mindspore.mint.nn.functional.selu

mindspore.mint.nn.functional.selu(input)

Activation function SELU (Scaled exponential Linear Unit).

The activation function is defined as:

$$E_i=scale\ast \{\begin{array}{ll}{x}_i,& \text{if }{x}_i\ge 0;\\ \text{alpha}\ast (\exp (x_i)-1),& \text{otherwise.}\end{array}$$

where $alpha$ and $scale$ are pre-defined constants($alpha=1.67326324$ and $scale=1.05070098$).

See more details in Self-Normalizing Neural Networks.

SELU Activation Function Graph:

Parameters

input (Tensor) – Tensor of any dimension. The data type is float16, float32, bfloat16.

Returns

Tensor, with the same type and shape as the input.

Raises

TypeError – If dtype of input is not float16, float32, bfloat16.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> from mindspore import Tensor, mint
>>> import numpy as np
>>> input = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32)
>>> output = mint.nn.functional.selu(input)
>>> print(output)
[[-1.1113307 4.202804 -1.7575096]
[ 2.101402 -1.7462534 9.456309 ]]