diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index dcb39784a54120b70082b3e0f15e9384b329998e..2b95c2ed0f356619fb39db6fcef62809e5aa0c2f 100755
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -3115,9 +3115,7 @@ def recurrent_group(step,
                     reverse=False,
                     name=None,
                     targetInlink=None,
-                    is_generating=False,
-                    in_args_converter=None,
-                    boot_layer=None):
+                    is_generating=False):
     """
     Recurrent layer group is an extremely flexible recurrent unit in
     PaddlePaddle. As long as the user defines the calculation done within a
@@ -3260,13 +3258,7 @@ def recurrent_group(step,
 
     assert (is_generating != has_LayerOutput)
 
-    if in_args_converter is None:
-        layer_outs = step(*in_args)
-    else:
-        # append boot_layer to the last of in_args
-        if boot_layer is not None:
-            in_args.append(boot_layer)
-        layer_outs = step(*in_args_converter(*in_args)).to_proto(dict())
+    layer_outs = step(*in_args)
 
     if isinstance(layer_outs, LayerOutput):
         layer_outs = [layer_outs]
diff --git a/python/paddle/v2/layer.py b/python/paddle/v2/layer.py
index 71d0e54c0a6f85dcb7634dc03a612aa4e897a170..f1ca0b46ebc42ec6deb14f3767d1dc9ec51cfc7d 100644
--- a/python/paddle/v2/layer.py
+++ b/python/paddle/v2/layer.py
@@ -131,11 +131,6 @@ class Layer(object):
 
         if self.context_name() is None:
             return self.to_proto_impl(**kwargs)
-        elif isinstance(self, MemoryV2):
-            name = self.name + "#__memory__"
-            if name not in context:
-                context[name] = self.to_proto_impl(**kwargs)
-            return context[name]
         elif self.context_name() not in context:
             context[self.context_name()] = self.to_proto_impl(**kwargs)
         return context[self.name]