class_docstr: Meta class defining interface for graph partitioning algorithms.
class_docstr_tok: ["Meta","class","defining","interface","for","graph","partitioning","algorithms","."]
docstr: Split data into `k` equal size partitions.
  
  Parameters
  ----------
  seed: int
       Seed to be used for repeatability purposes, it is only used when certain randomization is required.
  
  Returns
  -------
  Partitions:
      Partitions in which the entities are divided.
docstr_tok: ["Split","data","into","`","k","`","equal","size","partitions",".","Parameters","--","--","--","--","--","seed",":","int","Seed","to","be","used","for","repeatability","purposes",",","it","is","only","used","when","certain","randomization","is","required",".","Returns","--","--","--","-","Partitions",":","Partitions","in","which","the","entities","are","divided","."]
code: def _split(self, seed=None, **kwargs):
      """Split data into `k` equal size partitions.
  
      Parameters
      ----------
      seed: int
           Seed to be used for repeatability purposes, it is only used when certain randomization is required.
  
      Returns
      -------
      Partitions:
          Partitions in which the entities are divided.
      """
      pass
  
imports: import logging
  import os
  import shelve
  import tempfile
  from abc import ABC
  from datetime import datetime
  import numpy
  from ampligraph.utils.profiling import timing_and_memory
  from .graph_data_loader import GraphDataLoader
label_desc: Use image node_id 9 for calling the AbstractGraphPartitioner obj's underlying member method code with example usage: obj._split(seed) without return types