code: def setUp(self):
      self.comm = create_communicator("naive")
  
      batchsize_per_process = 5
      batchsize = batchsize_per_process * self.comm.size
      if self.comm.rank == 0:
          bboxes = [
              generate_random_bbox(5, (256, 324), 24, 120)
              for _ in range(10)
          ]
          labels = [
              np.random.choice(np.arange(3, dtype=np.int32), size=(5,))
              for _ in range(10)
          ]
      else:
          bboxes = None
          labels = None
      initial_count = self.comm.rank * batchsize_per_process
  
      bboxes = self.comm.bcast_obj(bboxes)
      labels = self.comm.bcast_obj(labels)
      self.bboxes = bboxes
      self.labels = labels
  
      areas = [
          [np.array([(bb[2] - bb[0]) * bb[3] - bb[0]]) for bb in bbox]
          for bbox in bboxes
      ]
      crowdeds = [np.zeros((5,)) for _ in range(10)]
      self.dataset = TupleDataset(
          np.random.uniform(size=(10, 3, 32, 48)),
          bboxes,
          labels,
          areas,
          crowdeds,
      )
      self.initial_count = initial_count
      self.batchsize = batchsize
  
imports: import numpy
  import unittest
  import chainer
  from chainer.datasets import TupleDataset
  from chainer.iterators import SerialIterator
  from chainer import testing
  from chainercv.extensions import DetectionCOCOEvaluator
  from chainercv.utils import generate_random_bbox
  from chainercv.utils.testing import attr
  from chainermn import create_communicator
label_desc: Use image node_id 1 for calling the TestDetectionCOCOEvaluatorMPI obj's underlying member method code with example usage: obj.setUp() without return types