code: def test_binomial_vector(self):
      random = RandomStreams(utt.fetch_seed())
      n = tensor.lvector()
      prob = tensor.vector()
      out = random.binomial(n=n, p=prob)
      assert out.ndim == 1
      f = function([n, prob], out)
  
      n_val = [1, 2, 3]
      prob_val = np.asarray([0.1, 0.2, 0.3], dtype=config.floatX)
      seed_gen = np.random.RandomState(utt.fetch_seed())
      numpy_rng = np.random.RandomState(int(seed_gen.randint(2**30)))
  
      # Arguments of size (3,)
      val0 = f(n_val, prob_val)
      numpy_val0 = numpy_rng.binomial(n=n_val, p=prob_val)
      assert np.all(val0 == numpy_val0)
  
      # arguments of size (2,)
      val1 = f(n_val[:-1], prob_val[:-1])
      numpy_val1 = numpy_rng.binomial(n=n_val[:-1], p=prob_val[:-1])
      assert np.all(val1 == numpy_val1)
  
      # Specifying the size explicitly
      g = function([n, prob], random.binomial(n=n, p=prob, size=(3,)))
      val2 = g(n_val, prob_val)
      numpy_rng = np.random.RandomState(int(seed_gen.randint(2**30)))
      numpy_val2 = numpy_rng.binomial(n=n_val, p=prob_val, size=(3,))
      assert np.all(val2 == numpy_val2)
      self.assertRaises(ValueError, g, n_val[:-1], prob_val[:-1])
  
imports: from __future__ import absolute_import, print_function, division
  import sys
  import unittest
  import numpy
  from theano.tensor import raw_random
  from theano.tensor.shared_randomstreams import RandomStreams
  from theano import function, shared
  from theano import tensor
  from theano import compile, config, gof
  from theano.tests import unittest_tools
label_desc: Use image node_id 24 for calling the T_SharedRandomStreams obj's underlying member method code with example usage: obj.test_binomial_vector() without return types