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

        Arguments:
            inference (bool): is inference only
            inputs (Tensor): input data

        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):
        """
        Apply the forward pass transformation to the input data.

        Arguments:
            inference (bool): is inference only
            inputs (Tensor): input data

        Returns:
            Tensor: output data
        """
        self.outputs = self.inputs = inputs
        if self.y is None or self.y.base is not self.outputs:
            self.y = self.outputs.reshape((self.bias_size, -1))
        self.y[:] = self.y + self.W
        return self.outputs
def fprop ( self , inputs , inference = False ) : self . outputs = self . inputs = inputs if self . y is None or self . y . base is not self . outputs : self . y = self . outputs . reshape ( ( self . bias_size , - 1 ) ) self . y [ : ] = self . y + self . W return self . outputs