From ba9b30253a7f52e4bf0fae36cef6365604036b22 Mon Sep 17 00:00:00 2001
From: lilei <lilei120@huawei.com>
Date: Thu, 9 Dec 2021 21:28:54 +0800
Subject: [PATCH] modify while list

---
 mindspore/nn/wrap/cell_wrapper.py            |  3 +++
 mindspore/parallel/_auto_parallel_context.py | 16 ++++++++--------
 2 files changed, 11 insertions(+), 8 deletions(-)

diff --git a/mindspore/nn/wrap/cell_wrapper.py b/mindspore/nn/wrap/cell_wrapper.py
index 92a84d2096a..123baaea942 100644
--- a/mindspore/nn/wrap/cell_wrapper.py
+++ b/mindspore/nn/wrap/cell_wrapper.py
@@ -471,6 +471,9 @@ class MicroBatchInterleaved(Cell):
         network (Cell): The target network to wrap.
         interleave_num (int): split num of batch size. Default: 2.
 
+    Supported Platforms:
+        ``Ascend`` ``GPU``
+
     Examples:
         >>> net = Net()
         >>> net = MicroBatchInterleaved(net, 4)
diff --git a/mindspore/parallel/_auto_parallel_context.py b/mindspore/parallel/_auto_parallel_context.py
index 921c98c6da1..ad0be70ea44 100644
--- a/mindspore/parallel/_auto_parallel_context.py
+++ b/mindspore/parallel/_auto_parallel_context.py
@@ -203,10 +203,10 @@ class _AutoParallelContext:
     def set_pipeline_stages(self, stages):
         """Set the stages of the pipeline"""
         if isinstance(stages, bool) or not isinstance(stages, int):
-            raise TypeError("For 'set_auto_parallel_context().set_pipeline_stages', the argument 'pipeline_stages' "
+            raise TypeError("For 'set_auto_parallel_context', the argument 'pipeline_stages' "
                             "must be int, but got the type : {}.".format(type(stages)))
         if stages < 1:
-            raise ValueError("For 'set_auto_parallel_context().set_pipeline_stages', the argument 'pipeline_stages' "
+            raise ValueError("For 'set_auto_parallel_context', the argument 'pipeline_stages' "
                              "should be greater or equal 1, but got the value of stages : {}.".format(stages))
         self.check_context_handle()
         self._context_handle.set_pipeline_stage_split_num(stages)
@@ -266,7 +266,7 @@ class _AutoParallelContext:
             loss_repeated_mean (bool): The loss_repeated_mean flag.
         """
         if not isinstance(loss_repeated_mean, bool):
-            raise TypeError("For 'auto_parallel_context().set_loss_repeated_mean', the argument 'loss_repeated_mean' "
+            raise TypeError("For 'auto_parallel_context', the argument 'loss_repeated_mean' "
                             "must be bool, but got the type : {}.".format(type(loss_repeated_mean)))
         self.check_context_handle()
         self._context_handle.set_loss_repeated_mean(loss_repeated_mean)
@@ -431,22 +431,22 @@ class _AutoParallelContext:
         self.check_context_handle()
         if isinstance(dataset_strategy, str):
             if dataset_strategy not in ("full_batch", "data_parallel"):
-                raise ValueError("For 'set_auto_parallel_context().set_dataset_strategy', the argument "
+                raise ValueError("For 'set_auto_parallel_context', the argument "
                                  "'dataset_strategy' must be 'full_batch' or 'data_parallel', but got the value : {}."
                                  .format(dataset_strategy))
             self._context_handle.set_full_batch(dataset_strategy == "full_batch")
             self._dataset_strategy_using_str = True
             return
         if not isinstance(dataset_strategy, tuple):
-            raise TypeError("For 'set_auto_parallel_context().set_dataset_strategy', the argument 'dataset_strategy' "
+            raise TypeError("For 'set_auto_parallel_context', the argument 'dataset_strategy' "
                             "must be str or tuple type, but got the type : {}.".format(type(dataset_strategy)))
         for ele in dataset_strategy:
             if not isinstance(ele, tuple):
-                raise TypeError("For 'set_auto_parallel_context().set_dataset_strategy', the element of argument "
+                raise TypeError("For 'set_auto_parallel_context', the element of argument "
                                 "'dataset_strategy' must be tuple, but got the type : {} .".format(type(ele)))
             for dim in ele:
                 if not isinstance(dim, int):
-                    raise TypeError("For 'set_auto_parallel_context().set_dataset_strategy', the element of argument "
+                    raise TypeError("For 'set_auto_parallel_context', the element of argument "
                                     "'dataset_strategy' must be int type, but got the type : {} .".format(type(dim)))
         self._dataset_strategy_using_str = False
         self._context_handle.set_dataset_strategy(dataset_strategy)
@@ -645,7 +645,7 @@ class _AutoParallelContext:
         """
         self.check_context_handle()
         if not isinstance(enable_parallel_optimizer, bool):
-            raise TypeError("For 'set_auto_parallel_context().set_enable_parallel_optimizer', "
+            raise TypeError("For 'set_auto_parallel_context', "
                             "the argument 'enable_parallel_optimizer' must be bool, but got the type : {}."
                             .format(type(enable_parallel_optimizer)))
         self._context_handle.set_enable_parallel_optimizer(enable_parallel_optimizer)