(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(LRN, self).allocate(shared_outputs)
        self.denom = self.be.iobuf(self.in_shape)
def allocate ( self , shared_outputs = None ) : super ( LRN , self ) . allocate ( shared_outputs ) self . denom = self . be . iobuf ( self . in_shape )