96 lines
1.8 KiB
Bash
96 lines
1.8 KiB
Bash
export CUDA_VISIBLE_DEVICES=2
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model_name=Chronos2
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seq_len=2048
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for pred_len in 96 192 336 720
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do
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python -u run.py \
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--task_name zero_shot_forecast \
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--is_training 0 \
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--root_path ./dataset/ETT-small/ \
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--data_path ETTh1.csv \
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--model_id ETTh1_$seq_len'_'$pred_len \
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--model $model_name \
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--data ETTh1 \
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--features M \
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--seq_len $seq_len \
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--pred_len $pred_len \
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--seg_len 24 \
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--enc_in 7 \
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--d_model 512 \
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--dropout 0.5 \
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--learning_rate 0.0001 \
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--des 'Exp' \
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--itr 1
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done
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for pred_len in 96 192 336 720
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do
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python -u run.py \
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--task_name zero_shot_forecast \
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--is_training 0 \
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--root_path ./dataset/ETT-small/ \
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--data_path ETTh2.csv \
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--model_id ETTh2_$seq_len'_'$pred_len \
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--model $model_name \
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--data ETTh2 \
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--features M \
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--seq_len $seq_len \
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--pred_len $pred_len \
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--seg_len 24 \
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--enc_in 7 \
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--d_model 256 \
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--dropout 0.5 \
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--learning_rate 0.0001 \
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--des 'Exp' \
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--itr 1
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done
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for pred_len in 192 336 720
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do
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python -u run.py \
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--task_name zero_shot_forecast \
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--is_training 0 \
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--root_path ./dataset/ETT-small/ \
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--data_path ETTm1.csv \
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--model_id ETTm1_$seq_len'_'$pred_len \
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--model $model_name \
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--data ETTm1 \
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--features M \
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--seq_len $seq_len \
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--pred_len $pred_len \
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--seg_len 24 \
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--enc_in 7 \
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--d_model 512 \
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--dropout 0.5 \
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--learning_rate 0.0001 \
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--des 'Exp' \
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--itr 1
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done
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for pred_len in 96 192 336 720
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do
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python -u run.py \
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--task_name zero_shot_forecast \
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--is_training 0 \
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--root_path ./dataset/ETT-small/ \
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--data_path ETTm2.csv \
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--model_id ETTm2_$seq_len'_'$pred_len \
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--model $model_name \
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--data ETTm2 \
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--features M \
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--seq_len $seq_len \
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--pred_len $pred_len \
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--seg_len 24 \
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--enc_in 7 \
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--d_model 512 \
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--dropout 0.5 \
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--learning_rate 0.0001 \
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--des 'Exp' \
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--itr 1
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done |