docstr: param_used_step
  get the timestep list using the param
  
  Args:
      param (torch.nn.Parameter): a torch param
  
  Returns:
      Optional[List[int]]: a list of int indicates the time step of preop hook.
docstr_tok: ["param_used_step","get","the","timestep","list","using","the","param","Args",":","param","(","torch.nn.Parameter",")",":","a","torch","param","Returns",":","Optional","[","List","[","int","]","]",":","a","list","of","int","indicates","the","time","step","of","preop","hook","."]
code: def param_used_step(
      self, param: torch.nn.Parameter
  ) -> Optional[List[int]]:
      """param_used_step
      get the timestep list using the param
  
      Args:
          param (torch.nn.Parameter): a torch param
  
      Returns:
          Optional[List[int]]: a list of int indicates the time step of preop hook.
      """
      if param not in self._param_step_dict:
          return None
      else:
          return self._param_step_dict[param]
  
file_path: ColossalAI/colossalai/zero/gemini/memory_tracer/memory_stats.py
imports: from typing import List, Optional
  import torch
  from .param_runtime_order import OrderedParamGenerator
label_desc: Use image node_id 7 for calling the MemStats obj's underlying member method code with example usage: obj.param_used_step(param) and returns: None, self