code: def make_skip_decoders(skip_decode, features):
      if skip_decode is None:
          return None
      elif isinstance(skip_decode, list) or isinstance(
          skip_decode, tuple
      ):
          return {
              f: tfds.decode.SkipDecoding()
              for f in skip_decode
              if f in features
          }
      elif isinstance(skip_decode, dict):
          return jax.tree_util.tree_map(
              lambda _: tfds.decode.SkipDecoding(), skip_decode
          )
      else:
          raise ValueError(
              "skip_decode should be None, tuple, list, or dict - instead got"
              f"{type(skip_decode)} {skip_decode}"
          )
  
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 15 for calling a global function with example usage: make_skip_decoders(skip_decode, features) and returns: None, unknown, jax