(self, shared_outputs=None)
Allocate output buffer to store activations from fprop.

        Arguments:
            shared_outputs (Tensor, optional): pre-allocated tensor for activations to be
                                               computed into
Allocate output buffer to store activations from fprop.
Allocate output buffer to store activations from fprop .
def allocate(self, shared_outputs=None):
        """
        Allocate output buffer to store activations from fprop.

        Arguments:
            shared_outputs (Tensor, optional): pre-allocated tensor for activations to be
                                               computed into
        """
        super(Recurrent, self).allocate(shared_outputs)
        self.h_ff_buffer = self.be.zeros_like(self.outputs)
        self.final_state_buffer = self.be.iobuf(self.out_shape[0])
        self.h_ff = get_steps(self.h_ff_buffer, self.out_shape)
        self.h = get_steps(self.outputs, self.out_shape)
        self.h_prev = self.h[-1:] + self.h[:-1]
        # State deltas
        self.h_delta_buffer = self.be.iobuf(self.out_shape)
        self.h_delta = get_steps(self.h_delta_buffer, self.out_shape)
        self.final_hidden_error = self.be.zeros(self.h_delta[0].shape)
        self.bufs_to_reset = [self.outputs]

        if self.W_input is None:
            self.init_params(self.weight_shape)
def allocate ( self , shared_outputs = None ) : super ( Recurrent , self ) . allocate ( shared_outputs ) self . h_ff_buffer = self . be . zeros_like ( self . outputs ) self . final_state_buffer = self . be . iobuf ( self . out_shape [ 0 ] ) self . h_ff = get_steps ( self . h_ff_buffer , self . out_shape ) self . h = get_steps ( self . outputs , self . out_shape ) self . h_prev = self . h [ - 1 : ] + self . h [ : - 1 ] # State deltas self . h_delta_buffer = self . be . iobuf ( self . out_shape ) self . h_delta = get_steps ( self . h_delta_buffer , self . out_shape ) self . final_hidden_error = self . be . zeros ( self . h_delta [ 0 ] . shape ) self . bufs_to_reset = [ self . outputs ] if self . W_input is None : self . init_params ( self . weight_shape )