diff --git a/x2paddle/core/program.py b/x2paddle/core/program.py
index 5c945dfe45c2fae04d47d57f2e2e42b184c16e1a..f51fa1f74989a8c1812ccf48b21dc2e673d10ae6 100644
--- a/x2paddle/core/program.py
+++ b/x2paddle/core/program.py
@@ -590,7 +590,7 @@ class PaddleGraph(object):
                 elif len(layer.outputs) == 2:
                     line = layer.outputs[1]
                 else:
-                    if layer.kernel in ["paddle.nn.LSTM", 'custom_layer:LSTM']:
+                    if layer.kernel in ["paddle.nn.LSTM"]:
                         line = "{}, ({})".format(layer.outputs[1], ', '.join(layer.outputs[-2:]))
                     else:
                         line = ','.join(layer.outputs[1:])
diff --git a/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py b/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py
index bf31b2f98633fc689bab244850e4d1b61281d8f4..1344206cf409f4c49cc0b1b7f6dc9c43c35a5cf0 100644
--- a/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py
+++ b/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py
@@ -611,8 +611,6 @@ class OpSet9():
         layer_attrs = {
             'num_features': node.out_shapes[0][1],
             'epsilon': epsilon,
-            #'weight_attr': string(val_scale.name),
-            #'bias_attr': string(val_b.name)
         }
         dim = len(val_x.out_shapes[0])
         if dim == 3:
@@ -1333,10 +1331,6 @@ class OpSet9():
             "momentum": momentum,
             "epsilon": epsilon,
             "is_test": True,
-            #"param_attr": string(val_scale.name),
-            #"bias_attr": string(val_b.name),
-            #"moving_mean_name": string(val_mean.name),
-            #"moving_variance_name": string(val_var.name),
             "use_global_stats": False,
         }
         self.paddle_graph.add_layer(
@@ -1402,7 +1396,6 @@ class OpSet9():
             if mode == 'channel':
                 slope_data = _const_weight_or_none(val_slope)
                 if len(shape_slope) > 1:
-                    #self.weights[val_slope.name] = np.reshape(slope_data, shape_slope[0])
                     self.weights[op_name+'._weight'] = np.reshape(slope_data, shape_slope[0])
                 num_parameters = val_x.out_shapes[0][1]
             else: