def test_dp_sum_structure_list(self):
query = privacy.GaussianSumQuery(5.0, 0.0)
def _value_type_fn(value):
del value
return [tff.TensorType(tf.float32), tff.TensorType(tf.float32)]
def _from_anon_tuple_fn(record):
return list(record)
dp_aggregate_fn, _ = differential_privacy.build_dp_aggregate(
query,
value_type_fn=_value_type_fn,
from_anon_tuple_fn=_from_anon_tuple_fn)
def datapoint(a, b):
return [tf.Variable(a, name='a'), tf.Variable(b, name='b')]
data = [
datapoint(1.0, 2.0),
datapoint(2.0, 3.0),
datapoint(6.0, 8.0), # Clipped to 3.0, 4.0
]
initialize, aggregate = wrap_aggregate_fn(dp_aggregate_fn, data[0])
global_state = initialize()
global_state, result = aggregate(global_state, data)
self.assertEqual(getattr(global_state, 'l2_norm_clip'), 5.0)
self.assertEqual(getattr(global_state, 'stddev'), 0.0)
result = list(result)
self.assertEqual(result[0], 6.0)
self.assertEqual(result[1], 9.0)
def test_dp_stateful_mean(self):
class ShrinkingSumQuery(privacy.GaussianSumQuery):
def get_noised_result(self, sample_state, global_state):
global_state = self._GlobalState(
tf.maximum(global_state.l2_norm_clip - 1, 0.0),
global_state.stddev)
return sample_state, global_state
query = ShrinkingSumQuery(4.0, 0.0)
dp_aggregate_fn, _ = differential_privacy.build_dp_aggregate(query)
initialize, aggregate = wrap_aggregate_fn(dp_aggregate_fn, 0.0)
global_state = initialize()
records = [1.0, 3.0, 5.0]
def run_and_check(global_state, expected_l2_norm_clip,
expected_result):
global_state, result = aggregate(global_state, records)
self.assertEqual(getattr(global_state, 'l2_norm_clip'),
expected_l2_norm_clip)
self.assertEqual(result, expected_result)
return global_state
self.assertEqual(getattr(global_state, 'l2_norm_clip'), 4.0)
global_state = run_and_check(global_state, 3.0, 8.0)
global_state = run_and_check(global_state, 2.0, 7.0)
global_state = run_and_check(global_state, 1.0, 5.0)
global_state = run_and_check(global_state, 0.0, 3.0)
global_state = run_and_check(global_state, 0.0, 0.0)
def test_dp_global_state_type(self):
query = tensorflow_privacy.GaussianSumQuery(5.0, 0.0)
_, dp_global_state_type = differential_privacy.build_dp_aggregate(query)
self.assertIsInstance(dp_global_state_type,
computation_types.StructWithPythonType)
def test_dp_global_state_type(self):
query = tensorflow_privacy.GaussianSumQuery(5.0, 0.0)
_, dp_global_state_type = differential_privacy.build_dp_aggregate(query)
self.assertEqual(dp_global_state_type.__class__.__name__,
'NamedTupleTypeWithPyContainerType')
def test_dp_sum(self):
query = privacy.GaussianSumQuery(4.0, 0.0)
dp_aggregate_fn, _ = differential_privacy.build_dp_aggregate(query)
initialize, aggregate = wrap_aggregate_fn(dp_aggregate_fn, 0.0)
global_state = initialize()
global_state, result = aggregate(global_state, [1.0, 3.0, 5.0])
self.assertEqual(getattr(global_state, 'l2_norm_clip'), 4.0)
self.assertEqual(getattr(global_state, 'stddev'), 0.0)
self.assertEqual(result, 8.0)
def test_dp_sum_structure_odict(self):
query = privacy.GaussianSumQuery(5.0, 0.0)
dp_aggregate_fn, _ = differential_privacy.build_dp_aggregate(query)
def datapoint(a, b):
return collections.OrderedDict([('a', (a, )), ('b', [b])])
data = [
datapoint(1.0, 2.0),
datapoint(2.0, 3.0),
datapoint(6.0, 8.0), # Clipped to 3.0, 4.0
]
initialize, aggregate = wrap_aggregate_fn(dp_aggregate_fn, data[0])
global_state = initialize()
global_state, result = aggregate(global_state, data)
self.assertEqual(getattr(global_state, 'l2_norm_clip'), 5.0)
self.assertEqual(getattr(global_state, 'stddev'), 0.0)
self.assertEqual(getattr(result, 'a')[0], 6.0)
self.assertEqual(getattr(result, 'b')[0], 9.0)
def test_dp_sum_structure_odict(self):
query = tensorflow_privacy.GaussianSumQuery(5.0, 0.0)
dp_aggregate_fn, _ = differential_privacy.build_dp_aggregate(query)
def datapoint(a, b):
return collections.OrderedDict(a=(a, ), b=[b])
data = [
datapoint(1.0, 2.0),
datapoint(2.0, 3.0),
datapoint(6.0, 8.0), # Clipped to 3.0, 4.0
]
initialize, aggregate = wrap_aggregate_fn(dp_aggregate_fn, data[0])
global_state = initialize()
global_state, result = aggregate(global_state, data)
self.assertEqual(global_state.l2_norm_clip, 5.0)
self.assertEqual(global_state.stddev, 0.0)
self.assertEqual(result['a'][0], 6.0)
self.assertEqual(result['b'][0], 9.0)
