code: def setup_gpu_op(
      self, activations, labels, input_length, compute_grad=True
  ):
      gpu_ctc_cost = gpu_ctc(activations, labels, input_length)
      outputs = [gpu_ctc_cost]
      if compute_grad:
          # Symbolic gradient of CTC cost
          gpu_ctc_grad = T.grad(T.mean(gpu_ctc_cost), activations)
          outputs += [gpu_ctc_grad]
      return theano.function([], outputs, mode=mode_with_gpu)
  
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 4 for calling the TestCTC obj's underlying member method code with example usage: obj.setup_gpu_op(activations, labels, input_length, compute_grad) and returns: theano