Aquila-Consortium/map2map
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Update slurm script to include adversary model

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This commit is contained in:
Yin Li 2020-01-21 12:44:46 -05:00
parent 94ce018cb8
commit 6e06682751
5 changed files with 23 additions and 19 deletions
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6
map2map/args.py
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@ -62,20 +62,20 @@ def add_train_args(parser):
parser.add_argument('--cgan', action='store_true', parser.add_argument('--cgan', action='store_true',
help='enable conditional GAN') help='enable conditional GAN')
parser.add_argument('--epochs', default=128, type=int,
help='total number of epochs to run')
parser.add_argument('--optimizer', default='Adam', type=str, parser.add_argument('--optimizer', default='Adam', type=str,
help='optimizer from torch.optim') help='optimizer from torch.optim')
parser.add_argument('--lr', default=0.001, type=float, parser.add_argument('--lr', default=0.001, type=float,
help='initial learning rate') help='initial learning rate')
# parser.add_argument('--momentum', default=0.9, type=float, # parser.add_argument('--momentum', default=0.9, type=float,
# help='momentum') # help='momentum')
parser.add_argument('--weight-decay', default=0., type=float, parser.add_argument('--weight-decay', default=0, type=float,
help='weight decay') help='weight decay')
parser.add_argument('--adv-lr', type=float, parser.add_argument('--adv-lr', type=float,
help='initial adversary learning rate') help='initial adversary learning rate')
parser.add_argument('--adv-weight-decay', type=float, parser.add_argument('--adv-weight-decay', type=float,
help='adversary weight decay') help='adversary weight decay')
parser.add_argument('--epochs', default=128, type=int,
help='total number of epochs to run')
parser.add_argument('--seed', default=42, type=int, parser.add_argument('--seed', default=42, type=int,
help='seed for initializing training') help='seed for initializing training')

6
scripts/dis2dis-test.slurm
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@ -13,11 +13,11 @@
hostname; pwd; date hostname; pwd; date
module load gcc python3 #module load gcc python3
source $HOME/anaconda/bin/activate torch
export OMP_NUM_THREADS=$SLURM_CPUS_ON_NODE export OMP_NUM_THREADS=$SLURM_CPUS_ON_NODE
echo OMP_NUM_THREADS = $OMP_NUM_THREADS
data_root_dir="/mnt/ceph/users/yinli/Quijote" data_root_dir="/mnt/ceph/users/yinli/Quijote"
@ -35,7 +35,7 @@ tgt_files="$files"
m2m.py test \ m2m.py test \
--test-in-patterns "$data_root_dir/$in_dir/$test_dirs/$in_files" \ --test-in-patterns "$data_root_dir/$in_dir/$test_dirs/$in_files" \
--test-tgt-patterns "$data_root_dir/$tgt_dir/$test_dirs/$tgt_files" \ --test-tgt-patterns "$data_root_dir/$tgt_dir/$test_dirs/$tgt_files" \
--norms cosmology.dis --crop 256 --pad 42 \ --norms cosmology.dis --crop 256 --pad 20 \
--model VNet \ --model VNet \
--load-state best_model.pth \ --load-state best_model.pth \
--batches 1 --loader-workers 0 \ --batches 1 --loader-workers 0 \

