class_docstr: MCCLK is a knowledge-based recommendation model.
  It focuses on the contrastive learning in KG-aware recommendation and proposes a novel multi-level cross-view
  contrastive learning mechanism. This model comprehensively considers three different graph views for KG-aware
  recommendation, including global-level structural view, local-level collaborative and semantic views. It hence
  performs contrastive learning across three views on both local and global levels, mining comprehensive graph
  feature and structure information in a self-supervised manner.
class_docstr_tok: ["MCCLK","is","a","knowledge-based","recommendation","model",".","It","focuses","on","the","contrastive","learning","in","KG-aware","recommendation","and","proposes","a","novel","multi-level","cross-view","contrastive","learning","mechanism",".","This","model","comprehensively","considers","three","different","graph","views","for","KG-aware","recommendation",",","including","global-level","structural","view",",","local-level","collaborative","and","semantic","views",".","It","hence","performs","contrastive","learning","across","three","views","on","both","local","and","global","levels",",","mining","comprehensive","graph","feature","and","structure","information","in","a","self-supervised","manner","."]
code: def sim(self, z1: torch.Tensor, z2: torch.Tensor):
      z1 = F.normalize(z1)
      z2 = F.normalize(z2)
      return torch.mm(z1, z2.t())
  
imports: import numpy
  import scipy.sparse
  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.layers import SparseDropout
  from recbole.model.loss import BPRLoss, EmbLoss
  from recbole.utils import InputType
label_desc: Use image node_id 6 for calling the MCCLK obj's underlying member method code with example usage: obj.sim(z1, z2) and returns: torch