code: def test_answer_gpu_cpu(self):
      x = cuda.to_gpu(self.x)
      y = F.batch_det(chainer.Variable(x))
      gpu = cuda.to_cpu(y.data)
      if self.dtype == numpy.float16:
          cpu = numpy.linalg.det(self.x.astype(numpy.float32)).astype(
              numpy.float16
          )
          testing.assert_allclose(gpu, cpu, atol=5e-3, rtol=5e-3)
      else:
          cpu = numpy.linalg.det(self.x)
          testing.assert_allclose(gpu, cpu)
  
imports: import unittest
  import numpy
  import six
  import chainer
  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.utils import type_check
label_desc: Use image node_id 2 for calling the TestBatchDetGPUCPUConsistency obj's underlying member method code with example usage: obj.test_answer_gpu_cpu() without return types