class_docstr: Implements an exploration strategy for Policies.
  
  An Exploration takes model outputs, a distribution, and a timestep from
  the agent and computes an action to apply to the environment using an
  implemented exploration schema.
class_docstr_tok: ["Implements","an","exploration","strategy","for","Policies",".","An","Exploration","takes","model","outputs",",","a","distribution",",","and","a","timestep","from","the","agent","and","computes","an","action","to","apply","to","the","environment","using","an","implemented","exploration","schema","."]
docstr: Handles post-processing of done episode trajectories.
  
  Changes the given batch in place. This callback is invoked by the
  sampler after policy.postprocess_trajectory() is called.
  
  Args:
      policy: The owning policy object.
      sample_batch: The SampleBatch object to post-process.
      tf_sess: An optional tf.Session object.
docstr_tok: ["Handles","post-processing","of","done","episode","trajectories",".","Changes","the","given","batch","in","place",".","This","callback","is","invoked","by","the","sampler","after","policy.postprocess_trajectory","(",")","is","called",".","Args",":","policy",":","The","owning","policy","object",".","sample_batch",":","The","SampleBatch","object","to","post-process",".","tf_sess",":","An","optional","tf.Session","object","."]
code: def postprocess_trajectory(
      self,
      policy: "Policy",
      sample_batch: SampleBatch,
      tf_sess: Optional["tf.Session"] = None,
  ):
      """Handles post-processing of done episode trajectories.
  
      Changes the given batch in place. This callback is invoked by the
      sampler after policy.postprocess_trajectory() is called.
  
      Args:
          policy: The owning policy object.
          sample_batch: The SampleBatch object to post-process.
          tf_sess: An optional tf.Session object.
      """
      return sample_batch
  
file_path: ray/rllib/utils/exploration/exploration.py
imports: from gymnasium.spaces import Space
  from typing import Dict, List, Optional, Union, TYPE_CHECKING
  from ray.rllib.env.base_env import BaseEnv
  from ray.rllib.models.action_dist import ActionDistribution
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.annotations import DeveloperAPI, PublicAPI
  from ray.rllib.utils.framework import try_import_torch, TensorType
  from ray.rllib.utils.typing import LocalOptimizer, AlgorithmConfigDict
label_desc: Use image node_id 6 for calling the Exploration obj's underlying member method code with example usage: obj.postprocess_trajectory(policy, sample_batch, tf_sess) and returns: sample_batch