in agents/bc_diffusion.py [0:0]
def __init__(self,
state_dim,
action_dim,
max_action,
device,
discount,
tau,
model_type='MLP',
beta_schedule='linear',
n_timesteps=100,
lr=2e-4,
):
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=lr)
self.max_action = max_action
self.action_dim = action_dim
self.discount = discount
self.tau = tau
self.device = device