dataloader.py

import numpy as np
import random
import torch
from torch.utils.data import Dataset

class GRDataset(Dataset):
	def __init__(self, data, u_items_divlist, u_avg_list, u_users_similar, u_users_items_list, i_users_list, i_avg_list):
		self.data = data
		self.u_items_divlist = u_items_divlist
		self.u_avg_list = u_avg_list
		self.u_users_similar = u_users_similar
		self.u_users_items_list = u_users_items_list
		self.i_users_list = i_users_list
		self.i_avg_list = i_avg_list

	def __getitem__(self, index):
		uid = self.data[index][0]
		iid = self.data[index][1]
		label = self.data[index][2]
		u_avg = self.u_avg_list[uid]
		u_items_div = self.u_items_divlist[uid]
		u_users = self.u_users_similar[uid]
		u_users_items = self.u_users_items_list[uid]
		i_users = self.i_users_list[iid]
		i_avg = self.i_avg_list[iid]

		return (uid, iid, label), u_items_div, u_avg, u_users, u_users_items, i_users, i_avg

	def __len__(self):
		return len(self.data)