python/dglke/models/general_models.py [133:154]:
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                @property
                def src(self):
                    return self._hobj

                @property
                def dst(self):
                    return self._tobj

                @property
                def data(self):
                    return self._robj

            for i in range((num_head + batch_size - 1) // batch_size):
                sh_emb = head_emb[i * batch_size : (i + 1) * batch_size \
                                                   if (i + 1) * batch_size < num_head \
                                                   else num_head]
                sr_emb = rel_emb[i * batch_size : (i + 1) * batch_size \
                                                  if (i + 1) * batch_size < num_head \
                                                  else num_head]
                st_emb = tail_emb[i * batch_size : (i + 1) * batch_size \
                                                   if (i + 1) * batch_size < num_head \
                                                   else num_head]
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python/dglke/models/ke_model.py [150:173]:
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                @property
                def src(self):
                    return self._hobj

                @property
                def dst(self):
                    return self._tobj

                @property
                def data(self):
                    return self._robj

            # calculate scores in mini-batches
            # so we can use GPU to accelerate the speed with avoiding GPU OOM
            for i in range((num_head + batch_size - 1) // batch_size):
                sh_emb = head_emb[i * batch_size : (i + 1) * batch_size \
                                                   if (i + 1) * batch_size < num_head \
                                                   else num_head]
                sr_emb = rel_emb[i * batch_size : (i + 1) * batch_size \
                                                  if (i + 1) * batch_size < num_head \
                                                  else num_head]
                st_emb = tail_emb[i * batch_size : (i + 1) * batch_size \
                                                   if (i + 1) * batch_size < num_head \
                                                   else num_head]
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