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!68998 Fix reduce all doc 

Merge pull request !68998 from jiangchenglin3/code_docs_master
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i-robot 2024-05-06 03:23:20 +00:00 committed by Gitee
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mindspore/core/ops/ops_def/doc/reduce_all_doc.yaml
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@ -1,36 +1,36 @@
reduce_all:
description: |
Reduces a dimension of a tensor by the "logicalAND" of all elements in the dimension, by default. And also can
reduce a dimension of `x` along the `axis`. Determine whether the dimensions of the output and input are the
Reduces a dimension of `input` by the "logical AND" of all elements in the dimension, by default. And also can
reduce a dimension of `input` along the `axis`. Determine whether the dimensions of the output and input are the
same by controlling `keep_dims`.
Note:
The `axis` with tensor type is only used for compatibility with older versions and is not recommended.
Args:
keep_dims (bool): If ``True`` , keep these reduced dimensions and the length is 1.
If ``False`` , don't keep these dimensions. Default: ``False`` .
input (Tensor): Input Tensor, has the shape :math:`(N, *)` where :math:`*` means,
any number of additional dimensions.
axis (Union[int, tuple(int), list(int), Tensor], optional): The dimensions to reduce.
Suppose the rank of `input` is r, `axis` must be in the range [-rank(input), rank(input)).
Default: ``None`` , all dimensions are reduced.
keep_dims (bool, optional): If ``True`` , keep these reduced dimensions and the length is 1.
If ``False`` , don't keep these dimensions. Default : ``False`` .
Inputs:
- **x** (Tensor[bool]) - The input tensor. The dtype of the tensor to be reduced is bool.
- **axis** (Union[int, tuple(int), list(int), Tensor]) - The dimensions to reduce. Default: ``()`` ,
reduce all dimensions. Only constant value is allowed. Must be in the range [-rank(x), rank(x)).
Outputs:
Returns:
Tensor, the dtype is bool.
- If `axis` is ``()`` , and `keep_dims` is ``False`` ,
the output is a 0-D tensor representing the "logical and" of all elements in the input tensor.
- If `axis` is int, set as 2, and `keep_dims` is ``False`` ,
the shape of output is :math:`(x_1, x_3, ..., x_R)`.
- If `axis` is tuple(int), set as (2, 3), and `keep_dims` is ``False`` ,
the shape of output is :math:`(x_1, x_4, ..., x_R)`.
- If `axis` is 1-D Tensor, set as [2, 3], and `keep_dims` is ``False`` ,
the shape of output is :math:`(x_1, x_4, ..., x_R)`.
- If `axis` is ``None`` , and `keep_dims` is ``False`` ,
the output is a 0-D Tensor representing the "logical AND" of all elements in the input Tensor.
- If `axis` is int, such as 2, and `keep_dims` is ``False`` ,
the shape of output is :math:`(input_1, input_3, ..., input_R)`.
- If `axis` is tuple(int), such as (2, 3), and `keep_dims` is ``False`` ,
the shape of output is :math:`(input_1, input_4, ..., input_R)`.
- If `axis` is 1-D Tensor, such as [2, 3], and `keep_dims` is ``False`` ,
the shape of output is :math:`(input_1, input_4, ..., input_R)`.
Raises:
TypeError: If `keep_dims` is not a bool.
TypeError: If `x` is not a Tensor.
TypeError: If `input` is not a Tensor.
TypeError: If `axis` is not one of the following: int, tuple, list or Tensor.
Supported Platforms:
@ -40,25 +40,17 @@ reduce_all:
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[True, False], [True, True]]))
>>> op = ops.ReduceAll(keep_dims=True)
>>> # case 1: Reduces a dimension by the "logicalAND" of all elements in the dimension.
>>> output = op(x)
>>> output = ops.all(x, keep_dims=True)
>>> print(output)
[[False]]
>>> print(output.shape)
(1, 1)
>>> # case 2: Reduces a dimension along axis 0.
>>> output = op(x, 0)
>>> output = ops.all(x, axis=0)
>>> print(output)
[[ True False]]
[ True False]
>>> # case 3: Reduces a dimension along axis 1.
>>> output = op(x, 1)
>>> output = ops.all(x, axis=1)
>>> print(output)
[[False]
[ True]]
>>> # case 4: input is a scalar.
>>> x = Tensor(True)
>>> op = ops.ReduceAll()
>>> output = op(x)
>>> print(output)
True
[False True]