Adversarial-Deep-Learning / Adversarial-Deep-Learning/code-soup
Add ATNs for ImageNet dataset
- Lenguaje dominante
- Jupyter Notebook
- Estrellas
- 17
- Forks
- 17
- Métricas de merge de PR
- Sin PR fusionados en 30 d
Descripción
This issue is a continuation of #19. The code for MNIST will be merged in #85. The original paper also mentions architectures for ImageNet models. It would be nice to have these implementations in the repository.
In this [comment](https://github.com/Adversarial-Deep-Learning/code-soup/pull/85#issuecomment-923621353), I have added dummy code for all architectures needed. However, the implementation should contain exactly the same number of channels/kernel sizes as the original model.
This will need effort in checking the what input/output paddings and strides will work given the architecture.
Guía de contribución
Evaluación
Este issue todavía no se ha evaluado.