t3w 0.1.0.post2

Typed Thin PyTorch Wrapper

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 stronger and static typing 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], or pip install t3w[all], where the [common] tag will install dependencies for commonly used side effects (like tqdm etc), and [all] tag will install dependencies for all supported side effects. Note that the mnist example requires installing t3w[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.