class_docstr: Module component with similar interface to numpy.random
  (numpy.random.RandomState).
  
  Parameters
  ----------
  seed : int or list of 6 int
      A default seed to initialize the random state.
      If a single int is given, it will be replicated 6 times.
      The first 3 values of the seed must all be less than M1 = 2147483647,
      and not all 0; and the last 3 values must all be less than
      M2 = 2147462579, and not all 0.
code: def set_rstate(self, seed):
      # TODO : need description for method, parameter
      if isinstance(seed, integer_types):
          if seed == 0:
              raise ValueError("seed should not be 0", seed)
          elif seed >= M2:
              raise ValueError("seed should be less than %i" % M2, seed)
          self.rstate = np.asarray([seed] * 6, dtype="int32")
      elif len(seed) == 6:
          if seed[0] == 0 and seed[1] == 0 and seed[2] == 0:
              raise ValueError(
                  "The first 3 values of seed should not be all 0", seed
              )
          if seed[3] == 0 and seed[4] == 0 and seed[5] == 0:
              raise ValueError(
                  "The last 3 values of seed should not be all 0", seed
              )
          if seed[0] >= M1 or seed[1] >= M1 or seed[2] >= M1:
              raise ValueError(
                  "The first 3 values of seed should be less than %i"
                  % M1,
                  seed,
              )
          if seed[3] >= M2 or seed[4] >= M2 or seed[5] >= M2:
              raise ValueError(
                  "The last 3 values of seed should be less than %i"
                  % M2,
                  seed,
              )
          self.rstate = np.asarray(seed, dtype="int32")
      else:
          raise TypeError("seed should be 1 integer or 6 integers")
  
imports: from __future__ import absolute_import, print_function, division
  import warnings
  import numpy
  from six import integer_types, string_types
  from six.moves import xrange
  import theano
  from theano import Op, Apply, shared, config, Variable
  from theano import gradient, function
  from theano.gradient import undefined_grad
  from theano import tensor
  from theano.tensor import TensorType, as_tensor_variable, get_vector_length, cast, opt, scal
  from theano.compile import optdb
  from theano.gof import local_optimizer, ParamsType
  from theano.scalar import bool, int32
  from .None import multinomial
label_desc: Use image node_id 3 for calling the MRG_RandomStreams obj's underlying member method code with example usage: obj.set_rstate(seed) without return types