code: def get_data(
      dataset,
      split,
      batch_size,
      filter_fn=None,
      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,
  ):
      """API kept for backwards compatibility."""
      dataset = dataset_utils.get_dataset_tfds(
          dataset=dataset,
          split=split,
          shuffle_files=shuffle_files,
          data_dir=data_dir,
      )
      if "train" not in split:
          dataset_service_address = None
      if filter_fn:
          dataset = dataset.filter(filter_fn)
      return dataset_utils.make_pipeline(
          data=dataset,
          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 functools
  from big_vision.datasets.imagenet import class_names
  import numpy
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib.big_transfer import registry
  from scenic.dataset_lib.big_transfer.preprocessing import utils
  from scenic.projects.t5 import tokenizer
  import tensorflow
label_desc: Use image node_id 9 for calling a global function with example usage: get_data(dataset, split, batch_size, filter_fn, preprocess_fn, repeats, shuffle_buffer_size, prefetch, cache, repeat_after_batching, drop_remainder, data_dir, ignore_errors, shuffle_files, dataset_service_address) and returns: dataset_utils