Layer/Model configuration

A layer config is an object returned from get_config() that contains the configuration of a layer or model. The same layer or model can be reinstantiated later (without its trained weights) from this configuration using from_config(). The config does not include connectivity information, nor the class name (those are handled externally).

get_config(object)

from_config(config)

Arguments

object

Layer or model object

config

Object with layer or model configuration

Value

get_config() returns an object with the configuration, from_config() returns a re-instantation of hte object.

Note

Objects returned from get_config() are not serializable. Therefore, if you want to save and restore a model across sessions, you can use the model_to_json() or model_to_yaml() functions (for model configuration only, not weights) or the save_model_hdf5() function to save the model configuration and weights to a file.

See also

Other model functions: compile, evaluate.keras.engine.training.Model, evaluate_generator, fit_generator, fit, get_layer, keras_model_sequential, keras_model, multi_gpu_model, pop_layer, predict.keras.engine.training.Model, predict_generator, predict_on_batch, predict_proba, summary.keras.engine.training.Model, train_on_batch

Other layer methods: count_params, get_input_at, get_weights, reset_states