Stagger game start times

codecraft.py

@@ -9,9 +9,12 @@
 
 RETRIES = 100
 
-def create_game() -> int:
+def create_game(game_length = None) -> int:
     try:
-        response = requests.post('http://localhost:9000/start-game').json()
+        if game_length:
+            response = requests.post(f'http://localhost:9000/start-game?maxTicks={game_length}').json()
+        else:
+            response = requests.post('http://localhost:9000/start-game').json()
         return int(response['id'])
     except requests.exceptions.ConnectionError:
         logging.info(f"Connection error on create_game, retrying")

gym_codecraft/envs/codecraft_vec_env.py

@@ -9,7 +9,7 @@
 
 
 class CodeCraftVecEnv(VecEnv):
-    def __init__(self, num_envs):
+    def __init__(self, num_envs, game_length):
         observations_low = []
         observations_high = []
         # Drone x, y
@@ -26,25 +26,27 @@ def __init__(self, num_envs):
             # size
             observations_low.append(0)
             observations_high.append(2)
-
         super().__init__(
             num_envs,
             spaces.Box(
                 low=np.array(observations_low),
                 high=np.array(observations_high),
                 dtype=np.float32),
             spaces.Discrete(6))
+
         self.games = []
         self.eplen = []
         self.eprew = []
         self.score = []
+        self.game_length = game_length
 
     def reset(self):
         self.games = []
         self.eplen = []
         self.score = []
-        for _ in range(self.num_envs):
-            game_id = codecraft.create_game()
+        for i in range(self.num_envs):
+            # spread out initial game lengths to stagger start times
+            game_id = codecraft.create_game((self.game_length * (i + 1) // self.num_envs))
             # print("Starting game:", game_id)
             self.games.append(game_id)
             self.eplen.append(1)

main.py

@@ -48,15 +48,16 @@ def run_codecraft():
 
 
 def train(hps):
-  env = envs.CodeCraftVecEnv(64)
-  ppo2.learn(
-          network=lambda it: network(hps, it),
-    env=env,
-    gamma=0.9,
-    nsteps=hps["rosteps"],
-    total_timesteps=hps["steps"],
-    log_interval=1,
-    lr=hps["lr"])
+    num_envs = 64 * 128 // hps["rosteps"]
+    env = envs.CodeCraftVecEnv(num_envs, 3 * 60 * 60)
+    ppo2.learn(
+        network=lambda it: network(hps, it),
+        env=env,
+        gamma=0.9,
+        nsteps=hps["rosteps"],
+        total_timesteps=hps["steps"],
+        log_interval=1,
+        lr=hps["lr"])
 
 def network(hps, input_tensor):
     #with tf.variable_scope(scope, reuse=reuse):