code: def get_dataset(name, split, args):
      """Creates input data pipeline from a TF Datasets dataset."""
      with tf.device("/cpu:0"):
          dataset = tfds.load(name, split=split, shuffle_files=True)
          if split == "train":
              dataset = dataset.repeat()
          dataset = dataset.filter(
              lambda x: check_image_size(x["image"], args.patchsize)
          )
          dataset = dataset.map(
              lambda x: crop_image(x["image"], args.patchsize)
          )
          dataset = dataset.batch(args.batchsize, drop_remainder=True)
      return dataset
  
imports: import argparse
  import functools
  import glob
  import sys
  from absl import app
  from absl.flags import argparse_flags
  import tensorflow
  import tensorflow_compression
  import tensorflow_datasets
label_desc: Use image node_id 5 for calling a global function with example usage: get_dataset(name, split, args) and returns: dataset