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export CUDA_VISIBLE_DEVICES=0
model_name=PatchTST
for aug in jitter scaling permutation magwarp timewarp windowslice windowwarp rotation spawner dtwwarp shapedtwwarp discdtw discsdtw
do
for pred_len in 96 192 336 720
do
echo using augmentation: ${aug}
python -u run.py \
--task_name long_term_forecast \
--is_training 1 \
--root_path ./dataset/exchange_rate/ \
--data_path exchange_rate.csv \
--model_id Exchange_96_${pred_len} \
--model $model_name \
--data custom \
--features M \
--seq_len 96 \
--label_len 48 \
--pred_len ${pred_len} \
--e_layers 2 \
--d_layers 1 \
--factor 3 \
--enc_in 8 \
--dec_in 8 \
--c_out 8 \
--des 'Exp' \
--itr 1 \
--augmentation_ratio 1 \
--${aug}
done
done |