Deep Learning with PyTorch made easy 🚀 !
v0.5.x WIP!
Here are the main design principles:
- The codes should be '
modulefirst', which means all previousmodels should be a simplemodulenow.- And
modelshould only be related to the training stuffs. If we only want to use the fancy AI models at inference stage,moduleshould be all we need.
- And
- The
modules should be as 'native' as possible: no inheritance from base classes exceptnn.Moduleshould be the best, and previous inheritance-based features should be achieved by dependency injection.- This helps the
modules to be moretorch.compilefriendly.
- This helps the
- 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.
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