147 lines
2.7 KiB
Bash
147 lines
2.7 KiB
Bash
export CUDA_VISIBLE_DEVICES=3
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model_name=FiLM
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python -u run.py \
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--task_name short_term_forecast \
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--is_training 1 \
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--root_path ./dataset/m4 \
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--seasonal_patterns 'Monthly' \
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--model_id m4_Monthly \
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--model $model_name \
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--data m4 \
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--features M \
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--e_layers 2 \
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--d_layers 1 \
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--factor 3 \
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--enc_in 1 \
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--dec_in 1 \
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--c_out 1 \
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--batch_size 16 \
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--d_model 32 \
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--d_ff 32 \
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--top_k 5 \
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--des 'Exp' \
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--itr 1 \
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--learning_rate 0.001 \
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--loss 'SMAPE'
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python -u run.py \
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--task_name short_term_forecast \
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--is_training 1 \
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--root_path ./dataset/m4 \
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--seasonal_patterns 'Yearly' \
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--model_id m4_Yearly \
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--model $model_name \
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--data m4 \
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--features M \
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--e_layers 2 \
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--d_layers 1 \
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--factor 3 \
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--enc_in 1 \
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--dec_in 1 \
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--c_out 1 \
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--batch_size 16 \
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--d_model 16 \
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--d_ff 32 \
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--top_k 5 \
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--des 'Exp' \
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--itr 1 \
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--learning_rate 0.001 \
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--loss 'SMAPE'
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python -u run.py \
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--task_name short_term_forecast \
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--is_training 1 \
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--root_path ./dataset/m4 \
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--seasonal_patterns 'Quarterly' \
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--model_id m4_Quarterly \
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--model $model_name \
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--data m4 \
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--features M \
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--e_layers 2 \
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--d_layers 1 \
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--factor 3 \
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--enc_in 1 \
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--dec_in 1 \
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--c_out 1 \
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--batch_size 16 \
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--d_model 64 \
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--d_ff 64 \
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--top_k 5 \
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--des 'Exp' \
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--itr 1 \
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--learning_rate 0.001 \
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--loss 'SMAPE'
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python -u run.py \
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--task_name short_term_forecast \
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--is_training 1 \
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--root_path ./dataset/m4 \
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--seasonal_patterns 'Daily' \
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--model_id m4_Daily \
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--model $model_name \
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--data m4 \
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--features M \
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--e_layers 2 \
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--d_layers 1 \
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--factor 3 \
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--enc_in 1 \
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--dec_in 1 \
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--c_out 1 \
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--batch_size 16 \
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--d_model 16 \
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--d_ff 16 \
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--top_k 5 \
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--des 'Exp' \
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--itr 1 \
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--learning_rate 0.001 \
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--loss 'SMAPE'
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python -u run.py \
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--task_name short_term_forecast \
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--is_training 1 \
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--root_path ./dataset/m4 \
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--seasonal_patterns 'Weekly' \
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--model_id m4_Weekly \
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--model $model_name \
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--data m4 \
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--features M \
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--e_layers 2 \
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--d_layers 1 \
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--factor 3 \
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--enc_in 1 \
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--dec_in 1 \
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--c_out 1 \
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--batch_size 16 \
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--d_model 32 \
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--d_ff 32 \
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--top_k 5 \
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--des 'Exp' \
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--itr 1 \
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--learning_rate 0.001 \
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--loss 'SMAPE'
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python -u run.py \
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--task_name short_term_forecast \
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--is_training 1 \
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--root_path ./dataset/m4 \
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--seasonal_patterns 'Hourly' \
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--model_id m4_Hourly \
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--model $model_name \
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--data m4 \
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--features M \
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--e_layers 2 \
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--d_layers 1 \
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--factor 3 \
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--enc_in 1 \
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--dec_in 1 \
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--c_out 1 \
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--batch_size 16 \
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--d_model 32 \
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--d_ff 32 \
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--top_k 5 \
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--des 'Exp' \
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--itr 1 \
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--learning_rate 0.001 \
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--loss 'SMAPE' |