diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py
index 7b999d0a1..fb422f491 100755
--- a/qlib/contrib/model/pytorch_gru.py
+++ b/qlib/contrib/model/pytorch_gru.py
@@ -293,22 +293,6 @@ class GRU(Model):
                 preds = self.gru_model(x_test).detach().numpy()
         return pd.Series(preds, index=index)
 
-    def save(self, filename, **kwargs):
-        with save_multiple_parts_file(filename) as model_dir:
-            model_path = os.path.join(model_dir, os.path.split(model_dir)[-1])
-            # Save model
-            torch.save(self.gru_model.state_dict(), model_path)
-
-    def load(self, buffer, **kwargs):
-        with unpack_archive_with_buffer(buffer) as model_dir:
-            # Get model name
-            _model_name = os.path.splitext(list(filter(lambda x: x.startswith("model.bin"), os.listdir(model_dir)))[0])[
-                0
-            ]
-            _model_path = os.path.join(model_dir, _model_name)
-            # Load model
-            self.gru_model.load_state_dict(torch.load(_model_path))
-        self._fitted = True
 
 
 class AverageMeter(object):
diff --git a/qlib/data/dataset/processor.py b/qlib/data/dataset/processor.py
old mode 100644
new mode 100755
index a9e404b7a..66db55323
--- a/qlib/data/dataset/processor.py
+++ b/qlib/data/dataset/processor.py
@@ -112,16 +112,13 @@ class Fillna(Processor):
     """Process infinity  """
 
     def __call__(self, df):
-        def fill_na(data):
-            def process_na(df):
-                for col in df.columns:
-                    # FIXME: Such behavior is very weird
-                    df[col] = df[col].fillna(0)
-                return df
+        def fill_na(df):
+            for col in df.columns:
+                # FIXME: Such behavior is very weird
+                df[col] = df[col].fillna(0)
 
-            data = datetime_groupby_apply(data, process_na)
-            data.sort_index(inplace=True)
-            return data
+            df.sort_index(inplace=True)
+            return df
 
         return fill_na(df)
 
@@ -163,7 +160,7 @@ class ZscoreNorm(Processor):
         df = fetch_df_by_index(df, slice(self.fit_start_time, self.fit_end_time), level="datetime")
         cols = get_group_columns(df, self.fields_group)
         self.mean_train = np.nanmean(df[cols].values, axis=0)
-        self.std_train = np.nanstd(_df[cols].values, axis=0)
+        self.std_train = np.nanstd(df[cols].values, axis=0)
         self.ignore = self.std_train == 0
         self.cols = cols