code: def skip_random_fraction(dataset, data_file):
      # Skip a random fraction at the beginning of the stream.  The skip is
      # essential for synchronous highly-parallel training to avoid multiple
      # replicas reading the same data in lock-step.
      num_skip = random.randint(0, _file_num_records_cached(data_file))
      return dataset.skip(num_skip)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import multiprocessing
  import random
  import six
  from six.moves import range
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import mlperf_log
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 14 for calling a global function with example usage: skip_random_fraction(dataset, data_file) and returns: dataset