diff --git a/modelscope/metainfo.py b/modelscope/metainfo.py
index 6c8d91fa..31bef3b8 100644
--- a/modelscope/metainfo.py
+++ b/modelscope/metainfo.py
@@ -452,9 +452,9 @@ class Datasets(object):
     """ Names for different datasets.
     """
     ClsDataset = 'ClsDataset'
-    Face2dKeypointsDataset = 'Face2dKeypointsDataset'
+    Face2dKeypointsDataset = 'FaceKeypointDataset'
     HandCocoWholeBodyDataset = 'HandCocoWholeBodyDataset'
-    HumanWholeBodyKeypointDataset = 'HumanWholeBodyKeypointDataset'
+    HumanWholeBodyKeypointDataset = 'WholeBodyCocoTopDownDataset'
     SegDataset = 'SegDataset'
     DetDataset = 'DetDataset'
     DetImagesMixDataset = 'DetImagesMixDataset'
diff --git a/modelscope/msdatasets/cv/easycv_base.py b/modelscope/msdatasets/cv/easycv_base.py
index a45827a3..7b6df6e0 100644
--- a/modelscope/msdatasets/cv/easycv_base.py
+++ b/modelscope/msdatasets/cv/easycv_base.py
@@ -26,11 +26,16 @@ class EasyCVBaseDataset(object):
         if self.split_config is not None:
             self._update_data_source(kwargs['data_source'])
 
+    def _update_data_root(self, input_dict, data_root):
+        for k, v in input_dict.items():
+            if isinstance(v, str) and self.DATA_ROOT_PATTERN in v:
+                input_dict.update(
+                    {k: v.replace(self.DATA_ROOT_PATTERN, data_root)})
+            elif isinstance(v, dict):
+                self._update_data_root(v, data_root)
+
     def _update_data_source(self, data_source):
         data_root = next(iter(self.split_config.values()))
         data_root = data_root.rstrip(osp.sep)
 
-        for k, v in data_source.items():
-            if isinstance(v, str) and self.DATA_ROOT_PATTERN in v:
-                data_source.update(
-                    {k: v.replace(self.DATA_ROOT_PATTERN, data_root)})
+        self._update_data_root(data_source, data_root)
diff --git a/requirements/cv.txt b/requirements/cv.txt
index d23fab3a..f29b296b 100644
--- a/requirements/cv.txt
+++ b/requirements/cv.txt
@@ -19,7 +19,7 @@ moviepy>=1.0.3
 networkx>=2.5
 numba
 onnxruntime>=1.10
-pai-easycv>=0.6.3.7
+pai-easycv>=0.6.3.9
 pandas
 psutil
 regex
diff --git a/tests/trainers/easycv/test_easycv_trainer_face_2d_keypoints.py b/tests/trainers/easycv/test_easycv_trainer_face_2d_keypoints.py
new file mode 100644
index 00000000..4dffa998
--- /dev/null
+++ b/tests/trainers/easycv/test_easycv_trainer_face_2d_keypoints.py
@@ -0,0 +1,71 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
+import glob
+import os
+import shutil
+import tempfile
+import unittest
+
+import torch
+
+from modelscope.metainfo import Trainers
+from modelscope.msdatasets import MsDataset
+from modelscope.trainers import build_trainer
+from modelscope.utils.constant import DownloadMode, LogKeys, Tasks
+from modelscope.utils.logger import get_logger
+from modelscope.utils.test_utils import test_level
+
+
+@unittest.skipIf(not torch.cuda.is_available(), 'cuda unittest')
+class EasyCVTrainerTestFace2DKeypoints(unittest.TestCase):
+    model_id = 'damo/cv_mobilenet_face-2d-keypoints_alignment'
+
+    def setUp(self):
+        self.logger = get_logger()
+        self.logger.info(('Testing %s.%s' %
+                          (type(self).__name__, self._testMethodName)))
+
+    def _train(self, tmp_dir):
+        cfg_options = {'train.max_epochs': 2}
+
+        trainer_name = Trainers.easycv
+
+        train_dataset = MsDataset.load(
+            dataset_name='face_2d_keypoints_dataset',
+            namespace='modelscope',
+            split='train',
+            download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS)
+        eval_dataset = MsDataset.load(
+            dataset_name='face_2d_keypoints_dataset',
+            namespace='modelscope',
+            split='train',
+            download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS)
+
+        kwargs = dict(
+            model=self.model_id,
+            train_dataset=train_dataset,
+            eval_dataset=eval_dataset,
+            work_dir=tmp_dir,
+            cfg_options=cfg_options)
+
+        trainer = build_trainer(trainer_name, kwargs)
+        trainer.train()
+
+    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    def test_trainer_single_gpu(self):
+        temp_file_dir = tempfile.TemporaryDirectory()
+        tmp_dir = temp_file_dir.name
+        if not os.path.exists(tmp_dir):
+            os.makedirs(tmp_dir)
+
+        self._train(tmp_dir)
+
+        results_files = os.listdir(tmp_dir)
+        json_files = glob.glob(os.path.join(tmp_dir, '*.log.json'))
+        self.assertEqual(len(json_files), 1)
+        self.assertIn(f'{LogKeys.EPOCH}_2.pth', results_files)
+
+        temp_file_dir.cleanup()
+
+
+if __name__ == '__main__':
+    unittest.main()