class_docstr: Base class for all models
class_docstr_tok: ["Base","class","for","all","models"]
docstr: Predict the scores between users and items.
  
  Args:
      interaction (Interaction): Interaction class of the batch.
  
  Returns:
      torch.Tensor: Predicted scores for given users and items, shape: [batch_size]
docstr_tok: ["Predict","the","scores","between","users","and","items",".","Args",":","interaction","(","Interaction",")",":","Interaction","class","of","the","batch",".","Returns",":","torch.Tensor",":","Predicted","scores","for","given","users","and","items",",","shape",":","[","batch_size","]"]
code: def predict(self, interaction):
      r"""Predict the scores between users and items.
  
      Args:
          interaction (Interaction): Interaction class of the batch.
  
      Returns:
          torch.Tensor: Predicted scores for given users and items, shape: [batch_size]
      """
      raise NotImplementedError
  
imports: from logging import getLogger
  import numpy
  import torch
  import torch.nn
  from recbole.model.layers import FMEmbedding, FMFirstOrderLinear, FLEmbedding
  from recbole.utils import ModelType, InputType, FeatureSource, FeatureType, set_color
label_desc: Use image node_id 3 for calling the AbstractRecommender obj's underlying member method code with example usage: obj.predict(interaction) without return types