Welcome to PINA’s documentation!#
PINA is an open-source Python library designed to simplify and accelerate the development of Scientific Machine Learning (SciML) solutions. Built on top of PyTorch, PyTorch Lightning, and PyTorch Geometric, PINA provides an intuitive framework for defining, experimenting with, and solving complex problems using Neural Networks, Physics-Informed Neural Networks (PINNs), Neural Operators, and more.
Modular Architecture: Designed with modularity in mind and relying on powerful yet composable abstractions, PINA allows users to easily plug, replace, or extend components, making experimentation and customization straightforward.
Scalable Performance: With native support for multi-device training, PINA handles large datasets efficiently, offering performance close to hand-crafted implementations with minimal overhead.
Highly Flexible: Whether you’re looking for full automation or granular control, PINA adapts to your workflow. High-level abstractions simplify model definition, while expert users can dive deep to fine-tune every aspect of the training and inference process.
For further information or questions about PINA contact us by email.