Coder Social home page Coder Social logo

diamondback's People

Contributors

kirillshmilovich avatar mrjoness avatar

Stargazers

avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar avatar

Watchers

avatar

Forkers

kimdn mrjoness bondrewd

diamondback's Issues

Can't backmap with test data

Hi,

Thank you for sharing this work!
I am trying to run the code on the provided test data as shared in the README.

When I "backmap the PDB test data using the PDB-trained model" with this command:
python run_eval.py --training_set PDB --data_type aa --pdb_dir ../data/PDB_test_pdbs/
It finishes all the steps successfully but errors when converting to mdtraj:

Traceback (most recent call last):
  File "/DiAMoNDBack/scripts/run_eval.py", line 260, in <module> 
    iterative_inference(data, training_set, cond_type, n_cond_res, model_name, pdb_save_names=pb_save_names, dtime=dtime,
  File "/DiAMoNDBack/scripts/run_eval.py", line 249, in iterative_inference
    crd_to_mdtrj(all_seqs, all_crds_ref, all_crds, end_id_list,
  File "/DiAMoNDBack/scripts/utils.py", line 792, in crd_to_mdtrj
    sb_ref = scn.StructureBuilder(s, crd=c)
  File "/home/md-mi/miniconda3/envs/diffback/lib/python3.10/site-packages/sidechainnet/structure/StructureBuilder.py", line 95, in __init__
    raise ValueError(
ValueError: The length of the coordinate matrix must match the sequence length. You have provided coords. shape[0] = 3080.

Additionally, when I "backmap the DES test set using the DES-finetuned model" with this command:
python run_eval.py --training_set PDB_DES-FT --data_type aa --pdb_dir ../data/all_train_test_pdbs/DES_test
It gives this error:

trained models/train_PDB_DES-FT/32-1-2-4-8-6128-11.0-05-gammal.0--rescale20.0- 1
Milestone = 15
Traceback (most recent call last):
  File "/DiAMoNDBack/scripts/run_eval.py", line 260, in <module>
    iterative_inference(data, training_set, cond_type, n_cond_res, model_name, pdb_save_names=pdb_save_names, dtime=dtime,
  File "/DiAMoNDBack/scripts/run_eval.py", line 181, in iterative_inference
    for i in range (max(n_res_list)):
ValueError: max() arg is an empty sequence

May I ask how to fix this?

Thanks

Installation

Hello!

First of all, thank you very much for making this work available!

I'm trying to use the code but having some trouble making it work.

First, I tried to install it by following the instructions on my MacOS machine, but then I found out that the environment needed to be Linux.

Then, I tried to install it on a Linux machine, but then found out that it requires a specific CUDA:

Traceback (most recent call last):
  File "run_eval.py", line 262, in <module>
    gamma=gamma, train_lr=train_lr, adamw=adamw, rescale=rescale, round2=False, decode_termini=decode_termini)
  File "run_eval.py", line 194, in iterative_inference
    gen_xyzs = run_inference(trainer, data_name=test_iter_prefix, folder_name=test_save_dir, batch_size=5000)
  File "/home/diego/bkp.bmp/DiAMoNDBack/scripts/utils.py", line 442, in run_inference
    trainer.op_number, batch_size=n, samples = next(sample_dl).cuda()[:n, :]), batches))
  File "/home/diego/bkp.bmp/DiAMoNDBack/scripts/utils.py", line 442, in <lambda>
    trainer.op_number, batch_size=n, samples = next(sample_dl).cuda()[:n, :]), batches))
  File "/home/diego/.local/conda/envs/diffback/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
    return func(*args, **kwargs)
  File "../denoising_diffusion_pytorch/denoising_diffusion_pytorch_backmap_combined.py", line 702, in sample
    return self.p_sample_loop((batch_size, 1, op_number), samples)
  File "/home/diego/.local/conda/envs/diffback/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
    return func(*args, **kwargs)
  File "../denoising_diffusion_pytorch/denoising_diffusion_pytorch_backmap_combined.py", line 655, in p_sample_loop
    state = torch.randn(shape, device=device)
RuntimeError: CUDA error: no kernel image is available for execution on the device

I wonder if you could update the conda environment script, make available a CPU version, or at least write down a list of minimum requirements that are needed to try/test/reproduce the work.

Thank you!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo 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.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.