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betas parameter in Adam shall not be integers #21

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4 changes: 2 additions & 2 deletions train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,8 +156,8 @@ def main(**kwargs):
c.G_kwargs = dnnlib.EasyDict(class_name='training.networks.Generator')
c.D_kwargs = dnnlib.EasyDict(class_name='training.networks.Discriminator')

c.G_opt_kwargs = dnnlib.EasyDict(class_name='torch.optim.Adam', betas=[0,0], eps=1e-8)
c.D_opt_kwargs = dnnlib.EasyDict(class_name='torch.optim.Adam', betas=[0,0], eps=1e-8)
c.G_opt_kwargs = dnnlib.EasyDict(class_name='torch.optim.Adam', betas=[0.0, 0.0], eps=1e-8)
c.D_opt_kwargs = dnnlib.EasyDict(class_name='torch.optim.Adam', betas=[0.0, 0.0], eps=1e-8)

c.loss_kwargs = dnnlib.EasyDict(class_name='training.loss.R3GANLoss')
c.data_loader_kwargs = dnnlib.EasyDict(pin_memory=True, prefetch_factor=2)
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2 changes: 1 addition & 1 deletion training/training_loop.py
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Expand Up @@ -328,7 +328,7 @@ def training_loop(
# Update weights.
for g in phase.opt.param_groups:
g['lr'] = cur_lr
g['betas'] = (0, cur_beta2)
g['betas'] = (0.0, cur_beta2)

with torch.autograd.profiler.record_function(phase.name + '_opt'):
params = [param for param in phase.module.parameters() if param.grad is not None]
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