class_docstr: Split dataset according to a split list based on volume_guid.
  The split is pseudorandom (can not supply the seed yet), i.e. the split outcome is always the same.
  Split is performed by hashing volume_guid uniformly to 0:1 range and returning part of full dataset
  which was hashed in given sub-range
  
  Example:
      'split_list = [0.5, 0.2, 0.3]' - dataset will be split on three subsets in proportion
      subset 1: 0.5 of log data
      subset 2: 0.2 of log data
      subset 3: 0.3 of log data
      Note, split is not exact, so avoid small fraction (e.g. 0.001) to avoid empty sets
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code: def get_fields(self):
      return {self._predicate_field}
  
imports: import abc
  import collections.abc
  import hashlib
  import numpy
  import six
  import sys
label_desc: Use image node_id 2 for calling the in_pseudorandom_split obj's underlying member method code with example usage: obj.get_fields() and returns: unknown