CNN PR [2/4]: Add CNN base class and IceCubeDNN model#894
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Introduce `graphnet.models.cnn`, the convolutional-network counterpart to the existing GNN backbones, intended to consume the image data representation added in the image-representation PR. - `CNN` — abstract base class (analogue of `GNN`) defining the interface for convolutional backbones operating on image-shaped `Data` objects. - `IceCubeDNN` — configurable CNN backbone following the IceCube DNN reconstruction architecture. `cnn/__init__.py` exports `CNN` and `IceCubeDNN`; the `LCSC` model lands in a follow-up PR. Split from graphnet-team#813.
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This was referenced May 27, 2026
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Summary
Third in the series of PRs being carved out of #813 (see the split tracking comment). Introduces
graphnet.models.cnn, the convolutional-network counterpart to the existing GNN backbones, intended to consume the image data representation added in #892.What's new
CNN— abstract base class (analogue ofGNN) defining the interface for convolutional backbones operating on image-shapedDataobjects.IceCubeDNN— configurable CNN backbone following the IceCube DNN reconstruction architecture.cnn/__init__.pyexportsCNNandIceCubeDNN.Dependencies / ordering
torch,torch_geometric.data.Data, andgraphnet.models.Model— there is no import-level dependency on the image-representation PR (CNN PR [1/4]: Add image data representation for CNN backbones #892). They consume image-shapedDataobjects at runtime. So this PR is independently importable, but conceptually it's meant to be used together with CNN PR [1/4]: Add image data representation for CNN backbones #892.LCSCmodel is intentionally not included here (its import was removed fromcnn/__init__.py); it lands in the next split PR.Test plan
black,flake8,docformatter,pydocstyle,mypy, EOL/whitespace)from graphnet.models.cnn import CNN, IceCubeDNNsucceedsSplit from #813.
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