Averaged Stochastic Gradient Descent optimizer
optim_asgd( params, lr = 0.01, lambda = 1e-04, alpha = 0.75, t0 = 1e+06, weight_decay = 0 )
params |
(iterable): iterable of parameters to optimize or lists defining parameter groups |
lr |
(float): learning rate |
lambda |
(float, optional): decay term (default: 1e-4) |
alpha |
(float, optional): power for eta update (default: 0.75) |
t0 |
(float, optional): point at which to start averaging (default: 1e6) |
weight_decay |
(float, optional): weight decay (L2 penalty) (default: 0) |
if (torch_is_installed()) {
## Not run:
optimizer <- optim_asgd(model$parameters(), lr=0.1)
optimizer$zero_grad()
loss_fn(model(input), target)$backward()
optimizer$step()
## End(Not run)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.