Represents a generic autoencoder network.

autoencoder(network, loss = "mean_squared_error")

Arguments

network

Layer construct of class "ruta_network" or coercible

loss

A "ruta_loss" object or a character string specifying a loss function

Value

A construct of class "ruta_autoencoder"

References

See also

Examples

# Basic autoencoder with a network of [input]-256-36-256-[input] and # no nonlinearities autoencoder(c(256, 36), loss = "binary_crossentropy")
#> Autoencoder learner #> ---------------------------------------- #> Type: basic #> #> Network structure: #> input #> dense(256 units) - linear #> dense(36 units) - linear #> dense(256 units) - linear #> dense - linear #> #> Loss: binary_crossentropy #> ----------------------------------------
# Customizing the activation functions in the same network network <- input() + dense(256, "relu") + dense(36, "tanh") + dense(256, "relu") + output("sigmoid") learner <- autoencoder( network, loss = "binary_crossentropy" )