(self, inputs=None, inference=False, beta=0)
return self.outputs
Passes output from preceding layer on without modification

        Arguments:
            inputs (Tensor): input data
            inference (bool): is inference only
            beta (float, optional): Scale to apply to the outputs

        Returns:
            Tensor: output data
Passes output from preceding layer on without modification
Passes output from preceding layer on without modification
def fprop(self, inputs=None, inference=False, beta=0):
        """
        Passes output from preceding layer on without modification

        Arguments:
            inputs (Tensor): input data
            inference (bool): is inference only
            beta (float, optional): Scale to apply to the outputs

        Returns:
            Tensor: output data
        """
        self.be.fprop_skipnode(inputs, self.outputs, beta)
        return self.outputs
def fprop ( self , inputs = None , inference = False , beta = 0 ) : self . be . fprop_skipnode ( inputs , self . outputs , beta ) return self . outputs