HAT-CL: A Hard-Attention-to-the-Task PyTorch Library for Continual Learning

Catastrophic forgetting, the phenomenon in which a neural network loses previously obtained knowledge during the learning of new tasks, poses a significant challenge in continual learning. The Hard-Attention-to-the-Task (HAT) mechanism has shown potential in mitigating this problem, but its practical implementation has been complicated by issues of usability and compatibility, and a lack of support for existing network reuse. In this paper, we introduce HAT-CL, a user-friendly, PyTorch-compatible redesign of the HAT mechanism. HAT-CL not only automates gradient manipulation but …

attention catastrophic forgetting challenge continual cs.ai cs.lg implementation knowledge library network neural network practical pytorch pytorch library tasks usability