code: def full_sort_predict(self, interaction):
      user = interaction[self.USER_ID]
  
      result = self.user_embeddings[user, :] @ self.item_embeddings
      return result.flatten()
  
file_path: RecBole/recbole/model/general_recommender/nceplrec.py
imports: import torch
  import numpy
  import scipy.sparse
  from sklearn.utils.extmath import randomized_svd
  from recbole.model.abstract_recommender import GeneralRecommender
  from recbole.utils import InputType
label_desc: Use image node_id 5 for calling the NCEPLRec obj's underlying member method code with example usage: obj.full_sort_predict(interaction) and returns: result