class_docstr: Handles partitioning and gathering of parameters.
code: def __release_param(self, param: Parameter) -> None:
      if (
          param.ds_status == ZeroParamStatus.AVAILABLE
          and not param.ds_active_sub_modules
      ):
          debug_rank0(f"-release: {param.ds_summary()}")
          param.partition()
          self.__n_available_params -= param.ds_numel
  
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 18 for calling the PartitionedParameterCoordinator obj's underlying member method code with example usage: obj.__release_param(param) without return types