code: def test_mixed_shape_bcastable(self):
      # Test when the provided shape is a tuple of ints and scalar vars
      rng_R = random_state_type()
      shape0 = tensor.lscalar()
      shape = (shape0, 1)
      post_r, u = uniform(rng_R, size=shape, ndim=2)
      assert u.broadcastable == (False, True)
      f = compile.function([rng_R, shape0], u)
      rng_state0 = np.random.RandomState(utt.fetch_seed())
  
      assert f(rng_state0, 2).shape == (2, 1)
      assert f(rng_state0, 8).shape == (8, 1)
  
      post_r, v = uniform(rng_R, size=shape)
      assert v.broadcastable == (False, True)
      g = compile.function([rng_R, shape0], v)
      assert g(rng_state0, 2).shape == (2, 1)
      assert g(rng_state0, 8).shape == (8, 1)
  
imports: from __future__ import absolute_import, print_function, division
  import numpy
  import pickle
  from theano.tests import unittest_tools
  from theano.tensor.raw_random import *
  from theano.tensor import raw_random, ivector, dvector, iscalar, dcol, dtensor3
  from theano import tensor
  from theano import compile, config, gof
label_desc: Use image node_id 22 for calling the T_random_function obj's underlying member method code with example usage: obj.test_mixed_shape_bcastable() without return types