[Examples] Allow EncoderDecoderModels to be trained with Seq2Seq (#7809)

* Make Seq2Seq Trainer more similar to Trainer

* fix typo

* fix seq2seq trainer

* remove from tests

* remove lock

* remove train files

* delete test files

* correct typo

* check at init

* make sure trainer is not slowed down on TPU

* correct isort

* remove use cache

* fix use cache

* add last use chache = false

examples/seq2seq/finetune_trainer.py

@@ -16,7 +16,6 @@ from transformers import (
 )
 from transformers.trainer_utils import EvaluationStrategy
 from utils import (
-    LegacySeq2SeqDataset,
     Seq2SeqDataCollator,
     Seq2SeqDataset,
     assert_all_frozen,
@@ -138,6 +137,10 @@ class DataTrainingArguments:
     src_lang: Optional[str] = field(default=None, metadata={"help": "Source language id for translation."})
     tgt_lang: Optional[str] = field(default=None, metadata={"help": "Target language id for translation."})
     eval_beams: Optional[int] = field(default=None, metadata={"help": "# num_beams to use for evaluation."})
+    ignore_pad_token_for_loss: bool = field(
+        default=True,
+        metadata={"help": "If only pad tokens should be ignored. This assumes that `config.pad_token_id` is defined."},
+    )
 
 
 def main():
@@ -223,7 +226,7 @@ def main():
         freeze_params(model.get_encoder())
         assert_all_frozen(model.get_encoder())
 
-    dataset_class = Seq2SeqDataset if hasattr(tokenizer, "prepare_seq2seq_batch") else LegacySeq2SeqDataset
+    dataset_class = Seq2SeqDataset
 
     # Get datasets
     train_dataset = (