API Reference¶
Package Overview¶
The common infrastructure used throughout various submodules and various functions for calculations and tensor-creation which may be used either within Inferno or may be helpful for end-users.
The protocols and various implementations for parameter bounding, interpolation, extrapolation, and dimensionality reduction.
The basic components for spiking neural networks, the infrastructure used for connecting them into a network and for supporting generalized parameter updates, and encoding non-spiking data into spike trains.
The functional implementation of various components used by different models as a way to generalize and share functionality, also useful when implementing new classes that represent neural components.
The components needed for training spiking neural networks, as well as components which may be used for specific inference tasks (e.g. classification).
The infrastructure and components for monitoring the internal states of components.
A work-in-progress module containing PyTorch-based implementations of various probability distributions.
A work-in-progress module containing assorted components which may be useful when attempting to generate visualizations or diagnose issues, or whenever a placeholder is needed.