modify the files to fix the webpage

This commit is contained in:
zhangyi 2022-08-04 15:00:55 +08:00
parent fa64c2e301
commit aff3805971
5 changed files with 9 additions and 7 deletions

View File

@ -22,7 +22,7 @@ mindspore.nn.AdaSumByDeltaWeightWrapCell
使用本接口时训练的卡的数量必须是2的幂并且至少需要16张卡。目前使用本接口时不支持优化器并行和流水线并行。
参数:
- **optimizer** (nn.optimizer) - 必须是单输入的优化器。
- **optimizer** (Union[Cell]) - 必须是单输入的优化器。
输入:
- **grads** (tuple[Tensor]) - `params` 的梯度形状shape`params` 相同,与所传优化器的输入一致。

View File

@ -20,9 +20,9 @@ mindspore.nn.GELU
参数:
- **approximate** (bool) - 是否启用approximation默认值True。如果approximate的值为True则高斯误差线性激活函数为:
:math:`0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3)))`
:math:`0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3)))`
否则为: :math:`x * P(X <= x) = 0.5 * x * (1 + erf(x / sqrt(2)))`, where P(X) ~ N(0, 1) 。
否则为: :math:`x * P(X <= x) = 0.5 * x * (1 + erf(x / sqrt(2)))`,其中P(X) ~ N(0, 1) 。
输入:
- **x** Tensor - 用于计算GELU的Tensor。数据类型为float16或float32。shape是 :math:`(N,*)` :math:`*` 表示任意的附加维度数。

View File

@ -8,7 +8,7 @@ mindspore.nn.WithEvalCell
参数:
- **network** (Cell) - 前向网络。
- **loss_fn** (Cell) - 损失函数。
- **add_cast_fp32** (bool)是否将数据类型调整为float32。默认值False。
- **add_cast_fp32** (bool) - 是否将数据类型调整为float32。默认值False。
输入:
- **data** Tensor - shape为 :math:`(N, \ldots)` 的Tensor。

View File

@ -513,7 +513,7 @@ Parameter Operation Functions
mindspore.ops.scatter_update
Differential Functions
----------------
----------------------
.. msplatformautosummary::
:toctree: ops

View File

@ -947,7 +947,8 @@ class Cell(Cell_):
"""
Compile and run Cell, the input must be consistent with the input defined in construct.
Note: It is not recommended to call directly.
Note:
It is not recommended to call directly.
Args:
inputs (tuple): Inputs of the Cell object.
@ -1080,7 +1081,8 @@ class Cell(Cell_):
"""
Defines the computation to be performed. This method must be overridden by all subclasses.
Note: It is not supported currently that inputs contain both tuple and non-tuple types at same time.
Note:
It is not supported currently that inputs contain both tuple and non-tuple types at same time.
Args:
inputs (tuple): Tuple of variable parameters.