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modeling_mic21.py

@@ -119,7 +119,7 @@ class MIC21SummarizerModel(PreTrainedModel):
                 break
         if titles is not None:
             target_tok = self.components["tokenizer"](titles, add_special_tokens=False, max_length=max_len+1, padding='max_length')
-            loss = torch.nn.CrossEntropyLoss()(out_logits.permute((0,2,1)), torch.LongTensor(target_tok["input_ids"]))
+            loss = torch.nn.CrossEntropyLoss()(out_logits.permute((0,2,1)), torch.LongTensor(target_tok["input_ids"]).cuda())
                 #.cuda(self.out_device))
             return {"loss": loss, "logits": logits}