Deep Learning with PyTorch made easy 🚀 !

v0.5.x WIP!

Here are the main design principles:

• The codes should be 'module first', which means all previous models should be a simple module now.
  • And model should only be related to the training stuffs. If we only want to use the fancy AI models at inference stage, module should be all we need.
• The modules should be as 'native' as possible: no inheritance from base classes except nn.Module should be the best, and previous inheritance-based features should be achieved by dependency injection.
  • This helps the modules to be more torch.compile friendly.
• Training stuffs are not considered at the first place, but they will definitely be added later on, based on the modern AI developments.
• APIs will be as BC as possible.

License

carefree-learn is MIT licensed, as found in the LICENSE file.