diff --git a/example/quantization/imagenet_gen_qsym_mkldnn.py b/example/quantization/imagenet_gen_qsym_mkldnn.py
index c38019fbe7b9..938890bb75df 100644
--- a/example/quantization/imagenet_gen_qsym_mkldnn.py
+++ b/example/quantization/imagenet_gen_qsym_mkldnn.py
@@ -273,7 +273,9 @@ def save_params(fname, arg_params, aux_params, logger=None):
     logger.info('rgb_std = %s' % rgb_std)
     rgb_std = [float(i) for i in rgb_std.split(',')]
     std_args = {'std_r': rgb_std[0], 'std_g': rgb_std[1], 'std_b': rgb_std[2]}    
-
+    combine_mean_std = {}
+    combine_mean_std.update(mean_args)
+    combine_mean_std.update(std_args)
     if calib_mode == 'none':
         logger.info('Quantizing FP32 model %s' % args.model)
         qsym, qarg_params, aux_params = quantize_model(sym=sym, arg_params=arg_params, aux_params=aux_params,
@@ -294,8 +296,7 @@ def save_params(fname, arg_params, aux_params, logger=None):
                                      shuffle=args.shuffle_dataset,
                                      shuffle_chunk_seed=args.shuffle_chunk_seed,
                                      seed=args.shuffle_seed,
-                                     **mean_args,
-                                     **std_args)
+                                     **combine_mean_std)
 
         qsym, qarg_params, aux_params = quantize_model(sym=sym, arg_params=arg_params, aux_params=aux_params,
                                                         ctx=ctx, excluded_sym_names=excluded_sym_names,
diff --git a/example/quantization/imagenet_inference.py b/example/quantization/imagenet_inference.py
index 3fdb52f40cb2..0725165b0ca5 100644
--- a/example/quantization/imagenet_inference.py
+++ b/example/quantization/imagenet_inference.py
@@ -181,6 +181,9 @@ def benchmark_score(symbol_file, ctx, batch_size, num_batches, logger=None):
     logger.info('rgb_std = %s' % rgb_std)
     rgb_std = [float(i) for i in rgb_std.split(',')]
     std_args = {'std_r': rgb_std[0], 'std_g': rgb_std[1], 'std_b': rgb_std[2]}
+    combine_mean_std = {}
+    combine_mean_std.update(mean_args)
+    combine_mean_std.update(std_args)
 
     label_name = args.label_name
     logger.info('label_name = %s' % label_name)
@@ -206,8 +209,7 @@ def benchmark_score(symbol_file, ctx, batch_size, num_batches, logger=None):
                                     shuffle=True,
                                     shuffle_chunk_seed=3982304,
                                     seed=48564309,
-                                    **mean_args,
-                                    **std_args)
+                                    **combine_mean_std)
 
         # loading model
         sym, arg_params, aux_params = load_model(symbol_file, param_file, logger)