code: def preprocess(file_path):
      image, label, image_spacings = load_pair(file_path)
      image, label = resample3d(image, label, image_spacings)
      image = normal_intensity(image.copy())
      image, label = pad_to_min_shape(image, label)
      return image, label
  
file_path: tinygrad/extra/datasets/kits19.py
imports: import random
  import functools
  from pathlib import Path
  import numpy
  import nibabel
  from scipy import signal
  import torch
  import torch.nn.functional
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import fetch
label_desc: Use image node_id 6 for calling a global function with example usage: preprocess(file_path) and returns: image,  label