Particlenet added and all km3net dependencies are deleted #740
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RasmusOrsoe
reviewed
Aug 26, 2024
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Hey @giogiopg @IvanMM27 - thanks for this very clean pull request 🚀 !
There is only a few minor changes needed before we can merge this.
ParticleNeT.pyshould be changed toparticlenet.pyorparticle_net.pyso that it is in line with the snake case convention. (remember to adjust the import statement in the__init__.pyfile accordingly)- Two lines exceed the maximum line length (see comments)
| Default to "mean". | ||
| activation_layer: The activation function to use in the model. | ||
| Default to "relu". | ||
| add_batchnorm_layer: Whether to add a batch normalization layer after |
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Line too long. See CodeClimate.
| skip_readout: Whether to skip the readout layer(s). If `True`, the | ||
| output of the last DynEdgeConv block is returned directly. | ||
| """ | ||
| # Latent feature subset for computing nearest neighbours in ParticleNeT. |
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src/graphnet/models/gnn/__init__.py
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| @@ -6,3 +6,4 @@ | |||
| from .dynedge_kaggle_tito import DynEdgeTITO | |||
| from .RNN_tito import RNN_TITO | |||
| from .icemix import DeepIce | |||
| from .ParticleNeT import ParticleNeT | |||
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from .particlenet import ParticleNeT
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Hello @RasmusOrsoe, I made the changes you commented. Nevertheless, the codeclimate scan shows 6 errors to fix that I think they were previously too. Could you please review this? Thank you! Adding @giogiopg for completeness |
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ParticleNeT model for Jet Tagging with particle cloud-like data used in KM3NeT was successfully implemented in GraphNeT. It uses all the utilities from GraphNeT, mainly DynEdgeConv blocks, to build its architecture. References:
Pull request previously opened by @IvanMM27 with the difference that all the km3net data processing dependencies have been removed.