text: # -*- coding: utf-8 -*-
  EMBEDDING_DIM = 18
  HIDDEN_SIZE = 18 * 2
  ATTENTION_SIZE = 18 * 2
  POS_EMBEDDING_DIM = 2
  
  # train.py
  model_type='TGIN'
  data_path='dataset'
  dataset='electronics'  
  tri_data='wnd3_alpha_01_theta_09_tri_num_10' 
  n_tri=10
  batch_size=128
  maxlen=10
  test_iter=100
  save_iter=100
  
  # model.py
  n_neg = 5
  use_dice = True
  use_negsampling = True
  
  # tgin.py
  single_tri_agg_flag = 'reduce_mean'
  multi_tri_agg_flag = 'weighted_sum'
  
  