def populate(self, info):
self.send(protocol.call_method("populate", info))
done = wait_until(self.return_method, conf.FUNC_TIMEOUT, 1, "populate")
if done and self.callbacks['populate']['s']:
del self.callbacks['populate']
log('success', f"{self} populated successfully")
elif done:
log("error", f"Error populating {self}")
else:
log('warning', f"Calling populate() timeout after {conf.FUNC_TIMEOUT} seconds")
def update_model(peer, w_gar, evaluate=False, t=None):
peer.set_model_params(w_gar)
# TODO Review update function
# peer.take_step()
if evaluate:
t_eval = peer.evaluate(peer.inference, one_batch=True)
peer.params.logs.append(t_eval)
r = f"ROUND[{t}], val_loss: {t_eval['val_loss']:.4f}, val_acc: {t_eval['val_acc']:.4f}"
peer.log("success", r, remote=False)
peer.bridge.send(protocol.call_method("log_results", t_eval))
def fit(self, inference):
self.send(protocol.call_method("fit", inference))
done = wait_until(self.return_method, conf.FUNC_TIMEOUT, 1, "fit")
if done and self.callbacks['fit']['s']:
history = self.callbacks['fit']['m']
del self.callbacks['fit']
# for i, h in enumerate(history):
# log('', f"Epoch [{i}], val_loss: {h['val_loss']:.4f}, val_acc: {h['val_acc']:.4f}")
return history
else:
log('warning', f"Calling fit() timeout after {conf.FUNC_TIMEOUT} seconds")
return None
def connect(self, neighbor):
self.send(protocol.call_method("connect", neighbor.id, neighbor.host, neighbor.port))
done = wait_until(self.return_method, conf.FUNC_TIMEOUT, 1, "connect")
if done and self.callbacks['connect']['s']:
self.neighbors.append(neighbor.id)
del self.callbacks["connect"]
return True
elif done:
log("error", self.callbacks['connect']['m'])
return False
else:
log('warning', f"Calling connect() timeout after {conf.FUNC_TIMEOUT} seconds")
return False
def train_init(peer):
peer.log('event',
f'Starting collaborative training using {name} ...',
remote=False)
peer.log("info", f"Initializing Collaborative training...", remote=False)
r = peer.evaluate(peer.inference, one_batch=True)
peer.bridge.send(protocol.call_method("log_results", r))
peer.params.logs = [r]
peer.params.exchanges = 0
peer.params.n_accept = 0
peer.params.n_reject = 0
peer.params.delta = 0.8
peer.params.beta = 1
peer.params.mu = 0.3
peer.params.Wi = {n.neighbor_id: 0 for n in peer.neighbors}
peer.params.E = 5
peer.params.e = peer.params.E
peer.params.k = int(np.sqrt(len(peer.neighbors)))
return
def execute(self, func, *args, **kwargs):
method = f"execute.{func.__name__}"
msg = protocol.call_method(method, *args, **kwargs)
self.send(msg)
self.current_exec = method