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JellyML is an open-source tool (python API and command line) for effortlessly embedding a snapshot of your code into a checkpoint of a pytorch (and pytorch lightning) model.

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mmulet/jellyml

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JellyML

JellyML is an open-source tool (python API and command line) for effortlessly embedding a snapshot of your code | into a checkpoint of a pytorch model. Learn more at jellyml.com

pip install jellyml

Structure of the jellyml repository

(Note that the jellyml repository is a monorepo. If you are reading this from the python package source code, go to github.com/mmulet/jellyml to see the whole repository)

  • jellyml is the source for the python package
  • jellyml-lightning is the source for pytorch lightning plugin
  • client is the source for the website
  • dev_server is the source for the development server of the website

Build

jellyml

  1. Make a venv
python3 -m venv venv
# activate the venv ( depends on your shell and OS)
# see https://docs.python.org/3/library/venv.html
# bash
source venv/bin/activate
  1. Install build
pip install build
  1. Build the package
cd jellyml
python -m build
pip install dist/jellyml-0.0.1-py3-none-any.whl

jellyml-lightning

  1. Follow the directions for building and installing jellyml. jellyml is a dependency of jellyml-lightning.
  2. Build the package
cd jellyml-lightning
python -m build
pip install dist/jellyml-lightning-0.0.1-py3-none-any.whl

Website

Build the website

cd client
npm install .
cd ../dev_server
npm install .
npm run build

Dev the website

cd client
npm install .
cd ../dev_server
npm install .
npm run build

Tests

Located in the source files in src/jellyml. Have the prefix test_. Run them as a module

cd src;
python3 -m jellyml.test_all

About

JellyML is an open-source tool (python API and command line) for effortlessly embedding a snapshot of your code into a checkpoint of a pytorch (and pytorch lightning) model.

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