We're excited to announce the first stable release of Bio Transformations! This Python package enhances artificial neural networks with biologically inspired mechanisms, aiming to improve learning speed, prediction accuracy, and resilience.
Key Features
- **Synaptic Diversity**: Implement diverse learning rates with `fuzzy_learning_rates()`
- **Structural Plasticity**: Simulate spine turnover with `rejuvenate_weights()`
- **Multi-synaptic Connectivity**: Allow multiple connections between neuron pairs
- **Homeostatic Plasticity**: Maintain network stability with synaptic scaling
- **Easy Integration**: Seamlessly convert existing PyTorch models
Highlights
- Compatible with PyTorch 1.8+
- Comprehensive documentation with tutorials and examples
- Efficient implementation with minimal overhead
Installation
bash
pip install bio-transformations
Quick Start
python
from bio_transformations import BioConverter
converter = BioConverter()
bio_model = converter(your_pytorch_model)
For full documentation, visit our visit our [GitHub Page](https://ceades.github.io/pytorch_bio_transformations/index.html) or
visit our [GitHub repository](https://github.com/CeadeS/pytorch_bio_transformations).
We welcome feedback and contributions from the community. Happy coding with biologically inspired neural networks!