Adversarial Autoencoders (with Pytorch)
Dependencies
- argparse
- time
- torch
- torchvision
- numpy
- itertools
- matplotlib
Create Datasets
python create_datasets.py
python create_datasets.py
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NeurIPS 2021 Title: Distilling Robust and Non-Robust Features in Adversarial Exa
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Hi, when I run the code, I meet the following errors: "AttributeError: can't set attribute". and I checked the code of data pre-process script:
trainset_new.train_data = train_data_sub.clone() trainset_new.train_labels = train_labels_sub.clone()
but in the "sub.py" file, the class "subMNIST" do not define this attribute, how do you run the code successfully?
When I tried the unsupervised experiment, I tried to improve the dimension of z_dim, but the generator was completely broken, and I failed to try to modify it. I wonder if you have tried, could you please provide some information? Thank you very much!
In aae_pytorch_basic.py, line 181 and line 212, those three constants are used for what? and how do you choose those? BTW, please forgive my poor english.... Thank you in advance.
The README mentions create_datasets.py
-- I guess it is missing?
Thanks v much for https://blog.paperspace.com/adversarial-autoencoders-with-pytorch/
, it is excellent.
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