Update modeling_nula.py

modeling_nula.py

@@ -55,7 +55,7 @@ class SEBlock(nn.Module):
         return x * z
 
 
-class NULAConvBlock(nn.Module):
+class NulaConvBlock(nn.Module):
     def __init__(self, in_ch, out_ch, downsample=False, use_se=False, se_reduction=16):
         super().__init__()
         stride = 1
@@ -122,9 +122,9 @@ class NulaForImageClassification(PreTrainedModel):
         self.stem_bn = nn.BatchNorm2d(c1)
         self.stem_act = nn.SiLU(inplace=True)
 
-        self.s1 = NULAConvBlock(c1, c1, False, config.use_se, config.se_reduction)
-        self.s2 = NULAConvBlock(c1, c2, True, config.use_se, config.se_reduction)
-        self.s3 = NULAConvBlock(c2, c3, True, config.use_se, config.se_reduction)
+        self.s1 = NulaConvBlock(c1, c1, False, config.use_se, config.se_reduction)
+        self.s2 = NulaConvBlock(c1, c2, True, config.use_se, config.se_reduction)
+        self.s3 = NulaConvBlock(c2, c3, True, config.use_se, config.se_reduction)
         self.global_pool = nn.AdaptiveAvgPool2d((1,1))
         self.head = nn.Sequential(
             nn.Linear(c3, config.classifier_hidden_dim),