diff --git a/model_zoo/official/cv/crnn/src/crnn_for_train.py b/model_zoo/official/cv/crnn/src/crnn_for_train.py
index 8d767ade348..fad288c36f4 100644
--- a/model_zoo/official/cv/crnn/src/crnn_for_train.py
+++ b/model_zoo/official/cv/crnn/src/crnn_for_train.py
@@ -14,8 +14,7 @@
 # ============================================================================
 """Automatic differentiation with grad clip."""
 import numpy as np
-from mindspore.parallel._utils import (_get_device_num, _get_gradients_mean,
-                                       _get_parallel_mode)
+from mindspore import context
 from mindspore.context import ParallelMode
 from mindspore.common import dtype as mstype
 from mindspore.ops import composite as C
@@ -89,13 +88,11 @@ class TrainOneStepCellWithGradClip(Cell):
         self.cast = P.Cast()
         self.concat = P.Concat(axis=0)
         self.ten = Tensor(np.array([10.0]).astype(np.float32))
-        parallel_mode = _get_parallel_mode()
+        parallel_mode = context.get_auto_parallel_context("parallel_mode")
         if parallel_mode in (ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL):
             self.reducer_flag = True
         if self.reducer_flag:
-            mean = _get_gradients_mean()
-            degree = _get_device_num()
-            self.grad_reducer = DistributedGradReducer(optimizer.parameters, mean, degree)
+            self.grad_reducer = DistributedGradReducer(optimizer.parameters)
 
     def construct(self, data, label):
         weights = self.weights