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feature: add support for PyTorch Lightning #774

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89 changes: 89 additions & 0 deletions graphstorm-lightning/.gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Sphinx documentation
docs/_build/

# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
.python-version


# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
poetry.lock


# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# VSCode
**/.vscode/

# pre-commit
.pre-commit-config.yaml
3 changes: 3 additions & 0 deletions graphstorm-lightning/README.md
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# GraphStorm Support for PyTorch Lightning

Provides essential wrappers for GraphStorm constructs to run training using [PyTorch Lightning](https://lightning.ai/docs/pytorch/stable/).
7 changes: 7 additions & 0 deletions graphstorm-lightning/examples/README.md
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# Setup

1. Run `poetry install --with dev`
1. Run `poetry run python -m ipykernel install --user --name=graphstorm_lightning`
1. Run `poetry run jupyter notebook`
1. Open an example notebook
1. In `Kernel -> Change Kernel` choose `graphstorm_lightning`
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