diff options
| author | junyanz <junyanz@berkeley.edu> | 2017-10-19 21:14:48 -0700 |
|---|---|---|
| committer | junyanz <junyanz@berkeley.edu> | 2017-10-19 21:14:48 -0700 |
| commit | 9d1bc76e6a4f791a25db1179c7c2b4c62a8d55cd (patch) | |
| tree | f8a3ad91d77f8ee2a1e377621ff76e15b3e1ec98 | |
| parent | 2a344ccd6f80ce0435d2c58ccfd94c76dd423b1a (diff) | |
fix learning rate
| -rw-r--r-- | models/networks.py | 5 |
1 files changed, 2 insertions, 3 deletions
diff --git a/models/networks.py b/models/networks.py index 19169c5..51e3f25 100644 --- a/models/networks.py +++ b/models/networks.py @@ -10,7 +10,6 @@ import numpy as np ############################################################################### - def weights_init_normal(m): classname = m.__class__.__name__ # print(classname) @@ -87,8 +86,8 @@ def get_norm_layer(norm_type='instance'): def get_scheduler(optimizer, opt): if opt.lr_policy == 'lambda': - def lambda_rule(epoch): # epoch ranges from [1, opt.niter+opt.niter_decay] - lr_l = 1.0 - max(0, epoch - opt.niter + 1) / float(opt.niter_decay + 1) + def lambda_rule(epoch): + lr_l = 1.0 - max(0, epoch + 1 + opt.epoch_count - opt.niter) / float(opt.niter_decay + 1) return lr_l scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lambda_rule) elif opt.lr_policy == 'step': |