code: def _create_synth_kitti_dataset(
      path_dir: str, image_dims: tuple = (1024, 512)
  ):
      """
      Create synthetic dataset with random images,
      just to simulate that the dataset have been already downloaded.
      """
      path_dir_images = os.path.join(path_dir, KITTI.IMAGE_PATH)
      path_dir_masks = os.path.join(path_dir, KITTI.MASK_PATH)
      for p_dir in (path_dir_images, path_dir_masks):
          os.makedirs(p_dir, exist_ok=True)
      for i in range(3):
          path_img = os.path.join(
              path_dir_images, f"dummy_kitti_{i}.png"
          )
          Image.new("RGB", image_dims).save(path_img)
          path_mask = os.path.join(
              path_dir_masks, f"dummy_kitti_{i}.png"
          )
          Image.new("L", image_dims).save(path_mask)
  
imports: import os
  import random
  from argparse import ArgumentParser, Namespace
  import numpy
  import torch
  import torch.nn.functional
  from bigdl.nano.pytorch.vision.transforms import transforms
  from PIL import Image
  from torch.utils.data import DataLoader, Dataset
  from typing import Union
  import pytorch_lightning
  from pl_examples import cli_lightning_logo
  from pl_examples.domain_templates.unet import UNet
  from pytorch_lightning.utilities.argparse import from_argparse_args
  from bigdl.nano.pytorch import Trainer
label_desc: Use image node_id 1 for calling a global function with example usage: _create_synth_kitti_dataset(path_dir, image_dims) without return types