Custom Pytorch Frontend I gradually build on for my projects. This has pretty much become a multi-year personal project I use to keep a personally customized front-end for deep learning when trying out new projects. Over the years I've added all kinds of cool features like:
- Input size inferral - no need to define the input size to your layers
- Interface to train models with multiple or arbitrarily complex optimizer schemes
- Interface to train models with multiple or arbitrarily complex loss schemes
- Tracking training stats that can persist state over multiple batches
- Keras-like training and usage of models
- Pythonic pipelining and management of data
- Integration with useful libraries like
imgaugandtqdm
Below is the console and graph output from running mnist.py in the examples folder
To install run the following in your HOME directory.
git clone https://github.com/abhmul/PyJet/
cd PyJet
sudo pip install -e .
cd ..
To update, go to your PyJet installation directory (should be HOME/PyJet if you followed the installation instructions) and run
git pull