code: def predict(self, imgs):
      labels = []
  
      for img in imgs:
          labels.append(
              np.random.randint(0, 21, size=img.shape[1:]).astype(
                  np.int32
              )
          )
  
      return labels
  
imports: import numpy
  import unittest
  import chainer
  from chainercv.utils import assert_is_semantic_segmentation_link
  from chainercv.utils import testing
label_desc: Use image node_id 1 for calling the SemanticSegmentationLink obj's underlying member method code with example usage: obj.predict(imgs) and returns: labels