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Title: Explicit valence for atom # 219 C, 5, is greater than permitted · Issue #8 · DeepGraphLearning/DiffPack · GitHub

Open Graph Title: Explicit valence for atom # 219 C, 5, is greater than permitted · Issue #8 · DeepGraphLearning/DiffPack

X Title: Explicit valence for atom # 219 C, 5, is greater than permitted · Issue #8 · DeepGraphLearning/DiffPack

Description: When I run diffpack on an antibody design I generated from diffab, I get the above error and it writes nothing to disk and just exits. This is the pdb file (just change the extension to .pdb) output.txt #!/usr/bin/env bash # # exec pytho...

Open Graph Description: When I run diffpack on an antibody design I generated from diffab, I get the above error and it writes nothing to disk and just exits. This is the pdb file (just change the extension to .pdb) outpu...

X Description: When I run diffpack on an antibody design I generated from diffab, I get the above error and it writes nothing to disk and just exits. This is the pdb file (just change the extension to .pdb) outpu...

Opengraph URL: https://github.com/DeepGraphLearning/DiffPack/issues/8

X: @github

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Domain: patch-diff.githubusercontent.com


Hey, it has json ld scripts:
{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Explicit valence for atom # 219 C, 5, is greater than permitted","articleBody":"When I run diffpack on an antibody design I generated from diffab, I get the above error and it writes nothing to disk and just exits.\r\n\r\nThis is the pdb file (just change the extension to .pdb)\r\n[output.txt](https://github.com/user-attachments/files/16364736/output.txt)\r\n\r\n\r\n```./run_example.sh\r\n#!/usr/bin/env bash\r\n#\r\n#\r\nexec python script/inference.py -c config/inference_confidence.yaml \\\r\n                           --seed 2023 \\\r\n                           --output_dir path/to/output \\\r\n                           --pdb_files $@\r\n```\r\n```\r\n| ./run_example.sh output.pdb\r\n16:45:24   Config file: /home/ws/projects/diffpack/DiffPack/config/inference_confidence.yaml\r\n16:45:24   {'engine': {'batch_size': 32, 'gpus': [0], 'log_interval': 1000},\r\n 'model_checkpoint': '~/scratch/trained_model/diffpack/gearnet_edge_confidence_converted.pth',\r\n 'optimizer': {'class': 'Adam', 'lr': 0.0001},\r\n 'task': {'class': 'ConfidencePrediction',\r\n          'confidence_model': {'batch_norm': True,\r\n                               'class': 'GearNet',\r\n                               'concat_hidden': True,\r\n                               'edge_input_dim': 58,\r\n                               'hidden_dims': [128, 128, 128, 128, 128, 128],\r\n                               'input_dim': 39,\r\n                               'num_angle_bin': 8,\r\n                               'num_relation': 6,\r\n                               'readout': 'sum',\r\n                               'short_cut': True},\r\n          'graph_construction_model': {'class': 'GraphConstruction',\r\n                                       'edge_feature': 'gearnet',\r\n                                       'edge_layers': [{'class': 'BondEdge'},\r\n                                                       {'class': 'SpatialEdge',\r\n                                                        'min_distance': 2,\r\n                                                        'radius': 4.5},\r\n                                                       {'class': 'KNNEdge',\r\n                                                        'k': 10,\r\n                                                        'min_distance': 0}]},\r\n          'model': {'batch_norm': True,\r\n                    'class': 'GearNet',\r\n                    'concat_hidden': True,\r\n                    'edge_input_dim': 58,\r\n                    'hidden_dims': [128, 128, 128, 128, 128, 128],\r\n                    'input_dim': 128,\r\n                    'num_angle_bin': 8,\r\n                    'num_relation': 6,\r\n                    'readout': 'sum',\r\n                    'short_cut': True},\r\n          'num_mlp_layer': 3,\r\n          'num_sample': 4,\r\n          'schedule_1pi_periodic': {'annealed_temp': 3,\r\n                                    'cache_folder': '~/scratch/output/diffpack',\r\n                                    'class': 'SO2VESchedule',\r\n                                    'mode': 'ode',\r\n                                    'pi_periodic': True},\r\n          'schedule_2pi_periodic': {'annealed_temp': 3,\r\n                                    'cache_folder': '~/scratch/output/diffpack',\r\n                                    'class': 'SO2VESchedule',\r\n                                    'mode': 'ode',\r\n                                    'pi_periodic': False},\r\n          