code: def center_crop(image, size):
      size = (size, size) if isinstance(size, int) else size
      orig_height, orig_width, _ = image.shape
      crop_height, crop_width = size
      top = (orig_height - orig_width) // 2
      left = (orig_width - crop_width) // 2
      image = tf.image.crop_to_bounding_box(
          image, top, left, crop_height, crop_width
      )
      return image
  
imports: import json
  import logging
  import os
  import sys
  import warnings
  from dataclasses import dataclass, field
  from typing import Optional
  import evaluate
  import numpy
  import tensorflow
  from datasets import load_dataset
  from PIL import Image
  import transformers
  from transformers import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING, AutoConfig, AutoImageProcessor, DefaultDataCollator, HfArgumentParser, PushToHubCallback, TFAutoModelForImageClassification, TFTrainingArguments, create_optimizer, set_seed
  from transformers.keras_callbacks import KerasMetricCallback
  from transformers.trainer_utils import get_last_checkpoint, is_main_process
  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 a global function with example usage: center_crop(image, size) and returns: image