code: def pad_to_min_shape(image, label, roi_shape=(128, 128, 128)):
      current_shape = image.shape[1:]
      bounds = [
          max(0, roi_shape[i] - current_shape[i]) for i in range(3)
      ]
      paddings = [(0, 0)] + [
          (bounds[i] // 2, bounds[i] - bounds[i] // 2) for i in range(3)
      ]
      image = np.pad(image, paddings, mode="edge")
      label = np.pad(label, paddings, mode="edge")
      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 5 for calling a global function with example usage: pad_to_min_shape(image, label, roi_shape) and returns: image,  label