(alg, seed,
dataset, net, num_classes, num_labels,
port,
weight_decay,
depth, widen_factor,
)
| 28 | |
| 29 | |
| 30 | def create_base_config(alg, seed, |
| 31 | dataset, net, num_classes, num_labels, |
| 32 | port, |
| 33 | weight_decay, |
| 34 | depth, widen_factor, |
| 35 | |
| 36 | ): |
| 37 | cfg = {} |
| 38 | |
| 39 | # save config |
| 40 | cfg['save_dir'] = './saved_models' |
| 41 | cfg['save_name'] = None |
| 42 | cfg['resume'] = False |
| 43 | cfg['load_path'] = None |
| 44 | cfg['overwrite'] = True |
| 45 | cfg['use_tensorboard'] = True |
| 46 | |
| 47 | # algorithm config |
| 48 | cfg['epoch'] = 1 |
| 49 | cfg['num_train_iter'] = 2 ** 20 |
| 50 | cfg['num_eval_iter'] = 5000 |
| 51 | cfg['num_labels'] = num_labels |
| 52 | cfg['batch_size'] = 64 |
| 53 | cfg['eval_batch_size'] = 1024 |
| 54 | if alg == 'fixmatch': |
| 55 | cfg['hard_label'] = True |
| 56 | cfg['T'] = 0.5 |
| 57 | cfg['p_cutoff'] = 0.95 |
| 58 | cfg['ulb_loss_ratio'] = 1.0 |
| 59 | cfg['uratio'] = 7 |
| 60 | elif alg == 'flexmatch': |
| 61 | cfg['hard_label'] = True |
| 62 | cfg['T'] = 0.5 |
| 63 | cfg['p_cutoff'] = 0.95 |
| 64 | cfg['ulb_loss_ratio'] = 1.0 |
| 65 | cfg['uratio'] = 7 |
| 66 | elif alg == 'uda': |
| 67 | cfg['TSA_schedule'] = 'none' |
| 68 | cfg['T'] = 0.4 |
| 69 | cfg['p_cutoff'] = 0.8 |
| 70 | cfg['ulb_loss_ratio'] = 1.0 |
| 71 | cfg['uratio'] = 7 |
| 72 | elif alg == 'pseudolabel': |
| 73 | cfg['ulb_loss_ratio'] = 1.0 |
| 74 | cfg['uratio'] = 1 |
| 75 | elif alg == 'mixmatch': |
| 76 | cfg['uratio'] = 1 |
| 77 | cfg['alpha'] = 0.5 |
| 78 | cfg['T'] = 0.5 |
| 79 | cfg['ulb_loss_ratio'] = 100 |
| 80 | cfg['ramp_up'] = 0.4 |
| 81 | elif alg == 'remixmatch': |
| 82 | cfg['alpha'] = 0.75 |
| 83 | cfg['T'] = 0.5 |
| 84 | cfg['ulb_loss_ratio'] = 1.0 |
| 85 | cfg['w_kl'] = 0.5 |
| 86 | cfg['w_match'] = 1.5 |
| 87 | cfg['w_rot'] = 0.5 |
no outgoing calls
no test coverage detected