class_docstr: KSR integrates the RNN-based networks with Key-Value Memory Network (KV-MN).
  And it further incorporates knowledge base (KB) information to enhance the semantic representation of KV-MN.
class_docstr_tok: ["KSR","integrates","the","RNN-based","networks","with","Key-Value","Memory","Network","(","KV-MN",")",".","And","it","further","incorporates","knowledge","base","(","KB",")","information","to","enhance","the","semantic","representation","of","KV-MN","."]
docstr: Initialize the weights
docstr_tok: ["Initialize","the","weights"]
code: def _init_weights(self, module):
      """Initialize the weights"""
      if isinstance(module, nn.Embedding):
          xavier_normal_(module.weight)
      elif isinstance(module, nn.GRU):
          xavier_uniform_(module.weight_hh_l0)
          xavier_uniform_(module.weight_ih_l0)
  
file_path: RecBole/recbole/model/sequential_recommender/ksr.py
imports: import torch
  from torch import nn
  from torch.nn.init import xavier_uniform_, xavier_normal_
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.loss import BPRLoss
label_desc: Use image node_id 2 for calling the KSR obj's underlying member method code with example usage: obj._init_weights(module) without return types