(self, x)
return self.be.maximum(x, 0) + self.alpha * (self.be.exp(self.be.minimum(x, 0)) - 1)
Returns the Exponential Linear activation

        Arguments:
            x (Tensor or optree): input value

        Returns:
            Tensor or optree: output activation
Returns the Exponential Linear activation
Returns the Exponential Linear activation
def __call__(self, x):
        """
        Returns the Exponential Linear activation

        Arguments:
            x (Tensor or optree): input value

        Returns:
            Tensor or optree: output activation
        """
        return self.be.maximum(x, 0) + self.alpha * (self.be.exp(self.be.minimum(x, 0)) - 1)
def __call__ ( self , x ) : return self . be . maximum ( x , 0 ) + self . alpha * ( self . be . exp ( self . be . minimum ( x , 0 ) ) - 1 )