MarianMTModel.from_pretrained('Helsinki-NLP/opus-marian-en-de') (#3908)

Co-Authored-By: Stefan Schweter <stefan@schweter.it>

src/transformers/modeling_utils.py

@@ -1530,18 +1530,6 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin):
 
         return decoded
 
-    # force one of token_ids to be generated by setting prob of all other tokens to 0.
-    def _force_token_ids_generation(self, scores, token_ids) -> None:
-        if isinstance(token_ids, int):
-            token_ids = [token_ids]
-        all_but_token_ids_mask = torch.tensor(
-            [x for x in range(self.config.vocab_size) if x not in token_ids],
-            dtype=torch.long,
-            device=next(self.parameters()).device,
-        )
-        assert len(scores.shape) == 2, "scores should be of rank 2 with shape: [batch_size, vocab_size]"
-        scores[:, all_but_token_ids_mask] = -float("inf")
-
     @staticmethod
     def _reorder_cache(past: Tuple, beam_idx: Tensor) -> Tuple[Tensor]:
         return tuple(layer_past.index_select(1, beam_idx) for layer_past in past)