class_docstr: Base MixIn for all Post-Normalization modules. The interface represented by this
  module is:
  
  residual, hidden_out = norm(residual + hidden_in)
  
  If residual and hidden_out are the same data type, then they may alias each other.
  Furthermore, residual should be updated in-place.
class_docstr_tok: ["Base","MixIn","for","all","Post-Normalization","modules",".","The","interface","represented","by","this","module","is",":","residual",",","hidden_out","=","norm","(","residual","+","hidden_in",")","If","residual","and","hidden_out","are","the","same","data","type",",","then","they","may","alias","each","other",".","Furthermore",",","residual","should","be","updated","in-place","."]
code: def __init__(
      self, config: DSNormConfig, implementation_config: Dict[str, Any]
  ) -> None:
      super().__init__(config, implementation_config)
  
file_path: DeepSpeed/deepspeed/inference/v2/modules/interfaces/post_norm_base.py
imports: from abc import abstractmethod
  from typing import Any, Dict, Optional, Tuple, Type
  import torch
  from deepspeed.runtime.config_utils import DeepSpeedConfigModel
  from ..ds_module import DSModuleBase
  from ..configs.norm_config import DSNormConfig
  from ..module_registry import DSModuleRegistryBase
  from ...inference_parameter import InferenceParameter
label_desc: Use image node_id 2 to create a new DSPostNormBase object from inherited base classes: DSModuleBase with example: obj = DSPostNormBase(config, implementation_config)