Fixing camembert tokenization

transformers/tokenization_camembert.py

@@ -51,7 +51,7 @@ class CamembertTokenizer(PreTrainedTokenizer):
 
     def __init__(self, vocab_file, bos_token="<s>", eos_token="</s>", sep_token="</s>",
                  cls_token="<s>", unk_token="<unk>", pad_token='<pad>', mask_token='<mask>',
-                 additional_special_tokens=['<s>NOTUSED', '<s>NOTUSED'], **kwargs):
+                 additional_special_tokens=['<s>NOTUSED', '</s>NOTUSED'], **kwargs):
         super(CamembertTokenizer, self).__init__(max_len=512, bos_token=bos_token, eos_token=eos_token, unk_token=unk_token,
                                                  sep_token=sep_token, cls_token=cls_token, pad_token=pad_token,
                                                  mask_token=mask_token, additional_special_tokens=additional_special_tokens,
@@ -125,7 +125,7 @@ class CamembertTokenizer(PreTrainedTokenizer):
 
     @property
     def vocab_size(self):
-        return self.fairseq_offset + len(self.sp_model)
+        return len(self.fairseq_tokens_to_ids) + len(self.sp_model)
 
     def _tokenize(self, text):
         return self.sp_model.EncodeAsPieces(text)
@@ -134,6 +134,9 @@ class CamembertTokenizer(PreTrainedTokenizer):
         """ Converts a token (str/unicode) in an id using the vocab. """
         if token in self.fairseq_tokens_to_ids:
             return self.fairseq_tokens_to_ids[token]
+        elif self.sp_model.PieceToId(token) == 0:
+            # Convert sentence piece unk token to fairseq unk token index
+            return self.unk_token_id
         return self.fairseq_offset + self.sp_model.PieceToId(token)
 
     def _convert_id_to_token(self, index):