User Guide#
This comprehensive user guide covers all aspects of using PyTorch Network Loader, from basic concepts to advanced features.
Overview#
The user guide is organized into the following sections:
- Network Configuration
Learn how to create network configurations using JSON files, including syntax, structure, and best practices.
- Layers
Complete reference of all available layer types, their parameters, and usage examples.
- Architectures
Detailed guide on training networks, including loss functions, optimizers, learning rate scheduling, and advanced training techniques.
- Datasets & Data Formats
Instructions on how to create and use datasets along with data formats for NetLoader architectures.
- Loss Functions
Loss functions compatible with PyTorch safe weight loading.
- Schedulers
Schedulers to vary parameters during training, such as learning rate.
- Transforms
Data transforms for preprocessing datasets.
Getting Help#
If you need help:
Check the API Reference for detailed API documentation
Visit the Issue Tracker