code: def test_multiple_outputs(self):
      m = tensor.matrix("m")
      v = tensor.vector("v")
      m_ = tensor.matrix("m_")
      v_ = tensor.vector("v_")
  
      mval = self.rng.uniform(size=(3, 7)).astype(theano.config.floatX)
      vval = self.rng.uniform(size=(7,)).astype(theano.config.floatX)
      m_val = self.rng.uniform(size=(3, 7)).astype(theano.config.floatX)
      v_val = self.rng.uniform(size=(7,)).astype(theano.config.floatX)
  
      rop_out1 = tensor.Rop([m, v, m + v], [m, v], [m_, v_])
      assert isinstance(rop_out1, list)
      assert len(rop_out1) == 3
      rop_out2 = tensor.Rop((m, v, m + v), [m, v], [m_, v_])
      assert isinstance(rop_out2, tuple)
      assert len(rop_out2) == 3
  
      all_outs = []
      for o in rop_out1, rop_out2:
          all_outs.extend(o)
      f = theano.function([m, v, m_, v_], all_outs)
      f(mval, vval, m_val, v_val)
  
imports: from __future__ import absolute_import, print_function, division
  import unittest
  from theano.tests import unittest_tools
  from theano import function
  import theano
  from theano import tensor
  import itertools
  import numpy
  from theano.gof import Op, Apply
  from theano.gradient import grad_undefined
  from theano.tests.unittest_tools import SkipTest
  from theano.tensor.signal.pool import Pool
  from theano.tensor.nnet import conv, conv2d
label_desc: Use image node_id 25 for calling the test_RopLop obj's underlying member method code with example usage: obj.test_multiple_outputs() without return types