modify tensor comment

mindspore/common/tensor.py

@@ -567,7 +567,7 @@ class Tensor(Tensor_):
         return tensor_operator_registry.get('any')(keep_dims)(self, axis)
 
     def view(self, *shape):
-        r"""
+        """
         Reshape the tensor according to the input shape.
 
         Args:
@@ -675,7 +675,7 @@ class Tensor(Tensor_):
 
     def transpose(self, *axes):
         r"""
-        Return a view of the tensor with axes transposed.
+        Return a tensor with axes transposed.
 
         - For a 1-D tensor, this has no effect, as a transposed vector is simply the same vector.
         - For a 2-D tensor, this is a standard matrix transpose.
@@ -696,7 +696,7 @@ class Tensor(Tensor_):
 
         Raises:
             TypeError: If input arguments have types not specified above.
-            ValueError: If the number of `axes` is not equal to a.ndim.
+            ValueError: If the number of `axes` is not equal to Tensor's ndim.
 
         Supported Platforms:
             ``Ascend`` ``GPU`` ``CPU``
@@ -727,8 +727,8 @@ class Tensor(Tensor_):
             Tensor, with new specified shape.
 
         Raises:
-            TypeError: If new_shape is not integer, list or tuple.
-            ValueError: If new_shape is not compatible with the original shape.
+            TypeError: If new shape is not integer, list or tuple.
+            ValueError: If new shape is not compatible with the original shape.
 
         Supported Platforms:
             ``Ascend`` ``GPU`` ``CPU``
@@ -863,7 +863,7 @@ class Tensor(Tensor_):
 
     def squeeze(self, axis=None):
         """
-        Remove single-dimensional entries from the shape of a tensor.
+        Remove the dimension of shape 1 from the Tensor
 
         Args:
             axis (Union[None, int, list(int), tuple(int)], optional): Selects a subset of the entries of
@@ -875,7 +875,7 @@ class Tensor(Tensor_):
 
         Raises:
             TypeError: If input arguments have types not specified above.
-            ValueError: If specified axis has shape entry :math:`> 1`.
+            ValueError: If axis is greater than one.
 
         Supported Platforms:
             ``Ascend`` ``GPU`` ``CPU``
@@ -1026,7 +1026,7 @@ class Tensor(Tensor_):
             >>> print(a.argmin())
             0
         """
-        # P.Argmax only supports float
+        # P.Argmin only supports float
         a = self.astype(mstype.float32)
         if axis is None:
             a = a.ravel()
@@ -1213,7 +1213,6 @@ class Tensor(Tensor_):
             :func:`mindspore.Tensor.max`: Return the maximum of a tensor or maximum along an axis.
 
         Examples:
-            >>> import numpy as np
             >>> from mindspore import Tensor
             >>> import mindspore.numpy as np
             >>> a = Tensor(np.arange(4).reshape((2,2)).astype('float32'))
@@ -1239,7 +1238,7 @@ class Tensor(Tensor_):
             value (Union[None, int, float, bool]): All elements of a will be assigned this value.
 
         Returns:
-            Tensor, with the original dtype and shape as input tensor.
+            Tensor, with the original dtype and shape.
 
         Raises:
             TypeError: If input arguments have types not specified above.
@@ -1552,7 +1551,7 @@ class Tensor(Tensor_):
                 second axis.
 
         Returns:
-            Tensor, if `a` is 2-D, then `a` 1-D array containing the diagonal.
+            Tensor, if Tensor is 2-D, return a 1-D Tensor containing the diagonal.
 
         Raises:
             ValueError: if the input tensor has less than two dimensions.
@@ -1843,7 +1842,7 @@ class Tensor(Tensor_):
         shape = v.shape
         if sorter is not None:
             if sorter.ndim != 1 or sorter.size != a.size:
-                raise ValueError('sorter must be 1-D array with the same size as `a`')
+                raise ValueError('sorter must be 1-D array with the same size as the Tensor')
             sorter = tensor_operator_registry.get('make_tensor')(sorter)
             sorter = sorter.reshape(sorter.shape + (1,))
             a = tensor_operator_registry.get('gather_nd')(a, sorter)

mindspore/train/callback/_callback.py

@@ -80,6 +80,10 @@ class Callback:
     You can use this mechanism to initialize and release resources automatically.
 
     Callback function will execute some operations in the current step or epoch.
+    To create a custom callback, subclass Callback and override the method associated
+    with the stage of interest. See
+    https://www.mindspore.cn/docs/programming_guide/zh-CN/master/custom_debugging_info.html#callback
+    for more information.
 
     It holds the information of the model. Such as `network`, `train_network`, `epoch_num`, `batch_num`,
     `loss_fn`, `optimizer`, `parallel_mode`, `device_number`, `list_callback`, `cur_epoch_num`,