class_docstr: Base class for all DeepSpeed Inference modules. This class establishes
  the basic attributes of a DSModule. Only abstract functionality modules should inherit
  directly from this class, not specific implementations.
class_docstr_tok: ["Base","class","for","all","DeepSpeed","Inference","modules",".","This","class","establishes","the","basic","attributes","of","a","DSModule",".","Only","abstract","functionality","modules","should","inherit","directly","from","this","class",",","not","specific","implementations","."]
docstr: Return the associated config class for this module.
  
  This should be implemented (along with the config class) by an abstract functionality
  module.
docstr_tok: ["Return","the","associated","config","class","for","this","module",".","This","should","be","implemented","(","along","with","the","config","class",")","by","an","abstract","functionality","module","."]
code: def config_class() -> Type[DSModuleConfig]:
      """
      Return the associated config class for this module.
  
      This should be implemented (along with the config class) by an abstract functionality
      module.
      """
      ...
  
file_path: DeepSpeed/deepspeed/inference/v2/modules/ds_module.py
imports: from abc import ABC, abstractstaticmethod
  from typing import Any, Dict, Type
  import torch
  from deepspeed.runtime.config_utils import DeepSpeedConfigModel
label_desc: Use image node_id 2 for calling the DSModuleBase obj's underlying member method code with example usage: obj.config_class() without return types