table2.sh
3.49 KB
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
#!/usr/bin/env sh
# DEFINE
DATA_ROOT_PATH=""
DEVICE="cuda"
############################## Table 2 #########################################
#### This commands Assumes that you have computed the best models for the architecture
#### or table 1 commands are already run
#### We show commands for k=2,
#### for other values of k just modify the frame_keep_fraction parameter
#### k=2 -> 0.5
#### k=4 -> 0.25
#### k=5 -> 0.2
#### k=10 -> 0.1
################################################################################
# 3d cnn with 50% frames (k=2), with imputation
python3 -m src.scripts.main -c config/config.py \
--exp_name 3d_cnn_eval_k=2_imputed \
-r /tmp \
--mode test \
--device $DEVICE --wandb.use 0 \
--model.arch.file src/arch/brain_age_3d.py \
--data.root_path "$DATA_ROOT_PATH" \
--data.frame_keep_style ordered --data.frame_keep_fraction 0.5 \
--data.impute fill \
--statefile result/3d_cnn/run_0001/best_model.pt
# 2d lstm with 50% frames (k=2), without imputation
python3 -m src.scripts.main -c config/config.py \
--exp_name 2d_slice_lstm_eval_k=2 \
-r /tmp \
--mode test \
--device $DEVICE --wandb.use 0 \
--model.arch.file src/arch/brain_age_slice_lstm.py \
--data.root_path "$DATA_ROOT_PATH" \
--data.frame_keep_style ordered --data.frame_keep_fraction 0.5 \
--data.impute drop \
--statefile result/2d_slice_lstm/run_0001/best_model.pt
# 2d lstm with 50% frames (k=2), with imputation
python3 -m src.scripts.main -c config/config.py \
--exp_name 2d_slice_lstm_eval_k=2_imputed \
-r /tmp \
--mode test \
--device $DEVICE --wandb.use 0 \
--model.arch.file src/arch/brain_age_slice_lstm.py \
--data.root_path "$DATA_ROOT_PATH" \
--data.frame_keep_style ordered --data.frame_keep_fraction 0.5 \
--data.impute fill \
--statefile result/2d_slice_lstm/run_0001/best_model.pt
# 2D-slice-attention with 50% frames (k=2), without imputation
python3 -m src.scripts.main -c config/config.py \
--exp_name 2d_slice_attention_eval_k=2 \
-r /tmp \
--mode test \
--device $DEVICE --wandb.use 0 \
--model.arch.file src/arch/brain_age_slice_set.py \
--model.arch.attn_dim 32 --model.arch.attn_num_heads 1 \
--model.arch.attn_drop 1 --model.arch.agg_fn "attention" \
--data.root_path "$DATA_ROOT_PATH" \
--data.frame_keep_style ordered --data.frame_keep_fraction 0.5 \
--data.impute drop \
--statefile result/2d_slice_attention/run_0001/best_model.pt
# 2D-slice-mean with 50% frames (k=2), without imputation
python3 -m src.scripts.main -c config/config.py \
--exp_name 2d_slice_mean_eval_k=2 \
-r /tmp \
--mode test \
--device $DEVICE --wandb.use 0 \
--model.arch.file src/arch/brain_age_slice_set.py \
--model.arch.attn_dim 32 --model.arch.attn_num_heads 1 \
--model.arch.attn_drop 1 --model.arch.agg_fn "mean" \
--data.root_path "$DATA_ROOT_PATH" \
--data.frame_keep_style ordered --data.frame_keep_fraction 0.5 \
--data.impute drop \
--statefile result/2d_slice_attention/run_0001/best_model.pt
# 2D-slice-max with 50% frames (k=2), without imputation
python3 -m src.scripts.main -c config/config.py \
--exp_name 2d_slice_max_eval_k=2 \
-r /tmp \
--mode test \
--device $DEVICE --wandb.use 0 \
--model.arch.file src/arch/brain_age_slice_set.py \
--model.arch.attn_dim 32 --model.arch.attn_num_heads 1 \
--model.arch.attn_drop 1 --model.arch.agg_fn "max" \
--data.root_path "$DATA_ROOT_PATH" \
--data.frame_keep_style ordered --data.frame_keep_fraction 0.5 \
--data.impute drop \
--statefile result/2d_slice_attention/run_0001/best_model.pt