[WIP] a high-level PyTorch helper package
This project is intended for my personal use. Backward compatibility will not be guaranteed. Important releases will be tagged.
fast.ai is great, and I recommend it for all deep learning beginners. But since it's beginner-friendly, a lot of more sophisticated stuffs are abstracted heavily and hidden from users. Reading the source code is often required before you can tweak the underlying algorithms. The advent of doc function greatly speeds up the process by quickly directing the user to the source code and documentation.
However, fast.ai has become stronger and bigger. Not everyone has time to keep up with its codebase. Hence the creation of this project. I built a relatively thin layer of abstraction upon PyTorch from scratch, with a lot of ideas and code borrowed from various sources (mainly fast.ai). Only features that are relevant to my use cases are added.
Another similar project is pytorch/ignite.
- Set the environment variable
SEED, and we will set the random seed of Python, Numpy and PyTorch for you. - Set the environment variable
DETERMINISTICto make CuDNN operations deterministic. - Set
pbar=Falsewhen initializing a bot to disable progress bar during evaluation.
There are almost no unit tests yet. The following example(s) are somewhat functional tests.