PAXlib
Augmentent PyTorch with some JAX
PAXlib augments PyTorch with JAX-inspired abstractions including functional state management and pytree-compatible module structures. It enables researchers to write more modular and composable deep learning code within a PyTorch workflow, without requiring a full migration to JAX.
PyTorch
- Technical
- Source code: Lab GitHub
- Last commit: 2022-03-02
Machine Learning and Optimization Laboratory
Machine Learning and Optimization Laboratory
The Machine Learning and Optimization Laboratory is interested in machine learning, optimization algorithms and text understanding, as well as several application domains.
This page was last edited on 2024-04-09.
This page was last edited on 2024-04-09.