(self, inputs, inference=False, beta=0.0)
return self.outputs
Apply the forward pass transformation to the input data.

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

        Returns:
            Tensor: output data
Apply the forward pass transformation to the input data.
Apply the forward pass transformation to the input data .
def fprop(self, inputs, inference=False, beta=0.0):
        """
        Apply the forward pass transformation to the input data.

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

        Returns:
            Tensor: output data
        """
        self.inputs = inputs
        self.be.fprop_pool(self.nglayer, inputs, self.outputs, self.argmax, beta=beta)
        return self.outputs
def fprop ( self , inputs , inference = False , beta = 0.0 ) : self . inputs = inputs self . be . fprop_pool ( self . nglayer , inputs , self . outputs , self . argmax , beta = beta ) return self . outputs