code: def __call__(self, image, target):
      for t in self.transforms:
          image, target = t(image, target)
      return image, target
  
imports: import argparse
  import json
  import math
  import os
  import random
  from pathlib import Path
  import datasets
  import numpy
  import torch
  from datasets import load_dataset
  from PIL import Image
  from torch.utils.data import DataLoader
  from torchvision import transforms
  from torchvision.transforms import functional
  from tqdm.auto import tqdm
  import evaluate
  import transformers
  from accelerate import Accelerator
  from accelerate.logging import get_logger
  from accelerate.utils import set_seed
  from huggingface_hub import Repository, hf_hub_download
  from transformers import AutoConfig, AutoFeatureExtractor, AutoModelForSemanticSegmentation, SchedulerType, default_data_collator, get_scheduler
  from transformers.utils import check_min_version, get_full_repo_name, send_example_telemetry
  from transformers.utils.versions import require_version
label_desc: Use image node_id 2 for calling the Compose obj's underlying member method code with example usage: obj.__call__(image, target) and returns: image,  target