code: def get_mask_transform(pad_mode):
      if pad_mode == "resize":
          return transforms.Compose(
              [
                  transforms.Resize((H, W)),
                  transforms.Lambda(mask_to_tensor),
              ]
          )
      else:
          return transforms.Compose(
              [
                  transforms.Lambda(mask_to_tensor),
              ]
          )
  
imports: import os, cv2, glob
  import numpy
  from PIL import Image
  import torch
  import torch.utils.data
  from torchvision import datasets, models, transforms
  from utils import read_masks, get_test_meta, get_nfold_split
  import augmentation
  from settings import *
label_desc: Use image node_id 4 for calling a global function with example usage: get_mask_transform(pad_mode) and returns: transforms, transforms