code: def generate_inputs(self):
      W = numpy.random.normal(
          0,
          numpy.sqrt(
              1.0 / (self.kh * self.kw * self.in_channels_a_group)
          ),
          (
              self.out_channels,
              self.in_channels_a_group,
              self.kh,
              self.kw,
          ),
      ).astype(self.W_dtype)
      x = numpy.random.uniform(
          -1, 1, (self.batches, self.in_channels, 4, 3)
      ).astype(self.x_dtype)
  
      if self.nobias:
          return x, W
      else:
          b = numpy.random.uniform(-1, 1, self.out_channels).astype(
              self.x_dtype
          )
          return x, W, b
  
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 3 for calling the TestConvolution2DFunction obj's underlying member method code with example usage: obj.generate_inputs() and returns: x,  W, x,  W,  b