def __init__(self, params, name='SubsampleGaussian'):
Mechanism.__init__(self)
self.name = name
self.params = {
'prob': params['prob'],
'sigma': params['sigma'],
'coeff': params['coeff']
}
# create such a mechanism as in previously
subsample = transformer_zoo.AmplificationBySampling(
) # by default this is using poisson sampling
mech = GaussianMechanism(sigma=params['sigma'])
# Create subsampled Gaussian mechanism
SubsampledGaussian_mech = subsample(mech,
params['prob'],
improved_bound_flag=True)
# Now run this for niter iterations
compose = transformer_zoo.Composition()
mech = compose([SubsampledGaussian_mech], [params['coeff']])
# Now we get it and let's extract the RDP function and assign it to the current mech being constructed
rdp_total = mech.RenyiDP
self.propagate_updates(rdp_total, type_of_update='RDP')
def __init__(self, prob, sigma, niter, PoissonSampling=True, name='NoisySGD'):
Mechanism.__init__(self)
self.name = name
self.params = {'prob': prob, 'sigma': sigma, 'niter': niter,
'PoissonSampling': PoissonSampling}
# create such a mechanism as in previously
subsample = transformer_zoo.AmplificationBySampling(PoissonSampling=PoissonSampling)
# by default this is using poisson sampling
mech = ExactGaussianMechanism(sigma=sigma)
prob = 0.01
# Create subsampled Gaussian mechanism
SubsampledGaussian_mech = subsample(mech, prob, improved_bound_flag=True)
# for Gaussian mechanism the improved bound always applies
# Now run this for niter iterations
compose = transformer_zoo.Composition()
mech = compose([SubsampledGaussian_mech], [niter])
# Now we get it and let's extract the RDP function and assign it to the current mech being constructed
rdp_total = mech.RenyiDP
self.propagate_updates(rdp_total, type_of_update='RDP')