diff --git a/ppocr/modeling/backbones/rec_resnet_32.py b/ppocr/modeling/backbones/rec_resnet_32.py
index 0b072dc5f6fefa8792338e8cce4716bdcbaeb135..cbd19251a3ed43a472d49f03743ead1491aa86ac 100644
--- a/ppocr/modeling/backbones/rec_resnet_32.py
+++ b/ppocr/modeling/backbones/rec_resnet_32.py
@@ -1,4 +1,4 @@
-# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
+# copyright (c) 2022 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -20,11 +20,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import paddle
-from paddle import ParamAttr
 import paddle.nn as nn
-import paddle.nn.functional as F
-import numpy as np
 
 __all__ = ["ResNet32"]
 
@@ -51,10 +47,10 @@ class ResNet32(nn.Layer):
     def forward(self, inputs):
         """
         Args:
-            inputs (torch.Tensor): input feature
+            inputs: input feature
 
         Returns:
-             torch.Tensor: output feature
+            output feature
 
         """
         return self.ConvNet(inputs)
@@ -92,7 +88,7 @@ class BasicBlock(nn.Layer):
             out_planes (int): channels of the middle feature
             stride (int): stride of the convolution
         Returns:
-            nn.Module: Conv2D with kernel = 3
+            nn.Layer: Conv2D with kernel = 3
 
         """
 
@@ -102,14 +98,6 @@ class BasicBlock(nn.Layer):
                          bias_attr=False)
 
     def forward(self, x):
-        """
-        Args:
-            x (torch.Tensor): input feature
-
-        Returns:
-            torch.Tensor: output feature of the BasicBlock
-
-        """
         residual = x
 
         out = self.conv1(x)
@@ -246,14 +234,6 @@ class ResNet(nn.Layer):
         return nn.Sequential(*layers)
 
     def forward(self, x):
-        """
-        Args:
-            x (torch.Tensor): input feature
-
-        Returns:
-            torch.Tensor: output feature of the Resnet
-
-        """
         x = self.conv0_1(x)
         x = self.bn0_1(x)
         x = self.relu(x)
diff --git a/ppocr/modeling/heads/rec_spin_att_head.py b/ppocr/modeling/heads/rec_spin_att_head.py
index 07a58b08327a602e9402cc122a6aedfe610fefd5..8f92d1ef45e87dd711847977a35ca7006ae52d49 100644
--- a/ppocr/modeling/heads/rec_spin_att_head.py
+++ b/ppocr/modeling/heads/rec_spin_att_head.py
@@ -19,7 +19,6 @@ from __future__ import print_function
 import paddle
 import paddle.nn as nn
 import paddle.nn.functional as F
-import numpy as np
 
 
 class SPINAttentionHead(nn.Layer):
diff --git a/ppocr/modeling/transforms/gaspin_transformer.py b/ppocr/modeling/transforms/gaspin_transformer.py
index 9440e360d151e4dfd0715a8ecf26bf47c55e238a..f4719eb2162a02141620586bcb6a849ae16f3b62 100644
--- a/ppocr/modeling/transforms/gaspin_transformer.py
+++ b/ppocr/modeling/transforms/gaspin_transformer.py
@@ -21,7 +21,6 @@ import paddle
 from paddle import nn, ParamAttr
 from paddle.nn import functional as F
 import numpy as np
-import itertools
 import functools
 from .tps import GridGenerator