diff --git a/examples/classification.py b/examples/classification.py
index e1ca9f14b39439e5f3db8300d2f778d8bc9b6d1c..49f29a6341a03dd158341ae5a7361af417a31533 100644
--- a/examples/classification.py
+++ b/examples/classification.py
@@ -50,6 +50,7 @@ def main(args):
     data = ((data - img_mean) * scale).astype(np.float32)
     data = np.ascontiguousarray(data.transpose((2, 0, 1)))
     assert data.dtype == np.float32
+    data = data.copy()
 
     graph = tg.Graph(None, 'tengine', tm_file)
     input_tensor = graph.getInputTensor(0, 0)
diff --git a/examples/landmark.py b/examples/landmark.py
index fc82c84abc6d97e63b6771325c241fce49afef01..e005c0bd930a27e52337fc00d9591eb59a8aedf5 100755
--- a/examples/landmark.py
+++ b/examples/landmark.py
@@ -60,6 +60,7 @@ def main(args):
     data = ((data - img_mean) * scale[0]).astype(np.float32)
     data = data.transpose((2, 0, 1))
     assert data.dtype == np.float32
+    data = data.copy()
 
     graph = tg.Graph(None, 'tengine', tm_file)
     input_tensor = graph.getInputTensor(0, 0)
diff --git a/examples/mobilenet_ssd.py b/examples/mobilenet_ssd.py
index 9cdc7c8bbd5b884ffa7430652a96f7c22f3400d6..4ac3048777c8dc49caec504dabdf845996047ab4 100755
--- a/examples/mobilenet_ssd.py
+++ b/examples/mobilenet_ssd.py
@@ -63,6 +63,7 @@ def main(args):
     data = ((data - img_mean) * DEFAULT_SCALE).astype(np.float32)
     data = data.transpose((2, 0, 1))
     assert data.dtype == np.float32
+    data = data.copy()
 
     graph = tg.Graph(None, 'tengine', tm_file)
     input_tensor = graph.getInputTensor(0, 0)
diff --git a/examples/retinaface.py b/examples/retinaface.py
index cf01db300493f43ef6c904d950fdd9b4fa17e703..68710b568933ac6ef587023b21e5f62974d82312 100755
--- a/examples/retinaface.py
+++ b/examples/retinaface.py
@@ -322,7 +322,7 @@ def main(args):
 
     #image_data = image_data.transpose((2, 0, 1)).astype(np.float32)
     image_data = np.ascontiguousarray(image_data.transpose((2, 0, 1)).astype(np.float32))
-    
+    image_data = image_data.copy()
     #print("img_h, img_w, img_c: %d, %d, %d" %(img_h, img_w, img_c))
 
     input_tensor = graph.getTensorByName(input_name)
diff --git a/tools/convert_tool/onnx/onnx2tengine.cpp b/tools/convert_tool/onnx/onnx2tengine.cpp
index db45da4d827c0f6a3ee47bfa5dda968ec8dbf85e..34a1fb7f6d9dae3ed288e5ba2e3497f35a2d2076 100644
--- a/tools/convert_tool/onnx/onnx2tengine.cpp
+++ b/tools/convert_tool/onnx/onnx2tengine.cpp
@@ -2132,9 +2132,7 @@ static int load_resize(ir_graph_t* graph, ir_node_t* node, const onnx::NodeProto
     interp_param->width_scale = 0;
 
     std::string coordinate_transformation_mode = GetAttributeOrDefault<std::string>(onnx_node, "coordinate_transformation_mode", "half_pixel");
-    TASSERT(coordinate_transformation_mode == "half_pixel" ||
-            coordinate_transformation_mode == "align_corners" ||
-            coordinate_transformation_mode == "asymmetric");
+    TASSERT(coordinate_transformation_mode == "half_pixel" || coordinate_transformation_mode == "align_corners" || coordinate_transformation_mode == "asymmetric");
     int align_corner = (coordinate_transformation_mode == "align_corners");
 
     if (onnx_node.input_size() == 1)
diff --git a/tools/save_graph/tm2_op_save.cpp b/tools/save_graph/tm2_op_save.cpp
index 6e0a1ce190778364e6995be58f57f3f8425c82ad..1ed7c03852815c47de17b559517e40d4efba65b2 100644
--- a/tools/save_graph/tm2_op_save.cpp
+++ b/tools/save_graph/tm2_op_save.cpp
@@ -749,7 +749,6 @@ tm_uoffset_t SaveTmMinimumOp(void* const start_ptr, tm_uoffset_t* cur_pos, ir_no
     return WriteTmObject(start_ptr, cur_pos, &tm_op, sizeof(TM2_Operator));
 }
 
-
 tm_uoffset_t SaveTmSqueezeOp(void* const start_ptr, tm_uoffset_t* cur_pos, ir_node_t* node)
 {
     struct squeeze_param* p = (struct squeeze_param*)node->op.param_mem;
@@ -1608,7 +1607,7 @@ op_save_t SaveTmOpFunc(uint32_t op_type)
     case OP_MINIMUM:
         return SaveTmMinimumOp;
     default:
-        fprintf(stderr, "Operator #%d not supported in tengine model yet\n",op_type);
+        fprintf(stderr, "Operator #%d not supported in tengine model yet\n", op_type);
         return nullptr;
     }
 }