docstr: the time step is increased. param list is used between current and the next
  time step.
  
  Args:
      param_list (List[torch.nn.Parameter]): a list of torch parameters.
docstr_tok: ["the","time","step","is","increased",".","param","list","is","used","between","current","and","the","next","time","step",".","Args",":","param_list","(","List","[","torch.nn.Parameter","]",")",":","a","list","of","torch","parameters","."]
code: def increase_preop_step(self, param_list: List[torch.nn.Parameter]):
      """
      the time step is increased. param list is used between current and the next
      time step.
  
      Args:
          param_list (List[torch.nn.Parameter]): a list of torch parameters.
      """
      for p in param_list:
          if p not in self._param_step_dict:
              self._param_step_dict[p] = [self._preop_step]
          else:
              self._param_step_dict[p].append(self._preop_step)
          self._param_runtime_order.append(p)
      self._step_param_dict[self._preop_step] = param_list
      self._preop_step += 1
  
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 6 for calling the MemStats obj's underlying member method code with example usage: obj.increase_preop_step(param_list) without return types