The brain does not rely on a single type of neuron to perform all kinds of tasks; instead, it designs different neurons for different tasks.
The concept of task-based neurons represents a paradigm shift compared to task-based architectures.
It argues that solving a specific problem requires customized neurons, as task-based neurons capture useful prior knowledge from task-related data.
To facilitate the use of task-based neurons in scientific research and industrial applications, we introduce TNLearn, an open-source Python package that provides automated construction of task-based neurons and networks, enabling smooth training of task-based networks.
Comprehensive documentation, including technical exposition, API reference, and representative examples, is available online.
TNLearn is open-sourced at https://github.com/NewT123-WM/tnlearn and has become a PyTorch ecosystem project.