diff --git a/demo/mnist/.gitignore b/demo/mnist/.gitignore
index 8bd9837523ccf98e6e72d5b82934b7b104816217..9c552159be6f73e06233956ba0ed1e077ac1d02a 100644
--- a/demo/mnist/.gitignore
+++ b/demo/mnist/.gitignore
@@ -5,3 +5,4 @@ plot.png
 train.log
 *pyc
 .ipynb_checkpoints
+params.pkl
diff --git a/demo/mnist/api_train_v2.py b/demo/mnist/api_train_v2.py
index a59b30ccdb2eddea6680d6ad5c790c857b9c5141..73fcb9d79d32cca5c679234f3e4a254f01861a72 100644
--- a/demo/mnist/api_train_v2.py
+++ b/demo/mnist/api_train_v2.py
@@ -1,4 +1,5 @@
 import paddle.v2 as paddle
+import cPickle
 
 
 def main():
@@ -16,7 +17,11 @@ def main():
                                 act=paddle.activation.Softmax())
     cost = paddle.layer.classification_cost(input=inference, label=label)
 
-    parameters = paddle.parameters.create(cost)
+    try:
+        with open('params.pkl', 'r') as f:
+            parameters = cPickle.load(f)
+    except IOError:
+        parameters = paddle.parameters.create(cost)
 
     adam_optimizer = paddle.optimizer.Adam(learning_rate=0.01)
 
@@ -34,6 +39,10 @@ def main():
                     event.pass_id, event.batch_id, event.cost, event.metrics,
                     result.metrics)
 
+                with open('params.pkl', 'w') as f:
+                    cPickle.dump(
+                        parameters, f, protocol=cPickle.HIGHEST_PROTOCOL)
+
         else:
             pass
 
diff --git a/python/paddle/v2/parameters.py b/python/paddle/v2/parameters.py
index 2a6026bcab1c8a373d8dd5eac480dec62a8eb3b9..d8c3a73b0ea9e5df11dd0933a1c87cf13e0b5ded 100644
--- a/python/paddle/v2/parameters.py
+++ b/python/paddle/v2/parameters.py
@@ -222,6 +222,33 @@ class Parameters(object):
 
         self.__gradient_machines__.append(gradient_machine)
 
+    def __getstate__(self):
+        params = {}
+        for name in self.names():
+            params[name] = self.get(name)
+
+        param_conf = {}
+        for name in self.__param_conf__:
+            conf = self.__param_conf__[name]
+            assert isinstance(conf, ParameterConfig)
+            param_conf[name] = conf.SerializeToString()
+
+        return {'conf': param_conf, 'params': params}
+
+    def __setstate__(self, obj):
+        Parameters.__init__(self)
+
+        def __impl__(conf, params):
+            for name in conf:
+                p = ParameterConfig()
+                p.ParseFromString(conf[name])
+                self.__append_config__(p)
+            for name in params:
+                shape = self.get_shape(name)
+                self.set(name, params[name].reshape(shape))
+
+        __impl__(**obj)
+
 
 def __get_parameter_in_gradient_machine__(gradient_machine, name):
     """
diff --git a/python/paddle/v2/trainer.py b/python/paddle/v2/trainer.py
index 5003f55f3e0d15149d28d1478e0487d6873d6e0a..709566ca4475f27dba2b64ee74041b9e6d7d9611 100644
--- a/python/paddle/v2/trainer.py
+++ b/python/paddle/v2/trainer.py
@@ -66,9 +66,9 @@ class SGD(ITrainer):
             self.__topology_in_proto__, api.CREATE_MODE_NORMAL,
             self.__optimizer__.enable_types())
         assert isinstance(gm, api.GradientMachine)
-        parameters.append_gradient_machine(gm)
         self.__gradient_machine__ = gm
         self.__gradient_machine__.randParameters()
+        parameters.append_gradient_machine(gm)
 
     def train(self, reader, num_passes=1, event_handler=None, reader_dict=None):
         """