class_docstr: Example of a custom env, for which you can specify rendering behavior.
class_docstr_tok: ["Example","of","a","custom","env",",","for","which","you","can","specify","rendering","behavior","."]
code: def __init__(self, config):
      self.end_pos = config.get("corridor_length", 10)
      self.max_steps = config.get("max_steps", 100)
      self.cur_pos = 0
      self.steps = 0
      self.action_space = Discrete(2)
      self.observation_space = Box(
          0.0, 999.0, shape=(1,), dtype=np.float32
      )
  
file_path: ray/rllib/examples/env_rendering_and_recording.py
imports: import argparse
  import gymnasium
  import numpy
  import ray
  from gymnasium.spaces import Box, Discrete
  from ray import air, tune
  from ray.rllib.algorithms.ppo import PPOConfig
  from ray.rllib.env.multi_agent_env import make_multi_agent
label_desc: Use image node_id 1 to create a new CustomRenderedEnv object from inherited base classes: gym with example: obj = CustomRenderedEnv(config)