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fix topk param docs

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fengyihang 2023-02-20 17:43:11 +08:00
parent 79fbf20385
commit d3d9e2bc74
4 changed files with 12 additions and 8 deletions
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4
docs/api/api_python/ops/mindspore.ops.TopK.rst
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@ -6,7 +6,7 @@
沿最后一个维度查找 `k` 个最大元素和对应的索引。 沿最后一个维度查找 `k` 个最大元素和对应的索引。
.. warning:: .. warning::
- 如果 `sorted` 设置为False，它将使用aicpu运算符，性能可能会降低。 - 如果 `sorted` 设置为False，它将使用aicpu运算符，性能可能会降低，另外，由于在不同平台上存在内存排布以及遍历方式不同等问题，`sorted` 设置为False时计算结果的显示顺序可能会出现不一致的情况。
如果 `input_x` 是一维Tensor，则查找Tensor中 `k` 个最大元素，并将其值和索引输出为Tensor。`values[k]` 是 `input_x` 中 `k` 个最大元素，其索引是 `indices[k]` 。 如果 `input_x` 是一维Tensor，则查找Tensor中 `k` 个最大元素，并将其值和索引输出为Tensor。`values[k]` 是 `input_x` 中 `k` 个最大元素，其索引是 `indices[k]` 。
@ -18,7 +18,7 @@
如果两个比较的元素相同，则优先返回索引值较小的元素。 如果两个比较的元素相同，则优先返回索引值较小的元素。
参数： 参数：
- **sorted** (bool, 可选) - 如果为True，则获取的元素将按值降序排序。如果为False，则获取的元素将按值升序排序。默认值：True。 - **sorted** (bool, 可选) - 如果为True，则获取的元素将按值降序排序。如果为False，则不对获取的元素进行排序。默认值：True。
输入： 输入：
- **input_x** (Tensor) - 需计算的输入，数据类型必须为float16、float32或int32。 - **input_x** (Tensor) - 需计算的输入，数据类型必须为float16、float32或int32。

4
docs/api/api_python/ops/mindspore.ops.func_topk.rst
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@ -6,7 +6,7 @@ mindspore.ops.topk
沿给定维度查找 `k` 个最大或最小元素和对应的索引。 沿给定维度查找 `k` 个最大或最小元素和对应的索引。
.. warning:: .. warning::
- 如果 `sorted` 设置为False，它将使用aicpu运算符，性能可能会降低。 - 如果 `sorted` 设置为False，它将使用aicpu运算符，性能可能会降低，另外，由于在不同平台上存在内存排布以及遍历方式不同等问题，`sorted` 设置为False时计算结果的显示顺序可能会出现不一致的情况。
如果 `input_x` 是一维Tensor，则查找Tensor中 `k` 个最大或最小元素，并将其值和索引输出为Tensor。`values[k]` 是 `input_x` 中 `k` 个最大元素，其索引是 `indices[k]` 。 如果 `input_x` 是一维Tensor，则查找Tensor中 `k` 个最大或最小元素，并将其值和索引输出为Tensor。`values[k]` 是 `input_x` 中 `k` 个最大元素，其索引是 `indices[k]` 。
@ -22,7 +22,7 @@ mindspore.ops.topk
- **k** (int) - 指定计算最大或最小元素的数量，必须为常量。 - **k** (int) - 指定计算最大或最小元素的数量，必须为常量。
- **dim** (int, 可选) - 需要排序的维度。默认值：None。 - **dim** (int, 可选) - 需要排序的维度。默认值：None。
- **largest** (bool, 可选) - 如果为False，则会返回前k个最小值。默认值：True。 - **largest** (bool, 可选) - 如果为False，则会返回前k个最小值。默认值：True。
- **sorted** (bool, 可选) - 如果为True，则获取的元素将按值降序排序。如果为False，则获取的元素将按值升序排序。默认值：True。 - **sorted** (bool, 可选) - 如果为True，则获取的元素将按值降序排序。如果为False，则不对获取的元素进行排序。默认值：True。
返回： 返回：
由 `values` 和 `indices` 组成的tuple。 由 `values` 和 `indices` 组成的tuple。

6
mindspore/python/mindspore/ops/function/array_func.py
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@ -5692,7 +5692,9 @@ def topk(input_x, k, dim=None, largest=True, sorted=True):
Finds values and indices of the `k` largest or smallest entries along a given dimension. Finds values and indices of the `k` largest or smallest entries along a given dimension.
.. warning:: .. warning::
- If sorted is set to False, it will use the aicpu operator, the performance may be reduced. - If sorted is set to False, it will use the aicpu operator, the performance may be reduced. In addition, due to
different memory layout and traversal methods on different platforms, the display order of calculation results
may be inconsistent when `sorted` is False.
If the `input_x` is a one-dimensional Tensor, finds the `k` largest or smallest entries in the Tensor, If the `input_x` is a one-dimensional Tensor, finds the `k` largest or smallest entries in the Tensor,
and outputs its value and index as a Tensor. values[`k`] is the `k` largest item in `input_x`, and outputs its value and index as a Tensor. values[`k`] is the `k` largest item in `input_x`,
@ -5713,7 +5715,7 @@ def topk(input_x, k, dim=None, largest=True, sorted=True):
dim (int, optional): The dimension to sort along. Default: None. dim (int, optional): The dimension to sort along. Default: None.
largest (bool, optional): If largest is False then the k smallest elements are returned. Default: True. largest (bool, optional): If largest is False then the k smallest elements are returned. Default: True.
sorted (bool, optional): If True, the obtained elements will be sorted by the values in descending order. sorted (bool, optional): If True, the obtained elements will be sorted by the values in descending order.
If False, the obtained elements will be sorted by the values in ascending order. Default: True. If False, the obtained elements will not be sorted. Default: True.
Returns: Returns:
A tuple consisting of `values` and `indexes`. A tuple consisting of `values` and `indexes`.

6
mindspore/python/mindspore/ops/operations/array_ops.py
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@ -7862,7 +7862,9 @@ class TopK(Primitive):
Finds values and indices of the `k` largest entries along the last dimension. Finds values and indices of the `k` largest entries along the last dimension.
.. warning:: .. warning::
- If sorted is set to False, it will use the aicpu operator, the performance may be reduced. - If sorted is set to False, it will use the aicpu operator, the performance may be reduced. In addition, due to
different memory layout and traversal methods on different platforms, the display order of calculation results
may be inconsistent when `sorted` is False.
If the `input_x` is a one-dimensional Tensor, finds the `k` largest entries in the Tensor, If the `input_x` is a one-dimensional Tensor, finds the `k` largest entries in the Tensor,
and outputs its value and index as a Tensor. values[`k`] is the `k` largest item in `input_x`, and outputs its value and index as a Tensor. values[`k`] is the `k` largest item in `input_x`,
@ -7879,7 +7881,7 @@ class TopK(Primitive):
Args: Args:
sorted (bool, optional): If True, the obtained elements will be sorted by the values in descending order. sorted (bool, optional): If True, the obtained elements will be sorted by the values in descending order.
If False, the obtained elements will be sorted by the values in ascending order. Default: True. If False, the obtained elements will not be sorted. Default: True.
Inputs: Inputs:
- **input_x** (Tensor) - Input to be computed, data type must be float16, float32 or int32. - **input_x** (Tensor) - Input to be computed, data type must be float16, float32 or int32.