code: def test_forward_consistency(self, nobias=False):
      x_cpu = chainer.Variable(self.x)
      W_cpu = chainer.Variable(self.W)
      b_cpu = None if nobias else chainer.Variable(self.b)
      y_cpu = F.dilated_convolution_2d(
          x_cpu,
          W_cpu,
          b_cpu,
          stride=self.stride,
          pad=self.pad,
          dilate=self.dilate,
          cover_all=self.cover_all,
      )
  
      x_gpu = chainer.Variable(cuda.to_gpu(self.x))
      W_gpu = chainer.Variable(cuda.to_gpu(self.W))
      b_gpu = None if nobias else chainer.Variable(cuda.to_gpu(self.b))
      with chainer.using_config("use_cudnn", self.use_cudnn):
          y_gpu = F.dilated_convolution_2d(
              x_gpu,
              W_gpu,
              b_gpu,
              stride=self.stride,
              pad=self.pad,
              dilate=self.dilate,
              cover_all=self.cover_all,
          )
  
      testing.assert_allclose(
          y_cpu.data, y_gpu.data.get(), **self.check_forward_options
      )
  
imports: import unittest
  import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  import chainer.functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 2 for calling the TestDilatedConvolution2DFunction obj's underlying member method code with example usage: obj.test_forward_consistency(nobias) without return types