diff --git a/x2paddle/op_mapper/paddle2onnx/opset11/opset.py b/x2paddle/op_mapper/paddle2onnx/opset11/opset.py
index 9e40c85b1e6a18d1b9f51649aa16b3259d9ea390..385b377b6577b035b5720a49317f4379300589de 100644
--- a/x2paddle/op_mapper/paddle2onnx/opset11/opset.py
+++ b/x2paddle/op_mapper/paddle2onnx/opset11/opset.py
@@ -41,6 +41,27 @@ class OpSet11(OpSet10):
             outputs=op.output('Out'), )
         return [min_node, max_node, node]
 
+    def pad2d(self, op, block):
+        x_shape = block.var(op.input('X')[0]).shape
+        paddings = op.attr('paddings')
+        onnx_pads = []
+        #TODO support pads is Variable
+        if op.attr('data_format') == 'NCHW':
+            pads = [
+                0, 0, paddings[0], paddings[2], 0, 0, paddings[1], paddings[3]
+            ]
+        else:
+            pads = [
+                0, paddings[0], paddings[2], 0, 0, paddings[1], paddings[3], 0
+            ]
+        pads_name = self.get_name(op.type, 'pads')
+        pads_node = self.make_constant_node(pads_name,
+                                            onnx_pb.TensorProto.INT64, pads)
+        constant_value_name = self.get_name(op.type, 'constant_value')
+        constant_value_node = self.make_constant_node(constant_value_name,
+                                                      onnx_pb.TensorProto.FLOAT,
+                                                      op.attr('pad_value'))
+
     def clip(self, op, block):
         min_name = self.get_name(op.type, 'min')
         max_name = self.get_name(op.type, 'max')
diff --git a/x2paddle/op_mapper/paddle2onnx/opset9/opset.py b/x2paddle/op_mapper/paddle2onnx/opset9/opset.py
index 231703181e6a3926cca64258378cbba91050678b..a0436e6b7ebed6c8695bee90308a67081a1ce10e 100644
--- a/x2paddle/op_mapper/paddle2onnx/opset9/opset.py
+++ b/x2paddle/op_mapper/paddle2onnx/opset9/opset.py
@@ -59,7 +59,7 @@ class OpSet9(object):
             'Constant', inputs=[], outputs=[name], value=tensor)
         return node
 
-    def convert_weights(self, program):
+    def convert_weights(self, program, scope=None):
         var_names = program.global_block().vars
         nodes = list()
         for name in var_names:
@@ -68,7 +68,7 @@ class OpSet9(object):
                 continue
             if not var.persistable:
                 continue
-            weight = np.array(fluid.global_scope().find_var(name).get_tensor())
+            weight = np.array(scope.find_var(name).get_tensor())
             tensor = helper.make_tensor(
                 name=name,
                 dims=var.shape,
@@ -236,6 +236,28 @@ class OpSet9(object):
                 pads=op.attr('paddings') + op.attr('paddings'))
         return node
 
+    def pad2d(self, op, block):
+        x_shape = block.var(op.input('X')[0]).shape
+        paddings = op.attr('paddings')
+        onnx_pads = []
+        if op.attr('data_format') == 'NCHW':
+            pads = [
+                0, 0, paddings[0], paddings[2], 0, 0, paddings[1], paddings[3]
+            ]
+        else:
+            pads = [
+                0, paddings[0], paddings[2], 0, 0, paddings[1], paddings[3], 0
+            ]
+        #TODO support pads is Variable
+        node = helper.make_node(
+            'Pad',
+            inputs=op.input('X'),
+            outputs=op.output('Out'),
+            mode=op.attr('mode'),
+            value=op.attr('pad_value'),
+            pads=pads)
+        return node
+
     def softmax(self, op, block):
         axis = op.attr('axis')
         shape = block.var(op.output('Out')[0]).shape