code: def _create_default_metadata_only_plan(
      state_dict: STATE_DICT_TYPE,
  ) -> SavePlan:
      requests = []
      for fqn, obj in state_dict.items():
          if isinstance(obj, DTensor):
              requests.append(_create_write_items_for_dtensor(fqn, obj))
          elif isinstance(obj, ShardedTensor):
              for shard_md in obj.metadata().shards_metadata:
                  requests.append(
                      _create_write_item_for_shard(fqn, obj, shard_md)
                  )
          elif isinstance(obj, torch.Tensor):
              requests.append(_create_write_item_for_tensor(fqn, obj))
          else:
              requests.append(_create_write_item_for_bytesio(fqn, obj))
      return SavePlan(requests)
  
imports: from typing import Any, cast, List
  import torch
  import torch.distributed
  from torch._utils import _get_device_module
  from torch.distributed._shard.metadata import ShardMetadata
  from torch.distributed._shard.sharded_tensor import ShardedTensor
  from torch.distributed._shard.sharded_tensor.metadata import TensorProperties
  from torch.distributed._tensor import DTensor
  from torch.distributed._tensor._utils import compute_local_shape_and_global_offset
  from torch.utils._pytree import tree_map_only
  from .metadata import BytesStorageMetadata, ChunkStorageMetadata, MetadataIndex, STATE_DICT_TYPE, STORAGE_TYPES, TensorStorageMetadata
  from .planner import LoadItemType, ReadItem, SavePlan, TensorWriteData, WriteItem, WriteItemType
  from .resharding import _check_shard_metadata_pair_overlap, _shards_get_overlap_region_wrt_saved_tensor
label_desc: Use image node_id 11 for calling a global function with example usage: _create_default_metadata_only_plan(state_dict) and returns: SavePlan