From 589b56b26458a7eb95ab93b2eb65ac4325c1d144 Mon Sep 17 00:00:00 2001 From: Pranjal Tandon Date: Mon, 3 Feb 2020 14:00:34 +0530 Subject: [PATCH] Update sac.py --- sac.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/sac.py b/sac.py index f494344..141c0b8 100644 --- a/sac.py +++ b/sac.py @@ -17,7 +17,7 @@ class SAC(object): self.target_update_interval = args.target_update_interval self.automatic_entropy_tuning = args.automatic_entropy_tuning - self.device = torch.device("cuda" if args.cuda else "cpu") + self.device = torch.device("cuda" if args.cuda else "cpu") self.critic = QNetwork(num_inputs, action_space.shape[0], args.hidden_size).to(device=self.device) self.critic_optim = Adam(self.critic.parameters(), lr=args.lr) @@ -41,9 +41,9 @@ class SAC(object): self.policy = DeterministicPolicy(num_inputs, action_space.shape[0], args.hidden_size, action_space).to(self.device) self.policy_optim = Adam(self.policy.parameters(), lr=args.lr) - def select_action(self, state, eval=False): + def select_action(self, state, evaluate=False): state = torch.FloatTensor(state).to(self.device).unsqueeze(0) - if eval is False: + if evaluate is False: action, _, _ = self.policy.sample(state) else: _, _, action = self.policy.sample(state) @@ -119,7 +119,7 @@ class SAC(object): print('Saving models to {} and {}'.format(actor_path, critic_path)) torch.save(self.policy.state_dict(), actor_path) torch.save(self.critic.state_dict(), critic_path) - + # Load model parameters def load_model(self, actor_path, critic_path): print('Loading models from {} and {}'.format(actor_path, critic_path))