map2map/scripts/srsgan.slurm

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#!/bin/bash
#SBATCH --job-name=srsgan
#SBATCH --output=%x-%j.out
#SBATCH --partition=rtx
##SBATCH --gres=gpu:4
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#SBATCH --exclusive
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=1
#SBATCH --time=2-00:00:00
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hostname; pwd; date
#module load gcc python3
source $HOME/anaconda3/bin/activate
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data_root_dir="/scratch1/06431/yueyingn/dmo-50MPC-train"
in_dir="low-resl"
tgt_dir="high-resl"
train_dirs="set[0-7]/output/PART_004"
#val_dirs="set4/output/PART_004"
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in_files_1="disp.npy"
in_files_2="vel.npy"
tgt_files_1="disp.npy"
tgt_files_2="vel.npy"
srun m2m.py train \
--train-in-patterns "$data_root_dir/$in_dir/$train_dirs/$in_files_1,$data_root_dir/$in_dir/$train_dirs/$in_files_2" \
--train-tgt-patterns "$data_root_dir/$tgt_dir/$train_dirs/$tgt_files_1,$data_root_dir/$tgt_dir/$train_dirs/$tgt_files_2" \
--in-norms cosmology.dis,cosmology.vel --tgt-norms cosmology.dis,cosmology.vel --augment --crop 88 --pad 20 --scale-factor 2 \
--model VNet --adv-model PatchGAN --cgan \
--lr 0.0001 --adv-lr 0.0004 --batches 1 --loader-workers 0 \
--epochs 1024 --seed $RANDOM \
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--cache --div-data
# --val-in-patterns "$data_root_dir/$in_dir/$val_dirs/$in_files_1,$data_root_dir/$in_dir/$val_dirs/$in_files_2" \
# --val-tgt-patterns "$data_root_dir/$tgt_dir/$val_dirs/$tgt_files_1,$data_root_dir/$tgt_dir/$val_dirs/$tgt_files_2" \
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date