code: def clean_state_dict_for_safetensors(state_dict: dict):
      """
      Cleans the state dictionary from a model and removes tensor aliasing if present.
  
      Args:
          state_dict (`dict`):
              The state dictionary from a model
      """
      ptrs = collections.defaultdict(list)
      # When bnb serialization is used, weights in state dict can be strings
      for name, tensor in state_dict.items():
          if not isinstance(tensor, str):
              ptrs[id_tensor_storage(tensor)].append(name)
  
      # These are all pointers of tensors with shared memory
      shared_ptrs = {
          ptr: names for ptr, names in ptrs.items() if len(names) > 1
      }
      warn_names = set()
      for names in shared_ptrs.values():
          # When not all duplicates have been cleaned, we still remove those keys but put a clear warning.
          # If the link between tensors was done at runtime then `from_pretrained` will not get
          # the key back leading to random tensor. A proper warning will be shown
          # during reload (if applicable), but since the file is not necessarily compatible with
          # the config, better show a proper warning.
          found_names = [name for name in names if name in state_dict]
          warn_names.update(found_names[1:])
          for name in found_names[1:]:
              del state_dict[name]
      if len(warn_names) > 0:
          logger.warning(
              f"Removed shared tensor {warn_names} while saving. This should be OK, but check by verifying that you don't receive any warning while reloading",
          )
      state_dict = {
          k: v.contiguous() if isinstance(v, torch.Tensor) else v
          for k, v in state_dict.items()
      }
      return state_dict
  
imports: import collections
  import os
  import platform
  import re
  import socket
  from contextlib import contextmanager
  from functools import partial
  from types import MethodType
  from typing import OrderedDict
  import torch
  from packaging.version import Version
  from safetensors.torch import save_file
  from ..commands.config.default import write_basic_config
  from ..logging import get_logger
  from ..state import PartialState
  from .constants import FSDP_PYTORCH_VERSION
  from .dataclasses import DistributedType
  from .imports import is_deepspeed_available, is_torch_distributed_available, is_tpu_available
  from .modeling import id_tensor_storage
  from .transformer_engine import convert_model
  from .versions import is_torch_version
label_desc: Use image node_id 4 for calling a global function with example usage: clean_state_dict_for_safetensors(state_dict) and returns: state_dict