activations.py 文件源码

def forward(self, input, *args, **kwargs):
        """A sigmoid function is a mathematical function having a 
        characteristic "S"-shaped curve or sigmoid curve. Often, 
        sigmoid function refers to the special case of the logistic 
        function and defined by the formula :math:`\\varphi(x) = \\frac{1}{1 + e^{-x}}`
        (given the input :math:`x`).

        Parameters
        ----------
        input : float32
            The activation (the summed, weighted input of a neuron).

        Returns
        -------
        float32 in [0, 1]
            The output of the sigmoid function applied to the activation.
        """

        self.last_forward = 1.0 / (1.0 + np.exp(-input))
        return self.last_forward