class_docstr: Example of a curriculum learning capable env.
  
  This simply wraps a FrozenLake-v1 env and makes it harder with each
  task. Task (difficulty levels) can range from 1 to 10.
code: def step(self, action):
      self._timesteps += 1
      obs, rew, done, truncated, info = self.frozen_lake.step(action)
      # Make rewards scale with the level exponentially:
      # Level 1: x1
      # Level 2: x10
      # Level 3: x100, etc..
      rew *= 10 ** (self.cur_level - 1)
      if self._timesteps >= self.max_timesteps:
          done = True
      return obs, rew, done, truncated, info
  
file_path: ray/python/ray/rllib/examples/env/curriculum_capable_env.py
imports: import gymnasium
  import random
  from ray.rllib.env.apis.task_settable_env import TaskSettableEnv
  from ray.rllib.env.env_context import EnvContext
  from ray.rllib.utils.annotations import override
label_desc: Use image node_id 3 for calling the CurriculumCapableEnv obj's underlying member method code with example usage: obj.step(action) and returns: obs,  rew,  done,  truncated,  info