code: def get_cross_validation_datasets_random(
      dataset, n_folds, seed=None, **kwargs
  ):
      """Creates a set of training/test splits for cross validation randomly.
  
      This function acts almost same as :func:`get_cross_validation_dataset`,
      except automatically generating random permutation.
  
      Args:
          dataset: Dataset to split.
          n_fold (int): *(deprecated)*
              `n_fold` is now deprecated for consistency of naming choice.
              Please use `n_folds` instead.
          n_folds (int): Number of splits for cross validation.
          seed (int): Seed the generator used for the permutation of indexes.
              If an integer beging convertible to 32 bit unsigned integers is
              specified, it is guaranteed that each sample
              in the given dataset always belongs to a specific subset.
              If ``None``, the permutation is changed randomly.
  
      Returns:
          list of tuples: List of dataset splits.
  
      """
      if "n_fold" in kwargs:
          warnings.warn(
              "Argument `n_fold` is deprecated. "
              "Please use `n_folds` instead",
              DeprecationWarning,
          )
          n_folds = kwargs["n_fold"]
      order = numpy.random.RandomState(seed).permutation(len(dataset))
      return get_cross_validation_datasets(dataset, n_folds, order)
  
file_path: chainer/chainer/datasets/sub_dataset.py
imports: import numpy
  import six
  import warnings
  from chainer.dataset import dataset_mixin
label_desc: Use image node_id 6 for calling a global function with example usage: get_cross_validation_datasets_random(dataset, n_folds, seed) and returns: get_cross_validation_datasets