code: def finish_plan(self, new_plan: SavePlan) -> SavePlan:
      self.plan = new_plan
      return new_plan
  
imports: import dataclasses
  import io
  import logging
  import operator
  from collections import ChainMap
  from functools import reduce
  from typing import Any, cast, Dict, List, Tuple, Union
  import torch
  from torch.distributed._shard._utils import narrow_tensor_by_index
  from torch.distributed._tensor import DTensor
  from torch.distributed.checkpoint._dedup_tensors import dedup_tensors
  from torch.distributed.checkpoint._nested_dict import FLATTEN_MAPPING, flatten_state_dict
  from torch.distributed.checkpoint._sharded_tensor_utils import _flatten_sharded_tensors
  from torch.distributed.checkpoint._traverse import set_element
  from torch.distributed.checkpoint.metadata import BytesStorageMetadata, ChunkStorageMetadata, Metadata, MetadataIndex, STATE_DICT_TYPE, STORAGE_TYPES, TensorStorageMetadata
  from torch.distributed.checkpoint.planner import LoadPlan, LoadPlanner, ReadItem, SavePlan, SavePlanner, WriteItem, WriteItemType
  from torch.distributed.checkpoint.planner_helpers import _create_default_metadata_only_plan, _create_read_items, _create_write_items, _init_state_dict
  from torch.distributed.checkpoint.utils import find_state_dict_object
label_desc: Use image node_id 5 for calling the DefaultSavePlanner obj's underlying member method code with example usage: obj.finish_plan(new_plan) and returns: new_plan