code: def get_provisional_boxes(pred, box, is_subword, start_idx=0):
      prov_predictions = [
          pred_ for idx, pred_ in enumerate(pred) if not is_subword[idx]
      ][start_idx:]
      prov_boxes = [
          box_ for idx, box_ in enumerate(box) if not is_subword[idx]
      ][start_idx:]
      return prov_predictions, prov_boxes
  
imports: from concurrent.futures import ThreadPoolExecutor
  from typing import List
  from transformers import LayoutLMv3ForTokenClassification
  from marker.bbox import unnormalize_box
  from transformers.models.layoutlmv3.image_processing_layoutlmv3 import normalize_box
  import io
  from PIL import Image
  from transformers import LayoutLMv3Processor
  import numpy
  from marker.settings import settings
  from marker.schema import Page, BlockType
  import torch
  from math import isclose
label_desc: Use image node_id 3 for calling a global function with example usage: get_provisional_boxes(pred, box, is_subword, start_idx) and returns: prov_predictions,  prov_boxes