Modular Neural Network Composition Via Self Modules Registry

via “modular neural network composition via self.modules registry”

PyTorch toolkit for all speech processing tasks.

Unique: Provides a registry-based composition pattern where custom PyTorch modules are registered in `self.modules` and accessed by name within the training loop, enabling clean separation between model architecture definition and training logic. Unlike monolithic model classes, this allows swapping components without rewriting the entire model.

vs others: More flexible than fixed model architectures, cleaner than manually managing module references in __init__, and enables easier experimentation with different component combinations than rebuilding models from scratch.