class_docstr: Update input callbacks to mutate batch with states entropy rewards.
class_docstr_tok: ["Update","input","callbacks","to","mutate","batch","with","states","entropy","rewards","."]
code: def __init__(
      self,
      *args,
      embeds_dim: int = 128,
      k_nn: int = 50,
      beta: float = 0.1,
      rho: float = 0.0001,
      beta_schedule: str = "constant",
      **kwargs,
  ):
      self.embeds_dim = embeds_dim
      self.k_nn = k_nn
      self.beta = beta
      self.rho = rho
      self.beta_schedule = beta_schedule
      self._rms = _MovingMeanStd()
      super().__init__(*args, **kwargs)
  
imports: import gc
  import os
  import platform
  import tracemalloc
  from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Type, Union
  import gymnasium
  import numpy
  from ray.rllib.core.rl_module.rl_module import RLModule
  from ray.rllib.env.base_env import BaseEnv
  from ray.rllib.env.env_context import EnvContext
  from ray.rllib.evaluation.episode import Episode
  from ray.rllib.evaluation.episode_v2 import EpisodeV2
  from ray.rllib.evaluation.postprocessing import Postprocessing
  from ray.rllib.policy import Policy
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.annotations import override, OverrideToImplementCustomLogic, PublicAPI
  from ray.rllib.utils.deprecation import deprecation_warning
  from ray.rllib.utils.exploration.random_encoder import _MovingMeanStd, compute_states_entropy, update_beta
  from ray.rllib.utils.typing import AgentID, EnvType, EpisodeType, PolicyID
  from ray.tune.callback import _CallbackMeta
  import psutil
label_desc: Use image node_id 1 to create a new RE3UpdateCallbacks object from inherited base classes: DefaultCallbacks with example: obj = RE3UpdateCallbacks()