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, custom_objects = NULL)
get_config()
returns an object with the configuration,
from_config()
returns a re-instantiation of the object.
Layer or model object
Object with layer or model configuration
list of custom objects needed to instantiate the layer,
e.g., custom layers defined by new_layer_class()
or similar.
Other model functions:
compile.keras.engine.training.Model()
,
evaluate.keras.engine.training.Model()
,
evaluate_generator()
,
fit.keras.engine.training.Model()
,
fit_generator()
,
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()