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

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

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

        Returns:
            Tensor: output data
        """
        self.outputs = self.inputs = inputs
        if inference:
            return self._fprop_inference(inputs)

        self.be.make_binary_mask(self.keep_mask, self.keep)
        self.outputs[:] = self.keep_mask * inputs * self._train_scaling

        return self.outputs
def fprop ( self , inputs , inference = False ) : self . outputs = self . inputs = inputs if inference : return self . _fprop_inference ( inputs ) self . be . make_binary_mask ( self . keep_mask , self . keep ) self . outputs [ : ] = self . keep_mask * inputs * self . _train_scaling return self . outputs