def fflayer(tparams, state_below, options, prefix='rconv', activ='lambda x: tensor.tanh(x)', **kwargs):
 return eval(activ)((tensor.dot(state_below, tparams[_p(prefix, 'W')]) + tparams[_p(prefix, 'b')]))

def fflayer ( tparams , state_below , options , prefix = 'rconv' , activ = 'lambda x: tensor.tanh(x)' , ** kwargs ) : return eval ( activ ) ( ( tensor . dot ( state_below , tparams [ _p ( prefix , 'W' ) ] ) + tparams [ _p ( prefix , 'b' ) ] ) )
feedforward pass .