Simple Keras Model with l1_l2 regularization

tf_keras_sequential_l1_l2.py

import tensorflow as tf
from tensorflow import keras

model = keras.models.Sequential([
  keras.layers.Dense(4, activation=tf.nn.relu, input_shape=(4,), kernel_regularizer=keras.regularizers.l1_l2(l1=0.1, l2=0.01)),
  keras.layers.Dense(4, activation=tf.nn.relu, kernel_regularizer=keras.regularizers.l1_l2(l1=0.1, l2=0.01)),
  keras.layers.Dense(1, activation=tf.nn.sigmoid)
])

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])