def test_with_federated_type(self):
add = _create_computation_add()
value = _mock_data_of_type(
computation_types.at_clients(
computation_types.SequenceType(np.int32)))
zero = intrinsics.federated_value(0, placements.CLIENTS)
result = intrinsics.sequence_reduce(value, zero, add)
self.assert_value(result, '{int32}@CLIENTS')
def test_with_non_federated_type(self):
@computations.tf_computation(np.int32, np.int32)
def add(x, y):
return x + y
value = _mock_data_of_type(computation_types.SequenceType(np.int32))
result = intrinsics.sequence_reduce(value, 0, add)
self.assert_value(result, 'int32')
def test_with_federated_type(self):
@computations.tf_computation(np.int32, np.int32)
def add(x, y):
return x + y
value = _mock_data_of_type(
computation_types.at_clients(
computation_types.SequenceType(np.int32)))
zero = intrinsics.federated_value(0, placements.CLIENTS)
result = intrinsics.sequence_reduce(value, zero, add)
self.assert_value(result, '{int32}@CLIENTS')
def _train_on_one_client(model, batches):
return intrinsics.sequence_reduce(batches, model, _train_on_one_batch)
def test_with_non_federated_type(self):
add = _create_computation_add()
value = _mock_data_of_type(computation_types.SequenceType(np.int32))
result = intrinsics.sequence_reduce(value, 0, add)
self.assert_value(result, 'int32')