class_docstr: An extension of the torch.Tensor class to support our inference focused features. One important
  thing to note here is that an InferenceParam can be used a torch.Tensor, but outputs of
  torch.Tensor operations will not be InferenceParams.
docstr: Create the inference parameter.
code: def initialize(
      cls, core_param: torch.Tensor, **kwargs
  ) -> "InferenceParameter":
      """
      Create the inference parameter.
      """
      param = InferenceParameter(core_param)
      setattr(param, "_aux_attrs", kwargs)
  
      for attr_name, attr in kwargs.items():
          if hasattr(param, attr_name):
              raise ValueError(
                  f"Attribute {attr_name} already exists on param."
              )
  
          if not isinstance(attr, torch.Tensor):
              raise ValueError(
                  f"Attribute {attr_name} must be a tensor."
              )
  
          setattr(param, attr_name, attr)
  
      return param
  
file_path: DeepSpeed/deepspeed/inference/v2/inference_parameter.py
imports: from typing import Dict
  import torch
label_desc: Use image node_id 3 for calling the InferenceParameter obj's underlying member method code with example usage: obj.initialize(cls, core_param) and returns: param