diff --git a/cv/classification/convnext/pytorch/README.md b/cv/classification/convnext/pytorch/README.md
index f193f7a4f421754146494896ca9c658e67884d5c..de160e208151aa10a3a73eb5c8f53dae92975c77 100644
--- a/cv/classification/convnext/pytorch/README.md
+++ b/cv/classification/convnext/pytorch/README.md
@@ -5,7 +5,7 @@ The ConvNeXT model was proposed in [A ConvNet for the 2020s](https://arxiv.org/a
 
 ## Step 1: Installing
 ```bash
-pip install timm==0.3.2 tensorboardX six torch torchvision
+pip install timm==0.4.5 tensorboardX six torch torchvision
 ```
 
 Sign up and login in [imagenet official website](https://www.image-net.org/index.php), then choose 'Download' to download the whole imagenet dataset. Specify `/path/to/imagenet` to your imagenet path in later training process.
diff --git a/cv/classification/wavemlp/pytorch/README.md b/cv/classification/wavemlp/pytorch/README.md
index a8b30f44ddeba9cc8ed5b310f67a9f5a11bd74aa..7275eb6ed102096385ddc91bbebe4f1c28c4ab14 100644
--- a/cv/classification/wavemlp/pytorch/README.md
+++ b/cv/classification/wavemlp/pytorch/README.md
@@ -6,7 +6,7 @@ In the field of computer vision, recent works show that a pure MLP architecture
 
 ## Step 1: Installing packages
 ```
-pip install thop timm==0.3.2 torchprofile 
+pip install thop timm==0.4.5 torchprofile
 ```
 
 ## Step 2: Training
@@ -40,4 +40,4 @@ bash run.sh /home/datasets/cv/ImageNet/
 
 
 ## Reference
-https://github.com/huawei-noah/Efficient-AI-Backbones/blob/master/wavemlp_pytorch/
\ No newline at end of file
+https://github.com/huawei-noah/Efficient-AI-Backbones/blob/master/wavemlp_pytorch/
diff --git a/cv/detection/ssd/pytorch/base/prepare.py b/cv/detection/ssd/pytorch/base/prepare.py
index 0a9eefd5f1f7e303a175e9a93722fa1c98bf6f45..b85fb7522796f12be613445473c03efc830a0ccf 100644
--- a/cv/detection/ssd/pytorch/base/prepare.py
+++ b/cv/detection/ssd/pytorch/base/prepare.py
@@ -150,9 +150,9 @@ def prepare_data():
 
     if exist_preprocessed_data:
         return
-    current_dir = os.path.join(MODEL_DIR, "pytorch")
+    # current_dir = os.path.join(MODEL_DIR, "pytorch")
     cmds = [
-        f"cd {current_dir}",
+        # f"cd {current_dir}",
         f"python3 data_preprocessing/prepare_json.py --keep-keys {DATA_DIR}/annotations/instances_val2017.json {DATA_DIR}/annotations/bbox_only_instances_val2017.json",
         f"python3 data_preprocessing/prepare_json.py {DATA_DIR}/annotations/instances_train2017.json {DATA_DIR}/annotations/bbox_only_instances_train2017.json"
     ]
diff --git a/cv/detection/ssd/pytorch/iluvatar/csrc/nhwc/Descriptors.cpp b/cv/detection/ssd/pytorch/iluvatar/csrc/nhwc/Descriptors.cpp
index f3143f92370bf778e0db20259b3174aa9fde100a..afe0466c9e00d77dac42b9b9ba2f3b181a4d3730 100644
--- a/cv/detection/ssd/pytorch/iluvatar/csrc/nhwc/Descriptors.cpp
+++ b/cv/detection/ssd/pytorch/iluvatar/csrc/nhwc/Descriptors.cpp
@@ -20,7 +20,7 @@
 #include "Descriptors.h"
 
 #include <ATen/ATen.h>
-
+#include <iostream>
 #include <ostream>
 #include <sstream>
 #include <string>