diff --git a/mindspore/common/parameter.py b/mindspore/common/parameter.py
index a9614855f3..2135bb9d86 100644
--- a/mindspore/common/parameter.py
+++ b/mindspore/common/parameter.py
@@ -502,9 +502,11 @@ class Parameter(Tensor_):
         Args:
             layout (Union[None, list(list(int))]): Parameter slice
                 layout [dev_mat, tensor_map, slice_shape]. Default: None.
+
                 - dev_mat (list(int)): Device matrix.
                 - tensor_map (list(int)): Tensor map.
                 - slice_shape (list(int)): Shape of slice.
+
             set_sliced (bool): True if the parameter is set sliced after initializing the data.
                 Default: False.
 
diff --git a/mindspore/dataset/transforms/c_transforms.py b/mindspore/dataset/transforms/c_transforms.py
index 463e1be14b..dcea2feb3c 100644
--- a/mindspore/dataset/transforms/c_transforms.py
+++ b/mindspore/dataset/transforms/c_transforms.py
@@ -164,15 +164,15 @@ class Slice(cde.SliceOp):
     (Currently only rank-1 tensors are supported).
 
     Args:
-        *slices(Union[int, list(int), slice, None, Ellipsis]):
-            Maximum `n` number of arguments to slice a tensor of rank `n`.
+        slices (Union[int, list[int], slice, None, Ellipsis]):
+            Maximum `n` number of arguments to slice a tensor of rank `n` .
             One object in slices can be one of:
 
             1.  :py:obj:`int`: Slice this index only along the first dimension. Negative index is supported.
             2.  :py:obj:`list(int)`: Slice these indices along the first dimension. Negative indices are supported.
             3.  :py:obj:`slice`: Slice the generated indices from the slice object along the first dimension.
                 Similar to start:stop:step.
-            4.  :py:obj:`None`: Slice the whole dimension. Similar to :py:obj:`[:]' in Python indexing.
+            4.  :py:obj:`None`: Slice the whole dimension. Similar to :py:obj:`[:]` in Python indexing.
             5.  :py:obj:`Ellipsis`: Slice the whole dimension, same result with `None`.
 
     Examples:
diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index 07dba39610..a746af6d62 100644
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -1887,6 +1887,7 @@ class Tile(PrimitiveWithInfer):
 
     Outputs:
         Tensor, has the same data type as the `input_x`.
+
         - If the length of `multiples` is the same as the length of shape of `input_x`,
           then the shape of their corresponding positions can be multiplied, and
           the shape of Outputs is :math:`(x_1*y_1, x_2*y_2, ..., x_S*y_R)`.
diff --git a/mindspore/ops/operations/sponge_ops.py b/mindspore/ops/operations/sponge_ops.py
index bc436e8384..85e6cfafb7 100644
--- a/mindspore/ops/operations/sponge_ops.py
+++ b/mindspore/ops/operations/sponge_ops.py
@@ -901,11 +901,10 @@ class Dihedral14LJForce(PrimitiveWithInfer):
         F = k*(-12*A/|dr|^{14} + 6*B/|dr|^{8})*dr
 
     Args:
-        dihedral_14_numbers(int32): the number of necessary dihedral 1,4 terms M.
-        atom_numbers(int32): the number of atoms N.
+        dihedral_14_numbers (int32): the number of necessary dihedral 1,4 terms M.
+        atom_numbers (int32): the number of atoms N.
 
     Inputs:
-
         - **uint_crd_f** (Tensor, uint32) - [N, 3], the unsigned int coordinate value of each atom.
         - **LJ_type** (Tensor, int32) - [N,], the Lennard-Jones type of each atom.
         - **charge** (Tensor, float32) - [N,], the charge of each atom.