for key, item in classifier_functions.items()
}
for name in classification_dataset_names:
for key in params:
for x in params[key]:
todos.add((name, key, x))
if options.resume:
p = Path(resultdir)
ids = list(
map(lambda s: int(s.stem.split('-')[1]), p.glob("tmp-*.pkl")))
for i in ids:
todos.complete(i)
total = todos.size()
print("found {} incomplete trials!".format(len(todos.remaining())))
clients = {}
s = start_server(options.port)
s.settimeout(1)
print("Starting to listen...")
s.listen(options.max_connections)
while len(todos.completed()) != todos.size():
try:
to_remove = []
for k in clients:
if handle_client(clients, k) != None:
to_remove.append(k)
for item in to_remove:
print("Removing {}".format(item))
if clients[item]['task'] != None:
