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jml's Issues

Is there something wrong wiht Data Preprocessing?

Hi, When I go through the data preprocessing, there is something wrong happennd. the program pre_data.py . The part of the program that classifies "aspect", "polarity", and "image_id" is wrong:
------aspect = lines[i + 1].lower().strip()
-----polarity = lines[i + 2].strip()
-----image_id = lines[i + 3].strip()
I add some print in it ,show what aspect ,polarity, image_id look like,show us:
+++++++++++++++++++++++++++++++++++++++++
aspect:
crazy hair day ! lydia is a contender . : )####crazy=o hair=o day=o !=o lydia=t-pos is=o a=o contender=o .=o :=o )=o

+++++++++++++++++++++++++++++++++++++++++
polarity:
rt @ historyneedsyou : mother and child # art for # mothersday by barbara hepworth , 1934####rt=O @=O historyneedsyou=O :=O mother=O and=O child=O #=O art=O for=O #=O mothersday=O by=O barbara=T-NEU hepworth=T-NEU ,=O 1934=O

+++++++++++++++++++++++++++++++++++++++++
image_id:
detailed illustrations of mythical creatures by jessica fortner####detailed=O illustrations=O of=O mythical=O creatures=O by=O jessica=T-NEU fortner=T-NEU

In addition,an error is reported:ValueError: invalid literal for int() with base 10: 'rt @ historyneedsyou : mother and child # art for # mothersday by barbara hepworth , 1934####rt=O @=O historyneedsyou=O :=O mother=O and=O child=O #=O art=O for=O #=O mothersday=O by=O barbara=T-NEU

关于训练参数

您好!想问下作者是用单卡跑的嘛,以及最终的参数就是脚本里那些吗 checkpoint结果是好的但重新训练结果差了快2个点5555

MATE、MASC子任务需要重新训练吗?

作者您好,请问在进行MATE和MASC子任务时,是将训练好的联合模型直接投入测试,还是要拆开联合模型再把这两个子任务进行一次重新训练呢?

twitter2017数据集的train.json/dev.json/test.json文件

您好!我在twitter2015数据集上修改训练之后,想要训练twitter2017数据,但是发现twitter17文件夹下没有train.json/dev.json/test.json文件,但是在twitter15数据集下有,请问代码中有预处理成json文件的部分吗?

关于重训练

请问这怎么重训练呢?我每次训练出来都是同样的数值,而且也没有50轮次。更像是直接加载了模型。

question about relation score

res_feture_R = res_feture * Rel_image_adds.unsqueeze(2)

Hi, author,
relation score 是一个0-1小数,乘以ResNet提取的图片特征,为什么可以说控制图片信息的输入呢?我能理解当relation score为0时图片信息为0,但是当不为0时,图片的特征整体乘以这样的一个小数,有什么意义呢?
您费心了!

question on pre_data.py

Hello, when I run pre_data.py, the test and dev data can transfer to multi aspect data successfully, however, the train data is not ok, and there is a error that:

(pytorch) root@1hhh/JML-main/JML_opened/data/Twitter# python pre_data.py
--------------IJCAI2019_data/twitter2015/test.txt---------------
--------------IJCAI2019_data/twitter2015/dev.txt---------------
--------------IJCAI2019_data/twitter2015/train.txt---------------
Traceback (most recent call last):
File "pre_data.py", line 145, in
write_data(data_add,save_path,Image_datas)
File "pre_data.py", line 124, in write_data
image_info=get_img_info(id,image_datas,dataset)
File "pre_data.py", line 112, in get_img_info
assert da_img['sentext'] == da_raw['sentent']
AssertionError

Therefore, I want to ask if the json file in /data/Twitter/twitter15 (the file path is the file location in baiduyun) can be used in pre_data.py, if not, which one should be used in pre_data.py in line 143?

Thank you!

process dataset

image
你好,我在没有找到您这个img_read_path路径提到的文件,能否提供一下这个文件?

resnet self-attention

Hello, I am very interested in your work. I have some questions to ask you. After RESNET network extracts image features, I don't understand how to implement the code of the self attention layer. At present, the code has not been uploaded. If you have time, can you help me answer this question ?

The utils package lacks a lot of modules

if i use the follow commands:
$ bash run_joint_method_(15/17).sh

Will feedback errors, such as
No module named 'utils.multihead'
No module named 'utils.data_loader_bb'

Could you please put some training code which can execute?
Thank you

想问一下data process的一些问题

我没有在IJCAI2019_data下发现data_process这个文件夹 想问下是不是test/train/dev.json是在twitter15这个文件夹下面 我替换成这个文件夹以后又出现了 assert da_img['sentext'] == da_raw['sentent']的问题

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