(self, time_steps, inputs, outputs, in_tensor, out_tensor, mask)
Prepare data for delivery to device.

        Arguments:
            time_steps (int): Number of time steps in this minibatch.
            inputs (numpy array): Inputs numpy array
            outputs (numpy array): Outputs numpy array
            in_tensor (Tensor): Device buffer holding inputs
            out_tensor (Tensor): Device buffer holding outputs
            mask (numpy array): Device buffer for the output mask
Prepare data for delivery to device.
Prepare data for delivery to device .
def fill_buffers(self, time_steps, inputs, outputs, in_tensor, out_tensor, mask):
        """
        Prepare data for delivery to device.

        Arguments:
            time_steps (int): Number of time steps in this minibatch.
            inputs (numpy array): Inputs numpy array
            outputs (numpy array): Outputs numpy array
            in_tensor (Tensor): Device buffer holding inputs
            out_tensor (Tensor): Device buffer holding outputs
            mask (numpy array): Device buffer for the output mask
        """
        # Put inputs and outputs, which are too small, into properly shaped arrays
        columns = time_steps * self.be.bsz
        inC = np.zeros((self.nin, self.max_columns))
        outC = np.zeros((self.nout, self.max_columns))
        inC[:, :columns] = inputs
        outC[:, :columns] = outputs

        # Copy those arrays to device
        in_tensor.set(inC)
        out_tensor.set(outC)

        # Set a mask over the unused part of the buffer
        mask[:, :columns] = 1
        mask[:, columns:] = 0
def fill_buffers ( self , time_steps , inputs , outputs , in_tensor , out_tensor , mask ) : # Put inputs and outputs, which are too small, into properly shaped arrays columns = time_steps * self . be . bsz inC = np . zeros ( ( self . nin , self . max_columns ) ) outC = np . zeros ( ( self . nout , self . max_columns ) ) inC [ : , : columns ] = inputs outC [ : , : columns ] = outputs # Copy those arrays to device in_tensor . set ( inC ) out_tensor . set ( outC ) # Set a mask over the unused part of the buffer mask [ : , : columns ] = 1 mask [ : , columns : ] = 0