fix KTO Trainer Sampler

src/llamafactory/train/kto/trainer.py

@@ -4,6 +4,7 @@ from types import MethodType
 from typing import TYPE_CHECKING, Dict, Literal, Optional, Tuple, Union
 
 import torch
+from torch.utils.data import RandomSampler
 from transformers import Trainer
 from trl import KTOTrainer
 from trl.trainer import disable_dropout_in_model
@@ -173,6 +174,21 @@ class CustomKTOTrainer(KTOTrainer):
 
         return reference_chosen_logps, reference_rejected_logps, reference_kl_logps
 
+    def has_length(self,dataset):
+        """
+        Checks if the dataset implements __len__() and it doesn't raise an error
+        """
+        try:
+            return len(dataset) is not None
+        except TypeError:
+            # TypeError: len() of unsized object
+            return False
+
+    def _get_train_sampler(self) -> Optional[torch.utils.data.Sampler]:
+        if self.train_dataset is None or not self.has_length(self.train_dataset):
+            return None
+        return RandomSampler(self.train_dataset)
+
     def get_batch_loss_metrics(
         self,
         model: "PreTrainedModel",