Hard sigmoid
In artificial intelligence, especially computer vision and artificial neural networks, a hard sigmoid is non-smooth function used in place of a sigmoid function. These retain the basic shape of a sigmoid, rising from 0 to 1, but using simpler functions, especially piecewise [linear function]s or piecewise [constant function]s. These are preferred where speed of computation is more important than precision.
Examples
The most extreme examples are the sign function or Heaviside step function, which go from −1 to 1 or 0 to 1 at 0.Other examples include the Theano library, which provides two approximations:
ultra_fast_sigmoid, which is a multi-part piecewise approximation and hard_sigmoid, which is a 3-part piecewise linear approximation.