class_docstr: Splitters split up Datasets into pieces for training/validation/testing.
  
  In machine learning applications, it's often necessary to split up a dataset
  into training/validation/test sets. Or to k-fold split a dataset (that is,
  divide into k equal subsets) for cross-validation. The `Splitter` class is
  an abstract superclass for all splitters that captures the common API across
  splitter classes.
  
  Note that `Splitter` is an abstract superclass. You won't want to
  instantiate this class directly. Rather you will want to use a concrete
  subclass for your application.
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docstr: Convert self to repr representation.
  
  Returns
  -------
  str
      The string represents the class.
  
  Examples
  --------
  >>> import deepchem as dc
  >>> dc.splits.RandomSplitter()
  RandomSplitter[]
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code: def __repr__(self) -> str:
      """Convert self to repr representation.
  
      Returns
      -------
      str
          The string represents the class.
  
      Examples
      --------
      >>> import deepchem as dc
      >>> dc.splits.RandomSplitter()
      RandomSplitter[]
      """
      args_spec = inspect.getfullargspec(self.__init__)  # type: ignore
      args_names = [arg for arg in args_spec.args if arg != "self"]
      args_info = ""
      for arg_name in args_names:
          value = self.__dict__[arg_name]
          # for str
          if isinstance(value, str):
              value = "'" + value + "'"
          # for list
          if isinstance(value, list):
              threshold = get_print_threshold()
              value = np.array2string(
                  np.array(value), threshold=threshold
              )
          args_info += arg_name + "=" + str(value) + ", "
      return self.__class__.__name__ + "[" + args_info[:-2] + "]"
  
imports: import inspect
  import itertools
  import logging
  import os
  import random
  import tempfile
  from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union
  import deepchem
  import numpy
  import pandas
  from deepchem.data import Dataset, DiskDataset
  from deepchem.utils import get_print_threshold
label_desc: Use image node_id 6 for calling the Splitter obj's underlying member method code with example usage: obj.__repr__() and returns: unknown