code: def decode_coco_deformable_detr_example(
      example: Mapping[str, Any]
  ) -> Mapping[str, Any]:
      """Given an instance and raw labels, creates <inputs, label> pair.
  
      Calls DETR decoder and then just converts the labels to those expected by
      deformable detr. Labels are the exact label indices in the coco map where
      max id is 90. Whereas, detr labels are the index of the sorted COCO ids.
  
      Args:
        example: Input image and raw labels.
  
      Returns:
        A dictionary of {'inputs': input image, 'labels': task label}.
      """
      result = decode_coco_detection_example(example)
  
      # Remap labels.
      label_ref_keys = sorted(
          list(coco_utils.get_label_map("ref_coco").keys())
      )
      label_keys = tf.range(len(label_ref_keys), dtype=tf.int64)
      label_vals = tf.constant(label_ref_keys, dtype=tf.int64)
      label_map = tf.lookup.StaticHashTable(
          tf.lookup.KeyValueTensorInitializer(label_keys, label_vals),
          default_value=0,
      )
      labels = label_map.lookup(result["label"]["labels"])
      labels = tf.cast(labels, tf.int32)
  
      result["label"]["labels"] = labels
      return result
  
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 5 for calling a global function with example usage: decode_coco_deformable_detr_example(example) and returns: result