class_docstr: The implementations of the GraphLayer part and the Attentional Edge Weights part are adapted from https://github.com/xue-pai/FuxiCTR.
class_docstr_tok: ["The","implementations","of","the","GraphLayer","part","and","the","Attentional","Edge","Weights","part","are","adapted","from","https",":","\/\/github.com\/xue-pai\/FuxiCTR","."]
code: def __init__(self, num_fields, embedding_size):
      super(GraphLayer, self).__init__()
      self.W_in = nn.Parameter(
          torch.Tensor(num_fields, embedding_size, embedding_size)
      )
      self.W_out = nn.Parameter(
          torch.Tensor(num_fields, embedding_size, embedding_size)
      )
      xavier_normal_(self.W_in)
      xavier_normal_(self.W_out)
      self.bias_p = nn.Parameter(torch.zeros(embedding_size))
  
file_path: RecBole/recbole/model/context_aware_recommender/fignn.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.init import xavier_uniform_, xavier_normal_, constant_
  from itertools import product
  from recbole.utils import InputType
  from recbole.model.abstract_recommender import ContextRecommender
label_desc: Use image node_id 1 to create a new GraphLayer object from inherited base classes: nn with example: obj = GraphLayer(num_fields, embedding_size)