code: def target_to_one_hot(batch, num_classes):
      """Converts the labels to one-hot targets.
  
      Args:
        batch: dict; A batch of data with 'inputs' and 'label'.
        num_classes: int; Number of classes.
  
      Returns:
        Batch with one-hot labels.
      """
      return {
          "inputs": batch["inputs"],
          "label": common_utils.onehot(batch["label"], num_classes),
      }
  
imports: import collections
  import dataclasses
  import functools
  import itertools
  from typing import Any, Callable, Dict, Iterator, Optional, Sequence, Union
  from absl import logging
  from flax.training import common_utils
  import jax
  import jax.numpy
  import numpy
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 11 for calling a global function with example usage: target_to_one_hot(batch, num_classes) and returns: dict