adding termination conditgion

cleanrl/ppo_rnd_envpool.py

@@ -37,6 +37,22 @@ def parse_args():
         help="the wandb's project name")
     parser.add_argument("--wandb-entity", type=str, default=None,
         help="the entity (team) of wandb's project")
+    parser.add_argument("--reward-goal", type=float, default=1.0, 
+        help="reward to give when the goal is achieved")
+    parser.add_argument("--reward-distance", type=float, default=1.0, 
+        help="reward to give when the goal is achieved")
+    parser.add_argument("--early-termination", type=lambda x: bool(strtobool(x)), default=True, nargs="?", const=True,
+        help="whether to terminate early i.e. when the catastrophe has happened")
+    parser.add_argument("--unifying-lidar", type=lambda x: bool(strtobool(x)), default=True, nargs="?", const=True,
+        help="what kind of sensor is used (same for every environment?)")
+    parser.add_argument("--term-cost", type=int, default=1,
+        help="how many violations before you terminate")
+    parser.add_argument("--failure-penalty", type=float, default=0.0,
+        help="Reward Penalty when you fail")
+    parser.add_argument("--collect-data", type=lambda x: bool(strtobool(x)), default=False, nargs="?", const=True,
+        help="store data while trianing")
+    parser.add_argument("--storage-path", type=str, default="./data/ppo/term_1",
+        help="the storage path for the data collected")
 
     # Algorithm specific arguments
     parser.add_argument("--env-id", type=str, default="MontezumaRevenge-v5",
@@ -140,9 +156,9 @@ def layer_init(layer, std=np.sqrt(2), bias_const=0.0):
 def make_env(cfg, idx, capture_video, run_name, gamma):
     def thunk():
         if capture_video:
-            env = gym.make(cfg.env_id)#, render_mode="rgb_array", early_termination=cfg.early_termination, term_cost=cfg.term_cost, failure_penalty=cfg.failure_penalty, reward_goal=cfg.reward_goal, reward_distance=cfg.reward_distance)
+            env = gym.make(cfg.env_id, render_mode="rgb_array", early_termination=cfg.early_termination, term_cost=cfg.term_cost, failure_penalty=cfg.failure_penalty, reward_goal=cfg.reward_goal, reward_distance=cfg.reward_distance)
         else:
-            env = gym.make(cfg.env_id)#, early_termination=cfg.early_termination, term_cost=cfg.term_cost, failure_penalty=cfg.failure_penalty, reward_goal=cfg.reward_goal, reward_distance=cfg.reward_distance)
+            env = gym.make(cfg.env_id, early_termination=cfg.early_termination, term_cost=cfg.term_cost, failure_penalty=cfg.failure_penalty, reward_goal=cfg.reward_goal, reward_distance=cfg.reward_distance)
         env = gym.wrappers.FlattenObservation(env)  # deal with dm_control's Dict observation space
         env = gym.wrappers.RecordEpisodeStatistics(env)
         if capture_video: