start using training_args.parallel_mode (#8882)

examples/seq2seq/seq2seq_trainer.py

@@ -18,6 +18,7 @@ from transformers.optimization import (
     get_polynomial_decay_schedule_with_warmup,
 )
 from transformers.trainer_pt_utils import get_tpu_sampler
+from transformers.training_args import ParallelMode
 
 
 logger = logging.get_logger(__name__)
@@ -123,7 +124,7 @@ class Seq2SeqTrainer(Trainer):
             if self.args.sortish_sampler:
                 self.train_dataset.make_sortish_sampler(
                     self.args.per_device_train_batch_size,
-                    distributed=(self.args.local_rank != -1),
+                    distributed=(self.args.parallel_mode == ParallelMode.DISTRIBUTED),
                 )
 
             return (