NWGraph
Graph library built on top of Pytorch to help the creation of GNNs.
Implementation based on (working draft) semantics defined at: https://www.overleaf.com/read/vfbqdgxtxnws
It does not define any trainer code (so no lightning), just graph semantics, edges, nodes and message passing. The training code is left to be done on a project by project basis.
Examples
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See ngclib trainer code, for example where they define a sequential way of training each edge independently. Upon training, the entire graph is loaded into memory to produce pseudo-labels, followed by a semi-supervised iteration. LME is used here for training.
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See mnist-ensemble-graph for a simple example where we train 5 edges in the same time. Each edge starts from a RGB image. Simple pytorch-lightning Trainer code is used here.
Metadata
Release files for nwgraph 3.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| nwgraph-3.0.2.tar.gz | 25.7 kB | Details |
Release files / nwgraph-3.0.2.tar.gz
| Download URL | nwgraph-3.0.2.tar.gz |
|---|---|
| Size | 25.7 kB |
| Tags | Source |
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7aceb08fdd2a87cf4e7abca0b94ad9cab54930d3301abb63bb430cedef4b1c01
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twine/5.1.1 CPython/3.12.4
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