code: def check_forward(
      self, t_data, xs_data, l_length, x_length, wrap_variable=True
  ):
      if wrap_variable:
          x = tuple(chainer.Variable(x_data) for x_data in xs_data)
          t = chainer.Variable(t_data)
      else:
          x = xs_data
          t = t_data
  
      args = (x, t, self.blank_symbol)
      if self.use_length:
          if wrap_variable:
              args += (
                  chainer.Variable(x_length),
                  chainer.Variable(l_length),
              )
          else:
              args += (x_length, l_length)
      loss = functions.connectionist_temporal_classification(
          *args, reduce=self.reduce
      ).data
  
      # compute expected value by recursive computation.
      xp = backend.get_array_module(self.x)
      xt = xp.swapaxes(self.x, 0, 1)
      for b in range(xt.shape[0]):
          for t in range(xt.shape[1]):
              xt[b][t] = numpy.exp(xt[b][t]) / numpy.sum(
                  numpy.exp(xt[b][t])
              )
      batch_size = xt.shape[0]
      path_length = 2 * l_length + 1
      loss_expect = xp.zeros((batch_size,), dtype=self.dtype)
      for i in range(batch_size):
          xtb, lb, xlb, plb = (
              xt[i],
              self.l[i],
              x_length[i],
              path_length[i],
          )
          loss_expect[i] = -math.log(
              self.alpha(xtb, lb, int(xlb - 1), int(plb - 1))
              + self.alpha(xtb, lb, int(xlb - 1), int(plb - 2))
          )
      if self.reduce == "mean":
          loss_expect = xp.mean(loss_expect)
      testing.assert_allclose(
          loss_expect, loss, **self.check_forward_options
      )
  
imports: import math
  import unittest
  import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
label_desc: Use image node_id 3 for calling the CTCTestBase obj's underlying member method code with example usage: obj.check_forward(t_data, xs_data, l_length, x_length, wrap_variable) without return types