def __init__()

in submix.py [0:0]


    def __init__(self, device, B, eps, public_model, ensemble,
        alpha=float('inf'), gamma=10, lambda_dec_factor=0.93, consumption_multiplier=1.0,
        lambda_solver='iteration', temp=1.0):
        self.alpha = alpha
        self.B = B
        self.queries_remaining = B
        self.eps_remaining = [eps]*len(ensemble)
        self.pairing = self._random_pairing(len(ensemble))
        self.STOP = False
        self.public_model = public_model
        self.ensemble = ensemble
        LMs = copy.copy(ensemble)
        LMs.insert(0,self.public_model)
        self.LMs = LMs
        self.temp = temp
        self.device = device
        self.queries_remaining = B
        self.tokenizer = GPT2Tokenizer.from_pretrained('distilgpt2')
        self.target_consumption = consumption_multiplier*eps/B
        assert lambda_dec_factor < 1.0, f'lambda_dec_factor should be less than 1'
        self.lambda_dec_factor = lambda_dec_factor
        self.gamma = gamma
        self.lambs = []
        self.epsilons = []
        self.lambda_solver = lambda_solver