if [ ! -d "./logs" ]; then
    mkdir ./logs
fi

if [ ! -d "./logs/LongForecasting" ]; then
    mkdir ./logs/LongForecasting
fi
seq_len=96
model_name=MCTEM

root_path_name=./dataset/ETT-small
data_path_name=ETTh1.csv
model_id_name=ETTh1
data_name=ETTh1

# for pred_len in 96 192 336 720
# do
#     python -u run_longExp.py \
#       --random_seed $random_seed \
#       --is_training 1 \
#       --root_path $root_path_name \
#       --data_path $data_path_name \
#       --model_id $model_id_name_$seq_len'_'$pred_len \
#       --model $model_name \
#       --data $data_name \
#       --features M \
#       --seq_len $seq_len \
#       --pred_len $pred_len \
#       --enc_in 7 \
#       --e_layers 3 \
#       --n_heads 4 \
#       --d_model 16 \
#       --d_ff 128 \
#       --dropout 0.3\
#       --fc_dropout 0.3\
#       --head_dropout 0\
#       --patch_len 16\
#       --stride 8\
#       --des 'Exp' \
#       --train_epochs 30\
#       --itr 1 --batch_size 16 --learning_rate 0.0001 >logs/LongForecasting/$model_name'_'$model_id_name'_'$seq_len'_'$pred_len.log 
# done

# for e_layers in 1 2 3 4 5
# do 
for pred_len in 96 192 336 720
do
    python -u run.py \
      --is_training 1 \
      --root_path $root_path_name \
      --data_path $data_path_name \
      --model_id $model_id_name_$seq_len'_'$pred_len \
      --model $model_name \
      --data $data_name \
      --features M \
      --seq_len $seq_len \
      --pred_len $pred_len \
      --enc_in 7 \
      --e_layers 1 \
      --n_heads 4 \
      --d_model 32 \
      --d_ff 32 \
      --dropout 0.3\
      --fc_dropout 0.3\
      --des 'Exp' \
      --train_epochs 30 \
      --patience 5\
      --itr 1 --batch_size 32 --learning_rate 0.0001 
done
# done
