code: def __init__(
      self,
      module,
      timers,
      ds_config,
      overlap_comm=True,
      prefetch_bucket_size=50000000,
      max_reuse_distance=1000000000,
      max_live_parameters=1000000000,
      param_persistence_threshold=100000,
      model_persistence_threshold=sys.maxsize,
      offload_param_config=None,
      mpu=None,
  ):
      see_memory_usage(
          "DeepSpeedZeRoOffload initialize [begin]", force=True
      )
  
      print_rank_0(
          f"initialized {__class__.__name__} with args: {locals()}",
          force=False,
      )
  
      self.module = module
      self.dtype = list(module.parameters())[0].dtype
      self.offload_device = None
      self.offload_param_pin_memory = False
  
      if (
          offload_param_config is not None
          and offload_param_config.device != OffloadDeviceEnum.none
      ):
          self.offload_device = offload_param_config.device
          self.offload_param_pin_memory = (
              offload_param_config.pin_memory
          )
  
      self._convert_to_zero_parameters(ds_config, module, mpu)
  
      for m in module.modules():
          _init_external_params(m)
  
      _inject_parameters(module, ZeROOrderedDict)
  
      self.param_numel_persistence_threshold = int(
          param_persistence_threshold
      )
      self.model_persistence_threshold = int(
          model_persistence_threshold
      )
      self.persistent_parameters = self.mark_persistent_parameters(
          self.param_numel_persistence_threshold,
          self.model_persistence_threshold,
      )
  
      self.param_coordinators = {}
      self._prefetch_bucket_sz = int(prefetch_bucket_size)
      self._max_reuse_distance_in_numel = int(max_reuse_distance)
      self._max_available_parameters_in_numel = int(max_live_parameters)
      self.__allgather_stream = (
          Stream() if overlap_comm else torch.cuda.default_stream()
      )
  
      self.forward_hooks = []
      self.backward_hooks = []
      self.setup_zero_stage3_hooks()
      print_rank_0(
          f"Created module hooks: forward = {len(self.forward_hooks)}, backward = {len(self.backward_hooks)}",
          force=False,
      )
  
      see_memory_usage(
          "DeepSpeedZeRoOffload initialize [end]", force=True
      )
  
imports: import sys
  import torch
  from torch.cuda import Stream
  from collections import OrderedDict
  from deepspeed.runtime.utils import see_memory_usage
  from deepspeed.runtime.zero.offload_config import OffloadDeviceEnum
  from deepspeed.runtime.zero.partition_parameters import _init_external_params
  from deepspeed.runtime.zero.partition_parameters import *
  from deepspeed.runtime.zero.partitioned_param_coordinator import PartitionedParameterCoordinator, iter_params
  from deepspeed import comm
label_desc: Use image node_id 1 to create a new DeepSpeedZeRoOffload object from inherited base classes: object with example: obj = DeepSpeedZeRoOffload(module, timers, ds_config, overlap_comm, prefetch_bucket_size, max_reuse_distance, max_live_parameters, param_persistence_threshold, model_persistence_threshold, offload_param_config, mpu)