class_docstr: CKE is a knowledge-based recommendation model, it can incorporate KG and other information such as corresponding
  images to enrich the representation of items for item recommendations.
  
  Note:
      In the original paper, CKE used structural knowledge, textual knowledge and visual knowledge. In our
      implementation, we only used structural knowledge. Meanwhile, the version we implemented uses a simpler
      regular way which can get almost the same result (even better) as the original regular way.
class_docstr_tok: ["CKE","is","a","knowledge-based","recommendation","model",",","it","can","incorporate","KG","and","other","information","such","as","corresponding","images","to","enrich","the","representation","of","items","for","item","recommendations",".","Note",":","In","the","original","paper",",","CKE","used","structural","knowledge",",","textual","knowledge","and","visual","knowledge",".","In","our","implementation",",","we","only","used","structural","knowledge",".","Meanwhile",",","the","version","we","implemented","uses","a","simpler","regular","way","which","can","get","almost","the","same","result","(","even","better",")","as","the","original","regular","way","."]
code: def full_sort_predict(self, interaction):
      user = interaction[self.USER_ID]
      user_e = self.user_embedding(user)
      all_item_e = (
          self.item_embedding.weight
          + self.entity_embedding.weight[: self.n_items]
      )
      score = torch.matmul(user_e, all_item_e.transpose(0, 1))
      return score.view(-1)
  
file_path: RecBole/recbole/model/knowledge_aware_recommender/cke.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from recbole.model.abstract_recommender import KnowledgeRecommender
  from recbole.model.init import xavier_normal_initialization
  from recbole.model.loss import BPRLoss, EmbLoss
  from recbole.utils import InputType
label_desc: Use image node_id 8 for calling the CKE obj's underlying member method code with example usage: obj.full_sort_predict(interaction) and returns: score