uic-paper / mimn Goto Github PK

import random

fi = open("local_test", "r")
ftrain = open("local_train_splitByUser", "w")
ftest = open("local_test_splitByUser", "w")

while True:
    rand_int = random.randint(1, 10)
    noclk_line = fi.readline().strip()
    clk_line = fi.readline().strip()
    if noclk_line == "" or clk_line == "":
        break
    if rand_int == 2:
        print >> ftest, noclk_line
        print >> ftest, clk_line
    else:
        print >> ftrain, noclk_line
        print >> ftrain, clk_line

这个脚本对测试集划分为train和test，写的有问题吧？ 不过看起来之前的步骤local_aggretor.py里就已经划分好了吧，

UserBehavior.csv共3G，跑了一晚上还是没完成，早上看卡在了3一动不动：
D:\Anaconda3\envs\TF2\python.exe F:/python/MIMN-master/preprocess/taobao_prepare.py
4162024 987994 9439 4
feature_size 4162024 5159462
group completed
987994
get user last touch time completed
1
2
3

然后一个白天也一动不动。有没有童鞋们把mimn跑起来呢？本想改成TF2的版本的，发现_Linear比较麻烦，然后放弃了

I think "i==1" in mimn.py Line84 should be changed by "i>=self.read_head_num".
From my point of view, this "i==1" is used to limit the operation only on write head weight when the self.read_head_num==1 and self.write_head_num==1.
But these two parameter can be changes in the code, so this "i==1" can cause problem when self.read_head_num!=1 or self.write_head_num!=1.

请问，我看了在taobao的训练数据中，数据得预处理，其中行为类型好像没有用到？是这样吗？另外时间数据，只是作为一个排序来使用的，并没有考虑行为之间的时间差是吗？