# CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.1 &

# CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.1 &

# CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.1 &


# # wait
# # echo "Done"


# CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.3 &

# CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.3 &

# CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.3 &


# # wait
# # echo "Done"

# CUDA_VISIBLE_DEVICES=3 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.7 &

# CUDA_VISIBLE_DEVICES=3 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.7 &

# CUDA_VISIBLE_DEVICES=3 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.7 &

# wait
# echo "Done"

# CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.4 &

# CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.4 &

# CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.4 &

# # wait
# # echo "Done"


# CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.8 &

# CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.8 &

# CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.8 


# CUDA_VISIBLE_DEVICES=3 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.5 &

# CUDA_VISIBLE_DEVICES=3 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.5 &

# CUDA_VISIBLE_DEVICES=3 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name PEMS-SF_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/PEMS-SF --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.5 


 

# # # wait
# # # echo "Done"



# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.1 &

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.1 &

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.1 &

# # wait
# # echo "Done"

 
# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.5 &

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.5 &

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.5 &

# # wait
# # echo "Done"




for be in 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
do
    CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta $be &

    CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta $be &


    CUDA_VISIBLE_DEVICES=2 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta $be & 
    wait 
    echo "Continue"
done




 
# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 1.2 &

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 1.2 &

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name UWaveGestureLibrary_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/UWaveGestureLibrary --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 1.2 &

# # wait
# # echo "Done"
 
# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.1

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.1

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.1



# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 0.5

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 0.5

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 0.5



# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 6 --beta 1.2

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 666 --beta 1.2

# # CUDA_VISIBLE_DEVICES=1 python main.py --output_dir /tanData/tam/output_tst --comment "classification for flowformer" --name SelfRegulationSCP2_fromScratch --records_file Classification_records.xls --data_dir /tanData/tam/Multivariate_ts/SelfRegulationSCP2 --data_class tsra --pattern TRAIN --val_pattern TEST --epochs 100 --lr 0.001 --batch_size 16 --optimizer RAdam  --pos_encoding learnable  --task classification  --key_metric accuracy --seed 1608 --beta 1.2
