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Make pytorch evaluate run without optimizer in checkpoint

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This commit is contained in:
Cody A. Coleman 2018-01-17 20:40:46 -08:00
parent 339261c19f
commit b7f332f460
1 changed files with 3 additions and 2 deletions
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5
pytorch/CIFAR10/benchmark/cifar10/train.py
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@ -210,7 +210,8 @@ def train(dataset_dir, checkpoint, restore, tracking, cuda, epochs,
assert restored_state['arch'] == arch assert restored_state['arch'] == arch
model.load_state_dict(restored_state['model']) model.load_state_dict(restored_state['model'])
optimizer.load_state_dict(restored_state['optimizer']) if 'optimizer' in restored_state:
optimizer.load_state_dict(restored_state['optimizer'])
if not isinstance(optimizer, YFOptimizer): if not isinstance(optimizer, YFOptimizer):
for group in optimizer.param_groups: for group in optimizer.param_groups:
group['lr'] = learning_rate group['lr'] = learning_rate
@ -225,7 +226,7 @@ def train(dataset_dir, checkpoint, restore, tracking, cuda, epochs,
print('Starting accuracy is {}'.format(best_accuracy)) print('Starting accuracy is {}'.format(best_accuracy))
if not os.path.exists(run_dir): if not os.path.exists(run_dir) and run_dir != '':
os.makedirs(run_dir) os.makedirs(run_dir)
utils.save_config(config, run_dir) utils.save_config(config, run_dir)