💄 super

examples/pplm/pplm_classification_head.py

@@ -5,7 +5,7 @@ class ClassificationHead(torch.nn.Module):
     """Classification Head for  transformer encoders"""
 
     def __init__(self, class_size, embed_size):
-        super(ClassificationHead, self).__init__()
+        super().__init__()
         self.class_size = class_size
         self.embed_size = embed_size
         # self.mlp1 = torch.nn.Linear(embed_size, embed_size)

examples/pplm/run_pplm_discrim_train.py

@@ -46,7 +46,7 @@ class Discriminator(torch.nn.Module):
     """Transformer encoder followed by a Classification Head"""
 
     def __init__(self, class_size, pretrained_model="gpt2-medium", cached_mode=False, device="cpu"):
-        super(Discriminator, self).__init__()
+        super().__init__()
         self.tokenizer = GPT2Tokenizer.from_pretrained(pretrained_model)
         self.encoder = GPT2LMHeadModel.from_pretrained(pretrained_model)
         self.embed_size = self.encoder.transformer.config.hidden_size