class_docstr: Tracks the current state of a (possibly multi-agent) episode.
class_docstr_tok: ["Tracks","the","current","state","of","a","(","possibly","multi-agent",")","episode","."]
docstr: Advance the episode forward by one step.
docstr_tok: ["Advance","the","episode","forward","by","one","step","."]
code: def step(self) -> None:
      """Advance the episode forward by one step."""
      self.active_env_steps += 1
      self.total_env_steps += 1
  
imports: import random
  from collections import defaultdict
  import numpy
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple
  from ray.rllib.env.base_env import _DUMMY_AGENT_ID
  from ray.rllib.evaluation.collectors.simple_list_collector import _PolicyCollector, _PolicyCollectorGroup
  from ray.rllib.evaluation.collectors.agent_collector import AgentCollector
  from ray.rllib.policy.policy_map import PolicyMap
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.annotations import DeveloperAPI
  from ray.rllib.utils.typing import AgentID, EnvID, EnvInfoDict, PolicyID, TensorType
label_desc: Use image node_id 5 for calling the EpisodeV2 obj's underlying member method code with example usage: obj.step() without return types