Fix type hint for train_dataset param of Trainer.__init__() to allow...

Fix type hint for train_dataset param of Trainer.__init__() to allow IterableDataset.  Issue 29678 (#29738)

* Fixed typehint for train_dataset param in Trainer.__init__().  Added IterableDataset option.

* make fixup

src/transformers/trainer.py

@@ -52,7 +52,7 @@ import torch.distributed as dist
 from huggingface_hub import ModelCard, create_repo, upload_folder
 from packaging import version
 from torch import nn
-from torch.utils.data import DataLoader, Dataset, RandomSampler, SequentialSampler
+from torch.utils.data import DataLoader, Dataset, IterableDataset, RandomSampler, SequentialSampler
 
 from . import __version__
 from .configuration_utils import PretrainedConfig
@@ -353,7 +353,7 @@ class Trainer:
         model: Union[PreTrainedModel, nn.Module] = None,
         args: TrainingArguments = None,
         data_collator: Optional[DataCollator] = None,
-        train_dataset: Optional[Dataset] = None,
+        train_dataset: Optional[Union[Dataset, IterableDataset]] = None,
         eval_dataset: Optional[Union[Dataset, Dict[str, Dataset]]] = None,
         tokenizer: Optional[PreTrainedTokenizerBase] = None,
         model_init: Optional[Callable[[], PreTrainedModel]] = None,