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).
Arguments
- object
Layer or model object
- config
Object with layer or model configuration
- custom_objects
list of custom objects needed to instantiate the layer, e.g., custom layers defined by
new_layer_class()or similar.
Value
get_config() returns an object with the configuration,
from_config() returns a re-instantiation of the object.
Note
Objects returned from get_config() are not serializable via RDS. If
you want to save and restore a model across sessions, you can use
save_model_config() (for model configuration only, not weights)
or save_model() to save the model configuration and weights
to the filesystem.
See also
Other model functions: get_layer() keras_model() keras_model_sequential() pop_layer() summary.keras.src.models.model.Model()
Other layer methods: count_params() get_weights() quantize_weights() reset_state()