diff --git a/mindspore/train/serialization.py b/mindspore/train/serialization.py
index 90d8816094..8ec1b38804 100644
--- a/mindspore/train/serialization.py
+++ b/mindspore/train/serialization.py
@@ -224,42 +224,60 @@ def load_param_into_net(net, parameter_dict):
         msg = ("Argument parameter_dict should be a dict, but got {}.".format(type(parameter_dict)))
         raise TypeError(msg)
 
-    logger.info("Execute parameter into net process.")
-    param_name_net_not_have = []
+    logger.info("Execute load parameter into net process.")
     for name in parameter_dict:
-        b_par_dict_have_par_of_net = False
         for _, param in net.parameters_and_names():
-            if name == param.name:
-                b_par_dict_have_par_of_net = True
+            if name == param.name and param.layerwise_parallel:
                 # layerwise parallel parameter data loaded from checkpoint file,
                 # was a complete(merged) data, need to be splited
-                if param.layerwise_parallel:
-                    new_param = parameter_dict[param.name]
-                    _load_tensor_for_layerwise(new_param, param)
+                new_param = parameter_dict[param.name]
+                _load_tensor_for_layerwise(new_param, param)
                 break
-        if not b_par_dict_have_par_of_net:
-            param_name_net_not_have.append(name)
 
-    param_name_param_dict_not_have = []
+    param_not_load = []
     for _, param in net.parameters_and_names():
         if param.name in parameter_dict:
             new_param = parameter_dict[param.name]
-
             if not isinstance(new_param, Parameter):
                 logger.error("Failed to combine the net and the parameters.")
                 msg = ("Argument parameter_dict element should be a Parameter, but got {}.".format(type(new_param)))
                 raise TypeError(msg)
             _update_param(param, new_param)
         else:
-            param_name_param_dict_not_have.append(param.name)
+            param_not_load.append(param.name)
+
+    if param_not_load:
+        _load_dismatch_prefix_params(net, parameter_dict, param_not_load)
 
     logger.debug("Params not matched(in net but not in parameter_dict):")
-    for paramname in param_name_param_dict_not_have:
-        logger.debug("%s", paramname)
-    logger.debug("Params not matched(in parameter_dict but not in net):")
-    for paramname in param_name_net_not_have:
-        logger.debug("%s", paramname)
-    logger.info("Load parameter into net process finish.")
+    for param_name in param_not_load:
+        logger.debug("%s", param_name)
+
+    logger.info("Load parameter into net finish, {} parameters has not been loaded.".format(len(param_not_load)))
+
+
+def _load_dismatch_prefix_params(net, parameter_dict, param_not_load):
+    """When some net parameter did not load, try to continue load."""
+    prefix_name = ""
+    longest_name = param_not_load[0]
+    while prefix_name != longest_name and param_not_load:
+        logger.debug("Count: {} parameters has not been loaded, try to load continue.".format(len(param_not_load)))
+        longest_name = sorted(param_not_load, key=len, reverse=True)[0]
+        prefix_name = longest_name
+        for net_param_name in param_not_load:
+            for dict_name in parameter_dict:
+                if dict_name.endswith(net_param_name):
+                    tmp_name = dict_name[:-len(net_param_name)]
+                    prefix_name = prefix_name if len(prefix_name) < len(tmp_name) else tmp_name
+
+        if prefix_name != longest_name:
+            logger.info("Remove parameter prefix name: {}, continue to load.".format(prefix_name))
+            for _, param in net.parameters_and_names():
+                new_param_name = prefix_name + param.name
+                if param.name in param_not_load and new_param_name in parameter_dict:
+                    new_param = parameter_dict[new_param_name]
+                    _update_param(param, new_param)
+                    param_not_load.remove(param.name)
 
 
 def _save_graph(network, file_name):