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
At present, the script has no heavy dependencies except for the rdp_accountant, which is by itself pretty light-weight. However, importing rdp_accountant triggers __init__.py in third_party/py/tensorflow_privacy/privacy, which loads TF and all of tf.privacy. The CL adds a check to the __init__.py, which controls this behavior.
PiperOrigin-RevId: 243172355
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
