code: def setup_cpu_op(
      self,
      activations,
      labels,
      input_length,
      compute_grad=True,
      mode=mode_without_gpu,
  ):
      cpu_ctc_cost = ctc(activations, labels, input_length)
      outputs = [cpu_ctc_cost]
      if compute_grad:
          # Symbolic gradient of CTC cost
          cpu_ctc_grad = T.grad(T.mean(cpu_ctc_cost), activations)
          outputs += [cpu_ctc_grad]
      return theano.function([], outputs, mode=mode)
  
imports: from __future__ import division, absolute_import, print_function
  import unittest
  import numpy
  import theano
  import theano.tensor
  from theano.tests import unittest_tools
  import theano.gpuarray
  from theano.gpuarray.ctc import gpu_ctc, GpuConnectionistTemporalClassification
  from theano.tensor.nnet.ctc import ctc, ctc_available, ConnectionistTemporalClassification
  from theano.tensor.nnet.tests.test_ctc import setup_torch_case, setup_ctc_case, setup_grad_case
  from .config import mode_with_gpu, mode_without_gpu
label_desc: Use image node_id 3 for calling the TestCTC obj's underlying member method code with example usage: obj.setup_cpu_op(activations, labels, input_length, compute_grad, mode) and returns: theano