def client_init_model(self, param):
self.aggregate_iteration_num = 0
self.aggregator = secure_mean_aggregator.Client(
self.transfer_variable.secure_aggregator_trans_var)
self.loss_scatter = loss_scatter.Client(
self.transfer_variable.loss_scatter_trans_var)
self.has_converged = has_converged.Client(
self.transfer_variable.has_converged_trans_var)
client_set_params(self, param)
def __init__(self, trans_var):
super().__init__(trans_var=trans_var)
self.aggregator = secure_mean_aggregator.Client(
self.transfer_variable.secure_aggregator_trans_var)
self.loss_scatter = loss_scatter.Client(
self.transfer_variable.loss_scatter_trans_var)
self.has_converged = has_converged.Client(
self.transfer_variable.has_converged_trans_var)
self.nn_model = None
def __init__(self, trans_var):
super().__init__(trans_var=trans_var)
self.aggregator = secure_mean_aggregator.Client(self.transfer_variable.secure_aggregator_trans_var)
self.loss_scatter = loss_scatter.Client(self.transfer_variable.loss_scatter_trans_var)
self.has_converged = has_converged.Client(self.transfer_variable.has_converged_trans_var)
self.nn_model = None
self._summary = dict(loss_history=[], is_converged=False)
self._header = []
self._label_align_mapping = None
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 model_broadcaster_call(job_id, role, ind, *args):
status = args[0]
if role == consts.ARBITER:
return has_converged.Server().remote_converge_status(status)
else:
return has_converged.Client().get_converge_status()
def __init__(self, ):
self.loss_scatter = loss_scatter.Client()
self.has_converged = has_converged.Client()