fix(vision/classification): fix pylint error due to version change (#61)

.github/workflows/ci.yml

@@ -40,7 +40,7 @@ jobs:
     - name: Pylint check
       run: |
         export PYTHONPATH=$PWD:$PYTHONPATH
-        pip install pylint
+        pip install pylint==2.5.2
         pylint official/vision --rcfile=.pylintrc || pylint_ret=$?
         echo test, and deploy your project.
         if [ "$pylint_ret" ]; then

official/vision/classification/resnet/model.py

@@ -60,7 +60,7 @@ class BasicBlock(M.Module):
         dilation=1,
         norm=M.BatchNorm2d,
     ):
-        super(BasicBlock, self).__init__()
+        super().__init__()
         if groups != 1 or base_width != 64:
             raise ValueError("BasicBlock only supports groups=1 and base_width=64")
         if dilation > 1:
@@ -105,7 +105,7 @@ class Bottleneck(M.Module):
         dilation=1,
         norm=M.BatchNorm2d,
     ):
-        super(Bottleneck, self).__init__()
+        super().__init__()
         width = int(channels * (base_width / 64.0)) * groups
         self.conv1 = M.Conv2d(in_channels, width, 1, 1, bias=False)
         self.bn1 = norm(width)
@@ -165,7 +165,7 @@ class ResNet(M.Module):
         replace_stride_with_dilation=None,
         norm=M.BatchNorm2d,
     ):
-        super(ResNet, self).__init__()
+        super().__init__()
         self.in_channels = 64
         self.dilation = 1
         if replace_stride_with_dilation is None:

official/vision/classification/shufflenet/model.py

@@ -40,7 +40,7 @@ import megengine.module as M
 
 class ShuffleV2Block(M.Module):
     def __init__(self, inp, oup, mid_channels, *, ksize, stride):
-        super(ShuffleV2Block, self).__init__()
+        super().__init__()
         self.stride = stride
         assert stride in [1, 2]
 
@@ -111,7 +111,7 @@ class ShuffleV2Block(M.Module):
 
 class ShuffleNetV2(M.Module):
     def __init__(self, num_classes=1000, model_size="1.5x"):
-        super(ShuffleNetV2, self).__init__()
+        super().__init__()
 
         self.stage_repeats = [4, 8, 4]
         self.model_size = model_size