#!/bin/bash
#SBATCH --job-name=JOB_spliceai_pytorch_train_MANE_small_dataset
#SBATCH --time=48:0:0
#SBATCH -p a100 # specify the GPU partition
#SBATCH -N 1 # Number of nodes
#SBATCH --ntasks-per-node=48
#SBATCH --gres=gpu:4
#SBATCH -A ssalzbe1_gpu ### Slurm-account is usually the PI’s userid
#SBATCH --export=ALL


# # Load system modules
# ml purge
# # module load gcc/9.3.0
# # module load cuda/11.1.0
# # module load anaconda

# source activate /home/kchao10/miniconda3/envs/pytorch_cuda

# # Check if the Python interpreter picks up packages from both the system and the Conda environment
# which python
# python -c "import sys; print(sys.path)"


python predict_spliceai27.py --flanking-size 10000 \
--project-name spliceai1_prediction \
--test-dataset /home/kchao10/data_ssalzbe1/khchao/data/train_test_dataset_MANE_test/dataset_test.h5 \
--output-dir /home/kchao10/data_ssalzbe1/khchao/spliceAI-toolkit/results/model_predict_outdir/ \
--model /home/kchao10/data_ssalzbe1/khchao/spliceAI-toolkit/models/spliceai/spliceai3.h5 -d

# \ > train_splan_LocalTransformer_MANE_80.log 2> train_splan_LocalTransformer_MANE_80_error.log

python predict_spliceaitoolkit.py --flanking-size 10000 \
--project-name spliceai1_prediction \
--test-dataset /home/kchao10/data_ssalzbe1/khchao/data/train_test_dataset_MANE_test/dataset_test.h5 \
--output-dir /home/kchao10/data_ssalzbe1/khchao/spliceAI-toolkit/results/model_predict_outdir/ \
--model /home/kchao10/data_ssalzbe1/khchao/spliceAI-toolkit/models/spliceai-mane/model_10000nt.pt -d

# --test-dataset /home/kchao10/data_ssalzbe1/khchao/data/train_test_dataset_MANE/dataset_test.h5 \
