class_docstr: A Policy that leaks very little memory.
  
  Useful for proving that our memory-leak tests can catch the
  slightest leaks.
class_docstr_tok: ["A","Policy","that","leaks","very","little","memory",".","Useful","for","proving","that","our","memory-leak","tests","can","catch","the","slightest","leaks","."]
code: def __init__(
      self,
      observation_space: gym.Space,
      action_space: gym.Space,
      config: AlgorithmConfigDict,
  ):
      super().__init__(observation_space, action_space, config)
      self._leakage_size = config.get("leakage_size", "small")
      self._leak = []
  
file_path: ray/rllib/examples/policy/memory_leaking_policy.py
imports: import gymnasium
  from ray.rllib.examples.policy.random_policy import RandomPolicy
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.typing import AlgorithmConfigDict
label_desc: Use image node_id 1 to create a new MemoryLeakingPolicy object from inherited base classes: RandomPolicy with example: obj = MemoryLeakingPolicy(observation_space, action_space, config)