code: def load_offloaded_weights(model, index, offload_folder):
      """
      Loads the weights from the offload folder into the model.
  
      Args:
          model (`torch.nn.Module`):
              The model to load the weights into.
          index (`dict`):
              A dictionary containing the parameter name and its metadata for each parameter that was offloaded from the
              model.
          offload_folder (`str`):
              The folder where the offloaded weights are stored.
      """
      if index is None or len(index) == 0:
          # Nothing to do
          return
      for param_name, metadata in index.items():
          if "SCB" in param_name:
              continue
          fp16_statistics = None
          if (
              "weight" in param_name
              and param_name.replace("weight", "SCB") in index.keys()
          ):
              weight_name = param_name.replace("weight", "SCB")
              fp16_statistics = load_offloaded_weight(
                  os.path.join(offload_folder, f"{weight_name}.dat"),
                  index[weight_name],
              )
          tensor_file = os.path.join(
              offload_folder, f"{param_name}.dat"
          )
          weight = load_offloaded_weight(tensor_file, metadata)
          set_module_tensor_to_device(
              model,
              param_name,
              "cpu",
              value=weight,
              fp16_statistics=fp16_statistics,
          )
  
imports: import contextlib
  import gc
  import inspect
  import json
  import logging
  import os
  import re
  import shutil
  import tempfile
  from collections import OrderedDict, defaultdict
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from ..state import AcceleratorState
  from .constants import SAFE_WEIGHTS_NAME, WEIGHTS_NAME
  from .dataclasses import AutocastKwargs, CustomDtype, DistributedType
  from .imports import is_mps_available, is_npu_available, is_xpu_available
  from .offload import load_offloaded_weight, offload_weight, save_offload_index
  from .tqdm import is_tqdm_available, tqdm
  from safetensors import safe_open
  from safetensors.torch import load_file
label_desc: Use image node_id 19 for calling a global function with example usage: load_offloaded_weights(model, index, offload_folder) without return types