| # | |
| # Trains a DeepSequence VAE model. | |
| # | |
| #SBATCH --cluster=<clustername> | |
| #SBATCH --partition=<partitionname> | |
| #SBATCH --account=<accountname> | |
| #SBATCH --job-name=vae | |
| #SBATCH --output=logs/vae.out | |
| #SBATCH --gres=gpu:1 # Number of GPU(s) per node. | |
| #SBATCH --cpus-per-task=1 # CPU cores/threads | |
| #SBATCH --mem=48000M # memory per node | |
| #SBATCH --time=0-36:00 # Max time (DD-HH:MM) | |
| #SBATCH --ntasks=1 # Only set to >1 if you want to use multi-threading | |
| export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK | |
| dataset=$1 | |
| seed=$2 | |
| THEANO_FLAGS='floatX=float32,device=cuda' python /share/vault/Users/gz2294/combining-evolutionary-and-assay-labelled-data/src/vae_train.mod.py \ | |
| msa/${dataset}.a2m ${dataset}_${seed} $seed | |