print('Waiting for PS\'s command...')
sys.stdout.flush()
client_socket.settimeout(600)
while True:
signal = client_socket.recv(10)
if signal == SRC.purpose:
print('Sending init purpose...')
sys.stdout.flush()
client_socket.send(SRC.init)
break
else:
client_socket.close()
print('Server Error! Exit!')
exit(-1)
hyperparameters = communication.get_np_array(client_socket)
communication_rounds = hyperparameters['communication_rounds']
local_epoch_num = hyperparameters['local_epoch_num']
train_batch_size = hyperparameters['train_batch_size']
embedding_dim = hyperparameters['embedding_dim']
opt_alg = hyperparameters['opt_alg']
clip_bound = hyperparameters['clip_bound']
init_user_id_set = hyperparameters['init_user_id_set']
# Some global parameters
machine_index = FLAGS.machine_index
random_user_index = init_user_id_set[machine_index -
1] #To save next Taobao user file index
# Probability parameters customized by a client for double randomized response
# prob2 and prob6 are not needed here for testing model accuracy
################################################################
with open('../taobao_data_process/taobao_user_item_cate_count.pkl', 'rb') as f:
user_count, item_count, cate_count = pickle.load(f)
for round_num in range(1, communication_rounds + 1):
print('Round %d starts!' % round_num)
sys.stdout.flush()
global_start_time = time.time()
######################################################
# Phase 0: Initialization and prepare some parameters
######################################################
print('Phase 0: Initialization begins...')
sys.stdout.flush()
client_socket = communication.start_socket_client()
received_message = communication.get_np_array(client_socket)
# It is the client's file index, but in fact contains the data of Taobao user with 'userID'
client_index = received_message['client_index']
hyperparameters = received_message['hyperparameters']
union_security_para_dict = received_message['union_security_para_dict']
fedsubavg_security_para_dict = received_message[
'fedsubavg_security_para_dict']
# reply to checking "online" state
cl_pl_fn.response_to_check_connection(client_socket)
local_epoch_num = hyperparameters['local_epoch_num']
train_batch_size = hyperparameters['train_batch_size']
learning_rate = hyperparameters[
'learning_rate'] # please pay attention to its update (already update by ps)
embedding_dim = hyperparameters['embedding_dim']
opt_alg = hyperparameters['opt_alg']