deepAI_demo.py 文件源码

def randomize_parameters(params, sigmas, sig_min_perturbations):

    r_params = []
    r_epsilons = []

    for i in range(len(params)):
        epsilon_half = theano_rng.normal((n_perturbations/2,params[i].shape[1],params[i].shape[2]), dtype = theano.config.floatX)
        r_epsilon = T.concatenate( [epsilon_half, -1.0*epsilon_half], axis = 0 )
        r_param = params[i] + r_epsilon*(T.nnet.softplus( sigmas[i] ) + sig_min_perturbations)
        r_params.append(r_param)
        r_epsilons.append(r_epsilon)

    return r_params, r_epsilons

####################################################################
#
# Create randomly perturbed version of parameters
#
####################################################################