def init_local(self, transmit):
"""
Instantiate client and struct.
"""
self.log.info('Init Local')
train_set, valid_set, test_set = load_data('mnist.pkl.gz')
model = LogisticModel(input_shape=(28, 28), n_out=10)
trainer = NLL_Trainer(transmit, model, train_set, valid_set, test_set)
self.client = LocalClient(trainer)
self.processor.set_model_struct(model.struct)
def parserArguments(parser):
parser.add_argument('--proc' , dest = 'processes', nargs='*', default = ['naoqi-service'], help = 'processes to watch')
parser.add_argument('--tout' , dest = 'timeout', type = int, default = '10000' , help = 'timeout in seconds')
parser.add_argument('--step' , dest = 'step', type = int, default = '1' , help = 'period of recording in seconds')
parser.add_argument('--rec' , dest = 'rec', nargs='*', default = ['local', 'remote'] , help = 'record mode, can be local or remote')
parser.add_argument('--verb', '-v' , dest = 'v', type = int, default = V_DEBUG , help = 'record mode, can be local or remote')
####
#### GLOBALS
####
log = Logger(SERV_LOG_FILE, D_VERB)
log.info('[SERV PROC] Server is launched')
data = Queue.Queue()
connection_table = {}
datasets = load_data('mnist.pkl.gz')
train_set = datasets[0]
valid_set = datasets[1]
test_set = datasets[2]
model = LogisticModel(input_shape=28 * 28, n_out=10)
trainer = NLL_Trainer(data, model, train_set, valid_set, test_set)
trainer.start_record()
log.info('[SERV PROC] CPU Thread instantiated')
data_manager = DataManager(data, connection_table)
log.info('[SERV PROC] DATA Thread instantiated')
####
#### ServerFunctions
####