diff --git a/mindspore/core/load_mindir/anf_model_parser.cc b/mindspore/core/load_mindir/anf_model_parser.cc
index 4d06d53a48..7cd8133df2 100644
--- a/mindspore/core/load_mindir/anf_model_parser.cc
+++ b/mindspore/core/load_mindir/anf_model_parser.cc
@@ -228,10 +228,12 @@ tensor::TensorPtr MSANFModelParser::BuildTensorInfoForFuncGraph(const mind_ir::T
   }
 
   if (!tensor_proto.has_data_type()) {
-    MS_LOG(EXCEPTION) << "mind_ir TensorProto has no data_type or name!";
+    MS_LOG(ERROR) << "mind_ir build tensor: " << tensor_proto.name() << " failed";
+    MS_LOG(EXCEPTION) << "mind_ir TensorProto has no data_type.";
   }
   if (kDefaultValueSwitchMap.find(tensor_proto.data_type()) == kDefaultValueSwitchMap.end()) {
-    MS_LOG(EXCEPTION) << "mind_ir TensorProto data_type is not support yet!";
+    MS_LOG(ERROR) << "mind_ir build tensor: " << tensor_proto.name() << " failed";
+    MS_LOG(EXCEPTION) << "mind_ir TensorProto data_type: " << tensor_proto.data_type() << " is not support yet!";
   }
 
   tensor::TensorPtr tensor_info =
diff --git a/mindspore/train/_utils.py b/mindspore/train/_utils.py
index 8d42ad0f02..f4d5e343b6 100644
--- a/mindspore/train/_utils.py
+++ b/mindspore/train/_utils.py
@@ -24,8 +24,8 @@ from mindspore.common import dtype as mstype
 from mindspore import log as logger
 from mindspore.common.api import _executor
 from mindspore.train.mind_ir_pb2 import ModelProto as mindir_model
-from mindspore.train.anf_ir_pb2 import ModelProto as anf_model
 from mindspore.train.checkpoint_pb2 import Checkpoint
+from mindspore.train.node_strategy_pb2 import ParallelStrategyMap as ckpt_strategy
 
 from .lineage_pb2 import DatasetGraph, TrainLineage, EvaluationLineage, UserDefinedInfo
 
@@ -215,7 +215,7 @@ def read_proto(file_name, proto_format="MINDIR", display_data=False):
 
     Args:
         file_name (str): File name.
-        proto_format (str): Proto format {MINDIR, ANF, CKPT}.  Default: MINDIR.
+        proto_format (str): Proto format {MINDIR, CKPT, CKPT_STRATEGY}.  Default: MINDIR.
         display_data (bool): Whether display data. Default: False.
 
     Returns:
@@ -224,10 +224,10 @@ def read_proto(file_name, proto_format="MINDIR", display_data=False):
 
     if proto_format == "MINDIR":
         model = mindir_model()
-    elif proto_format == "ANF":
-        model = anf_model()
     elif proto_format == "CKPT":
         model = Checkpoint()
+    elif proto_format == "CKPT_STRATEGY":
+        model = ckpt_strategy()
     else:
         raise ValueError("Unsupported proto format.")
 
diff --git a/mindspore/train/serialization.py b/mindspore/train/serialization.py
index 283ad875b2..7d87478855 100644
--- a/mindspore/train/serialization.py
+++ b/mindspore/train/serialization.py
@@ -658,13 +658,18 @@ def _save_mindir(net, file_name, *inputs):
     net_dict = net.parameters_dict()
     data_total = 0
     save_together = True
-    for i in net_dict.values():
-        data_total += sys.getsizeof(i.data.asnumpy().tobytes())/1024
+
+    model.ParseFromString(mindir_stream)
+    for param_proto in model.graph.parameter:
+        name = param_proto.name[param_proto.name.find(":") + 1:]
+        if name in net_dict.keys():
+            data_total += sys.getsizeof(net_dict[name].data.asnumpy().tobytes()) / 1024
+        else:
+            raise RuntimeError('Graph parameter: {} Undefined in network.'.format(param_proto.name))
         if data_total > TOTAL_SAVE:
             save_together = False
             break
 
-    model.ParseFromString(mindir_stream)
     if save_together:
         for param_proto in model.graph.parameter:
             param_name = param_proto.name[param_proto.name.find(":")+1:]
@@ -697,19 +702,19 @@ def _save_mindir(net, file_name, *inputs):
         index = 0
         graphproto = graph_proto()
         data_size = 0
+
         for name, param in net_dict.items():
-            byte_data = param.data.asnumpy().tobytes()
-            data_size += sys.getsizeof(byte_data)/1024
-            parameter = graphproto.parameter.add()
             for param_proto in model.graph.parameter:
                 if name == param_proto.name[param_proto.name.find(":") + 1:]:
+                    parameter = graphproto.parameter.add()
                     parameter.name = param_proto.name
                     parameter.data_type = param_proto.data_type
                     for dim in param_proto.dims:
                         parameter.dims.append(dim)
+                    byte_data = param.data.asnumpy().tobytes()
+                    parameter.raw_data = byte_data
+                    data_size += sys.getsizeof(byte_data) / 1024
                     break
-
-            parameter.raw_data = byte_data
             if data_size > TOTAL_SAVE:
                 data_file_name = data_path + "/" + "data_" + str(index)
                 with open(data_file_name, "ab") as f: