code: def run_gpu_optimization_with_grad(
      self, activations, labels, input_length
  ):
      # Compile CPU function with optimization
      cpu_lifted_train = self.setup_cpu_op(
          activations, labels, input_length, mode=mode_with_gpu
      )
      # Check whether Op is lifted to the GPU
      assert self.has_only_gpu_op(cpu_lifted_train)
  
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 8 for calling the TestCTC obj's underlying member method code with example usage: obj.run_gpu_optimization_with_grad(activations, labels, input_length) without return types