A PyTorch Implementation code for developing super fast adversarial training

This is a PyTorch Implementation code for developing super fast adversarial training.
This code is combined with below state-of-the-art technologies for
accelerating adversarial attacks and defenses with Deep Neural Networks
on Volta GPU architecture.

• Distributed Data Parallel [link]
• Channel Last Memory Format [link]
• Mixed Precision Training [link]
• Mixed Precision + Adversarial Attack (based on torchattacks [link])
• Faster Adversarial Training for Large Dataset [link]
• Fast

   

   

   

  To finish reading, please visit source site