diff --git a/mindspore/train/quant/quant.py b/mindspore/train/quant/quant.py
index 1a2b1b4a4c..78ffc00f94 100644
--- a/mindspore/train/quant/quant.py
+++ b/mindspore/train/quant/quant.py
@@ -342,14 +342,6 @@ class ExportToQuantInferNetwork:
         network = self._convert_quant2deploy(network)
         return network
 
-    def statistic_weight(self, weight):
-        out_nums = np.shape(weight)[0]
-        sta_metric = np.zeros((out_nums, 2), dtype=np.float32)
-        for num in range(out_nums):
-            sta_metric[num, 0] = np.min(weight[num])
-            sta_metric[num, 1] = np.max(weight[num])
-        return np.mean(sta_metric[:, 1]).tolist(), np.mean(sta_metric[:, 0]).tolist()
-
     def _get_quant_block(self, cell_core, activation, fake_quant_a_out):
         """convet network's quant subcell to deploy subcell"""
         # Calculate the scale and zero point
@@ -410,7 +402,8 @@ class ExportToQuantInferNetwork:
         elif isinstance(cell_core, quant.Conv2dBnWithoutFoldQuant):
             weight, bias = quant_utils.without_fold_batchnorm(weight, cell_core)
         if self.is_mindir:
-            param_dict["filter_maxq"], param_dict["filter_minq"] = self.statistic_weight(weight)
+            param_dict["filter_maxq"], param_dict["filter_minq"] = cell_core.fake_quant_weight.maxq, \
+                                                                   cell_core.fake_quant_weight.minq
         weight_b = weight
         bias_b = bias
         # apply the quant