config_optimizer {cito} | R Documentation |
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,
...
)
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
Value
object of class cito_optim to give to dnn
Examples
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)
}
[Package cito version 1.1 Index]