class_docstr: Module component with similar interface to numpy.random
  (numpy.random.RandomState)
  
  Parameters
  ----------
  seed: None or int
      A default seed to initialize the RandomState
      instances after build.  See `RandomStreamsInstance.__init__`
      for more details.
code: def __init__(self, seed=None):
      super(RandomStreams, self).__init__()
      # A list of pairs of the form (input_r, output_r).  This will be
      # over-ridden by the module instance to contain stream generators.
      self.state_updates = []
      # Instance variable should take None or integer value. Used to seed the
      # random number generator that provides seeds for member streams.
      self.default_instance_seed = seed
      # numpy.RandomState instance that gen() uses to seed new streams.
      self.gen_seedgen = np.random.RandomState(seed)
  
file_path: Theano/theano/tensor/shared_randomstreams.py
imports: from __future__ import absolute_import, print_function, division
  import copy
  import numpy
  from theano.compile.sharedvalue import SharedVariable, shared_constructor, shared
  from theano.tensor import raw_random
label_desc: Use image node_id 2 to create a new RandomStreams object from inherited base classes: raw_random with example: obj = RandomStreams(seed)