diff --git a/mindspore/nn/learning_rate_schedule.py b/mindspore/nn/learning_rate_schedule.py
index bf7ea4c5939..a83cf9967b6 100644
--- a/mindspore/nn/learning_rate_schedule.py
+++ b/mindspore/nn/learning_rate_schedule.py
@@ -280,8 +280,8 @@ class CosineDecayLR(LearningRateSchedule):
         ValueError: If `min_lr` is less than 0 or `decay_steps` is less than 1.
         ValueError: If `max_lr` is less than or equal to 0.
 
-        Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+    Supported Platforms:
+        ``Ascend`` ``GPU``
 
     Examples:
         >>> min_lr = 0.01
@@ -357,7 +357,7 @@ class PolynomialDecayLR(LearningRateSchedule):
         ValueError: If `learning_rate` or `power` is less than or equal to 0.
 
     Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+        ``Ascend`` ``GPU``
 
     Examples:
         >>> learning_rate = 0.1
@@ -436,7 +436,7 @@ class WarmUpLR(LearningRateSchedule):
         ValueError: If `learning_rate` is less than or equal to 0.
 
     Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+        ``Ascend`` ``GPU``
 
     Examples:
         >>> learning_rate = 0.1
diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index eb0de0287d1..d25bd84eb85 100644
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -5240,7 +5240,7 @@ class Range(PrimitiveWithCheck):
        A 1-D Tensor, with the same type as the inputs.
 
     Supported Platforms:
-        ``GPU``
+        ``GPU`` `CPU`
 
     Examples:
         >>> start = Tensor(0, mstype.int32)