forked from mindspore-Ecosystem/mindspore
\add random_shuffle docs
This commit is contained in:
parent
376f7f92dd
commit
bc2a361823
|
@ -282,6 +282,7 @@ Tensor创建
|
|||
mindspore.ops.random_poisson
|
||||
mindspore.ops.random_categorical
|
||||
mindspore.ops.random_gamma
|
||||
mindspore.ops.shuffle
|
||||
mindspore.ops.standard_laplace
|
||||
mindspore.ops.standard_normal
|
||||
mindspore.ops.uniform
|
||||
|
|
|
@ -0,0 +1,16 @@
|
|||
mindspore.ops.shuffle
|
||||
=====================
|
||||
|
||||
.. py:function:: mindspore.ops.shuffle(x, seed=None)
|
||||
|
||||
沿着Tensor第一维随机打乱数据。
|
||||
|
||||
参数:
|
||||
- **x** (Tensor) - 需要随机打乱的Tensor。
|
||||
- **seed** (int) - 随机数种子,用于生成随机数,必须为非负数。如果 `seed` 为0,则替换为随机生成的值。默认值是None, 表示使用0作为随机数种子。
|
||||
|
||||
返回:
|
||||
Tensor,与输入相同的shape和类型。
|
||||
|
||||
异常:
|
||||
- **TypeError** - 如果 `seed` 不是None或非负整数。
|
|
@ -281,6 +281,7 @@ Randomly Generating Functions
|
|||
mindspore.ops.random_poisson
|
||||
mindspore.ops.random_categorical
|
||||
mindspore.ops.random_gamma
|
||||
mindspore.ops.shuffle
|
||||
mindspore.ops.standard_laplace
|
||||
mindspore.ops.standard_normal
|
||||
mindspore.ops.uniform
|
||||
|
|
|
@ -397,16 +397,17 @@ def shuffle(x, seed=None):
|
|||
|
||||
Args:
|
||||
x (Tensor): The Tensor need be shuffled.
|
||||
seed (int): The operator-level random seed, used to generate random numbers, must be non-negative. Default: 0.
|
||||
seed (int): Random seed used for random number generation, must be non-negative. If `seed` is 0, which will be
|
||||
replaced with a randomly generated value. Default: None, which will be treated as 0.
|
||||
|
||||
Returns:
|
||||
Tensor. The shape and type are the same as the input `x`.
|
||||
|
||||
Raises:
|
||||
TypeError: If data type of `seed` or `seed2` is not int.
|
||||
TypeError: If data type of `seed` is not None or non-negative int.
|
||||
|
||||
Supported Platforms:
|
||||
``CPU`` ``GPU``
|
||||
``Ascend`` ``GPU`` ``CPU``
|
||||
|
||||
Examples:
|
||||
>>> x = Tensor(np.array([1, 2, 3, 4]), mstype.float32)
|
||||
|
|
|
@ -905,9 +905,10 @@ class RandomShuffle(Primitive):
|
|||
Randomly shuffles a Tensor along its first dimension.
|
||||
|
||||
Args:
|
||||
seed (int): The operator-level random seed, used to generate random numbers, must be non-negative. Default: 0.
|
||||
seed2 (int): The global random seed and it will combile with the operator-level random seed to determine the
|
||||
final generated random number, must be non-negative. Default: 0.
|
||||
seed (int): Random seed. If `seed` or `seed2` is set to non-zero, the random number generator will be seeded
|
||||
by the given seed. Otherwise, it will be seeded randomly. The seed must be non-negative. Default: 0.
|
||||
seed2 (int): Random seed2, a second seed to avoid seed collision. If `seed` is 0, the `seed2` will be used as
|
||||
the seed of the random generator. It must be non-negative. Default: 0.
|
||||
|
||||
Inputs:
|
||||
- **x** (Tensor) - The Tensor need be shuffled.
|
||||
|
@ -919,7 +920,7 @@ class RandomShuffle(Primitive):
|
|||
TypeError: If data type of `seed` or `seed2` is not int.
|
||||
|
||||
Supported Platforms:
|
||||
``CPU`` ``GPU``
|
||||
``Ascend`` ``GPU`` ``CPU``
|
||||
|
||||
Examples:
|
||||
>>> x = Tensor(np.array([1, 2, 3, 4]), mstype.float32)
|
||||
|
|
Loading…
Reference in New Issue