sokrypton / sokrypton/ColabFold

RosettaFold2 (WIP) Colab crash

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Jupyter Notebook
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Description

While trying to run RF2 this morning, I get two separate error messages as the program crashes. The first fault occurs at the early 'Setup RosettaFold' stage (below), and the second at the next "Run RosettaFold' point, apparently while trying to assemble the MSA (error msg at the bottom). Thx in advance for your kind help.

FIRST error msg:
install RoseTTAFold2
install hhsuite

OSError Traceback (most recent call last)
in

/content/RoseTTAFold2/network/predict.py in
6 from torch.utils import data
7 from parsers import parse_a3m, read_templates, read_template_pdb, parse_pdb
----> 8 from RoseTTAFoldModel import RoseTTAFoldModule
9 import util
10 from collections import namedtuple

8 frames
/usr/lib/python3.10/ctypes/init.py in init(self, name, mode, handle, use_errno, use_last_error, winmode)
372
373 if handle is None:
--> 374 self._handle = _dlopen(self._name, mode)
375 else:
376 self._handle = handle

OSError: libcudart.so.11.0: cannot open shared object file: No such file or directory

SECOND error msg:
jobname: xxxxxxxxxxxxx_X1_43e20
lengths: [167, 116]

NameError Traceback (most recent call last)
in <cell line: 60>()
59 os.makedirs(jobname, exist_ok=True)
60 if msa_method == "mmseqs2":
---> 61 get_msa(u_sequences, jobname, mode=pair_mode, max_msa=max_extra_msa)
62
63 elif msa_method == "single_sequence":

NameError: name 'get_msa' is not defined

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reproducing the RosettaFold2 Colab notebook, then inspect network/predict.py around the RoseTTAFoldModel import and the notebook cell calling get_msa. Check the reported CUDA library and undefined-name failures in the installation and MSA stages; done means both stages run without these crashes.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
bioinformatics, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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