Applied patch to OpenAI GPT, RoBERTa, TransfoL, XLM and XLNet

pytorch_transformers/modeling_roberta.py

@@ -168,7 +168,7 @@ class RobertaModel(BertModel):
         super(RobertaModel, self).__init__(config)
 
         self.embeddings = RobertaEmbeddings(config)
-        self.apply(self.init_weights)
+        self.init_weights()
 
     def forward(self, input_ids, token_type_ids=None, attention_mask=None, position_ids=None, head_mask=None):
         if input_ids[:, 0].sum().item() != 0:
@@ -220,7 +220,7 @@ class RobertaForMaskedLM(BertPreTrainedModel):
         self.roberta = RobertaModel(config)
         self.lm_head = RobertaLMHead(config)
 
-        self.apply(self.init_weights)
+        self.init_weights()
         self.tie_weights()
 
     def tie_weights(self):