A model is a directed acyclic graph of layers.

keras_model(inputs, outputs = NULL, ...)

Arguments

inputs

Input layer

outputs

Output layer

...

Any additional arguments

See also

Examples

if (FALSE) { library(keras) # input layer inputs <- layer_input(shape = c(784)) # outputs compose input + dense layers predictions <- inputs %>% layer_dense(units = 64, activation = 'relu') %>% layer_dense(units = 64, activation = 'relu') %>% layer_dense(units = 10, activation = 'softmax') # create and compile model model <- keras_model(inputs = inputs, outputs = predictions) model %>% compile( optimizer = 'rmsprop', loss = 'categorical_crossentropy', metrics = c('accuracy') ) }