code: def test_1(self):
      n_batches = 2
      in_channels = 3
      out_channels = 1  # important
      x_shape = (n_batches, in_channels, 10, 10)
      w_shape = (out_channels, in_channels, 3, 3)
      x = numpy.ones(x_shape, numpy.float32)
      w = numpy.ones(w_shape, numpy.float32)
      y = F.convolution_2d(x, chainer.Variable(w))
      z = F.sum(y)
      z.backward()
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import backend
label_desc: Use image node_id 1 for calling the TestConvolution2DBackwardNoncontiguousGradOutputs obj's underlying member method code with example usage: obj.test_1() without return types