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Counterfactual Samples Synthesizing for Robust VQA

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我改成了import _pickle as cPickle 然后在数据预处理时,报错 vals = list(map(float, vals[1:])) ![feb077d81bf6621670285c5cb2f554b](https://user-images.githubusercontent.com/16870890/187818574-8178e614-b997-44aa-bae0-74a8f6d80d02.png) 但是在运行main 时又出现新的编码问题 utf-8 ![image](https://user-images.githubusercontent.com/16870890/187818664-90217fde-7e63-4c7b-bd4c-88b76ad226d8.png) 通过 fe=torch.load('data/rcnn_feature/'+str(img_id)+'.pth', encoding="ISO-8859-1")['image_feature'] classifier nn.Dropout(dropout, inplace=False) 又跑通了 最大 57.98 与文中的最好值相差1个点,是正常现象吗? ![image](https://user-images.githubusercontent.com/16870890/187893036-950b2549-f3fe-4dc4-977f-a57bbf008b17.png)

What are the parameters of the best result of the model? I can't reproduce similar results. Thank you very much for your work!

When I tired to run `CUDA_VISIBLE_DEVICES=0 python main.py --dataset cpv2 --mode q_v_debias --debias learned_mixin --topq 1 --topv -1 --qvp 5 --output [] --seed 0`, it went error. @yanxinzju

Thank you very much for your excellent work. I would like to ask you about the parameter entry["bias"] when processing the dataset. What does it refer to and how did...

i want to know if i want to use other picture to test this code ,how can i get the feature. can you give us the code about this?

Hi, nice work and I am interested in it. In train.py, there are a few lines of code I do not understand: ``` m1 = copy.deepcopy(sen_mask) ##[0,0,0...0,1,1,1,1] m1.scatter_(1, w_ind, 0)...

Hi, can you share the code for spacy to extract the nouns in the question? Thank you so much