12
scripts/dis2dis.slurm
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@ -14,11 +14,12 @@
hostname; pwd; date hostname; pwd; date
module load gcc python3 #module load gcc python3
source $HOME/anaconda/bin/activate torch
export MASTER_ADDR=$HOSTNAME export MASTER_ADDR=$HOSTNAME
export MASTER_PORT=8888 export MASTER_PORT=60606
data_root_dir="/mnt/ceph/users/yinli/Quijote" data_root_dir="/mnt/ceph/users/yinli/Quijote"
@ -39,9 +40,10 @@ srun m2m.py train \
--train-tgt-patterns "$data_root_dir/$tgt_dir/$train_dirs/$tgt_files" \ --train-tgt-patterns "$data_root_dir/$tgt_dir/$train_dirs/$tgt_files" \
--val-in-patterns "$data_root_dir/$in_dir/$val_dirs/$in_files" \ --val-in-patterns "$data_root_dir/$in_dir/$val_dirs/$in_files" \
--val-tgt-patterns "$data_root_dir/$tgt_dir/$val_dirs/$tgt_files" \ --val-tgt-patterns "$data_root_dir/$tgt_dir/$val_dirs/$tgt_files" \
--norms cosmology.dis --augment --crop 100 --pad 42 \ --norms cosmology.dis --augment --crop 128 --pad 20 \
--model VNet \ --model VNet --adv-model UNet --cgan \
--epochs 128 --lr 0.001 --batches 1 --loader-workers 0 --seed $RANDOM \ --lr 0.0001 --adv-lr 0.0004 --batches 1 --loader-workers 0 \
--epochs 128 --seed $RANDOM \
--cache --div-data --cache --div-data
# --load-state checkpoint.pth \ # --load-state checkpoint.pth \

6
scripts/vel2vel-test.slurm
View File

@ -13,11 +13,11 @@
hostname; pwd; date hostname; pwd; date
module load gcc python3 #module load gcc python3
source $HOME/anaconda/bin/activate torch
export OMP_NUM_THREADS=$SLURM_CPUS_ON_NODE export OMP_NUM_THREADS=$SLURM_CPUS_ON_NODE
echo OMP_NUM_THREADS = $OMP_NUM_THREADS
data_root_dir="/mnt/ceph/users/yinli/Quijote" data_root_dir="/mnt/ceph/users/yinli/Quijote"
@ -35,7 +35,7 @@ tgt_files="$files"
m2m.py test \ m2m.py test \
--test-in-patterns "$data_root_dir/$in_dir/$test_dirs/$in_files" \ --test-in-patterns "$data_root_dir/$in_dir/$test_dirs/$in_files" \
--test-tgt-patterns "$data_root_dir/$tgt_dir/$test_dirs/$tgt_files" \ --test-tgt-patterns "$data_root_dir/$tgt_dir/$test_dirs/$tgt_files" \
--norms cosmology.vel --crop 256 --pad 42 \ --norms cosmology.vel --crop 256 --pad 20 \
--model VNet \ --model VNet \
--load-state best_model.pth \ --load-state best_model.pth \
--batches 1 --loader-workers 0 \ --batches 1 --loader-workers 0 \

12
scripts/vel2vel.slurm
View File

@ -14,11 +14,12 @@
hostname; pwd; date hostname; pwd; date
module load gcc python3 #module load gcc python3
source $HOME/anaconda/bin/activate torch
export MASTER_ADDR=$HOSTNAME export MASTER_ADDR=$HOSTNAME
export MASTER_PORT=8888 export MASTER_PORT=60606
data_root_dir="/mnt/ceph/users/yinli/Quijote" data_root_dir="/mnt/ceph/users/yinli/Quijote"
@ -39,9 +40,10 @@ srun m2m.py train \
--train-tgt-patterns "$data_root_dir/$tgt_dir/$train_dirs/$tgt_files" \ --train-tgt-patterns "$data_root_dir/$tgt_dir/$train_dirs/$tgt_files" \
--val-in-patterns "$data_root_dir/$in_dir/$val_dirs/$in_files" \ --val-in-patterns "$data_root_dir/$in_dir/$val_dirs/$in_files" \
--val-tgt-patterns "$data_root_dir/$tgt_dir/$val_dirs/$tgt_files" \ --val-tgt-patterns "$data_root_dir/$tgt_dir/$val_dirs/$tgt_files" \
--norms cosmology.vel --augment --crop 100 --pad 42 \ --norms cosmology.vel --augment --crop 128 --pad 20 \
--model VNet \ --model VNet --adv-model UNet --cgan \
--epochs 128 --lr 0.001 --batches 1 --loader-workers 0 --seed $RANDOM \ --lr 0.0001 --adv-lr 0.0004 --batches 1 --loader-workers 0 \
--epochs 128 --seed $RANDOM \
--cache --div-data --cache --div-data
# --load-state checkpoint.pth \ # --load-state checkpoint.pth \