diff --git a/python/paddle/v2/config_base.py b/python/paddle/v2/config_base.py
index 035f96b0f2e978a413a1ebe0ec115f75ff07befc..be3e39a06ef9d33cac6f65f47824da7685859b00 100644
--- a/python/paddle/v2/config_base.py
+++ b/python/paddle/v2/config_base.py
@@ -19,9 +19,10 @@ import paddle.trainer_config_helpers as conf_helps
 
 
 class Layer(object):
-    def __init__(self, name=None, parent_layers=None):
+    def __init__(self, name=None, size=None, parent_layers=None):
         assert isinstance(parent_layers, dict)
         self.name = name
+        self.size = size
         self.__parent_layers__ = parent_layers
 
     def to_proto(self, context):
@@ -39,16 +40,30 @@ class Layer(object):
                                self.__parent_layers__[layer_name])
             kwargs[layer_name] = v1_layer
 
-        if self.name is None:
+        if self.context_name() is None:
             return self.to_proto_impl(**kwargs)
-        elif self.name not in context:
-            context[self.name] = self.to_proto_impl(**kwargs)
+        elif self.context_name() not in context:
+            context[self.context_name()] = self.to_proto_impl(**kwargs)
 
-        return context[self.name]
+        if self.use_context_name():
+            return context[self.context_name()]
+        else:
+            return context[self.name]
 
     def to_proto_impl(self, **kwargs):
         raise NotImplementedError()
 
+    def context_name(self):
+        """
+        Context name means the context which stores `to_proto_impl` result.
+        If multiple layer share same context_name, the `to_proto_impl` of them
+        will be invoked only once.
+        """
+        return self.name
+
+    def use_context_name(self):
+        return False
+
 
 def __convert_to_v2__(method_name, parent_names, is_default_name=True):
     if is_default_name:
@@ -69,7 +84,8 @@ def __convert_to_v2__(method_name, parent_names, is_default_name=True):
                     other_kwargs[key] = kwargs[key]
 
             name = kwargs.get('name', None)
-            super(V2LayerImpl, self).__init__(name, parent_layers)
+            size = kwargs.get('size', None)
+            super(V2LayerImpl, self).__init__(name, size, parent_layers)
             self.__other_kwargs__ = other_kwargs
 
         if wrapper is not None: