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| author | junyanz <junyanz@berkeley.edu> | 2017-11-04 02:27:18 -0700 |
|---|---|---|
| committer | junyanz <junyanz@berkeley.edu> | 2017-11-04 02:27:18 -0700 |
| commit | 6b8e96c4bbd73a1e1d4e126d795a26fd0dae983c (patch) | |
| tree | 67072a0442b705b5d5b29840f4b41e13af1d4597 /models/base_model.py | |
| parent | 5f858eb70a3c110238f74a592bad0e7be601c539 (diff) | |
add update_html_freq flag
Diffstat (limited to 'models/base_model.py')
| -rw-r--r-- | models/base_model.py | 3 |
1 files changed, 2 insertions, 1 deletions
diff --git a/models/base_model.py b/models/base_model.py index d62d189..646a014 100644 --- a/models/base_model.py +++ b/models/base_model.py @@ -44,13 +44,14 @@ class BaseModel(): save_path = os.path.join(self.save_dir, save_filename) torch.save(network.cpu().state_dict(), save_path) if len(gpu_ids) and torch.cuda.is_available(): - network.cuda(device_id=gpu_ids[0]) # network.cuda(device=gpu_ids[0]) for the latest version. + network.cuda(device_id=gpu_ids[0]) # network.cuda(device=gpu_ids[0]) for the latest version. # helper loading function that can be used by subclasses def load_network(self, network, network_label, epoch_label): save_filename = '%s_net_%s.pth' % (epoch_label, network_label) save_path = os.path.join(self.save_dir, save_filename) network.load_state_dict(torch.load(save_path)) + # update learning rate (called once every epoch) def update_learning_rate(self): for scheduler in self.schedulers: |