diff --git "a/ACL_PyTorch/docs/ONNX/04.\347\246\273\347\272\277\346\216\250\347\220\206.md" "b/ACL_PyTorch/docs/ONNX/04.\347\246\273\347\272\277\346\216\250\347\220\206.md"
index 20f5e6090084b0e98b58a3fbed6317a8bf48d173..c1b4f812913f3c5b5925f8a708d291be742e0716 100644
--- "a/ACL_PyTorch/docs/ONNX/04.\347\246\273\347\272\277\346\216\250\347\220\206.md"
+++ "b/ACL_PyTorch/docs/ONNX/04.\347\246\273\347\272\277\346\216\250\347\220\206.md"
@@ -152,7 +152,7 @@ print(inferencer.e2e_inference("./ILSVRC2012_val_00006083.jpeg"))
 2. 使用数据集测试模型精度
    
    ```python
-   def evaluate(inferencer, image_dir, label_file):
+   def evaluate(inferencer, img_dir, label_file):
        groundtruth = {}
        with open(label_file, 'r') as f:
            for line in f:
@@ -161,7 +161,7 @@ print(inferencer.e2e_inference("./ILSVRC2012_val_00006083.jpeg"))
    
        num_total, num_right = 0, 0
        for i, image_name in tqdm.tqdm(enumerate(os.listdir(img_dir))):
-           label = gt_dict[image_name]
+           label = groundtruth[image_name]
            image_path = osp.join(img_dir, image_name)
            pred = inferencer.e2e_inference(image_path)['class_id']
            num_total += 1