tf_privacy.NormalizedQuery

DPQuery for queries with a DPQuery numerator and fixed denominator.

Inherits From: SumAggregationDPQuery, DPQuery

tf_privacy.NormalizedQuery(
    numerator_query, denominator
)

If the number of records per round is a public constant R, NormalizedQuery could be used with a sum query as the numerator and R as the denominator to implement an average. Under some sampling schemes, such as Poisson subsampling, the actual number of records in a sample is a private quantity, so we cannot use it directly. Using this class with the expected number of records as the denominator gives an unbiased estimate of the average.

Args
numerator_query	A SumAggregationDPQuery for the numerator.
denominator	A value for the denominator. May be None if it will be supplied via the set_denominator function before get_noised_result is called.

Methods

accumulate_preprocessed_record

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accumulate_preprocessed_record(
    sample_state, preprocessed_record
)

Implements tensorflow_privacy.DPQuery.accumulate_preprocessed_record.

accumulate_record

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accumulate_record(
    params, sample_state, record
)

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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derive_metrics(
    global_state
)

Implements tensorflow_privacy.DPQuery.derive_metrics.

derive_sample_params

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derive_sample_params(
    global_state
)

Implements tensorflow_privacy.DPQuery.derive_sample_params.

get_noised_result

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get_noised_result(
    sample_state, global_state
)

Implements tensorflow_privacy.DPQuery.get_noised_result.

initial_global_state

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initial_global_state()

Implements tensorflow_privacy.DPQuery.initial_global_state.

initial_sample_state

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initial_sample_state(
    template
)

Implements tensorflow_privacy.DPQuery.initial_sample_state.

merge_sample_states

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merge_sample_states(
    sample_state_1, sample_state_2
)

Implements tensorflow_privacy.DPQuery.merge_sample_states.

preprocess_record

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preprocess_record(
    params, record
)

Implements tensorflow_privacy.DPQuery.preprocess_record.