def __init__()

in agents/qgdp.py [0:0]

• 33 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self,
                 state_dim,
                 action_dim,
                 max_action,
                 device,
                 discount,
                 tau,
                 model_type='MLP',
                 beta_schedule='linear',
                 n_timesteps=100,
                 quantile=0.7,
                 ):

        if model_type == 'MLP':
            self.model = MLP(state_dim=state_dim, action_dim=action_dim, device=device)
        elif model_type == 'MLP_Unet':
            self.model = MLP_Unet(state_dim=state_dim, action_dim=action_dim, device=device)
        elif model_type == 'Tanh_MLP':
            self.model = Tanh_MLP(state_dim=state_dim, action_dim=action_dim, max_action=max_action, device=device)

        self.actor = Diffusion(state_dim=state_dim, action_dim=action_dim, model=self.model, max_action=max_action,
                               beta_schedule=beta_schedule, n_timesteps=n_timesteps,
                               ).to(device)
        self.actor_optimizer = torch.optim.Adam(self.actor.parameters(), lr=2e-4)

        self.value_fun = Value(state_dim).to(device)
        self.value_optimizer = torch.optim.Adam(self.value_fun.parameters(), lr=2e-4)

        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=2e-4)

        self.max_action = max_action
        self.action_dim = action_dim
        self.discount = discount
        self.tau = tau
        self.device = device

        self.quantile = quantile