code: def test_rebroadcast():
      d = np.random.rand(10, 10).astype("float32")
      v = theano.tensor.fmatrix()
      up = tensor.unbroadcast(v.sum().dimshuffle("x", "x"), 0, 1)
      f = theano.function([v], [up], mode=mode_with_gpu)
  
      f(d)
  
      topo = f.maker.fgraph.toposort()
      rebrs = [
          node
          for node in topo
          if isinstance(node.op, tensor.Rebroadcast)
      ]
      assert len(rebrs) == 1
      rebr = rebrs[0]
  
      assert isinstance(rebr.inputs[0].type, GpuArrayType)
      assert isinstance(rebr.outputs[0].type, GpuArrayType)
      assert _check_stack_trace(f)
  
imports: from __future__ import absolute_import, print_function, division
  from nose.tools import assert_raises
  import numpy
  import theano
  from theano import tensor
  import theano.tensor.slinalg
  from theano.tests.breakpoint import PdbBreakpoint
  from theano.tests import unittest_tools, test_ifelse
  from theano.tensor.tests import test_basic
  from theano.gof.opt import check_stack_trace
  import theano.gpuarray
  from ..None import basic_ops
  from ..type import GpuArrayType, gpuarray_shared_constructor, get_context
  from ..basic_ops import GpuAlloc, GpuAllocEmpty, GpuReshape, GpuFromHost, HostFromGpu, host_from_gpu
  from ..blas import GpuGemm
  from ..elemwise import GpuCAReduceCuda, GpuCAReduceCPY, GpuElemwise, Elemwise, max_inputs_to_GpuElemwise
  from ..dnn import GpuDnnReduction
  from ..subtensor import GpuSubtensor
  from ..linalg import GpuCusolverSolve, cusolver_available, GpuCholesky
  from .config import mode_with_gpu, mode_without_gpu, test_ctx_name, SkipTest
  import unittest
  from theano.tensor.nnet import abstract_conv
  from theano.gpuarray import dnn, blas, opt
label_desc: Use image node_id 10 for calling a global function with example usage: test_rebroadcast() without return types