def __init__()

in qlearn/toys/agent.py [0:0]


    def __init__(self, args, env):
        self.action_space = env.action_space.n
        self.batch_size = args.batch_size
        self.discount = args.discount
        self.double_q = args.double_q

        self.online_net = DQN(args, self.action_space)
        if args.model and os.path.isfile(args.model):
            self.online_net.load_state_dict(torch.load(args.model))
        self.online_net.train()

        self.target_net = DQN(args, self.action_space)
        self.update_target_net()
        self.target_net.eval()
        for param in self.target_net.parameters():
            param.requires_grad = False

        self.optimiser = optim.Adam(self.online_net.parameters(), lr=args.lr, eps=args.adam_eps)
        if args.cuda:
            self.online_net.cuda()
            self.target_net.cuda()
        self.FloatTensor = torch.cuda.FloatTensor if args.cuda else torch.FloatTensor
        self.LongTensor = torch.cuda.LongTensor if args.cuda else torch.LongTensor
        self.ByteTensor = torch.cuda.ByteTensor if args.cuda else torch.ByteTensor