!3566 dataset: api format problem in totype, totensor, slice

Merge pull request !3566 from ms_yan/r0.6_api_format

mindspore/dataset/text/utils.py

@@ -210,7 +210,7 @@ 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`.

mindspore/dataset/transforms/c_transforms.py

@@ -78,11 +78,11 @@ 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(Union[int, list[int], slice, None, 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.
+            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`.
             4.  :py:obj:`None`: Slice the whole dimension. Similar to `:` in python indexing.
             5.  :py:obj:`Ellipses`: Slice all dimensions between the two slices. Similar to `...` in python indexing.

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