jax_privacy.accounting.dpsgd_event
- jax_privacy.accounting.dpsgd_event(noise_multiplier, iterations, *, sampling_prob, use_zcdp=False)[source]
Returns the DpEvent for DP-SGD with the given training parameters.
This mechanism is a composition of poisson-sampled Gaussian mechanisms. See this paper for more details:
[Deep Learning with Differential Privacy](https://arxiv.org/abs/1607.00133)
- Parameters:
noise_multiplier (
float) – The noise multiplier of the mechanism.iterations (
int) – The number of iterations to run the mechanism for.sampling_prob (
float) – The Poisson sampling probability of the mechanism, i.e., the probability an example will be included in each batch.use_zcdp (
bool) – Whether to use generic dp_event.ZCDpEvent instead of specific dp_event.GaussianDpEvent. For example, set this to True if using discrtete Gaussian noise instead of continuous Gaussian noise.
- Return type:
DpEvent- Returns:
A DpEvent object.