[s2s]Use prepare_translation_batch for Marian finetuning (#6293)

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

src/transformers/tokenization_marian.py

@@ -127,10 +127,12 @@ class MarianTokenizer(PreTrainedTokenizer):
         src_texts: List[str],
         tgt_texts: Optional[List[str]] = None,
         max_length: Optional[int] = None,
+        max_target_length: Optional[int] = None,
         pad_to_max_length: bool = True,
         return_tensors: str = "pt",
         truncation_strategy="only_first",
         padding="longest",
+        **unused,
     ) -> BatchEncoding:
         """Prepare model inputs for translation. For best performance, translate one sentence at a time.
         Arguments:
@@ -162,6 +164,9 @@ class MarianTokenizer(PreTrainedTokenizer):
         if tgt_texts is None:
             return model_inputs
 
+        if max_target_length is not None:
+            tokenizer_kwargs["max_length"] = max_target_length
+
         self.current_spm = self.spm_target
         decoder_inputs: BatchEncoding = self(tgt_texts, **tokenizer_kwargs)
         for k, v in decoder_inputs.items():