gcnn_keras
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aimat-lab
Graph convolutions in Keras with TensorFlow, PyTorch or Jax.
4 topics: A. transformers: - [x] MAT ( https://github.com/ardigen/MAT & https://arxiv.org/abs/2002.08264) - [ ] RMAT (https://github.com/gmum/huggingmolecules & https://arxiv.org/abs/2110.05841) B. Recursive Graphs: - [x] RGIN ( https://arxiv.org/pdf/1906.12192.pdf + code https://github.com/microsoft/tf2-gnn &...
Messages from: Internal 3d INFO:kgcnn.mol.encoder:OneHotEncoder Symbol found ['Cl', 'C', 'Br', 'O', 'N', 'P', 'S'] INFO:kgcnn.mol.encoder:OneHotEncoder Hybridization found [rdkit.Chem.rdchem.HybridizationType.SP3, rdkit.Chem.rdchem.HybridizationType.SP2, rdkit.Chem.rdchem.HybridizationType.SP] INFO:kgcnn.mol.encoder:OneHotEncoder TotalDegree found [1, 4, 3, 2] INFO:kgcnn.mol.encoder:OneHotEncoder TotalNumHs found...
MolFromXYZBlock ``` !cat ./data/dsgdb9nsd_107313.xyz def cleanup_qm9_xyz(fname): ind = open(fname).readlines() nAts = int(ind[0]) smi = ind[-2].split()[-1] ind[1] = '\n' ind = ind[:nAts+2] for i in range(2,nAts+2): l = ind[i] l =...
Can you implement for GAT this special Normalisation on the Attention operator https://github.com/gdasoulas/LipschitzNorm/blob/master/normalizations/lipschitznorm.py
training % python3 train_graph.py --hyper hyper/hyper_esol.py --category GIN Traceback (most recent call last): File "/Users/tgg/Github/gcnn_keras4/training/train_graph.py", line 9, in import kgcnn.losses.losses ModuleNotFoundError: No module named 'kgcnn.losses' I've updated github last code...
Hi, when looking at the dimensions of the attributes for nodes and bonds it appears that there are 41 and 11 atomic and bond level features included in the DMPNN...
Hi, I would like to utilise transfer learning similar to how it is outlined in this post: https://keras.io/guides/transfer_learning/ and was wondering if there were any examples on freezing the weights...
First of all, I think it is a very good idea to provide Keras with functionalities to work with graph networks. Currently, there is no alternative to PyG and the...
Hi, I am using the torch backend with gcnn_keras but my gpu is not being used. If i called `torch.cuda.isavaliable()` I get true but I'm unsure what I need to...
I would like to move to 2.13 but have lot of errors with 3.0.1 version is the 3.0.2 or current code is fixing it ? requirement file is not limiting...