code: def normalize_box(box, width, height):
      return [
          int(1000 * (box[0] / width)),
          int(1000 * (box[1] / height)),
          int(1000 * (box[2] / width)),
          int(1000 * (box[3] / height)),
      ]
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
imports: from typing import List, Optional, Union
  import numpy
  from PIL import Image
  from transformers.image_utils import PILImageResampling
  from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
  from ...image_utils import ImageFeatureExtractionMixin, is_torch_tensor
  from ...utils import TensorType, is_pytesseract_available, logging, requires_backends
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_box(box, width, height) and returns: list