def _build_cluster(self, workers):
if len(workers) != 3:
raise ValueError("Expected three workers but {} were given".format(
len(workers)))
player_to_worker_mapping = OrderedDict()
player_to_worker_mapping["server0"] = workers[0]
player_to_worker_mapping["server1"] = workers[1]
player_to_worker_mapping["server2"] = workers[2]
use_local_config = all(worker.host is None for worker in workers)
if use_local_config:
config = tfe.LocalConfig(
player_names=player_to_worker_mapping.keys(),
auto_add_unknown_players=False)
return config, player_to_worker_mapping
# use tfe.RemoteConfig
hostmap = OrderedDict([
(player_name, worker.host)
for player_name, worker in player_to_worker_mapping.items()
])
config = tfe.RemoteConfig(hostmap)
return config, player_to_worker_mapping
def config_from_workers(cls, workers):
if len(workers) != 3:
raise ValueError("Expected three workers but {} were given".format(
len(workers)))
player_to_worker_mapping = OrderedDict()
player_to_worker_mapping["server0"] = workers[0]
player_to_worker_mapping["server1"] = workers[1]
player_to_worker_mapping["server2"] = workers[2]
hostmap = OrderedDict([
(player_name, worker.host)
for player_name, worker in player_to_worker_mapping.items()
])
config = tfe.RemoteConfig(hostmap)
return config, player_to_worker_mapping
activation='relu'),
tf.keras.layers.GlobalAveragePooling2D()
])
pre_trained_weights = 'my_model3.h5'
model.load_weights(pre_trained_weights)
from collections import OrderedDict
players = OrderedDict([
('server0', 'localhost:4000'),
('server1', 'localhost:4001'),
('server2', 'localhost:4002'),
])
config = tfe.RemoteConfig(players)
config.save('/tmp/tfe.config')
tfe.set_config(config)
tfe.set_protocol(tfe.protocol.SecureNN())
tfe_model = tfe.keras.models.clone_model(model)
for player_name in players.keys():
print("python -m tf_encrypted.player --config /tmp/tfe.config {}".format(
player_name))
q_input_shape = (1, 224, 224, 3)
q_output_shape = (1, 10)
server = tfe.serving.QueueServer(input_shape=q_input_shape,