Source code of the Stanford Ribonanza RNA Folding first place solution
You can read the detailed solution description here -- https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/discussion/460121
Ubuntu 20.04.4 LTS x86_64
CPU: 2x EPYC 7662 (128 CPU each)
6 GPU NVIDIA Tesla V100 32GB CoWoS HBM2
1000GB RAM
2TB SSD
Use setup_data.sh to download train and test data
Use setup_tools.sh to install all required software
Use calculate_features.sh to calculate features required for the model
To train model use python_scripts/train_uni_adjnet.py script
We recommend to train model with the following options
python3 python_scripts/train_uni_adjnet_se.py --bpp_path /projects_nvme/deepbeer/eterna/ --train_path /projects/deepbeer/ribonanza/train_data/train_data.parquet --out_path outmodel_dir --device 0 --num_workers 20 --wd 0.05 --epoch 270 --lr_max 5e-3 --pct_start 0.05 --batch_cnt 1791 --sgd_lr 5e-5 --sgd_epochs 25 --sgd_batch_cnt 500 --sgd_wd 0.05 --fold 0 --nfolds 1000 --pos_embedding dyn --adj_ks 3 --seed 42 --use_se
Use python_scripts/train_uni_adjnet.py
Example:
python3 python_scripts/predict.py --bpp_path $bpp_path --test_path $test_path --model_path $model_weights_path --out_path $out_dir --device 0 --pos_embedding dyn --adj_ks 3 --num_workers 20 --use_se
In case of any question you write to dmitrypenzar1996@gmail.com