diff --git a/mmdeploy/codebase/base/task.py b/mmdeploy/codebase/base/task.py
index 813c9d93fd..1e27c35f50 100644
--- a/mmdeploy/codebase/base/task.py
+++ b/mmdeploy/codebase/base/task.py
@@ -68,7 +68,7 @@ def init_pytorch_model(self,
     def build_dataset(self,
                       dataset_cfg: Union[str, mmcv.Config],
                       dataset_type: str = 'val',
-                      is_sort_dataset: bool = True,
+                      is_sort_dataset: bool = False,
                       **kwargs) -> Dataset:
         """Build dataset for different codebase.
 
@@ -80,6 +80,7 @@ def build_dataset(self,
             is_sort_dataset (bool): When 'True', the dataset will be sorted
                 by image shape in ascending order if 'dataset_cfg'
                 contains information about height and width.
+                Default is `False`.
 
         Returns:
             Dataset: The built dataset.
diff --git a/tools/test.py b/tools/test.py
index 139f9bdfbb..d3957a19d4 100644
--- a/tools/test.py
+++ b/tools/test.py
@@ -107,9 +107,7 @@ def main():
 
     # prepare the dataset loader
     dataset_type = 'test'
-
-    dataset = task_processor.build_dataset(
-        model_cfg, dataset_type, is_sort_dataset=False)
+    dataset = task_processor.build_dataset(model_cfg, dataset_type)
     # override samples_per_gpu that used for training
     model_cfg.data['samples_per_gpu'] = args.batch_size
     data_loader = task_processor.build_dataloader(