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Add a gamma parameter in CycleGAN train_options.py #732

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Add a gamma parameter in CycleGAN train_options.py #732

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2 changes: 1 addition & 1 deletion models/networks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,7 @@ def lambda_rule(epoch):
return lr_l
scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lambda_rule)
elif opt.lr_policy == 'step':
scheduler = lr_scheduler.StepLR(optimizer, step_size=opt.lr_decay_iters, gamma=0.1)
scheduler = lr_scheduler.StepLR(optimizer, step_size=opt.lr_decay_iters, gamma=opt.lr_gamma)
elif opt.lr_policy == 'plateau':
scheduler = lr_scheduler.ReduceLROnPlateau(optimizer, mode='min', factor=0.2, threshold=0.01, patience=5)
elif opt.lr_policy == 'cosine':
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1 change: 1 addition & 0 deletions options/train_options.py
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Expand Up @@ -35,6 +35,7 @@ def initialize(self, parser):
parser.add_argument('--pool_size', type=int, default=50, help='the size of image buffer that stores previously generated images')
parser.add_argument('--lr_policy', type=str, default='linear', help='learning rate policy. [linear | step | plateau | cosine]')
parser.add_argument('--lr_decay_iters', type=int, default=50, help='multiply by a gamma every lr_decay_iters iterations')
parser.add_argument('--lr_gamma', type=float, default=0.1, help='gamma value used with lr_decay_iters')

self.isTrain = True
return parser