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tf_privacy.DiscreteGaussianSumQuery

Implements DPQuery for discrete Gaussian sum queries.

Inherits From: SumAggregationDPQuery, DPQuery

For each local record, we check the L2 norm bound and add discrete Gaussian noise. In particular, this DPQuery does not perform L2 norm clipping and the norms of the input records are expected to be bounded.

l2_norm_bound The L2 norm bound to verify for each record.
stddev The stddev of the discrete Gaussian noise added to the sum.

Methods

accumulate_preprocessed_record

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Implements tensorflow_privacy.DPQuery.accumulate_preprocessed_record.

accumulate_record

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Accumulates a single record into the sample state.

This is a helper method that simply delegates to preprocess_record and accumulate_preprocessed_record for the common case when both of those functions run on a single device. Typically this will be a simple sum.

Args
params The parameters for the sample. In standard DP-SGD training, the clipping norm for the sample's microbatch gradients (i.e., a maximum norm magnitude to which each gradient is clipped)
sample_state The current sample state. In standard DP-SGD training, the accumulated sum of previous clipped microbatch gradients.
record The record to accumulate. In standard DP-SGD training, the gradient computed for the examples in one microbatch, which may be the gradient for just one example (for size 1 microbatches).

Returns
The updated sample state. In standard DP-SGD training, the set of previous microbatch gradients with the addition of the record argument.

derive_metrics

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Derives metric information from the current global state.

Any metrics returned should be derived only from privatized quantities.

Args
global_state The global state from which to derive metrics.

Returns
A collections.OrderedDict mapping string metric names to tensor values.

derive_sample_params

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Given the global state, derives parameters to use for the next sample.

For example, if the mechanism needs to clip records to bound the norm, the clipping norm should be part of the sample params. In a distributed context, this is the part of the state that would be sent to the workers so they can process records.

Args
global_state The current global state.

Returns
Parameters to use to process records in the next sample.

get_noised_result

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Adds discrete Gaussian noise to the aggregate.

initial_global_state

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Returns the initial global state for the DPQuery.

The global state contains any state information that changes across repeated applications of the mechanism. The default implementation returns just an empty tuple for implementing classes that do not have any persistent state.

Returns
The global state.

initial_sample_state

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Implements tensorflow_privacy.DPQuery.initial_sample_state.

merge_sample_states

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Implements tensorflow_privacy.DPQuery.merge_sample_states.

preprocess_record

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Check record norm and add noise to the record.