class_docstr: FwFM is a context-based recommendation model. It aims to model the different feature interactions
  between different fields in a much more memory-efficient way. It proposes a field pair weight matrix
  :math:`r_{F(i),F(j)}`, to capture the heterogeneity of field pair interactions.
  
  The model defines as follows:
  
  .. math::
     y = w_0 + \sum_{i=1}^{m}x_{i}w_{i} + \sum_{i=1}^{m}\sum_{j=i+1}^{m}x_{i}x_{j}<v_{i}, v_{j}>r_{F(i),F(j)}
class_docstr_tok: ["FwFM","is","a","context-based","recommendation","model",".","It","aims","to","model","the","different","feature","interactions","between","different","fields","in","a","much","more","memory-efficient","way",".","It","proposes","a","field","pair","weight","matrix",":","math",":","`","r_","{","F","(","i",")",",","F","(","j",")","}","`",",","to","capture","the","heterogeneity","of","field","pair","interactions",".","The","model","defines","as","follows",":","..","math",":",":","y","=","w_0","+","\\sum_","{","i=1","}","^","{","m","}","x_","{","i","}","w_","{","i","}","+","\\sum_","{","i=1","}","^","{","m","}","\\sum_","{","j=i+1","}","^","{","m","}","x_","{","i","}","x_","{","j","}","<","v_","{","i","}",",","v_","{","j","}",">","r_","{","F","(","i",")",",","F","(","j",")","}"]
code: def _init_weights(self, module):
      if isinstance(module, nn.Embedding):
          xavier_normal_(module.weight.data)
      elif isinstance(module, nn.Linear):
          xavier_normal_(module.weight.data)
          if module.bias is not None:
              constant_(module.bias.data, 0)
  
file_path: RecBole/recbole/model/context_aware_recommender/fwfm.py
imports: import torch
  import torch.nn
  from torch.nn.init import xavier_normal_, constant_
  from recbole.model.abstract_recommender import ContextRecommender
label_desc: Use image node_id 2 for calling the FwFM obj's underlying member method code with example usage: obj._init_weights(module) without return types