code: def get_data(
      dataset,
      split,
      batch_size,
      preprocess_fn=lambda x: x,
      repeats=None,
      shuffle_buffer_size=None,
      prefetch=2,
      cache="loaded",
      repeat_after_batching=False,
      drop_remainder=True,
      data_dir=None,
      ignore_errors=False,
      shuffle_files=True,
      dataset_service_address=None,
      skip_decode=("image",),
  ):
      """API kept for backwards compatibility."""
      data = get_dataset_tfds(
          dataset=dataset,
          split=split,
          shuffle_files=shuffle_files,
          data_dir=data_dir,
          skip_decode=skip_decode,
      )
      if "train" not in split:
          dataset_service_address = None
      return make_pipeline(
          data=data,
          preprocess_fn=preprocess_fn,
          batch_size=batch_size,
          drop_remainder=drop_remainder,
          cache=cache,
          repeats=repeats,
          prefetch=prefetch,
          shuffle_buffer_size=shuffle_buffer_size,
          repeat_after_batching=repeat_after_batching,
          ignore_errors=ignore_errors,
          dataset_service_address=dataset_service_address,
      )
  
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 18 for calling a global function with example usage: get_data(dataset, split, batch_size, preprocess_fn, repeats, shuffle_buffer_size, prefetch, cache, repeat_after_batching, drop_remainder, data_dir, ignore_errors, shuffle_files, dataset_service_address, skip_decode) and returns: make_pipeline