def test_type_properties_unweighted(self, value_type):
value_type = computation_types.to_type(value_type)
factory_ = mean_factory.UnweightedMeanFactory()
self.assertIsInstance(factory_, factory.UnweightedAggregationFactory)
process = factory_.create(value_type)
self.assertIsInstance(process, aggregation_process.AggregationProcess)
param_value_type = computation_types.at_clients(value_type)
result_value_type = computation_types.at_server(value_type)
expected_state_type = computation_types.at_server(())
expected_measurements_type = computation_types.at_server(
collections.OrderedDict(mean_value=()))
expected_initialize_type = computation_types.FunctionType(
parameter=None, result=expected_state_type)
self.assertTrue(
process.initialize.type_signature.is_equivalent_to(
expected_initialize_type))
expected_next_type = computation_types.FunctionType(
parameter=collections.OrderedDict(
state=expected_state_type, value=param_value_type),
result=measured_process.MeasuredProcessOutput(
expected_state_type, result_value_type, expected_measurements_type))
self.assertTrue(
process.next.type_signature.is_equivalent_to(expected_next_type))
def test_incorrect_create_type_raises(self, wrong_type):
factory_ = mean_factory.MeanFactory()
correct_type = computation_types.to_type(tf.float32)
with self.assertRaises(TypeError):
factory_.create(wrong_type, correct_type)
with self.assertRaises(TypeError):
factory_.create(correct_type, wrong_type)
factory_ = mean_factory.UnweightedMeanFactory()
with self.assertRaises(TypeError):
factory_.create(wrong_type)
def test_structure_value_unweighted(self):
factory_ = mean_factory.UnweightedMeanFactory()
value_type = computation_types.to_type(_test_struct_type)
process = factory_.create(value_type)
expected_state = ()
expected_measurements = collections.OrderedDict(mean_value=())
state = process.initialize()
self.assertAllEqual(expected_state, state)
client_data = [((1.0, 2.0), 3.0), ((2.0, 5.0), 4.0), ((3.0, 0.0), 5.0)]
output = process.next(state, client_data)
self.assertAllEqual(expected_state, output.state)
self.assertAllClose(((2.0, 7 / 3), 4.0), output.result)
self.assertEqual(expected_measurements, output.measurements)
def test_inner_value_sum_factory_unweighted(self):
sum_factory = aggregators_test_utils.SumPlusOneFactory()
factory_ = mean_factory.UnweightedMeanFactory(value_sum_factory=sum_factory)
value_type = computation_types.to_type(tf.float32)
process = factory_.create(value_type)
state = process.initialize()
self.assertAllEqual(0, state)
# Values will be summed to 7.0.
client_data = [1.0, 2.0, 3.0]
output = process.next(state, client_data)
self.assertAllEqual(1, output.state)
self.assertAllClose(7 / 3, output.result)
self.assertEqual(
collections.OrderedDict(mean_value=M_CONST), output.measurements)
def test_scalar_value_unweighted(self):
factory_ = mean_factory.UnweightedMeanFactory()
value_type = computation_types.to_type(tf.float32)
process = factory_.create(value_type)
expected_state = ()
expected_measurements = collections.OrderedDict(mean_value=())
state = process.initialize()
self.assertAllEqual(expected_state, state)
client_data = [1.0, 2.0, 3.0]
output = process.next(state, client_data)
self.assertAllClose(2.0, output.result)
self.assertAllEqual(expected_state, output.state)
self.assertEqual(expected_measurements, output.measurements)