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#export CUDA_VISIBLE_DEVICES=0
model_name=TimeMixer
seq_len=96
e_layers=3
down_sampling_layers=3
down_sampling_window=2
learning_rate=0.01
d_model=32
d_ff=64
batch_size=8
python -u run.py \
--task_name long_term_forecast \
--is_training 1 \
--root_path ./dataset/traffic/ \
--data_path traffic.csv \
--model_id Traffic_$seq_len'_'96 \
--model $model_name \
--data custom \
--features M \
--seq_len $seq_len \
--label_len 0 \
--pred_len 96 \
--e_layers $e_layers \
--d_layers 1 \
--factor 3 \
--enc_in 862 \
--dec_in 862 \
--c_out 862 \
--des 'Exp' \
--itr 1 \
--d_model $d_model \
--d_ff $d_ff \
--batch_size $batch_size \
--learning_rate $learning_rate \
--down_sampling_layers $down_sampling_layers \
--down_sampling_method avg \
--down_sampling_window $down_sampling_window
python -u run.py \
--task_name long_term_forecast \
--is_training 1 \
--root_path ./dataset/traffic/ \
--data_path traffic.csv \
--model_id Traffic_$seq_len'_'192 \
--model $model_name \
--data custom \
--features M \
--seq_len $seq_len \
--label_len 0 \
--pred_len 192 \
--e_layers $e_layers \
--d_layers 1 \
--factor 3 \
--enc_in 862 \
--dec_in 862 \
--c_out 862 \
--des 'Exp' \
--itr 1 \
--d_model $d_model \
--d_ff $d_ff \
--batch_size $batch_size \
--learning_rate $learning_rate \
--down_sampling_layers $down_sampling_layers \
--down_sampling_method avg \
--down_sampling_window $down_sampling_window
python -u run.py \
--task_name long_term_forecast \
--is_training 1 \
--root_path ./dataset/traffic/ \
--data_path traffic.csv \
--model_id Traffic_$seq_len'_'336 \
--model $model_name \
--data custom \
--features M \
--seq_len $seq_len \
--label_len 0 \
--pred_len 336 \
--e_layers $e_layers \
--d_layers 1 \
--factor 3 \
--enc_in 862 \
--dec_in 862 \
--c_out 862 \
--des 'Exp' \
--itr 1 \
--d_model $d_model \
--d_ff $d_ff \
--batch_size $batch_size \
--learning_rate $learning_rate \
--down_sampling_layers $down_sampling_layers \
--down_sampling_method avg \
--down_sampling_window $down_sampling_window
python -u run.py \
--task_name long_term_forecast \
--is_training 1 \
--root_path ./dataset/traffic/ \
--data_path traffic.csv \
--model_id Traffic_$seq_len'_'720 \
--model $model_name \
--data custom \
--features M \
--seq_len $seq_len \
--label_len 0 \
--pred_len 720 \
--e_layers $e_layers \
--d_layers 1 \
--factor 3 \
--enc_in 862 \
--dec_in 862 \
--c_out 862 \
--des 'Exp' \
--itr 1 \
--d_model $d_model \
--d_ff $d_ff \
--batch_size $batch_size \
--learning_rate $learning_rate \
--down_sampling_layers $down_sampling_layers \
--down_sampling_method avg \
--down_sampling_window $down_sampling_window |