code: def decode_boxes(bbox, size):
      """Convert yxyx [0, 1] normalized boxes to xyxy unnormalized format."""
      y0, x0, y1, x1 = tf.split(bbox, 4, axis=-1)
      h = tf.cast(size[0], tf.float32)
      w = tf.cast(size[1], tf.float32)
  
      y0 = tf.clip_by_value(y0 * h, 0.0, h)
      x0 = tf.clip_by_value(x0 * w, 0.0, w)
      y1 = tf.clip_by_value(y1 * h, 0.0, h)
      x1 = tf.clip_by_value(x1 * w, 0.0, w)
  
      bbox = tf.concat([x0, y0, x1, y1], axis=-1)
      return bbox
  
imports: import functools
  from typing import Any, Callable, Mapping, Optional
  from absl import logging
  from flax import jax_utils
  import jax
  import jax.numpy
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  from scenic.dataset_lib.coco_dataset import coco_utils
  from scenic.projects.baselines.detr import transforms
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling a global function with example usage: decode_boxes(bbox, size) and returns: bbox