diff --git a/mindspore/nn/wrap/cell_wrapper.py b/mindspore/nn/wrap/cell_wrapper.py
index ba92cd49817..0018b5b26c9 100644
--- a/mindspore/nn/wrap/cell_wrapper.py
+++ b/mindspore/nn/wrap/cell_wrapper.py
@@ -88,7 +88,7 @@ class WithLossCell(Cell):
         TypeError: If dtype of `data` or `label` is neither float16 nor float32.
 
     Supported Platforms:
-        ``Ascend`` ``GPU``
+        ``Ascend`` ``GPU`` ``CPU``
 
     Examples:
         >>> net = Net()
@@ -150,7 +150,7 @@ class WithGradCell(Cell):
         TypeError: If `sens` is not one of None, Tensor, Scalar or Tuple.
 
     Supported Platforms:
-        ``Ascend`` ``GPU``
+        ``Ascend`` ``GPU`` ``CPU``
 
     Examples:
         >>> # For a defined network Net without loss function
@@ -304,7 +304,7 @@ class TrainOneStepCell(Cell):
         TypeError: If `sens` is not a number.
 
     Supported Platforms:
-        ``Ascend`` ``GPU``
+        ``Ascend`` ``GPU`` ``CPU``
 
     Examples:
         >>> net = Net()
@@ -605,7 +605,7 @@ class WithEvalCell(Cell):
         TypeError: If `add_cast_fp32` is not a bool.
 
     Supported Platforms:
-        ``Ascend`` ``GPU``
+        ``Ascend`` ``GPU`` ``CPU``
 
     Examples:
         >>> # For a defined network Net without loss function
@@ -642,7 +642,7 @@ class ParameterUpdate(Cell):
         KeyError: If parameter with the specified name does not exist.
 
     Supported Platforms:
-        ``Ascend``
+        ``Ascend`` ``CPU``
 
     Examples:
         >>> network = nn.Dense(3, 4)
diff --git a/mindspore/ops/composite/base.py b/mindspore/ops/composite/base.py
index f494d3fdf15..cc4ce5c3271 100644
--- a/mindspore/ops/composite/base.py
+++ b/mindspore/ops/composite/base.py
@@ -77,7 +77,7 @@ def core(fn=None, **flags):
                       other flag. Default: None.
 
     Supported Platforms:
-        ``Ascend`` ``GPU``
+        ``Ascend`` ``GPU`` ``CPU``
 
     Examples:
         >>> net = Net()
@@ -271,9 +271,9 @@ class GradOperation(GradOperation_):
         >>> print(output)
         (Tensor(shape=[2, 3], dtype=Float32, value=
         [[ 2.21099997e+00,  5.09999990e-01,  1.49000001e+00],
-         [ 5.58799982e+00,  2.68000007e+00,  4.07000017e+00]]), Tensor(shape=[3, 3], dtype=Float32, value=
+         [ 5.58800030e+00,  2.68000007e+00,  4.07000017e+00]]), Tensor(shape=[3, 3], dtype=Float32, value=
         [[ 1.51999998e+00,  2.81999993e+00,  2.14000010e+00],
-         [ 1.09999990e+00,  2.04999971e+00,  1.54999995e+00],
+         [ 1.09999990e+00,  2.04999995e+00,  1.54999995e+00],
          [ 9.00000036e-01,  1.54999995e+00,  1.25000000e+00]]))
         >>>
         >>> class GradNetWithWrtParams(nn.Cell):