code: def unpack_dataset(folder, threads=8, key="data"):
      p = Pool(threads)
      npz_files = [
          os.path.join(folder, path)
          for path in os.listdir(folder)
          if os.path.isfile(os.path.join(folder, path))
          and path.endswith(".npz")
      ]
      npz_files.sort()
      p.map(convert_to_npy, zip(npz_files, [key] * len(npz_files)))
      p.close()
      p.join()
  
imports: import os
  import pickle
  import glob
  import json
  import numpy
  from multiprocessing import Pool
  from collections import OrderedDict
  from sklearn.model_selection import KFold
  from typing import List
  from medicalseg.datasets import MedicalDataset
  from medicalseg.cvlibs import manager
  from nnunet.transforms import get_moreDA_augmentation, default_2D_augmentation_params, default_3D_augmentation_params
  from nnunet.transforms import rotate_coords_3d, rotate_coords_2d, NumpyToTensor
  from .dataloader import DataLoader2D, DataLoader3D
  from tools.preprocess_utils import verify_dataset_integrity, convert_to_decathlon, crop, ExperimentPlanner2D_v21, ExperimentPlanner3D_v21, DatasetAnalyzer
label_desc: Use image node_id 1 for calling a global function with example usage: unpack_dataset(folder, threads, key) without return types