target_label and target_conf_weight do not have gradient.
+    target_label.stop_gradient = True
+    target_conf_weight.stop_gradient = True
+
     # 5.2 Compute regression loss.
     location = __reshape_to_2d(location)
     target_bbox = __reshape_to_2d(target_bbox)
@@ -508,6 +513,10 @@ def ssd_loss(location,
     target_loc_weight = __reshape_to_2d(target_loc_weight)
     loc_loss = loc_loss * target_loc_weight
 
+    # the target_bbox and target_loc_weight do not have gradient.
+    target_bbox.stop_gradient = True
+    target_loc_weight.stop_gradient = True
+
     # 5.3 Compute overall weighted loss.
     loss = conf_loss_weight * conf_loss + loc_loss_weight * loc_loss
     # reshape to [N, Np], N is the batch size and Np is the prior box number.