chainer.functions.hard_sigmoid

chainer.functions.hard_sigmoid(x)

Element-wise hard-sigmoid function.

This function is defined as

$$\begin{split}f(x) = \left \{ \begin{array}{ll} 0 & {\rm if}~ x < -2.5 \\ 0.2 x + 0.5 & {\rm if}~ -2.5 < x < 2.5 \\ 1 & {\rm if}~ 2.5 < x. \end{array} \right.\end{split}$$

Parameters

x (Variable or N-dimensional array) – Input variable. A $(s_1, s_2, ..., s_N)$-shaped float array.

Returns

Output variable. A $(s_1, s_2, ..., s_N)$-shaped float array.

Return type

Variable

Example

It maps the input values into the range of $[0, 1]$.

>>> x = np.array([-2.6, -1, 0, 1, 2.6])
>>> x
array([-2.6, -1. ,  0. ,  1. ,  2.6])
>>> F.hard_sigmoid(x).array
array([0. , 0.3, 0.5, 0.7, 1. ])