diff --git a/ppdet/modeling/heads/mask_head.py b/ppdet/modeling/heads/mask_head.py
index 5b9de3760fb935ae088b083829e27d1ff53a4f7f..604847a2d07224314b2eba700eefa00729b4f95f 100644
--- a/ppdet/modeling/heads/mask_head.py
+++ b/ppdet/modeling/heads/mask_head.py
@@ -209,7 +209,7 @@ class MaskHead(nn.Layer):
         scale_factor (Tensor): The scale factor from origin size to input size
         """
         if not self.export_onnx and rois.shape[0] == 0:
-            mask_out = paddle.full([1, 1, 1, 1], -1)
+            mask_out = paddle.full([1, 1, 1], -1)
         else:
             bbox = [rois[:, 2:]]
             labels = rois[:, 0].cast('int32')
diff --git a/ppdet/modeling/ops.py b/ppdet/modeling/ops.py
index 7d08a19799df6ea3a16a87487bad6393a47c0061..52a4f33962a49c45a3597c372842d965a0023166 100644
--- a/ppdet/modeling/ops.py
+++ b/ppdet/modeling/ops.py
@@ -482,6 +482,8 @@ def collect_fpn_proposals(multi_rois,
             rois_num = helper.create_variable_for_type_inference(dtype='int32')
             rois_num.stop_gradient = True
             outputs['RoisNum'] = rois_num
+        else:
+            rois_num = None
         helper.append_op(
             type='collect_fpn_proposals',
             inputs=inputs,
@@ -602,6 +604,8 @@ def distribute_fpn_proposals(fpn_rois,
                 for i in range(num_lvl)
             ]
             outputs['MultiLevelRoIsNum'] = rois_num_per_level
+        else:
+            rois_num_per_level = None
 
         helper.append_op(
             type='distribute_fpn_proposals',