code: def setUp(self):
      self.N = 3
      self.group_size = 2
      self.spatial_scale = 0.6
      out_c, _, _ = _outsize(self.outsize)
      if out_c is None:
          self.n_channels = self.group_size * self.group_size * 2 - 1
      else:
          self.n_channels = (
              self.group_size * self.group_size * (out_c + 1)
          )
  
      self.x = np.arange(
          self.N * self.n_channels * 10 * 12, dtype=np.float32
      ).reshape((self.N, self.n_channels, 10, 12))
      np.random.shuffle(self.x)
      self.x = 2 * self.x / self.x.size - 1
      self.x = self.x.astype(np.float32)
      self.rois = np.array(
          [[0, 0, 7, 7], [1, 0, 5, 12], [0, 1, 10, 5], [3, 3, 4, 4]],
          dtype=np.float32,
      )
      self.roi_indices = np.array([0, 2, 1, 0], dtype=np.int32)
      self.n_roi = self.rois.shape[0]
  
imports: import chainer
  from chainer.backends import cuda
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
  import numpy
  import unittest
  from chainercv import functions
  from tests.functions_tests.test_ps_roi_average_pooling_2d import _outsize
label_desc: Use image node_id 1 for calling the TestPSROIAverageAlign2DFailure obj's underlying member method code with example usage: obj.setUp() without return types