code: def speed_reduce10():
      data = np.random.rand(1000, 1000).astype("float32")
      m = theano.tensor.fmatrix()
      f = theano.function(
          [m], [m.sum(axis=0), m.T.sum(axis=0)], mode=mode_with_gpu
      )
      f(data)
  
imports: from __future__ import absolute_import, print_function, division
  from copy import copy
  from unittest import TestCase
  import numpy
  import theano
  from theano import scalar, gof, tensor
  from theano.compile import DebugMode, Mode
  from theano.tests.unittest_tools import SkipTest, assert_allclose
  from theano.tensor.tests import test_elemwise
  from .config import mode_with_gpu, mode_without_gpu, test_ctx_name
  from .test_basic_ops import rand_gpuarray
  from ..elemwise import GpuElemwise, GpuDimShuffle, GpuCAReduceCuda, GpuCAReduceCPY, GpuErfinv, GpuErfcinv
  from ..dnn import GpuDnnReduction
  from ..type import GpuArrayType, get_context, gpuarray_shared_constructor
  from pygpu import ndgpuarray
label_desc: Use image node_id 2 for calling a global function with example usage: speed_reduce10() without return types