seq2seq/run_eval.py can take decoder_start_token_id (#5949)

src/transformers/tokenization_utils_base.py

@@ -2255,8 +2255,23 @@ class PreTrainedTokenizerBase(SpecialTokensMixin):
 
         return encoded_inputs
 
-    def batch_decode(self, sequences: List[List[int]], **kwargs) -> List[str]:
-        return [self.decode(seq, **kwargs) for seq in sequences]
+    def batch_decode(
+        self, sequences: List[List[int]], skip_special_tokens: bool = False, clean_up_tokenization_spaces: bool = True
+    ) -> List[str]:
+        """
+        Convert a list of lists of token ids into a list of strings by calling decode.
+
+        Args:
+            token_ids: list of tokenized input ids. Can be obtained using the `encode` or `encode_plus` methods.
+            skip_special_tokens: if set to True, will replace special tokens.
+            clean_up_tokenization_spaces: if set to True, will clean up the tokenization spaces.
+        """
+        return [
+            self.decode(
+                seq, skip_special_tokens=skip_special_tokens, clean_up_tokenization_spaces=clean_up_tokenization_spaces
+            )
+            for seq in sequences
+        ]
 
     def decode(
         self, token_ids: List[int], skip_special_tokens: bool = False, clean_up_tokenization_spaces: bool = True