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 ####