View source: R/model-creation.R
| keras_model | R Documentation | 
A model is a directed acyclic graph of layers.
keras_model(inputs = NULL, outputs = NULL, ...)
| inputs | Input tensor(s) (from  | 
| outputs | Output tensors (from calling layers with  | 
| ... | Any additional arguments | 
A Model instance.
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')
)
Other model functions: 
get_config() 
get_layer() 
get_state_tree() 
keras_model_sequential() 
pop_layer() 
set_state_tree() 
summary.keras.src.models.model.Model() 
Other model creation: 
keras_input() 
keras_model_sequential() 
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