Fix attribute error problem (#20765)

fix: 修复Trainer无法使用use_legacy_prediction_loop参数的问题

解决使用use_legacy_prediction_loop参数在predict阶段使用prediction_loop进行预测时，遇到AttributeError: 'PredictionOutput' object has no attribute 'num_samples'的问题
Co-authored-by: ZhouHang <zhouhang@idataway.com>

src/transformers/trainer.py

@@ -3514,7 +3514,7 @@ class Trainer:
         prediction_loss_only: Optional[bool] = None,
         ignore_keys: Optional[List[str]] = None,
         metric_key_prefix: str = "eval",
-    ) -> PredictionOutput:
+    ) -> EvalLoopOutput:
         """
         Prediction/evaluation loop, shared by `Trainer.evaluate()` and `Trainer.predict()`.
 
@@ -3651,7 +3651,7 @@ class Trainer:
             if not key.startswith(f"{metric_key_prefix}_"):
                 metrics[f"{metric_key_prefix}_{key}"] = metrics.pop(key)
 
-        return PredictionOutput(predictions=preds, label_ids=label_ids, metrics=metrics)
+        return EvalLoopOutput(predictions=preds, label_ids=label_ids, metrics=metrics, num_samples=num_examples)
 
     def _gather_and_numpify(self, tensors, name):
         """