diff --git a/mindspore/dataset/text/utils.py b/mindspore/dataset/text/utils.py
index 1dc3012ce95..3a1eeaea8eb 100644
--- a/mindspore/dataset/text/utils.py
+++ b/mindspore/dataset/text/utils.py
@@ -217,7 +217,7 @@ def to_str(array, encoding='utf8'):
 
     Args:
         array (numpy.ndarray): Array of type `bytes` representing strings.
-        encoding (string): Indicating the charset for decoding.
+        encoding (str): Indicating the charset for decoding.
 
     Returns:
         numpy.ndarray, numpy array of `str`.
diff --git a/mindspore/dataset/transforms/c_transforms.py b/mindspore/dataset/transforms/c_transforms.py
index b99e6a69d7b..910c56182c1 100644
--- a/mindspore/dataset/transforms/c_transforms.py
+++ b/mindspore/dataset/transforms/c_transforms.py
@@ -78,9 +78,9 @@ class Slice(cde.SliceOp):
     (Currently only rank-1 tensors are supported).
 
     Args:
-        *slices(Variable length argument list, supported types are, int, list(int), slice, None or Ellipses):
-            Maximum `n` number of arguments to slice a tensor of rank `n`.
-            One object in slices can be one of:
+        slices(Variable length argument list, supported types are, int, list[int], slice, None or Ellipses):
+            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. Negative index is supported.
             2.  :py:obj:`list(int)`: Slice these indices ion the list only. Negative indices are supported.
             3.  :py:obj:`slice`: Slice the generated indices from the slice object. Similar to `start:stop:step`.
diff --git a/mindspore/dataset/transforms/vision/py_transforms.py b/mindspore/dataset/transforms/vision/py_transforms.py
index 07630b96cc9..7b994c31174 100644
--- a/mindspore/dataset/transforms/vision/py_transforms.py
+++ b/mindspore/dataset/transforms/vision/py_transforms.py
@@ -100,7 +100,7 @@ class ToTensor:
         The range of channel dimension remains the same.
 
     Args:
-        output_type (numpy datatype, optional): The datatype of the numpy output (default=np.float32).
+        output_type (numpy datatype, optional): The datatype of the numpy output (default=numpy.float32).
 
     Examples:
         >>> py_transforms.ComposeOp([py_transforms.Decode(),
@@ -129,7 +129,7 @@ class ToType:
     Convert the input Numpy image array to desired numpy dtype.
 
     Args:
-        output_type (numpy datatype): The datatype of the numpy output. e.g. np.float32.
+        output_type (numpy datatype): The datatype of the numpy output, e.g. numpy.float32.
 
     Examples:
         >>> import numpy as np