diff --git a/modelscope/msdatasets/ms_dataset.py b/modelscope/msdatasets/ms_dataset.py
index f6896e4a..8174d054 100644
--- a/modelscope/msdatasets/ms_dataset.py
+++ b/modelscope/msdatasets/ms_dataset.py
@@ -517,10 +517,3 @@ class MsDataset:
     def to_hf_dataset(self) -> Dataset:
         self._hf_ds.reset_format()
         return self._hf_ds
-
-    @staticmethod
-    def interleave_datasets(datasets: List[Any],
-                            probabilities: Optional[List[float]] = None,
-                            seed: Optional[int] = None):
-        from datasets import interleave_datasets
-        return interleave_datasets(datasets, probabilities, seed)
diff --git a/modelscope/trainers/hooks/evaluation_hook.py b/modelscope/trainers/hooks/evaluation_hook.py
index 80d8c03c..aea27f2f 100644
--- a/modelscope/trainers/hooks/evaluation_hook.py
+++ b/modelscope/trainers/hooks/evaluation_hook.py
@@ -32,7 +32,6 @@ class EvaluationHook(Hook):
     def do_evaluate(self, trainer):
         """Evaluate the results."""
         eval_res = trainer.evaluate()
-        trainer.data_loader = trainer.train_dataloader
         for name, val in eval_res.items():
             trainer.log_buffer.output[name] = val
 
diff --git a/tests/trainers/test_trainer_with_nlp.py b/tests/trainers/test_trainer_with_nlp.py
index a2d899ba..e102cd27 100644
--- a/tests/trainers/test_trainer_with_nlp.py
+++ b/tests/trainers/test_trainer_with_nlp.py
@@ -23,7 +23,6 @@ class TestTrainerWithNlp(unittest.TestCase):
         if not os.path.exists(self.tmp_dir):
             os.makedirs(self.tmp_dir)
 
-        # todo: Replace below scripts with MsDataset.load when the formal dataset service is ready
         self.dataset = MsDataset.load(
             'afqmc_small', namespace='userxiaoming', split='train')