code: def forward(self, x):
      shape = (x.shape[0],) + self.shape_0
      y0 = self.xp.random.rand(*shape).astype(np.float32)
  
      if self.shape_1 is None:
          return chainer.Variable(y0)
      shape = (x.shape[0],) + self.shape_1
      y1 = self.xp.random.rand(*shape).astype(np.float32)
      return chainer.Variable(y0), chainer.Variable(y1)
  
imports: import numpy
  import unittest
  import chainer
  from chainer import testing
  from chainer.testing import attr
  from chainercv.links import FeaturePredictor
label_desc: Use image node_id 2 for calling the DummyFeatureExtractor obj's underlying member method code with example usage: obj.forward(x) and returns: chainer,  chainer, chainer