'sigma_embedding': {'class': 'SigmaEmbeddingLayer',\r\n                              'hidden_dims': [64, 128],\r\n                              'input_dim': 39,\r\n                              'sigma_dim': 64},\r\n          'torsion_mlp_hidden_dims': [64, 128],\r\n          'train_chi_id': None},\r\n 'test_set': {'atom_feature': 'residue_symbol',\r\n              'bond_feature': None,\r\n              'class': 'SideChainDataset',\r\n              'mol_feature': None,\r\n              'path': None,\r\n              'pdb_files': ['output_test.pdb'],\r\n              'removeHs': True,\r\n              'residue_feature': None,\r\n              'sanitize': True,\r\n              'transform': {'class': 'Compose', 'transforms': []}},\r\n 'train': {'num_epoch': 0}}\r\n16:45:24   Output dir: /home/ws/projects/diffpack/DiffPack/path/to/output\r\n16:45:34   Preprocess training set\r\n16:45:37   {'batch_size': 32,\r\n 'class': 'core.Engine',\r\n 'gpus': [0],\r\n 'gradient_interval': 1,\r\n 'log_interval': 1000,\r\n 'logger': 'logging',\r\n 'num_worker': 0,\r\n 'optimizer': None,\r\n 'scheduler': None,\r\n 'task': {'class': 'tasks.ConfidencePrediction',\r\n          'graph_construction_model': {'class': 'layers.GraphConstruction',\r\n                                       'edge_feature': 'gearnet',\r\n                                       'edge_layers': [{'class': 'layers.geometry.BondEdge'},\r\n                                                       {'class': 'layers.geometry.SpatialEdge',\r\n                                                        'max_distance': None,\r\n                                                        'max_num_neighbors': 32,\r\n                                                        'min_distance': 2,\r\n                                                        'radius': 4.5},\r\n                                                       {'class': 'layers.geometry.KNNEdge',\r\n                                                        'k': 10,\r\n                                                        'max_distance': None,\r\n                                                        'min_distance': 0}],\r\n                                       'node_layers': None},\r\n          'model': {'activation': 'relu',\r\n                    'batch_norm': True,\r\n                    'class': 'models.GearNet',\r\n                    'concat_hidden': True,\r\n                    'edge_input_dim': 58,\r\n                    'hidden_dims': [128, 128, 128, 128, 128, 128],\r\n                    'input_dim': 128,\r\n                    'num_angle_bin': 8,\r\n                    'num_relation': 6,\r\n                    'readout': 'sum',\r\n                    'short_cut': True},\r\n          'schedule_1pi_periodic': {'PI': 1.5707963267948966,\r\n                                    'cache_folder': '~/scratch/output/diffpack',\r\n                                    'class': 'SO2VESchedule'},\r\n          'schedule_2pi_periodic': {'PI': 3.141592653589793,\r\n                                    'cache_folder': '~/scratch/output/diffpack',\r\n                                    'class': 'SO2VESchedule'},\r\n          'sigma_embedding': {'class': 'layers.SigmaEmbeddingLayer',\r\n                              'embed_type': 'sinusoidal',\r\n                              'hidden_dims': [64, 128],\r\n                              'input_dim': 39,\r\n                              'operation': 'post_add',\r\n                              'sigma_dim': 64},\r\n          'torsion_mlp_hidden_dims': [64, 128],\r\n          'train_chi_id': None,\r\n          'verbose': 0},\r\n 'test_set': None,\r\n 'train_set': None,\r\n 'valid_set': None}\r\n16:45:37   #parameter: 9351987\r\n16:45:37   Loading dataset from pdb files\r\nConstructing proteins from pdbs:   0%|                                                                                                                                                                                | 0/1 [00:00\u003c?, ?it/s][16:45:37] Explicit valence for atom # 219 C, 5, is greater than permitted\r\nConstructing proteins from pdbs: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00\u003c00:00,  9.68it/s]\r\n16:45:37   Test on SideChainDataset(  #sample: 0)\r\n16:45:37   /home/ws/projects/diffpack/DiffPack/path/to/output\r\n```","author":{"url":"https://github.com/wjs20","@type":"Person","name":"wjs20"},"datePublished":"2024-07-24T16:04:01.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":1},"url":"https://github.com/8/DiffPack/issues/8"}

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og:image:altWhen I run diffpack on an antibody design I generated from diffab, I get the above error and it writes nothing to disk and just exits. This is the pdb file (just change the extension to .pdb) outpu...
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