optim_ignite_rmsprop function

LibTorch implementation of RMSprop

Proposed by G. Hinton in his course.

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 TRUE, compute the centered RMSProp, the gradient is normalized by an estimation of its variance weight_decay (float, optional): weight decay (L2 penalty) (default: 0)

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)

}