code: def check_ctc(
      self,
      activations,
      labels,
      input_length,
      expected_costs,
      expected_grads,
  ):
      # Create symbolic variables
      t_activations = theano.shared(activations, name="activations")
      t_activation_times = theano.shared(
          input_length, name="activation_times"
      )
      t_labels = theano.shared(labels, name="labels")
  
      inputs = [t_activations, t_labels, t_activation_times]
  
      # Execute several tests for each test case
      self.check_expected_values(
          t_activations,
          t_labels,
          t_activation_times,
          expected_costs,
          expected_grads,
      )
      self.compare_gpu_and_cpu_values(*inputs)
      self.check_grads_disabled(*inputs)
      self.run_gpu_optimization_with_grad(*inputs)
      self.run_gpu_optimization_no_grad(*inputs)
  
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 2 for calling the TestCTC obj's underlying member method code with example usage: obj.check_ctc(activations, labels, input_length, expected_costs, expected_grads) without return types