class_docstr: Class containing attributes to pass to input/output class constructors.
  
  RLlib auto-sets these attributes when constructing input/output classes,
  such as InputReaders and OutputWriters.
docstr: Returns the RolloutWorker's SamplerInput object, if any.
  
  Returns None if the RolloutWorker has no SamplerInput. Note that local
  workers in case there are also one or more remote workers by default
  do not create a SamplerInput object.
  
  Returns:
      The RolloutWorkers' SamplerInput object or None if none exists.
docstr_tok: ["Returns","the","RolloutWorker","'s","SamplerInput","object",",","if","any",".","Returns","None","if","the","RolloutWorker","has","no","SamplerInput",".","Note","that","local","workers","in","case","there","are","also","one","or","more","remote","workers","by","default","do","not","create","a","SamplerInput","object",".","Returns",":","The","RolloutWorkers","'","SamplerInput","object","or","None","if","none","exists","."]
code: def default_sampler_input(self) -> Optional["SamplerInput"]:
      """Returns the RolloutWorker's SamplerInput object, if any.
  
      Returns None if the RolloutWorker has no SamplerInput. Note that local
      workers in case there are also one or more remote workers by default
      do not create a SamplerInput object.
  
      Returns:
          The RolloutWorkers' SamplerInput object or None if none exists.
      """
      return self.worker.sampler
  
file_path: ray/rllib/offline/io_context.py
imports: import os
  from typing import Optional, TYPE_CHECKING
  from ray.rllib.utils.annotations import PublicAPI
label_desc: Use image node_id 2 for calling the IOContext obj's underlying member method code with example usage: obj.default_sampler_input() and returns: self