optim_ignite_rmsprop {torch} | R Documentation |
LibTorch implementation of RMSprop
Description
Proposed by G. Hinton in his course.
Usage
optim_ignite_rmsprop(
params,
lr = 0.01,
alpha = 0.99,
eps = 1e-08,
weight_decay = 0,
momentum = 0,
centered = FALSE
)
Arguments
params |
(iterable): iterable of parameters to optimize or list defining parameter groups |
lr |
(float, optional): learning rate (default: 1e-2) |
alpha |
(float, optional): smoothing constant (default: 0.99) |
eps |
(float, optional): term added to the denominator to improve numerical stability (default: 1e-8) |
weight_decay |
optional weight decay penalty. (default: 0) |
momentum |
(float, optional): momentum factor (default: 0) |
centered |
(bool, optional) : if |
Fields and Methods
See OptimizerIgnite
.
Examples
if (torch_is_installed()) {
## Not run:
optimizer <- optim_ignite_rmsprop(model$parameters(), lr = 0.1)
optimizer$zero_grad()
loss_fn(model(input), target)$backward()
optimizer$step()
## End(Not run)
}
[Package torch version 0.15.1 Index]