Ctrl+K

ELU

Contents

ELU#

class brainpy.dnn.ELU(alpha=1.0, inplace=False)[source]#

Applies the Exponential Linear Unit (ELU) function, element-wise, as described in the paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

ELU is defined as:

\[\begin{split}\text{ELU}(x) = \begin{cases} x, & \text{ if } x > 0\\ \alpha * (\exp(x) - 1), & \text{ if } x \leq 0 \end{cases}\end{split}\]
Parameters:

  • alpha (float) – the \(\alpha\) value for the ELU formulation. Default: 1.0

  • inplace (bool) – can optionally do the operation in-place. Default: False

Shape:

  • Input: \((*)\), where \(*\) means any number of dimensions.

  • Output: \((*)\), same shape as the input.

Examples:

>>> import brainpy as bp
>>> import brainpy.math as bm
>>> m = bp.dnn.ELU()
>>> input = bm.random.randn(2)
>>> output = m(input)
update(input)[source]#

The function to specify the updating rule.

Return type:

TypeVar(ArrayType, Array, Variable, TrainVar, Array, ndarray)

Contents