Upload LUAR

model.py

@@ -44,7 +44,6 @@ class LUAR(PreTrainedModel):
     def mean_pooling(self, token_embeddings, attention_mask):
         """Mean Pooling as described in the SBERT paper.
         """
-        # input_mask_expanded = repeat(attention_mask, 'b l -> b l d', d=self.hidden_size).float()
         input_mask_expanded = repeat(attention_mask, 'b l -> b l d', d=self.hidden_size).type(token_embeddings.type())
         sum_embeddings = reduce(token_embeddings * input_mask_expanded, 'b l d -> b d', 'sum')
         sum_mask = torch.clamp(reduce(input_mask_expanded, 'b l d -> b d', 'sum'), min=1e-9)