⬅ configs/algorithm.py source

1 algorithm_defaults = {
2 'ERM': {
3 'train_loader': 'standard',
4 'uniform_over_groups': False,
5 'eval_loader': 'standard',
6 },
7 'groupDRO': {
8 'train_loader': 'standard',
9 'uniform_over_groups': True,
10 'distinct_groups': True,
11 'eval_loader': 'standard',
12 'group_dro_step_size': 0.01,
13 },
14 'deepCORAL': {
15 'train_loader': 'group',
16 'uniform_over_groups': True,
17 'distinct_groups': True,
18 'eval_loader': 'standard',
19 'coral_penalty_weight': 1.,
20 },
21 'IRM': {
22 'train_loader': 'group',
23 'uniform_over_groups': True,
24 'distinct_groups': True,
25 'eval_loader': 'standard',
26 'irm_lambda': 1.,
27 'irm_penalty_anneal_iters': 500,
28 },
29 'FLAG': {
30 'train_loader': 'standard',
31 'uniform_over_groups': False,
32 'eval_loader': 'standard',
33 'flag_step_size': 1e-2
34 },
35 'GCL': {
36 'train_loader': 'standard',
37 'uniform_over_groups': False,
38 'eval_loader': 'standard',
39 'use_cl': False,
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40 'gcl_aug_prob': 0.5, #0.0 should be equiv to ERM, as aug is never applied, 1.0 is GCL setting where orig data is never seen
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41 'aug_type': 'random', #'node_drop','edge_perm','random' can only use a single aug_type currently, or random choice of them
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42 'gcl_aug_ratio': 0.1 # 0.0 should be equiv to ERM, as each graph is unchanged, 0.2 is GCL paper default
43 },
44 'GSN': {
45 'train_loader': 'standard',
46 'uniform_over_groups': False,
47 'eval_loader': 'standard',
48 },
49 'DANN': {
50 'train_loader': 'group',
51 'uniform_over_groups': True,
52 'distinct_groups': True,
53 'eval_loader': 'standard',
54 'dann_lambda': 0.1
55 },
56 'CDANN': {
57 'train_loader': 'group',
58 'uniform_over_groups': True,
59 'distinct_groups': True,
60 'eval_loader': 'standard',
61 'dann_lambda': 1.
62 },
63 'DANN-G': {
64 'train_loader': 'group',
65 'uniform_over_groups': True,
66 'distinct_groups': True,
67 'eval_loader': 'standard',
68 'dann_lambda': 0.1
69 },
70 'MLDG': {
71 'train_loader': 'group',
72 'uniform_over_groups': True,
73 'distinct_groups': True,
74 'eval_loader': 'standard',
75 'mldg_beta': 0.1
76 },
77 }