Hardsigmoid

class brainpy.dnn.Hardsigmoid(inplace=False)

Applies the Hardsigmoid function element-wise.

Hardsigmoid is defined as:

\[\begin{split}\text{Hardsigmoid}(x) = \begin{cases} 0 & \text{if~} x \le -3, \\ 1 & \text{if~} x \ge +3, \\ x / 6 + 1 / 2 & \text{otherwise} \end{cases}\end{split}\]

Parameters:

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.Hardsigmoid()
>>> input = bm.random.randn(2)
>>> output = m(input)

update(input)

The function to specify the updating rule.

Return type:

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