p60975123
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!17717 modify tensor api document 

From: @huangbingjian
Reviewed-by: @zh_qh,@ginfung
Signed-off-by: @zh_qh
This commit is contained in:
mindspore-ci-bot 2021-06-04 17:46:09 +08:00 committed by Gitee
parent 08847d2f64 3bac020c8a
commit 3d76d462d1
2 changed files with 35 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
mindspore/_extends/parse/standard_method.py
View File

@ -56,14 +56,23 @@ def mean(x, axis=(), keep_dims=False):
Reduces a dimension of a tensor by averaging all elements in the dimension.
Args:
axis (Union[None, int, tuple(int)]): Dimensions of reduction,
when axis is None or empty tuple, reduce all dimensions.
Default: (), reduce all dimensions.
keep_dims (bool): Whether to keep the reduced dimensions.
Default : False, don't keep these reduced dimensions.
axis (Union[None, int, tuple(int), list(int)]): Dimensions of reduction,
when axis is None or empty tuple, reduce all dimensions. Default: ().
keep_dims (bool): Whether to keep the reduced dimensions. Default: False.
Returns:
Tensor, has the same data type as x.
Tensor, has the same data type as input tensor.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> import numpy as np
>>> from mindspore import Tensor
>>> input_x = Tensor(np.array([1, 2, 3], dtype=np.float32))
>>> output = input_x.mean()
>>> print(output)
2.0
"""
if axis is None:
axis = ()
@ -501,7 +510,7 @@ def cumsum(x, axis=None, dtype=None):
>>> import numpy as np
>>> from mindspore import Tensor
>>> a = Tensor(np.ones((3,3)).astype("float32"))
>>> output = a.cumsum()
>>> output = a.cumsum(axis=0)
>>> print(output)
[[1. 1. 1.]
[2. 2. 2.]
@ -909,8 +918,7 @@ def choose(x, choices, mode='clip'):
Examples:
>>> import mindspore.numpy as np
>>> choices = [[0, 1, 2, 3], [10, 11, 12, 13],
[20, 21, 22, 23], [30, 31, 32, 33]]
>>> choices = [[0, 1, 2, 3], [10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33]]
>>> x = np.array([2, 3, 1, 0])
>>> print(x.choose(choices))
[20 31 12 3]

26
mindspore/common/tensor.py
View File

@ -491,7 +491,18 @@ class Tensor(Tensor_):
keep_dims (bool): Whether to keep the reduced dimensions. Default: False.
Returns:
Tensor, has the same data type as x.
Tensor, has the same data type as input tensor.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> import numpy as np
>>> from mindspore import Tensor
>>> input_x = Tensor(np.array([1, 2, 3], dtype=np.float32))
>>> output = input_x.mean()
>>> print(output)
2.0
"""
self.init_check()
if axis is None:
@ -839,7 +850,7 @@ class Tensor(Tensor_):
>>> import numpy as np
>>> from mindspore import Tensor
>>> a = Tensor(np.ones((3,3)).astype("float32"))
>>> output = a.cumsum()
>>> output = a.cumsum(axis=0)
>>> print(output)
[[1. 1. 1.]
[2. 2. 2.]
@ -1464,8 +1475,7 @@ class Tensor(Tensor_):
Examples:
>>> import numpy as np
>>> from mindspore import Tensor
>>> choices = [[0, 1, 2, 3], [10, 11, 12, 13],
[20, 21, 22, 23], [30, 31, 32, 33]]
>>> choices = [[0, 1, 2, 3], [10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33]]
>>> x = Tensor(np.array([2, 3, 1, 0]))
>>> print(x.choose(choices))
[20 31 12 3]
@ -1651,7 +1661,7 @@ class Tensor(Tensor_):
Examples:
>>> import numpy as np
>>> from mindspore import Tensor
>>> input_x = Tensor(np.array([1., 2., 3., 4.]))
>>> input_x = Tensor(np.array([1, 2, 3, 4], dtype=np.float32))
>>> output = input_x.std()
>>> print(output)
1.118034
@ -1697,10 +1707,10 @@ class Tensor(Tensor_):
Examples:
>>> import numpy as np
>>> from mindspore import Tensor
>>> input_x = Tensor(np.array([-1, 0, 1]).astype('int32'))
>>> input_x = Tensor(np.array([-1, 0, 1]).astype(np.float32))
>>> print(input_x.sum())
0
>>> input_x = Tensor(np.arange(10).reshape(2, 5).astype('float32'))
0.0
>>> input_x = Tensor(np.arange(10).reshape(2, 5).astype(np.float32))
>>> print(input_x.sum(axis=1))
[10. 35.]
"""