docstr: Mapping master parameter and working parameter
  
  Args:
      master_param (Tensor): The parameter copy in optimizer
      working_param (Tensor): The parameter of the model
docstr_tok: ["Mapping","master","parameter","and","working","parameter","Args",":","master_param","(","Tensor",")",":","The","parameter","copy","in","optimizer","working_param","(","Tensor",")",":","The","parameter","of","the","model"]
code: def link_master_and_working_param(
      self, master_param: Tensor, working_param: Tensor
  ):
      """Mapping master parameter and working parameter
  
      Args:
          master_param (Tensor): The parameter copy in optimizer
          working_param (Tensor): The parameter of the model
      """
  
      self.master_to_working_param[id(master_param)] = working_param
      self.working_to_master_param[id(working_param)] = master_param
  
file_path: colossalai/colossalai/zero/low_level/bookkeeping/parameter_store.py
imports: from torch import Tensor
  from torch.distributed import ProcessGroup
  from .base_store import BaseStore
label_desc: Use image node_id 4 for calling the ParameterStore obj's underlying member method code with example usage: obj.link_master_and_working_param(master_param, working_param) without return types