Comments (8)
I know, you should set use_chirality=True and explicit_H=False.
from rtmscore.
you can use the script RTMScore/RTMScore/feats/mol2graph_rdmda_res.py to generate the graph from pdb files.
from rtmscore.
Hi, I have been trying to use the script as well, however it looks like data are prepared in a different way.
Below you find two examples of data extracted by the .bin
files you provided on zenodo (https://zenodo.org/record/6859325#.Y1ayTtJBxH5) and the ones generated by the script. Looks like the graphs have different features dimensions. The first graphs (provided) works for training the model. In fact, the second example give a runtime mismatch error in cuda.
Thank you for your time an help.
('3d0e', Graph(num_nodes=31, num_edges=68,
ndata_schemes={'atom': Scheme(shape=(41,), dtype=torch.float64), 'pos': Scheme(shape=(3,), dtype=torch.float64)}
edata_schemes={'bond': Scheme(shape=(10,), dtype=torch.int64)}), Graph(num_nodes=99, num_edges=2812,
ndata_schemes={'feats': Scheme(shape=(41,), dtype=torch.float64), 'ca_pos': Scheme(shape=(3,), dtype=torch.float32), 'center_pos': Scheme(shape=(3,), dtype=torch.float64), 'pos': Scheme(shape=(24, 3), dtype=torch.float64)}
edata_schemes={'feats': Scheme(shape=(5,), dtype=torch.float64)}))
('03168_2FWZ', Graph(num_nodes=28, num_edges=62,
ndata_schemes={'pos': Scheme(shape=(3,), dtype=torch.float64), 'atom': Scheme(shape=(38,), dtype=torch.int64)}
edata_schemes={'bond': Scheme(shape=(6,), dtype=torch.int64)}), Graph(num_nodes=158, num_edges=5072,
ndata_schemes={'pos': Scheme(shape=(24, 3), dtype=torch.float64), 'feats': Scheme(shape=(41,), dtype=torch.float64)}
edata_schemes={'feats': Scheme(shape=(5,), dtype=torch.float64)}))
Error in CUDNN
** On entry to SGEMM parameter number 10 had an illegal value
Traceback (most recent call last):
File "train_model.py", line 116, in <module>
total_loss_train, mdn_loss_train, atom_loss_train, bond_loss_train = run_a_train_epoch(epoch, model, train_loader, optimizer, aux_weight=args["aux_weight"], device=args["device"])
File "/home/pmorerio/code/RTMScore/scripts/../RTMScore/model/utils.py", line 522, in run_a_train_epoch
pi, sigma, mu, dist, atom_types, bond_types, batch = model(bgp, bgl)
File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/pmorerio/code/RTMScore/scripts/../RTMScore/model/model2.py", line 499, in forward
h_l = self.lig_model(bgl, bgl.ndata['atom'].float(), bgl.edata['bond'].float())
File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/pmorerio/code/RTMScore/scripts/../RTMScore/model/model2.py", line 444, in forward
node_feats = self.node_encoder(node_feats)
File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 96, in forward
return F.linear(input, self.weight, self.bias)
File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/functional.py", line 1847, in linear
return torch._C._nn.linear(input, weight, bias)
RuntimeError: CUDA error: CUBLAS_STATUS_INVALID_VALUE when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)`
from rtmscore.
Are you exactly use the script RTMScore/RTMScore/feats/mol2graph_rdmda_res.py to generate the graphs? I think the same results can be obtained if you directly use this script. Some changes may have been made for my script.
Hi, I have been trying to use the script as well, however it looks like data are prepared in a different way. Below you find two examples of data extracted by the
.bin
files you provided on zenodo an(https://zenodo.org/record/6859325#.Y1ayTtJBxH5) and the ones generated by the script. Looks like the graphs have different features dimensions. The first graphs (provided) works for training the model. In fact, the second example give a runtime mismatch error in cuda.Thank you for your time an help.
