code: def check_sum(self, x, gpu=False):
      total = 0
      for i in range(5):
          t = numpy.array([i], dtype=numpy.int32)
          if gpu:
              t = cuda.to_gpu(t)
          loss = self.link(
              chainer.Variable(x), chainer.Variable(t)
          ).data
          self.assertEqual(loss.dtype, self.dtype)
          self.assertEqual(loss.shape, ())
          total += numpy.exp(-cuda.to_cpu(loss))
      self.assertAlmostEqual(
          1.0, float(total), **self.check_sum_options
      )
  
imports: import copy
  import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import gradient_check
  from chainer import links
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
label_desc: Use image node_id 3 for calling the TestBinaryHierarchicalSoftmax obj's underlying member method code with example usage: obj.check_sum(x, gpu) without return types