Implements Adam algorithm.
It has been proposed in Adam: A Method for Stochastic Optimization.
optim_adam( params, lr = 0.001, betas = c(0.9, 0.999), eps = 1e-08, weight_decay = 0, amsgrad = FALSE )
params |
(iterable): iterable of parameters to optimize or dicts defining parameter groups |
lr |
(float, optional): learning rate (default: 1e-3) |
betas |
( |
eps |
(float, optional): term added to the denominator to improve numerical stability (default: 1e-8) |
weight_decay |
(float, optional): weight decay (L2 penalty) (default: 0) |
amsgrad |
(boolean, optional): whether to use the AMSGrad variant of this algorithm from the paper On the Convergence of Adam and Beyond (default: FALSE) |
if (torch_is_installed()) {
## Not run:
optimizer <- optim_adam(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.