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.
class_docstr_tok: ["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 reset(self, *, seed=None, options=None):
      if self.switch_env:
          self.switch_env = False
          self._make_lake()
      self._timesteps = 0
      return self.frozen_lake.reset(seed=seed, options=options)
  
file_path: 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 2 for calling the CurriculumCapableEnv obj's underlying member method code with example usage: obj.reset() and returns: self