code: def forward(self, x: Image) -> torch.Tensor:
      with torch.no_grad():
          x = self.transforms(x)
      return x
  
imports: import logging
  import os
  import sys
  from dataclasses import dataclass, field
  from typing import Optional
  import torch
  from datasets import load_dataset
  from PIL import Image
  from torchvision.io import ImageReadMode, read_image
  from torchvision.transforms import CenterCrop, ConvertImageDtype, Normalize, Resize
  from torchvision.transforms.functional import InterpolationMode
  import transformers
  from transformers import AutoFeatureExtractor, AutoModel, AutoTokenizer, HfArgumentParser, Trainer, TrainingArguments, set_seed
  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 2 for calling the Transform obj's underlying member method code with example usage: obj.forward(x) and returns: x