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.
      expand_initialW = np.ones(
          (self.expansion_size, self.in_channels), dtype=np.float32
      ).reshape((self.expansion_size, self.in_channels, 1, 1))
      depthwise_initialW = np.array(
          [[0, 0, 0], [0, 1, 0], [0, 0, 0]] * self.expansion_size,
          dtype=np.float32,
      ).reshape((self.expansion_size, 1, 3, 3))
      project_initialW = np.ones(
          (self.out_channels, self.expansion_size), dtype=np.float32
      ).reshape((self.out_channels, self.expansion_size, 1, 1))
      bn_kwargs = {"decay": 0.8}
      self.l = ExpandedConv2D(
          self.in_channels,
          self.out_channels,
          expansion_size=self.expansion_size,
          expand_pad=self.expand_pad,
          depthwise_stride=self.depthwise_stride,
          depthwise_ksize=self.depthwise_ksize,
          depthwise_pad=self.depthwise_pad,
          project_pad=self.project_pad,
          bn_kwargs=bn_kwargs,
      )
      if self.expansion_size > self.in_channels:
          self.l.expand.conv.W.array = expand_initialW
      self.l.depthwise.conv.W.array = depthwise_initialW
      self.l.project.conv.W.array = project_initialW
  
file_path: chainercv/tests/links_tests/model_tests/mobilenet_tests/test_expanded_conv_2d.py
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import testing
  from chainermn import create_communicator
  from chainercv.links.model.mobilenet import ExpandedConv2D
  from chainercv.utils.testing import attr
label_desc: Use image node_id 1 for calling the TestExpandedConv2D obj's underlying member method code with example usage: obj.setUp() without return types