chore: import upstream snapshot with attribution

rllib/examples/envs/classes/repeat_initial_obs_env.py

@@ -0,0 +1,33 @@
+import random
+
+import gymnasium as gym
+from gymnasium.spaces import Discrete
+
+
+class RepeatInitialObsEnv(gym.Env):
+    """Env in which the initial observation has to be repeated all the time.
+
+    Runs for n steps.
+    r=1 if action correct, -1 otherwise (max. R=100).
+    """
+
+    def __init__(self, episode_len=100):
+        self.observation_space = Discrete(2)
+        self.action_space = Discrete(2)
+        self.token = None
+        self.episode_len = episode_len
+        self.num_steps = 0
+
+    def reset(self, *, seed=None, options=None):
+        self.token = random.choice([0, 1])
+        self.num_steps = 0
+        return self.token, {}
+
+    def step(self, action):
+        if action == self.token:
+            reward = 1
+        else:
+            reward = -1
+        self.num_steps += 1
+        done = truncated = self.num_steps >= self.episode_len
+        return 0, reward, done, truncated, {}