!13232 add parallel validation

From: @gong_zi_yan
Reviewed-by: @stsuteng,@kisnwang
Signed-off-by: @stsuteng

mindspore/common/parameter.py

@@ -19,6 +19,8 @@ import numbers
 import numpy as np
 from .._c_expression import ParamInfo
 from . import dtype as mstype
+from .. import context
+from ..parallel._utils import _get_parallel_mode
 from .initializer import initializer
 from .tensor import Tensor
 from .._checkparam import Validator
@@ -292,7 +294,18 @@ class Parameter(Tensor_):
 
     @comm_fusion.setter
     def comm_fusion(self, comm_fusion_):
-        """Set the fusion type for communication operators corresponding to this parameter."""
+        """
+        In `AUTO_PARALLEL` and `SEMI_AUTO_PARALLEL` mode, some communication operators used for parameters or
+        gradients aggregation are inserted automatically.Set the fusion type for communication operators generated
+        for this parameter. Only `Ascend` and `Graph` mode is supported.
+
+        Args:
+            comm_fusion_ (int): The value of fusion must be greater than or equal to 0.
+                                When the value of fusion is 0, operators will not be fused together.
+        """
+        if context.get_context("mode") == context.PYNATIVE_MODE and "auto_parallel" in _get_parallel_mode():
+            raise RuntimeError("`comm_fusion` does not support PYNATIVE_MODE")
+        Validator.check_non_negative_int(comm_fusion_)
         self.param_info.comm_fusion = comm_fusion_
 
     @property

mindspore/nn/cell.py

@@ -1129,7 +1129,18 @@ class Cell(Cell_):
             param.set_param_ps(init_in_server)
 
     def set_comm_fusion(self, fusion_type, recurse=True):
-        Validator.check_is_int(fusion_type)
+        """
+        Set `comm_fusion` for all the parameters in the Net. Please refer to the description of
+        `mindspore.common.parameter.comm_fusion`.
+
+        Note:
+            The value of attribute will be overwritten when the function is called multiply.
+
+        Args:
+            fusion_type (int): The value of `comm_fusion`.
+            recurse (bool): Whether sets the trainable parameters of subcells. Default: True.
+        """
+        Validator.check_non_negative_int(fusion_type)
         for param in self.trainable_params(recurse):
             param.comm_fusion = fusion_type
         return self