fix check dtype in comm_ops.py

mindspore/ops/operations/comm_ops.py

@@ -39,6 +39,8 @@ class ReduceOp:
     PROD = "prod"
 
 
+target_dtypes = (mstype.int8, mstype.int32, mstype.float16, mstype.float32)
+
 class AllReduce(PrimitiveWithInfer):
     """
     Reduces the tensor data across all devices in such a way that all devices will get the same final result.
@@ -102,8 +104,7 @@ class AllReduce(PrimitiveWithInfer):
         return x_shape
 
     def infer_dtype(self, x_dtype):
-        if x_dtype.element_type() == mstype.bool_:
-            raise TypeError("AllReduce does not support 'Bool' as the dtype of input!")
+        validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
         return x_dtype
 
 
@@ -161,8 +162,7 @@ class AllGather(PrimitiveWithInfer):
         return x_shape
 
     def infer_dtype(self, x_dtype):
-        if x_dtype.element_type() == mstype.bool_:
-            raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
+        validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
         return x_dtype
 
     def __call__(self, tensor):
@@ -219,8 +219,7 @@ class ReduceScatter(PrimitiveWithInfer):
         return x_shape
 
     def infer_dtype(self, x_dtype):
-        if x_dtype.element_type() == mstype.bool_:
-            raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
+        validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
         return x_dtype
 
     def __call__(self, tensor):
@@ -279,8 +278,7 @@ class Broadcast(PrimitiveWithInfer):
         if not isinstance(x_dtype, tuple):
             raise TypeError(f"{self.name}'s input should be a tuple!")
         for _ele in x_dtype:
-            if _ele.element_type() == mstype.bool_:
-                raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
+            validator.check_tensor_type_same({'x': _ele}, target_dtypes, self.name)
         return x_dtype
 
 
@@ -322,8 +320,7 @@ class _AlltoAll(PrimitiveWithInfer):
         return x_shape
 
     def infer_dtype(self, x_dtype):
-        if x_dtype.element_type() == mstype.bool_:
-            raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
+        validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
         return x_dtype
 
     def __call__(self, tensor):