Keras Model (Functional API)

A model is a directed acyclic graph of layers.

Usage

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

Arguments

inputs

Input tensor(s) (from keras_input())

outputs

Output tensors (from calling layers with inputs)

...

Any additional arguments

Value

A Model instance.

Examples

library(keras3)

# input tensor
inputs <- keras_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')
)

See also

Other model functions:
get_config()
get_layer()
keras_model_sequential()
pop_layer()
summary.keras.src.models.model.Model()

Other model creation:
keras_input()
keras_model_sequential()