Comments (4)
Hi Sam,
thanks a lot for the heads-up. I have replaced the '.full()' by '.to(torch.float32)' which solves the issue on my end.
from prostt5.
Thank you very much. That worked perfectly.
While I am here, can I ask you if there is any difference in accuracy in creating 3DI sequences from amino acids when running predict_3DI_encoderOnly.py compared to translate.py?
Thanks again!
Sam
from prostt5.
Yes, indeed there will be a difference. Unfortunately, I still did not manage to update the bioRxiv version of the paper to have a proper description of the difference but in a nutshell:
- predict_3DI_encoderOnly.py only runs the encoder part of ProstT5 and predicts 3Di using an encoder trained on top of those embeddings.
- translate.py will run the full ProstT5 encoder/decoder for generating 3Di.
On the sets we compared, there is there is only a small (and even inconsistent - sometimes one is better sometimes the other) difference. So performance is nearly the same but running the encoder-only is MUCH faster, so I would clearly recommend that one.
Only use-case for translate.py is if you want to generate a distribution over different 3Di-possibilities. Sampling from the encoder-decoder model is much easier than sampling from the probability distribution output by the CNN in predict_3Di_encoderOnly.py.
from prostt5.
Very interesting. Thank you for the detailed response!
from prostt5.
Related Issues (16)
- Issue downloading model weights HOT 1
- Protein sequence length limit HOT 1
- Translation result is unexpected! HOT 1
- Foldseek not liking generate_foldseek_db.py output TSVs HOT 6
- 'T5Tokenizer' object has no attribute 'to' HOT 1
- Dataset version with IDs? HOT 11
- Problem while trying to convert AA to 3Diaa HOT 2
- computing residue logits from 3Di input HOT 5
- How well does this scale with length of amino acids? HOT 1
- Probability cutoff? HOT 6
- Converting the AA sequences to 3Di and getting the output in PDB format for Foldseek input? HOT 4
- Base Roundtrip Accuracy HOT 7
- translate.py documentation HOT 1
- Back Translate 3Di Tokesn to PDB Format HOT 1
- ProstT5 for tasks like AMP classification or protein localization. Also protT5 xxl results. HOT 1
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