diff --git a/python/level2_simple_inference/1_classification/resnet50_async_imagenet_classification/src/acl_net.py b/python/level2_simple_inference/1_classification/resnet50_async_imagenet_classification/src/acl_net.py
index a70a7f7ddda983796475b5421c216f5bc0e024d8..ef60270b61790ff5dff0e9e9b918fc88be26c60d 100644
--- a/python/level2_simple_inference/1_classification/resnet50_async_imagenet_classification/src/acl_net.py
+++ b/python/level2_simple_inference/1_classification/resnet50_async_imagenet_classification/src/acl_net.py
@@ -51,7 +51,7 @@ class Net(object):
         self.model_id = None            # pointer
         self.context = None             # pointer
         self.stream = None              # pointer
-        self.excute_times = execute_times
+        self.execute_times = execute_times
         self.callback_interval = callback_interval
         self.is_callback = True if callback_interval else False
         self.memory_pool = memory_pool
@@ -169,8 +169,8 @@ class Net(object):
         for idx in range(self.memory_pool):
             img_idx = idx % len(images_dataset_list)
             img_input = self._load_input_data(images_dataset_list[img_idx])
-            infer_ouput = self._load_output_data()
-            self.dataset_list.append([img_input, infer_ouput])
+            infer_output = self._load_output_data()
+            self.dataset_list.append([img_input, infer_output])
         print("data interaction from host to device success")
 
     def _destroy_dataset_and_databuf(self, ):
@@ -226,16 +226,16 @@ class Net(object):
     def _get_callback(self, idx):
         if (idx + 1) % self.callback_interval == 0:
             acl.rt.launch_callback(self.callback_func,
-                                   self.excute_dataset,
+                                   self.execute_dataset,
                                    1,
                                    self.stream)
-            self.dataset_list.extend(self.excute_dataset)
-            self.excute_dataset = []
+            self.dataset_list.extend(self.execute_dataset)
+            self.execute_dataset = []
 
     def forward(self):
         print('execute stage:')
-        self.excute_dataset = []
-        for idx in range(self.excute_times):
+        self.execute_dataset = []
+        for idx in range(self.execute_times):
             img_data, infer_output = self.dataset_list.pop(0)
             ret = acl.mdl.execute_async(self.model_id,
                                         img_data,
@@ -244,7 +244,7 @@ class Net(object):
             check_ret("acl.mdl.execute_async", ret)
 
             if self.is_callback:
-                self.excute_dataset.append([img_data, infer_output])
+                self.execute_dataset.append([img_data, infer_output])
                 self._get_callback(idx)
         print('execute stage success')