code: def test_vector_arguments(self):
      rng_R = random_state_type()
      low = tensor.vector()
      post_r, out = uniform(rng_R, low=low, high=1)
      assert out.ndim == 1
      f = compile.function(
          [rng_R, low], [post_r, out], accept_inplace=True
      )
  
      def as_floatX(thing):
          return np.asarray(thing, dtype=theano.config.floatX)
  
      rng_state0 = np.random.RandomState(utt.fetch_seed())
      numpy_rng = np.random.RandomState(utt.fetch_seed())
      post0, val0 = f(rng_state0, [-5, 0.5, 0, 1])
      post1, val1 = f(post0, as_floatX([0.9]))
      numpy_val0 = as_floatX(
          numpy_rng.uniform(low=[-5, 0.5, 0, 1], high=1)
      )
      numpy_val1 = as_floatX(
          numpy_rng.uniform(low=as_floatX([0.9]), high=1)
      )
  
      assert np.all(val0 == numpy_val0)
      assert np.all(val1 == numpy_val1)
  
      high = tensor.vector()
      post_rb, outb = uniform(rng_R, low=low, high=high)
      assert outb.ndim == 1
      fb = compile.function(
          [rng_R, low, high], [post_rb, outb], accept_inplace=True
      )
  
      post0b, val0b = fb(post1, [-4.0, -2], [-1, 0])
      post1b, val1b = fb(post0b, [-4.0], [-1])
      numpy_val0b = as_floatX(
          numpy_rng.uniform(low=[-4.0, -2], high=[-1, 0])
      )
      numpy_val1b = as_floatX(numpy_rng.uniform(low=[-4.0], high=[-1]))
      assert np.all(val0b == numpy_val0b)
      assert np.all(val1b == numpy_val1b)
      self.assertRaises(ValueError, fb, post1b, [-4.0, -2], [-1, 0, 1])
      # TODO: do we want that?
      # self.assertRaises(ValueError, fb, post1b, [-4., -2], [-1])
  
      size = tensor.lvector()
      post_rc, outc = uniform(
          rng_R, low=low, high=high, size=size, ndim=1
      )
      fc = compile.function(
          [rng_R, low, high, size], [post_rc, outc], accept_inplace=True
      )
      post0c, val0c = fc(post1b, [-4.0, -2], [-1, 0], [2])
      post1c, val1c = fc(post0c, [-4.0], [-1], [1])
      numpy_val0c = as_floatX(
          numpy_rng.uniform(low=[-4.0, -2], high=[-1, 0])
      )
      numpy_val1c = as_floatX(numpy_rng.uniform(low=[-4.0], high=[-1]))
      assert np.all(val0c == numpy_val0c)
      assert np.all(val1c == numpy_val1c)
      # self.assertRaises(ValueError, fc, post1c, [-4., -2], [-1, 0], [1])
      self.assertRaises(
          ValueError, fc, post1c, [-4.0, -2], [-1, 0], [1, 2]
      )
      self.assertRaises(
          ValueError, fc, post1c, [-4.0, -2], [-1, 0], [2, 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 24 for calling the T_random_function obj's underlying member method code with example usage: obj.test_vector_arguments() and returns: np