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
  import torchvision.transforms
  from lightning.pytorch import LightningModule, Trainer, cli_lightning_logo
  from PIL import Image
  from torch import nn
  from torch.utils.data import DataLoader, Dataset
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