def sync_random_padding(job_id, role, ind, *args):
if role == consts.ARBITER:
rp_cipher = random_padding_cipher.Server()
rp_cipher.exchange_secret_keys()
return
elif role == consts.HOST:
rp_cipher = random_padding_cipher.Client()
rp_cipher.create_cipher()
return rp_cipher
else:
rp_cipher = random_padding_cipher.Client()
rp_cipher.create_cipher()
return rp_cipher
def __init__(
self,
trans_var: SecureAggregatorTransVar = SecureAggregatorTransVar(),
enable_secure_aggregate=True):
self.enable_secure_aggregate = enable_secure_aggregate
self._aggregator = aggregator.Client(
trans_var=trans_var.aggregator_trans_var)
if enable_secure_aggregate:
self._random_padding_cipher: PadsCipher = \
random_padding_cipher.Client(trans_var=trans_var.random_padding_cipher_trans_var).create_cipher()
def __init__(self, trans_var=LegacyAggregatorTransVar()):
self._enable_secure_aggregate = False
self._loss_sync = loss_scatter.Client(trans_var.loss_scatter)
self._converge_sync = has_converged.Client(trans_var.has_converged)
self._model_scatter = model_scatter.Client(trans_var.model_scatter)
self._model_broadcaster = model_broadcaster.Client(
trans_var.model_broadcaster)
self._random_padding_cipher = random_padding_cipher.Client(
trans_var.random_padding_cipher)
def __init__(self, max_num_aggregation, aggregate_every_n_epoch, name="default"):
super(PyTorchSAClientContext, self).__init__(
max_num_aggregation=max_num_aggregation, name=name
)
self.transfer_variable = SecureAggregatorTransVar()
self.aggregator = aggregator.Client(self.transfer_variable.aggregator_trans_var)
self.random_padding_cipher = random_padding_cipher.Client(
self.transfer_variable.random_padding_cipher_trans_var
)
self.aggregate_every_n_epoch = aggregate_every_n_epoch
self._params: list = None
self._should_stop = False
self.loss_summary = []