[s2s] add config params like Dropout in Seq2SeqTrainingArguments (#7532)

examples/seq2seq/utils.py

@@ -269,7 +269,11 @@ class Seq2SeqDataCollator:
         ), f"pad_token_id is not defined for ({self.tokenizer.__class__.__name__}), it must be defined."
         self.data_args = data_args
         self.tpu_num_cores = tpu_num_cores
-        self.add_prefix_space = isinstance(tokenizer, BartTokenizer)
+        self.dataset_kwargs = {"add_prefix_space": isinstance(tokenizer, BartTokenizer)}
+        if data_args.src_lang is not None:
+            self.dataset_kwargs["src_lang"] = data_args.src_lang
+        if data_args.tgt_lang is not None:
+            self.dataset_kwargs["tgt_lang"] = data_args.tgt_lang
 
     def __call__(self, batch) -> Dict[str, torch.Tensor]:
         if hasattr(self.tokenizer, "prepare_seq2seq_batch"):
@@ -310,14 +314,12 @@ class Seq2SeqDataCollator:
     def _encode(self, batch) -> Dict[str, torch.Tensor]:
         batch_encoding = self.tokenizer.prepare_seq2seq_batch(
             [x["src_texts"] for x in batch],
-            src_lang=self.data_args.src_lang,
             tgt_texts=[x["tgt_texts"] for x in batch],
-            tgt_lang=self.data_args.tgt_lang,
             max_length=self.data_args.max_source_length,
             max_target_length=self.data_args.max_target_length,
             padding="max_length" if self.tpu_num_cores is not None else "longest",  # TPU hack
             return_tensors="pt",
-            add_prefix_space=self.add_prefix_space,
+            **self.dataset_kwargs,
         )
         return batch_encoding.data