def __init__(self, ops): Operator.__init__(self, ops) self.transacs = [] self.uid = CSV.uid self.current = None self.length = 1 CSV.uid += 1
def __init__(self, pin, n = "relay"): Producer.__init__(self, n, interval = 60000) Operator.__init__(self, n) self.__relay = Pin(pin ,Pin.OUT) self.add_sensor(n, self.get_state) self.__async_blinking = False self.add_command(self.__op, SET) self.add_command(self.__get, GET)
def __init__(self, ops, accumulate): global Do_Maths Operator.__init__(self, ops) self.doers = [] for doer in self.get_doers(): self.doers.append(doer) self.daily_val = defaultdict(lambda : 0) self.dumps = defaultdict(lambda : []) self.accumulate = accumulate self.dumped = True
def main(config): config.device = torch.device( 'cuda:{}'.format(config.gpu) if torch.cuda.is_available() else 'cpu') # load data_loader data_loader = get_dataloader(config) check_point = Checkpoint(config) operator = Operator(config, check_point) if config.is_train: operator.train(data_loader) else: operator.test(data_loader)
def main(config): config.device = torch.device( 'cuda:{}'.format(config.gpu) if torch.cuda.is_available() else 'cpu') # load data_loader check_point = Checkpoint(config) operator = Operator(config, check_point) if config.is_train: midi_data = MidiData(config) operator.train(midi_data) else: operator.test()
def addOp(self, id): operator = Operator(id) operator.status = 'available' self.operators.append(operator)
def __init__(self): Consumer.__init__(self) self.__name = 'sensors' Operator.__init__(self, 'sensors') self.add_command(self.__get, GET) self.__sensors = {}
def __init__(self, name, fn): self.__fn = fn self.__config = None Operator.__init__(self, name) self.add_command(self.__get, GET, 'config') self.add_command(self.__set, SET, 'config')