diff --git a/modelscope/pipelines/base.py b/modelscope/pipelines/base.py
index 37d6f1e3..b1d82557 100644
--- a/modelscope/pipelines/base.py
+++ b/modelscope/pipelines/base.py
@@ -239,7 +239,6 @@ class Pipeline(ABC):
         """
         from torch.utils.data.dataloader import default_collate
         from modelscope.preprocessors import InputFeatures
-        from text2sql_lgesql.utils.batch import Batch
         if isinstance(data, dict) or isinstance(data, Mapping):
             return type(data)(
                 {k: self._collate_fn(v)
@@ -260,8 +259,6 @@ class Pipeline(ABC):
             return data
         elif isinstance(data, InputFeatures):
             return data
-        elif isinstance(data, Batch):
-            return data
         else:
             import mmcv
             if isinstance(data, mmcv.parallel.data_container.DataContainer):
diff --git a/modelscope/pipelines/nlp/conversational_text_to_sql_pipeline.py b/modelscope/pipelines/nlp/conversational_text_to_sql_pipeline.py
index 875c47fd..399dad5a 100644
--- a/modelscope/pipelines/nlp/conversational_text_to_sql_pipeline.py
+++ b/modelscope/pipelines/nlp/conversational_text_to_sql_pipeline.py
@@ -64,3 +64,6 @@ class ConversationalTextToSqlPipeline(Pipeline):
         sql = Example.evaluator.obtain_sql(inputs['predict'][0], inputs['db'])
         result = {OutputKeys.TEXT: sql}
         return result
+
+    def _collate_fn(self, data):
+        return data