class_docstr: Sampler that generates random orders.
  
  This is expected to be used together with Chainer's iterators.
  An order sampler is called by an iterator every epoch.
  
  The two initializations below create basically the same objects.
  
  >>> dataset = [(1, 2), (3, 4)]
  >>> it = chainer.iterators.MultiprocessIterator(dataset, 1, shuffle=True)
  >>> it = chainer.iterators.MultiprocessIterator(
  ...     dataset, 1, order_sampler=chainer.iterators.ShuffleOrderSampler())
  
  Args:
      random_state (numpy.random.RandomState): Pseudo-random number
          generator.
code: def __init__(self, random_state=None):
      if random_state is None:
          random_state = numpy.random.random.__self__
      self._random = random_state
  
file_path: chainer/chainer/iterators/order_samplers.py
imports: import numpy
label_desc: Use image node_id 1 to create a new ShuffleOrderSampler object from inherited base classes: OrderSampler with example: obj = ShuffleOrderSampler(random_state)