code: def test_uniform_vector(self):
      rng_R = random_state_type()
      low = tensor.vector()
      high = tensor.vector()
      post_r, out = uniform(rng_R, low=low, high=high)
      assert out.ndim == 1
      f = compile.function(
          [rng_R, low, high], [post_r, out], accept_inplace=True
      )
  
      def as_floatX(thing):
          return np.asarray(thing, dtype=theano.config.floatX)
  
      low_val = as_floatX([0.1, 0.2, 0.3])
      high_val = as_floatX([1.1, 2.2, 3.3])
      rng = np.random.RandomState(utt.fetch_seed())
      numpy_rng = np.random.RandomState(utt.fetch_seed())
  
      # Arguments of size (3,)
      rng0, val0 = f(rng, low_val, high_val)
      numpy_val0 = as_floatX(
          numpy_rng.uniform(low=low_val, high=high_val)
      )
      assert np.all(val0 == numpy_val0)
  
      # arguments of size (2,)
      rng1, val1 = f(rng0, low_val[:-1], high_val[:-1])
      numpy_val1 = as_floatX(
          numpy_rng.uniform(low=low_val[:-1], high=high_val[:-1])
      )
      assert np.all(val1 == numpy_val1)
  
      # Specifying the size explicitly
      g = compile.function(
          [rng_R, low, high],
          uniform(rng_R, low=low, high=high, size=(3,)),
          accept_inplace=True,
      )
      rng2, val2 = g(rng1, low_val, high_val)
      numpy_val2 = as_floatX(
          numpy_rng.uniform(low=low_val, high=high_val, size=(3,))
      )
      assert np.all(val2 == numpy_val2)
      self.assertRaises(
          ValueError, g, rng2, low_val[:-1], high_val[:-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 26 for calling the T_random_function obj's underlying member method code with example usage: obj.test_uniform_vector() and returns: np