class_docstr: Factorization Machine considers the second-order interaction with features to predict the final score.
class_docstr_tok: ["Factorization","Machine","considers","the","second-order","interaction","with","features","to","predict","the","final","score","."]
code: def _init_weights(self, module):
      if isinstance(module, nn.Embedding):
          xavier_normal_(module.weight.data)
  
file_path: RecBole/recbole/model/context_aware_recommender/fm.py
imports: import torch.nn
  from torch.nn.init import xavier_normal_
  from recbole.model.abstract_recommender import ContextRecommender
  from recbole.model.layers import BaseFactorizationMachine
label_desc: Use image node_id 2 for calling the FM obj's underlying member method code with example usage: obj._init_weights(module) without return types