sokrypton / sokrypton/ColabFold
In colabfold_search GPU mmseqs not compatible with `--use-templates 1`
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Description
In this line:
https://github.com/sokrypton/ColabFold/blob/406d4c6cf25a0755f61b3adac7c5d47d3025f42c/colabfold/mmseqs/search.py#L171
The --gpu 1 parameter is not propagated from the command line.
I built the local databases with:
GPU=1 ./setup_databases.sh /path/to/db_folder
as in the documentation.
When my run gets to the template search, it runs the command:
mmseqs search msas/prof_res /mnt/rbg/sequence_databases/colabfold_db/pdb100_230517 msas/res_pdb msas/tmp2 --db-load-mode 1 --threads 64 -s 7.5 -a -e 0.1 --prefilter-mode 0
and crashes with this error:
Index version: 16
Generated by: 8ef870f95af2a3ee474c2cdbb845f5f007fe5be6
ScoreMatrix: VTML80.out
Query database size: 1 type: Profile
Estimated memory consumption: 1G
Target database size: 329605 type: Aminoacid
Invalid database read for database data file=/mnt/rbg/sequence_databases/colabfold_db/pdb100_230517.idx, database index=/mnt/rbg/sequence_databases/colabfold_db/pdb100_230517.idx.index
getData: local id (4294967295) >= db size (17)
Error: Prefilter died
I can get the search to complete by modifying the command to:
mmseqs search msas/prof_res /mnt/rbg/sequence_databases/colabfold_db/pdb100_230517 msas/res_pdb msas/tmp2 --db-load-mode 1 --threads 64 -s 7.5 -a -e 0.1 --prefilter-mode 1 --gpu 1
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start at colabfold/mmseqs/search.py line 171 and inspect how the template-search command is assembled from command-line options. Reproduce the local-database search with GPU-enabled mmseqs and verify that the generated command includes the required GPU settings and completes without the reported prefilter error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- bioinformatics
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 55/100