code: def split_dataset_n_random(dataset, n, seed=None):
      """Splits a dataset into ``n`` subsets randomly.
  
      Args:
          dataset: Dataset to split.
          n(int): The number of subsets.
          seed (int): Seed the generator used for the permutation of indexes.
              If an integer being 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: List of ``n`` :class:`SubDataset` objects.
              Each subset contains ``len(dataset) // n`` examples randomly chosen
              from the dataset without replacement.
  
      """
      n_examples = len(dataset)
      sub_size = n_examples // n
      order = numpy.random.RandomState(seed).permutation(len(dataset))
      return [
          SubDataset(dataset, sub_size * i, sub_size * (i + 1), order)
          for i in six.moves.range(n)
      ]
  
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 4 for calling a global function with example usage: split_dataset_n_random(dataset, n, seed) and returns: unknown