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View All on GitHubGigantic Graph Learning (GiGL) Framework: Large-scale training and inference for Graph Neural Networks
AI Summary: Add type hints to the `jupyter_magics.py` file to improve code readability and maintainability, removing the existing type ignore.
Gigantic Graph Learning (GiGL) Framework: Large-scale training and inference for Graph Neural Networks
AI Summary: The task is to refactor the GiGL Python codebase to replace imports from the `typing` module (e.g., `List`, `Dict`) with the built-in collection type syntax (e.g., `list[str]`, `dict[str, int]`) for type annotations, leveraging Python 3.9+ features. This involves finding all instances of these imports and updating the type hints accordingly.
Gigantic Graph Learning (GiGL) Framework: Large-scale training and inference for Graph Neural Networks