set_denominator was added so that the batch size doesn't need to be specified before constructing the optimizer, but it breaks the DPQuery abstraction. Now the optimizer uses a GaussianSumQuery instead of GaussianAverageQuery, and normalization by batch size is done inside the optimizer.
Also instead of creating all DPQueries with a PrivacyLedger and then wrapping with QueryWithLedger, it is now sufficient to create the queries with no ledger and QueryWithLedger will construct the ledger and pass it to all inner queries.
PiperOrigin-RevId: 251462353
Prior to this change the PrivacyLedger is running to keep a log of private queries, but the ledger is not actually used to compute the (epsilon, delta) guarantees. This CL adds a function to compute the RDP directly from the ledger.
Note I did verify that the tutorial builds and runs with the changes and for the first few iterations prints the same epsilon values as before the change.
PiperOrigin-RevId: 241063532
Moved query classes from dir optimizers into new dir dp_query. Added NormalizedQuery class for queries that divide the output of another query by a constant like GaussianAverageQuery.
PiperOrigin-RevId: 240167115
1. Rename PrivateQuery to DPQuery.
2. Move construction of DPQuery to outside of optimizer.
3. Remove PrivateAverageQuery and PrivateSumQuery, and rename DPQuery's 'get_query_result' method to 'get_noised_result'. Rename private_queries.py to dp_query.py.
4. Remove thrice-replicated run_query function from the test classes and replace with a single function in new test_utils.py.
5. Add functions gaussian_sum_query_from_noise_multplier and gaussian_average_query_from_noise_multplier.
PiperOrigin-RevId: 230595991
