def __init__()

in agents/ql_cvae.py [0:0]


    def __init__(self,
                 state_dim,
                 action_dim,
                 max_action,
                 device,
                 discount,
                 tau,
                 max_q_backup=False,
                 eta=0.1,
                 ema_decay=0.995,
                 step_start_ema=1000,
                 update_ema_every=5,
                 lr=3e-4,
                 ):

        latent_dim = action_dim * 2
        self.actor = actor(state_dim, action_dim, latent_dim, max_action, device, hidden_dim=500).to(device)
        self.actor_optimizer = torch.optim.Adam(self.actor.parameters(), lr=lr)

        self.step = 0
        self.step_start_ema = step_start_ema
        self.ema = EMA(ema_decay)
        self.ema_model = copy.deepcopy(self.actor)
        self.update_ema_every = update_ema_every

        self.critic = Critic(state_dim, action_dim).to(device)
        self.critic_target = copy.deepcopy(self.critic)
        self.critic_optimizer = torch.optim.Adam(self.critic.parameters(), lr=lr)

        self.max_action = max_action
        self.action_dim = action_dim
        self.discount = discount
        self.tau = tau
        self.eta = eta  # q_learning weight
        self.device = device
        self.max_q_backup = max_q_backup