remove inner api for warpctc

model_zoo/official/cv/warpctc/src/warpctc_for_train.py

@@ -14,9 +14,6 @@
 # ============================================================================
 """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.context import ParallelMode
 from mindspore.common import dtype as mstype
 from mindspore.ops import composite as C
 from mindspore.ops import functional as F
@@ -25,6 +22,7 @@ from mindspore.nn.cell import Cell
 from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
 import mindspore.nn as nn
 from mindspore.common.tensor import Tensor
+from src.model_utils.device_adapter import get_device_num
 
 compute_norm = C.MultitypeFuncGraph("compute_norm")
 
@@ -89,13 +87,10 @@ 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()
-        if parallel_mode in (ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL):
+        if get_device_num() > 1:
             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