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 self-contained codebase that basically only depends on PyTorch to run. The plugin system under interface
ISideEffectmakes 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 install it with pip install t3w.
API documentation is currently available at https://tjyuyao.github.io/t3w/api/. We are going to add more detailed user guide in the future.
Metadata
Release files for t3w 0.3.3
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Source distribution (sdist)
| File | Size | Uploaded | |
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| t3w-0.3.3.tar.gz | 33.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| t3w-0.3.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 69.3 kB
Release files / t3w-0.3.3.tar.gz
| Download URL | t3w-0.3.3.tar.gz |
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| Size | 33.1 kB |
| Tags | Source |
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Release files / t3w-0.3.3-py3-none-any.whl
| Download URL | t3w-0.3.3-py3-none-any.whl |
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| Size | 36.1 kB |
| Tags | Python 3 |
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