cito (version 1.1)

config_optimizer: Creation of customized optimizer objects

Description

Helps you create custom optimizer for dnn. It is recommended to set learning rate in dnn.

Usage

config_optimizer(
  type = c("adam", "adadelta", "adagrad", "rmsprop", "rprop", "sgd"),
  verbose = FALSE,
  ...
)

Value

object of class cito_optim to give to dnn

Arguments

type

character string defining which optimizer should be used. See Details.

verbose

If TRUE, additional information about scheduler will be printed to console

...

additional arguments to be passed to optimizer. See Details.

Details

different optimizer need different variables, this function will tell you how the variables are set. For more information see the corresponding functions:

• adam: optim_adam

• adadelta: optim_adadelta

• adagrad: optim_adagrad

• rmsprop: optim_rmsprop

• rprop: optim_rprop

• sgd: optim_sgd

Examples

# \donttest{
if(torch::torch_is_installed()){
library(cito)

# create optimizer object
opt <- config_optimizer(type = "adagrad",
                        lr_decay = 1e-04,
                        weight_decay = 0.1,
                        verbose = TRUE)

# Build and train  Network
nn.fit<- dnn(Sepal.Length~., data = datasets::iris, optimizer = opt)

}
# }