-
Notifications
You must be signed in to change notification settings - Fork 5
/
exchange_rate.sh
executable file
·164 lines (153 loc) · 3.46 KB
/
exchange_rate.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
if [ ! -d "./logs" ]; then
mkdir ./logs
fi
>logs/exchange_rate.log
gpu=0
for pred_len in 96 192 336 720
do
model=MambaFormer
label_len=192
seq_len=$label_len
python -u run_exp.py \
--is_training 1 \
--root_path ./dataset/exchange'_'rate \
--data_path exchange'_'rate.csv \
--model_id exchange'_'rate'_'$label_len'_'$pred_len \
--model $model \
--data custom \
--features M \
--seq_len $seq_len \
--label_len $label_len \
--pred_len $pred_len \
--embed_type 2 \
--d_state 16 \
--d_conv 4 \
--d_layers 1 \
--dec_in 8 \
--c_out 8 \
--batch_size 64 \
--train_epochs 10 \
--learning_rate 0.001 \
--lradj type1 \
--des 'Exp' \
--gpu $gpu \
--itr 1 >>logs/exchange'_'rate.log
done
for pred_len in 96 192 336 720
do
model=AttMam
label_len=192
seq_len=$label_len
python -u run_exp.py \
--is_training 1 \
--root_path ./dataset/exchange'_'rate \
--data_path exchange'_'rate.csv \
--model_id exchange'_'rate'_'$label_len'_'$pred_len \
--model $model \
--data custom \
--features M \
--seq_len $seq_len \
--label_len $label_len \
--pred_len $pred_len \
--embed_type 1 \
--d_state 16 \
--d_conv 4 \
--d_layers 1 \
--dec_in 8 \
--c_out 8 \
--batch_size 64 \
--train_epochs 10 \
--learning_rate 0.001 \
--lradj type1 \
--des 'Exp' \
--gpu $gpu \
--itr 1 >>logs/exchange'_'rate.log
done
for pred_len in 96 192 336 720
do
model=MamAtt
label_len=192
seq_len=$label_len
python -u run_exp.py \
--is_training 1 \
--root_path ./dataset/exchange'_'rate \
--data_path exchange'_'rate.csv \
--model_id exchange'_'rate'_'$label_len'_'$pred_len \
--model $model \
--data custom \
--features M \
--seq_len $seq_len \
--label_len $label_len \
--pred_len $pred_len \
--embed_type 2 \
--d_state 16 \
--d_conv 4 \
--d_layers 1 \
--dec_in 8 \
--c_out 8 \
--batch_size 64 \
--train_epochs 10 \
--learning_rate 0.001 \
--lradj type1 \
--des 'Exp' \
--gpu $gpu \
--itr 1 >>logs/exchange'_'rate.log
done
for pred_len in 96 192 336 720
do
model=Mamba
label_len=192
seq_len=$label_len
python -u run_exp.py \
--is_training 1 \
--root_path ./dataset/exchange'_'rate \
--data_path exchange'_'rate.csv \
--model_id exchange'_'rate'_'$label_len'_'$pred_len \
--model $model \
--data custom \
--features M \
--seq_len $seq_len \
--label_len $label_len \
--pred_len $pred_len \
--embed_type 2 \
--d_state 16 \
--d_conv 4 \
--d_layers 1 \
--dec_in 8 \
--c_out 8 \
--batch_size 64 \
--train_epochs 10 \
--learning_rate 0.001 \
--lradj type1 \
--des 'Exp' \
--gpu $gpu \
--itr 1 >>logs/exchange'_'rate.log
done
for pred_len in 96 192 336 720
do
model=DecoderOnly
label_len=192
seq_len=$label_len
python -u run_exp.py \
--is_training 1 \
--root_path ./dataset/exchange'_'rate \
--data_path exchange'_'rate.csv \
--model_id exchange'_'rate'_'$label_len'_'$pred_len \
--model $model \
--data custom \
--features M \
--seq_len $seq_len \
--label_len $label_len \
--pred_len $pred_len \
--embed_type 1 \
--d_layers 1 \
--dec_in 8 \
--c_out 8 \
--batch_size 64 \
--train_epochs 10 \
--learning_rate 0.001 \
--lradj type1 \
--des 'Exp' \
--gpu $gpu \
--itr 1 >>logs/exchange'_'rate.log
done