feat(PPOTrainer.py): added logging messages

experiments/_train_backup.py

@@ -81,7 +81,6 @@ def train(args: PPOArgs):
     run_name = f"{args.exp_name}__seed_{args.seed}__{git_hash}__{int(time.time())}"
     # args.num_iterations = args.total_timesteps // args.batch_size
     args.num_iterations = 5
-    run_name = f"{args.exp_name}__seed_{args.seed}__{int(time.time())}"
     print(f"running name: {run_name}")
 
     if args.run_dir is None:
@@ -385,8 +384,6 @@ def train(args: PPOArgs):
             )
 
     if args.save_model:
-        model_path = f"runs/{run_name}/{args.exp_name}.cleanrl_model"
-        save_model(model_path, agent_state, args)
         model_path = f"{args.run_dir}/{args.exp_name}.cleanrl_model"
         with open(model_path, "wb") as f:
             f.write(
@@ -408,12 +405,6 @@ def train(args: PPOArgs):
     writer.close()
 
     print("Saving loss plot...")
-    simple_plot(
-        list(range(len(returns))),
-        returns,
-        show_window=True,
-        filename=f"runs/{run_name}/{args.exp_name}_losses.png",
-    )
     plt.plot(losses)
     plt.title("PPO Loss, mean over minibatches")
     plt.savefig(f"{args.run_dir}/{args.exp_name}_losses.png")