('3d0e', Graph(num_nodes=31, num_edges=68, ndata_schemes={'atom': Scheme(shape=(41,), dtype=torch.float64), 'pos': Scheme(shape=(3,), dtype=torch.float64)} edata_schemes={'bond': Scheme(shape=(10,), dtype=torch.int64)}), Graph(num_nodes=99, num_edges=2812, ndata_schemes={'feats': Scheme(shape=(41,), dtype=torch.float64), 'ca_pos': Scheme(shape=(3,), dtype=torch.float32), 'center_pos': Scheme(shape=(3,), dtype=torch.float64), 'pos': Scheme(shape=(24, 3), dtype=torch.float64)} edata_schemes={'feats': Scheme(shape=(5,), dtype=torch.float64)})) ('03168_2FWZ', Graph(num_nodes=28, num_edges=62, ndata_schemes={'pos': Scheme(shape=(3,), dtype=torch.float64), 'atom': Scheme(shape=(38,), dtype=torch.int64)} edata_schemes={'bond': Scheme(shape=(6,), dtype=torch.int64)}), Graph(num_nodes=158, num_edges=5072, ndata_schemes={'pos': Scheme(shape=(24, 3), dtype=torch.float64), 'feats': Scheme(shape=(41,), dtype=torch.float64)} edata_schemes={'feats': Scheme(shape=(5,), dtype=torch.float64)}))
Error in CUDNN
** On entry to SGEMM parameter number 10 had an illegal value Traceback (most recent call last): File "train_model.py", line 116, in <module> total_loss_train, mdn_loss_train, atom_loss_train, bond_loss_train = run_a_train_epoch(epoch, model, train_loader, optimizer, aux_weight=args["aux_weight"], device=args["device"]) File "/home/pmorerio/code/RTMScore/scripts/../RTMScore/model/utils.py", line 522, in run_a_train_epoch pi, sigma, mu, dist, atom_types, bond_types, batch = model(bgp, bgl) File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl return forward_call(*input, **kwargs) File "/home/pmorerio/code/RTMScore/scripts/../RTMScore/model/model2.py", line 499, in forward h_l = self.lig_model(bgl, bgl.ndata['atom'].float(), bgl.edata['bond'].float()) File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl return forward_call(*input, **kwargs) File "/home/pmorerio/code/RTMScore/scripts/../RTMScore/model/model2.py", line 444, in forward node_feats = self.node_encoder(node_feats) File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl return forward_call(*input, **kwargs) File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 96, in forward return F.linear(input, self.weight, self.bias) File "/home/pmorerio/anaconda3/envs/rtmscore/lib/python3.8/site-packages/torch/nn/functional.py", line 1847, in linear return torch._C._nn.linear(input, weight, bias) RuntimeError: CUDA error: CUBLAS_STATUS_INVALID_VALUE when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)`
from rtmscore.
Yes, I have used the script RTMScore/RTMScore/feats/mol2graph_rdmda_res.py
to generate the second graph (03168_2FWZ
), while the firs graph (3d0e
) was stored inside v2020_train_l.bin
provided on zenodo at https://zenodo.org/record/6859325#.Y1ayTtJBxH5. With the graphs provided on zenodo I am able to retrain the model, while I get errors with the graphs generated by your script. Maybe you have used a different script to generate v2020_train_l.bin
?
from rtmscore.
Ok, thank you very much, I will try that!
from rtmscore.
Definitely works, thank you.
from rtmscore.
Related Issues (19)
- error of create conda env HOT 3
- Meaning of the distance threshold HOT 2
- casf对接和筛选能力 HOT 10
- Pretrained models - question HOT 2
- rdkit cannot load some mol2 files HOT 7
- 环境问题 HOT 6
- RTMScore的score的打分如何查看?
- 使用新的口袋和配体测试Score为0 HOT 1
- re-train a model based on new dataset
- The AUC values presented in Table 6 and Figure 6A seem to be inconsistent. HOT 2
- How to Batch Process RTMScore for Multiple Models in PDB and SDF Files
- Could you provide raw data of pdbbind2020? HOT 1
- integrating w/ docking HOT 1
- sanity checking on new target HOT 40
- Some of the ligands in CASF core set cannot be read by RDKit successfully HOT 2
- Additive terms in MDN outputs HOT 2
- How should we preprocess .pdbqt files before using RTMScore? HOT 6
- Graph files on zenodo HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from rtmscore.