code: def __init__(self, flip_prob):
      self.flip_prob = flip_prob
  
imports: import json
  import logging
  import os
  import random
  import sys
  from dataclasses import dataclass, field
  from typing import Optional
  import numpy
  import torch
  from datasets import load_dataset
  from PIL import Image
  from torch import nn
  from torchvision import transforms
  from torchvision.transforms import functional
  import evaluate
  import transformers
  from huggingface_hub import hf_hub_download
  from transformers import AutoConfig, AutoFeatureExtractor, AutoModelForSemanticSegmentation, HfArgumentParser, Trainer, TrainingArguments, default_data_collator
  from transformers.trainer_utils import get_last_checkpoint
  from transformers.utils import check_min_version, send_example_telemetry
  from transformers.utils.versions import require_version
label_desc: Use image node_id 1 to create a new RandomHorizontalFlip object  with example: obj = RandomHorizontalFlip(flip_prob)