fix nasnet built in function

model_zoo/official/cv/nasnet/src/nasnet_a_mobile.py

@@ -15,6 +15,7 @@
 """NASNet-A-Mobile model definition"""
 import numpy as np
 
+from mindspore import context
 from mindspore import Tensor
 import mindspore.nn as nn
 from mindspore.nn.loss.loss import Loss
@@ -24,7 +25,6 @@ import mindspore.ops.composite as C
 import mindspore.common.dtype as mstype
 from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
 from mindspore.context import ParallelMode
-from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_gradients_mean
 
 
 GRADIENT_CLIP_TYPE = 1
@@ -917,12 +917,12 @@ class NASNetAMobileTrainOneStepWithClipGradient(nn.Cell):
         self.sens = sens
         self.reducer_flag = False
         self.grad_reducer = None
-        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()
+            mean = context.get_auto_parallel_context("gradients_mean")
+            degree = context.get_auto_parallel_context("device_num")
             self.grad_reducer = DistributedGradReducer(optimizer.parameters, mean, degree)
 
     def construct(self, *inputs):