code: def setUp(self):
      self.x = np.random.uniform(
          -1, 1, (5, self.in_channels, 5, 5)
      ).astype(np.float32)
      self.gy = np.random.uniform(
          -1, 1, (5, self.out_channels, 5, 5)
      ).astype(np.float32)
  
      # Convolution is the identity function.
      initialW = np.array(
          [[0, 0, 0], [0, 1, 0], [0, 0, 0]], dtype=np.float32
      ).reshape((1, 1, 3, 3))
      bn_kwargs = {"decay": 0.8, "comm": create_communicator("naive")}
      initial_bias = 0
      activ = relu
      self.l = Conv2DBNActiv(
          self.in_channels,
          self.out_channels,
          self.ksize,
          self.stride,
          self.pad,
          self.dilate,
          initialW=initialW,
          initial_bias=initial_bias,
          activ=activ,
          bn_kwargs=bn_kwargs,
      )
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer.functions import relu
  from chainer import testing
  from chainermn import create_communicator
  from chainercv.links import Conv2DBNActiv
  from chainercv.utils.testing import attr
label_desc: Use image node_id 1 for calling the TestConv2DMultiNodeBNActiv obj's underlying member method code with example usage: obj.setUp() without return types