save_model().Loads a model saved via save_model().
load_model(model, custom_objects = NULL, compile = TRUE, safe_mode = TRUE)A Keras model instance. If the original model was compiled,
and the argument compile = TRUE is set, then the returned model
will be compiled. Otherwise, the model will be left uncompiled.
string, path to the saved model file,
or a raw vector, as returned by save_model(filepath = NULL)
Optional named list mapping names to custom classes or functions to be considered during deserialization.
Boolean, whether to compile the model after loading.
Boolean, whether to disallow unsafe lambda deserialization.
When safe_mode=FALSE, loading an object has the potential to
trigger arbitrary code execution. This argument is only
applicable to the Keras v3 model format. Defaults to TRUE.
model <- keras_model_sequential(input_shape = c(3)) |>
layer_dense(5) |>
layer_activation_softmax()model |> save_model("model.keras")
loaded_model <- load_model("model.keras")
x <- random_uniform(c(10, 3))
stopifnot(all.equal(
model |> predict(x),
loaded_model |> predict(x)
))
Note that the model variables may have different name values
(var$name property, e.g. "dense_1/kernel:0") after being reloaded.
It is recommended that you use layer attributes to
access specific variables, e.g. model |> get_layer("dense_1") |> _$kernel.
Other saving and loading functions:
export_savedmodel.keras.src.models.model.Model()
layer_tfsm()
load_model_weights()
register_keras_serializable()
save_model()
save_model_config()
save_model_weights()
with_custom_object_scope()