A regularizer that applies both L1 and L2 regularization penalties.

Inherits From: Regularizer

The L1 regularization penalty is computed as: loss = l1 * reduce_sum(abs(x))

The L2 regularization penalty is computed as loss = l2 * reduce_sum(square(x))

L1L2 may be passed to a layer as a string identifier:

dense = tf.keras.layers.Dense(3, kernel_regularizer='l1_l2')

In this case, the default values used are l1=0.01 and l2=0.01.

l1 Float; L1 regularization factor.
l2 Float; L2 regularization factor.



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Creates a regularizer from its config.

This method is the reverse of get_config, capable of instantiating the same regularizer from the config dictionary.

This method is used by Keras model_to_estimator, saving and loading models to HDF5 formats, Keras model cloning, some visualization utilities, and exporting models to and from JSON.

config A Python dictionary, typically the output of get_config.

A regularizer instance.