diff --git a/modules/deeplearning/cloud_opd_srcnn_abi_v2.py b/modules/deeplearning/cloud_opd_srcnn_abi_v2.py
index 4ab1310cb000514dfcb7583052cb970a3946df2b..5e71cccc128a69b4b309a4ef711a449e820c9d17 100644
--- a/modules/deeplearning/cloud_opd_srcnn_abi_v2.py
+++ b/modules/deeplearning/cloud_opd_srcnn_abi_v2.py
@@ -271,15 +271,6 @@ class SRCNN:
             tmp = normalize(tmp, param, mean_std_dct)
             data_norm.append(tmp)
 
-        tmp = input_label[:, label_idx_i, :, :]
-        tmp = tmp.copy()
-        tmp = np.where(np.isnan(tmp), 0.0, tmp)
-        tmp = tmp[:, self.slc_y_2, self.slc_x_2]
-        tmp = self.upsample(tmp)
-        tmp = smooth_2d(tmp)
-        tmp = normalize(tmp, label_param, mean_std_dct)
-        data_norm.append(tmp)
-
         # for param in sub_fields:
         #     idx = params.index(param)
         #     tmp = input_data[:, idx, :, :]
@@ -305,6 +296,15 @@ class SRCNN:
             data_norm.append(tmp)
         # ---------------------------------------------------
 
+        tmp = input_label[:, label_idx_i, :, :]
+        tmp = tmp.copy()
+        tmp = np.where(np.isnan(tmp), 0.0, tmp)
+        tmp = tmp[:, self.slc_y_2, self.slc_x_2]
+        tmp = self.upsample(tmp)
+        tmp = smooth_2d(tmp)
+        tmp = normalize(tmp, label_param, mean_std_dct)
+        data_norm.append(tmp)
+
         data = np.stack(data_norm, axis=3)
         data = data.astype(np.float32)