chainer.functions.hard_sigmoid

chainer.functions.hard_sigmoid(x)[source]

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 numpy.ndarray or cupy.ndarray) – 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. ])