Sigmoid

class brainpy.dnn.Sigmoid(name=None, mode=None)

Applies the element-wise function:

\[\text{Sigmoid}(x) = \sigma(x) = \frac{1}{1 + \exp(-x)}\]

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.Sigmoid()
>>> 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)