-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathrunner2.sh
111 lines (93 loc) · 3.85 KB
/
runner2.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
#!/bin/bash
########################################################################
# less pre-training data
########################################################################
# p=0
# python -m src.finetune config/less_pretrain.yaml \
# base.name=less_pretrain${p} \
# pretrain.params.label_percentage=${p} \
# finetune.load_path=None
# for p in `seq 20 20 100`
# for p in 80
# do
# python -m src.pretrain config/less_pretrain.yaml \
# base.name=less_pretrain${p} \
# pretrain.params.label_percentage=${p}
# python -m src.finetune config/less_pretrain.yaml \
# base.name=less_pretrain${p} \
# pretrain.params.label_percentage=${p} \
# finetne.load_path='${base.save_root}/less_pretrain'${p}'/pretrain/epoch=10.pt'
# done
# find ../checkpoints/ -name 'epoch*' | grep -v 'epoch=10' | xargs rm
# ########################################################################
# # pre-train with gap
# ########################################################################
# # for g in 0 100 10
# for g in 0
# do
# python -m src.pretrain config/gap.yaml \
# base.name=gap${g} \
# pretrain.params.gap=${g}
# python -m src.finetune config/gap.yaml \
# base.name=gap${g} \
# pretrain.params.gap=${g} \
# finetne.load_path='${base.save_root}/gap'${g}'/pretrain/epoch=10.pt'
# done
# find ../checkpoints/ -name 'epoch*' | grep -v 'epoch=10' | xargs rm
#################
# python -m src.pretrain config/selfsup_best.yaml
# python -m src.finetune config/selfsup_best.yaml
# find ../checkpoints/ -name 'epoch*' | grep -v 'epoch=10' | xargs rm
# ########################################################################
# # pre-train with o% overlap
# ########################################################################
# for o in 10 20 5 1 0
# do
# python -m src.pretrain config/gap.yaml \
# base.name=overlap${o} \
# pretrain.params.overlap=${o}
# python -m src.finetune config/gap.yaml \
# base.name=overlap${o} \
# pretrain.params.overlap=${o} \
# finetne.load_path='${base.save_root}/overlap'${o}'/pretrain/epoch=10.pt'
# done
# ########################################################################
# # finetune MLP on OVSD/BBC with avg(len(shots)) and evaluate each film
# ########################################################################
# # finetuned, n=21
# for idx in `seq 0 20`
# do
# python -m src.finetune config/ovsd_avg.yaml \
# base.name=ovsd_avg_finetune${idx} \
# finetune.aim_index=${idx} \
# finetune.load_path='../checkpoints/selfsup_best/finetune/epoch=10.pt'
# find ../checkpoints/ -name 'epoch*' | grep -v 'epoch=10' | xargs rm
# done
# # finetuned, n=21
# for idx in `seq 0 10`
# do
# for no in `seq 0 4`
# do
# python -m src.finetune config/bbc_avg.yaml \
# base.name=bbc${no}_avg_finetune${idx} \
# finetune.aim_index=${idx} \
# finetune.load_path='../checkpoints/selfsup_best/finetune/epoch=10.pt' \
# base.path.scene_path='${..data_root}/scene_annotation_'${no}'.pkl' \
# base.path.label_path='${..data_root}/label_dict_'${no}'.pkl'
# find ../checkpoints/ -name 'epoch*' | grep -v 'epoch=10' | xargs rm
# done
# done
# ########################################################################
# # filter false negtive pseudo boundaries
# ########################################################################
# # save prediction
# python -m src.predict config/selfsup_best.yaml \
# evaluate.test.vid_list=other_vids \
# evaluate.test.dataset=predict
# python -m src.pretrain config/filter_pseudo.yaml
# python -m src.finetune config/filter_pseudo.yaml
# find ../checkpoints/ -name 'epoch*' | grep -v 'epoch=10' | xargs rm
###############################
# echo 'shutdown after 60 seconds.'
# sleep 60
# shutdown