!2323 [CT][MS][Auto-Parallel]Recursive interface needs to be changed to external interface

Merge pull request !2323 from Chong/interface

mindspore/context.py

@@ -381,8 +381,8 @@ def _context():
 
 
 @args_type_check(device_num=int, global_rank=int, mirror_mean=bool, cast_before_mirror=bool, parallel_mode=str,
-                 parameter_broadcast=bool, strategy_ckpt_load_file=str, strategy_ckpt_save_file=str,
-                 full_batch=bool)
+                 auto_parallel_search_mode=str, parameter_broadcast=bool, strategy_ckpt_load_file=str,
+                 strategy_ckpt_save_file=str, full_batch=bool)
 def set_auto_parallel_context(**kwargs):
     """
     Set auto parallel context.
@@ -414,6 +414,12 @@ def set_auto_parallel_context(**kwargs):
                        setting parallel strategies.
 
                      - auto_parallel: Achieving parallelism automatically.
+        auto_parallel_search_mode (str): There are two kinds of search modes, "recursive_programming"
+                     and "dynamic_programming".
+
+                     - recursive_programming: Recursive programming search mode.
+
+                     - dynamic_programming: Dynamic programming search mode.
         parameter_broadcast (bool): Indicating whether to broadcast parameters before training.
                        "stand_alone", "semi_auto_parallel" and "auto_parallel" do not support parameter
                        broadcast. Default: False.

mindspore/parallel/_auto_parallel_context.py

@@ -185,13 +185,20 @@ class _AutoParallelContext:
         self.check_context_handle()
         return self._context_handle.get_parallel_mode()
 
-    def set_strategy_search_mode(self, strategy_search_mode):
+    def set_strategy_search_mode(self, auto_parallel_search_mode):
+        """
+        Set search mode of strategy.
+
+        Args:
+            auto_parallel_search_mode (str): The search mode of strategy.
+        """
         self.check_context_handle()
-        ret = self._context_handle.set_strategy_search_mode(strategy_search_mode)
+        ret = self._context_handle.set_strategy_search_mode(auto_parallel_search_mode)
         if ret is False:
-            raise ValueError("Strategy search mode does not support {}".format(strategy_search_mode))
+            raise ValueError("Strategy search mode does not support {}".format(auto_parallel_search_mode))
 
     def get_strategy_search_mode(self):
+        """Get search mode of strategy."""
         self.check_context_handle()
         return self._context_handle.get_strategy_search_mode()
 
@@ -422,6 +429,7 @@ _set_auto_parallel_context_func_map = {
     "cast_before_mirror": auto_parallel_context().set_cast_before_mirror,
     "loss_repeated_mean": auto_parallel_context().set_loss_repeated_mean,
     "parallel_mode": auto_parallel_context().set_parallel_mode,
+    "auto_parallel_search_mode": auto_parallel_context().set_strategy_search_mode,
     "parameter_broadcast": auto_parallel_context().set_parameter_broadcast,
     "strategy_ckpt_load_file": auto_parallel_context().set_strategy_ckpt_load_file,
     "strategy_ckpt_save_file": auto_parallel_context().set_strategy_ckpt_save_file,
@@ -435,6 +443,7 @@ _get_auto_parallel_context_func_map = {
     "cast_before_mirror": auto_parallel_context().get_cast_before_mirror,
     "loss_repeated_mean": auto_parallel_context().get_loss_repeated_mean,
     "parallel_mode": auto_parallel_context().get_parallel_mode,
+    "auto_parallel_search_mode": auto_parallel_context().get_strategy_search_mode,
     "parameter_broadcast": auto_parallel_context().get_parameter_broadcast,
     "strategy_ckpt_load_file": auto_parallel_context().get_strategy_ckpt_load_file,
     "strategy_ckpt_save_file": auto_parallel_context().get_strategy_ckpt_save_file,
@@ -442,8 +451,9 @@ _get_auto_parallel_context_func_map = {
 
 
 @args_type_check(device_num=int, global_rank=int, mirror_mean=bool, cast_before_mirror=bool,
-                 loss_repeated_mean=bool, parallel_mode=str, parameter_broadcast=bool,
-                 strategy_ckpt_load_file=str, strategy_ckpt_save_file=str, full_batch=bool)
+                 loss_repeated_mean=bool, parallel_mode=str, auto_parallel_search_mode=str,
+                 parameter_broadcast=bool, strategy_ckpt_load_file=str,
+                 strategy_ckpt_save_file=str, full_batch=bool)
 def _set_auto_parallel_context(**kwargs):
     """
     Set auto parallel context.
@@ -471,6 +481,12 @@ def _set_auto_parallel_context(**kwargs):
                        setting parallel strategies.
 
                      - auto_parallel: Achieving parallelism automatically.
+        auto_parallel_search_mode (str): There are two kinds of search modes, "recursive_programming"
+                     and "dynamic_programming".
+
+                     - recursive_programming: Recursive programming search mode.
+
+                     - dynamic_programming: Dynamic programming search mode.
         parameter_broadcast (bool): Indicating whether to broadcast parameters before training.
                        "stand_alone", "semi_auto_parallel" and "auto_parallel" do not support parameter
                        broadcast. Default: False.