Typed Thin PyTorch Wrapper
Project description
t3w.py
- Typed Thin (Py)Torch Wrapper
T3W is a lightweight framework for training PyTorch models written by Yuyao Huang during his PhD at Tongji University.
- T3W is "typed". It leverages a stronger and static type compared to normal python code for clearer architecture and less bugs. The programming model is object-oriented. Users (you) are required to implement interfaces as subclasses and inject them as dependencies.
- T3W is "thin". With the philosophy "less is more" in mind, it leverages a minimal codebase in a self-contained single python script that basically only depends on PyTorch to run. The plugin system under interface
ISideEffect
makes T3W not only thin, but also highly extensible. - T3W stands with "PyTorch".
See the concise example mnist_example.py.
If you feel like using t3w.py
, you can either
- install it with
pip install t3w
,pip install t3w[common]
, orpip install t3w[all]
, where the latter will install common side effects dependencies liketqdm
etc. Note that the mnist example requires installingt3w[common]
. - just download and integrate the t3w.py source file into your own project if you feel like freezing the version and/or ready to make some of your favorite hacks at low-level.
Detailed documentation will come in the future.
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