def test_simple_sum(self):
encoded_f = encoded.EncodedSumFactory(_identity_encoder_fn)
process = encoded_f.create(computation_types.to_type(tf.float32))
state = process.initialize()
client_data = [1.0, 2.0, 3.0]
for _ in range(3):
output = process.next(state, client_data)
self.assertAllClose(6.0, output.result)
self.assertEqual((), output.measurements)
state = output.state
def test_structure_sum(self):
encoded_f = encoded.EncodedSumFactory(_identity_encoder_fn)
process = encoded_f.create(
computation_types.to_type(((tf.float32, (2, )), tf.float32)))
state = process.initialize()
client_data = [
[[1.0, -1.0], 2],
[[2.0, 4.0], 3],
[[3.0, 5.0], 5],
]
for _ in range(3):
output = process.next(state, client_data)
self.assertAllClose([[6.0, 8.0], 10], output.result)
self.assertEqual((), output.measurements)
state = output.state
def test_type_properties(self, encoder_fn):
encoded_f = encoded.EncodedSumFactory(encoder_fn)
self.assertIsInstance(encoded_f, factory.UnweightedAggregationFactory)
process = encoded_f.create(_test_struct_type)
self.assertIsInstance(process, aggregation_process.AggregationProcess)
self.assertIsNone(process.initialize.type_signature.parameter)
server_state_type = process.initialize.type_signature.result
# State structure should have one element per tensor aggregated,
self.assertLen(server_state_type.member, 2)
self.assertEqual(placements.SERVER, server_state_type.placement)
expected_next_type = computation_types.FunctionType(
parameter=collections.OrderedDict(
state=server_state_type,
value=computation_types.at_clients(_test_struct_type)),
result=measured_process.MeasuredProcessOutput(
state=server_state_type,
result=computation_types.at_server(_test_struct_type),
measurements=computation_types.at_server(())))
self.assertTrue(
process.next.type_signature.is_equivalent_to(expected_next_type))
def test_encoder_fn_not_callable_raises(self):
encoder = te.encoders.as_gather_encoder(te.encoders.identity(),
tf.TensorSpec((), tf.float32))
with self.assertRaises(TypeError):
encoded.EncodedSumFactory(encoder)
