| #SBATCH --partition=main # Ask for unkillable job | |
| #SBATCH --gres=gpu:1 | |
| #SBATCH --mem=10G # Ask for 10 GB of RAM | |
| #SBATCH --time=2:00:00 # The job will run for 3 hours | |
| #SBATCH --output=./logs/abstractive_out.txt | |
| #SBATCH --error=./logs/abstractive_error.txt | |
| #SBATCH -c 2 | |
| # Load the required modules | |
| module --quiet load miniconda/3 | |
| module --quiet load cuda/12.1.1 | |
| conda activate "glimpse" | |
| # Check if input file path is provided and valid | |
| if [ -z "$1" ] || [ ! -f "$1" ]; then | |
| # if no path is provided, or the path is invalid, use the default test dataset | |
| echo "Couldn't find a valid path. Using default path: data/processed/all_reviews_2017.csv" | |
| dataset_path="data/processed/all_reviews_2017.csv" | |
| else | |
| dataset_path="$1" | |
| fi | |
| # Generate abstractive summaries | |
| if [[ "$@" =~ "--add-padding" ]]; then # check if padding argument is present | |
| # add '--no-trimming' flag to the script | |
| candidates=$(python glimpse/data_loading/generate_abstractive_candidates.py --dataset_path "$dataset_path" --scripted-run --no-trimming | tail -n 1) | |
| else | |
| # no additional flags | |
| candidates=$(python glimpse/data_loading/generate_abstractive_candidates.py --dataset_path "$dataset_path" --scripted-run | tail -n 1) | |
| fi | |
| # Compute the RSA scores based on the generated summaries | |
| rsa_scores=$(python glimpse/src/compute_rsa.py --summaries $candidates | tail -n 1) | |