)
def test_distributed_discrete_gaussian_tree_aggregation_no_overflow(
self, value_shape, num_clients, arity):
client_records = []
for _ in range(num_clients):
client_records.append(np.zeros(value_shape, dtype=int).tolist())
agg_factory = hihi_factory.create_hierarchical_histogram_aggregation_factory(
num_bins=value_shape,
arity=arity,
clip_mechanism='sub-sampling',
max_records_per_user=1,
dp_mechanism='distributed-discrete-gaussian',
noise_multiplier=0,
enable_secure_sum=True)
value_type = computation_types.to_type((tf.int32, (value_shape, )))
process = agg_factory.create(value_type)
state = process.initialize()
output = process.next(state, client_records).result
reference_aggregated_record = build_tree_from_leaf.create_hierarchical_histogram(
np.zeros_like(client_records[0], dtype=int).tolist(), arity)
self.assertAllClose(output, reference_aggregated_record)
if __name__ == '__main__':
execution_contexts.set_test_python_execution_context()
tf.test.main()
def setUp(self):
super().setUp()
execution_contexts.set_test_python_execution_context()
