class_docstr: Abstract base class for datasets.
docstr: Split this dataset into multiple partitions.
  
  Args:
      num_or_size_splits (array or int): If `num_or_size_splits` is an
          int, *k*, the value is the number of equal-sized folds to make
          (if *k* does not evenly divide the dataset these folds are
          approximately equal-sized). If `num_or_size_splits` is an array
          of type int, the values are taken as the indices at which to
          split the dataset. If the values are floats (< 1.), they are
          considered to be fractional proportions of the dataset at which
          to split.
      shuffle (bool, optional): Randomly shuffle the dataset before
          splitting.
  
  Returns:
      list(Dataset): Splits. Contains *k* or `len(num_or_size_splits) + 1`
      datasets depending on `num_or_size_splits`.
code: def split(self, num_or_size_splits, shuffle=False):
      """Split this dataset into multiple partitions.
  
      Args:
          num_or_size_splits (array or int): If `num_or_size_splits` is an
              int, *k*, the value is the number of equal-sized folds to make
              (if *k* does not evenly divide the dataset these folds are
              approximately equal-sized). If `num_or_size_splits` is an array
              of type int, the values are taken as the indices at which to
              split the dataset. If the values are floats (< 1.), they are
              considered to be fractional proportions of the dataset at which
              to split.
          shuffle (bool, optional): Randomly shuffle the dataset before
              splitting.
  
      Returns:
          list(Dataset): Splits. Contains *k* or `len(num_or_size_splits) + 1`
          datasets depending on `num_or_size_splits`.
      """
      raise NotImplementedError
  
file_path: AIF360/aif360/datasets/dataset.py
imports: from abc import ABC, abstractmethod
  import copy
label_desc: Use image node_id 5 for calling the Dataset obj's underlying member method code with example usage: obj.split(num_or_size_splits, shuffle) without return types