R: Save and load model configuration as JSON

save_model_config {keras3}

R Documentation

Save and load model configuration as JSON

Description

Save and re-load models configurations as JSON. Note that the representation does not include the weights, only the architecture.

Usage

save_model_config(model, filepath = NULL, overwrite = FALSE)

load_model_config(filepath, custom_objects = NULL)

Arguments

`model`	Model object to save
`filepath`	path to json file with the model config.
`overwrite`	Whether we should overwrite any existing model configuration json at `filepath`, or instead ask the user via an interactive prompt.
`custom_objects`	Optional named list mapping names to custom classes or functions to be considered during deserialization.

Details

Note: save_model_config() serializes the model to JSON using serialize_keras_object(), not get_config(). serialize_keras_object() returns a superset of get_config(), with additional information needed to create the class object needed to restore the model. See example for how to extract the get_config() value from a saved model.

Value

This is called primarily for side effects. model is returned, invisibly, to enable usage with the pipe.

Example

model <- keras_model_sequential(input_shape = 10) |> layer_dense(10)
file <- tempfile("model-config-", fileext = ".json")
save_model_config(model, file)

# load a new model instance with the same architecture but different weights
model2 <- load_model_config(file)

stopifnot(exprs = {
  all.equal(get_config(model), get_config(model2))

  # To extract the `get_config()` value from a saved model config:
  all.equal(
      get_config(model),
      structure(jsonlite::read_json(file)$config,
                "__class__" = keras_model_sequential()$`__class__`)
  )
})