class_docstr: Handles partitioning and gathering of parameters.
docstr: use module trace to construct parameter trace
docstr_tok: ["use","module","trace","to","construct","parameter","trace"]
code: def construct_parameter_trace_from_module_trace(self):
      """use module trace to construct parameter trace"""
      self.__param_order = []
      for sub_module in self.__submodule_order:
          self.record_parameters(sub_module)
  
imports: from dataclasses import dataclass
  import collections
  from collections import UserDict
  from typing import Deque, Set
  from torch.cuda import Event, Stream
  from deepspeed import comm
  from deepspeed.utils.logging import logger
  from deepspeed.runtime.zero.offload_config import OffloadDeviceEnum
  from deepspeed.runtime.zero.partition_parameters import *
  from deepspeed.runtime.swap_tensor.partitioned_param_swapper import PartitionedParamStatus
  from deepspeed.utils.debug import debug_module2name_id, debug_param2name_id
label_desc: Use image node_id 10 for calling the PartitionedParameterCoordinator obj's underlying member method code with example usage: obj.construct_parameter_trace_from_module_trace() without return types